{ "cells": [ { "cell_type": "code", "execution_count": 34, "id": "79413bc7", "metadata": {}, "outputs": [], "source": [ "import os\n", "from evoagentx.models import OpenAILLMConfig, OpenAILLM\n", "\n", "# Load the API key from environment\n", "OPENAI_API_KEY = \"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\"\n", "\n", "# Define LLM configuration\n", "openai_config = OpenAILLMConfig(\n", " model=\"gpt-4o-mini\", # Specify the model name\n", " openai_key=OPENAI_API_KEY, # Pass the key directly\n", " stream=True, # Enable streaming response\n", " output_response=True # Print response to stdout\n", ")\n", "\n", "# Initialize the language model\n", "llm = OpenAILLM(config=openai_config)\n", "\n", "from evoagentx.workflow import WorkFlowGenerator, WorkFlowGraph, WorkFlow\n", "from evoagentx.agents import AgentManager\n" ] }, { "cell_type": "code", "execution_count": 35, "id": "0459b141", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[32m2025-12-22 23:50:44.438\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.tools.storage_handler\u001b[0m:\u001b[36m_initialize_storage\u001b[0m:\u001b[36m133\u001b[0m - \u001b[1mLocal storage initialized with base path: .\u001b[0m\n" ] } ], "source": [ "from evoagentx.benchmark import HotPotQA\n", "from evoagentx.tools import ArxivToolkit\n", "import evoagentx.tools\n", "wiki_toolkit = evoagentx.tools.WikipediaSearchToolkit(max_summary_sentences=5)\n", "arxiv_toolkit = evoagentx.tools.ArxivToolkit()\n", "search_toolkit = evoagentx.tools.DDGSSearchToolkit( num_search_pages=5,\n", " max_content_words=300,\n", " backend=\"auto\", # Options: \"auto\", \"duckduckgo\", \"google\", \"bing\", \"brave\", \"yahoo\"\n", " region=\"us-en\" # Language and region settings\n", " )" ] }, { "cell_type": "code", "execution_count": 36, "id": "5802adf1", "metadata": {}, "outputs": [], "source": [ "import os\n", "\n", "from dotenv import load_dotenv\n", "\n", "from evoagentx.agents.agent_manager import AgentManager\n", "from evoagentx.benchmark import HotPotQA\n", "from evoagentx.core.callbacks import suppress_logger_info\n", "from evoagentx.core.logging import logger\n", "from evoagentx.evaluators import Evaluator\n", "from evoagentx.models import OpenAILLM, OpenAILLMConfig\n", "from evoagentx.optimizers import TextGradOptimizer\n", "from evoagentx.prompts import StringTemplate\n", "from evoagentx.workflow import SequentialWorkFlowGraph\n", "from dotenv import load_dotenv\n", "\n", "from evoagentx.agents.agent_manager import AgentManager\n", "from evoagentx.benchmark import MBPP\n", "from evoagentx.core.callbacks import suppress_logger_info\n", "from evoagentx.core.logging import logger\n", "from evoagentx.evaluators import Evaluator\n", "from evoagentx.models import OpenAILLM, OpenAILLMConfig\n", "from evoagentx.optimizers import QASTRUCTUREOptimizer, TextGradOptimizer\n", "from evoagentx.prompts import StringTemplate\n", "from evoagentx.workflow import SequentialWorkFlowGraph\n", "\n", "from evoagentx.models import OpenAILLMConfig, OpenAILLM\n", "from evoagentx.workflow import SEWWorkFlowGraph, QASTRUCTUREWorkFlowGraph\n", "from evoagentx.agents import AgentManager\n", "from evoagentx.benchmark import HumanEval,AFlowMBPP\n", "from evoagentx.evaluators import Evaluator \n", "from evoagentx.optimizers import SEWOptimizer, STRUCTUREOptimizer\n", "from evoagentx.optimizers.structure_optimizer import STRUCTUREWorkFlowScheme\n", "from evoagentx.core.callbacks import suppress_logger_info\n", "\n", "from evoagentx.models import OpenAILLMConfig, OpenAILLM,AzureOpenAIConfig,LiteLLMConfig,LiteLLM\n", "from evoagentx.workflow import SEWWorkFlowGraph \n", "from evoagentx.agents import AgentManager\n", "from evoagentx.benchmark import MBPPPLUS, AFlowMBPPPLUS\n", "from evoagentx.evaluators import Evaluator \n", "from evoagentx.optimizers import SEWOptimizer \n", "from evoagentx.core.callbacks import suppress_logger_info\n", "from evoagentx.benchmark import HumanEvalPLUS\n", "from evoagentx.benchmark import SciCode\n", "from copy import deepcopy\n", "\n", "api_key= \"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\"\n", "\n", "import os\n", "os.environ[\"OPENAI_API_KEY\"] = api_key\n", "OPENAI_API_KEY = os.getenv(\"OPENAI_API_KEY\")\n", "from evoagentx.benchmark import PubMedQA\n", "from copy import deepcopy\n", "\n", "import nest_asyncio\n", "nest_asyncio.apply()\n", "\n", "class PubMedQASplits(PubMedQA):\n", "\n", " def _load_data(self):\n", " # load the original test data \n", " super()._load_data()\n", " # split the data into train, dev and test\n", " import numpy as np \n", " np.random.seed(42)\n", " permutation = np.random.permutation(len(self._dev_data))\n", " full_test_data = deepcopy(self._dev_data) \n", " # randomly select 10 samples for train, 40 for dev, and 100 for test\n", " self._train_data = [full_test_data[idx] for idx in permutation[:50]]\n", " self._dev_data = [full_test_data[idx] for idx in permutation[:50]]\n", " self._test_data =self._test_data[0:500]\n", "# self._fulldata = full_test_data\n", " self._dev_data_full = full_test_data\n", "\n", "\n", "def collate_func(example: dict) -> dict:\n", " context_list = []\n", " paragraphs = example[\"context\"][\"contexts\"]\n", " context = \"\\n\".join(paragraphs)\n", " problem = \"Context: {}\\n\\nQuestion: {}\\n\\nAnswer:\".format(context, example[\"question\"])\n", " return {\"question\": problem}\n", "\n", "hotpotqa_graph_data = {\n", " \"goal\": \"Answer user questions accurately and concisely by decomposing the problem into analysis and generate.\",\n", " \"tasks\": [\n", " {\n", " \"name\": \"generate_answer\",\n", " \"description\": \"Draft an answer using the retrieved context.\",\n", " \"inputs\": [ {\"name\": \"question\", \"type\": \"str\", \"required\": True,\n", " \"description\": \"The original question from the user.\"},\n", " ],\n", " \"outputs\": [\n", " {\"name\": \"draft_answer\", \"type\": \"str\", \"required\": True,\n", " \"description\": \"A concise, direct answer to the question.\"}\n", " ],\n", " \"prompt_template\": StringTemplate(instruction=\"You can search and integrate the context to generate answers. You should provide the final answer (Yes or No) in the 'answer' field. Format your answer in xxx.\"),\n", " \"parse_mode\": \"xml\",\n", " 'tool_names': ['DDGSSearchToolkit', 'WikipediaSearchToolkit','ArxivToolkit'],\n", "# 'tools': [wiki_toolkit,search_toolkit]\n", " },\n", "\n", " {\n", " \"name\": \"critique_answer\",\n", " \"description\": \"Check the drafted answer for correctness, faithfulness to the context, and alignment with the question.\",\n", " \"inputs\": [\n", " {\"name\": \"question\", \"type\": \"str\", \"required\": True,\n", " \"description\": \"The original question from the user.\"},\n", " {\"name\": \"draft_answer\", \"type\": \"str\", \"required\": True,\n", " \"description\": \"The answer proposed by generate_answer.\"}\n", " ],\n", " \"outputs\": [\n", " {\"name\": \"is_valid\", \"type\": \"bool\", \"required\": True,\n", " \"description\": \"Whether the draft answer is correct and well-supported by the context.\"},\n", " {\"name\": \"issues\", \"type\": \"list[str]\", \"required\": False,\n", " \"description\": \"List of detected issues (e.g., hallucination, missing details, ambiguity).\"},\n", " {\"name\": \"suggested_improvements\", \"type\": \"str\", \"required\": False,\n", " \"description\": \"Textual suggestions on how to improve the answer, if needed.\"}\n", " ],\n", " \"prompt_template\": StringTemplate(\n", " instruction=(\n", " \"You are an Answer Critique Agent.\\n\"\n", " \"Compare the draft answer to the context and question.\\n\"\n", " \"1) Mark if the answer is fully supported and correctly addresses the question.\\n\"\n", " \"2) If not valid, list concrete issues and suggest how to fix them.\\n\"\n", " \"Return XML with , (items as ), and .\"\n", " )\n", " ),\n", " \"parse_mode\": \"xml\"\n", " },\n", "\n", " {\n", " \"name\": \"refine_answer\",\n", " \"description\": \"Refine or rewrite the answer based on critique, preserving factual alignment with the context.\",\n", " \"inputs\": [\n", " {\"name\": \"question\", \"type\": \"str\", \"required\": True,\n", " \"description\": \"The original question from the user.\"},\n", " {\"name\": \"draft_answer\", \"type\": \"str\", \"required\": True,\n", " \"description\": \"The initial answer to be refined.\"},\n", " {\"name\": \"is_valid\", \"type\": \"bool\", \"required\": True,\n", " \"description\": \"Validation flag from critique_answer.\"},\n", " {\"name\": \"suggested_improvements\", \"type\": \"str\", \"required\": False,\n", " \"description\": \"Guidance from the critique_answer step on how to improve the answer.\"}\n", " ],\n", " \"outputs\": [\n", " {\"name\": \"answer\", \"type\": \"str\", \"required\": True,\n", " \"description\": \"Final, concise, and validated answer ready to return to the user.\"}\n", " ],\n", " \"prompt_template\": StringTemplate(\n", " instruction=(\n", " \"You are an Answer Refinement Agent.\\n\"\n", " \"If is_valid is true, you may lightly polish the draft answer for clarity and brevity.\\n\"\n", " \"If is_valid is false, use the suggested improvements and context to rewrite the answer so that it is correct, \"\n", " \"fully supported, and concise (1–3 sentences).\\n\"\n", " \"You should provide the final answer (Yes or No) in the 'answer' field. Format your answer in xxx.\"\n", " )\n", " ),\n", " \"parse_mode\": \"xml\"\n", " }\n", " ]\n", "}\n" ] }, { "cell_type": "code", "execution_count": null, "id": "24179599", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 37, "id": "a962ae1e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[32m2025-12-22 23:50:45.695\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.actions.customize_action\u001b[0m:\u001b[36madd_tools\u001b[0m:\u001b[36m195\u001b[0m - \u001b[1mAdded toolkit 'DDGSSearchToolkit' with 1 valid tools in GenerateansweragentActionV3: ['ddgs_search'].\u001b[0m\n", "\u001b[32m2025-12-22 23:50:45.695\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.actions.customize_action\u001b[0m:\u001b[36madd_tools\u001b[0m:\u001b[36m195\u001b[0m - \u001b[1mAdded toolkit 'WikipediaSearchToolkit' with 1 valid tools in GenerateansweragentActionV3: ['wikipedia_search'].\u001b[0m\n", "\u001b[32m2025-12-22 23:50:45.695\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.actions.customize_action\u001b[0m:\u001b[36madd_tools\u001b[0m:\u001b[36m195\u001b[0m - \u001b[1mAdded toolkit 'ArxivToolkit' with 2 valid tools in GenerateansweragentActionV3: ['arxiv_search', 'arxiv_download'].\u001b[0m\n", "\u001b[32m2025-12-22 23:50:45.728\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.benchmark.pubmedqa\u001b[0m:\u001b[36m_load_data_from_file\u001b[0m:\u001b[36m51\u001b[0m - \u001b[1mloading HotPotQA data from /gpfs/radev/pi/ying_rex/tl688/selfevolve/EvoAgentX/examples/pubmedqa/pubmedqa_train.json ...\u001b[0m\n", "\u001b[32m2025-12-22 23:50:47.821\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.benchmark.pubmedqa\u001b[0m:\u001b[36m_load_data_from_file\u001b[0m:\u001b[36m51\u001b[0m - \u001b[1mloading HotPotQA data from /gpfs/radev/pi/ying_rex/tl688/selfevolve/EvoAgentX/examples/pubmedqa/pubmedqa_train.json ...\u001b[0m\n", "\u001b[32m2025-12-22 23:50:50.284\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.benchmark.pubmedqa\u001b[0m:\u001b[36m_load_data_from_file\u001b[0m:\u001b[36m51\u001b[0m - \u001b[1mloading HotPotQA data from /gpfs/radev/pi/ying_rex/tl688/selfevolve/EvoAgentX/examples/pubmedqa/pubmedqa_label.json ...\u001b[0m\n" ] } ], "source": [ "llm_config = OpenAILLMConfig(model=\"gpt-4o-mini-2024-07-18\", openai_key=OPENAI_API_KEY, top_p=0.85, temperature=0.2, frequency_penalty=0.0, presence_penalty=0.0)\n", "llm = OpenAILLM(config=llm_config)\n", "\n", "# obtain SEW workflow \n", "# sew_graph = SEWWorkFlowGraph.from_dict(hotpotqa_graph_data)\n", "# agent_manager = AgentManager()\n", "# agent_manager.add_agents_from_workflow(sew_graph, executor_llm.config)\n", "# obtain SEW workflow \n", "# sew_graph = QASTRUCTUREWorkFlowGraph.from_dict(hotpotqa_graph_data)\n", "sew_graph = SequentialWorkFlowGraph.from_dict(hotpotqa_graph_data)\n", "agent_manager = AgentManager(tools=[search_toolkit,wiki_toolkit,arxiv_toolkit])\n", "agent_manager.add_agents_from_workflow(sew_graph, llm_config=llm_config)\n", "benchmark = PubMedQASplits()\n", "# obtain Evaluator\n", "evaluator = Evaluator(\n", " llm=llm, \n", " agent_manager=agent_manager, \n", " collate_func=collate_func, \n", " num_workers=20, \n", " verbose=True\n", ")" ] }, { "cell_type": "code", "execution_count": 38, "id": "3a647b61", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'DDGSSearchToolkit'" ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" } ], "source": [ "search_toolkit.name" ] }, { "cell_type": "code", "execution_count": 39, "id": "656b3c46", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[WorkFlowEdge(class_name='WorkFlowEdge', source='generate_answer', target='critique_answer', priority=0),\n", " WorkFlowEdge(class_name='WorkFlowEdge', source='generate_answer', target='refine_answer', priority=0),\n", " WorkFlowEdge(class_name='WorkFlowEdge', source='critique_answer', target='refine_answer', priority=0)]" ] }, "execution_count": 39, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sew_graph.edges" ] }, { "cell_type": "code", "execution_count": 40, "id": "beb24ef7", "metadata": {}, "outputs": [], "source": [ "# len(benchmark._fulldata)" ] }, { "cell_type": "code", "execution_count": 41, "id": "227fc475", "metadata": { "scrolled": true }, "outputs": [], "source": [ "evaluator = Evaluator(llm=llm, agent_manager=agent_manager, collate_func=collate_func, num_workers=10, verbose=True)\n", "# obtain SEWOptimizer after having more roles\n", "optimizer = QASTRUCTUREOptimizer(\n", " graph=sew_graph, \n", " evaluator=evaluator, \n", " llm=llm, \n", " max_steps=10,\n", " eval_rounds=1, \n", " repr_scheme=\"python\", \n", " optimize_mode=\"all\", \n", " order=\"zero-order\",\n", " max_rounds=1\n", ")\n", "optimizer.calltime = 1\n", "optimizer.collate_func = collate_func\n", "\n", "benchmark.error_list = {}\n", "benchmark.timeout = 900\n", "benchmark.dataname = 'hotpotqa'" ] }, { "cell_type": "code", "execution_count": 42, "id": "019bb9e5", "metadata": { "scrolled": true }, "outputs": [], "source": [ "# optimizer.evaluator.dataname = 'hotpotqa'\n", "# with suppress_logger_info():\n", "# metrics = optimizer.evaluate(dataset=benchmark, eval_mode=\"test\")\n", "# print(\"Evaluation metrics: \", metrics)" ] }, { "cell_type": "code", "execution_count": 43, "id": "3984171e", "metadata": {}, "outputs": [], "source": [ "# metrics" ] }, { "cell_type": "code", "execution_count": null, "id": "458eb432", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[32m2025-12-22 23:50:54.598\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.optimizers.qastructure_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m971\u001b[0m - \u001b[1mOptimizing the SequentialWorkFlowGraph workflow with python representation.\u001b[0m\n", "\u001b[32m2025-12-22 23:50:54.599\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.optimizers.qastructure_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m975\u001b[0m - \u001b[1mRun initial evaluation on the original workflow ...\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Evaluating workflow: 2%|▏ | 1/50 [00:10<08:55, 10.93s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "_____________________ Start Function Calling _____________________\n", "Executing function calling: ddgs_search with parameters: {'query': 'heart-type fatty acid binding protein early marker myocardial damage radiofrequency catheter ablation', 'num_search_pages': 5}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 4%|▍ | 2/50 [00:22<09:06, 11.38s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "_____________________ Start Function Calling _____________________\n", "Executing function calling: ddgs_search with parameters: {'query': 'Does nitric oxide modulate spreading depolarization threshold in the human and rodent cortex?', 'num_search_pages': 5}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 6%|▌ | 3/50 [00:38<10:40, 13.63s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 8%|▊ | 4/50 [00:50<09:47, 12.77s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "_____________________ Start Function Calling _____________________\n", "Executing function calling: ddgs_search with parameters: {'query': 'new FIGO staging system vulvar cancer prognosis', 'num_search_pages': 5}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 10%|█ | 5/50 [01:03<09:38, 12.86s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 12%|█▏ | 6/50 [01:08<07:29, 10.21s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 14%|█▍ | 7/50 [01:14<06:20, 8.85s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "_____________________ Start Function Calling _____________________\n", "Executing function calling: ddgs_search with parameters: {'query': 'one-day hypothermic preservation isolated hearts halothane calcium cardiac function', 'num_search_pages': 5}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 16%|█▌ | 8/50 [01:28<07:14, 10.34s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 18%|█▊ | 9/50 [01:32<05:54, 8.65s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 20%|██ | 10/50 [01:40<05:32, 8.32s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "_____________________ Start Function Calling _____________________\n", "Executing function calling: ddgs_search with parameters: {'query': 'anguilla japonica lectin 1 adenovirus vector apoptotic cancer cell death PRMT5', 'num_search_pages': 5}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 22%|██▏ | 11/50 [02:02<08:12, 12.62s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "_____________________ Start Function Calling _____________________\n", "Executing function calling: ddgs_search with parameters: {'query': 'Research of 10-23 DNAZyme inhibit the expression of eIF4E genes', 'num_search_pages': 5}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 24%|██▍ | 12/50 [02:15<08:00, 12.64s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "_____________________ Start Function Calling _____________________\n", "Executing function calling: ddgs_search with parameters: {'query': 'correlation of MAP kinases with COX-2 induction MKN45 HT29 cells', 'num_search_pages': 5}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 26%|██▌ | 13/50 [02:40<10:02, 16.27s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "_____________________ Start Function Calling _____________________\n", "Executing function calling: ddgs_search with parameters: {'query': 'ascorbic acid content tomato fruits gene expression pectin degradation', 'num_search_pages': 5}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 28%|██▊ | 14/50 [02:55<09:32, 15.91s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "_____________________ Start Function Calling _____________________\n", "Executing function calling: ddgs_search with parameters: {'query': 'stiffness index osteoporotic fractures ultrasound velocity attenuation', 'num_search_pages': 5}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 30%|███ | 15/50 [03:09<09:03, 15.52s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "_____________________ Start Function Calling _____________________\n", "Executing function calling: ddgs_search with parameters: {'query': 'continuous epidural pumping saline postdural puncture headache prevention treatment', 'num_search_pages': 5}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 32%|███▏ | 16/50 [03:23<08:31, 15.05s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "_____________________ Start Function Calling _____________________\n", "Executing function calling: ddgs_search with parameters: {'query': 'negative carotid plaque area test superiority noninvasive atherosclerosis studies coronary artery disease', 'num_search_pages': 5}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 34%|███▍ | 17/50 [03:36<07:54, 14.37s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 36%|███▌ | 18/50 [03:44<06:35, 12.35s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "_____________________ Start Function Calling _____________________\n", "Executing function calling: ddgs_search with parameters: {'query': 'ERAP1 gene expression nonsynonymous polymorphisms spondyloarthritis', 'num_search_pages': 5}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 38%|███▊ | 19/50 [03:58<06:37, 12.82s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "_____________________ Start Function Calling _____________________\n", "Executing function calling: ddgs_search with parameters: {'query': 'daily temperature fluctuations influence developmental rate morphology early larval stage frog', 'num_search_pages': 5}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 40%|████ | 20/50 [04:10<06:21, 12.70s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "_____________________ Start Function Calling _____________________\n", "Executing function calling: ddgs_search with parameters: {'query': 'hypoxia challenge test accuracy in predicting hypoxia in ex-preterm neonates', 'num_search_pages': 5}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 42%|████▏ | 21/50 [04:24<06:21, 13.17s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 44%|████▍ | 22/50 [04:34<05:39, 12.13s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "_____________________ Start Function Calling _____________________\n", "Executing function calling: ddgs_search with parameters: {'query': 'tauroursodeoxycholic acid anticholestatic effects cPKC alpha PKA mechanism rat liver', 'num_search_pages': 5}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 46%|████▌ | 23/50 [05:27<10:55, 24.27s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "_____________________ Start Function Calling _____________________\n", "Executing function calling: ddgs_search with parameters: {'query': 'safety and effectiveness of irrigated radiofrequency ablation for chronic atrial fibrillation', 'num_search_pages': 5}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 48%|████▊ | 24/50 [05:43<09:31, 21.98s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "_____________________ Start Function Calling _____________________\n", "Executing function calling: ddgs_search with parameters: {'query': 'rapid early monoclonal protein reduction bortezomib pegylated liposomal doxorubicin relapsed refractory myeloma time to progression', 'num_search_pages': 5}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 50%|█████ | 25/50 [05:58<08:15, 19.83s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 52%|█████▏ | 26/50 [06:06<06:28, 16.20s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 54%|█████▍ | 27/50 [06:14<05:13, 13.64s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 56%|█████▌ | 28/50 [06:26<04:49, 13.14s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "_____________________ Start Function Calling _____________________\n", "Executing function calling: ddgs_search with parameters: {'query': 'oculomotor behavior hemianopic chronic stroke patients driving simulator vision training', 'num_search_pages': 5}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 58%|█████▊ | 29/50 [06:47<05:26, 15.55s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "_____________________ Start Function Calling _____________________\n", "Executing function calling: ddgs_search with parameters: {'query': 'resveratrol curcumin experimental periodontitis rats', 'num_search_pages': 5}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 60%|██████ | 30/50 [06:59<04:51, 14.55s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "_____________________ Start Function Calling _____________________\n", "Executing function calling: ddgs_search with parameters: {'query': 'brain CT perfusion severe traumatic brain injury additional information', 'num_search_pages': 5}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 62%|██████▏ | 31/50 [07:11<04:23, 13.88s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 64%|██████▍ | 32/50 [07:20<03:44, 12.45s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 66%|██████▌ | 33/50 [07:29<03:11, 11.29s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 68%|██████▊ | 34/50 [07:35<02:36, 9.75s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 70%|███████ | 35/50 [07:44<02:24, 9.61s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "_____________________ Start Function Calling _____________________\n", "Executing function calling: ddgs_search with parameters: {'query': 'caspase-1 activation and interleukin-1β release uncoupled events in monocytes', 'num_search_pages': 5}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 72%|███████▏ | 36/50 [07:59<02:34, 11.05s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] } ], "source": [ "\n", "optimizer.evaluator.dataname = 'hotpotqa'\n", "optimizer.optimize(dataset=benchmark,provided_scorer=True)\n", "\n", "# evaluate the optimized SEW workflow\n", "\n", "optimizer.evaluator.dataname = 'hotpotqa'\n", "with suppress_logger_info():\n", " metrics = optimizer.evaluate(dataset=benchmark, eval_mode=\"test\")\n", "print(\"Evaluation metrics: \", metrics)" ] }, { "cell_type": "code", "execution_count": null, "id": "f3aef633", "metadata": { "scrolled": true }, "outputs": [], "source": [ "# optimizer.save(\"debug/optimized_ourmethod_gpt4omini_optzall.json\")\n", "optimizer.save(\"debug/optimized_ourmethod_gpt4omini_optzall_generate_critic_refine.json\")" ] }, { "cell_type": "code", "execution_count": 13, "id": "89ae2e8f", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'f1': 0.0, 'em': 0.0, 'acc': 0.422}" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "metrics" ] }, { "cell_type": "code", "execution_count": null, "id": "817a4d52", "metadata": {}, "outputs": [], "source": [ "metrics" ] }, { "cell_type": "code", "execution_count": null, "id": "1cd1b376", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 1, "id": "f828d530", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/gpfs/radev/home/tl688/.conda/envs/evoagentx/lib/python3.11/site-packages/PyPDF2/__init__.py:21: DeprecationWarning: PyPDF2 is deprecated. Please move to the pypdf library instead.\n", " warnings.warn(\n" ] } ], "source": [ "import os\n", "from evoagentx.models import OpenAILLMConfig, OpenAILLM\n", "\n", "# Load the API key from environment\n", "OPENAI_API_KEY = api_key = \"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\"\n", "# Define LLM configuration\n", "openai_config = OpenAILLMConfig(\n", " model=\"gpt-4o-mini\", # Specify the model name\n", " openai_key=OPENAI_API_KEY, # Pass the key directly\n", " stream=True, # Enable streaming response\n", " output_response=True # Print response to stdout\n", ")\n", "\n", "# Initialize the language model\n", "llm = OpenAILLM(config=openai_config)\n", "\n", "from evoagentx.workflow import WorkFlowGenerator, WorkFlowGraph, WorkFlow\n", "from evoagentx.agents import AgentManager\n" ] }, { "cell_type": "code", "execution_count": 2, "id": "29b73f39", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "\u001b[32m2026-01-05 21:46:08.629\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.tools.storage_handler\u001b[0m:\u001b[36m_initialize_storage\u001b[0m:\u001b[36m133\u001b[0m - \u001b[1mLocal storage initialized with base path: .\u001b[0m\n" ] } ], "source": [ "from evoagentx.benchmark import HotPotQA\n", "from evoagentx.tools import ArxivToolkit\n", "import evoagentx.tools\n", "wiki_toolkit = evoagentx.tools.WikipediaSearchToolkit(max_summary_sentences=5)\n", "arxiv_toolkit = evoagentx.tools.ArxivToolkit()\n", "search_toolkit = evoagentx.tools.DDGSSearchToolkit( num_search_pages=5,\n", " max_content_words=300,\n", " backend=\"auto\", # Options: \"auto\", \"duckduckgo\", \"google\", \"bing\", \"brave\", \"yahoo\"\n", " region=\"us-en\" # Language and region settings\n", " )" ] }, { "cell_type": "code", "execution_count": 3, "id": "d265a7a9", "metadata": {}, "outputs": [], "source": [ "import os\n", "\n", "from dotenv import load_dotenv\n", "\n", "from evoagentx.agents.agent_manager import AgentManager\n", "from evoagentx.benchmark import HotPotQA\n", "from evoagentx.core.callbacks import suppress_logger_info\n", "from evoagentx.core.logging import logger\n", "from evoagentx.evaluators import Evaluator\n", "from evoagentx.models import OpenAILLM, OpenAILLMConfig\n", "from evoagentx.optimizers import TextGradOptimizer\n", "from evoagentx.prompts import StringTemplate\n", "from evoagentx.workflow import SequentialWorkFlowGraph\n", "from dotenv import load_dotenv\n", "\n", "from evoagentx.agents.agent_manager import AgentManager\n", "from evoagentx.benchmark import MBPP\n", "from evoagentx.core.callbacks import suppress_logger_info\n", "from evoagentx.core.logging import logger\n", "from evoagentx.evaluators import Evaluator\n", "from evoagentx.models import OpenAILLM, OpenAILLMConfig\n", "from evoagentx.optimizers import QASTRUCTUREOptimizer, TextGradOptimizer\n", "from evoagentx.prompts import StringTemplate\n", "from evoagentx.workflow import SequentialWorkFlowGraph\n", "\n", "from evoagentx.models import OpenAILLMConfig, OpenAILLM\n", "from evoagentx.workflow import SEWWorkFlowGraph, QASTRUCTUREWorkFlowGraph\n", "from evoagentx.agents import AgentManager\n", "from evoagentx.benchmark import HumanEval,AFlowMBPP\n", "from evoagentx.evaluators import Evaluator \n", "from evoagentx.optimizers import SEWOptimizer, STRUCTUREOptimizer\n", "from evoagentx.optimizers.structure_optimizer import STRUCTUREWorkFlowScheme\n", "from evoagentx.core.callbacks import suppress_logger_info\n", "\n", "from evoagentx.models import OpenAILLMConfig, OpenAILLM,AzureOpenAIConfig,LiteLLMConfig,LiteLLM\n", "from evoagentx.workflow import SEWWorkFlowGraph \n", "from evoagentx.agents import AgentManager\n", "from evoagentx.benchmark import MBPPPLUS, AFlowMBPPPLUS\n", "from evoagentx.evaluators import Evaluator \n", "from evoagentx.optimizers import SEWOptimizer \n", "from evoagentx.core.callbacks import suppress_logger_info\n", "from evoagentx.benchmark import HumanEvalPLUS\n", "from evoagentx.benchmark import SciCode\n", "from copy import deepcopy\n", "\n", "api_key= api_key = \"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\"\n", "import os\n", "os.environ[\"OPENAI_API_KEY\"] = api_key\n", "OPENAI_API_KEY = os.getenv(\"OPENAI_API_KEY\")\n", "from evoagentx.benchmark import PubMedQA\n", "from copy import deepcopy\n", "\n", "import nest_asyncio\n", "nest_asyncio.apply()\n", "\n", "class PubMedQASplits(PubMedQA):\n", "\n", " def _load_data(self):\n", " # load the original test data \n", " super()._load_data()\n", " # split the data into train, dev and test\n", " import numpy as np \n", " np.random.seed(42)\n", " permutation = np.random.permutation(len(self._dev_data))\n", " full_test_data = deepcopy(self._dev_data) \n", " # randomly select 10 samples for train, 40 for dev, and 100 for test\n", " self._train_data = [full_test_data[idx] for idx in permutation[:50]]\n", " self._dev_data = [full_test_data[idx] for idx in permutation[:50]]\n", " self._test_data =self._test_data[0:500]\n", "# self._fulldata = full_test_data\n", " self._dev_data_full = full_test_data\n", "\n", "\n", "def collate_func(example: dict) -> dict:\n", " context_list = []\n", " paragraphs = example[\"context\"][\"contexts\"]\n", " context = \"\\n\".join(paragraphs)\n", " problem = \"Context: {}\\n\\nQuestion: {}\\n\\nAnswer:\".format(context, example[\"question\"])\n", " return {\"question\": problem}\n", "\n", "hotpotqa_graph_data = {\n", " \"goal\": \"Answer user questions accurately and concisely by decomposing the problem into analysis and generate.\",\n", " \"tasks\": [\n", " {\n", " \"name\": \"generate_answer\",\n", " \"description\": \"Draft an answer using the retrieved context.\",\n", " \"inputs\": [ {\"name\": \"question\", \"type\": \"str\", \"required\": True,\n", " \"description\": \"The original question from the user.\"},\n", " ],\n", " \"outputs\": [\n", " {\"name\": \"draft_answer\", \"type\": \"str\", \"required\": True,\n", " \"description\": \"A concise, direct answer to the question.\"}\n", " ],\n", " \"prompt_template\": StringTemplate(instruction=\"You can search and integrate the context to generate answers. You should provide the final answer (Yes or No) in the 'answer' field. Format your answer in xxx.\"),\n", " \"parse_mode\": \"xml\",\n", "# 'tools': [wiki_toolkit,search_toolkit]\n", " },\n", "\n", "# {\n", "# \"name\": \"critique_answer\",\n", "# \"description\": \"Check the drafted answer for correctness, faithfulness to the context, and alignment with the question.\",\n", "# \"inputs\": [\n", "# {\"name\": \"question\", \"type\": \"str\", \"required\": True,\n", "# \"description\": \"The original question from the user.\"},\n", "# {\"name\": \"draft_answer\", \"type\": \"str\", \"required\": True,\n", "# \"description\": \"The answer proposed by generate_answer.\"}\n", "# ],\n", "# \"outputs\": [\n", "# {\"name\": \"is_valid\", \"type\": \"bool\", \"required\": True,\n", "# \"description\": \"Whether the draft answer is correct and well-supported by the context.\"},\n", "# {\"name\": \"issues\", \"type\": \"list[str]\", \"required\": False,\n", "# \"description\": \"List of detected issues (e.g., hallucination, missing details, ambiguity).\"},\n", "# {\"name\": \"suggested_improvements\", \"type\": \"str\", \"required\": False,\n", "# \"description\": \"Textual suggestions on how to improve the answer, if needed.\"}\n", "# ],\n", "# \"prompt_template\": StringTemplate(\n", "# instruction=(\n", "# \"You are an Answer Critique Agent.\\n\"\n", "# \"Compare the draft answer to the context and question.\\n\"\n", "# \"1) Mark if the answer is fully supported and correctly addresses the question.\\n\"\n", "# \"2) If not valid, list concrete issues and suggest how to fix them.\\n\"\n", "# \"Return XML with , (items as ), and .\"\n", "# )\n", "# ),\n", "# \"parse_mode\": \"xml\"\n", "# },\n", "\n", "# {\n", "# \"name\": \"refine_answer\",\n", "# \"description\": \"Refine or rewrite the answer based on critique, preserving factual alignment with the context.\",\n", "# \"inputs\": [\n", "# {\"name\": \"question\", \"type\": \"str\", \"required\": True,\n", "# \"description\": \"The original question from the user.\"},\n", "# {\"name\": \"draft_answer\", \"type\": \"str\", \"required\": True,\n", "# \"description\": \"The initial answer to be refined.\"},\n", "# {\"name\": \"is_valid\", \"type\": \"bool\", \"required\": True,\n", "# \"description\": \"Validation flag from critique_answer.\"},\n", "# {\"name\": \"suggested_improvements\", \"type\": \"str\", \"required\": False,\n", "# \"description\": \"Guidance from the critique_answer step on how to improve the answer.\"}\n", "# ],\n", "# \"outputs\": [\n", "# {\"name\": \"answer\", \"type\": \"str\", \"required\": True,\n", "# \"description\": \"Final, concise, and validated answer ready to return to the user.\"}\n", "# ],\n", "# \"prompt_template\": StringTemplate(\n", "# instruction=(\n", "# \"You are an Answer Refinement Agent.\\n\"\n", "# \"If is_valid is true, you may lightly polish the draft answer for clarity and brevity.\\n\"\n", "# \"If is_valid is false, use the suggested improvements and context to rewrite the answer so that it is correct, \"\n", "# \"fully supported, and concise (1–3 sentences).\\n\"\n", "# \"You should provide the final answer (Yes or No) in the 'answer' field. Format your answer in xxx.\"\n", "# )\n", "# ),\n", "# \"parse_mode\": \"xml\"\n", "# }\n", " ]\n", "}\n", "\n", "\n", "hotpotqa_graph_data = {\n", " \"goal\": \"Answer user questions accurately and concisely by decomposing the problem into analysis and generate.\",\n", " \"tasks\": [\n", " {\n", " \"name\": \"generate_answer\",\n", " \"description\": \"Draft an answer using the retrieved context.\",\n", " \"inputs\": [ {\"name\": \"question\", \"type\": \"str\", \"required\": True,\n", " \"description\": \"The original question from the user.\"},\n", " ],\n", " \"outputs\": [\n", " {\"name\": \"draft_answer\", \"type\": \"str\", \"required\": True,\n", " \"description\": \"A concise, direct answer to the question.\"}\n", " ],\n", " \"prompt_template\": StringTemplate(instruction=\"You can think to generate answers. You should provide the final answer (either Yes or No) in the 'answer' field. Format your answer in xxx.\"),\n", " \"parse_mode\": \"xml\",\n", "# 'tools': [wiki_toolkit,search_toolkit]\n", " }\n", " ]\n", "}\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "id": "acad4be3", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 4, "id": "7444b9e3", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "\u001b[32m2026-01-05 21:46:10.133\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.benchmark.pubmedqa\u001b[0m:\u001b[36m_load_data_from_file\u001b[0m:\u001b[36m51\u001b[0m - \u001b[1mloading HotPotQA data from /gpfs/radev/pi/ying_rex/tl688/selfevolve/EvoAgentX/examples/pubmedqa/pubmedqa_train.json ...\u001b[0m\n", "\u001b[32m2026-01-05 21:46:12.973\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.benchmark.pubmedqa\u001b[0m:\u001b[36m_load_data_from_file\u001b[0m:\u001b[36m51\u001b[0m - \u001b[1mloading HotPotQA data from /gpfs/radev/pi/ying_rex/tl688/selfevolve/EvoAgentX/examples/pubmedqa/pubmedqa_train.json ...\u001b[0m\n", "\u001b[32m2026-01-05 21:46:15.614\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.benchmark.pubmedqa\u001b[0m:\u001b[36m_load_data_from_file\u001b[0m:\u001b[36m51\u001b[0m - \u001b[1mloading HotPotQA data from /gpfs/radev/pi/ying_rex/tl688/selfevolve/EvoAgentX/examples/pubmedqa/pubmedqa_label.json ...\u001b[0m\n" ] } ], "source": [ "# llm_config = OpenAILLMConfig(model=\"gpt-4o-mini-2024-07-18\", openai_key=OPENAI_API_KEY, top_p=0.85, temperature=0.2, frequency_penalty=0.0, presence_penalty=0.0)\n", "# llm = OpenAILLM(config=llm_config)\n", "\n", "# llm_config = OpenAILLMConfig(model=\"gpt-4o-mini-2024-07-18\", openai_key=OPENAI_API_KEY, top_p=0.85, temperature=0.2, frequency_penalty=0.0, presence_penalty=0.0)\n", "# llm = OpenAILLM(config=llm_config)\n", "os.environ[\"AZURE_OPENAI_DEPLOYMENT_NAME\"] = \"gpt-4o-mini\"\n", "os.environ[\"AZURE_OPENAI_ENDPOINT\"] = \"https://tianyuliu-hua-raredisea-resource.cognitiveservices.azure.com/\"\n", "os.environ[\"AZURE_OPENAI_KEY\"] = \"2pa9h2ZIN1lQepFWwYADlXIKIansa9KPhxMoumeGbRQ08f2uDTXiJQQJ99BKACHYHv6XJ3w3AAAAACOGsQIt\"\n", "os.environ[\"AZURE_OPENAI_API_VERSION\"] = \"2025-01-01-preview\"\n", "llm_config = LiteLLMConfig(model=\"azure/\" + os.getenv(\"AZURE_OPENAI_DEPLOYMENT_NAME\"), # Azure model format\n", " azure_endpoint=os.getenv(\"AZURE_OPENAI_ENDPOINT\"),\n", " azure_key=os.getenv(\"AZURE_OPENAI_KEY\"),\n", " api_version=os.getenv(\"AZURE_OPENAI_API_VERSION\", \"2024-12-01-preview\"), top_p=0.85, temperature=0.2, frequency_penalty=0.0, presence_penalty=0.0)\n", "\n", "executor_llm = LiteLLM(config=llm_config)\n", "optimizer_llm = LiteLLM(config=llm_config)\n", "llm = executor_llm\n", "\n", "# obtain SEW workflow \n", "# sew_graph = SEWWorkFlowGraph.from_dict(hotpotqa_graph_data)\n", "# agent_manager = AgentManager()\n", "# agent_manager.add_agents_from_workflow(sew_graph, executor_llm.config)\n", "# obtain SEW workflow \n", "# sew_graph = QASTRUCTUREWorkFlowGraph.from_dict(hotpotqa_graph_data)\n", "sew_graph = SequentialWorkFlowGraph.from_dict(hotpotqa_graph_data)\n", "agent_manager = AgentManager(tools=[search_toolkit,wiki_toolkit,arxiv_toolkit])\n", "agent_manager.add_agents_from_workflow(sew_graph, llm_config=llm_config)\n", "benchmark = PubMedQASplits()\n", "# obtain Evaluator\n", "evaluator = Evaluator(\n", " llm=llm, \n", " agent_manager=agent_manager, \n", " collate_func=collate_func, \n", " num_workers=20, \n", " verbose=True\n", ")" ] }, { "cell_type": "code", "execution_count": 5, "id": "8e808452", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'DDGSSearchToolkit'" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "search_toolkit.name" ] }, { "cell_type": "code", "execution_count": 6, "id": "63c35641", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sew_graph.edges" ] }, { "cell_type": "code", "execution_count": 24, "id": "31b0e6ba", "metadata": {}, "outputs": [], "source": [ "# len(benchmark._fulldata)" ] }, { "cell_type": "code", "execution_count": 25, "id": "1b6b8f5a", "metadata": { "scrolled": true }, "outputs": [], "source": [ "evaluator = Evaluator(llm=llm, agent_manager=agent_manager, collate_func=collate_func, num_workers=10, verbose=True)\n", "# obtain SEWOptimizer after having more roles\n", "optimizer = QASTRUCTUREOptimizer(\n", " graph=sew_graph, \n", " evaluator=evaluator, \n", " llm=llm, \n", " max_steps=5,\n", " eval_rounds=1, \n", " repr_scheme=\"python\", \n", " optimize_mode=\"all\", \n", " order=\"zero-order\",\n", " max_rounds=2\n", ")\n", "optimizer.calltime = 3\n", "optimizer.collate_func = collate_func\n", "\n", "benchmark.error_list = {}\n", "benchmark.timeout = 900\n", "benchmark.dataname = 'hotpotqa'" ] }, { "cell_type": "code", "execution_count": 26, "id": "abd9e896", "metadata": { "scrolled": true }, "outputs": [], "source": [ "# optimizer.evaluator.dataname = 'hotpotqa'\n", "# with suppress_logger_info():\n", "# metrics = optimizer.evaluate(dataset=benchmark, eval_mode=\"test\")\n", "# print(\"Evaluation metrics: \", metrics)" ] }, { "cell_type": "code", "execution_count": 27, "id": "ac65ca8b", "metadata": {}, "outputs": [], "source": [ "# metrics" ] }, { "cell_type": "code", "execution_count": 28, "id": "fed162e4", "metadata": {}, "outputs": [], "source": [ "# benchmark._test_data[0]" ] }, { "cell_type": "code", "execution_count": 29, "id": "f91ec33b", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[32m2026-01-06 08:37:33.148\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.optimizers.qastructure_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m1016\u001b[0m - \u001b[1mOptimizing the SequentialWorkFlowGraph workflow with python representation.\u001b[0m\n", "\u001b[32m2026-01-06 08:37:33.149\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.optimizers.qastructure_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m1020\u001b[0m - \u001b[1mRun initial evaluation on the original workflow ...\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Evaluating workflow: 2%|▏ | 1/50 [00:01<01:15, 1.54s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 4%|▍ | 2/50 [00:02<01:06, 1.38s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 6%|▌ | 3/50 [00:04<01:20, 1.72s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", 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\u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.191 | Total tokens: 6013040 | Current cost: $0.003 | Current tokens: 19610\u001b[0m\n", "\u001b[32m2026-01-06 08:38:50.610\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.194 | Total tokens: 6032625 | Current cost: $0.003 | Current tokens: 19585\u001b[0m\n", "\u001b[32m2026-01-06 08:38:52.651\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.198 | Total tokens: 6052234 | Current cost: $0.003 | Current tokens: 19609\u001b[0m\n", "\u001b[32m2026-01-06 08:38:53.864\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.198 | Total tokens: 6052775 | Current cost: $0.000 | Current tokens: 541\u001b[0m\n", "The detected issues across the workflows highlight several critical shortcomings: a lack of validation steps to ensure answer accuracy before final output, which risks presenting incorrect conclusions; insufficient mechanisms to identify and flag ambiguous or misleading prompts, potentially leading to misinterpretation; and a linear control flow that fails to accommodate errors or allow for multiple drafts, which could improve output quality. Additionally, execution histories reveal instances of incorrect evaluations despite logically sound answers, suggesting flaws in the evaluation criteria or scoring systems. Lastly, the absence of clear context or criteria for determining answer correctness contributes to inconsistencies in scoring and interpretation.\n", "\u001b[32m2026-01-06 08:38:54.773\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.198 | Total tokens: 6053374 | Current cost: $0.000 | Current tokens: 599\u001b[0m\n", "```python\n", "steps = [\n", " {'name': 'generate_answer', 'args': ['question'], 'outputs': ['draft_answer']},\n", " {'name': 'validate_answer', 'args': ['draft_answer'], 'outputs': ['validated_answer']},\n", " {'name': 'evaluate_answer', 'args': ['validated_answer'], 'outputs': ['evaluation_score']}\n", "]\n", "```\n", "Questions: Context: To investigate the resistance to dislodgment produced by Biodentine (Septodont) and White-MTA (Angelus) after immersion in phosphate-buffered saline (PBS) for different durations.\n", "Dentin disks 1 ± 0.1 mm thick were obtained from the middle third of the roots of 6 human maxillary canines. On the coronal surface of each dentin disk, four 0.8-mm-diameter holes were drilled. Then the slices were halved using a low-speed saw diamond disk, and the two holes in each half were filled with one of the two tested materials. Each filled half was immersed in PBS solution (pH 7.2) either for 7 days (short term) or 60 days (long term) at 37°C. The push-out test was performed after both time periods. A general linear model (GLM) for repeated measures ANOVA was used to verify the effect of the material and duration of contact with PBS on the push-out strength. The material was considered as the within-subject contrast and the contact duration as the between-subjects effect (p < 0.05).\n", "Repeated measures GLM indicated a significant impact of material and time on the push-out strength of the samples (p = 0.000 and p = 0.033, respectively). Biodentine significantly improved the push-out strength compared to MTA at both times (p = 0.000). The lack of significance in the interaction between material and time indicates that PBS immersion positively influenced the push-out values of both tested materials.\n", "\n", "Question: Does resistance of Hydraulic Calcium Silicate cement to Dislodgment in Short- and Long-term Assessment?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, the resistance of Hydraulic Calcium Silicate cement to dislodgment was assessed in both short- and long-term evaluations, showing significant differences in push-out strength between the materials tested.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Ganglion cells were thought not to occur within the mucosa of the normal colon and found only in the setting of inflammatory bowel disease and neuronal intestinal dysplasia. The aim of this study was to firmly establish the incidence of intramucosal ganglion cells in diverticular disease, normal mucosa and in a spectrum of gastrointestinal diseases.\n", "We retrospectively reviewed 50 resection specimens from cases of symptomatic diverticular disease and biopsies and/or resection specimens for several neoplastic and non-neoplastic gastrointestinal diseases (50 normal and 120 cases for a variety of gastrointestinal diseases). Normal cases were constituted by biopsies with no clinical history of large bowel disease and no pathology detected microscopically.\n", "All 50 cases of diverticular disease contained intramucosal ganglion cells, located within the muscularis mucosae (49/50 cases) as well as within the lamina propria in nine cases. Intramucosal ganglion cells occurred throughout the colorectum within the muscularis mucosae or lamina propria in normal mucosa in 11 cases and in a further 26 colorectal specimens with Crohn's disease (11/20), ulcerative colitis (11/20), adenocarcinoma (1/20), tubular adenoma (2/20), and mucosal prolapse (1/20). None of the 20 hyperplastic polyps contained intramucosal ganglion cells.\n", "\n", "Question: Are intramucosal ganglion cells common in diverticular disease?\n", "\n", "Answer:\n", "Predictions: {\"draft_answer\": \"Yes, intramucosal ganglion cells are common in diverticular disease, as all 50 cases reviewed contained them.\"}\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The chemokines and cytokines CXCL13, CXCL12, CCL19, CCL21, BAFF and APRIL are believed to play a role in the recruitment of B cells to the central nervous system (CNS) compartment during neuroinflammation. To determine which chemokines/cytokines show the strongest association with a humoral immune response in the cerebrospinal fluid (CSF), we measured their concentrations in the CSF and correlated them with immune cell subsets and antibody levels.\n", "Cytokine/chemokine concentrations were measured in CSF and serum by ELISA in patients with non-inflammatory neurological diseases (NIND, n = 20), clinically isolated syndrome (CIS, n = 30), multiple sclerosis (MS, n = 20), Lyme neuroborreliosis (LNB, n = 8) and patients with other inflammatory neurological diseases (OIND, n = 30). Albumin, IgG, IgA and IgM were measured by nephelometry. CSF immune cell subsets were determined by seven-color flow cytometry.\n", "CXCL13 was significantly elevated in the CSF of all patient groups with inflammatory diseases. BAFF levels were significantly increased in patients with LNB and OIND. CXCL12 was significantly elevated in patients with LNB. B cells and plasmablasts were significantly elevated in the CSF of all patients with inflammatory diseases. CXCL13 showed the most consistent correlation with CSF B cells, plasmablasts and intrathecal Ig synthesis.\n", "\n", "Question: Is cXCL13 the major determinant for B cell recruitment to the CSF during neuroinflammation?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, CXCL13 is the major determinant for B cell recruitment to the CSF during neuroinflammation, as it showed the most consistent correlation with CSF B cells, plasmablasts, and intrathecal Ig synthesis.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: This is a randomised controlled trial to examine whether intra-articular injection of tranexamic acid (TXA) decreases blood loss, as well as reducing leg swelling after total knee arthroplasty (TKA).\n", "We performed 100 TKA in osteoarthritis patients. At closure, a total of 2,000 mg/20 ml TXA was injected into the knee joint through a closed suction drain (TXA group). For the control group, the same volume of physiological saline was injected. The pre-operative condition of the patients, post-operative haemoglobin (Hb) levels, discharge volumes from drain, D-dimer and needs for transfusion were compared between these two groups. Furthermore, leg diameters (thigh, suprapatellar portion and calf girth) were measured pre- and post-operatively to investigate whether TXA has an influence on leg swelling after surgery.\n", "The results revealed that post-operative decrease in Hb level was significantly reduced in the TXA group. Furthermore, knee joint swelling after operation was significantly suppressed in the TXA group compared to the control group.\n", "\n", "Question: Reduces intra-articular injection of tranexamic acid only blood loss but also knee joint swelling after total knee arthroplasty?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, the intra-articular injection of tranexamic acid reduces both blood loss and knee joint swelling after total knee arthroplasty.\"\n", "Solutions: no\n", "Score: 0.0\n", "Error reason: Computation result is incorrect.Questions: Context: A technique to decrease visceral ischemic time during thoracoabdominal aneurysm (TAA) repair is reported.\n", "A 10 mm Dacron side-arm graft is attached to the aortic prosthesis and positioned immediately distal to the planned proximal thoracic aortic anastomosis. On completion of the anastomosis, a 16 to 22 Fr perfusion catheter is attached to the side-arm graft and inserted into the orifice of the celiac axis or superior mesenteric artery. The cross-clamp is then placed on the aortic graft distal to the mesenteric side-arm graft. Pulsatile arterial perfusion is thus established to the visceral circulation while intercostal anastomoses or reconstruction of celiac, superior mesenteric, and right renal arteries is performed. Visceral ischemic time and the rise in end-tidal Pco2 after reconstruction of the visceral vessels in patients with mesenteric shunting was compared with a control group matched for aneurysm extent and treated immediately before use of the mesenteric shunt technique.\n", "Between July and Oct, 1996, the technique was applied in 15 patients undergoing type I, II, or III TAA repair with a clamp and sew technique. The mean decrease in systolic arterial pressure was 12.5 +/- 8.5 mm Hg, with a concomitant rise in end-tidal Pco2 (mean, 6.9 +/- 5.8 mm Hg), after perfusion was established through the mesenteric shunt. Mean time to establishment of visceral perfusion through the shunt was 25.5 +/- 4.4 minutes; the resultant decrement in visceral ischemic time averaged 31.3 minutes (i.e., until celiac, superior mesenteric, and right renal arteries were reconstructed). Compared with controls, patients with shunts had a significantly decreased (6.9 +/- 5.8 versus 21.6 +/- 8.4 mm Hg; p = 0.0003) rise in end-tidal CO2 on completion of visceral vessel reconstruction.\n", "\n", "Question: Does mesenteric shunting decrease visceral ischemia during thoracoabdominal aneurysm repair?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Endothelial cells (ECs) play an essential role in pancreatic organogenesis. We hypothesise that effective in vitro interactions between human microvascular endothelial cells (HMECs) and human pluripotent stem cells (hPSCs) results in the generation of functional pancreatic beta cells.\n", "Embryoid bodies (EBs) derived from hPSCs were cultured alone (controls) or with ECs in collagen gels. Subsequently, cells were analysed for pancreatic beta cell markers, and then isolated and expanded. Insulin secretion in response to glucose was evaluated in vitro by static and dynamic (perifusion) assays, and in vivo by EB transplantation into immunodeficient mice.\n", "Co-cultured EBs had a higher expression of mature beta cells markers and enhanced insulin secretion in vitro, compared with controls. In mice, transplanted EBs had higher levels of human C-peptide secretion with a significant reduction in hyperglycaemia after the selective destruction of native pancreatic beta cells. In addition, there was significant in vitro upregulation of bone morphogenetic proteins 2 and 4 (BMP-2, 4) in co-cultured cells, compared with controls.\n", "\n", "Question: Do effective endothelial cell and human pluripotent stem cell interactions generate functional insulin-producing beta cells?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, effective endothelial cell and human pluripotent stem cell interactions generate functional insulin-producing beta cells.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Serotonin is believed as an important factor in brain function. The role of serotonin in cerebral psycho-patho-physiology has already been well established. However, the function of serotonin antagonist in anesthetized subjects under hyperthermia has not been studied properly.\n", "Experiments were performed in three groups of urethane-anesthetized rats, such as: (i) control group, (ii) whole body hyperthermia group and (iii) p-CPA (para-Chlorophenylalanine) pretreated hyperthermia group. Hyperthermia was produced by subjecting the rats to high ambient temperature of 38 +/- 1 degrees C (relative humidity 45-50%). Each group was divided for EEG (electroencephalogram) study and for determination of edematous swelling in the brain.\n", "Urethane anesthetized rats under hyperthermia show highly significant reduction in their survival time. The body temperature recorded during the hyperthermia was observed with significant and linear rise with marked increase in brain water content, which was analyzed just after the death of the subjects. The results of the electroencephalographic study in urethane-anesthetized rats recorded before death indicate that brain function varies in systematic manner during hyperthermia as sequential changes in EEG patterns were observed. However, a serotonin antagonist, p-CPA pretreatment increases the survival time with significant reduction in edematous swelling in brain but it does not affect the relationship between the core body temperature and the brain cortical potentials as observed in urethane anesthetized subjects exposed to whole body hyperthermia. The core body temperature in p-CPA pretreated rats show non-linear relationship with respect to the exposure time as it was observed in drug untreated subjects.\n", "\n", "Question: Does depletion of serotonin synthesis with p-CPA pretreatment alter EEG in urethane anesthetized rats under whole body hyperthermia?\n", "\n", "Answer:\n", "Predictions: No, the serotonin antagonist p-CPA pretreatment does not affect the relationship between the core body temperature and the brain cortical potentials in urethane anesthetized subjects exposed to whole body hyperthermia.\n", "Solutions: yes\n", "Score: 0.0\n", "Error reason: Computation result is incorrect.Questions: Context: Postoperative atrial fibrillation remains a significant source of morbidity after coronary artery bypass grafting. We reviewed the data on 2,569 patients to determine if the absence of cardiopulmonary bypass resulted in a lower incidence of atrial fibrillation.\n", "All patients undergoing coronary artery bypass grafting without cardiopulmonary bypass from January 1, 1997 through June 30, 2001 were evaluated for postoperative atrial fibrillation. The data of 252 patients with no cardiopulmonary bypass (group 1) were reviewed and compared with three other patient groups. Group 2 consisted of 1,470 patients using cardiopulmonary bypass during the same study period. Group 3 consisted of 841 patients with a similar number of grafts as the study group but using cardiopulmonary bypass. Group 4 consisted of historical data for 847 patients operated on using cardiopulmonary bypass collected from January 1995 through December 1996. Prophylactic beta-blockade was instituted in January 1997. Groups 1 to 3 received this treatment, but group 4 did not.\n", "Group 1 had an incidence of atrial fibrillation of 8.8%. Groups 2, 3, and 4 had incidences of atrial fibrillation of 11.6%, 9.4%, and 28.0%, respectively. When compared with group 1, the incidence of atrial fibrillation in group 4 was statistically different (p <. 0001).\n", "\n", "Question: Does off-pump coronary artery bypass grafting decrease the incidence of atrial fibrillation?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, off-pump coronary artery bypass grafting decreases the incidence of atrial fibrillation compared to on-pump procedures, as indicated by the lower incidence of 8.8% in group 1 compared to higher incidences in the other groups.\"\n", "Solutions: no\n", "Score: 0.0\n", "Error reason: Computation result is incorrect.Questions: Context: A substantial number of people living with HIV (PLWH) are co-infected with Hepatitis C Virus (HCV) but have a negative screening HCV antibody test (seronegative HCV infection, or SN-HCV).\n", "To identify a concise set of clinical variables that could be used to improve case finding for SN-HCV co-infection among PLWH.\n", "Two hundred HIV-infected participants of the CHARTER study were selected based on 7 clinical variables associated with HCV infection but were HCV seronegative. Data were analyzed using Fisher's exact tests, receiver-operating characteristic (ROC) curves, and logistic regression.\n", "Twenty-six (13%) participants had detectable HCV RNA. SN-HCV was associated with a history of IDU, elevated ALT and AST, low platelets, black ethnicity, and undetectable HIV RNA in plasma. Each of these clinical variables, except for abnormal AST, remained independently associated with SN-HCV in a multivariate logistic regression analysis. A composite risk score correctly identified SN-HCV with sensitivity up to 85% and specificity up to 88%.\n", "\n", "Question: Do clinical variables identify seronegative HCV co-infection in HIV-infected individuals?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, clinical variables can identify seronegative HCV co-infection in HIV-infected individuals.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To determine if an inverse association exits between latitude, ultraviolet B (UVB) irradiance and incidence rates of pancreatic cancer worldwide.\n", "Multiple linear regression was used to investigate the relationship and between UVB irradiance incidence rates of pancreatic cancer and while controlling for cigarette, alcohol and sugar consumption, and proportion overweight. Serum 25-hydroxyvitamin D [25(OH)D] levels were estimated, and their association with incidence rates also was analyzed.\n", "Incidence rates were higher at higher latitudes (R2 for latitude for men, 0.51; P < 0.001; R2 for latitude for women, 0.32; P < 0.001). Ultraviolet B irradiance also was independently inversely associated with incidence in men (P < 0.01) and women (P = 0.02). Alcohol (P < 0.0001) and cigarette (P < or = 0.01) consumption were positively associated with incidence in men (R2 for overall model for men, 0.76; P < 0.0001). Alcohol (P < 0.0001) and sugar (P = 0.001) consumption were positively associated with incidence rates in women (R2 for overall model for women, 0.64; P < 0.0001). Incidence rates were half as high in countries with estimated serum 25(OH)D >30 ng/mL (75 nmol/L) than in those with < or =30 ng/mL.\n", "\n", "Question: Are ultraviolet B irradiance and vitamin D status inversely associated with incidence rates of pancreatic cancer worldwide?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, ultraviolet B irradiance and vitamin D status are inversely associated with incidence rates of pancreatic cancer worldwide.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Lethal injuries can be surgically repaired under asanguineous hypothermic condition (suspended animation) with excellent outcome. However, the optimal rate for the induction of hypothermic metabolic arrest following uncontrolled lethal hemorrhage (ULH) is unknown.\n", "ULH was induced in 32 female swine (80-120 lbs) by creating an iliac artery and vein injury, followed 30 minutes later by laceration of the descending thoracic aorta. Through a left thoracotomy approach, total body hypothermic hyperkalemic metabolic arrest was induced by infusing organ preservation fluids into the aorta. Experimental groups were: normothermic controls (no cooling, NC), or hypothermia induced at a rate of 0.5 degrees C/min (slow, SC), 1 degrees C/min (medium, MC), or 2 degrees C/min (fast, FC). Vascular injuries were repaired during the 60 minutes of profound (10 degrees C) hypothermic arrest. Hyperkalemia was reversed by hypokalemic fluid exchange, and blood was infused for resuscitation during the re-warming (0.5 degrees C/ minute) period. The survivors were monitored for 6 weeks.\n", "The 6 week survival rates were 0% (NC), 37.5% (SC), 62.5% (MC), and 87.5% (FC) respectively (p < 0.05 MC&FC versus NC). All of the surviving hypothermic arrest animals were neurologically intact and displayed no long term organ dysfunction.\n", "\n", "Question: Does the rate of induction of hypothermic arrest determine the outcome in a Swine model of lethal hemorrhage?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, the rate of induction of hypothermic arrest determines the outcome in a Swine model of lethal hemorrhage, as evidenced by the varying survival rates among the different experimental groups.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Prostaglandins (PGs) produced within ovarian follicles in response to the ovulatory gonadotropin surge are essential for follicle rupture and oocyte release. Arachidonic acid, the common precursor for PG synthesis, is cleaved from membrane phospholipids via the activity of phospholipase A2 (PLA2).\n", "The purpose of this study was to determine which PLA2 form(s) is involved in PG production by primate periovulatory follicles.\n", "Gonadotropins were administered to cynomolgus monkeys to stimulate multiple follicular development; human chorionic gonadotropin (hCG) initiated periovulatory events. Granulosa cells and whole ovaries were obtained before (0 h), and 12, 24, and 36 h after hCG administration.\n", "Granulosa-lutein cells were also obtained from women undergoing infertility treatment.\n", "mRNA for cytosolic (c)PLA2 and secretory (s)PLA2V, but not sPLA2IIA, was expressed by granulosa cells. cPLA2 mRNA levels were low at 0 h, elevated by 12 h, and remained high 24-36 h after hCG administration. sPLA2V mRNA levels were low at 0 h and did not change in response to hCG. cPLA2 and sPLA2V were detected by immunocytochemistry in granulosa cells of periovulatory follicles before and at all times after hCG administration. PLA2 activity was low in lysates of granulosa cells obtained 0-24 h after hCG and was elevated in granulosa cells obtained 36 h after hCG administration. A cPLA2-selective inhibitor decreased both PLA2 activity in monkey granulosa cell lysates and PGE2 accumulation in cultures of human granulosa-lutein cells.\n", "\n", "Question: Does an ovulatory gonadotropin stimulus increase cytosolic phospholipase A2 expression and activity in granulosa cells of primate periovulatory follicles?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, an ovulatory gonadotropin stimulus increases cytosolic phospholipase A2 expression and activity in granulosa cells of primate periovulatory follicles.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: One of the main limitations of peritoneal dialysis (PD) is deterioration of functional and morphological characteristics of the peritoneum. This complication appears to be related to the low biocompatibility profile of PD fluids. Recently, induction of the heat shock protein (HSP) stress response was demonstrated in cultured human mesothelial cells exposed to PD fluid in vitro. We investigated whether expression of heat shock protein 72 (HSP-72) in peritoneal macrophages is induced upon exposure to PD fluid during continuous ambulatory PD.\n", "Peritoneal leukocytes were isolated from 4-hour dwell dialysate; peripheral blood mononuclear cells (PBMC) and peripheral blood monocytes isolated from the same patients were used as a control. In separate experiments, PBMC from healthy individuals were exposed in vitro to different PD fluids or to culture media. Expression of HSP-72 was assessed by Western immunoblotting, flow cytometry, and reverse-transcription polymerase chain reaction analysis.\n", "Macrophages and leukocytes isolated from dialysis effluent expressed significantly increased HSP-72 and mRNA levels compared to blood monocytes and PBMC of the same patients. In vitro exposure of PBMC to fresh PD fluids resulted in significantly higher expression of HSP-72 compared to those incubated in culture medium. PBMC exposed in vitro to standard lactate-buffered dialysis fluids also expressed significantly more HSP-72 compared to cells exposed to bicarbonate/lactate-buffered fluids.\n", "\n", "Question: Is expression of heat shock protein 72 in peritoneal leukocytes induced by peritoneal dialysis?\n", "\n", "Answer:\n", "Predictions: {\"draft_answer\": \"Yes, expression of heat shock protein 72 in peritoneal leukocytes is induced by peritoneal dialysis.\"}\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Plasma acyl and des-acyl ghrelin are thought of as components of total ghrelin, but this has never been validated using ex vivo spiking experiments, human sample collection comparisons and fit-for-purpose translatable assays.\n", "Acyl ghrelin plasma stability was analyzed by LC-MS/MS and it revealed that acyl ghrelin is enzymatically and chemically converted to des-acyl ghrelin in the presence of active serine proteases and HCl. ELISAs with less than 30% total error were used to assess acyl ghrelin behavior in matched authentic human samples. Acyl and total ghrelin were not statistically different in 4-(2-aminoethyl)benzenesulfonyl fluoride hydrochloride samples and acyl ghrelin losses in K(2)EDTA plasma were accounted for in des-acyl ghrelin formation.\n", "\n", "Question: Does prandial ghrelin attenuation provide evidence that des-acyl ghrelin may be an artifact of sample handling in human plasma?\n", "\n", "Answer:\n", "Predictions: No, the information provided does not support the idea that des-acyl ghrelin is an artifact of sample handling in human plasma. The study indicates that acyl ghrelin is converted to des-acyl ghrelin under certain conditions, but it does not directly link prandial ghrelin attenuation to sample handling artifacts.\n", "Solutions: yes\n", "Score: 0.0\n", "Error reason: Computation result is incorrect.Questions: Context: To evaluate whether tumor invasion depth can be a reliable and easily applicable pathologic assessment strategy to predict outcomes using surgically resected cervical squamous cell carcinoma specimens from patients who have received neoadjuvant radiotherapy (RT) or concurrent chemoradiotherapy (CCRT).\n", "We included 173 patients with cervical squamous cell carcinoma who received neoadjuvant CCRT (n = 125) or RT (n = 48) and underwent subsequent radical hysterectomy. Data for the pre-operative clinical International Federation of Gynecology and Obstetrics (FIGO) stage, post-operative pathologic FIGO stage, World Health Organization (WHO) double diameter measurement evaluation, response evaluation criteria in solid tumors (RECIST 1.1) criteria, tumor necrosis rate (TNR), and tumor regression grade (TRG) were investigated to identify correlations with outcomes related to distant metastasis and survival. The tumor invasion depth (TID) and the tumor invasion depth with cytokeratin immunostaining correction (TIDC) at the cervical internal surface were measured to assess their relations to patients' outcomes.\n", "Based on measurements taken via transvaginal ultrasound, the pre-operative clinical and post-operative pathologic FIGO staging as well as the WHO double diameter measurement evaluation and RECIST 1.1 criteria were predictive of distant metastasis and survival-related outcomes. Also, lymph node involvement was found to be an independent prognostic factor for recurrence and distant metastasis. Finally, univariate analysis showed both the TID and TIDC were highly related to distant metastasis, overall survival, and progression-free survival, irrespective of the clinical stage of carcinomas.\n", "\n", "Question: Is tumor invasion depth a useful pathologic assessment for predicting outcomes in cervical squamous cell carcinoma after neoadjuvant radiotherapy?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Increased lipid supply causes beta cell death, which may contribute to reduced beta cell mass in type 2 diabetes. We investigated whether endoplasmic reticulum (ER) stress is necessary for lipid-induced apoptosis in beta cells and also whether ER stress is present in islets of an animal model of diabetes and of humans with type 2 diabetes.\n", "Expression of genes involved in ER stress was evaluated in insulin-secreting MIN6 cells exposed to elevated lipids, in islets isolated from db/db mice and in pancreas sections of humans with type 2 diabetes. Overproduction of the ER chaperone heat shock 70 kDa protein 5 (HSPA5, previously known as immunoglobulin heavy chain binding protein [BIP]) was performed to assess whether attenuation of ER stress affected lipid-induced apoptosis.\n", "We demonstrated that the pro-apoptotic fatty acid palmitate triggers a comprehensive ER stress response in MIN6 cells, which was virtually absent using non-apoptotic fatty acid oleate. Time-dependent increases in mRNA levels for activating transcription factor 4 (Atf4), DNA-damage inducible transcript 3 (Ddit3, previously known as C/EBP homologous protein [Chop]) and DnaJ homologue (HSP40) C3 (Dnajc3, previously known as p58) correlated with increased apoptosis in palmitate- but not in oleate-treated MIN6 cells. Attenuation of ER stress by overproduction of HSPA5 in MIN6 cells significantly protected against lipid-induced apoptosis. In islets of db/db mice, a variety of marker genes of ER stress were also upregulated. Increased processing (activation) of X-box binding protein 1 (Xbp1) mRNA was also observed, confirming the existence of ER stress. Finally, we observed increased islet protein production of HSPA5, DDIT3, DNAJC3 and BCL2-associated X protein in human pancreas sections of type 2 diabetes subjects.\n", "\n", "Question: Does endoplasmic reticulum stress contribute to beta cell apoptosis in type 2 diabetes?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, endoplasmic reticulum stress contributes to beta cell apoptosis in type 2 diabetes.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Local bone yielding at the pin-bone interface of external fixation half-pins has been known to initiate fixator loosening. Deterioration of bone properties due to ageing and disease can lead to an increase in the risk of pin loosening. This study determines the extent, locations and mechanics of bone yielding for unilateral external fixation systems at the tibial midshaft with changes in age-related bone structure and properties. The study also evaluates the effect of the number of pins used in the fixation system and use of titanium pins (in place of steel) on bone yielding.\n", "We employ nonlinear finite element (FE) simulations. Strain-based plasticity is used to simulate bone yielding within FE analyses. Our analyses also incorporate contact behaviour at pin-bone interfaces, orthotropic elasticity and periosteal-endosteal variation of bone properties.\n", "The results show that peri-implant yielded bone volume increases by three times from young to old-aged cases. The use of three, rather than two half-pins (on either side of the fracture), reduces the volume of yielded bone by 80% in all age groups. The use of titanium half-pins resulted in approximately 60-65% greater volumes of yielded bone.\n", "\n", "Question: Do bone properties affect loosening of half-pin external fixators at the pin-bone interface?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, bone properties affect loosening of half-pin external fixators at the pin-bone interface.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The prostate specific membrane antigen (PSMA) represents an attractive antigen for antibody-based diagnostic and therapeutic intervention in prostate cancer, since it is highly restricted to the prostate and overexpressed in all tumor stages. The present work describes the in vitro characterization of the three anti-PSMA monoclonal antibodies (mAbs) 3/A12, 3/E7, and 3/F11 in comparison to the mAb J591.\n", "The mAbs were tested for saturation and competitive binding on C4-2 prostate cancer cells by flow cytometry. Immunohistochemical staining was conducted on frozen prostate normal and cancer tissues as well as on lymph node metastases. Similarly, potential crossreactivities were tested on a broad panel of human normal tissues.\n", "The anti-PSMA mAbs showed a strong binding to C4-2 cells with mean half-maximal saturation concentrations of about 14 nM for 3/A12, 17 nM for 3/E7, 9 nM for 3/F11, and 16 nM for J591. Competitive binding studies revealed that our three mAbs bind to different extracellular PSMA epitopes. The mAbs showed comparable staining of epithelial cells for all tested normal and tumorous prostate tissues. Extraprostatic staining was observed on secretory cells of the salivary glands and on the brush border of the duodenal columnar epithelium. J591 additionally showed positive staining of the normal breast epithelium.\n", "\n", "Question: Are three conformational antibodies specific for different PSMA epitopes promising diagnostic and therapeutic tools for prostate cancer?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, the three conformational antibodies specific for different PSMA epitopes are promising diagnostic and therapeutic tools for prostate cancer.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The objective of this study was to determine if adding spironolactone to an angiotensin II receptor blocker improves left ventricular (LV) function, mass, and volumes in chronic heart failure.\n", "Add-on spironolactone therapy substantially improves clinical outcomes among patients with severe heart failure (HF) on standard therapy. However, the value of combining spironolactone with an angiotensin II receptor blocker on LV reverse remodeling in mild-to-moderate systolic HF is unclear.\n", "Fifty-one systolic HF patients with left ventricular ejection fraction (LVEF) <40% were randomly assigned to receive 1-year treatment of candesartan and spironolactone (combination group) or candesartan and placebo (control group). Reverse remodeling was assessed by serial cardiac magnetic resonance imaging and echocardiographic tissue Doppler imaging (TDI).\n", "There were significant improvements in LVEF (35 +/- 3% vs. 26 +/- 2%, p < 0.01) and reduction of LV end-diastolic volume index (121 +/- 16 ml/m2 vs. 155 +/- 14 ml/m2, p = 0.001), end-systolic volume index (88 +/- 17 ml/m2 vs. 120 +/- 15 ml/m2, p < 0.0005), and LV mass index (81 +/- 6 g/m2 vs. 93 +/- 6 g/m2, p = 0.002) in the combination group at 1 year. In addition, there was significant increase in peak basal systolic velocity and strain by TDI, decrease in index of filling pressure, and increase in cyclic variation integrated backscatter. In the control group, there were no significant changes in all these parameters after 1 year.\n", "\n", "Question: Does aldosterone receptor antagonism induce reverse remodeling when added to angiotensin receptor blockade in chronic heart failure?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, aldosterone receptor antagonism induces reverse remodeling when added to angiotensin receptor blockade in chronic heart failure, as evidenced by significant improvements in left ventricular function and structure in the combination group compared to the control group.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Polo-like kinase 1 (PLK1) plays an important role in mitotic progression, is frequently overexpressed and associated with a poor prognosis of cancer patients, thus providing a promising target in anticancer treatment. Aim of the current project was to evaluate the effect of the novel PLK1 inhibitor BI 6727 in combination with irradiation.\n", "In vitro proliferation and radiation cell survival assays as well as in vivo local tumour control assays after single treatment and combined radiation and drug application were carried out using the squamous cell carcinoma models A431 and FaDu. In addition, cell cycle phases were monitored in vitro and in vivo.\n", "BI 6727 showed a dose-dependent antiproliferative effect and an increase in the mitotic fraction. BI 6727 alone reduced clonogenic cell survival, while radiosensitivity in vitro (SF2) and in vivo (single-dose TCD(50) under clamped hypoxia) was not affected. In contrast, local tumour control was significantly improved after application of BI 6727 simultaneously to fractionated irradiation (A431: TCD(50) = 60.5 Gy [95% C.I. 57; 63] after IR alone and <30 Gy after combined treatment; FaDu: 49.5 Gy [43; 56 Gy] versus 32.9 Gy [26; 40]).\n", "\n", "Question: Does simultaneous PLK1 inhibition improve local tumour control after fractionated irradiation?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, simultaneous PLK1 inhibition improves local tumour control after fractionated irradiation.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Besides being responsible for energy production in the cell, mitochondria are central players in apoptosis as well as the main source of harmful reactive oxygen species. Therefore, it can be hypothesised that sequence variation in the mitochondrial genome is a contributing factor to the etiology of diseases related to these different cellular events, including cancer. The aim of the present study was to assess the frequency of haplogroups and polymorphisms in the control region (CR) of mitochondrial DNA of peripheral blood mononuclear cells from patients with prostate carcinoma (n = 304) versus patients screened for prostate disease but found to be negative for cancer on biopsy (n = 278) in a Middle European population.\n", "The nine major European haplogroups and the CR polymorphisms were identified by means of primer extension analysis and DNA sequencing, respectively. We found that mitochondrial haplogroup frequencies and CR polymorphisms do not differ significantly between patients with or without prostate cancer, implying no impact of inherited mitochondrial DNA variation on predisposition to prostate carcinoma in a Middle European population.\n", "\n", "Question: Are mitochondrial haplogroups and control region polymorphisms associated with prostate cancer in Middle European Caucasians?\n", "\n", "Answer:\n", "Predictions: No, mitochondrial haplogroups and control region polymorphisms are not associated with prostate cancer in Middle European Caucasians.\n", "Solutions: no\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Essential for mitotic growth 1 (EMG1) is a highly conserved nucleolar protein identified in yeast to have a critical function in ribosome biogenesis. A mutation in the human EMG1 homolog causes Bowen-Conradi syndrome (BCS), a developmental disorder characterized by severe growth failure and psychomotor retardation leading to death in early childhood. To begin to understand the role of EMG1 in mammalian development, and how its deficiency could lead to Bowen-Conradi syndrome, we have used mouse as a model. The expression of Emg1 during mouse development was examined and mice carrying a null mutation for Emg1 were generated and characterized.\n", "Our studies indicated that Emg1 is broadly expressed during early mouse embryonic development. However, in late embryonic stages and during postnatal development, Emg1 exhibited specific expression patterns. To assess a developmental role for EMG1 in vivo, we exploited a mouse gene-targeting approach. Loss of EMG1 function in mice arrested embryonic development prior to the blastocyst stage. The arrested Emg1-/- embryos exhibited defects in early cell lineage-specification as well as in nucleologenesis. Further, loss of p53, which has been shown to rescue some phenotypes resulting from defects in ribosome biogenesis, failed to rescue the Emg1-/- pre-implantation lethality.\n", "\n", "Question: Is eMG1 essential for mouse pre-implantation embryo development?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, EMG1 is essential for mouse pre-implantation embryo development as loss of EMG1 function leads to arrested embryonic development prior to the blastocyst stage.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Acute rejection (AR) remains the primary risk factor for renal transplant outcome; development of non-invasive diagnostic biomarkers for AR is an unmet need.\n", "We used shotgun proteomics applying LC-MS/MS and ELISA to analyze a set of 92 urine samples, from patients with AR, stable grafts (STA), proteinuria (NS), and healthy controls.\n", "A total of 1446 urinary proteins (UP) were identified along with a number of nonspecific proteinuria-specific, renal transplantation specific and AR-specific proteins. Relative abundance of identified UP was measured by protein-level spectral counts adopting a weighted fold-change statistic, assigning increased weight for more frequently observed proteins. We have identified alterations in a number of specific UP in AR, primarily relating to MHC antigens, the complement cascade and extra-cellular matrix proteins. A subset of proteins (uromodulin, SERPINF1 and CD44), have been further cross-validated by ELISA in an independent set of urine samples, for significant differences in the abundance of these UP in AR.\n", "\n", "Question: Does shotgun proteomics identify proteins specific for acute renal transplant rejection?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, shotgun proteomics identifies proteins specific for acute renal transplant rejection.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To describe the long-term outcome of eyes with uveitis after repeated treatment with dexamethasone implants (Ozurdex; Allergan, Inc., Irvine, CA).\n", "Retrospective, observational case series.\n", "Thirty-eight eyes of 27 patients with uveitis that were treated with 61 dexamethasone implants.\n", "All eyes underwent dexamethasone pellet implantation. Anatomic and functional outcomes, as well as ocular complications, were noted.\n", "Best-corrected visual acuity (BCVA), central retinal thickness (CRT), vitreous haze score, and presence of increased intraocular pressure or cataract.\n", "Average follow-up was 17.3 ± 1.8 months after the first implant (median, 13.3 months; range, 3-54.5 months; 54.65 eye-years), with 14 eyes (36.9%) receiving a single implant and 24 eyes (63.1%) receiving multiple implantations. After the first implantation, average BCVA improved significantly from 0.47 ± 0.05 logarithm of the minimum angle of resolution (logMAR) units (Snellen equivalent, 20/60) to 0.27 ± 0.07 logMAR (Snellen equivalent, 20/37; P<0.001); CRT decreased by 263 ± 44.22 μm (P = 0.003), although macular edema persisted in 50% of eyes, and the percentage of eyes achieving a vitreous haze score of 0 increased from 58% to 83% (P = 0.03). The median duration of therapeutic effect after the first injection was 6 months (range, 2-42 months), with a similar response achieved after each repeat implantation. The accumulated effect of repeat dexamethasone implants resulted in a continued improvement in BCVA (R(2) = 0.91; P<0.0001), with significant improvement and stabilization of CRT. After repeated implantations, 2 eyes had progression of posterior subcapsular opacities, although neither required surgery. There were 7 instances of increased intraocular pressure of more than 21 mmHg at a rate of 0.13 per eye-year, all of which responded to pharmacologic treatment.\n", "\n", "Question: Does treatment with repeat dexamethasone implants result in long-term disease control in eyes with noninfectious uveitis?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, treatment with repeat dexamethasone implants results in long-term disease control in eyes with noninfectious uveitis, as indicated by significant improvements in visual acuity and stabilization of central retinal thickness over time.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To identify serologic markers of salivary gland disease activity in 43 patients with primary Sjögren's syndrome.\n", "Comparison of salivary gland biopsies (focus scores) and flow rates with serum concentrations of IgA and IgM rheumatoid factor (RF), total serum IgG, serum anti-SS-B/La antibodies, and the erythrocyte sedimentation rate.\n", "Serum anti-SS-B/La antibody levels correlated with focus scores (rs = 0.477, P < 0.0025). Serum IgA-RF concentrations correlated inversely with stimulated parotid gland salivary flow rates (rs = -0.394, P < 0.01).\n", "\n", "Question: Are serum anti-SS-B/La and IgA rheumatoid factor markers of salivary gland disease activity in primary Sjögren 's syndrome?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, serum anti-SS-B/La and IgA rheumatoid factor are markers of salivary gland disease activity in primary Sjögren's syndrome.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: This study assessed the impact of a pre-medical pipeline program on successful completion of medical school and the capacity of this program to address achievement gaps experienced by disadvantaged students. The University of North Carolina (USA) Medical Education Development (MED) program provides intensive academic and test skills preparation for admission to medical, dental, and other allied health professions schools.\n", "This retrospective study evaluated the academic progress of a longitudinal sample of 1738 disadvantaged college students who completed MED between 1974 and 2001. Data sources included MED participant data, medical school admissions data for the host school, aggregate data from the Association of American Medical Colleges (AAMC), and individual MED participant data from AAMC. Methods of analysis utilized Chi-square, independent samples t test, and logistic regression to examine associations between factors.\n", "Of the 935 students in MED from 1974 to 2001, who had indicated an interest in medical school, 887 (94.9%) successfully matriculated and 801 (85.7%) successfully earned the MD degree. Using logistic regression, factors that were significantly correlated with earning the medical degree included the student's race, college undergraduate total and science grade point averages, with Hispanic, African American, and Native American participants earning the medical degree at rates comparable to Caucasian participants. MED students successfully earned the MD degree despite having significantly lower Medical College Admissions Test (MCAT) scores and undergraduate grade point averages compared to all United States medical school applicants: MCAT scores had little relationship with student's success.\n", "\n", "Question: Does a social and academic enrichment program promote medical school matriculation and graduation for disadvantaged students?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, a social and academic enrichment program promotes medical school matriculation and graduation for disadvantaged students, as evidenced by the high rates of matriculation and graduation among participants in the MED program.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The mechanisms underlying the initiation of sustained ventricular tachycardia (VT) have not been fully elucidated. The extent to which reentry, abnormal automaticity, and triggered activity play a role in VT differs depending on the etiology of left ventricular dysfunction. By analyzing electrograms from implantable cardioverter defibrillator (ICD), we sought to determine whether there were differences in VT initiation patterns between patients with ischemic and nonischemic cardiomyopathy.\n", "We analyzed ICD electrograms in patients with ejection fractions < 40% who had sustained VT over a 27-month period. The trigger for VT onset was classified as a ventricular premature beat (VPB), supraventricular tachycardia, or of \"sudden onset.\" The baseline cycle length, VT cycle length, coupling interval, and prematurity ratio were recorded for each event. The prematurity ratio was calculated as the coupling interval of the VT initiator divided by the baseline cycle length.\n", "Sixty-three VT events in 14 patients met the inclusion criteria. A VPB initiated the VT in 58 episodes (92%), 1 episode (2%) was initiated by a supraventricular tachycardia, and 4 episodes (6%) were sudden onset. The prematurity ratio was significantly higher (P < 0.05) in patients with ischemic cardiomyopathy (0.751 +/- 0.068) as compared to patients with nonischemic cardiomyopathy (0.604 +/- 0.139).\n", "\n", "Question: Do triggers of sustained monomorphic ventricular tachycardia differ among patients with varying etiologies of left ventricular dysfunction?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, triggers of sustained monomorphic ventricular tachycardia differ among patients with varying etiologies of left ventricular dysfunction.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To evaluate the association between electronic health record (EHR) satisfaction and job satisfaction in primary care physicians (PCPs).\n", "Cross-sectional survey of PCPs at 825 primary care practices in North Carolina.\n", "Surveys were returned from 283 individuals across 214 practices (26% response rate for practices), of whom 122 were physicians with EHRs and no missing information. We found that for each point increase in EHR satisfaction, job satisfaction increased by ∼0.36 points both in an unadjusted and an adjusted model (β 0.359 unadjusted, 0.361 adjusted; p < 0.001 for both models).\n", "\n", "Question: Is satisfaction with electronic health records associated with job satisfaction among primary care physicians?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "Yes, satisfaction with electronic health records is associated with job satisfaction among primary care physicians.\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Extracellular matrix metalloproteinase inducer (EMMPRIN), an immunoglobulin-like cell surface glycoprotein, could promote collagenolytic balance in favor of the expression and activation of matrix metalloproteinases (MMPs). This study was to investigate the expression of EMMPRIN in gingival tissues from different periodontal conditions and to correlate it with the production of MMP-1 and MMP-2.\n", "Gingival biopsies were collected from 15 patients with untreated advanced chronic periodontitis and 15 patients with aggressive periodontitis (AgP). The control group consisted of 12 subjects diagnosed either as periodontally healthy individuals or as individuals with a gingival index of one (H/G1). The peptides and mRNA of EMMPRIN, MMP-1 and MMP-2 were detected by immunohistochemistry and semi-quantitative reverse transcriptase-polymerase chain reaction, respectively.\n", "The expression of EMMPRIN, MMP-1 and MMP-2 peptides in periodontally healthy tissues was mainly confined to the gingival epithelium. The EMMPRIN was strongly expressed in the cell membrane of the basal layer. Immunoreactivity for EMMPRIN was more intensive and more widespread in periodontitis, extended from the epithelial layers to the underlying connective tissues, and was essential in both inflammatory and fibroblast-like cells. In addition, MMP-1 and MMP-2 showed the same localized expression. The chronic periodontitis group had a significantly higher mRNA expression of EMMPRIN and MMP-2 compared with the H/G1 subjects (p < 0.05). Production of MMP-1 and MMP-2 by gingival tissues was correlated with the mRNA level of EMMPRIN (r = 0.463, p = 0.013 for MMP-1 and r = 0.404, p = 0.033 for MMP-2).\n", "\n", "Question: Is increased expression of extracellular matrix metalloproteinase inducer associated with matrix metalloproteinase-1 and -2 in gingival tissues from patients with periodontitis?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, increased expression of extracellular matrix metalloproteinase inducer is associated with matrix metalloproteinase-1 and -2 in gingival tissues from patients with periodontitis.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Comparison of preverbal communication behavior in young children before receiving cochlear implants with outcomes 3 yr after implantation on speech identification and speech production tasks, to assess whether outcomes can be predicted from characteristics inherent to the child before implantation.\n", "Video recordings of preverbal communicative behavior were examined before use of the implant to quantify turn-taking and demonstration of autonomy by the child. Speech identification ability was measured 3 yr after implantation based on the Iowa Closed-Set Speech Perception Sentence Test, continuous discourse tracking, and an observational measure of telephone use. Speech production ability was measured 3 yr after implantation by the Edinburgh Articulation Test. Associations between the preimplant measures and the 3-yr outcomes were assessed by correlation analysis of data from 33 children.\n", "The 3-yr performance measures of speech identification were correlated with the preimplant measure of autonomy. Telephone use and speech production ability were not significantly associated with the preimplant measures.\n", "\n", "Question: Do preimplant measures of preverbal communicative behavior as predictors of cochlear implant outcomes in children?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, preimplant measures of preverbal communicative behavior can serve as predictors of cochlear implant outcomes in children, particularly in relation to speech identification ability.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To determine the structure of T cell receptors (TCR) used by Sm-B-reactive human T cell clones, to map T cell epitopes on the Sm-B autoantigen, and to determine the HLA restriction element used in the recognition of Sm-B by T cells.\n", "Sm-B-reactive T cell clones were generated from patients with connective tissue disease by using either a recombinant fusion protein or synthetic peptides. The TCR structure was defined with the use of polymerase chain reaction and DNA sequencing. Synthetic peptides were used to map T cell epitopes on Sm-B. HLA restriction element usage was defined by using monoclonal antibody blocking.\n", "Usage of the TCR third complementarity-determining region (CDR3) was highly restricted among Sm-B autoantigen-specific human T cell clones. Only amino acids 48-96 of the Sm-B2 autoantigen were recognized by T cells, and this occurred in the context of HLA-DR.\n", "\n", "Question: Is t cell receptor beta-chain third complementarity-determining region gene usage highly restricted among Sm-B autoantigen-specific human T cell clones derived from patients with connective tissue disease?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, the T cell receptor beta-chain third complementarity-determining region gene usage is highly restricted among Sm-B autoantigen-specific human T cell clones derived from patients with connective tissue disease.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To assess the influence of inducible and endothelial nitric oxide synthase (iNOS and eNOS) polymorphisms in susceptibility to rheumatoid arthritis (RA).\n", "Two hundred RA patients fulfilling the 1987 American College of Rheumatology classification criteria followed at the out-patient rheumatology clinic of the Hospital Xeral-Calde (Lugo, Spain) and 251 ethnically matched controls were studied. Patients and controls were genotyped by PCR-based techniques for a multiallelic (CCTTT)(n) repeat in the promoter region of the iNOS gene and for a T/C polymorphism at position -786 in the promoter region and a polymorphism in exon 7 (298Glu/Asp or 5557G/T) of the eNOS gene.\n", "No significant difference in allele or genotype frequencies for either polymorphism in the eNOS gene was observed between RA patients and controls. The overall iNOS CCTTT(n) allelic or genotypic distribution did not show statistical significant differences between RA patients and controls. Interestingly, when we stratified the iNOS alleles into short (8-11) and long (12-16) repeats, significant differences were observed between RA patients and controls (P = 0.021; odds ratio = 1.37, 95% confidence interval 1.04-1.81). Of note, individuals carrying two alleles with a repeat number less than 12 (fewer than 196 base pairs) exhibited a double risk of developing RA (P = 0.005, odds ratio 2.26, 95% confidence interval 1.25-4.08).\n", "\n", "Question: Is inducible but not endothelial nitric oxide synthase polymorphism associated with susceptibility to rheumatoid arthritis in northwest Spain?\n", "\n", "Answer:\n", "Predictions: {\"draft_answer\": \"Yes, inducible nitric oxide synthase polymorphism is associated with susceptibility to rheumatoid arthritis in northwest Spain, while endothelial nitric oxide synthase polymorphism is not.\"}\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: A beneficial effect of regional anesthesia on cancer related outcome in various solid tumors has been proposed. The data on prostate cancer is conflicting and reports on long-term cancer specific survival are lacking.\n", "In a retrospective, single-center study, outcomes of 148 consecutive patients with locally advanced prostate cancer pT3/4 who underwent retropubic radical prostatectomy (RRP) with general anesthesia combined with intra- and postoperative epidural analgesia (n=67) or with postoperative ketorolac-morphine analgesia (n=81) were reviewed. The median observation time was 14.00 years (range 10.87-17.75 yrs). Biochemical recurrence (BCR)-free, local and distant recurrence-free, cancer-specific, and overall survival were estimated using the Kaplan-Meier technique. Multivariate Cox proportional-hazards regression models were used to analyze clinicopathologic variables associated with disease progression and death.\n", "The survival estimates for BCR-free, local and distant recurrence-free, cancer-specific survival and overall survival did not differ between the two groups (P=0.64, P=0.75, P=0.18, P=0.32 and P=0.07). For both groups, higher preoperative PSA (hazard ratio (HR) 1.02, 95% confidence interval (CI) 1.01-1.02, P<0.0001), increased specimen Gleason score (HR 1.24, 95% CI 1.06-1.46, P=0.007) and positive nodal status (HR 1.66, 95% CI 1.03-2.67, P=0.04) were associated with higher risk of BCR. Increased specimen Gleason score predicted death from prostate cancer (HR 2.46, 95% CI 1.65-3.68, P<0.0001).\n", "\n", "Question: Does epidural analgesia during open radical prostatectomy improve long-term cancer-related outcome : a retrospective study in patients with advanced prostate cancer?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"No, the study found that survival estimates did not differ between the group receiving epidural analgesia and the group receiving ketorolac-morphine analgesia.\"\n", "Solutions: no\n", "Score: 1.0\n", "The solution is correct.Questions: Context: CD133 is one of the most important cancer-initiating (stem) cell markers and was confirmed to be expressed in solid cancers such as colon cancer. However, no one has investigated the role of CD133 in intrahepatic cholangiocarcinoma (IHCC). The aim of this study was to clarify the clinical role of CD133 expression in IHCC.\n", "Twenty-nine patients with IHCC who underwent hepatic resection at our institution were enrolled in this study. Expression of CD133 was examined using anti-CD133 antibody. Staining was observed in the cytoplasm of cancer cells and CD133-positive cells distributed in the whole tumor. The patients were divided into two groups: the CD133-positive group (n = 14) and CD133-negative group (n = 15), in which no staining of CD133 was observed. Clinicopathological factors including hypoxia-inducible factor-1alpha expression were compared between the two groups. The prognostic factors were investigated by multivariate analysis using Cox's proportional hazard model.\n", "The 5-year survival rate in the CD133-positive group (8.0%) was worse than that in the CD133-negative group (57.0%). In the CD133-positive group, the incidence of intrahepatic metastasis and positive expression of hypoxia-inducible factor-1alpha tended to be higher than that in the CD133 negative group. The multivariate analysis revealed CD133 expression was an independent prognostic indicator in IHCC.\n", "\n", "Question: Is cD133 expression a potential prognostic indicator in intrahepatic cholangiocarcinoma?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, CD133 expression is a potential prognostic indicator in intrahepatic cholangiocarcinoma.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Stable dry-state storage of DNA is desirable to minimize required storage space and to reduce electrical and shipping costs. DNA purified from various commercially available dry-state stabilization matrices has been used successfully in downstream molecular applications (e.g., quantitative polymerase chain reaction [qPCR], microarray, and sequence-based genotyping). However, standard DNA storage conditions still include freezing of DNA eluted in aqueous buffers or nuclease-free water. Broad implementation of dry-state, long-term DNA storage requires enhancement of such dry-state DNA stabilization products to control for temperature fluctuations at specimen collection, transit, and storage. This study tested the integrity of genomic DNA subjected to long-term storage on GenTegra(™) DNA stabilization matrices (GenTegra LLC, Pleasanton, CA) at extreme conditions, as defined by a 4-year storage period at ambient temperature with an initial incubation for 7 months at 37°C, 56°C, or ambient temperature. Subsequently, purified DNA performance and integrity were measured by qPCR and next-generation sequencing (NGS)-based human leokocyte antigen (HLA) genotyping.\n", "High molecular weight genomic DNA samples were recovered from the GenTegra product matrix and exhibited integrity comparable to a highly characterized commercial standard under assessment by qPCR. Samples were genotyped for classical HLA loci using next generation sequencing-based methodolgy on the Roche 454 GS Junior instrument. Amplification efficiency, sequence coverage, and sequence quality were all comparable with those produced from a cell line DNA sequenced as a control. No significant differences were observed in the mean, median, or mode quality scores between samples and controls (p≥0.4).\n", "\n", "Question: Does dNA storage under high temperature conditions affect performance in human leukocyte antigen genotyping via next-generation sequencing ( DNA integrity maintained in extreme conditions )?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"No, DNA storage under high temperature conditions does not affect performance in human leukocyte antigen genotyping via next-generation sequencing, as DNA integrity was maintained in extreme conditions.\"\n", "Solutions: no\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The role of the Ferric Uptake Regulator (FUR) in the acid resistance of Helicobacter pylori (H. pylori) has been thought to be independent of urease. However, we demonstrated in this study that Fur influences urease activity.\n", "A fur knockout mutant of H. pylori was constructed by replacing the Fur gene with a kanamycin resistant marker gene. The wild-type H. pylori and fur mutant were compared for survival. The integrity of the inner membrane of the bacteria was evaluated by confocal microscopy using membrane-permeant and -impermeant fluorescent DNA probes. Urease activity of intact H. pylori was measured between pH 3 and 8. Real time PCR of both strains was performed for urease genes including ureI, ureE, ureF, ureG, and ureH.\n", "The fur deletion affected the survival of H. pylori at pH 4. The urease activity curve of the intact fur mutant showed the same shape as the wild-type but was 3-fold lower than the wild-type at a pH of less than 5. Real time PCR revealed that the expression of all genes was consistently down-regulated in the fur mutant.\n", "\n", "Question: Is helicobacter pylori urease activity influenced by ferric uptake regulator?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, Helicobacter pylori urease activity is influenced by the ferric uptake regulator (FUR).\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Obese Alms1 mutant (foz/foz) NOD.B10 mice develop diabetes and fibrotic NASH when fed high-fat(HF) diet. To establish whether diabetes or obesity is more closely associated with NASH fibrosis, we compared diabetic foz/foz C57BL6/J with non-diabetic foz/foz BALB/c mice. We also determined hepatic cytokines, growth factors and related profibrotic pathways.\n", "Male and female foz/foz BALB/c and C57BL6/J mice were fed HF or chow for 24 weeks before determining metabolic indices, liver injury, cytokines, growth factors, pathology/fibrosis and matrix deposition pathways.\n", "All foz/foz mice were obese. Hepatomegaly, hyperinsulinemia, hyperglycaemia and hypoadiponectinaemia occurred only in foz/foz C57BL6/J mice, whereas foz/foz BALB/c formed more adipose. Serum ALT, steatosis, ballooning, liver inflammation and NAFLD activity score were worse in C57BL6/J mice. In HF-fed mice, fibrosis was severe in foz/foz C57BL6/J, appreciable in WT C57BL6/J, but absent in foz/foz BALB/c mice. Hepatic mRNA expression of TNF-α, IL-12, IL-4, IL-10 was increased (but not IFN-γ, IL-1β, IL-17A), and IL-4:IFN-γ ratio (indicating Th-2 predominance) was higher in HF-fed foz/foz C57BL6/J than BALB/c mice. In livers of HF-fed foz/foz C57BL6/J mice, TGF-β was unaltered but PDGFα and CTGF were increased in association with enhanced α-SMA, CD147and MMP activity.\n", "\n", "Question: Is strain dependence of diet-induced NASH and liver fibrosis in obese mice linked to diabetes and inflammatory phenotype?\n", "\n", "Answer:\n", "Predictions: {\"draft_answer\": \"Yes, the strain dependence of diet-induced NASH and liver fibrosis in obese mice is linked to diabetes and inflammatory phenotype, as indicated by the differences observed between the diabetic foz/foz C57BL6/J and non-diabetic foz/foz BALB/c mice in terms of metabolic indices, liver injury, and cytokine expression.\"}\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: This study aimed at exploring the psychosocial and clinical correlates of substance use disorder in an adolescent inpatient psychiatric population.\n", "During the period from 2006-2007, all subjects were systematically screened for substance use disorder (SUD) and were assessed for SUD characteristics by an independent support team using the RECAP (Joint Report on Drug Addiction and Treatment). Each SUD case was matched for age, gender, unit, and admission week, so as to compare a consumer sample (cases) with a non-consumer sample (controls). We retrospectively extracted data (socio-demographic and clinical characteristics) from charts to realize a case-control comparison. To assess Axis II borderline psychopathology, the child retro-DIB (Diagnosis Interview for Borderline) was used.\n", "The sample included 30 cases and 30 controls between 14 and 17 years of age. SUD was significantly associated with maltreatment (p=0.038), loss of a first-degree relative (p=0.039), school absenteeism (p=0.035) and suicide attempts (p=0.02). Regarding psychopathology, significant co-occurrence was observed between SUD and conduct disorder (p=0.019), all personality disorders (p=0.003) and borderline personality disorder specifically (p=0.021).\n", "\n", "Question: Do psychosocial and Clinical Correlates of Substance use Disorder in an Adolescent Inpatient Psychiatric Population?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, the study explores the psychosocial and clinical correlates of substance use disorder in an adolescent inpatient psychiatric population.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Earlier studies have shown a prolonged frequency-adjusted Q-T interval (QTc>0.440 s(1/2)) in a substantial fraction of patients with cirrhosis. The effect of beta-blockade on QTc is unknown, and its determination was the aim of the study.\n", "Seventeen patients with cirrhosis received 80 mg propranolol orally during a haemodynamic investigation with measurements at baseline and 90 min after propranolol ingestion.\n", "Beta-blockade reduced cardiac output (-21%, P<0.001), heart rate (-20%, P<0.001), and the hepatic venous pressure gradient (HVPG, -17%, P<0.02). The mean QTc=0.460 s(1/2) was prolonged compared to 0.410 s(1/2) in age-matched controls (P<0.01). Whereas QTc decreased during beta-blockade in the cirrhotic patients (from 0.460 to 0.440 s(1/2), P<0.01), no effect was found in the subgroup with normal QTc (0.429 vs. 0.422 s(1/2), ns), and a reduction was seen in the patients with prolonged QTc (from 0.488 to 0.456 s(1/2), P<0.01). The percentage decrease in QTc was related to the reduction in HVPG (r=0.48, P=0.03) and cardiac output (r=0.56, P=0.02).\n", "\n", "Question: Does acute non-selective beta-adrenergic blockade reduce prolonged frequency-adjusted Q-T interval ( QTc ) in patients with cirrhosis?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, acute non-selective beta-adrenergic blockade reduces prolonged frequency-adjusted Q-T interval (QTc) in patients with cirrhosis.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Bardet-Biedl syndrome (BBS) is a genetically heterogeneous disorder of the primary cilium associated with obesity. In BBS mouse models, ciliary dysfunction leads to impaired leptin signaling and hyperleptinemia before obesity onset. To study the pathophysiology of obesity in BBS, we compared patients with BBS and body mass index Z-score (BMI-Z)-matched controls.\n", "Fifty patients with BBS were matched 2:1 by age, sex, race, and BMI-Z with 100 controls. Patients with BBS and controls were compared for differences in body composition (dual-energy x-ray absorptiometry, abdominal magnetic resonance imaging), blood pressure Z-score (BP-Z; standardized for age, sex, and height), and fasting concentrations of leptin, lipids, insulin, and glucose. Patients with BBS were also compared by genotype.\n", "Leptin, triglycerides, intraabdominal fat mass, and diastolic BP-Z were significantly greater in patients with BBS than in the controls. BBS1 (27%) and BBS10 (30%) mutations were the most prevalent. Patients with BBS10 mutations had significantly higher BMI-Z, greater visceral adiposity, and greater insulin resistance than those with BBS1 mutations.\n", "\n", "Question: Do patients with Bardet-Biedl syndrome have hyperleptinemia suggestive of leptin resistance?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, patients with Bardet-Biedl syndrome have hyperleptinemia suggestive of leptin resistance.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Oral Squamous Cell Carcinoma (OSCC) is a major cause of cancer death worldwide, which is mainly due to recurrence leading to treatment failure and patient death. Histological status of surgical margins is a currently available assessment for recurrence risk in OSCC; however histological status does not predict recurrence, even in patients with histologically negative margins. Therefore, molecular analysis of histologically normal resection margins and the corresponding OSCC may aid in identifying a gene signature predictive of recurrence.\n", "We used a meta-analysis of 199 samples (OSCCs and normal oral tissues) from five public microarray datasets, in addition to our microarray analysis of 96 OSCCs and histologically normal margins from 24 patients, to train a gene signature for recurrence. Validation was performed by quantitative real-time PCR using 136 samples from an independent cohort of 30 patients.\n", "We identified 138 significantly over-expressed genes (> 2-fold, false discovery rate of 0.01) in OSCC. By penalized likelihood Cox regression, we identified a 4-gene signature with prognostic value for recurrence in our training set. This signature comprised the invasion-related genes MMP1, COL4A1, P4HA2, and THBS2. Over-expression of this 4-gene signature in histologically normal margins was associated with recurrence in our training cohort (p = 0.0003, logrank test) and in our independent validation cohort (p = 0.04, HR = 6.8, logrank test).\n", "\n", "Question: Is a gene signature in histologically normal surgical margins predictive of oral carcinoma recurrence?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, a gene signature in histologically normal surgical margins is predictive of oral carcinoma recurrence.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Hepatitis C virus (HCV) is a major cause of chronic hepatitis worldwide. Scavenger receptor class B type I (SR-BI) has been shown to bind HCV envelope glycoprotein E2, participate in entry of HCV pseudotype particles, and modulate HCV infection. However, the functional role of SR-BI for productive HCV infection remains unclear. In this study, we investigated the role of SR-BI as an entry factor for infection of human hepatoma cells using cell culture-derived HCV (HCVcc). Anti-SR-BI antibodies directed against epitopes of the human SR-BI extracellular loop specifically inhibited HCVcc infection in a dose-dependent manner. Down-regulation of SR-BI expression by SR-BI-specific short interfering RNAs (siRNAs) markedly reduced the susceptibility of human hepatoma cells to HCVcc infection. Kinetic studies demonstrated that SR-BI acts predominately after binding of HCV at an entry step occurring at a similar time point as CD81-HCV interaction. Although the addition of high-density lipoprotein (HDL) enhanced the efficiency of HCVcc infection, anti-SR-BI antibodies and SR-BI-specific siRNA efficiently inhibited HCV infection independent of lipoprotein.\n", "\n", "Question: Is scavenger receptor class B type I a key host factor for hepatitis C virus infection required for an entry step closely linked to CD81?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, scavenger receptor class B type I is a key host factor for hepatitis C virus infection required for an entry step closely linked to CD81.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Previous studies have demonstrated that Caveolin-1 (Cav-1) can ambiguously behave as tumor suppressor or tumor promoter in different neoplasms, depending on cancer type. Some findings have also revealed that cell proliferation, migration and invasion were attenuated by the knockdown of Caveolin-1 expressions. However, the functional and prognostic significance of Caveolin-1 in most tumors remains to be fully elucidated.\n", "The aim of the study was to investigate a possible association between tissue Caveolin-1 expression and the clinicopathologic features of ovarian serous tumors.\n", "Caveolin-1 expression was studied in a total of 82 formalin-fixed, paraffin-embedded specimens of ovarian serous tumors and its association with different clinicopathologic parameters was evaluated.\n", "The study included 36 (43.9%) benign, 12 (14.6%) borderline and 34 (41.5%) malignant serous tumors. Mean patient age was 43.9 ± 14.4 years (17-72 years). Statistical analysis revealed that if the tumor becomes more aggressive and invasive, it losses the stromal Caveolin-1 expression (p = 0.001). Also, parallel changes between stromal and perivascular Caveolin-1 expressions were observed.\n", "\n", "Question: Is expression of caveolin-1 in peritumoral stroma associated with histological grade in ovarian serous tumors?\n", "\n", "Answer:\n", "Predictions: {\"draft_answer\": \"Yes, the expression of caveolin-1 in peritumoral stroma is associated with histological grade in ovarian serous tumors, as indicated by the findings that aggressive and invasive tumors lose stromal Caveolin-1 expression.\"}\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The endocannabinoid N-arachidonoylethanolamide (anandamide) is co-synthesized with other N-acylethanolamides, namely N-palmitoylethanolamide (PEA) and N-oleoylethanolamide (OEA), which have been shown to potentiate anandamide responses (so-called 'entourage effects') in non-vascular tissues. It remains unclear whether such interactions occur in the circulation.\n", "In rat isolated small mesenteric arteries, the effects of PEA and OEA on relaxation to anandamide and tissue contents of the N-acylethanolamides were examined under myographic conditions.\n", "Anandamide-induced relaxation was potentiated by pretreatment with PEA (10 microM) or OEA (1 microM), or in combination. The potentiation by PEA and OEA was endothelium-independent and abolished by treatment with capsaicin (10 microM), which desensitizes the transient receptor potential vanilloid type 1 (TRPV1) receptor system, or by the TRPV1 receptor antagonist, N-(3-methoxyphenyl)-4-chlorocinnamide (SB366791) (2 microM). It was also observed at molar ratios of anandamide and PEA (or OEA) similar to those found in mesenteric arteries. PEA and inhibition of anandamide hydrolysis by 3'-carbamoyl-biphenyl-3-yl-cyclohexylcarbamate (URB597) (1 microM) additively potentiated anandamide responses. On the other hand, PEA and OEA also induced vasorelaxation per se (rank order of potency: anandamide>OEA>PEA), but relaxation to the three N-acylethanolamides displayed different sensitivity to treatment with capsaicin, SB366791 and URB597. For example, relaxations to anandamide and OEA, but not PEA, were attenuated by both capsaicin and SB366791.\n", "\n", "Question: Do 'Entourage ' effects of N-palmitoylethanolamide and N-oleoylethanolamide on vasorelaxation to anandamide occur through TRPV1 receptors?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"No, the entourage effects of N-palmitoylethanolamide and N-oleoylethanolamide on vasorelaxation to anandamide do not occur through TRPV1 receptors, as the potentiation was endothelium-independent and abolished by TRPV1 receptor antagonists.\"\n", "Solutions: yes\n", "Score: 0.0\n", "Error reason: Computation result is incorrect.Questions: Context: Surgical procedures on the thoracoabdominal part of the aorta make the spinal cord vulnerable to ischemia. Paraplegia is the most severe complication following thoracoabdominal operations. In this study, iloprost was used as an agent to decrease the severity of ischemia and reperfusion injury to the spinal cord during aortic occlusion and declamping.\n", "Twelve adult mongrel dogs weighing 17+/-2 kg were used in this study. The animals were randomly assigned to either group I, which received saline solution (6 dogs), or group II, which received prostacyclin. Group I was referred to as the control group and group II as the iloprost group. After baseline measurements were completed, the aorta was cross-clamped for sixty minutes distal to the left subclavian artery. No pharmacologic agents were used to control blood pressure in group I. Proximal and distal mean arterial pressures (DMAP) were monitored continuously. DMAP were considered as diastolic pressure in preocclusion and reperfusion periods. Iloprost administration was started at a rate of 5 ng/kg/minute five minutes before the aortic occlusion. This dosage was increased to 25 ng/kg/minute during aortic occlusion.\n", "Mean proximal arterial pressure was 147+/-12 mmHg in the control group and 116+/-13 mmHg in the iloprost group at occlusion (p<0.01). Mean distal arterial pressure was 19+/-7 in the control group and 37+/-5 in the iloprost group during clamping (p<0.05). Functional outcome was evaluated according to Tarlov scores 24 hours after the study. Although none of the animals recovered completely from the control group, 4 animals from the iloprost group recovered (p<0.05). Following the neurologic assessment, animals were sacrificed and specimens were taken for the electron microscopic study. Electron microscopic changes documented that severe mitochondrial damage and vacuolisation occurred in the control group. However these changes were more subtle in the iloprost group.\n", "\n", "Question: Does iloprost protect the spinal cord during aortic cross-clamping in a canine model?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, iloprost protects the spinal cord during aortic cross-clamping in a canine model, as evidenced by improved functional outcomes and less severe mitochondrial damage compared to the control group.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Expressive therapies are increasingly incorporated into the management of Parkinson's disease (PD), although there are little objective data assessing their benefits.\n", "Develop and study a novel community Improvisation Theater (IT) program for PD in order to improve quality of life.\n", "A prospective, rater-blinded, modified cross-over design study of IT for PD. 22 subjects were randomized 1:1 to active-start (AS) or control-start (CS) groups, controlling for age and Hoehn and Yahr stage. Participants were recruited from the Northwestern PD and Movement Disorders Center. 60 min IT sessions were led by The Second City\n", "All 22 participants completed the study. 21/22 (95%) participants attended at least 80% of the classes. All participants indicated that they would recommend the class to others with PD. 21/22 participants enjoyed the class and felt it was beneficial for their symptoms. A significant improvement pre-to-post intervention was seen with the UPDRS part II ADL measure (mean -1.5, p = 0.019).\n", "\n", "Question: Is laughter the best medicine : The Second?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, laughter can be considered beneficial for health, as evidenced by the positive outcomes from expressive therapies like Improvisation Theater for individuals with Parkinson's disease.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Many countries use cooling plates to actively cool collected whole blood (WB) to room temperature. Until now, no paired comparison had been performed, and it was our aim to compare the effect of active versus no active cooling on the in vitro quality of WB and subsequently prepared blood components.\n", "Two units of WB were pooled and divided shortly after donation. One unit was placed under a butane-1,4-diol plate to obtain active cooling; the other was placed in an insulated box with other warm units to mimic worst-case holding conditions. WB was held overnight and processed into a white blood cell (WBC)-reduced red blood cells (RBCs), buffy coat (BC), and plasma. The BCs were further processed into platelet (PLT) concentrates. RBCs were stored for 42 days, and PLT concentrates for 8 days (n = 12 paired experiments).\n", "After overnight storage, ATP content of the RBCs was 4.9 ± 0.3 µmol/g Hb for actively cooled WB versus 4.5 ± 0.4 µmol/g Hb for not actively cooled WB (p < 0.001). On Day 42 of storage, RBCs prepared from this WB contained 3.1 ± 0.3 µmol ATP/g Hb with active cooling versus 2.6 ± 0.3 µmol/g Hb without (p < 0.001). Hemolysis on Day 42 was 0.35 ± 0.08% with active cooling and 0.67 ± 0.21% without (p < 0.001). No effect was observed on the in vitro quality of plasma, BC, or PLT concentrates.\n", "\n", "Question: Does active cooling of whole blood to room temperature improve blood component quality?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "Yes, active cooling of whole blood to room temperature improves blood component quality.\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Tumor size is one of the most important factors in making clinical and pathological assessment of breast cancer. In the present study, we aimed to determine whether the preoperative measurement of tumor size, by imaging modalities, deviate from the postoperative pathological measurement in breast cancer.\n", "1296 patients diagnosed with invasive ductal breast carcinoma (IDC) during 2007 and 2009 were involved. Pre- and postoperative measurements of tumor size were compared using paired t-test and Chi-square test.\n", "The mean maximum diameters of tumors by imaging modalities and pathology were 27.9 mm and 22.4 mm, respectively. There was a statistically significant difference of 5.5 mm (95% CI: 4.7-6.2, p<0.001) between them. The discordance between pre- and post-surgical measurements of tumor size had significant effect on choosing surgery type, causing less application of breast conserving therapy (p<0.0001).\n", "\n", "Question: Does preoperative measurement of breast cancer overestimate tumor size compared to pathological measurement?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, the preoperative measurement of breast cancer overestimates tumor size compared to pathological measurement.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Basal-phenotype or basal-like breast cancers are characterized by basal epithelium cytokeratin (CK5/14/17) expression, negative estrogen receptor (ER) status and distinct gene expression signature. We studied the clinical and biological features of the basal-phenotype tumors determined by immunohistochemistry (IHC) and cDNA microarrays especially within the ER-negative subgroup.\n", "IHC was used to evaluate the CK5/14 status of 445 stage II breast cancers. The gene expression signature of the CK5/14 immunopositive tumors was investigated within a subset (100) of the breast tumors (including 50 ER-negative tumors) with a cDNA microarray. Survival for basal-phenotype tumors as determined by CK5/14 IHC and gene expression signature was assessed.\n", "From the 375 analyzable tumor specimens, 48 (13%) were immunohistochemically positive for CK5/14. We found adverse distant disease-free survival for the CK5/14-positive tumors during the first years (3 years hazard ratio (HR) 2.23, 95% confidence interval (CI) 1.17 to 4.24, p = 0.01; 5 years HR 1.80, 95% CI 1.02 to 3.15, p = 0.04) but the significance was lost at the end of the follow-up period (10 years HR 1.43, 95% CI 0.84 to 2.43, p = 0.19). Gene expression profiles of immunohistochemically determined CK5/14-positive tumors within the ER-negative tumor group implicated 1,713 differently expressed genes (p < 0.05). Hierarchical clustering analysis with the top 500 of these genes formed one basal-like and a non-basal-like cluster also within the ER-negative tumor entity. A highly concordant classification could be constructed with a published gene set (Sorlie's intrinsic gene set, concordance 90%). Both gene sets identified a basal-like cluster that included most of the CK5/14-positive tumors, but also immunohistochemically CK5/14-negative tumors. Within the ER-negative tumor entity there was no survival difference between the non-basal and basal-like tumors as identified by immunohistochemical or gene-expression-based classification.\n", "\n", "Question: Is basal-like phenotype associated with patient survival in estrogen-receptor-negative breast cancers?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"No, within the ER-negative tumor entity there was no survival difference between the non-basal and basal-like tumors as identified by immunohistochemical or gene-expression-based classification.\"\n", "Solutions: no\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Proteins and peptides occurring in human body fluids can be useful biological markers for neurological diseases and can even contribute to the pathogenesis of such diseases. However, proteins and peptides are potential substrates of proteases and other enzymes. Proteolysis and enzymatic modification may lead to their degradation and modification.\n", "Using mass spectrometry we investigated the degradation and modification of indicator peptides in the presence of cerebrospinal fluid (CSF). We further applied a fluorometric assay to study the activity of the presumed enzyme glutaminyl cyclase.\n", "In CSF we observed an aminopeptidase activity that could partially be inhibited by protease inhibitors and EDTA. In addition, the formation of pyroglutamate (pGlu) from N-terminal glutamine (Gln) was regularly observed. The reaction to pGlu was rapid and protected the indicator peptides from further N-terminal degradation. The conversion of Gln to pGlu could be attributed to the activity of the enzyme glutaminyl cyclase (QC). The QC activity was a characteristic feature of all 45 CSF samples collected from multiple sclerosis patients and controls.\n", "\n", "Question: Is glutaminyl cyclase activity a characteristic feature of human cerebrospinal fluid?\n", "\n", "Answer:\n", "Predictions: {\"draft_answer\": \"Yes, glutaminyl cyclase activity is a characteristic feature of human cerebrospinal fluid.\"}\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.\n", "{'name': 'generate_answer', 'description': 'Draft an answer using the retrieved context.', 'inputs': [{'name': 'question', 'type': 'str', 'description': 'The original question from the user.', 'required': True}], 'outputs': [{'name': 'draft_answer', 'type': 'str', 'description': 'A concise, direct answer to the question.', 'required': True}], 'prompt': None, 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"You can think to generate answers. You should provide the final answer (either Yes or No) in the 'answer' field. Format your answer in xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[32m2026-01-06 08:38:57.013\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.201 | Total tokens: 6073142 | Current cost: $0.003 | Current tokens: 19768\u001b[0m\n", "\u001b[32m2026-01-06 08:38:59.560\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.201 | Total tokens: 6073411 | Current cost: $0.000 | Current tokens: 269\u001b[0m\n", "\u001b[32m2026-01-06 08:39:01.145\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.202 | Total tokens: 6074195 | Current cost: $0.000 | Current tokens: 784\u001b[0m\n", "{'name': 'validate_answer9330', 'description': 'Task to validate_answer9330. Takes draft_answer as input. Produces validated_answer as output.', 'inputs': [{'name': 'draft_answer', 'type': 'str', 'description': 'Input parameter draft_answer for validate_answer9330', 'required': False}], 'outputs': [{'name': 'validated_answer', 'type': 'str', 'description': 'Output parameter validated_answer from validate_answer9330', 'required': True}], 'prompt': 'Your are a task solver.', 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"Think step by step to answer the question based on the question context. You should integrate context for answering. You should explain your thinking process in the 'thought' field, and provide the final answer in the 'answer' field.\\nFormat your output in xml format, such as xxx and xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n", "\u001b[32m2026-01-06 08:39:04.058\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.205 | Total tokens: 6093991 | Current cost: $0.003 | Current tokens: 19796\u001b[0m\n", "\u001b[32m2026-01-06 08:39:05.548\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.205 | Total tokens: 6094156 | Current cost: $0.000 | Current tokens: 165\u001b[0m\n", "\u001b[32m2026-01-06 08:39:07.148\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.205 | Total tokens: 6094855 | Current cost: $0.000 | Current tokens: 699\u001b[0m\n", "{'name': 'evaluate_answer9619', 'description': 'Task to evaluate_answer9619. Takes validated_answer as input. Produces evaluation_score as output.', 'inputs': [{'name': 'validated_answer', 'type': 'str', 'description': 'Input parameter validated_answer for evaluate_answer9619', 'required': False}], 'outputs': [{'name': 'evaluation_score', 'type': 'str', 'description': 'Output parameter evaluation_score from evaluate_answer9619', 'required': True}], 'prompt': 'Your are a task solver.', 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"Think step by step to answer the question based on the question context. You should integrate context for answering. You should explain your thinking process in the 'thought' field, and provide the final answer in the 'answer' field.\\nFormat your output in xml format, such as xxx and xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n", "\u001b[32m2026-01-06 08:39:11.315\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.209 | Total tokens: 6114678 | Current cost: $0.003 | Current tokens: 19823\u001b[0m\n", "\u001b[32m2026-01-06 08:39:14.095\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.209 | Total tokens: 6114976 | Current cost: $0.000 | Current tokens: 298\u001b[0m\n", "\u001b[32m2026-01-06 08:39:15.736\u001b[0m | \u001b[1mINFO \u001b[0m | 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"text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Evaluating workflow: 100%|██████████| 50/50 [01:15<00:00, 1.51s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "\u001b[32m2026-01-06 08:40:31.093\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.optimizers.qastructure_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m1057\u001b[0m - \u001b[1mStep 1 metrics: {'f1': 0.0, 'em': 0.0, 'acc': 0.92}\u001b[0m\n", "randomly update dataset\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[32m2026-01-06 08:40:33.211\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.222 | Total tokens: 6184223 | Current cost: $0.003 | Current tokens: 19669\u001b[0m\n", "\u001b[32m2026-01-06 08:40:34.718\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.226 | Total tokens: 6203888 | Current cost: $0.003 | Current tokens: 19665\u001b[0m\n", "\u001b[32m2026-01-06 08:40:36.029\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.229 | Total tokens: 6223513 | Current cost: $0.003 | Current tokens: 19625\u001b[0m\n", "\u001b[32m2026-01-06 08:40:37.982\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.229 | Total tokens: 6224082 | Current cost: $0.000 | Current tokens: 569\u001b[0m\n", "The workflow exhibits several critical issues: it lacks a clear step for comprehensive context analysis before answer generation, which can lead to misunderstandings; the validation criteria are unspecified, resulting in inconsistent evaluations; and there is no mechanism to address ambiguities in question prompts, risking oversimplified responses. Additionally, the absence of a feedback loop to learn from incorrect answers and a clear process for handling validation failures may leave errors unaddressed. The control flow does not accommodate discrepancies between draft and validated answers, and the prompts often lack clarity, contributing to misinterpretations and incorrect outputs. Overall, these deficiencies suggest a need for improved clarity, consistency, and adaptability in the workflow.\n", "\u001b[32m2026-01-06 08:40:40.470\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.229 | Total tokens: 6224841 | Current cost: $0.000 | Current tokens: 759\u001b[0m\n", "```python\n", "steps = [\n", "{'name': 'generate_answer', 'args': ['question'], 'outputs': ['draft_answer']},\n", "{'name': 'validate_answer9330', 'args': ['draft_answer'], 'outputs': ['validated_answer']},\n", "{'name': 'evaluate_answer9619', 'args': ['validated_answer'], 'outputs': ['evaluation_score']},\n", "{'name': 'context_analysis', 'args': ['question'], 'outputs': ['context']},\n", "{'name': 'handle_ambiguities', 'args': ['context'], 'outputs': ['clarified_question']},\n", "{'name': 'generate_answer', 'args': ['clarified_question'], 'outputs': ['draft_answer']},\n", "{'name': 'feedback_loop', 'args': ['evaluation_score', 'draft_answer'], 'outputs': ['improved_answer']}\n", "]\n", "```\n", "Questions: Context: To investigate the resistance to dislodgment produced by Biodentine (Septodont) and White-MTA (Angelus) after immersion in phosphate-buffered saline (PBS) for different durations.\n", "Dentin disks 1 ± 0.1 mm thick were obtained from the middle third of the roots of 6 human maxillary canines. On the coronal surface of each dentin disk, four 0.8-mm-diameter holes were drilled. Then the slices were halved using a low-speed saw diamond disk, and the two holes in each half were filled with one of the two tested materials. Each filled half was immersed in PBS solution (pH 7.2) either for 7 days (short term) or 60 days (long term) at 37°C. The push-out test was performed after both time periods. A general linear model (GLM) for repeated measures ANOVA was used to verify the effect of the material and duration of contact with PBS on the push-out strength. The material was considered as the within-subject contrast and the contact duration as the between-subjects effect (p < 0.05).\n", "Repeated measures GLM indicated a significant impact of material and time on the push-out strength of the samples (p = 0.000 and p = 0.033, respectively). Biodentine significantly improved the push-out strength compared to MTA at both times (p = 0.000). The lack of significance in the interaction between material and time indicates that PBS immersion positively influenced the push-out values of both tested materials.\n", "\n", "Question: Does resistance of Hydraulic Calcium Silicate cement to Dislodgment in Short- and Long-term Assessment?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, the resistance of Hydraulic Calcium Silicate cement to dislodgment was assessed in both short- and long-term evaluations, showing significant results.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Ganglion cells were thought not to occur within the mucosa of the normal colon and found only in the setting of inflammatory bowel disease and neuronal intestinal dysplasia. The aim of this study was to firmly establish the incidence of intramucosal ganglion cells in diverticular disease, normal mucosa and in a spectrum of gastrointestinal diseases.\n", "We retrospectively reviewed 50 resection specimens from cases of symptomatic diverticular disease and biopsies and/or resection specimens for several neoplastic and non-neoplastic gastrointestinal diseases (50 normal and 120 cases for a variety of gastrointestinal diseases). Normal cases were constituted by biopsies with no clinical history of large bowel disease and no pathology detected microscopically.\n", "All 50 cases of diverticular disease contained intramucosal ganglion cells, located within the muscularis mucosae (49/50 cases) as well as within the lamina propria in nine cases. Intramucosal ganglion cells occurred throughout the colorectum within the muscularis mucosae or lamina propria in normal mucosa in 11 cases and in a further 26 colorectal specimens with Crohn's disease (11/20), ulcerative colitis (11/20), adenocarcinoma (1/20), tubular adenoma (2/20), and mucosal prolapse (1/20). None of the 20 hyperplastic polyps contained intramucosal ganglion cells.\n", "\n", "Question: Are intramucosal ganglion cells common in diverticular disease?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, intramucosal ganglion cells are common in diverticular disease, as all 50 cases reviewed contained them.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The chemokines and cytokines CXCL13, CXCL12, CCL19, CCL21, BAFF and APRIL are believed to play a role in the recruitment of B cells to the central nervous system (CNS) compartment during neuroinflammation. To determine which chemokines/cytokines show the strongest association with a humoral immune response in the cerebrospinal fluid (CSF), we measured their concentrations in the CSF and correlated them with immune cell subsets and antibody levels.\n", "Cytokine/chemokine concentrations were measured in CSF and serum by ELISA in patients with non-inflammatory neurological diseases (NIND, n = 20), clinically isolated syndrome (CIS, n = 30), multiple sclerosis (MS, n = 20), Lyme neuroborreliosis (LNB, n = 8) and patients with other inflammatory neurological diseases (OIND, n = 30). Albumin, IgG, IgA and IgM were measured by nephelometry. CSF immune cell subsets were determined by seven-color flow cytometry.\n", "CXCL13 was significantly elevated in the CSF of all patient groups with inflammatory diseases. BAFF levels were significantly increased in patients with LNB and OIND. CXCL12 was significantly elevated in patients with LNB. B cells and plasmablasts were significantly elevated in the CSF of all patients with inflammatory diseases. CXCL13 showed the most consistent correlation with CSF B cells, plasmablasts and intrathecal Ig synthesis.\n", "\n", "Question: Is cXCL13 the major determinant for B cell recruitment to the CSF during neuroinflammation?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, CXCL13 is the major determinant for B cell recruitment to the CSF during neuroinflammation, as it showed the most consistent correlation with CSF B cells, plasmablasts, and intrathecal Ig synthesis.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: This is a randomised controlled trial to examine whether intra-articular injection of tranexamic acid (TXA) decreases blood loss, as well as reducing leg swelling after total knee arthroplasty (TKA).\n", "We performed 100 TKA in osteoarthritis patients. At closure, a total of 2,000 mg/20 ml TXA was injected into the knee joint through a closed suction drain (TXA group). For the control group, the same volume of physiological saline was injected. The pre-operative condition of the patients, post-operative haemoglobin (Hb) levels, discharge volumes from drain, D-dimer and needs for transfusion were compared between these two groups. Furthermore, leg diameters (thigh, suprapatellar portion and calf girth) were measured pre- and post-operatively to investigate whether TXA has an influence on leg swelling after surgery.\n", "The results revealed that post-operative decrease in Hb level was significantly reduced in the TXA group. Furthermore, knee joint swelling after operation was significantly suppressed in the TXA group compared to the control group.\n", "\n", "Question: Reduces intra-articular injection of tranexamic acid only blood loss but also knee joint swelling after total knee arthroplasty?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, the intra-articular injection of tranexamic acid reduces both blood loss and knee joint swelling after total knee arthroplasty.\"\n", "Solutions: no\n", "Score: 0.0\n", "Error reason: Computation result is incorrect.Questions: Context: A technique to decrease visceral ischemic time during thoracoabdominal aneurysm (TAA) repair is reported.\n", "A 10 mm Dacron side-arm graft is attached to the aortic prosthesis and positioned immediately distal to the planned proximal thoracic aortic anastomosis. On completion of the anastomosis, a 16 to 22 Fr perfusion catheter is attached to the side-arm graft and inserted into the orifice of the celiac axis or superior mesenteric artery. The cross-clamp is then placed on the aortic graft distal to the mesenteric side-arm graft. Pulsatile arterial perfusion is thus established to the visceral circulation while intercostal anastomoses or reconstruction of celiac, superior mesenteric, and right renal arteries is performed. Visceral ischemic time and the rise in end-tidal Pco2 after reconstruction of the visceral vessels in patients with mesenteric shunting was compared with a control group matched for aneurysm extent and treated immediately before use of the mesenteric shunt technique.\n", "Between July and Oct, 1996, the technique was applied in 15 patients undergoing type I, II, or III TAA repair with a clamp and sew technique. The mean decrease in systolic arterial pressure was 12.5 +/- 8.5 mm Hg, with a concomitant rise in end-tidal Pco2 (mean, 6.9 +/- 5.8 mm Hg), after perfusion was established through the mesenteric shunt. Mean time to establishment of visceral perfusion through the shunt was 25.5 +/- 4.4 minutes; the resultant decrement in visceral ischemic time averaged 31.3 minutes (i.e., until celiac, superior mesenteric, and right renal arteries were reconstructed). Compared with controls, patients with shunts had a significantly decreased (6.9 +/- 5.8 versus 21.6 +/- 8.4 mm Hg; p = 0.0003) rise in end-tidal CO2 on completion of visceral vessel reconstruction.\n", "\n", "Question: Does mesenteric shunting decrease visceral ischemia during thoracoabdominal aneurysm repair?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Endothelial cells (ECs) play an essential role in pancreatic organogenesis. We hypothesise that effective in vitro interactions between human microvascular endothelial cells (HMECs) and human pluripotent stem cells (hPSCs) results in the generation of functional pancreatic beta cells.\n", "Embryoid bodies (EBs) derived from hPSCs were cultured alone (controls) or with ECs in collagen gels. Subsequently, cells were analysed for pancreatic beta cell markers, and then isolated and expanded. Insulin secretion in response to glucose was evaluated in vitro by static and dynamic (perifusion) assays, and in vivo by EB transplantation into immunodeficient mice.\n", "Co-cultured EBs had a higher expression of mature beta cells markers and enhanced insulin secretion in vitro, compared with controls. In mice, transplanted EBs had higher levels of human C-peptide secretion with a significant reduction in hyperglycaemia after the selective destruction of native pancreatic beta cells. In addition, there was significant in vitro upregulation of bone morphogenetic proteins 2 and 4 (BMP-2, 4) in co-cultured cells, compared with controls.\n", "\n", "Question: Do effective endothelial cell and human pluripotent stem cell interactions generate functional insulin-producing beta cells?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, effective endothelial cell and human pluripotent stem cell interactions generate functional insulin-producing beta cells.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Serotonin is believed as an important factor in brain function. The role of serotonin in cerebral psycho-patho-physiology has already been well established. However, the function of serotonin antagonist in anesthetized subjects under hyperthermia has not been studied properly.\n", "Experiments were performed in three groups of urethane-anesthetized rats, such as: (i) control group, (ii) whole body hyperthermia group and (iii) p-CPA (para-Chlorophenylalanine) pretreated hyperthermia group. Hyperthermia was produced by subjecting the rats to high ambient temperature of 38 +/- 1 degrees C (relative humidity 45-50%). Each group was divided for EEG (electroencephalogram) study and for determination of edematous swelling in the brain.\n", "Urethane anesthetized rats under hyperthermia show highly significant reduction in their survival time. The body temperature recorded during the hyperthermia was observed with significant and linear rise with marked increase in brain water content, which was analyzed just after the death of the subjects. The results of the electroencephalographic study in urethane-anesthetized rats recorded before death indicate that brain function varies in systematic manner during hyperthermia as sequential changes in EEG patterns were observed. However, a serotonin antagonist, p-CPA pretreatment increases the survival time with significant reduction in edematous swelling in brain but it does not affect the relationship between the core body temperature and the brain cortical potentials as observed in urethane anesthetized subjects exposed to whole body hyperthermia. The core body temperature in p-CPA pretreated rats show non-linear relationship with respect to the exposure time as it was observed in drug untreated subjects.\n", "\n", "Question: Does depletion of serotonin synthesis with p-CPA pretreatment alter EEG in urethane anesthetized rats under whole body hyperthermia?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "No, the serotonin antagonist p-CPA pretreatment does not affect the relationship between the core body temperature and the brain cortical potentials in urethane anesthetized subjects exposed to whole body hyperthermia.\n", "Solutions: yes\n", "Score: 0.0\n", "Error reason: Computation result is incorrect.Questions: Context: Postoperative atrial fibrillation remains a significant source of morbidity after coronary artery bypass grafting. We reviewed the data on 2,569 patients to determine if the absence of cardiopulmonary bypass resulted in a lower incidence of atrial fibrillation.\n", "All patients undergoing coronary artery bypass grafting without cardiopulmonary bypass from January 1, 1997 through June 30, 2001 were evaluated for postoperative atrial fibrillation. The data of 252 patients with no cardiopulmonary bypass (group 1) were reviewed and compared with three other patient groups. Group 2 consisted of 1,470 patients using cardiopulmonary bypass during the same study period. Group 3 consisted of 841 patients with a similar number of grafts as the study group but using cardiopulmonary bypass. Group 4 consisted of historical data for 847 patients operated on using cardiopulmonary bypass collected from January 1995 through December 1996. Prophylactic beta-blockade was instituted in January 1997. Groups 1 to 3 received this treatment, but group 4 did not.\n", "Group 1 had an incidence of atrial fibrillation of 8.8%. Groups 2, 3, and 4 had incidences of atrial fibrillation of 11.6%, 9.4%, and 28.0%, respectively. When compared with group 1, the incidence of atrial fibrillation in group 4 was statistically different (p <. 0001).\n", "\n", "Question: Does off-pump coronary artery bypass grafting decrease the incidence of atrial fibrillation?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, off-pump coronary artery bypass grafting decreases the incidence of atrial fibrillation compared to on-pump procedures, as indicated by the lower incidence of 8.8% in group 1 compared to higher rates in groups 2, 3, and 4.\"\n", "Solutions: no\n", "Score: 0.0\n", "Error reason: Computation result is incorrect.Questions: Context: A substantial number of people living with HIV (PLWH) are co-infected with Hepatitis C Virus (HCV) but have a negative screening HCV antibody test (seronegative HCV infection, or SN-HCV).\n", "To identify a concise set of clinical variables that could be used to improve case finding for SN-HCV co-infection among PLWH.\n", "Two hundred HIV-infected participants of the CHARTER study were selected based on 7 clinical variables associated with HCV infection but were HCV seronegative. Data were analyzed using Fisher's exact tests, receiver-operating characteristic (ROC) curves, and logistic regression.\n", "Twenty-six (13%) participants had detectable HCV RNA. SN-HCV was associated with a history of IDU, elevated ALT and AST, low platelets, black ethnicity, and undetectable HIV RNA in plasma. Each of these clinical variables, except for abnormal AST, remained independently associated with SN-HCV in a multivariate logistic regression analysis. A composite risk score correctly identified SN-HCV with sensitivity up to 85% and specificity up to 88%.\n", "\n", "Question: Do clinical variables identify seronegative HCV co-infection in HIV-infected individuals?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, clinical variables can identify seronegative HCV co-infection in HIV-infected individuals.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To determine if an inverse association exits between latitude, ultraviolet B (UVB) irradiance and incidence rates of pancreatic cancer worldwide.\n", "Multiple linear regression was used to investigate the relationship and between UVB irradiance incidence rates of pancreatic cancer and while controlling for cigarette, alcohol and sugar consumption, and proportion overweight. Serum 25-hydroxyvitamin D [25(OH)D] levels were estimated, and their association with incidence rates also was analyzed.\n", "Incidence rates were higher at higher latitudes (R2 for latitude for men, 0.51; P < 0.001; R2 for latitude for women, 0.32; P < 0.001). Ultraviolet B irradiance also was independently inversely associated with incidence in men (P < 0.01) and women (P = 0.02). Alcohol (P < 0.0001) and cigarette (P < or = 0.01) consumption were positively associated with incidence in men (R2 for overall model for men, 0.76; P < 0.0001). Alcohol (P < 0.0001) and sugar (P = 0.001) consumption were positively associated with incidence rates in women (R2 for overall model for women, 0.64; P < 0.0001). Incidence rates were half as high in countries with estimated serum 25(OH)D >30 ng/mL (75 nmol/L) than in those with < or =30 ng/mL.\n", "\n", "Question: Are ultraviolet B irradiance and vitamin D status inversely associated with incidence rates of pancreatic cancer worldwide?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, ultraviolet B irradiance and vitamin D status are inversely associated with incidence rates of pancreatic cancer worldwide.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Lethal injuries can be surgically repaired under asanguineous hypothermic condition (suspended animation) with excellent outcome. However, the optimal rate for the induction of hypothermic metabolic arrest following uncontrolled lethal hemorrhage (ULH) is unknown.\n", "ULH was induced in 32 female swine (80-120 lbs) by creating an iliac artery and vein injury, followed 30 minutes later by laceration of the descending thoracic aorta. Through a left thoracotomy approach, total body hypothermic hyperkalemic metabolic arrest was induced by infusing organ preservation fluids into the aorta. Experimental groups were: normothermic controls (no cooling, NC), or hypothermia induced at a rate of 0.5 degrees C/min (slow, SC), 1 degrees C/min (medium, MC), or 2 degrees C/min (fast, FC). Vascular injuries were repaired during the 60 minutes of profound (10 degrees C) hypothermic arrest. Hyperkalemia was reversed by hypokalemic fluid exchange, and blood was infused for resuscitation during the re-warming (0.5 degrees C/ minute) period. The survivors were monitored for 6 weeks.\n", "The 6 week survival rates were 0% (NC), 37.5% (SC), 62.5% (MC), and 87.5% (FC) respectively (p < 0.05 MC&FC versus NC). All of the surviving hypothermic arrest animals were neurologically intact and displayed no long term organ dysfunction.\n", "\n", "Question: Does the rate of induction of hypothermic arrest determine the outcome in a Swine model of lethal hemorrhage?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, the rate of induction of hypothermic arrest determines the outcome in a Swine model of lethal hemorrhage, as indicated by the varying survival rates among the different experimental groups.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Prostaglandins (PGs) produced within ovarian follicles in response to the ovulatory gonadotropin surge are essential for follicle rupture and oocyte release. Arachidonic acid, the common precursor for PG synthesis, is cleaved from membrane phospholipids via the activity of phospholipase A2 (PLA2).\n", "The purpose of this study was to determine which PLA2 form(s) is involved in PG production by primate periovulatory follicles.\n", "Gonadotropins were administered to cynomolgus monkeys to stimulate multiple follicular development; human chorionic gonadotropin (hCG) initiated periovulatory events. Granulosa cells and whole ovaries were obtained before (0 h), and 12, 24, and 36 h after hCG administration.\n", "Granulosa-lutein cells were also obtained from women undergoing infertility treatment.\n", "mRNA for cytosolic (c)PLA2 and secretory (s)PLA2V, but not sPLA2IIA, was expressed by granulosa cells. cPLA2 mRNA levels were low at 0 h, elevated by 12 h, and remained high 24-36 h after hCG administration. sPLA2V mRNA levels were low at 0 h and did not change in response to hCG. cPLA2 and sPLA2V were detected by immunocytochemistry in granulosa cells of periovulatory follicles before and at all times after hCG administration. PLA2 activity was low in lysates of granulosa cells obtained 0-24 h after hCG and was elevated in granulosa cells obtained 36 h after hCG administration. A cPLA2-selective inhibitor decreased both PLA2 activity in monkey granulosa cell lysates and PGE2 accumulation in cultures of human granulosa-lutein cells.\n", "\n", "Question: Does an ovulatory gonadotropin stimulus increase cytosolic phospholipase A2 expression and activity in granulosa cells of primate periovulatory follicles?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, an ovulatory gonadotropin stimulus increases cytosolic phospholipase A2 expression and activity in granulosa cells of primate periovulatory follicles.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: One of the main limitations of peritoneal dialysis (PD) is deterioration of functional and morphological characteristics of the peritoneum. This complication appears to be related to the low biocompatibility profile of PD fluids. Recently, induction of the heat shock protein (HSP) stress response was demonstrated in cultured human mesothelial cells exposed to PD fluid in vitro. We investigated whether expression of heat shock protein 72 (HSP-72) in peritoneal macrophages is induced upon exposure to PD fluid during continuous ambulatory PD.\n", "Peritoneal leukocytes were isolated from 4-hour dwell dialysate; peripheral blood mononuclear cells (PBMC) and peripheral blood monocytes isolated from the same patients were used as a control. In separate experiments, PBMC from healthy individuals were exposed in vitro to different PD fluids or to culture media. Expression of HSP-72 was assessed by Western immunoblotting, flow cytometry, and reverse-transcription polymerase chain reaction analysis.\n", "Macrophages and leukocytes isolated from dialysis effluent expressed significantly increased HSP-72 and mRNA levels compared to blood monocytes and PBMC of the same patients. In vitro exposure of PBMC to fresh PD fluids resulted in significantly higher expression of HSP-72 compared to those incubated in culture medium. PBMC exposed in vitro to standard lactate-buffered dialysis fluids also expressed significantly more HSP-72 compared to cells exposed to bicarbonate/lactate-buffered fluids.\n", "\n", "Question: Is expression of heat shock protein 72 in peritoneal leukocytes induced by peritoneal dialysis?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, expression of heat shock protein 72 in peritoneal leukocytes is induced by peritoneal dialysis.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Plasma acyl and des-acyl ghrelin are thought of as components of total ghrelin, but this has never been validated using ex vivo spiking experiments, human sample collection comparisons and fit-for-purpose translatable assays.\n", "Acyl ghrelin plasma stability was analyzed by LC-MS/MS and it revealed that acyl ghrelin is enzymatically and chemically converted to des-acyl ghrelin in the presence of active serine proteases and HCl. ELISAs with less than 30% total error were used to assess acyl ghrelin behavior in matched authentic human samples. Acyl and total ghrelin were not statistically different in 4-(2-aminoethyl)benzenesulfonyl fluoride hydrochloride samples and acyl ghrelin losses in K(2)EDTA plasma were accounted for in des-acyl ghrelin formation.\n", "\n", "Question: Does prandial ghrelin attenuation provide evidence that des-acyl ghrelin may be an artifact of sample handling in human plasma?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, prandial ghrelin attenuation suggests that des-acyl ghrelin may be an artifact of sample handling in human plasma, as the conversion of acyl ghrelin to des-acyl ghrelin can occur due to enzymatic and chemical processes during sample processing.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To evaluate whether tumor invasion depth can be a reliable and easily applicable pathologic assessment strategy to predict outcomes using surgically resected cervical squamous cell carcinoma specimens from patients who have received neoadjuvant radiotherapy (RT) or concurrent chemoradiotherapy (CCRT).\n", "We included 173 patients with cervical squamous cell carcinoma who received neoadjuvant CCRT (n = 125) or RT (n = 48) and underwent subsequent radical hysterectomy. Data for the pre-operative clinical International Federation of Gynecology and Obstetrics (FIGO) stage, post-operative pathologic FIGO stage, World Health Organization (WHO) double diameter measurement evaluation, response evaluation criteria in solid tumors (RECIST 1.1) criteria, tumor necrosis rate (TNR), and tumor regression grade (TRG) were investigated to identify correlations with outcomes related to distant metastasis and survival. The tumor invasion depth (TID) and the tumor invasion depth with cytokeratin immunostaining correction (TIDC) at the cervical internal surface were measured to assess their relations to patients' outcomes.\n", "Based on measurements taken via transvaginal ultrasound, the pre-operative clinical and post-operative pathologic FIGO staging as well as the WHO double diameter measurement evaluation and RECIST 1.1 criteria were predictive of distant metastasis and survival-related outcomes. Also, lymph node involvement was found to be an independent prognostic factor for recurrence and distant metastasis. Finally, univariate analysis showed both the TID and TIDC were highly related to distant metastasis, overall survival, and progression-free survival, irrespective of the clinical stage of carcinomas.\n", "\n", "Question: Is tumor invasion depth a useful pathologic assessment for predicting outcomes in cervical squamous cell carcinoma after neoadjuvant radiotherapy?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, tumor invasion depth is a useful pathologic assessment for predicting outcomes in cervical squamous cell carcinoma after neoadjuvant radiotherapy.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Increased lipid supply causes beta cell death, which may contribute to reduced beta cell mass in type 2 diabetes. We investigated whether endoplasmic reticulum (ER) stress is necessary for lipid-induced apoptosis in beta cells and also whether ER stress is present in islets of an animal model of diabetes and of humans with type 2 diabetes.\n", "Expression of genes involved in ER stress was evaluated in insulin-secreting MIN6 cells exposed to elevated lipids, in islets isolated from db/db mice and in pancreas sections of humans with type 2 diabetes. Overproduction of the ER chaperone heat shock 70 kDa protein 5 (HSPA5, previously known as immunoglobulin heavy chain binding protein [BIP]) was performed to assess whether attenuation of ER stress affected lipid-induced apoptosis.\n", "We demonstrated that the pro-apoptotic fatty acid palmitate triggers a comprehensive ER stress response in MIN6 cells, which was virtually absent using non-apoptotic fatty acid oleate. Time-dependent increases in mRNA levels for activating transcription factor 4 (Atf4), DNA-damage inducible transcript 3 (Ddit3, previously known as C/EBP homologous protein [Chop]) and DnaJ homologue (HSP40) C3 (Dnajc3, previously known as p58) correlated with increased apoptosis in palmitate- but not in oleate-treated MIN6 cells. Attenuation of ER stress by overproduction of HSPA5 in MIN6 cells significantly protected against lipid-induced apoptosis. In islets of db/db mice, a variety of marker genes of ER stress were also upregulated. Increased processing (activation) of X-box binding protein 1 (Xbp1) mRNA was also observed, confirming the existence of ER stress. Finally, we observed increased islet protein production of HSPA5, DDIT3, DNAJC3 and BCL2-associated X protein in human pancreas sections of type 2 diabetes subjects.\n", "\n", "Question: Does endoplasmic reticulum stress contribute to beta cell apoptosis in type 2 diabetes?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, endoplasmic reticulum stress contributes to beta cell apoptosis in type 2 diabetes.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Local bone yielding at the pin-bone interface of external fixation half-pins has been known to initiate fixator loosening. Deterioration of bone properties due to ageing and disease can lead to an increase in the risk of pin loosening. This study determines the extent, locations and mechanics of bone yielding for unilateral external fixation systems at the tibial midshaft with changes in age-related bone structure and properties. The study also evaluates the effect of the number of pins used in the fixation system and use of titanium pins (in place of steel) on bone yielding.\n", "We employ nonlinear finite element (FE) simulations. Strain-based plasticity is used to simulate bone yielding within FE analyses. Our analyses also incorporate contact behaviour at pin-bone interfaces, orthotropic elasticity and periosteal-endosteal variation of bone properties.\n", "The results show that peri-implant yielded bone volume increases by three times from young to old-aged cases. The use of three, rather than two half-pins (on either side of the fracture), reduces the volume of yielded bone by 80% in all age groups. The use of titanium half-pins resulted in approximately 60-65% greater volumes of yielded bone.\n", "\n", "Question: Do bone properties affect loosening of half-pin external fixators at the pin-bone interface?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, bone properties affect loosening of half-pin external fixators at the pin-bone interface.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The prostate specific membrane antigen (PSMA) represents an attractive antigen for antibody-based diagnostic and therapeutic intervention in prostate cancer, since it is highly restricted to the prostate and overexpressed in all tumor stages. The present work describes the in vitro characterization of the three anti-PSMA monoclonal antibodies (mAbs) 3/A12, 3/E7, and 3/F11 in comparison to the mAb J591.\n", "The mAbs were tested for saturation and competitive binding on C4-2 prostate cancer cells by flow cytometry. Immunohistochemical staining was conducted on frozen prostate normal and cancer tissues as well as on lymph node metastases. Similarly, potential crossreactivities were tested on a broad panel of human normal tissues.\n", "The anti-PSMA mAbs showed a strong binding to C4-2 cells with mean half-maximal saturation concentrations of about 14 nM for 3/A12, 17 nM for 3/E7, 9 nM for 3/F11, and 16 nM for J591. Competitive binding studies revealed that our three mAbs bind to different extracellular PSMA epitopes. The mAbs showed comparable staining of epithelial cells for all tested normal and tumorous prostate tissues. Extraprostatic staining was observed on secretory cells of the salivary glands and on the brush border of the duodenal columnar epithelium. J591 additionally showed positive staining of the normal breast epithelium.\n", "\n", "Question: Are three conformational antibodies specific for different PSMA epitopes promising diagnostic and therapeutic tools for prostate cancer?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, the three conformational antibodies specific for different PSMA epitopes are promising diagnostic and therapeutic tools for prostate cancer.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The objective of this study was to determine if adding spironolactone to an angiotensin II receptor blocker improves left ventricular (LV) function, mass, and volumes in chronic heart failure.\n", "Add-on spironolactone therapy substantially improves clinical outcomes among patients with severe heart failure (HF) on standard therapy. However, the value of combining spironolactone with an angiotensin II receptor blocker on LV reverse remodeling in mild-to-moderate systolic HF is unclear.\n", "Fifty-one systolic HF patients with left ventricular ejection fraction (LVEF) <40% were randomly assigned to receive 1-year treatment of candesartan and spironolactone (combination group) or candesartan and placebo (control group). Reverse remodeling was assessed by serial cardiac magnetic resonance imaging and echocardiographic tissue Doppler imaging (TDI).\n", "There were significant improvements in LVEF (35 +/- 3% vs. 26 +/- 2%, p < 0.01) and reduction of LV end-diastolic volume index (121 +/- 16 ml/m2 vs. 155 +/- 14 ml/m2, p = 0.001), end-systolic volume index (88 +/- 17 ml/m2 vs. 120 +/- 15 ml/m2, p < 0.0005), and LV mass index (81 +/- 6 g/m2 vs. 93 +/- 6 g/m2, p = 0.002) in the combination group at 1 year. In addition, there was significant increase in peak basal systolic velocity and strain by TDI, decrease in index of filling pressure, and increase in cyclic variation integrated backscatter. In the control group, there were no significant changes in all these parameters after 1 year.\n", "\n", "Question: Does aldosterone receptor antagonism induce reverse remodeling when added to angiotensin receptor blockade in chronic heart failure?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, aldosterone receptor antagonism induces reverse remodeling when added to angiotensin receptor blockade in chronic heart failure, as indicated by the significant improvements in left ventricular function and structure in the combination group compared to the control group.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Polo-like kinase 1 (PLK1) plays an important role in mitotic progression, is frequently overexpressed and associated with a poor prognosis of cancer patients, thus providing a promising target in anticancer treatment. Aim of the current project was to evaluate the effect of the novel PLK1 inhibitor BI 6727 in combination with irradiation.\n", "In vitro proliferation and radiation cell survival assays as well as in vivo local tumour control assays after single treatment and combined radiation and drug application were carried out using the squamous cell carcinoma models A431 and FaDu. In addition, cell cycle phases were monitored in vitro and in vivo.\n", "BI 6727 showed a dose-dependent antiproliferative effect and an increase in the mitotic fraction. BI 6727 alone reduced clonogenic cell survival, while radiosensitivity in vitro (SF2) and in vivo (single-dose TCD(50) under clamped hypoxia) was not affected. In contrast, local tumour control was significantly improved after application of BI 6727 simultaneously to fractionated irradiation (A431: TCD(50) = 60.5 Gy [95% C.I. 57; 63] after IR alone and <30 Gy after combined treatment; FaDu: 49.5 Gy [43; 56 Gy] versus 32.9 Gy [26; 40]).\n", "\n", "Question: Does simultaneous PLK1 inhibition improve local tumour control after fractionated irradiation?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, simultaneous PLK1 inhibition improves local tumour control after fractionated irradiation.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Besides being responsible for energy production in the cell, mitochondria are central players in apoptosis as well as the main source of harmful reactive oxygen species. Therefore, it can be hypothesised that sequence variation in the mitochondrial genome is a contributing factor to the etiology of diseases related to these different cellular events, including cancer. The aim of the present study was to assess the frequency of haplogroups and polymorphisms in the control region (CR) of mitochondrial DNA of peripheral blood mononuclear cells from patients with prostate carcinoma (n = 304) versus patients screened for prostate disease but found to be negative for cancer on biopsy (n = 278) in a Middle European population.\n", "The nine major European haplogroups and the CR polymorphisms were identified by means of primer extension analysis and DNA sequencing, respectively. We found that mitochondrial haplogroup frequencies and CR polymorphisms do not differ significantly between patients with or without prostate cancer, implying no impact of inherited mitochondrial DNA variation on predisposition to prostate carcinoma in a Middle European population.\n", "\n", "Question: Are mitochondrial haplogroups and control region polymorphisms associated with prostate cancer in Middle European Caucasians?\n", "\n", "Answer:\n", "Predictions: No, mitochondrial haplogroups and control region polymorphisms are not associated with prostate cancer in Middle European Caucasians.\n", "Solutions: no\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Essential for mitotic growth 1 (EMG1) is a highly conserved nucleolar protein identified in yeast to have a critical function in ribosome biogenesis. A mutation in the human EMG1 homolog causes Bowen-Conradi syndrome (BCS), a developmental disorder characterized by severe growth failure and psychomotor retardation leading to death in early childhood. To begin to understand the role of EMG1 in mammalian development, and how its deficiency could lead to Bowen-Conradi syndrome, we have used mouse as a model. The expression of Emg1 during mouse development was examined and mice carrying a null mutation for Emg1 were generated and characterized.\n", "Our studies indicated that Emg1 is broadly expressed during early mouse embryonic development. However, in late embryonic stages and during postnatal development, Emg1 exhibited specific expression patterns. To assess a developmental role for EMG1 in vivo, we exploited a mouse gene-targeting approach. Loss of EMG1 function in mice arrested embryonic development prior to the blastocyst stage. The arrested Emg1-/- embryos exhibited defects in early cell lineage-specification as well as in nucleologenesis. Further, loss of p53, which has been shown to rescue some phenotypes resulting from defects in ribosome biogenesis, failed to rescue the Emg1-/- pre-implantation lethality.\n", "\n", "Question: Is eMG1 essential for mouse pre-implantation embryo development?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, EMG1 is essential for mouse pre-implantation embryo development as the loss of EMG1 function leads to arrested embryonic development prior to the blastocyst stage.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Acute rejection (AR) remains the primary risk factor for renal transplant outcome; development of non-invasive diagnostic biomarkers for AR is an unmet need.\n", "We used shotgun proteomics applying LC-MS/MS and ELISA to analyze a set of 92 urine samples, from patients with AR, stable grafts (STA), proteinuria (NS), and healthy controls.\n", "A total of 1446 urinary proteins (UP) were identified along with a number of nonspecific proteinuria-specific, renal transplantation specific and AR-specific proteins. Relative abundance of identified UP was measured by protein-level spectral counts adopting a weighted fold-change statistic, assigning increased weight for more frequently observed proteins. We have identified alterations in a number of specific UP in AR, primarily relating to MHC antigens, the complement cascade and extra-cellular matrix proteins. A subset of proteins (uromodulin, SERPINF1 and CD44), have been further cross-validated by ELISA in an independent set of urine samples, for significant differences in the abundance of these UP in AR.\n", "\n", "Question: Does shotgun proteomics identify proteins specific for acute renal transplant rejection?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, shotgun proteomics identifies proteins specific for acute renal transplant rejection.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To describe the long-term outcome of eyes with uveitis after repeated treatment with dexamethasone implants (Ozurdex; Allergan, Inc., Irvine, CA).\n", "Retrospective, observational case series.\n", "Thirty-eight eyes of 27 patients with uveitis that were treated with 61 dexamethasone implants.\n", "All eyes underwent dexamethasone pellet implantation. Anatomic and functional outcomes, as well as ocular complications, were noted.\n", "Best-corrected visual acuity (BCVA), central retinal thickness (CRT), vitreous haze score, and presence of increased intraocular pressure or cataract.\n", "Average follow-up was 17.3 ± 1.8 months after the first implant (median, 13.3 months; range, 3-54.5 months; 54.65 eye-years), with 14 eyes (36.9%) receiving a single implant and 24 eyes (63.1%) receiving multiple implantations. After the first implantation, average BCVA improved significantly from 0.47 ± 0.05 logarithm of the minimum angle of resolution (logMAR) units (Snellen equivalent, 20/60) to 0.27 ± 0.07 logMAR (Snellen equivalent, 20/37; P<0.001); CRT decreased by 263 ± 44.22 μm (P = 0.003), although macular edema persisted in 50% of eyes, and the percentage of eyes achieving a vitreous haze score of 0 increased from 58% to 83% (P = 0.03). The median duration of therapeutic effect after the first injection was 6 months (range, 2-42 months), with a similar response achieved after each repeat implantation. The accumulated effect of repeat dexamethasone implants resulted in a continued improvement in BCVA (R(2) = 0.91; P<0.0001), with significant improvement and stabilization of CRT. After repeated implantations, 2 eyes had progression of posterior subcapsular opacities, although neither required surgery. There were 7 instances of increased intraocular pressure of more than 21 mmHg at a rate of 0.13 per eye-year, all of which responded to pharmacologic treatment.\n", "\n", "Question: Does treatment with repeat dexamethasone implants result in long-term disease control in eyes with noninfectious uveitis?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, treatment with repeat dexamethasone implants results in long-term disease control in eyes with noninfectious uveitis, as indicated by significant improvement in best-corrected visual acuity and stabilization of central retinal thickness over time.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To identify serologic markers of salivary gland disease activity in 43 patients with primary Sjögren's syndrome.\n", "Comparison of salivary gland biopsies (focus scores) and flow rates with serum concentrations of IgA and IgM rheumatoid factor (RF), total serum IgG, serum anti-SS-B/La antibodies, and the erythrocyte sedimentation rate.\n", "Serum anti-SS-B/La antibody levels correlated with focus scores (rs = 0.477, P < 0.0025). Serum IgA-RF concentrations correlated inversely with stimulated parotid gland salivary flow rates (rs = -0.394, P < 0.01).\n", "\n", "Question: Are serum anti-SS-B/La and IgA rheumatoid factor markers of salivary gland disease activity in primary Sjögren 's syndrome?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "Yes, serum anti-SS-B/La and IgA rheumatoid factor are markers of salivary gland disease activity in primary Sjögren's syndrome.\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: This study assessed the impact of a pre-medical pipeline program on successful completion of medical school and the capacity of this program to address achievement gaps experienced by disadvantaged students. The University of North Carolina (USA) Medical Education Development (MED) program provides intensive academic and test skills preparation for admission to medical, dental, and other allied health professions schools.\n", "This retrospective study evaluated the academic progress of a longitudinal sample of 1738 disadvantaged college students who completed MED between 1974 and 2001. Data sources included MED participant data, medical school admissions data for the host school, aggregate data from the Association of American Medical Colleges (AAMC), and individual MED participant data from AAMC. Methods of analysis utilized Chi-square, independent samples t test, and logistic regression to examine associations between factors.\n", "Of the 935 students in MED from 1974 to 2001, who had indicated an interest in medical school, 887 (94.9%) successfully matriculated and 801 (85.7%) successfully earned the MD degree. Using logistic regression, factors that were significantly correlated with earning the medical degree included the student's race, college undergraduate total and science grade point averages, with Hispanic, African American, and Native American participants earning the medical degree at rates comparable to Caucasian participants. MED students successfully earned the MD degree despite having significantly lower Medical College Admissions Test (MCAT) scores and undergraduate grade point averages compared to all United States medical school applicants: MCAT scores had little relationship with student's success.\n", "\n", "Question: Does a social and academic enrichment program promote medical school matriculation and graduation for disadvantaged students?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, a social and academic enrichment program promotes medical school matriculation and graduation for disadvantaged students, as evidenced by the high rates of matriculation and graduation among participants in the MED program.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The mechanisms underlying the initiation of sustained ventricular tachycardia (VT) have not been fully elucidated. The extent to which reentry, abnormal automaticity, and triggered activity play a role in VT differs depending on the etiology of left ventricular dysfunction. By analyzing electrograms from implantable cardioverter defibrillator (ICD), we sought to determine whether there were differences in VT initiation patterns between patients with ischemic and nonischemic cardiomyopathy.\n", "We analyzed ICD electrograms in patients with ejection fractions < 40% who had sustained VT over a 27-month period. The trigger for VT onset was classified as a ventricular premature beat (VPB), supraventricular tachycardia, or of \"sudden onset.\" The baseline cycle length, VT cycle length, coupling interval, and prematurity ratio were recorded for each event. The prematurity ratio was calculated as the coupling interval of the VT initiator divided by the baseline cycle length.\n", "Sixty-three VT events in 14 patients met the inclusion criteria. A VPB initiated the VT in 58 episodes (92%), 1 episode (2%) was initiated by a supraventricular tachycardia, and 4 episodes (6%) were sudden onset. The prematurity ratio was significantly higher (P < 0.05) in patients with ischemic cardiomyopathy (0.751 +/- 0.068) as compared to patients with nonischemic cardiomyopathy (0.604 +/- 0.139).\n", "\n", "Question: Do triggers of sustained monomorphic ventricular tachycardia differ among patients with varying etiologies of left ventricular dysfunction?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, triggers of sustained monomorphic ventricular tachycardia differ among patients with varying etiologies of left ventricular dysfunction.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To evaluate the association between electronic health record (EHR) satisfaction and job satisfaction in primary care physicians (PCPs).\n", "Cross-sectional survey of PCPs at 825 primary care practices in North Carolina.\n", "Surveys were returned from 283 individuals across 214 practices (26% response rate for practices), of whom 122 were physicians with EHRs and no missing information. We found that for each point increase in EHR satisfaction, job satisfaction increased by ∼0.36 points both in an unadjusted and an adjusted model (β 0.359 unadjusted, 0.361 adjusted; p < 0.001 for both models).\n", "\n", "Question: Is satisfaction with electronic health records associated with job satisfaction among primary care physicians?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, satisfaction with electronic health records is associated with job satisfaction among primary care physicians.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Extracellular matrix metalloproteinase inducer (EMMPRIN), an immunoglobulin-like cell surface glycoprotein, could promote collagenolytic balance in favor of the expression and activation of matrix metalloproteinases (MMPs). This study was to investigate the expression of EMMPRIN in gingival tissues from different periodontal conditions and to correlate it with the production of MMP-1 and MMP-2.\n", "Gingival biopsies were collected from 15 patients with untreated advanced chronic periodontitis and 15 patients with aggressive periodontitis (AgP). The control group consisted of 12 subjects diagnosed either as periodontally healthy individuals or as individuals with a gingival index of one (H/G1). The peptides and mRNA of EMMPRIN, MMP-1 and MMP-2 were detected by immunohistochemistry and semi-quantitative reverse transcriptase-polymerase chain reaction, respectively.\n", "The expression of EMMPRIN, MMP-1 and MMP-2 peptides in periodontally healthy tissues was mainly confined to the gingival epithelium. The EMMPRIN was strongly expressed in the cell membrane of the basal layer. Immunoreactivity for EMMPRIN was more intensive and more widespread in periodontitis, extended from the epithelial layers to the underlying connective tissues, and was essential in both inflammatory and fibroblast-like cells. In addition, MMP-1 and MMP-2 showed the same localized expression. The chronic periodontitis group had a significantly higher mRNA expression of EMMPRIN and MMP-2 compared with the H/G1 subjects (p < 0.05). Production of MMP-1 and MMP-2 by gingival tissues was correlated with the mRNA level of EMMPRIN (r = 0.463, p = 0.013 for MMP-1 and r = 0.404, p = 0.033 for MMP-2).\n", "\n", "Question: Is increased expression of extracellular matrix metalloproteinase inducer associated with matrix metalloproteinase-1 and -2 in gingival tissues from patients with periodontitis?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, increased expression of extracellular matrix metalloproteinase inducer is associated with matrix metalloproteinase-1 and -2 in gingival tissues from patients with periodontitis.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Comparison of preverbal communication behavior in young children before receiving cochlear implants with outcomes 3 yr after implantation on speech identification and speech production tasks, to assess whether outcomes can be predicted from characteristics inherent to the child before implantation.\n", "Video recordings of preverbal communicative behavior were examined before use of the implant to quantify turn-taking and demonstration of autonomy by the child. Speech identification ability was measured 3 yr after implantation based on the Iowa Closed-Set Speech Perception Sentence Test, continuous discourse tracking, and an observational measure of telephone use. Speech production ability was measured 3 yr after implantation by the Edinburgh Articulation Test. Associations between the preimplant measures and the 3-yr outcomes were assessed by correlation analysis of data from 33 children.\n", "The 3-yr performance measures of speech identification were correlated with the preimplant measure of autonomy. Telephone use and speech production ability were not significantly associated with the preimplant measures.\n", "\n", "Question: Do preimplant measures of preverbal communicative behavior as predictors of cochlear implant outcomes in children?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, preimplant measures of preverbal communicative behavior can serve as predictors of cochlear implant outcomes in children, particularly in relation to speech identification performance.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To determine the structure of T cell receptors (TCR) used by Sm-B-reactive human T cell clones, to map T cell epitopes on the Sm-B autoantigen, and to determine the HLA restriction element used in the recognition of Sm-B by T cells.\n", "Sm-B-reactive T cell clones were generated from patients with connective tissue disease by using either a recombinant fusion protein or synthetic peptides. The TCR structure was defined with the use of polymerase chain reaction and DNA sequencing. Synthetic peptides were used to map T cell epitopes on Sm-B. HLA restriction element usage was defined by using monoclonal antibody blocking.\n", "Usage of the TCR third complementarity-determining region (CDR3) was highly restricted among Sm-B autoantigen-specific human T cell clones. Only amino acids 48-96 of the Sm-B2 autoantigen were recognized by T cells, and this occurred in the context of HLA-DR.\n", "\n", "Question: Is t cell receptor beta-chain third complementarity-determining region gene usage highly restricted among Sm-B autoantigen-specific human T cell clones derived from patients with connective tissue disease?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, the T cell receptor beta-chain third complementarity-determining region gene usage is highly restricted among Sm-B autoantigen-specific human T cell clones derived from patients with connective tissue disease.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To assess the influence of inducible and endothelial nitric oxide synthase (iNOS and eNOS) polymorphisms in susceptibility to rheumatoid arthritis (RA).\n", "Two hundred RA patients fulfilling the 1987 American College of Rheumatology classification criteria followed at the out-patient rheumatology clinic of the Hospital Xeral-Calde (Lugo, Spain) and 251 ethnically matched controls were studied. Patients and controls were genotyped by PCR-based techniques for a multiallelic (CCTTT)(n) repeat in the promoter region of the iNOS gene and for a T/C polymorphism at position -786 in the promoter region and a polymorphism in exon 7 (298Glu/Asp or 5557G/T) of the eNOS gene.\n", "No significant difference in allele or genotype frequencies for either polymorphism in the eNOS gene was observed between RA patients and controls. The overall iNOS CCTTT(n) allelic or genotypic distribution did not show statistical significant differences between RA patients and controls. Interestingly, when we stratified the iNOS alleles into short (8-11) and long (12-16) repeats, significant differences were observed between RA patients and controls (P = 0.021; odds ratio = 1.37, 95% confidence interval 1.04-1.81). Of note, individuals carrying two alleles with a repeat number less than 12 (fewer than 196 base pairs) exhibited a double risk of developing RA (P = 0.005, odds ratio 2.26, 95% confidence interval 1.25-4.08).\n", "\n", "Question: Is inducible but not endothelial nitric oxide synthase polymorphism associated with susceptibility to rheumatoid arthritis in northwest Spain?\n", "\n", "Answer:\n", "Predictions: {\"draft_answer\": \"Yes, inducible nitric oxide synthase polymorphism is associated with susceptibility to rheumatoid arthritis in northwest Spain, while no significant association was found for endothelial nitric oxide synthase polymorphism.\"}\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: A beneficial effect of regional anesthesia on cancer related outcome in various solid tumors has been proposed. The data on prostate cancer is conflicting and reports on long-term cancer specific survival are lacking.\n", "In a retrospective, single-center study, outcomes of 148 consecutive patients with locally advanced prostate cancer pT3/4 who underwent retropubic radical prostatectomy (RRP) with general anesthesia combined with intra- and postoperative epidural analgesia (n=67) or with postoperative ketorolac-morphine analgesia (n=81) were reviewed. The median observation time was 14.00 years (range 10.87-17.75 yrs). Biochemical recurrence (BCR)-free, local and distant recurrence-free, cancer-specific, and overall survival were estimated using the Kaplan-Meier technique. Multivariate Cox proportional-hazards regression models were used to analyze clinicopathologic variables associated with disease progression and death.\n", "The survival estimates for BCR-free, local and distant recurrence-free, cancer-specific survival and overall survival did not differ between the two groups (P=0.64, P=0.75, P=0.18, P=0.32 and P=0.07). For both groups, higher preoperative PSA (hazard ratio (HR) 1.02, 95% confidence interval (CI) 1.01-1.02, P<0.0001), increased specimen Gleason score (HR 1.24, 95% CI 1.06-1.46, P=0.007) and positive nodal status (HR 1.66, 95% CI 1.03-2.67, P=0.04) were associated with higher risk of BCR. Increased specimen Gleason score predicted death from prostate cancer (HR 2.46, 95% CI 1.65-3.68, P<0.0001).\n", "\n", "Question: Does epidural analgesia during open radical prostatectomy improve long-term cancer-related outcome : a retrospective study in patients with advanced prostate cancer?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"No, the study found that survival estimates did not differ between the groups receiving epidural analgesia and those receiving ketorolac-morphine analgesia.\"\n", "Solutions: no\n", "Score: 1.0\n", "The solution is correct.Questions: Context: CD133 is one of the most important cancer-initiating (stem) cell markers and was confirmed to be expressed in solid cancers such as colon cancer. However, no one has investigated the role of CD133 in intrahepatic cholangiocarcinoma (IHCC). The aim of this study was to clarify the clinical role of CD133 expression in IHCC.\n", "Twenty-nine patients with IHCC who underwent hepatic resection at our institution were enrolled in this study. Expression of CD133 was examined using anti-CD133 antibody. Staining was observed in the cytoplasm of cancer cells and CD133-positive cells distributed in the whole tumor. The patients were divided into two groups: the CD133-positive group (n = 14) and CD133-negative group (n = 15), in which no staining of CD133 was observed. Clinicopathological factors including hypoxia-inducible factor-1alpha expression were compared between the two groups. The prognostic factors were investigated by multivariate analysis using Cox's proportional hazard model.\n", "The 5-year survival rate in the CD133-positive group (8.0%) was worse than that in the CD133-negative group (57.0%). In the CD133-positive group, the incidence of intrahepatic metastasis and positive expression of hypoxia-inducible factor-1alpha tended to be higher than that in the CD133 negative group. The multivariate analysis revealed CD133 expression was an independent prognostic indicator in IHCC.\n", "\n", "Question: Is cD133 expression a potential prognostic indicator in intrahepatic cholangiocarcinoma?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, CD133 expression is a potential prognostic indicator in intrahepatic cholangiocarcinoma.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Stable dry-state storage of DNA is desirable to minimize required storage space and to reduce electrical and shipping costs. DNA purified from various commercially available dry-state stabilization matrices has been used successfully in downstream molecular applications (e.g., quantitative polymerase chain reaction [qPCR], microarray, and sequence-based genotyping). However, standard DNA storage conditions still include freezing of DNA eluted in aqueous buffers or nuclease-free water. Broad implementation of dry-state, long-term DNA storage requires enhancement of such dry-state DNA stabilization products to control for temperature fluctuations at specimen collection, transit, and storage. This study tested the integrity of genomic DNA subjected to long-term storage on GenTegra(™) DNA stabilization matrices (GenTegra LLC, Pleasanton, CA) at extreme conditions, as defined by a 4-year storage period at ambient temperature with an initial incubation for 7 months at 37°C, 56°C, or ambient temperature. Subsequently, purified DNA performance and integrity were measured by qPCR and next-generation sequencing (NGS)-based human leokocyte antigen (HLA) genotyping.\n", "High molecular weight genomic DNA samples were recovered from the GenTegra product matrix and exhibited integrity comparable to a highly characterized commercial standard under assessment by qPCR. Samples were genotyped for classical HLA loci using next generation sequencing-based methodolgy on the Roche 454 GS Junior instrument. Amplification efficiency, sequence coverage, and sequence quality were all comparable with those produced from a cell line DNA sequenced as a control. No significant differences were observed in the mean, median, or mode quality scores between samples and controls (p≥0.4).\n", "\n", "Question: Does dNA storage under high temperature conditions affect performance in human leukocyte antigen genotyping via next-generation sequencing ( DNA integrity maintained in extreme conditions )?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"No, DNA storage under high temperature conditions does not affect performance in human leukocyte antigen genotyping via next-generation sequencing, as the integrity was maintained in extreme conditions.\"\n", "Solutions: no\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The role of the Ferric Uptake Regulator (FUR) in the acid resistance of Helicobacter pylori (H. pylori) has been thought to be independent of urease. However, we demonstrated in this study that Fur influences urease activity.\n", "A fur knockout mutant of H. pylori was constructed by replacing the Fur gene with a kanamycin resistant marker gene. The wild-type H. pylori and fur mutant were compared for survival. The integrity of the inner membrane of the bacteria was evaluated by confocal microscopy using membrane-permeant and -impermeant fluorescent DNA probes. Urease activity of intact H. pylori was measured between pH 3 and 8. Real time PCR of both strains was performed for urease genes including ureI, ureE, ureF, ureG, and ureH.\n", "The fur deletion affected the survival of H. pylori at pH 4. The urease activity curve of the intact fur mutant showed the same shape as the wild-type but was 3-fold lower than the wild-type at a pH of less than 5. Real time PCR revealed that the expression of all genes was consistently down-regulated in the fur mutant.\n", "\n", "Question: Is helicobacter pylori urease activity influenced by ferric uptake regulator?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "Yes, Helicobacter pylori urease activity is influenced by the ferric uptake regulator (FUR).\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Obese Alms1 mutant (foz/foz) NOD.B10 mice develop diabetes and fibrotic NASH when fed high-fat(HF) diet. To establish whether diabetes or obesity is more closely associated with NASH fibrosis, we compared diabetic foz/foz C57BL6/J with non-diabetic foz/foz BALB/c mice. We also determined hepatic cytokines, growth factors and related profibrotic pathways.\n", "Male and female foz/foz BALB/c and C57BL6/J mice were fed HF or chow for 24 weeks before determining metabolic indices, liver injury, cytokines, growth factors, pathology/fibrosis and matrix deposition pathways.\n", "All foz/foz mice were obese. Hepatomegaly, hyperinsulinemia, hyperglycaemia and hypoadiponectinaemia occurred only in foz/foz C57BL6/J mice, whereas foz/foz BALB/c formed more adipose. Serum ALT, steatosis, ballooning, liver inflammation and NAFLD activity score were worse in C57BL6/J mice. In HF-fed mice, fibrosis was severe in foz/foz C57BL6/J, appreciable in WT C57BL6/J, but absent in foz/foz BALB/c mice. Hepatic mRNA expression of TNF-α, IL-12, IL-4, IL-10 was increased (but not IFN-γ, IL-1β, IL-17A), and IL-4:IFN-γ ratio (indicating Th-2 predominance) was higher in HF-fed foz/foz C57BL6/J than BALB/c mice. In livers of HF-fed foz/foz C57BL6/J mice, TGF-β was unaltered but PDGFα and CTGF were increased in association with enhanced α-SMA, CD147and MMP activity.\n", "\n", "Question: Is strain dependence of diet-induced NASH and liver fibrosis in obese mice linked to diabetes and inflammatory phenotype?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, the strain dependence of diet-induced NASH and liver fibrosis in obese mice is linked to diabetes and the inflammatory phenotype, as indicated by the differences observed between the diabetic foz/foz C57BL6/J and non-diabetic foz/foz BALB/c mice in terms of metabolic indices and liver pathology.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: This study aimed at exploring the psychosocial and clinical correlates of substance use disorder in an adolescent inpatient psychiatric population.\n", "During the period from 2006-2007, all subjects were systematically screened for substance use disorder (SUD) and were assessed for SUD characteristics by an independent support team using the RECAP (Joint Report on Drug Addiction and Treatment). Each SUD case was matched for age, gender, unit, and admission week, so as to compare a consumer sample (cases) with a non-consumer sample (controls). We retrospectively extracted data (socio-demographic and clinical characteristics) from charts to realize a case-control comparison. To assess Axis II borderline psychopathology, the child retro-DIB (Diagnosis Interview for Borderline) was used.\n", "The sample included 30 cases and 30 controls between 14 and 17 years of age. SUD was significantly associated with maltreatment (p=0.038), loss of a first-degree relative (p=0.039), school absenteeism (p=0.035) and suicide attempts (p=0.02). Regarding psychopathology, significant co-occurrence was observed between SUD and conduct disorder (p=0.019), all personality disorders (p=0.003) and borderline personality disorder specifically (p=0.021).\n", "\n", "Question: Do psychosocial and Clinical Correlates of Substance use Disorder in an Adolescent Inpatient Psychiatric Population?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, the study explores psychosocial and clinical correlates of substance use disorder in an adolescent inpatient psychiatric population.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Earlier studies have shown a prolonged frequency-adjusted Q-T interval (QTc>0.440 s(1/2)) in a substantial fraction of patients with cirrhosis. The effect of beta-blockade on QTc is unknown, and its determination was the aim of the study.\n", "Seventeen patients with cirrhosis received 80 mg propranolol orally during a haemodynamic investigation with measurements at baseline and 90 min after propranolol ingestion.\n", "Beta-blockade reduced cardiac output (-21%, P<0.001), heart rate (-20%, P<0.001), and the hepatic venous pressure gradient (HVPG, -17%, P<0.02). The mean QTc=0.460 s(1/2) was prolonged compared to 0.410 s(1/2) in age-matched controls (P<0.01). Whereas QTc decreased during beta-blockade in the cirrhotic patients (from 0.460 to 0.440 s(1/2), P<0.01), no effect was found in the subgroup with normal QTc (0.429 vs. 0.422 s(1/2), ns), and a reduction was seen in the patients with prolonged QTc (from 0.488 to 0.456 s(1/2), P<0.01). The percentage decrease in QTc was related to the reduction in HVPG (r=0.48, P=0.03) and cardiac output (r=0.56, P=0.02).\n", "\n", "Question: Does acute non-selective beta-adrenergic blockade reduce prolonged frequency-adjusted Q-T interval ( QTc ) in patients with cirrhosis?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, acute non-selective beta-adrenergic blockade reduces prolonged frequency-adjusted Q-T interval (QTc) in patients with cirrhosis.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Bardet-Biedl syndrome (BBS) is a genetically heterogeneous disorder of the primary cilium associated with obesity. In BBS mouse models, ciliary dysfunction leads to impaired leptin signaling and hyperleptinemia before obesity onset. To study the pathophysiology of obesity in BBS, we compared patients with BBS and body mass index Z-score (BMI-Z)-matched controls.\n", "Fifty patients with BBS were matched 2:1 by age, sex, race, and BMI-Z with 100 controls. Patients with BBS and controls were compared for differences in body composition (dual-energy x-ray absorptiometry, abdominal magnetic resonance imaging), blood pressure Z-score (BP-Z; standardized for age, sex, and height), and fasting concentrations of leptin, lipids, insulin, and glucose. Patients with BBS were also compared by genotype.\n", "Leptin, triglycerides, intraabdominal fat mass, and diastolic BP-Z were significantly greater in patients with BBS than in the controls. BBS1 (27%) and BBS10 (30%) mutations were the most prevalent. Patients with BBS10 mutations had significantly higher BMI-Z, greater visceral adiposity, and greater insulin resistance than those with BBS1 mutations.\n", "\n", "Question: Do patients with Bardet-Biedl syndrome have hyperleptinemia suggestive of leptin resistance?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, patients with Bardet-Biedl syndrome have hyperleptinemia suggestive of leptin resistance.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Oral Squamous Cell Carcinoma (OSCC) is a major cause of cancer death worldwide, which is mainly due to recurrence leading to treatment failure and patient death. Histological status of surgical margins is a currently available assessment for recurrence risk in OSCC; however histological status does not predict recurrence, even in patients with histologically negative margins. Therefore, molecular analysis of histologically normal resection margins and the corresponding OSCC may aid in identifying a gene signature predictive of recurrence.\n", "We used a meta-analysis of 199 samples (OSCCs and normal oral tissues) from five public microarray datasets, in addition to our microarray analysis of 96 OSCCs and histologically normal margins from 24 patients, to train a gene signature for recurrence. Validation was performed by quantitative real-time PCR using 136 samples from an independent cohort of 30 patients.\n", "We identified 138 significantly over-expressed genes (> 2-fold, false discovery rate of 0.01) in OSCC. By penalized likelihood Cox regression, we identified a 4-gene signature with prognostic value for recurrence in our training set. This signature comprised the invasion-related genes MMP1, COL4A1, P4HA2, and THBS2. Over-expression of this 4-gene signature in histologically normal margins was associated with recurrence in our training cohort (p = 0.0003, logrank test) and in our independent validation cohort (p = 0.04, HR = 6.8, logrank test).\n", "\n", "Question: Is a gene signature in histologically normal surgical margins predictive of oral carcinoma recurrence?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "Yes, a gene signature in histologically normal surgical margins is predictive of oral carcinoma recurrence.\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Hepatitis C virus (HCV) is a major cause of chronic hepatitis worldwide. Scavenger receptor class B type I (SR-BI) has been shown to bind HCV envelope glycoprotein E2, participate in entry of HCV pseudotype particles, and modulate HCV infection. However, the functional role of SR-BI for productive HCV infection remains unclear. In this study, we investigated the role of SR-BI as an entry factor for infection of human hepatoma cells using cell culture-derived HCV (HCVcc). Anti-SR-BI antibodies directed against epitopes of the human SR-BI extracellular loop specifically inhibited HCVcc infection in a dose-dependent manner. Down-regulation of SR-BI expression by SR-BI-specific short interfering RNAs (siRNAs) markedly reduced the susceptibility of human hepatoma cells to HCVcc infection. Kinetic studies demonstrated that SR-BI acts predominately after binding of HCV at an entry step occurring at a similar time point as CD81-HCV interaction. Although the addition of high-density lipoprotein (HDL) enhanced the efficiency of HCVcc infection, anti-SR-BI antibodies and SR-BI-specific siRNA efficiently inhibited HCV infection independent of lipoprotein.\n", "\n", "Question: Is scavenger receptor class B type I a key host factor for hepatitis C virus infection required for an entry step closely linked to CD81?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, scavenger receptor class B type I is a key host factor for hepatitis C virus infection required for an entry step closely linked to CD81.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Previous studies have demonstrated that Caveolin-1 (Cav-1) can ambiguously behave as tumor suppressor or tumor promoter in different neoplasms, depending on cancer type. Some findings have also revealed that cell proliferation, migration and invasion were attenuated by the knockdown of Caveolin-1 expressions. However, the functional and prognostic significance of Caveolin-1 in most tumors remains to be fully elucidated.\n", "The aim of the study was to investigate a possible association between tissue Caveolin-1 expression and the clinicopathologic features of ovarian serous tumors.\n", "Caveolin-1 expression was studied in a total of 82 formalin-fixed, paraffin-embedded specimens of ovarian serous tumors and its association with different clinicopathologic parameters was evaluated.\n", "The study included 36 (43.9%) benign, 12 (14.6%) borderline and 34 (41.5%) malignant serous tumors. Mean patient age was 43.9 ± 14.4 years (17-72 years). Statistical analysis revealed that if the tumor becomes more aggressive and invasive, it losses the stromal Caveolin-1 expression (p = 0.001). Also, parallel changes between stromal and perivascular Caveolin-1 expressions were observed.\n", "\n", "Question: Is expression of caveolin-1 in peritumoral stroma associated with histological grade in ovarian serous tumors?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, the expression of Caveolin-1 in peritumoral stroma is associated with histological grade in ovarian serous tumors, as indicated by the observed parallel changes between stromal and perivascular Caveolin-1 expressions and the loss of stromal Caveolin-1 expression with more aggressive and invasive tumors.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The endocannabinoid N-arachidonoylethanolamide (anandamide) is co-synthesized with other N-acylethanolamides, namely N-palmitoylethanolamide (PEA) and N-oleoylethanolamide (OEA), which have been shown to potentiate anandamide responses (so-called 'entourage effects') in non-vascular tissues. It remains unclear whether such interactions occur in the circulation.\n", "In rat isolated small mesenteric arteries, the effects of PEA and OEA on relaxation to anandamide and tissue contents of the N-acylethanolamides were examined under myographic conditions.\n", "Anandamide-induced relaxation was potentiated by pretreatment with PEA (10 microM) or OEA (1 microM), or in combination. The potentiation by PEA and OEA was endothelium-independent and abolished by treatment with capsaicin (10 microM), which desensitizes the transient receptor potential vanilloid type 1 (TRPV1) receptor system, or by the TRPV1 receptor antagonist, N-(3-methoxyphenyl)-4-chlorocinnamide (SB366791) (2 microM). It was also observed at molar ratios of anandamide and PEA (or OEA) similar to those found in mesenteric arteries. PEA and inhibition of anandamide hydrolysis by 3'-carbamoyl-biphenyl-3-yl-cyclohexylcarbamate (URB597) (1 microM) additively potentiated anandamide responses. On the other hand, PEA and OEA also induced vasorelaxation per se (rank order of potency: anandamide>OEA>PEA), but relaxation to the three N-acylethanolamides displayed different sensitivity to treatment with capsaicin, SB366791 and URB597. For example, relaxations to anandamide and OEA, but not PEA, were attenuated by both capsaicin and SB366791.\n", "\n", "Question: Do 'Entourage ' effects of N-palmitoylethanolamide and N-oleoylethanolamide on vasorelaxation to anandamide occur through TRPV1 receptors?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"No, the entourage effects of N-palmitoylethanolamide and N-oleoylethanolamide on vasorelaxation to anandamide do not occur through TRPV1 receptors, as the potentiation by PEA and OEA was endothelium-independent and abolished by treatment with capsaicin and the TRPV1 receptor antagonist.\"\n", "Solutions: yes\n", "Score: 0.0\n", "Error reason: Computation result is incorrect.Questions: Context: Surgical procedures on the thoracoabdominal part of the aorta make the spinal cord vulnerable to ischemia. Paraplegia is the most severe complication following thoracoabdominal operations. In this study, iloprost was used as an agent to decrease the severity of ischemia and reperfusion injury to the spinal cord during aortic occlusion and declamping.\n", "Twelve adult mongrel dogs weighing 17+/-2 kg were used in this study. The animals were randomly assigned to either group I, which received saline solution (6 dogs), or group II, which received prostacyclin. Group I was referred to as the control group and group II as the iloprost group. After baseline measurements were completed, the aorta was cross-clamped for sixty minutes distal to the left subclavian artery. No pharmacologic agents were used to control blood pressure in group I. Proximal and distal mean arterial pressures (DMAP) were monitored continuously. DMAP were considered as diastolic pressure in preocclusion and reperfusion periods. Iloprost administration was started at a rate of 5 ng/kg/minute five minutes before the aortic occlusion. This dosage was increased to 25 ng/kg/minute during aortic occlusion.\n", "Mean proximal arterial pressure was 147+/-12 mmHg in the control group and 116+/-13 mmHg in the iloprost group at occlusion (p<0.01). Mean distal arterial pressure was 19+/-7 in the control group and 37+/-5 in the iloprost group during clamping (p<0.05). Functional outcome was evaluated according to Tarlov scores 24 hours after the study. Although none of the animals recovered completely from the control group, 4 animals from the iloprost group recovered (p<0.05). Following the neurologic assessment, animals were sacrificed and specimens were taken for the electron microscopic study. Electron microscopic changes documented that severe mitochondrial damage and vacuolisation occurred in the control group. However these changes were more subtle in the iloprost group.\n", "\n", "Question: Does iloprost protect the spinal cord during aortic cross-clamping in a canine model?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, iloprost protects the spinal cord during aortic cross-clamping in a canine model, as evidenced by improved functional outcomes and less severe mitochondrial damage compared to the control group.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Expressive therapies are increasingly incorporated into the management of Parkinson's disease (PD), although there are little objective data assessing their benefits.\n", "Develop and study a novel community Improvisation Theater (IT) program for PD in order to improve quality of life.\n", "A prospective, rater-blinded, modified cross-over design study of IT for PD. 22 subjects were randomized 1:1 to active-start (AS) or control-start (CS) groups, controlling for age and Hoehn and Yahr stage. Participants were recruited from the Northwestern PD and Movement Disorders Center. 60 min IT sessions were led by The Second City\n", "All 22 participants completed the study. 21/22 (95%) participants attended at least 80% of the classes. All participants indicated that they would recommend the class to others with PD. 21/22 participants enjoyed the class and felt it was beneficial for their symptoms. A significant improvement pre-to-post intervention was seen with the UPDRS part II ADL measure (mean -1.5, p = 0.019).\n", "\n", "Question: Is laughter the best medicine : The Second?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, laughter can be considered beneficial for health, as indicated by the positive outcomes of the Improvisation Theater program for participants with Parkinson's disease.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Many countries use cooling plates to actively cool collected whole blood (WB) to room temperature. Until now, no paired comparison had been performed, and it was our aim to compare the effect of active versus no active cooling on the in vitro quality of WB and subsequently prepared blood components.\n", "Two units of WB were pooled and divided shortly after donation. One unit was placed under a butane-1,4-diol plate to obtain active cooling; the other was placed in an insulated box with other warm units to mimic worst-case holding conditions. WB was held overnight and processed into a white blood cell (WBC)-reduced red blood cells (RBCs), buffy coat (BC), and plasma. The BCs were further processed into platelet (PLT) concentrates. RBCs were stored for 42 days, and PLT concentrates for 8 days (n = 12 paired experiments).\n", "After overnight storage, ATP content of the RBCs was 4.9 ± 0.3 µmol/g Hb for actively cooled WB versus 4.5 ± 0.4 µmol/g Hb for not actively cooled WB (p < 0.001). On Day 42 of storage, RBCs prepared from this WB contained 3.1 ± 0.3 µmol ATP/g Hb with active cooling versus 2.6 ± 0.3 µmol/g Hb without (p < 0.001). Hemolysis on Day 42 was 0.35 ± 0.08% with active cooling and 0.67 ± 0.21% without (p < 0.001). No effect was observed on the in vitro quality of plasma, BC, or PLT concentrates.\n", "\n", "Question: Does active cooling of whole blood to room temperature improve blood component quality?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, active cooling of whole blood to room temperature improves blood component quality.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Tumor size is one of the most important factors in making clinical and pathological assessment of breast cancer. In the present study, we aimed to determine whether the preoperative measurement of tumor size, by imaging modalities, deviate from the postoperative pathological measurement in breast cancer.\n", "1296 patients diagnosed with invasive ductal breast carcinoma (IDC) during 2007 and 2009 were involved. Pre- and postoperative measurements of tumor size were compared using paired t-test and Chi-square test.\n", "The mean maximum diameters of tumors by imaging modalities and pathology were 27.9 mm and 22.4 mm, respectively. There was a statistically significant difference of 5.5 mm (95% CI: 4.7-6.2, p<0.001) between them. The discordance between pre- and post-surgical measurements of tumor size had significant effect on choosing surgery type, causing less application of breast conserving therapy (p<0.0001).\n", "\n", "Question: Does preoperative measurement of breast cancer overestimate tumor size compared to pathological measurement?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, preoperative measurement of breast cancer overestimates tumor size compared to pathological measurement.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Basal-phenotype or basal-like breast cancers are characterized by basal epithelium cytokeratin (CK5/14/17) expression, negative estrogen receptor (ER) status and distinct gene expression signature. We studied the clinical and biological features of the basal-phenotype tumors determined by immunohistochemistry (IHC) and cDNA microarrays especially within the ER-negative subgroup.\n", "IHC was used to evaluate the CK5/14 status of 445 stage II breast cancers. The gene expression signature of the CK5/14 immunopositive tumors was investigated within a subset (100) of the breast tumors (including 50 ER-negative tumors) with a cDNA microarray. Survival for basal-phenotype tumors as determined by CK5/14 IHC and gene expression signature was assessed.\n", "From the 375 analyzable tumor specimens, 48 (13%) were immunohistochemically positive for CK5/14. We found adverse distant disease-free survival for the CK5/14-positive tumors during the first years (3 years hazard ratio (HR) 2.23, 95% confidence interval (CI) 1.17 to 4.24, p = 0.01; 5 years HR 1.80, 95% CI 1.02 to 3.15, p = 0.04) but the significance was lost at the end of the follow-up period (10 years HR 1.43, 95% CI 0.84 to 2.43, p = 0.19). Gene expression profiles of immunohistochemically determined CK5/14-positive tumors within the ER-negative tumor group implicated 1,713 differently expressed genes (p < 0.05). Hierarchical clustering analysis with the top 500 of these genes formed one basal-like and a non-basal-like cluster also within the ER-negative tumor entity. A highly concordant classification could be constructed with a published gene set (Sorlie's intrinsic gene set, concordance 90%). Both gene sets identified a basal-like cluster that included most of the CK5/14-positive tumors, but also immunohistochemically CK5/14-negative tumors. Within the ER-negative tumor entity there was no survival difference between the non-basal and basal-like tumors as identified by immunohistochemical or gene-expression-based classification.\n", "\n", "Question: Is basal-like phenotype associated with patient survival in estrogen-receptor-negative breast cancers?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"No, within the ER-negative tumor entity there was no survival difference between the non-basal and basal-like tumors as identified by immunohistochemical or gene-expression-based classification.\"\n", "Solutions: no\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Proteins and peptides occurring in human body fluids can be useful biological markers for neurological diseases and can even contribute to the pathogenesis of such diseases. However, proteins and peptides are potential substrates of proteases and other enzymes. Proteolysis and enzymatic modification may lead to their degradation and modification.\n", "Using mass spectrometry we investigated the degradation and modification of indicator peptides in the presence of cerebrospinal fluid (CSF). We further applied a fluorometric assay to study the activity of the presumed enzyme glutaminyl cyclase.\n", "In CSF we observed an aminopeptidase activity that could partially be inhibited by protease inhibitors and EDTA. In addition, the formation of pyroglutamate (pGlu) from N-terminal glutamine (Gln) was regularly observed. The reaction to pGlu was rapid and protected the indicator peptides from further N-terminal degradation. The conversion of Gln to pGlu could be attributed to the activity of the enzyme glutaminyl cyclase (QC). The QC activity was a characteristic feature of all 45 CSF samples collected from multiple sclerosis patients and controls.\n", "\n", "Question: Is glutaminyl cyclase activity a characteristic feature of human cerebrospinal fluid?\n", "\n", "Answer:\n", "Predictions: {\"draft_answer\": \"Yes, glutaminyl cyclase activity is a characteristic feature of human cerebrospinal fluid.\"}\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.\n", "{'name': 'generate_answer', 'description': 'Draft an answer using the retrieved context.', 'inputs': [{'name': 'question', 'type': 'str', 'description': 'The original question from the user.', 'required': True}], 'outputs': [{'name': 'draft_answer', 'type': 'str', 'description': 'A concise, direct answer to the question.', 'required': True}], 'prompt': '\"\"\"\\nYou can think to generate answers based on the provided {question}. Ensure that your response is clear and concise, and consider whether a simple \"Yes\" or \"No\" is sufficient or if a more nuanced answer is required. Format your final answer in the \\'answer\\' field as xxx. If the draft answer requires significant revision, note the necessary changes before proceeding to validation. Additionally, if the {question} is ambiguous or poorly defined, indicate this in your response and suggest clarifying questions. Prioritize and weigh evidence carefully to enhance the reliability of your answer.\\n\"\"\"', 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"You can think to generate answers. You should provide the final answer (either Yes or No) in the 'answer' field. Format your answer in xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[32m2026-01-06 08:40:44.229\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.233 | Total tokens: 6244713 | Current cost: $0.003 | Current tokens: 19872\u001b[0m\n", "\u001b[32m2026-01-06 08:40:46.484\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.233 | Total tokens: 6245008 | Current cost: $0.000 | Current tokens: 295\u001b[0m\n", "\u001b[32m2026-01-06 08:40:48.228\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.233 | Total tokens: 6246004 | Current cost: $0.000 | Current tokens: 996\u001b[0m\n", "{'name': 'validate_answer9330', 'description': 'Task to validate_answer9330. Takes draft_answer as input. Produces validated_answer as output.', 'inputs': [{'name': 'draft_answer', 'type': 'str', 'description': 'Input parameter draft_answer for validate_answer9330', 'required': False}], 'outputs': [{'name': 'validated_answer', 'type': 'str', 'description': 'Output parameter validated_answer from validate_answer9330', 'required': True}], 'prompt': '\"\"\"\\nThink step by step to answer the question based on the context provided in {question}. Begin by identifying the key components and underlying issues within the question. In the \\'thought\\' field, explain your reasoning process, detailing how you arrived at your conclusions and addressing any complexities or ambiguities present in the question. Then, provide a clear and concise final answer in the \\'answer\\' field, ensuring it is directly relevant to the user\\'s needs. Format your output in XML format, such as {thought} and {answer}.\\n\"\"\"', 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"Think step by step to answer the question based on the question context. You should integrate context for answering. You should explain your thinking process in the 'thought' field, and provide the final answer in the 'answer' field.\\nFormat your output in xml format, such as xxx and xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n", "\u001b[32m2026-01-06 08:40:51.210\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.236 | Total tokens: 6265947 | Current cost: $0.003 | Current tokens: 19943\u001b[0m\n", "\u001b[32m2026-01-06 08:40:53.727\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.236 | Total tokens: 6266232 | Current cost: $0.000 | Current tokens: 285\u001b[0m\n", "\u001b[32m2026-01-06 08:40:55.145\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.237 | Total tokens: 6267284 | Current cost: $0.000 | Current tokens: 1052\u001b[0m\n", "{'name': 'evaluate_answer9619', 'description': 'Task to evaluate_answer9619. Takes validated_answer as input. Produces evaluation_score as output.', 'inputs': [{'name': 'validated_answer', 'type': 'str', 'description': 'Input parameter validated_answer for evaluate_answer9619', 'required': False}], 'outputs': [{'name': 'evaluation_score', 'type': 'str', 'description': 'Output parameter evaluation_score from evaluate_answer9619', 'required': True}], 'prompt': '\"\"\"\\nThink step by step to answer the question based on the context provided in {question}. Begin by analyzing the key components of the question to identify the main issue and any underlying factors. Integrate this context into your reasoning process. In the \\'thought\\' field, explain your reasoning and how you arrived at your conclusion, ensuring clarity and coherence. Provide the final answer in the \\'answer\\' field, making sure it directly addresses the main issue identified. Format your output in XML format, such as {thought} and {answer}. Additionally, ensure that your answer is validated against predefined criteria for accuracy and relevance before finalizing it.\\n\"\"\"', 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"Think step by step to answer the question based on the question context. You should integrate context for answering. You should explain your thinking process in the 'thought' field, and provide the final answer in the 'answer' field.\\nFormat your output in xml format, such as xxx and xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n", "\u001b[32m2026-01-06 08:40:57.401\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.240 | Total tokens: 6287183 | Current cost: $0.003 | Current tokens: 19899\u001b[0m\n", "\u001b[32m2026-01-06 08:40:59.455\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.240 | Total tokens: 6287438 | Current cost: $0.000 | Current tokens: 255\u001b[0m\n", "\u001b[32m2026-01-06 08:41:03.873\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.240 | Total tokens: 6288475 | Current cost: $0.000 | Current tokens: 1037\u001b[0m\n", "{'name': 'context_analysis3328', 'description': 'Task to context_analysis3328. Takes question as input. Produces context as output.', 'inputs': [{'name': 'question', 'type': 'str', 'description': 'Input parameter question for context_analysis3328', 'required': False}], 'outputs': [{'name': 'context', 'type': 'str', 'description': 'Output parameter context from context_analysis3328', 'required': True}], 'prompt': 'Your are a task solver.', 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"Think step by step to answer the question based on the question context. You should integrate context for answering. You should explain your thinking process in the 'thought' field, and provide the final answer in the 'answer' field.\\nFormat your output in xml format, such as xxx and xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n", "\u001b[32m2026-01-06 08:41:05.810\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.244 | Total tokens: 6308374 | Current cost: $0.003 | Current tokens: 19899\u001b[0m\n", "\u001b[32m2026-01-06 08:41:06.692\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.244 | Total tokens: 6308514 | Current cost: $0.000 | Current tokens: 140\u001b[0m\n", "\u001b[32m2026-01-06 08:41:07.825\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.244 | Total tokens: 6309222 | Current cost: $0.000 | Current tokens: 708\u001b[0m\n", "{'name': 'handle_ambiguities7850', 'description': 'Task to handle_ambiguities7850. Takes context as input. Produces clarified_question as output.', 'inputs': [{'name': 'context', 'type': 'str', 'description': 'Input parameter context for handle_ambiguities7850', 'required': False}], 'outputs': [{'name': 'clarified_question', 'type': 'str', 'description': 'Output parameter clarified_question from handle_ambiguities7850', 'required': True}], 'prompt': 'Your are a task solver.', 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"Think step by step to answer the question based on the question context. You should integrate context for answering. You should explain your thinking process in the 'thought' field, and provide the final answer in the 'answer' field.\\nFormat your output in xml format, such as xxx and xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n", "\u001b[32m2026-01-06 08:41:10.985\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.247 | Total tokens: 6329189 | Current cost: $0.003 | Current tokens: 19967\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[32m2026-01-06 08:41:13.141\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.248 | Total tokens: 6329474 | Current cost: $0.000 | Current tokens: 285\u001b[0m\n", "\u001b[32m2026-01-06 08:41:14.692\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.248 | Total tokens: 6330432 | Current cost: $0.000 | Current tokens: 958\u001b[0m\n", "{'name': 'feedback_loop7764', 'description': 'Task to feedback_loop7764. Takes evaluation_score, draft_answer as input. Produces improved_answer as output.', 'inputs': [{'name': 'evaluation_score', 'type': 'str', 'description': 'Input parameter evaluation_score for feedback_loop7764', 'required': False}, {'name': 'draft_answer', 'type': 'str', 'description': 'Input parameter draft_answer for feedback_loop7764', 'required': False}], 'outputs': [{'name': 'improved_answer', 'type': 'str', 'description': 'Output parameter improved_answer from feedback_loop7764', 'required': True}], 'prompt': 'Your are a task solver.', 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"Think step by step to answer the question based on the question context. You should integrate context for answering. You should explain your thinking process in the 'thought' field, and provide the final answer in the 'answer' field.\\nFormat your output in xml format, such as xxx and xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n", "\u001b[32m2026-01-06 08:41:36.283\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.251 | Total tokens: 6350415 | Current cost: $0.003 | Current tokens: 19983\u001b[0m\n", "\u001b[32m2026-01-06 08:41:39.427\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.251 | Total tokens: 6350757 | Current cost: $0.000 | Current tokens: 342\u001b[0m\n", "\u001b[32m2026-01-06 08:41:40.734\u001b[0m | \u001b[1mINFO \u001b[0m | 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"text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Evaluating workflow: 100%|██████████| 50/50 [01:18<00:00, 1.58s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "\u001b[32m2026-01-06 08:42:59.692\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.optimizers.qastructure_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m1057\u001b[0m - \u001b[1mStep 2 metrics: {'f1': 0.0, 'em': 0.0, 'acc': 0.98}\u001b[0m\n", "randomly update dataset\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[32m2026-01-06 08:43:03.609\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.265 | Total tokens: 6421388 | Current cost: $0.003 | Current tokens: 19765\u001b[0m\n", "\u001b[32m2026-01-06 08:43:06.246\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.268 | Total tokens: 6441160 | Current cost: $0.003 | Current tokens: 19772\u001b[0m\n", "\u001b[32m2026-01-06 08:43:08.039\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.272 | Total tokens: 6460914 | Current cost: $0.003 | Current tokens: 19754\u001b[0m\n", "\u001b[32m2026-01-06 08:43:09.832\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.272 | Total tokens: 6461585 | Current cost: $0.000 | Current tokens: 671\u001b[0m\n", "The identified issues across the workflows highlight several critical flaws: a lack of integration between context analysis and answer generation, leading to disjointed or irrelevant responses; an ambiguous validation step that fails to define criteria for \"validated answers,\" risking the acceptance of incorrect information; and a flawed control flow where feedback loops occur after evaluation, potentially hindering effective improvements. Additionally, prompts often lack specificity, resulting in ambiguity and confusion, particularly in complex topics like Hydraulic Calcium Silicate cement and serotonin antagonists. Furthermore, discrepancies between provided context and questions can lead to irrelevant answers, while execution histories reveal a troubling trend of incorrect answers being marked as correct due to insufficient clarity and precision checks.\n", "\u001b[32m2026-01-06 08:43:11.598\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.272 | Total tokens: 6462413 | Current cost: $0.000 | Current tokens: 828\u001b[0m\n", "```python\n", "steps = [\n", " {'name': 'context_analysis3328', 'args': ['question'], 'outputs': ['context']},\n", " {'name': 'handle_ambiguities7850', 'args': ['context'], 'outputs': ['clarified_question']},\n", " {'name': 'generate_answer', 'args': ['clarified_question'], 'outputs': ['draft_answer']},\n", " {'name': 'validate_answer9330', 'args': ['draft_answer'], 'outputs': ['validated_answer']},\n", " {'name': 'evaluate_answer9619', 'args': ['validated_answer'], 'outputs': ['evaluation_score']},\n", " {'name': 'feedback_loop7764', 'args': ['evaluation_score', 'draft_answer'], 'outputs': ['improved_answer']}\n", "]\n", "```\n", "Questions: Context: Here, we ask whether platelet GPIb and GPIIb/IIIa receptors modulate platelet sequestration and activation during GalTKO.hCD46 pig lung xenograft perfusion.\n", "GalTKO.hCD46 transgenic pig lungs were perfused with heparinized fresh human blood. Results from perfusions in which αGPIb Fab (6B4, 10 mg/l blood, n = 6), αGPIIb/IIIa Fab (ReoPro, 3.5 mg/l blood, n = 6), or both drugs (n = 4) were administered to the perfusate were compared to two additional groups in which the donor pig received 1-desamino-8-d-arginine vasopressin (DDAVP), 3 μg/kg (to pre-deplete von Willebrand Factor (pVWF), the main GPIb ligand), with or without αGPIb (n = 6 each).\n", "Platelet sequestration was significantly delayed in αGPIb, αGPIb+DDAVP, and αGPIb+αGPIIb/IIIa groups. Median lung \"survival\" was significantly longer (>240 vs. 162 min reference, p = 0.016), and platelet activation (as CD62P and βTG) were significantly inhibited, when pigs were pre-treated with DDAVP, with or without αGPIb Fab treatment. Pulmonary vascular resistance rise was not significantly attenuated in any group, and was associated with residual thromboxane and histamine elaboration.\n", "\n", "Question: Is platelet sequestration and activation during GalTKO.hCD46 pig lung perfusion by human blood primarily mediated by GPIb , GPIIb/IIIa , and von Willebrand Factor?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, platelet sequestration and activation during GalTKO.hCD46 pig lung perfusion by human blood is primarily mediated by GPIb, GPIIb/IIIa, and von Willebrand Factor.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Despite advances in the understanding of the pathophysiological basis of autoimmune hepatitis (AIH), it is still difficult to delineate the mechanisms involved in progression from hepatic inflammation toward fibrosis. Our aim was to study serum concentrations of NO in AIH of different histological severity and possible effects of immunosuppressive therapy on NO production.\n", "We studied serum NO metabolites (NOx) in 47 consecutive patients with AIH and in 28 age- and sex-matched controls.\n", "Serum NOx concentrations were higher in AIH patients than in controls (10.3 (4.5-27.3 µmol/L) vs. 4.3 (1.6-14.3 µmol/L), p < 0.001). According to liver histology, median NOx concentrations were significantly higher in patients with severe interface hepatitis compared to patients with mild-moderate interface hepatitis (12.3 (4.5-27.3 µmol/L) vs. 9.3 (4.6-20.3 µmol/L), p = 0.029). Similarly, serum NOx concentrations were significantly higher in patients with advanced fibrosis than in those with early fibrosis (12.2 (4.6-27.3 µmol/L) vs. 9.3 (6.6-12.8 µmol/L), p = 0.018). NOx concentrations decreased in 16 AIH patients who were tested also after biochemical remission was achieved (12.6 (4.5-22.8 µmol/L) at baseline and 5.9 (2.8-10.5 µmol/L) after remission, p = 0.001).\n", "\n", "Question: Is nitric oxide a potential mediator of hepatic inflammation and fibrogenesis in autoimmune hepatitis?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "Yes, nitric oxide is a potential mediator of hepatic inflammation and fibrogenesis in autoimmune hepatitis.\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: We aimed to investigate the prognostic value of tumour-infiltrating lymphocytes' (TILs) expression in pretreatment specimens from patients with head and neck squamous cell carcinoma (HNSCC) treated with definitive chemoradiotherapy (CRT).\n", "The prevalence of CD3+, CD8+, CD4+ and FOXP3+ TILs was assessed using immunohistochemistry in tumour tissue obtained from 101 patients before CRT and was correlated with clinicopathological characteristics as well as local failure-free- (LFFS), distant metastases free- (DMFS), progression-free (PFS) and overall survival (OS). Survival curves were measured using the Kaplan-Meier method, and differences in survival between the groups were estimated using the log-rank test. Prognostic effects of TIL subset density were determined using the Cox regression analysis.\n", "With a mean follow-up of 25 months (range, 2.3-63 months), OS at 2 years was 57.4% for the entire cohort. Patients with high immunohistochemical CD3 and CD8 expression had significantly increased OS (P=0.024 and P=0.028), PFS (P=0.044 and P=0.047) and DMFS (P=0.021 and P=0.026) but not LFFS (P=0.90 and P=0.104) in multivariate analysis that included predictive clinicopathologic factors, such as age, sex, T-stage, N-stage, tumour grading and localisation. Neither CD4 nor FOXP3 expression showed significance for the clinical outcome. The lower N-stage was associated with improved OS in the multivariate analysis (P=0.049).\n", "\n", "Question: Do tumour-infiltrating lymphocytes predict response to definitive chemoradiotherapy in head and neck cancer?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, tumour-infiltrating lymphocytes (TILs), specifically high expression of CD3 and CD8, are associated with significantly increased overall survival, progression-free survival, and distant metastases-free survival in patients with head and neck squamous cell carcinoma treated with definitive chemoradiotherapy.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Distinguishing small cell epithelial malignancies of the sinonasal cavity and nasopharynx is difficult due to overlapping morphologic characteristics, particularly in small biopsies. This distinction is important, however, because of the inherent differences in biology, natural history, prognosis, and treatment among these neoplasms. The aim of this study is to identify a limited immunohistochemical panel that may help to differentiate these morphologically similar small cell epithelial malignancies.\n", "We reviewed 37 cases of histologically similar small cell epithelial malignancies of the sinonasal cavity and nasopharynx: nasopharyngeal carcinoma (NPC) (16), basaloid squamous cell carcinoma (BSCC) (15), and high-grade neuroendocrine carcinoma (HGNEC) (6) obtained at Jackson Memorial Hospital/UM Sylvester Comprehensive Cancer Center between 2003 and 2007. Immunohistochemistry for pancytokeratin (CK), CK5/6, p63, and HLA-DR was performed using the labeled streptavidin-biotin method.\n", "All cases in this study were positive for CK and p63. The CK staining pattern of HGNEC was characteristically dot-like whereas the remaining tumors stained with strong and diffuse cytoplasmic membrane positivity. Likewise, the p63 staining pattern of HGNEC was focal and weak whereas the remaining tumors stained with diffuse and strong nuclear positivity. Immunohistochemistry for HLA-DR was positive in all cases of NPC, whereas BSCC and HGNEC were uniformly negative. Cases of NPC and BSCC were positive for CK5/6 whereas cases of HGNEC were negative.\n", "\n", "Question: Does a limited immunohistochemical panel help differentiate small cell epithelial malignancies of the sinonasal cavity and nasopharynx?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, a limited immunohistochemical panel helps differentiate small cell epithelial malignancies of the sinonasal cavity and nasopharynx.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The aim was to identify subjects with incipient Alzheimer's disease (AD) among patients with mild cognitive impairment (MCI) using brief cognitive tests.\n", "A total of 147 MCI patients were followed for 4-6 years and the incidence of AD was 11.6%/year. At baseline, the cube copying test, clock drawing test, MMSE and measurements of regional cerebral blood flow (rCBF) and cerebrospinal fluid (CSF) beta-amyloid(1-42) (A beta (42)) were performed.\n", "The cube copying test, but not the clock drawing test, could predict AD among MCI patients with an area under the receiver operating characteristic curve of 0.64 (p < 0.01). The relative risk for future AD was increased in MCI subjects with impaired cube copying test (sex- and age-adjusted hazard ratio = 1.8, p < 0.05) and the incidence of AD was 18.2% in this subgroup. Combining the cube copying test with either rCBF or CSF A beta(42) had additive effects on the risk assessment for future development of AD. MCI patients achieving high scores on both MMSE and cube copying test had a very low risk of developing AD (incidence of AD = 1.6%).\n", "\n", "Question: Does cube copying test in combination with rCBF or CSF A beta 42 predict development of Alzheimer 's disease?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, combining the cube copying test with either rCBF or CSF A beta(42) had additive effects on the risk assessment for future development of Alzheimer's disease.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The influence of phenotype and detection of clonality on prognosis in early mycosis fungoides has never been addressed in large studies.\n", "To correlate immunophenotype and detection of clonality with clinical outcome.\n", "We analysed 73 biopsy specimens from 68 patients with early mycosis fungoides (stage Ia or Ib) and at least 10 years of follow up (or dead of disease).\n", "Four phenotypic groups could be identified: group A (alpha/beta+ CD4+ CD8- TIA1-), 51 patients; median survival time 160 months; group B (alpha/beta+ CD4- CD8+ TIA1+), 10 patients; median survival time 195 months; group C (alpha/beta- CD4- CD8+/- TIA1+), five patients; median survival time 165 months; and group D (alpha/beta+ CD4- CD8- TIA1-), two patients; median survival time 130 months. Survival curves did not show statistical differences among the groups. Monoclonality was detected in 36 of 67 tested biopsies (54%), and statistical analyses did not show prognostic differences between the clonal and nonclonal cases.\n", "\n", "Question: Is the prognosis of early mycosis fungoides influenced by phenotype and T-cell clonality?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"No\"\n", "Solutions: no\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Health-related quality of life (HRQoL) is reduced after a burn, and is affected by coexisting conditions. The aims of the investigation were to examine and describe effects of coexisting disease on HRQoL, and to quantify the proportion of burned people whose HRQoL was below that of a reference group matched for age, gender, and coexisting conditions.\n", "A nationwide study covering 9 years and examined HRQoL 12 and 24 months after the burn with the SF-36 questionnaire. The reference group was from the referral area of one of the hospitals.\n", "The HRQoL of the burned patients was below that of the reference group mainly in the mental dimensions, and only single patients were affected in the physical dimensions. The factor that significantly affected most HRQoL dimensions (n=6) after the burn was unemployment, whereas only smaller effects could be attributed directly to the burn.\n", "\n", "Question: Is long term health-related quality of life after burns strongly dependent on pre-existing disease and psychosocial issues and less due to the burn itself?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, long term health-related quality of life after burns is strongly dependent on pre-existing disease and psychosocial issues, and less due to the burn itself.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: This study aims to examine the effects of dental implant surgery on vestibular-evoked myogenic potential (VEMP) responses.\n", "Between October 2012 and October 2014, a total of 60 consecutive patients undergoing dental implant surgery at Başkent University Hospital, Department of Otorhinolaryngology were included in the study. The control group consisted of 40 healthy subjects undergoing routine clinical examination. The VEMP response was evaluated at baseline, second and seventh days. Positional tests and Dix-Hallpike testing for vertigo were performed at baseline, second and seventh days.\n", "Hundred-eight dental implants were placed in 60 patients. There was no significant difference in the p1 and n1 latencies in the control group at baseline, second day, and seventh day (p>0.05). However, there was a significant increase at the second day for p1 latencies in the study group, compared to the baseline and seventh day (p=0.038). There was a significant increase at the second day for n1 compared to the baseline (p=0.016) and seventh day in the study group (p=0.005). There was a significant increase at the seventh day for n1 compared to the baseline in the study group (p=0.016).\n", "\n", "Question: Do vestibular-evoked myogenic potentials before and after dental implant surgery?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, vestibular-evoked myogenic potentials (VEMP) were evaluated before and after dental implant surgery, showing significant changes in the study group at different time points.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The optimal target of endoscopic dilation of postsurgical esophageal strictures is unknown. Our aim was to compare the dilation-free period of patients who underwent dilation up to 16 mm with patients who were dilated up to 17 or 18 mm.\n", "We retrospectively analyzed adult patients who received bougie/balloon dilation for a benign anastomotic stricture after esophagectomy. An anastomotic stricture was defined as dysphagia in combination with a luminal diameter of ≤13 mm at endoscopy. We analyzed the dilation-free period using Kaplan-Meier and multivariable Cox regression analysis.\n", "Eighty-eight patients were dilated up to a maximum diameter of 16 mm and 91 patients to a diameter >16 mm. The stricture recurrence rate was 79.5 % in the 16 mm group and 68.1 % in the >16 mm group (p = 0.083). The overall dilation-free period had a median of 41.5 (range 8-3233) days and 92 (range 17-1745) days, respectively (p < 0.001). For patients who developed a stricture recurrence, the median dilation-free period was 28 (range 8-487) days and 63 (range 17-1013) days, respectively (p = 0.001). Cox regression analysis showed a reduced risk of stricture recurrence for patients who were dilated up to >16 mm: crude hazard ratio (HR) 0.57 (95 % confidence interval (CI) 0.41-0.81) and adjusted HR 0.48 (95 % CI 0.33-0.70).\n", "\n", "Question: Does endoscopic dilation of benign esophageal anastomotic strictures over 16 mm have a longer lasting effect?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, endoscopic dilation of benign esophageal anastomotic strictures over 16 mm has a longer lasting effect, as indicated by the longer dilation-free period and reduced risk of stricture recurrence in patients dilated to >16 mm compared to those dilated to 16 mm.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To evaluate whether the Milan criteria are useful in patients with hepatocellular carcinoma (HCC) who received transarterial chemoembolization (TACE) before liver transplantation (LT).\n", "Thirty-six HCC patients who fulfilled the Milan criteria after having received TACE and subsequently underwent LT were included (TACE + LT group) in the study. As controls, 21 patients who also met the Milan criteria and underwent LT without prior treatment were selected (LT group). Post-LT clinical outcomes, such as HCC recurrence, survival rate, and histologic features of explanted livers, were compared between the two groups.\n", "Baseline characteristics were not different between the two groups. Pre-LT maximal tumor diameter in TACE + LT group was similar to that of LT group (2.0 +/- 0.6 cm vs 2.3 +/- 0.9 cm; P = 0.10). Post-LT histologic findings also revealed similar maximal tumor diameter in the two groups (2.4 +/- 1.4 cm vs 2.3 +/- 0.9 cm; P = 0.70). Explanted livers showed similar incidence of unfavorable pathologic features. The morality within 60 d after transplantation was not different between the two groups (8.3% vs 9.5%; P = 0.99). Post-LT 5-year survival rate (57% vs 74%; P = 0.70) and cumulative recurrence rate (8.3% vs 4.8%; P = 0.90) were not significantly different between the two groups.\n", "\n", "Question: Are milan criteria useful predictors for favorable outcomes in hepatocellular carcinoma patients undergoing liver transplantation after transarterial chemoembolization?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"No, the Milan criteria are not shown to be useful predictors for favorable outcomes in hepatocellular carcinoma patients undergoing liver transplantation after transarterial chemoembolization, as the study found no significant differences in outcomes between the two groups.\"\n", "Solutions: yes\n", "Score: 0.0\n", "Error reason: Computation result is incorrect.Questions: Context: Dysfunction of the rapidly activating delayed rectifier K(+) channel (IKr) encoded by the human ether-à-go-go-related gene (hERG) is the primary cause of acquired long QT syndrome (LQTS). Fever has been reported to trigger LQTS in various conditions.\n", "We aim to clarify the effect and underlying mechanisms of febrile temperature on hERG expressed in HEK cells, IKr in neonatal rat ventricular myocytes, and the QT interval in rabbits.\n", "Western blot analysis was used to determine the expression of hERG channel protein in stably transfected HEK 293 cells. Immunocytochemistry was used to visualize the localization of hERG channels. The whole-cell patch clamp technique was used to record hERG K(+) current (IhERG) in hERG expressing HEK 293 cells, as well as IKr, transient outward K(+) current (Ito), and L-type Ca(2+) current (ICa) in neonatal rat ventricular myocytes. Electrocardiographic recordings were performed in an in vivo rabbit model.\n", "Compared with culture at 37°C, culture at 40°C reduced the mature hERG expression and IhERG in an extracellular K(+) concentration-dependent manner. Point mutations that remove the K(+) dependence of hERG-S624T and F627Y-also abolished the febrile temperature-induced hERG reduction. In neonatal rat ventricular myocytes, febrile temperature prolonged the action potential duration and selectively reduced IKr in a manner similar to low K(+) culture. In an in vivo rabbit model, fever and hypokalemia synergistically prolonged the QT interval.\n", "\n", "Question: Does febrile temperature facilitate hERG/IKr degradation through an altered K ( + ) dependence?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, febrile temperature facilitates hERG/IKr degradation through an altered K(+) dependence.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To determine whether anthocyanin-enriched bilberry extracts modulate pre- or posttranslational levels of oxidative stress defense enzymes heme-oxygenase (HO)-1 and glutathione S-transferase-pi (GST-pi) in cultured human retinal pigment epithelial (RPE) cells.\n", "Confluent ARPE-19 cells were preincubated with anthocyanin and nonanthocyanin phenolic fractions of a 25% enriched extract of bilberry (10(-6)-1.0 mg/mL) and, after phenolic removal, cells were oxidatively challenged with H(2)O(2). The concentration of intracellular glutathione was measured by HPLC and free radical production determined by the dichlorofluorescin diacetate assay. HO-1 and GST-pi protein and mRNA levels were determined by Western blot and RT-PCR, respectively.\n", "Preincubation with bilberry extract ameliorated the intracellular increase of H(2)O(2)-induced free radicals in RPE, though H(2)O(2) cytotoxicity was not affected. By 4 hours, the extract had upregulated HO-1 and GST-pi protein by 2.8- and 2.5-fold, respectively, and mRNA by 5.5- and 7.1-fold, respectively, in a dose-dependent manner. Anthocyanin and nonanthocyanin phenolic fractions contributed similarly to mRNA upregulation.\n", "\n", "Question: Do bilberry ( Vaccinium myrtillus ) anthocyanins modulate heme oxygenase-1 and glutathione S-transferase-pi expression in ARPE-19 cells?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, bilberry (Vaccinium myrtillus) anthocyanins modulate heme oxygenase-1 and glutathione S-transferase-pi expression in ARPE-19 cells.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Allergic rhinitis (AR) precedes and is often associated with bronchial asthma. Indeed, local and systemic inflammations in both conditions are very similar. Cysteinyl-leukotrienes (cys-LTs) are generated during early- and late-phase allergic reactions and induce smooth-muscle contraction, microvascular leakage, and mucous hypersecretion. Cys-LTs are detected in exhaled breath condensate (EBC) of asthmatics and regardless of bronchial symptoms, they are also found in EBC of rhinitic patients.\n", "To evaluate cys-LTs in EBC of allergic patients and to assess the activity of nasal fluticasone propionate (FP) on EBC cys-LTs levels.\n", "Cys-LTs coefficient of variation (CV) was evaluated from different EBC in 5 healthy volunteers. Cys-LTs levels from EBCs in 13 healthy controls and 56 allergic rhinitic (n=31) and rhinitic/asthmatic (n=25) patients were also evaluated at baseline. Subsequently patients were randomized to receive either FP 100 microg/day per nostril or placebo for 2 weeks and then re-evaluated for EBC cys-LTs.\n", "The CV was 14.12%. EBC cys-LTs in allergic patients were significantly higher than in healthy subjects (70.9 vs. 20.6 pg/mL (median), P<0.05), while it did not differ between asthmatic/rhinitic and purely rhinitic patients. Treatment significantly reduced cys-LTs (from 93.6 to 19.9 pg/mL, P<0.001). This effect was evident both in asthmatic/rhinitic and in rhinitic patients.\n", "\n", "Question: Does intranasal steroid reduce exhaled bronchial cysteinyl leukotrienes in allergic patients?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, intranasal steroid reduces exhaled bronchial cysteinyl leukotrienes in allergic patients.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Diltiazem reduces systemic blood pressure by decreasing the vascular smooth muscle tone. In the liver however, diltiazem seems to cause vasoconstriction, as evidenced by increases in portal pressure. The questions raised by this observation are concerned with a) the site of action of diltiazem (large vessels or sinusoids), b) the formation of permeability barriers and c) the role of Ca2+. The experiments in the present study should provide an answer to these questions.\n", "The experimental system was the hemoglobin-free perfused rat liver. The multiple-indicator dilution technique was employed with simultaneous injection of [14C]sucrose and [3H]water. Mean transit times and distribution spaces were calculated from the normalized outflow profiles.\n", "Calcium alone did not affect the hemodynamics of the liver. Diltiazem, however, changed several hemodynamic parameters when Ca2+ was present, but it was inactive in the absence of this cation. The hemodynamic effects of 500 microM diltiazem were: a) diminution of the transit time through the large vessels (t(o)) and, consequently, of the accessible vascular space (66.9%); b) diminution of the mean transit time of [14C]sucrose (tsuc) and, consequently, of the accessible sinusoidal space (28.1%); c) diminution of the mean transit time of tritiated water (twater) and, consequently, of the accessible cellular space (68.9%); d) diminution of the cellular to extracellular space ratio (theta) from 1.42 +/- 0.05 to 0.46 +/- 0.11.\n", "\n", "Question: Are the hemodynamic effects of diltiazem in the isolated perfused rat liver Ca ( 2+ ) -dependent?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To evaluate the quality of life (QoL) and potential QoL determinants in patients with clinically isolated syndrome (CIS).\n", "Eighteen CIS patients and eighteen controls were submitted to QoL evaluation with Functional Assessment of Multiple Sclerosis QoL instrument (FAMS). Cognition was evaluated with specific battery tests; Anxiety and depression with Beck Anxiety (BAI) and Depression (BDI) Inventories and Neurological disability with Guy's Neurological Disability Scale (GNDS).\n", "There was a significant difference in QoL between CIS patients and controls. CIS patients had worse performance in Paced Auditory Serial Addition 2 seconds (p=0.009) and fluency tests (p=0.0038). There was a significant difference in BAI (p=0.003), but no significant difference in BDI between patients and controls. There were significant correlations between QoL measure and verbal fluency and Stroop's test.\n", "\n", "Question: Is cognitive impairment correlated with reduced quality of life in patients with clinically isolated syndrome?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, cognitive impairment is correlated with reduced quality of life in patients with clinically isolated syndrome, as indicated by the significant correlations between QoL measures and cognitive tests such as verbal fluency and Stroop's test.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Growing evidence has shown that menthol has potent anticancer activity in various human cancers via the transient receptor potential melastatin 8 (TRPM8)-dependent pathway or in a TRPM8-independent manner. However, its effect on bladder cancer remains obscure. In the present investigation, we examined the expression of TRPM8 and the role of menthol in cells of the human bladder cancer cell line T24.\n", "RT-PCR, Western blotting and immunocytochemistry were used to confirm the expression and location of TRPM8 in T24 cells.\n", "TRPM8 was highly expressed in T24 cells and located in both the cell membrane and cytoplasm. With the use of small interfering RNA to silence the expression of TRPM8, we found that menthol could increase the concentration of intracellular calcium and decrease cell viability via the TRPM8 channel in T24 cells. We also found that menthol could induce cell death through TRPM8 in T24 cells, rather than cell cycle arrest or apoptosis. Moreover, the detection of mitochondrial membrane potential showed that menthol could induce mitochondrial membrane depolarization in T24 cells.\n", "\n", "Question: Does menthol induce cell death via the TRPM8 channel in the human bladder cancer cell line T24?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, menthol induces cell death via the TRPM8 channel in the human bladder cancer cell line T24.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The enzyme dihydropyrimidine dehydrogenase (DPD) is involved in the metabolism of 5-fluorouracil (5-FU). The aim of this study was to clarify the correlation between the expression of DPD and the efficacy of 5-FU therapy in patients with lung adenocarcinoma (AD).\n", "We examined surgically resected specimens from 90 stage I to IIIA patients with lung ADs to determine the level of intra-tumoral DPD mRNA.\n", "Administration of 5-FU improved the prognosis of patients with low DPD-expressing tumors, whereas it did not do so for patients with high DPD expressing tumors. Patients with low DPD-expressing tumors administered with 5-FU had a significantly better prognosis than those who underwent surgery alone. A Cox proportional hazards regression model revealed that administration of 5-FU was an independent variable to predict prognosis in patients with low DPD-expressing tumors.\n", "\n", "Question: Does low dihydropyrimidine dehydrogenase correlate with prolonged survival in patients with lung adenocarcinoma treated with 5-fluorouracil?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, low dihydropyrimidine dehydrogenase correlates with prolonged survival in patients with lung adenocarcinoma treated with 5-fluorouracil.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: We assessed the impact of abdominal aortic aneurysm (AAA)-specific simulation training on resident performance in simulated open AAA repair (SOAAAR) and determined whether simulation training required dedicated faculty instruction.\n", "We randomized 18 residents (postgraduate years 3-5) to an AAA simulation course consisting of two mandatory practice sessions proctored either by a surgical skills lab coordinator (Group A, n = 8) or by a vascular surgery faculty instructor (Group B, n = 10). All residents received a detailed manual and video demonstrating the technique of open AAA repair. Using a validated tool, vascular faculty who were blinded to resident identity, level of training, and randomization status graded SOAAAR performance via videos that were recorded before and after the course.\n", "Characteristics and baseline scores between Groups A and B were not different. Postcourse, there was a no significant improvement in performance in Group A. Group B performance was improved significantly from baseline with regard to task-specific checklist scores (44.1 ± 6.3 vs 34.9 ± .5; P = .02), global rating scores (28.4 ± .6 vs 25.3 ± 5.0; P = .049), and overall assessment of operative competence (P = .02). Time to complete SOAAAR improved in both groups (P = .02). Baseline performance varied significantly with year of training as measured by task-specific checklist scores, global rating scores, final product analysis, time to complete repair, and overall operative competence. Improvement varied inversely with year of training (P < .05) and postcourse scores were equivalent for postgraduate year 3-5 residents.\n", "\n", "Question: Does simulation-based training to teach open abdominal aortic aneurysm repair to surgical residents require dedicated faculty instruction?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, simulation-based training to teach open abdominal aortic aneurysm repair to surgical residents requires dedicated faculty instruction, as evidenced by the significant improvement in performance in the group that received instruction from a vascular surgery faculty instructor compared to the group that did not.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The amount of visceral fat mass strongly relates to insulin resistance in humans. The transcription factor peroxisome proliferator activated receptor gamma (PPARG) is abundant in adipocytes and regulates genes of importance for insulin sensitivity. Our objective was to study PPARG activity in human visceral and subcutaneous adipocytes and to compare this with the most common model for human disease, the mouse.\n", "We transfected primary human adipocytes with a plasmid encoding firefly luciferase controlled by PPARG response element (PPRE) from the acyl-CoA-oxidase gene and measured PPRE activity by emission of light.\n", "We found that PPRE activity was 6.6-fold higher (median) in adipocytes from subcutaneous than from omental fat from the same subjects (n = 23). The activity was also 6.2-fold higher in subcutaneous than in intra-abdominal fat cells when we used a PPARG ligand-binding domain-GAL4 fusion protein as reporter, demonstrating that the difference in PPRE activity was due to different levels of activity of the PPARG receptor in the two fat depots. Stimulation with 5 micromol/l rosiglitazone did not induce a PPRE activity in visceral adipocytes that was as high as basal levels in subcutaneous adipocytes. Interestingly, in mice of two different strains the PPRE activity was similar in visceral and subcutaneous fat cells.\n", "\n", "Question: Is peroxisome proliferator activated receptor gamma activity low in mature primary human visceral adipocytes?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, peroxisome proliferator activated receptor gamma activity is low in mature primary human visceral adipocytes compared to subcutaneous adipocytes.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Recently, insoluble fibre from carob pulp has been found to affect blood lipids in animals in a similar manner as soluble dietary fibre.\n", "To investigate whether a carob pulp preparation containing high amounts of insoluble fibre has a beneficial effect on serum cholesterol in humans.\n", "Volunteers (n = 58) with hypercholesterolemia were recruited to participate in a randomised, double- blind, placebo-controlled and parallel arm clinical study with a 6 week intervention phase. All participants consumed daily both, bread (two servings) and a fruitbar (one serving) either with (n = 29) or without (n = 29) a total amount of 15 g/d of a carob pulp preparation (carob fibre). Serum concentrations of total, LDL and HDL cholesterol and triglycerides were assessed at baseline and after week 4 and 6.\n", "The consumption of carob fibre reduced LDL cholesterol by 10.5 +/- 2.2% (p = 0.010). The LDL:HDL cholesterol ratio was marginally decreased by 7.9 +/- 2.2 % in the carob fibre group compared to the placebo group (p = 0.058). Carob fibre consumption also lowered triglycerides in females by 11.3 +/- 4.5% (p = 0.030). Lipid lowering effects were more pronounced in females than in males.\n", "\n", "Question: Does carob pulp preparation rich in insoluble fibre lower total and LDL cholesterol in hypercholesterolemic patients?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, carob pulp preparation rich in insoluble fibre lowers LDL cholesterol in hypercholesterolemic patients.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: An active device that downregulates abdominal vagal signalling has resulted in significant weight loss in feasibility studies.\n", "To prospectively evaluate the effect of intermittent vagal blocking (VBLOC) on weight loss, glycemic control, and blood pressure (BP) in obese subjects with DM2.\n", "Twenty-eight subjects were implanted with a VBLOC device (Maestro Rechargeable System) at 5 centers in an open-label study. Effects on weight loss, HbA1c, fasting blood glucose, and BP were evaluated at 1 week to 12 months.\n", "26 subjects (17 females/9 males, 51 ± 2 years, BMI 37 ± 1 kg/m(2), mean ± SEM) completed 12 months followup. One serious adverse event (pain at implant site) was easily resolved. At 1 week and 12 months, mean excess weight loss percentages (% EWL) were 9 ± 1% and 25 ± 4% (P < 0.0001), and HbA1c declined by 0.3 ± 0.1% and 1.0 ± 0.2% (P = 0.02, baseline 7.8 ± 0.2%). In DM2 subjects with elevated BP (n = 15), mean arterial pressure reduced by 7 ± 3 mmHg and 8 ± 3 mmHg (P = 0.04, baseline 100 ± 2 mmHg) at 1 week and 12 months. All subjects MAP decreased by 3 ± 2 mmHg (baseline 95 ± 2 mmHg) at 12 months.\n", "\n", "Question: Does vagal blocking improve glycemic control and elevated blood pressure in obese subjects with type 2 diabetes mellitus?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, vagal blocking improves glycemic control and reduces elevated blood pressure in obese subjects with type 2 diabetes mellitus, as indicated by the decline in HbA1c and mean arterial pressure in the study.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: In prior analyses, conditional survival (CS) estimates for gastric cancer have weighed clinical and pathologic factors to predict prognosis at time intervals after surgery. Since racial disparities in gastric cancer outcomes were not considered, our objective was to determine whether race influences CS estimates.\n", "Data from the Surveillance, Epidemiology, and End Results cancer registry were used to identify gastric adenocarcinoma patients who underwent curative surgical intervention between 1988 and 2005. Five-year relative conditional survival (RCS) was computed for patients who survived at least 1 to 5 years after surgery. RCS was calculated by assessing observed and expected survival in an age- and race-matched standard population. Results were compared across time and racial groups (white, black, and Asian) using z test statistics.\n", "Of 14,067 patients, 63.8 % were white, 15.5 % black, and 20.7 % Asian. Racial disparities among groups were observed with improved survival of Asians at time point zero and improved RCS at 1 year. At 5 years following curative surgery, each racial group had increased RCS and the greatest magnitude of relative increase was observed in white and black patients (121 and 118 %, respectively). Comparison of RCS at the 5-year time point revealed a reduction of racial disparities in survival among the three groups.\n", "\n", "Question: Do estimates of conditional survival in gastric cancer reveal a reduction of racial disparities with long-term follow-up?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, estimates of conditional survival in gastric cancer reveal a reduction of racial disparities with long-term follow-up.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Organ preservation injury is associated with endothelial cell damage, destabilization of mitochondrial and cell membranes, and the release of proteolytic enzymes. In addition to its well-known clinical effect of reducing perioperative blood loss, aprotinin has antiproteolytic and membrane-stabilizing properties. We hypothesized that adding aprotinin to Euro-Collins (EC) and University of Wisconsin (UW) solutions would decrease preservation injury in cultured endothelial cells and a whole organ rat lung model.\n", "Bovine aortic endothelial cells were cultured and stored in the respective solution at 4 degrees C for 12 or 48 hours. Endothelial cell viability after storage was assessed by dimethylthiazole tetrazolium cytotoxicity assay. In the whole organ model, rat lungs were isolated, flushed with the respective solution, and stored at 4 degrees C for 6 or 12 hours. The lungs were ventilated with 100% O2 and reperfused with fresh blood. Alveolar-arterial O2 difference, O2 tension, capillary filtration coefficient, and compliance were determined.\n", "Endothelial cell viability was optimized with the addition of aprotinin to EC and UW at a dose of 150 KIU/mL (0.02 mg/mL). In the isolated perfused lung model, after 6 hours of ischemic storage, aprotinin-enhanced (100 KIU/mL [0.014 mg/mL]) EC and UW decreased alveolar-arterial O2 difference, increased O2 tension, and decreased capillary filtration coefficient compared with EC and UW alone. After 12 hours of ischemic storage, aprotinin-enhanced EC and UW decreased alveolar-arterial O2 difference, increased O2 tension, decreased capillary filtration coefficient, and increased compliance compared with EC and UW alone.\n", "\n", "Question: Does addition of aprotinin to organ preservation solutions decrease lung reperfusion injury?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, the addition of aprotinin to organ preservation solutions decreases lung reperfusion injury.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Leukemia inhibitory factor (LIF) is known to inhibit myogenic differentiation as well as to inhibit apoptosis and caspase-3 activation in non-differentiating myoblasts. In addition caspase-3 activity is required for myogenic differentiation. Therefore the aim of this study was to further investigate mechanisms of the differentiation suppressing effect of LIF in particular the possibility of a caspase-3 mediated inhibition of differentiation.\n", "LIF dependent inhibition of differentiation appeared to involve several mechanisms. Differentiating myoblasts that were exposed to LIF displayed increased transcripts for c-fos. Transcripts for the cell cycle inhibitor p21 as well as muscle regulatory factors myoD and myogenin were decreased with LIF exposure. However, LIF did not directly induce a proliferative effect under differentiation conditions, but did prevent the proportion of myoblasts that were proliferating from decreasing as differentiation proceeded. LIF stimulation decreased the percentage of cells positive for active caspase-3 occurring during differentiation. Both the effect of LIF inhibiting caspase-3 activation and differentiation appeared dependent on mitogen activated protein kinase and extracellular signal regulated kinase kinase (MEK) signalling. The role of LIF in myogenic differentiation was further refined to demonstrate that myoblasts are unlikely to secrete LIF endogenously.\n", "\n", "Question: Are caspase-3 , myogenic transcription factors and cell cycle inhibitors regulated by leukemia inhibitory factor to mediate inhibition of myogenic differentiation?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, caspase-3, myogenic transcription factors, and cell cycle inhibitors are regulated by leukemia inhibitory factor (LIF) to mediate inhibition of myogenic differentiation.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To identify the genetic defect of a patient with severe hemophilia A (SH9).\n", "PCR, denaturing gradient gel electrophoresis (DGGE) and DNA sequencing were used to screen mutations in the factor VIII gene. Intron 22 inversion was excluded previously by Southern blotting with F8A probe. PCR primers were designed to cover all the coding regions and flanking intron sequences. Amplified products were analysed with DGGE, and bands of abnormal mobility were directly sequenced.\n", "PCR fragment 14-2 showed slower mobility than normal. A single nucleotide substitution C2535A causing a missense mutation in the B domain, 826Asp(GAC)-->Glu(GAA) was identified by DNA sequencing.\n", "\n", "Question: Does [ A novel missense mutation in the B domain of factor VIII cause severe hemophilia A ]?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, a novel missense mutation in the B domain of factor VIII can cause severe hemophilia A.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Neonatal neurodevelopment is influenced by a variety of external factors, although the mechanisms responsible are poorly understood. Prenatal hypoxia, from physiological or chemical sources, can have no discernible effect, or can result in a broad spectrum of abnormalities.\n", "To mimic some of the maternal effects of smoking, we developed a model that investigates the effects of intermittent hypoxia (IH), with or without concurrent nicotine in timed pregnant Sprague-Dawley rats.\n", "We found no significant differences between litter sizes or birthweight of pups from any treatment group, but animals exposed to IH (with or without nicotine) showed long term diminished body weights. Animals subjected to IH consistently showed a transient delay in neuronal migration early in the postpartum period, which was amplified by concurrent nicotine administration. We observed increased c-Abl protein levels in animals from the IH treatment groups. Multiple proteins involved in the intricate control of neuronal migration were also altered in response to this treatment, primarily the downstream targets of c-Abl: Cdk5, p25, and the cytoskeletal elements neurofilament H and F-actin and catalase. Catalase activity and protein levels, already elevated in response to IH, were further amplified by simultaneous nicotine exposure.\n", "\n", "Question: Is neuronal migration transiently delayed by prenatal exposure to intermittent hypoxia?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, neuronal migration is transiently delayed by prenatal exposure to intermittent hypoxia.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The steady increase in end-stage renal disease (ESRD) incidence is a worldwide public health crisis.\n", "To determine whether the increasing incidence of ESRD in the United States is preceded by increased prevalence of chronic renal insufficiency.\n", "Birth cohort analysis.\n", "Nationally representative Second and Third National Health and Nutrition Examination Surveys (NHANES II [1976-1980] and III [1988-1994]) and nationally comprehensive U.S. Renal Data System registry.\n", "Adults, 20 to 74 years of age, surveyed in NHANES II (midpoint, 1978) and NHANES III (midpoint, 1991), and adults, 25 to 79 years of age, who developed ESRD in 1983 and 1996.\n", "Prevalent chronic renal insufficiency (estimated glomerular filtration rate, 15 to 59 mL/min per 1.73 m2) and new ESRD cases.\n", "From 1978 to 1991, the number of adults age 20 to 74 years with chronic renal insufficiency increased from 2.6 to 3.9 million, an increase in prevalence from 1970 to 2460 per 100 000 persons. However, the increased incidence of ESRD was even greater during this period. For every 1000 adults with chronic renal insufficiency in 1978, 9 new cases of ESRD developed in 1983, but every 1000 adults with chronic renal insufficiency in 1991 produced 16 new cases of ESRD in 1996 (relative risk, 1.7 [95% CI, 1.1 to 2.7]).\n", "\n", "Question: Is the incidence of end-stage renal disease increasing faster than the prevalence of chronic renal insufficiency?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, the incidence of end-stage renal disease is increasing faster than the prevalence of chronic renal insufficiency.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: In acetaminophen-induced acute liver failure (ALF), the hepatic coma grade worsens and mortality rates increase, as the number of systemic inflammatory response syndrome components fulfilled (SIRS score) increases. This study aimed to investigate the impact of SIRS score on clinical features of non-acetaminophen-related ALF.\n", "Ninety-nine patients with non-acetaminophen-related ALF with hepatic coma who did not undergo liver transplantation were investigated. Each patient was given a SIRS score of 0, 1, 2, 3 or 4 at the time of diagnosis.\n", "At the diagnosis of ALF with hepatic coma, with the increase of SIRS score, hepatic coma grade and prothrombin activity were deteriorated. After the diagnosis of ALF with hepatic coma, 25 patients (25%) developed acute respiratory distress syndrome (ARDS), 31 patients (31%) developed disseminated intravascular coagulation (DIC), and 21 patients (22%) developed acute renal failure (ARF). Thirty-eight patients (38%) developed MOF. With the increase of SIRS score, frequencies of the development of ARDS, DIC and MOF increased. ARF was more frequently developed in patients with a SIRS score of 2 or higher. Overall, 36 patients (36%) survived. Overall survival rate was 66% in 29 patients with a score of 0, 43% in 21 patients with a score of 1, 17% in 29 patients with a score of 2 and 15% in 20 patients with a score of 3 or 4.\n", "\n", "Question: Does sIRS score reflect clinical features of non-acetaminophen-related acute liver failure with hepatic coma?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, the SIRS score reflects clinical features of non-acetaminophen-related acute liver failure with hepatic coma, as it correlates with the deterioration of hepatic coma grade, prothrombin activity, and the development of complications such as ARDS, DIC, and MOF.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Epidermal growth factor receptor (EGFR)-mediated increase in enterocyte proliferation following massive resection is a major mechanism by which the small intestine adapts to the loss of its mucosal surface area. In addition, expression of the cyclin-dependent kinase inhibitor p21(waf1/cip1) is required for resection-induced enterocyte proliferation. This study sought to establish a mechanistic link between EGFR-mediated intestinal epithelial cell proliferation and p21(waf1/cip1) expression.\n", "EGF was used to stimulate IEC-6 and HCA-7 cells. P21(waf1/cip1) messenger RNA (mRNA) and protein expression were measured by real-time polymerase chain reaction and Western blot, respectively. P21(waf1/cip1) promoter studies were performed using p21(waf1/cip1) promoter-driven luciferase assay. Pharmacologic inhibitors of PI3-kinase and mitogen activated protein kinase (MAPK) were used to block these pathways downstream of the activated EGFR. Constitutively active Ras, Raf, or MEK-1 constructs were transfected into cells for overexpression studies. Cell proliferation was measured by bromodeoxyuridine incorporation following p21(waf1/cip1) silencing with RNAi. Finally, Cyclin D(1)/Cdk interaction was evaluated by immunoprecipitation.\n", "EGFR activation in intestinal epithelial cells induced the expression of p21(waf1/cip1) mRNA and protein This event was transcriptionally regulated via a 50-bp segment of the p21(waf1/cip1) promoter as a result of MAPK activation. Exogenous EGF failed to induce proliferation in p21(waf1/cip1)-silenced cells and adaptive proliferation after intestinal resection in p21(waf1/cip1)-null mice. Functionally, p21(waf1/cip1) up-regulation was required for stabilizing Cyclin D/Cdk 4 complexes and intestinal cell proliferation.\n", "\n", "Question: Does epidermal growth factor receptor-mediated proliferation of enterocytes require p21waf1/cip1 expression?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, epidermal growth factor receptor-mediated proliferation of enterocytes requires p21(waf1/cip1) expression.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Members of the family of ABC transporters are involved in different processes of sterol metabolism, and ABCA1 was recently identified as a key regulator of high-density lipoprotein (HDL) metabolism. Our aim was to further analyze the role of ABCA1 in cholesterol metabolism.\n", "ABCA1-deficient mice (ABCA1-/-) and wild-type mice were compared for different aspects of sterol metabolism. Intestinal cholesterol absorption was determined by a dual stable isotope technique, and analysis of fecal, plasma, and tissue sterols was performed by gas chromatography/mass spectrometry. Key regulators of sterol metabolism were investigated by Northern and Western blot analyses or enzyme activity assays.\n", "ABCA1-disrupted sv129/C57BL/6 hybrid mice showed a significant reduction in intestinal cholesterol absorption. The decrease in cholesterol absorption was followed by an enhanced fecal loss of neutral sterols, whereas fecal bile acid excretion was not affected. Total body cholesterol synthesis was significantly increased, with enhanced 3-hydroxy-3-methyglutaryl-coenzyme A (HMG-CoA) reductase observed in adrenals and spleen. In addition, ABCA1-/- mice showed markedly increased concentrations of cholesterol precursors in the plasma, lung, intestine, and feces. Reduced HMG-CoA reductase messenger RNA and enzyme activity in the liver suggest that enhanced cholesterol synthesis in ABCA1-/- mice occurs in peripheral tissues rather than the liver.\n", "\n", "Question: Does aTP-binding cassette transporter A1 ( ABCA1 ) affect total body sterol metabolism?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, ABCA1 affects total body sterol metabolism.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Stress-induced cardiomyopathy (SIC) is an important differential diagnosis to acute myocardial infarction (AMI) that is associated with significant morbidity and mortality. The typical hallmark of SIC is left-ventricular apical akinesia but preserved function in basal segments. Catecholamines are postulated to play an important role in SIC but the precise pathophysiology is incompletely understood. Whether myocardial perfusion of the affected segments is impaired in SIC has been debated and remains unknown.\n", "Myocardial contrast echocardiography (MCE) was used to study regional myocardial perfusion in a rat model of SIC. Twelve rats received 50 mg/kg isoproterenol (ISO) i.p. and were continuously monitored by MCE. Apical and basal perfusion were estimated and expressed as a ratio at baseline, 5, 10, 20, 30, 40, 50, 60, 70, 80, and 90 min post-ISO. The rats developed typical apical ballooning after 43 ± 9 min post-ISO injection. The ratio of apical:basal perfusion was close to 1.00 at all time-points and never dropped below 0.89 (95% CI never extended below 0.73). Light and electron microcoscopical investigation revealed no structural damage of myocardial vessels.\n", "\n", "Question: Does contrast echocardiography reveal apparently normal coronary perfusion in a rat model of stress-induced ( Takotsubo ) cardiomyopathy?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, contrast echocardiography reveals apparently normal coronary perfusion in a rat model of stress-induced (Takotsubo) cardiomyopathy, as indicated by the ratio of apical:basal perfusion being close to 1.00 and not dropping below 0.89.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Reactive oxygen species (ROS) may mediate pressure overload-induced myocardial hypertrophy. NADPH oxidase may be involved in this process, because its expression and activity are upregulated by pressure overload and because myocardial hypertrophy caused by a subpressor infusion of angiotensin is attenuated in mice deficient in the gp91phox catalytic subunit of NADPH oxidase.\n", "To test the role of NADPH oxidase-dependent ROS in mediating pressure overload-induced myocardial hypertrophy, we subjected transgenic mice lacking gp91phox to chronic pressure overload caused by constriction of the ascending aorta. Contrary to our hypothesis, neither myocardial hypertrophy nor NADPH-dependent superoxide generation was decreased in gp91phox-deficient mice after aortic constriction. Aortic constriction caused an exaggerated increase in p22phox and p47phox mRNA in gp91phox-deficient mice.\n", "\n", "Question: Does pressure overload-induced myocardial hypertrophy in mice require gp91phox?\n", "\n", "Answer:\n", "Predictions: No, pressure overload-induced myocardial hypertrophy in mice does not require gp91phox.\n", "Solutions: no\n", "Score: 1.0\n", "The solution is correct.Questions: Context: A higher proportion of male offspring has been observed after transferring faster-developing embryos in a number of animal species. Therefore, we evaluated the correlation between the sex ratio of delivered babies and the cleavage stage of transferred embryos in a human IVF-ET program.\n", "The sex of infants born (n = 104) after transfer of exclusively slower-cleaving < or = 3 cell (n = 41) versus exclusively faster-cleaving > or = 4 cell (n = 63) embryos was compared. Furthermore, all boys and girls resulting from IVF-ET (n = 213) were compared with respect to: the average number of cells in the embryos that were transferred, the embryo with the greatest number of cells in the cohort transferred and the percentage of embryos that were faster cleaving.\n", "Thirty seven percent (15/41) of infants resulting from the transfer of exclusively slower-growing embryos were girls and 38% (24/36) of the infants from the faster-growing embryos were girls (NS). The analysis all 213 babies born after 145 embryo transfer procedures did not suggest any differences in embryo cleavage rates in embryo transfers leading to male versus female infants.\n", "\n", "Question: Is sex ratio of babies unchanged after transfer of fast- versus slow-cleaving embryos?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: N-3 polyunsaturated fatty acids (n-3 PUFAs), in particular eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), have been shown to effectively improve hepatic steatosis and insulin resistance caused by obesity. Lipodystrophy could also develop insulin resistance and hepatic steatosis. However, the effect of supplemental DHA/EPA to hepatic steatosis caused by lipodystrophy is unknown. In this study, we investigated whether a diet rich in n-3 PUFAs could ameliorate severe steatosis in lipoatrophic seipin gene knockout (SKO) mice.\n", "Eight-week-old C57BL/6 J WT and SKO mice were fed with normal chow diet (NC), or 2 % DHA/EPA (3:1) diet for 12 weeks. Total cholesterol (TC) and triglycerides (TG) in plasma and liver, plasma high density lipoprotein-cholesterol (HDL-C), glucose (Glu), insulin, leptin and adiponectin levels were measured. Gene regulations and protein levels were investigated using quantitative PCR and western blot in liver.\n", "We found that the DHA/EPA diet protected against hepatic steatosis effectively in SKO mice morphologically. Hepatic TG content was decreased about 40 % (p < 0.05) in SKO mice fed with the DHA/EPA diet compared to chow fed SKO controls. Glucose and insulin tolerance were also improved significantly in SKO mice with DHA/EPA diet. In analyzing hepatic gene expression pattern it was found that TG synthesis related genes, such as carbohydrate response element binding protein (ChREBP), stearoyl-CoA desaturase 1 (SCD1) and fatty acid synthase (Fas) were upregulated in SKO mice compared to WT mice but were significantly decreased in SKO mice on DHA/EPA diet. Fatty acid β-oxidation related genes, on the other hand, such as peroxisome proliferator-activated receptor α (PPARα), carnitine palmitoyltransferase (CPT) and acyl-CoA oxidase 1 (ACOX1) were elevated in both WT and SKO groups on DHA/EPA diets. The protein levels of PPARα, SCD1, CPT1α, Insulin receptor substrate 1 (IRS1) and ratio of p-AKT to AKT showed the same tendency as the result of genes expressions.\n", "\n", "Question: Does diet rich in Docosahexaenoic Acid/Eicosapentaenoic Acid robustly ameliorate hepatic steatosis and insulin resistance in seipin deficient lipodystrophy mice?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, the diet rich in Docosahexaenoic Acid/Eicosapentaenoic Acid effectively ameliorates hepatic steatosis and improves insulin resistance in seipin deficient lipodystrophy mice.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Hopea odorata Roxb. (Dipterocarpaceae) is a representative Thai ethnopharmacological herbal plant used in the treatment of various inflammation-related diseases. In spite of its traditional use, systematic studies of its anti-inflammatory action have not been performed.\n", "The inhibitory activities of a Hopea odorata methanol extract (Ho-ME) on the production of nitric oxide (NO), tumour necrosis factor (TNF)-α, and prostaglandin E(2) (PGE(2)) in RAW264.7 cells and peritoneal macrophages were investigated. The effects of Ho-ME on the gastritis symptoms induced by HCl/EtOH and on ear oedemas induced by arachidonic acid were also examined. Furthermore, to identify the immunopharmacological targets of this extract, nuclear fractionation, a reporter gene assay, immunoprecipitation, immunoblot analysis, and a kinase assay were employed.\n", "Ho-ME strongly inhibited the release of NO, PGE(2), and TNF-α in RAW264.7 cells and peritoneal macrophages stimulated by lipopolysaccharide (LPS). Ho-ME also clearly suppressed the gene expression of pro-inflammatory cytokines and chemokines, such as interferon (IFN)-β, interleukin (IL)-12, and monocyte chemotactic protein-1 (MCP-1). By analysing the inhibited target molecules, Syk and Src were found to be suppressed in the inhibition of nuclear factor (NF)-κB pathway. In addition, the observed downregulation of activator protein (AP)-1 and cAMP response element-binding (CREB) was due to the direct inhibition of interleukin-1 receptor-associated kinase (IRAK)1 and IRAK4, which was also linked to the suppression of c-Jun N-terminal kinase (JNK) and p38. In agreement with the in vitro observations, this extract also ameliorated the inflammatory symptoms in EtOH/HCl-induced gastritis and arachidonic acid-induced ear oedemas in mice.\n", "\n", "Question: Does methanol extract of Hopea odorata suppress inflammatory responses via the direct inhibition of multiple kinases?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, the methanol extract of Hopea odorata suppresses inflammatory responses via the direct inhibition of multiple kinases, including IRAK1, IRAK4, JNK, and p38.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Few data are available on the frequency or importance of perioperative atrial tachycardia in infants. We hypothesized that atrial tachycardia in infants undergoing cardiac surgery is not rare and is associated with increased morbidity and mortality.\n", "From 2007 through 2010, 777 infants (median age, 1.8 months; interquartile range, 0.33-5.73) underwent cardiac surgery. Their medical records were reviewed for atrial tachycardia during the perioperative period.\n", "Of the 777 patients, 64 (8.2%) developed atrial tachycardia. The independent risk factors for developing atrial tachycardia included surgical age 6 months or younger (odds ratio, 4.4; 95% confidence interval, 1.1-19.15), use of 3 or more inotropes (odds ratio, 2.9; 95% confidence interval, 1.4-6.2), and heterotaxy syndrome (odds ratio, 2.9; 95% confidence interval, 1.1-7.4). All-cause mortality in the atrial tachycardia group was increased (21.9% vs 7.2%, P<.001) during a median follow-up period of 14.6 months (interquartile range, 6.8-24.6), and atrial tachycardia was independently associated with decreased survival (hazard ratio, 1.9; 95% confidence interval, 1.1-3.8). Infants with perioperative atrial tachycardia had a longer hospital length of stay (32 vs 17 days, P<.001) and duration of inotrope use (10.5 vs 3.0 days, P<.001). A total of 57 patients received antiarrhythmic therapy, with propranolol the most common (n=31). Among the survivors, 48 patients received outpatient antiarrhythmic therapy, which was successfully discontinued in 23 patients at a median duration of 14 months (interquartile range, 5.7-18.6) without recurrence.\n", "\n", "Question: Is perioperative atrial tachycardia associated with increased mortality in infants undergoing cardiac surgery?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, perioperative atrial tachycardia is associated with increased mortality in infants undergoing cardiac surgery, as indicated by the increased all-cause mortality rate in the atrial tachycardia group (21.9% vs 7.2%, P<.001).\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Although patients with chronic hepatitis C (CHC) have been found to have reduced quality of life, little is known about how other characteristics affect their quality of life. The purpose of this study was to investigate the effect of other characteristics, including history of cancer, on quality of life in patients with CHC.\n", "One hundred forty patients from clinics at three hospitals in New York City completed a detailed epidemiologic interview about demographic and lifestyle characteristics and the SF-36 measuring health-related quality of life. We compared results from our patients to normative data using t-tests of differences between means. We used multivariate analyses to determine other personal and health-related factors associated with quality of life outcomes.\n", "Compared to normative data, these patients had reduced quality of life, particularly on physical functioning. The summary Physical Component Score (PCS) was 45.4 +/- 10.6 and the Mental Component Score (MCS) was 48.2 +/- 11.1, vs norms of 50 +/- 10.0; p-values were < 0.0001 and < 0.05, respectively. In multivariate analyses, the PCS was significantly lower among those with cancer history, > or = 2 other chronic conditions, less education, low physical activity, and higher alanine aminotransferase (ALT) levels. Cancer was more important for men, while other chronic conditions were more important for women. On the MCS, history of depression, low physical activity, alcohol use, and female gender were independently associated with poorer scores.\n", "\n", "Question: Do cancer history and other personal factors affect quality of life in patients with hepatitis C?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, cancer history and other personal factors affect quality of life in patients with hepatitis C.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Fusarium oxysporum is among the few filamentous fungi that have been reported of being able to directly ferment biomass to ethanol in a consolidated bioprocess. Understanding its metabolic pathways and their limitations can provide some insights on the genetic modifications required to enhance its growth and subsequent fermentation capability. In this study, we investigated the hypothesis reported previously that phosphoglucomutase and transaldolase are metabolic bottlenecks in the glycolysis and pentose phosphate pathway of the F. oxysporum metabolism.\n", "Both enzymes were homologously overexpressed in F. oxysporum F3 using the gpdA promoter of Aspergillus nidulans for constitutive expression. Transformants were screened for their phosphoglucomutase and transaldolase genes expression levels with northern blot. The selected transformant exhibited high mRNA levels for both genes, as well as higher specific activities of the corresponding enzymes, compared to the wild type. It also displayed more than 20 and 15% higher specific growth rate upon aerobic growth on glucose and xylose, respectively, as carbon sources and 30% higher biomass to xylose yield. The determination of the relative intracellular amino and non-amino organic acid concentrations at the end of growth on glucose revealed higher abundance of most determined metabolites between 1.5- and 3-times in the recombinant strain compared to the wild type. Lower abundance of the determined metabolites of the Krebs cycle and an 68-fold more glutamate were observed at the end of the cultivation, when xylose was used as carbon source.\n", "\n", "Question: Does constitutive homologous expression of phosphoglucomutase and transaldolase increase the metabolic flux of Fusarium oxysporum?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, the constitutive homologous expression of phosphoglucomutase and transaldolase increases the metabolic flux of Fusarium oxysporum, as indicated by the higher specific growth rates and biomass yields observed in the recombinant strain compared to the wild type.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To relate baseline plasma HIV genotypic and virtual phenotypic antiretroviral drug susceptibility to subsequent virological response in patients receiving saquinavir (SQV)-enhancing therapy. Individuals were randomized to receive stavudine (d4T), SQV, and one of ritonavir, nelfinavir, or delavirdine to enhance SQV blood levels.\n", "The protease and reverse transcriptase baseline sequences of 31 treatment-experienced patients were analyzed by genotype and virtual phenotype and were related to viral load at weeks 12 and 24. Genotypic resistance to SQV was defined by the presence of G48V and/or L90M mutations in the protease gene. Potential cross-resistance to d4T in zidovudine (ZDV)-experienced individuals was defined by the presence of thymidine-associated mutations in the reverse transcriptase gene.\n", "ZDV-associated mutations did not affect the virological response at 24 weeks. Individuals who were sensitive to SQV at baseline as determined by either genotyping or virtual phenotyping showed a greater decrease in viral load at week 24 than those resistant to SQV, irrespective of treatment arm. By genotyping, SQV-sensitive individuals had a median log decrease of 1.12 compared to 0.32 for those individuals who were SQV resistant. By virtual phenotyping, SQV-sensitive individuals had a median log decrease of 1.0 compared to a rise of 0.08 in resistant individuals.\n", "\n", "Question: Does baseline antiretroviral drug susceptibility influence treatment response in patients receiving saquinavir-enhancing therapy?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, baseline antiretroviral drug susceptibility influences treatment response in patients receiving saquinavir-enhancing therapy, as those sensitive to SQV showed a greater decrease in viral load compared to those resistant.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC) method can be used to assess the content of glycosaminoglycan in cartilage. In in vitro and model studies, the content of glycosaminoglycan is often expressed in terms of a fixed charge density (FCD). Values of the fixed charge density obtained using the dGEMRIC method differs from values obtained using other methods. The purpose of this work was to further clarify the origin of this discrepancy.\n", "dGEMRIC experiments were performed in a μMRI setup on a custom-designed, well-defined model system capturing the relevant ionic features of cartilage. The model system allows for good control over and systematic variation of relevant parameters. The experimental data was compared with results from Monte Carlo simulations on a coarse-grained model.\n", "Application of ideal Donnan theory on data obtained from experiments as well as simulations lead to underestimation of the fixed charge density, in agreement with previous studies.\n", "\n", "Question: Are electrostatic interactions important for the distribution of Gd ( DTPA ) ( 2- ) in articular cartilage?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, electrostatic interactions are important for the distribution of Gd (DTPA)(2-) in articular cartilage.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Currently, we lack biomarkers to predict whether high-risk women with mammary atypia will respond to tamoxifen chemoprevention.\n", "Thirty-four women with cytologic mammary atypia from the Duke University High-Risk clinic were offered tamoxifen chemoprevention. We tested whether ESR1 promoter hypermethylation and/or estrogen receptor (ER) protein expression by immunohistochemistry predicted persistent atypia in 18 women who were treated with tamoxifen for 12 months and in 16 untreated controls.\n", "We observed a statistically significant decrease in the Masood score of women on tamoxifen chemoprevention for 12 months compared with control women. This was a significant interaction effect of time (0, 6, and 12 months) and treatment group (tamoxifen versus control) P = 0.0007. However, neither ESR1 promoter hypermethylation nor low ER expression predicted persistent atypia in Random Periareolar Fine Needle Aspiration after 12 months tamoxifen prevention.\n", "\n", "Question: Does eSR1 promoter hypermethylation predict atypia in RPFNA nor persistent atypia after 12 months tamoxifen chemoprevention?\n", "\n", "Answer:\n", "Predictions: No, ESR1 promoter hypermethylation does not predict atypia in RPFNA nor persistent atypia after 12 months of tamoxifen chemoprevention.\n", "Solutions: no\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Spontaneous echo contrast (SEC) is thought to represent a risk factor for cardioembolic stroke. In vitro studies suggest that SEC results from interaction between red cells and fibrinogen. To better understand the relation between SEC and stroke and to investigate the in vivo genesis of SEC, we examined the relation between SEC, the constituents of the blood, and plasma and serum viscosity in patients with acute stroke or chronic cerebrovascular disease.\n", "Fifty patients with acute stroke or chronic cerebrovascular disease referred for transesophageal echocardiogram (TEE) were studied by transthoracic echocardiography and TEE. Complete blood count, fibrinogen, albumin, gamma-globulin, and plasma and serum viscosity determinations were made. Left atrial SEC was graded as absent, mild, or marked by means of TEE.\n", "SEC was absent in 31 patients, mild in 10 patients, and marked in 9 patients. Higher grade of SEC was associated with a significantly greater percentage of patients with atrial fibrillation and larger left atrial dimension. Atrial fibrillation was present in 23% of the patients in the SEC absent group, 50% of the patients in the mild SEC group, and 78% of the patients in the marked SEC group (P < .01). Left atrial diameter averaged 3.8 +/- 0.6 cm in the SEC absent group, 4.3 +/- 1.1 in the mild SEC group, and 4.9 +/- 0.7 in the marked SEC group (P < .001). Hematocrit, white blood cell count, and platelet count did not differ among the three groups. Fibrinogen, gamma-globulin, plasma viscosity, and serum viscosity values were all significantly higher in the presence of SEC (P < .05). Fibrinogen values were 361 +/- 97 mg/dL in the SEC absent group and 427 +/- 135 mg/dL in the marked SEC group. gamma-Globulin levels were 0.75 +/- 0.23 g/dL in the SEC absent group and 1.06 +/- 0.48 g/dL in the marked SEC group. Both plasma viscosity (1.97 cp) and serum viscosity (1.64 cp) were higher in the marked SEC group than in the SEC absent group (1.77 and 1.50 cp, respectively).\n", "\n", "Question: Do spontaneous echo contrast and hemorheologic abnormalities in cerebrovascular disease?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Lung contusion (LC) is a common injury resulting from blunt thoracic trauma. LC is an important risk factor for the development acute lung injury, adult respiratory distress syndrome, and ventilator-associated pneumonia, all of which increase mortality from trauma. LC produces a nonspecific immune cellular response. Neutrophil recruitment is known to increase the severity of inflammation during LC. However, the exact role of macrophages in modulating the response to LC has not been well described.\n", "We used a cortical contusion impactor to induce unilateral LC in mice. Thoracic micro computed tomographic scans of these animals were obtained to document radiologic changes over time following LC. To understand the role of macrophages during LC, liposomal clodronate was used to deplete macrophage levels before traumatic insult. Acute inflammatory attributes after LC were assessed, by measuring pressure-volume mechanics; quantifying bronchial alveolar lavage levels of leukocytes, albumin, and cytokines; and finally examining lung specimen histopathology at 5, 24, 48, and 72 hours after injury.\n", "After LC, alveolar macrophage numbers were significantly reduced and exhibited slowed recovery. Simultaneously, there was a significant increase in bronchial alveolar lavage neutrophil counts. The loss of macrophages could be attributed to both cellular apoptosis and necrosis. Pretreatment with clodronate increased the severity of lung inflammation as measured by worsened pulmonary compliance, increased lung permeability, amplification of neutrophil recruitment, and increases in early proinflammatory cytokine levels.\n", "\n", "Question: Does alveolar macrophage depletion increase the severity of acute inflammation following nonlethal unilateral lung contusion in mice?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, alveolar macrophage depletion increases the severity of acute inflammation following nonlethal unilateral lung contusion in mice.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Local anesthetics are used for local irrigation after many types of operations. However, recent evidence of toxic effects of local anesthetics at large concentrations during continuous administration suggests an advantage of using decreased local anesthetic concentrations for irrigation solutions. In this study, we determined whether smaller concentrations of local anesthetics may maintain an antiinflammatory and, therefore, analgesic effect without the risk of possible toxicity. Lidocaine and bupivacaine were studied for their ability to inhibit both components of neurogenic inflammation-C fiber-mediated and sympathetic postganglionic neuron (SPGN)-mediated inflammation-in the rat knee joint. Intraarticular lidocaine 0.02% reduced 5-hydroxytryptamine (5-HT)-induced (SPGN-mediated) plasma extravasation (PE) by 35%, and further decreases were obtained by perfusing larger concentrations of lidocaine. Intraarticular bupivacaine 0.025% inhibited 5-HT-induced PE by 60%, and a 95% inhibition was obtained with bupivacaine 0.05%. Larger local anesthetic concentrations were necessary to inhibit C fiber-mediated PE than those required to inhibit SPGN-mediated PE. Lidocaine 0.4% was required to reduce mustard oil-induced PE by 60%. Lidocaine 2% inhibited mustard oil-induced PE to baseline levels. Bupivacaine 0.1% was required for an 80% reduction of PE. Bupivacaine 0.25% inhibited mustard oil-induced PE to baseline levels. Our results demonstrate differential effects of local anesthetics on SPGN- and C fiber-mediated PE but confirm the concept of using smaller concentrations of local anesthetics to achieve inhibition of postoperative inflammation.\n", "\n", "Question: Do local anesthetics differentially inhibit sympathetic neuron-mediated and C fiber-mediated synovial neurogenic plasma extravasation?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, local anesthetics differentially inhibit sympathetic neuron-mediated and C fiber-mediated synovial neurogenic plasma extravasation.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Current research highlights the role of microcirculatory disorders in post-cardiac arrest patients. Affected microcirculation shows not only dissociation from systemic hemodynamics but also strong connection to outcome of these patients. However, only few studies evaluated microcirculation directly during cardiac arrest (CA) and cardiopulmonary resuscitation (CPR). The aim of our experimental study in a porcine model was to describe sublingual microcirculatory changes during CA and CPR using recent videomicroscopic technology and provide a comparison to parameters of global hemodynamics.\n", "Cardiac arrest was induced in 18 female pigs (50 ± 3 kg). After 3 min without treatment, 5 min of mechanical CPR followed. Continuous hemodynamic monitoring including systemic blood pressure and carotid blood flow was performed and blood lactate was measured at the end of baseline and CPR. Sublingual microcirculation was assessed by the Sidestream Dark Field (SDF) technology during baseline, CA and CPR. Following microcirculatory parameters were assessed off-line separately for capillaries (≤20 µm) and other vessels: total and perfused vessel density (TVD, PVD), proportion of perfused vessels (PPV), microvascular flow index (MFI) and heterogeneity index (HI).\n", "In comparison to baseline the CA small vessel microcirculation was only partially preserved: TVD 15.64 (13.59-18.48) significantly decreased to 12.51 (10.57-13.98) mm/mm(2), PVD 15.57 (13.56-17.80) to 5.53 (4.17-6.60) mm/mm(2), PPV 99.64 (98.05-100.00) to 38.97 (27.60-46.29) %, MFI 3.00 (3.00-3.08) to 1.29 (1.08-1.58) and HI increased from 0.08 (0.00-0.23) to 1.5 (0.71-2.00), p = 0.0003 for TVD and <0.0001 for others, respectively. Microcirculation during ongoing CPR in small vessels reached 59-85 % of the baseline values: TVD 13.33 (12.11-15.11) mm/mm(2), PVD 9.34 (7.34-11.52) mm/mm(2), PPV 72.34 (54.31-87.87) %, MFI 2.04 (1.58-2.42), HI 0.65 (0.41-1.07). The correlation between microcirculation and global hemodynamic parameters as well as to lactate was only weak to moderate (i.e. Spearman's ρ 0.02-0.51) and after adjustment for multiple correlations it was non-significant.\n", "\n", "Question: Does microcirculatory blood flow during cardiac arrest and cardiopulmonary resuscitation correlate with global hemodynamics : an experimental study?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"No, the correlation between microcirculation and global hemodynamic parameters was only weak to moderate and non-significant after adjustment for multiple correlations.\"\n", "Solutions: no\n", "Score: 1.0\n", "The solution is correct.Questions: Context: A previous study found that, with repeated exposure to slipping during a sit-to-stand task, fall incidence decreased at a similar exponential rate in young and older adults. This study investigated the adaptations responsible for this decrease.\n", "Slips were induced, using bilateral low-friction platforms, during a sit-to-stand in 60 young and 41 older healthy safety-harnessed adults. Participants underwent 5 slips, then a 6th slip (reslip) after 3-4 nonslipping trials. Between-trial adjustments in body center of mass state at seat-off were examined and correlated to the likelihoods of falling and stepping. Changes in reactive response between the first slip and reslip were investigated.\n", "With repeated slipping, both young and older adults adjusted to increase their center of mass anterior position and forward velocity at seat-off (p <.001), contributing to decreased fall incidence and changes in step incidence and direction (p <.001). These proactive adjustments predicted fall incidence well in later trials, but underpredicted fall incidence upon the first slip by 9%-21%, suggesting that reactive response deficiencies also initially contributed to falls by both age groups. Ten participants who initially fell without stepping adapted by stepping to recover upon the reslip. Thirty-six participants who stepped backward initially and upon the reslip altered their nonstepping limb reactive response to reduce hip vertical descent during the step (p <.001).\n", "\n", "Question: Do young and older adults exhibit proactive and reactive adaptations to repeated slip exposure?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, young and older adults exhibit proactive and reactive adaptations to repeated slip exposure.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The aim of the study was to investigate the role of lymphangiogenesis in human cervical cancer progression.\n", "The expression of VEGF-C, VEGF-D, VEGFR-3, podoplanin (D2-40), LYVE-1 and Prox-1 was studied by immunohistochemistry in 72 cases of invasive squamous cell carcinoma of the uterine cervix. For lymphatic endothelial markers lymphatic vessel density (LVD) was assessed. Correlations with lymphatic vessel invasion, nodal metastases, tumour grade, FIGO stage, and inflammation were also evaluated.\n", "VEGF-D expression significantly correlated with lymph node metastasis, lymphatic emboli and FIGO stage as well as with peritumoural LVD. A marginally significant correlation was also found between the expression of VEGF-C and prognostic parameters. Lymphatic tumour emboli were successfully identified using D2-40 immunohistochemistry and peritumoural D2-40 LVD significantly correlated with lymphatic vessel invasion. However, LVD as assessed by multiple lymphatic markers was not associated with lymphatic metastasis. There was a significant correlation of Prox-1 and LYVE-1 LVD with the inflammatory stromal reaction.\n", "\n", "Question: Is tumour expression of lymphangiogenic growth factors but not lymphatic vessel density implicated in human cervical cancer progression?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\n", "\"Yes, the study indicates that tumour expression of lymphangiogenic growth factors, such as VEGF-C and VEGF-D, is implicated in human cervical cancer progression, while lymphatic vessel density (LVD) was not associated with lymphatic metastasis.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: We sought to test the hypothesis that training medical assistants to provide health coaching would improve patients' experience of care received and overall satisfaction with their clinic.\n", "Randomized controlled trial.\n", "Low-income English- or Spanish-speaking patients aged 18 to 75 years with poorly controlled type 2 diabetes, hypertension, and/or hyperlipidemia were randomized to receive either a health coach or usual care for 12 months. Patient care experience was measured using the Patient Assessment of Chronic Illness Care (PACIC) scale at baseline and at 12 months. Patient overall satisfaction with the clinic was assessed with a single item asking if they would recommend the clinic to a friend or family member. PACIC and satisfaction scores were compared between study arms using generalized estimating equations to account for clustering at the clinician level.\n", "PACIC scores were available from baseline and at 12 months on 366 (76%) of the 441 patients randomized. At baseline, patients receiving health coaching were similar to those in the usual care group with respect to demographic and other characteristics, including mean PACIC scores (3.00 vs 3.06) and the percent who would \"definitely recommend\" their clinic (73% and 73%, respectively). At 12 months, coached patients had a significantly higher mean PACIC score (3.82 vs 3.13; P < .001) and were more likely to report they would definitely recommend their clinic (85% vs 73%; P = .002).\n", "\n", "Question: Does health coaching by medical assistants improve patients ' chronic care experience?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, health coaching by medical assistants improves patients' chronic care experience.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To determine the biochemical defects that underlie Axenfeld-Rieger malformations, to determine a functional role for wing 2 in FOXC1, and to understand how mutations in this region disrupt FOXC1 function.\n", "Sequencing DNA from patients with Axenfeld-Rieger malformation resulted in the identification of two novel missense mutations (G165R and R169P) in wing 2 of FOXC1. Site-directed mutagenesis was used to introduce these mutations, as well as previously reported mutation (M161K), into the FOXC1 cDNA. These FOXC1 mutants were evaluated to determine their ability to localize to the nucleus, bind DNA and activate gene expression.\n", "Two novel missense mutations were identified in unrelated patients, in wing 2 of the FOXC1 forkhead domain. Because there had been no previous biochemical analysis, the mutation M161K was also investigated. All three mutant proteins localized correctly to the nucleus. The G165R mutation maintained wild-type levels of DNA binding; however, both the M161K and R169P mutations displayed reduced DNA binding ability. Biochemical analysis showed that all three mutations disrupt FOXC1's transactivation ability.\n", "\n", "Question: Is the wing 2 region of the FOXC1 forkhead domain necessary for normal DNA-binding and transactivation functions?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, the wing 2 region of the FOXC1 forkhead domain is necessary for normal DNA-binding and transactivation functions, as mutations in this region disrupt these abilities.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The aim of the present conventional observational study was to compare the clinical outcomes of initial non-weight-bearing therapy and conventional relative rest therapy among elderly patients with clinical vertebral fractures.\n", "In total, 196 consecutive patients with clinical vertebral fractures (mean age: 78 years) who were hospitalized for treatment between January 1999 and March 2007 were analyzed. Initial non-weight-bearing therapy consisted of complete bed rest allowing rolling on the bed without any weight-bearing to the spine for 2 weeks, followed by rehabilitation wearing a soft brace. The indications for initial non-weight-bearing therapy were vertebral fracture involving the posterior portion of the vertebral body at the thoraco-lumbar spine, mild neurological deficit, instability of the fracture site, severe pain, multiple vertebral fractures arising from trauma, malalignment at the fracture site, and mild spinal canal stenosis caused by the fracture. Patients who met the indication criteria were treated with initial non-weight-bearing therapy (n = 103), while the other patients were treated with conventional relative rest (n = 93). All the patients were uniformly treated with intramuscular elcatonin to relieve pain. The primary endpoint was progression of the vertebral fracture. The secondary endpoints included bony union and subjective back pain. The follow-up period was 12 weeks.\n", "Compared with the conventional relative rest group, the collapse rate of the anterior and posterior portions of the vertebral body was significantly smaller in the initial non-weight-bearing group. The bony union rate was 100% in the initial non-weight-bearing group and 97% in the conventional relative rest group. The number of patients who experienced back pain was significantly lower in the initial non-weight-bearing group than in the conventional relative rest group.\n", "\n", "Question: Is initial non-weight-bearing therapy important for preventing vertebral body collapse in elderly patients with clinical vertebral fractures?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, initial non-weight-bearing therapy is important for preventing vertebral body collapse in elderly patients with clinical vertebral fractures, as it resulted in a significantly smaller collapse rate compared to conventional relative rest therapy.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.\n", "{'name': 'context_analysis3328', 'description': 'Task to context_analysis3328. Takes question as input. Produces context as output.', 'inputs': [{'name': 'question', 'type': 'str', 'description': 'Input parameter question for context_analysis3328', 'required': False}], 'outputs': [{'name': 'context', 'type': 'str', 'description': 'Output parameter context from context_analysis3328', 'required': True}], 'prompt': '```xml\\n\"\"\"\\nAnalyze the context of the question step by step to ensure a relevant and accurate response. Begin by identifying key components of the question and any potential ambiguities. Explain your thought process clearly in the field, detailing how you arrived at your conclusions. Provide the final answer in the field, ensuring it directly addresses the clarified question. Format your output in XML, using {thought} and {answer}.\\n\"\"\"\\n```', 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"Think step by step to answer the question based on the question context. You should integrate context for answering. You should explain your thinking process in the 'thought' field, and provide the final answer in the 'answer' field.\\nFormat your output in xml format, such as xxx and xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[32m2026-01-06 08:43:14.495\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.276 | Total tokens: 6482945 | Current cost: $0.003 | Current tokens: 20532\u001b[0m\n", "\u001b[32m2026-01-06 08:43:15.603\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.276 | Total tokens: 6483098 | Current cost: $0.000 | Current tokens: 153\u001b[0m\n", "\u001b[32m2026-01-06 08:43:17.358\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.276 | Total tokens: 6483981 | Current cost: $0.000 | Current tokens: 883\u001b[0m\n", "{'name': 'handle_ambiguities7850', 'description': 'Task to handle_ambiguities7850. Takes context as input. Produces clarified_question as output.', 'inputs': [{'name': 'context', 'type': 'str', 'description': 'Input parameter context for handle_ambiguities7850', 'required': False}], 'outputs': [{'name': 'clarified_question', 'type': 'str', 'description': 'Output parameter clarified_question from handle_ambiguities7850', 'required': True}], 'prompt': '```xml\\n\"\"\"\\nTo effectively answer the question, follow these steps:\\n\\n1. Analyze the context derived from `{context}` to identify any specific nuances or details that may influence the answer.\\n2. If ambiguities are present, clarify the question by addressing specific aspects that need further explanation or detail.\\n3. Integrate the clarified context into your reasoning process to ensure the answer is relevant and comprehensive.\\n4. Provide a clear and concise final answer in the `{answer}` field, ensuring it directly addresses the user\\'s inquiry and incorporates any necessary details or examples.\\n\\nFormat your output in XML format, using to explain your reasoning process and for the final response.\\n\"\"\"\\n```', 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"Think step by step to answer the question based on the question context. You should integrate context for answering. You should explain your thinking process in the 'thought' field, and provide the final answer in the 'answer' field.\\nFormat your output in xml format, such as xxx and xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n", "\u001b[32m2026-01-06 08:43:19.884\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.279 | Total tokens: 6504517 | Current cost: $0.003 | Current tokens: 20536\u001b[0m\n", "\u001b[32m2026-01-06 08:43:22.299\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.280 | Total tokens: 6504833 | Current cost: $0.000 | Current tokens: 316\u001b[0m\n", "\u001b[32m2026-01-06 08:43:24.584\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.280 | Total tokens: 6506038 | Current cost: $0.000 | Current tokens: 1205\u001b[0m\n", "{'name': 'generate_answer', 'description': 'Draft an answer using the retrieved context.', 'inputs': [{'name': 'question', 'type': 'str', 'description': 'The original question from the user.', 'required': True}], 'outputs': [{'name': 'draft_answer', 'type': 'str', 'description': 'A concise, direct answer to the question.', 'required': True}], 'prompt': '\"\"\"\\nYou can think to generate answers based on the provided {question}. Ensure that your response is clear and concise, considering whether a simple \"Yes\" or \"No\" is sufficient or if a more nuanced answer is required. If the {question} is ambiguous or lacks detail, indicate this in your response and suggest specific clarifying questions to gather more information. Format your final answer in the \\'answer\\' field as xxx. If the draft answer requires significant revision, note the necessary changes before proceeding to validation. Prioritize and weigh evidence carefully to enhance the reliability of your answer.\\n\"\"\"', 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"You can think to generate answers. You should provide the final answer (either Yes or No) in the 'answer' field. Format your answer in xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n", "\u001b[32m2026-01-06 08:43:26.637\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.283 | Total tokens: 6526505 | Current cost: $0.003 | Current tokens: 20467\u001b[0m\n", "\u001b[32m2026-01-06 08:43:29.179\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.284 | Total tokens: 6526815 | Current cost: $0.000 | Current tokens: 310\u001b[0m\n", "\u001b[32m2026-01-06 08:43:31.146\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.284 | Total tokens: 6527962 | Current cost: $0.000 | Current tokens: 1147\u001b[0m\n", "{'name': 'validate_answer9330', 'description': 'Task to validate_answer9330. Takes draft_answer as input. Produces validated_answer as output.', 'inputs': [{'name': 'draft_answer', 'type': 'str', 'description': 'Input parameter draft_answer for validate_answer9330', 'required': False}], 'outputs': [{'name': 'validated_answer', 'type': 'str', 'description': 'Output parameter validated_answer from validate_answer9330', 'required': True}], 'prompt': '\"\"\"\\nThink step by step to answer the question based on the context provided in {question}. Begin by identifying the key components, underlying issues, and any ambiguities within the question. In the \\'thought\\' field, explain your reasoning process, detailing how you arrived at your conclusions and addressing any complexities present in the question. If ambiguities are identified, clarify them before proceeding. Then, provide a clear and concise final answer in the \\'answer\\' field, ensuring it is directly relevant to the user\\'s needs. Format your output in XML format, such as {thought} and {answer}.\\n\"\"\"', 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"Think step by step to answer the question based on the question context. You should integrate context for answering. You should explain your thinking process in the 'thought' field, and provide the final answer in the 'answer' field.\\nFormat your output in xml format, such as xxx and xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n", "\u001b[32m2026-01-06 08:43:33.826\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.287 | Total tokens: 6548480 | Current cost: $0.003 | Current tokens: 20518\u001b[0m\n", "\u001b[32m2026-01-06 08:43:34.900\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.287 | Total tokens: 6548624 | Current cost: $0.000 | Current tokens: 144\u001b[0m\n", "\u001b[32m2026-01-06 08:43:37.086\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.288 | Total tokens: 6549657 | Current cost: $0.000 | Current tokens: 1033\u001b[0m\n", "{'name': 'evaluate_answer9619', 'description': 'Task to evaluate_answer9619. Takes validated_answer as input. Produces evaluation_score as output.', 'inputs': [{'name': 'validated_answer', 'type': 'str', 'description': 'Input parameter validated_answer for evaluate_answer9619', 'required': False}], 'outputs': [{'name': 'evaluation_score', 'type': 'str', 'description': 'Output parameter evaluation_score from evaluate_answer9619', 'required': True}], 'prompt': '\"\"\"\\nThink step by step to answer the question based on the context provided in {question}. Begin by analyzing the key components of the question to identify the main issue and any underlying factors. If the question is ambiguous, clarify the necessary details before proceeding. Integrate this context into your reasoning process. In the \\'thought\\' field, explain your reasoning, how you arrived at your conclusion, and any clarifications made. Provide the final answer in the \\'answer\\' field, ensuring it directly addresses the main issue identified. Format your output in XML format, such as {thought} and {answer}. Additionally, ensure that your answer is validated against predefined criteria for accuracy and relevance before finalizing it, and be prepared to revisit earlier steps based on the evaluation score if necessary.\\n\"\"\"', 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"Think step by step to answer the question based on the question context. You should integrate context for answering. You should explain your thinking process in the 'thought' field, and provide the final answer in the 'answer' field.\\nFormat your output in xml format, such as xxx and xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[32m2026-01-06 08:43:41.028\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.291 | Total tokens: 6570183 | Current cost: $0.003 | Current tokens: 20526\u001b[0m\n", "\u001b[32m2026-01-06 08:43:43.694\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.291 | Total tokens: 6570478 | Current cost: $0.000 | Current tokens: 295\u001b[0m\n", "\u001b[32m2026-01-06 08:43:45.814\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.291 | Total tokens: 6571758 | Current cost: $0.000 | Current tokens: 1280\u001b[0m\n", "{'name': 'feedback_loop7764', 'description': 'Task to feedback_loop7764. Takes evaluation_score, draft_answer as input. Produces improved_answer as output.', 'inputs': [{'name': 'evaluation_score', 'type': 'str', 'description': 'Input parameter evaluation_score for feedback_loop7764', 'required': False}, {'name': 'draft_answer', 'type': 'str', 'description': 'Input parameter draft_answer for feedback_loop7764', 'required': False}], 'outputs': [{'name': 'improved_answer', 'type': 'str', 'description': 'Output parameter improved_answer from feedback_loop7764', 'required': True}], 'prompt': '\"\"\"\\nThink step by step to answer the question based on the context derived from {question}. Begin by analyzing the context to identify any ambiguities or complexities in the inquiry. Then, integrate this context into your reasoning process to formulate a well-informed answer. In the \\'thought\\' field, explain your reasoning, including how the context influenced your answer. Provide the final answer in the \\'answer\\' field, ensuring it is clear and directly addresses the user\\'s question.\\nFormat your output in xml format, such as xxx and xxx.\\n\"\"\"', 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"Think step by step to answer the question based on the question context. You should integrate context for answering. You should explain your thinking process in the 'thought' field, and provide the final answer in the 'answer' field.\\nFormat your output in xml format, such as xxx and xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n", "\u001b[32m2026-01-06 08:44:01.777\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.295 | Total tokens: 6592252 | Current cost: $0.003 | Current tokens: 20494\u001b[0m\n", "\u001b[32m2026-01-06 08:44:03.352\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.295 | Total tokens: 6592402 | Current cost: $0.000 | Current tokens: 150\u001b[0m\n", "\u001b[32m2026-01-06 08:44:04.776\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.295 | Total tokens: 6593283 | Current cost: $0.000 | Current tokens: 881\u001b[0m\n", "\u001b[32m2026-01-06 08:44:04.779\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.optimizers.qastructure_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m1054\u001b[0m - \u001b[1mEvaluate the workflow at step 3 ...\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Evaluating workflow: 2%|▏ | 1/50 [00:01<01:21, 1.67s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 4%|▍ | 2/50 [00:03<01:20, 1.67s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 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"text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Evaluating workflow: 100%|██████████| 50/50 [01:28<00:00, 1.78s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "\u001b[32m2026-01-06 08:45:33.607\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.optimizers.qastructure_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m1057\u001b[0m - \u001b[1mStep 3 metrics: {'f1': 0.0, 'em': 0.0, 'acc': 0.94}\u001b[0m\n", "randomly update dataset\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[32m2026-01-06 08:45:37.549\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.309 | Total tokens: 6663232 | Current cost: $0.003 | Current tokens: 19899\u001b[0m\n", "\u001b[32m2026-01-06 08:45:39.633\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.312 | Total tokens: 6682969 | Current cost: $0.003 | Current tokens: 19737\u001b[0m\n", "\u001b[32m2026-01-06 08:45:41.485\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.316 | Total tokens: 6702701 | Current cost: $0.003 | Current tokens: 19732\u001b[0m\n", "\u001b[32m2026-01-06 08:45:43.310\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.316 | Total tokens: 6703451 | Current cost: $0.000 | Current tokens: 750\u001b[0m\n", "The workflow exhibits several critical issues: it lacks a defined step for integrating context analysis with answer generation, risking disjointed responses and misinterpretations. Validation criteria for \"validated answers\" are inadequately specified, allowing incorrect responses to pass unchecked. The control flow is flawed, failing to ensure that context analysis precedes answer generation and does not account for low evaluation scores, which could result in unrefined outputs. Additionally, the feedback loop lacks mechanisms for learning from past errors and does not clarify how improvements will be implemented. Several prompts are ambiguous or misleading, lacking specificity regarding the materials, expected outcomes, or parameters being measured, which may lead to confusion in interpreting the questions.\n", "\u001b[32m2026-01-06 08:45:45.298\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.316 | Total tokens: 6704275 | Current cost: $0.000 | Current tokens: 824\u001b[0m\n", "```python\n", "steps = [\n", "{'name': 'context_analysis3328', 'args': ['question'], 'outputs': ['context']},\n", "{'name': 'handle_ambiguities7850', 'args': ['context'], 'outputs': ['clarified_question']},\n", "{'name': 'generate_answer', 'args': ['clarified_question'], 'outputs': ['draft_answer']},\n", "{'name': 'validate_answer9330', 'args': ['draft_answer'], 'outputs': ['validated_answer']},\n", "{'name': 'evaluate_answer9619', 'args': ['validated_answer'], 'outputs': ['evaluation_score']},\n", "{'name': 'feedback_loop7764', 'args': ['evaluation_score', 'draft_answer'], 'outputs': ['improved_answer']}\n", "]\n", "```\n", "Questions: Context: The aim of the study was to analyze whether female sex hormones and other factors connected with the female sex could increase the risk of differentiated thyroid cancer (DTC).\n", "Ninety-nine patients with a mean age±SD of 40.5±5.9 years with DTC and 51 healthy women with a mean age of 36.52±8.3 years were examined. Gynecological and obstetric histories were taken and serum estradiol and progesterone levels were analyzed in all women.\n", "Patients with DTC had more frequent menstrual cycle disturbances, used hormone-containing medicines more frequently, were mulitiparous more frequently, had spontaneous miscarriages more frequently, and their duration of lactation was significantly shorter than in controls. The mean serum estradiol level±SD in women with DTC was significantly higher than in the controls, in the follicular phase 193.74±66.31 vs. 157.63±42.88 pmol/l and in the luteal phase 519±176.9 vs. 369±71.49 pmol/l. The mean serum progesterone level±SD was higher in the controls than in patients with DTC, in the follicular phase: 2.11±0.70 vs. 1.38±0.56 nmol/l and in the luteal phase 20.95±17.46 vs. 17.31±12.28 nmol/l.\n", "\n", "Question: Do factors connected with the female sex seem to play an important role in differentiated thyroid cancer?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, factors connected with the female sex seem to play an important role in differentiated thyroid cancer, as indicated by the differences in hormonal levels and reproductive histories between patients with DTC and healthy controls.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To investigate the mechanism of Advanced glycation end products (AGEs) promoting the calcification of smooth muscle cells.\n", "The successfully cultured smooth muscle cells were divided into three groups: normal culture group (group A), calcified culture group (group B), calcification + AGEs group (group C); the concentration of intracellular calcium ion was detected in each group; the promotion of AGEs on the calcification of HSMCs was confirmed by VON KOSSA staining; and the expressions of β-catenin, RAGE, β-catenin, OPG and E-cadherin protein were detected by immunofluorescence and western blot.\n", "The morphology of the cells in each group showed that the amount of calcified plaques in calcification + AGES group were significantly higher than the calcification group. VON KOSSA staining showed that with increasing concentrations of AGE-BSA, the amount of its calcification gradually increased. Calcium concentration in Calcification + 20 mg/L AGEs group was significantly higher, followed by 40 mg/L AGEs group. The expression of β-catenin increased with the increasing concentrations of AGEs.\n", "\n", "Question: Do advanced glycation endproducts regulate smooth muscle cells calcification in cultured HSMCs?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, advanced glycation endproducts regulate smooth muscle cells calcification in cultured HSMCs.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To search candidate tumor suppressor genes (TSGs) on chromosome 4q through detecting high loss of heterozygosity (LOH) regions in sporadic colorectal carcinoma in Chinese patients.\n", "Thirteen fluorescent labeled polymorphic microsatellite markers were analyzed in 83 cases of colorectal carcinoma and matched normal tissue DNA by polymerase chain reaction (PCR). PCR products were electrophoresed on an ABI 377 DNA sequencer. Genescan 3.7 and Genotype 3.7 software were used for LOH scanning and analysis. Comparison between LOH frequency and clinicopathological factors were performed by c2 test.\n", "Data were collected on all informative loci. The average LOH frequency on 4q was 28.56%. The D4S2915 locus showed highest LOH frequency (36.17%). Two obvious deletion regions were detected: one between D4S3000 and D4S2915 locus (4q12-21.1), another flanked by D4S407 and D4S2939 locus (4q25-31.1). None case showed complete deletion of 4q, most cases displayed interstitial deletion pattern solely. Furthermore, compared with clinicopathological features, a significant relationship was observed between LOH frequencies on D4S3018 locus. In tumors larger than 5 cm in diameter, LOH frequency was significantly higher than tumors that were less than 5 cm (56% vs 13.79%, P = 0.01). On D4S1534 locus, LOH was significantly associated with liver metastasis (80% vs 17.25%, P = 0.012). No relationship was detected on other locus compared with clinicopathological features.\n", "\n", "Question: Do tumor suppress genes screening analysis on 4q in sporadic colorectal carcinoma?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, tumor suppressor genes screening analysis on 4q in sporadic colorectal carcinoma was conducted as described in the context.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Pulmonary metastasis of hepatocellular carcinoma (HCC) could be defined as advanced HCC and systematic treatment is the main therapeutic modality. However, local therapy of intrahepatic tumor, which is significantly associated with the prognosis of HCC, remains important for advanced HCC.\n", "Twenty-six HCC patients with pulmonary metastasis underwent intrahepatic transcatheter arterial chemoembolization (TACE). We investigated the progression of lung metastastic tumors, overall survival and risk factors related to survival of these patients.\n", "Of the 26 patients who underwent TACE for one to four times, 10 patients achieved complete remission (CR) of intrahepatic tumors and among these 10 patients, 4 patients successfully received hepatic artery-venous shunt embolization combined with TACE. The lung metastasis lesions also achieved CR and the survival time was significantly longer than the other 22 patients. The lung metastastic lesions of the other 6 patients of intrahepatic tumors achieved stable disease (SD). Six patients acquired partial remission (PR) of intrahepatic tumors after TACE, while the lung metastastic lesions showed SD or progress disease (PD). Patients who showed CR and PR of intrahepatic tumors had longer survival time than patients with SD and PD. Portal vein tumor thrombus and size of the lung metastastic lesions were significant prognostic factors in these advanced HCC patients.\n", "\n", "Question: Does pure transcatheter arterial chemoembolization therapy for intrahepatic tumors cause a shrink in pulmonary metastases of hepatocellular carcinoma?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, pure transcatheter arterial chemoembolization therapy for intrahepatic tumors can cause a shrink in pulmonary metastases of hepatocellular carcinoma, as evidenced by the complete remission of lung metastasis lesions in some patients who achieved complete remission of intrahepatic tumors.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Type 2 diabetes is frequently associated with co-morbidities, including hypertension. Here we investigated if hypertension is a critical factor in myocardial remodeling and the development of cardiac dysfunction in type 2 diabetic db/db mice.\n", "Thereto, 14-wks-old male db/db mice and non-diabetic db/+ mice received vehicle or angiotensin II (AngII) for 4 wks to induce mild hypertension (n = 9-10 per group). Left ventricular (LV) function was assessed by serial echocardiography and during a dobutamine stress test. LV tissue was subjected to molecular and (immuno)histochemical analysis to assess effects on hypertrophy, fibrosis and inflammation.\n", "Vehicle-treated diabetic mice neither displayed marked myocardial structural remodeling nor cardiac dysfunction. AngII-treatment did not affect body weight and fasting glucose levels, and induced a comparable increase in blood pressure in diabetic and control mice. Nonetheless, AngII-induced LV hypertrophy was significantly more pronounced in diabetic than in control mice as assessed by LV mass (increase +51% and +34%, respectively, p<0.01) and cardiomyocyte size (+53% and +31%, p<0.001). This was associated with enhanced LV mRNA expression of markers of hypertrophy and fibrosis and reduced activation of AMP-activated protein kinase (AMPK), while accumulation of Advanced Glycation End products (AGEs) and the expression levels of markers of inflammation were not altered. Moreover, AngII-treatment reduced LV fractional shortening and contractility in diabetic mice, but not in control mice.\n", "\n", "Question: Is hypertension a conditional factor for the development of cardiac hypertrophy in type 2 diabetic mice?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, hypertension is a conditional factor for the development of cardiac hypertrophy in type 2 diabetic mice, as indicated by the more pronounced LV hypertrophy observed in diabetic mice compared to control mice following AngII treatment.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Although morbidity and mortality rates from asthma are highest in patients > 65 years of age, the effect of older age on airway inflammation in asthma is not well established.\n", "To investigate age-related differences in the promotion of allergic inflammation after influenza A viral respiratory infection on antigen-specific IgE production, antigen-induced airway inflammation and airway hyperresponsiveness in mice.\n", "To accomplish this objective, the following model system was used. Young (6 week) and aged (18 months) BALB/c mice were first infected with a non-lethal dose of influenza virus A (H/HKx31). Mice were then ovalbumin (OVA)-sensitized during the acute infection (3-days post inoculation) and then chronically underwent challenge to the airways with OVA. Forty-eight hours after the final OVA challenge, airway hyperresponsiveness (AHR), bronchoalveolar fluid (BALF) cellular and cytokine profile, antigen-specific IgE and IgG1, and lung tissue inflammation were measured.\n", "Age-specific differences were noted on the effect of a viral infection, allergic sensitization, airway inflammation and airway hyperresponsiveness. Serum OVA-specific IgE was significantly increased in only the aged mice infected with influenza virus. Despite greater morbidity (e.g. weight loss and sickness scores) during the acute infection in the 18-month old mice that were OVA-sensitized, there was little effect on the AHR and BALF cellular differential. In contrast, BALF neutrophils and AHR increased, but eosinophils decreased in 6-week mice that were OVA-sensitized during an acute influenza infection.\n", "\n", "Question: Does influenza A infection enhance antigen-induced airway inflammation and hyperresponsiveness in young but not aged mice?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, influenza A infection enhances antigen-induced airway inflammation and hyperresponsiveness in young mice but not in aged mice.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Numerous patients will develop recurrent disease after esophagectomy for esophageal carcinoma (EC). In literature, survival after recurrent EC is poor with 6-8 months. In these studies, diagnostic imaging during follow-up (FU) is routinely performed. In the Netherlands, routine imaging is not part of FU and only performed on indication. The aim of this study was to determine survival after diagnosis of recurrent disease in patients after esophagectomy without routine imaging during FU.\n", "All EC patients who underwent esophagectomy between 1993 and 2010 were included and followed for clinical evidence of recurrent EC. Location, symptoms, diagnosis, and treatment of recurrent disease were registered. Pattern of recurrence was compared between patients who underwent neoadjuvant therapy and patients who underwent surgery alone. Survival after detection of recurrence was determined in all patients and related to the year of surgery.\n", "A total of 493 of 1,088 patients (45 %) who underwent esophagectomy between 1993 and 2010 developed recurrent disease. Median interval between esophagectomy and recurrence was 10.5 months. Within the first 2 years after surgery, 33 % of patients developed recurrent EC. The majority of patients (51 %) were diagnosed with distant metastases. Locoregional recurrence occurred significantly less often among patients who underwent neoadjuvant therapy (6 vs 16 %, p = .017). Median survival after diagnosis of recurrent disease was 3 months. No relation was observed between the year of surgery and survival after recurrent disease (p = .931).\n", "\n", "Question: Has survival after recurrent esophageal carcinoma improved over the past 18 years?\n", "\n", "Answer:\n", "Predictions: No, the study found no relation between the year of surgery and survival after recurrent disease, indicating that survival has not improved over the past 18 years.\n", "Solutions: no\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Creation of non-transmural myocardial channels by lasers transmitted through endovascular fiberoptics is a novel therapeutic option in the management of patients with coronary artery disease. The acute effect of transventricular laser treatment (TvL) on coronary blood flow, myocardial metabolism and left ventricular function are not well established.\n", "In five anesthetized pigs, flow in the proximal left anterior descending coronary artery (LAD) was reduced and maintained at 70% of baseline. A venous shunt had previously been established draining the hypoperfused region. At 30 min of ischemia, non-transmural myocardial channels were created through the endocardium using a Ho:YAG laser. We measured (a) left ventricular, central venous and arterial pressures, (b) ascending aortic, LAD and coronary venous blood flows, as well as (c) lactate concentration and blood gases in arterial and coronary venous blood, prior to ischemia (baseline), before and 30 min after TvL. Data (given as mean +/- SD) were analyzed with repeated measures ANOVA.\n", "Reduction of LAD blood flow resulted in reduced regional coronary venous blood flow and myocardial oxygen consumption, conversion of regional myocardial lactate uptake to release and adaptation of left ventricular contractility to a lower level. Following transventricular laser, the peak left ventricular systolic pressure declined from 86 +/- 12 to 77 +/- 11 mmHg (P < 0.05), its maximal first positive derivative (LV dP/dt) declined from 900 +/- 221 to 763 +/- 127 mmHg/s (P < 0.05) and the stroke volume decreased from 19.2 +/- 4.1 to 16.4 +/- 5.4 ml (P < 0.05). The changes in regional coronary venous flow, myocardial oxygen consumption and myocardial lactate release after TvL were not significant compared to before TvL. Significant intramural hematomas and tissue destruction were found around the channels at autopsy and by histologic examination.\n", "\n", "Question: Does transventricular non-transmural laser treatment of hypoperfused porcine myocardium acutely reduce left ventricular contractile function?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\n", "\"Yes, transventricular non-transmural laser treatment of hypoperfused porcine myocardium acutely reduces left ventricular contractile function, as indicated by the decline in peak left ventricular systolic pressure, maximal first positive derivative, and stroke volume after the treatment.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The macrophage receptor with collagenous structure (MARCO) belongs to the scavenger receptor family; however, few studies have assessed their potentials in modulating inflammatory signaling other than the typical function of pattern recognition and phagocytic clearance. Interestingly, RNA-Seq analyses of hepatocellular carcinoma (HCC) have identified MARCO as one of the top 30 differentially expressed genes between cancerous and adjacent non-cancerous tissues. However, no research has been performed to study MARCO in liver cancer.\n", "MARCO protein expression was evaluated by immunostaining liver tissue specimens collected from 88 HCC patients, 10 liver cirrhosis patients, 6 metastatic patients and 5 healthy controls. All sections were reviewed by blinded observers followed by the interpretation of integral optical density per area as a measure of protein intensity.\n", "We observed significantly decreased expression of MARCO in intratumoural tissues of HCC compared with expression in peritumoural tissues. The expression of MARCO declined progressively as the disease condition was aggravated, with the highest expression found in healthy controls and the lowest found in patients with HCC metastasis. Furthermore, MARCO expression decreased along with tumour progression. MARCO\n", "\n", "Question: Is decreased expression of the macrophage scavenger receptor MARCO associated with tumour progression and poor prognosis in human hepatocellular carcinoma?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, decreased expression of the macrophage scavenger receptor MARCO is associated with tumour progression and poor prognosis in human hepatocellular carcinoma.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: OT was reported to be a direct regulator of bone mass in young rodents, and this anabolic effect on bone is a peripheral action of OT. The goal of this study was to investigate the peripheral action of oxytocin (OT) in the alveolar healing process in old female rats.\n", "Females Wistar rats (24-month-old) in permanent diestrus phase, received two ip (12h apart) injections of saline (NaCl 0.15M - control group) or OT (45μg/rat - treated group). Seven days later, the right maxillary incisor was extracted and analyses were performed up to 28 days of the alveolar healing process (35 days after saline or OT administration).\n", "Calcium and phosphorus plasma concentrations did not differ between the groups. The plasma biochemical bone formations markers, alkaline phosphatase (ALP) and osteocalcin were significantly higher in the treated group. Histomorphometric analyses confirmed bone formation as the treated group presented the highest mean value of post-extraction bone formation. Tartrate-resistant acid phosphatase (TRAP) was significantly reduced in the treated group indicating an anti-resorptive effect of OT. Immunohistochemistry reactions performed in order to identify the presence of osteocalcin and TRAP in the bone cells of the dental socket confirmed these outcomes.\n", "\n", "Question: Does oxytocin promote bone formation during the alveolar healing process in old acyclic female rats?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, oxytocin promotes bone formation during the alveolar healing process in old acyclic female rats.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Sex hormone fluctuations were shown to affect female vocal folds and laryngeal function. Laryngeal changes are evident throughout the span of life, starting at puberty with the arousal of the hormonal system, fluctuating systematically during the reproductive years with the menstrual cycle, and then changing again with the decline of hormonal activity at menopause. This paper reviews recent developments in this field.\n", "Early studies that explored this relation were based merely on subjective impressions of voice quality, recent studies have used more objective tools for examining this relation, including histologic observations, stroboscope, electroglottography (EGG), and computerized acoustic analyses. In these studies, the larynx was shown to be a hormonal target organ and, as such, sex hormones affect its morphology, histology, and function, similar to their effect on the genitals and other organs.\n", "\n", "Question: Does the impact of hormonal fluctuations on female vocal fold?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, hormonal fluctuations impact female vocal folds.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The cingulate island sign (CIS), which refers to sparing of the posterior cingulate relative to the precuneus and cuneus, has been proposed as an FDG-PET imaging feature of dementia with Lewy bodies (DLB). The sign is reportedly associated with Alzheimer's disease (AD) type neurofibrillary tangle (NFT) pathology in autopsy cases. To confirm this relationship using neuroimaging modalities in vivo, we investigated associations between CIS and the medial temporal lobe (MTL) atrophy in DLB.\n", "Twenty-four patients each of DLB and AD underwent both (18)F-FDG-PET and MRI with voxel-based morphometry. Dopamine transporter (DAT) density was also measured by DAT-SPECT in all those with DLB and in five with AD. The accumulation of FDG in the posterior cingulate ROI was divided by that in the precuneus plus cuneus ROI to derive the CIS ratio from the FDG-PET images. Values for cognitive function of Mini-Mental State Examination (MMSE), Frontal Assessment Battery (FAB) and Ray Auditory Verbal Learning Test (RAVLT) and scores for the core-feature triad of fluctuation, hallucination and parkinsonism were also statistically analyzed.\n", "The CIS ratio was higher in DLB than in AD (p < 0.001). The degree of MTL atrophy was lower in DLB than in AD (p < 0.001). The CIS ratio and the degree of MTL atrophy were inversely correlated with DLB (p < 0.001) and with AD (p < 0.05). The CIS ratio did not significantly correlate with DAT density in DLB or with MMSE, FAB, fluctuation score and parkinsonism score. However, the CIS ratio significantly correlated with RAVLT and hallucination scores (both, p < 0.05).\n", "\n", "Question: Is cingulate island sign on FDG-PET associated with medial temporal lobe atrophy in dementia with Lewy bodies?\n", "\n", "Answer:\n", "Predictions: No, the cingulate island sign (CIS) ratio did not significantly correlate with medial temporal lobe (MTL) atrophy in dementia with Lewy bodies (DLB).\n", "Solutions: yes\n", "Score: 0.0\n", "Error reason: Computation result is incorrect.Questions: Context: Impulse control disorders (ICDs) in Parkinson's disease (PD) are related to treatment with dopamine agonists, which is thought to deregulate the dopaminergic mesolimbic pathway and impair reward evaluation. EEG studies in healthy controls (HCs) have suggested that the increase in theta power observed after negative outcome is a marker of reward processing.\n", "To compare outcome-locked, event-related spectral perturbation in a gambling task in PD patients with and without ICDs and in HCs.\n", "Twelve PD patients with ICDs, 12 PD patients without ICDs and 14 HCs underwent EEG while performing a gambling task. The groups were compared in terms of (i) the peak EEG power in the theta (4-7 Hz), alpha (8-14 Hz) and beta (15-30 Hz) frequency bands between 200 and 500 ms after the outcome, and (ii) time-frequency plots at Fz, FCz and Cz.\n", "Positive outcomes were associated with greater theta power than negative outcomes in patients without ICDs and in HCs, but not in patients with ICDs. Patients with ICDs and HCs displayed greater theta power following unexpectedly high outcomes. HCs displayed greater beta power following high amplitude than low amplitude outcomes, whereas patients with ICD showed the opposite pattern.\n", "\n", "Question: Are impulse Control Disorders in Parkinson 's Disease Associated with Alterations in Reward-Related Cortical Oscillations?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, impulse control disorders in Parkinson's Disease are associated with alterations in reward-related cortical oscillations, as indicated by differences in theta power responses to outcomes between patients with and without ICDs.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Oxidation of propofol to 4-hydroxypropofol represents a significant pathway in the metabolism of this anesthetic agent in humans. The aim of this study was to identify the principal cytochrome P-450 (CYP) isoforms mediating this biotransformation.\n", "Propofol hydroxylation activities and enzyme kinetics were determined using human liver microsomes and cDNA-expressed CYPs. CYP-specific marker activities and CYP2B6 protein content were also quantified in hepatic microsomes for correlational analyses. Finally, inhibitory antibodies were used to ascertain the relative contribution of CYPs to propofol hydroxylation by hepatic microsomes.\n", "Propofol hydroxylation by hepatic microsomes showed more than 19-fold variability and was most closely correlated to CYP2B6 protein content (r = 0.904), and the CYP2B6 marker activities, S-mephenytoin N-demethylation (r = 0.919) and bupropion hydroxylation (r = 0.854). High- and intermediate-activity livers demonstrated high-affinity enzyme kinetics (K(m) < 8 microm), whereas low-activity livers displayed low-affinity kinetics (K(m) > 80 microm). All of the CYPs evaluated were capable of hydroxylating propofol; however, CYP2B6 and CYP2C9 were most active. Kinetic analysis indicated that CYP2B6 is a high-affinity (K(m) = 10 +/- 2 microm; mean +/- SE of the estimate), high-capacity enzyme, whereas CYP2C9 is a low-affinity (K(m) = 41 +/- 8 microm), high-capacity enzyme. Furthermore, immunoinhibition showed a greater contribution of CYP2B6 (56 +/- 22% inhibition; mean +/- SD) compared with CYP2C isoforms (16 +/- 7% inhibition) to hepatic microsomal activity.\n", "\n", "Question: Is cytochrome P-450 2B6 responsible for interindividual variability of propofol hydroxylation by human liver microsomes?\n", "\n", "Answer:\n", "Predictions: {\"draft_answer\": \"Yes, cytochrome P-450 2B6 is responsible for interindividual variability of propofol hydroxylation by human liver microsomes, as it showed a strong correlation with propofol hydroxylation activities and contributed significantly to the hepatic microsomal activity.\"}\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Growth-differentiation factor (GDF)-15, a member of the TGF-beta superfamily, is potently induced in the intestine following mechanical injury, genotoxic insult and following non-steroidal anti-inflammatory drugs (NSAIDs) exposure. GDF-15 expression correlates with apoptosis in intestinal cells and has been implicated in the pathogenesis of colorectal cancer formation and the anti-tumor effects of NSAIDs. We sought to determine the effect of loss of Gdf15 on animal tumor models of hereditary colon cancer and in the NSAID-mediated prevention of heritable colorectal cancer.\n", "GDF-15 null (Gdf15 (-/-)) mice and mice with the genetic mutation found in hereditary poliposis coli, Apc ( min/+ ) were bred. Gdf15 ( -/- ), Apc ( min/+ ) and Gdf15 ( +/+ ), Apc ( min/+ ) mice were generated.\n", "In Gdf15 ( -/- ), Apc ( min/+ ) mice, intestinal neoplasia formation rate and size were indistinguishable from that in Gdf15 ( +/+ ), Apc ( min/+ ) mice. Sulindac chemoprotection activity although potent in Gdf15 ( +/+ ), Apc ( min/+ ) mice was abolished in Gdf15 ( -/- ), Apc ( min/+ ) mice.\n", "\n", "Question: Does loss of GDF-15 abolish sulindac chemoprevention in the ApcMin/+ mouse model of intestinal cancer?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, loss of GDF-15 abolishes sulindac chemoprevention in the ApcMin/+ mouse model of intestinal cancer.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Mesenchymal stem cells (MSCs) have been proposed to be a useful tool for treatment of rheumatoid arthritis (RA), not only because of their multipotency but also because of their immunosuppressive effect on lymphocytes, dendritic cells, and other proinflammatory cells. Since bone destruction caused by activated osteoclasts occurs in RA, we undertook the present study to investigate the effect of MSCs on osteoclast function and differentiation in order to evaluate their potential use in RA therapy.\n", "Human MSCs and peripheral blood mononuclear cells were cultured under cell-cell contact-free conditions with osteoclast induction medium. Differentiation into osteoclast-like cells was determined by tartrate-resistant acid phosphatase staining and expression of osteoclast differentiation markers.\n", "The number of osteoclast-like cells was decreased and expression of cathepsin K and nuclear factor of activated T cells c1 (NF-ATc1) was down-regulated by the addition of either MSCs or a conditioned medium obtained from MSCs. Osteoprotegerin (OPG) was constitutively produced by MSCs and inhibited osteoclastogenesis. However, osteoclast differentiation was not fully recovered upon treatment with either anti-OPG antibody or OPG small interfering RNA, suggesting that OPG had only a partial role in the inhibitory effect of MSCs. Moreover, bone-resorbing activity of osteoclast-like cells was partially recovered by addition of anti-OPG antibody into the conditioned medium.\n", "\n", "Question: Do human mesenchymal stem cells inhibit osteoclastogenesis through osteoprotegerin production?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, human mesenchymal stem cells inhibit osteoclastogenesis through osteoprotegerin production, as indicated by the constitutive production of OPG by MSCs and its role in inhibiting osteoclast differentiation.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Pesticide exposure is a recognized risk factor for neurodegenerative diseases. Recently, bifenthrin, a pyrethroid pesticide, was shown to inhibit the formation of neurites and cause neurite retraction, raising concern that these newer and less toxic pesticides may also contribute to neurodegenerative diseases. PolicosanolPlus and Neuroprevin are nutraceutical supplements which promote the survival of neurites in neuronal cell cultures. Here we determine if PolicosanolPlus and Neuroprevin can ameliorate the neurodegenerative effects of bifenthrin.\n", "PC12 cells were treated with NGF, bifenthrin, PolicosanolPlus and Neuroprevin in various combinations and the formation of neurites was assessed microscopically at times ranging from 12 to 72 hours post treatment. Bifenthrin was also withheld at the time of NGF, PolicosanolPlus and Neuroprevin treatment and added after neurite formed to assess neurite retraction.\n", "Bifenthrin (1 x 10(-6) M) inhibits neurite outgrowth, in the absence of cell death, by more than 50% at 12 hours and by more than 80% at 72 hours. With addition of PolicosanolPlus and/or Neuroprevin at the time of cell seeding, bifenthrin does not inhibit neurite outgrowth. Addition of bifenthrin to differentiated cells results in a retraction of 90% of neurites, while those with PolicosanolPlus and Neuroprevin show no significant retraction of neurites.\n", "\n", "Question: Do policosanolPlus and Neuroprevin ameliorate pesticide-mediated inhibition of neurite outgrowth and neurite degeneration?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, PolicosanolPlus and Neuroprevin ameliorate pesticide-mediated inhibition of neurite outgrowth and neurite degeneration.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Recent outbreaks of Clostridium difficile infection (CDI) in North America and in Europe with very high case-fatality rates have been associated with infection by North American Pulsed Field Type I (NAP-1) isolates. This study examined whether NAP-1 strains are associated with worse outcomes of CDI in a nonepidemic, nosocomial setting.\n", "All cases of CDI that occurred over a 13-month period at a tertiary medical center were examined for risk factors associated with increased severity of CDI and other outcomes. Stool samples from each patient were cultured for C difficile and the resulting isolates were strain-typed by pulsed-field gel electrophoresis.\n", "Strain types were obtained from 236 of 272 CDI samples; the NAP-1 strain was identified in 59 (25%). In this inpatient cohort of patients with CDI, the incidence of in hospital death was 12.1% and of death caused by CDI was 4.0%. Of the patients with CDI, 22.1% met the combined outcome end point of severe CDI. In both univariate and multivariate analyses, patients infected with the NAP-1 strain did not have worse outcomes compared with those infected with non-NAP-1 strains. Infection with the NAP-1 strain was correlated with admission from outside health care facilities regardless of whether symptoms of CDI began before or after admission to the study hospital.\n", "\n", "Question: Is clostridium difficile strain NAP-1 associated with severe disease in a nonepidemic setting?\n", "\n", "Answer:\n", "Predictions: No, infection with the NAP-1 strain was not associated with worse outcomes compared to non-NAP-1 strains in a nonepidemic setting.\n", "Solutions: no\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Several studies have implicated the mitogen-activated protein kinase (MAPK) signal pathway in non-hepatic organ ischemia-reperfusion injury. However, the role of p38 MAPK in hepatic ischemia-reperfusion injury remains unclear. This study investigated the role of p38 MAPK in hepatic ischemia-reperfusion injury.\n", "Male Sprague-Dawley rats were divided into 4 groups (sham, FR-only, control, and FR-treated groups). The animals in the control and FR-treated groups were subjected to 30 minutes of warm ischemia with congestion of the gut. The FR-only and FR-treated groups received FR167653 (FR), which is a novel p38 MAPK inhibitor. The serum levels of aspartate transaminase, alanine transaminase, lactate dehydrogenase, tumor necrosis factor-alpha (TNF-alpha), and interleukin-1beta (IL-1beta) were measured (each, n = 6). Liver tissue blood flow was measured at pre-ischemia, end-ischemia, and 30, 60, 90, and 120 minutes after reperfusion (each, n = 4). The liver tissues in the control and FR-treated groups were excised for p38 MAPK and c-Jun N-terminal kinase (JNK) analyses and histopathology (each, n = 4).\n", "Serum levels of aspartate transaminase, alanine transaminase, lactate dehydrogenase, TNF-alpha, and IL-1beta were significantly lower in the FR-treated group than in the control group, and liver tissue blood flow was significantly higher in the FR-treated group than in the control group. Histopathologically, tissue damage was milder in the FR-treated group than in the control group. Both p38 MAPK and JNK were markedly phosphorylated after 30 minutes of reperfusion, and FR inhibited the phosphorylation of p38 MAPK without affecting the JNK.\n", "\n", "Question: Does p38 mitogen-activated protein kinase inhibition attenuate ischemia-reperfusion injury of the rat liver?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The Child Behavior Checklist (CBCL) has been used to provide a quantitative description of childhood bipolar disorder (BPAD). Many have reported that children in the clinical range on the Attention Problems (AP), Aggressive Behavior (AGG), and Anxious-Depressed (A/D) syndromes simultaneously are more likely to meet the criteria for childhood BPAD. The purpose of this study was to determine if Latent Class Analysis (LCA) could identify heritable phenotypes representing the CBCL-Juvenile Bipolar (CBCL-JBD) profile and whether this phenotype demonstrates increased frequency of suicidal endorsement.\n", "The CBCL data were received by survey of mothers of twins in two large twin samples, the Netherlands Twin Registry. The setting for the study was the general community twin sample. Participants included 6246 10-year-old Dutch twins from the Netherlands Twin Registry. The main outcome measure consisted of the LCA on the items comprising the AP, AGG, and A/D subscales and means from the suicidal items #18 and #91 within classes.\n", "A 7 class model fit best for girls and an 8 class fit best for boys. The most common class for boys or girls was one with no symptoms. The CBCL-JBD phenotype was the least common--about 4%-5% of the boys and girls. This class was the only one that had significant elevations on the suicidal items of the CBCL. Gender differences were present across latent classes with girls showing no aggression without the CBCL-JBD phenotype and rarely showing attention problems in isolation. Evidence of high heritability of these latent classes was found with odds ratios.\n", "\n", "Question: Does latent class analysis show strong heritability of the child behavior checklist-juvenile bipolar phenotype?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, latent class analysis shows strong heritability of the child behavior checklist-juvenile bipolar phenotype.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: This study was conducted to investigate the effects of creatine loading and resistance training on the homocysteine and lipid profiles of young males.\n", "Sixty male University students (22.34 ± 2.19 years, 1.79 ± 0.08 m, 77.18 ± 12.57 kg, 15.48 ± 4.57% body fat) were randomly divided in to three groups; control (CG=20), creatine supplement (CEG=20) and placebo (PEG=20). Both CEG and PEG participated in a same resistance-training regimen and either taking a creatine supplement (25 g/d for the first 5 days followed 5 g/d thereafter) or the same amount of placebo for 8 weeks. Participants in CG did not take any creatine supplementation and not engage any exercise program. After the body composition were assessed, the homocysteine (Hcy) concentrations, blood lipids, folic acid and vitamin B12 levels of all the participants were measured at the beginning and end of the eight weeks of resistance training.\n", "The analysis of the data indicated that the Hcy levels of the CEG after resistance training and receiving the creatine supplement (9.33 ± 4.60) was significantly lower than that of baseline (12.66 ± 5.89) measurements, F(1,18)=12.28, P=0.00. No significant differences were seen in the Hcy levels of the PEG (15.01 ± 10.87) after 8 weeks of training and receiving a placebo (12.46 ± 12.50), F(1,16)=4.65, P=0.05. Furthermore, there were no significant differences among groups in terms of Hcy levels, F(2,52)=1.72, P=0.19.\n", "\n", "Question: Does creatine supplementation alter homocysteine level in resistance trained men?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To investigate the contribution of genetic polymorphisms of vitamin K epoxide reductase complex subunit 1 gene VKORC1-1639G>A, cytochrome P450 2C9 gene (CYP2C9), EPHXI, and clinical factors to warfarin sensitivity in southwest Chinese Han patients with mechanical heart valve prostheses.\n", "A total of 127 patients with mechanical heart valve prostheses who have been followed up at our department during the past 23 years were enrolled in this study and compared to a control group that consisted of 133 randomly selected healthy blood donors. These Chinese patients met stable warfarin dosage requirements and had reached the target international normalized ratio (INR) of 1.5-2.0. PCR and direct sequencing were carried out to identify the polymorphisms of VKORC1-1639G>A (rs9923231), CYP2C9*3 (rs1057910), CYP2C9 IVS3-65G>C (rs9332127), and EPHX1691A>G (rs4653436). In addition, total and free (non-protein-bound) warfarin concentrations were analyzed.\n", "\n", "Question: Are vKORC1-1639G > A , CYP2C9 , EPHX1691A > G genotype , body weight , and age important predictors for warfarin maintenance doses in patients with mechanical heart valve prostheses in southwest China?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, VKORC1-1639G>A, CYP2C9, EPHX1691A>G genotype, body weight, and age are important predictors for warfarin maintenance doses in patients with mechanical heart valve prostheses in southwest China.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Subclinical inflammation is a common phenomenon in patients on either continuous ambulatory peritoneal dialysis (CAPD) or maintenance hemodialysis (MHD). We hypothesized that vitamin C had anti-inflammation effect because of its electron offering ability. The current study was designed to test the relationship of plasma vitamin C level and some inflammatory markers.\n", "In this cross-sectional study, 284 dialysis patients were recruited, including 117 MHD and 167 CAPD patients. The demographics were recorded. Plasma vitamin C was measured by high-performance liquid chromatography. And we also measured body mass index (BMI, calculated as weight/height(2)), Kt/V, serum albumin, serum prealbumin, high-sensitivity C-reactive protein (hsCRP), ferritin, hemoglobin. The relationships between vitamin C and albumin, pre-albumin and hsCRP levels were tested by Spearman correlation analysis and multiple regression analysis. Patients were classified into three subgroups by vitamin C level according to previous recommendation 12 in MHD and CAPD patients respectively: group A: < 2 ug/ml (< 11.4 umol/l, deficiency), group B: 2-4 ug/ml (11.4-22.8 umol/l, insufficiency) and group C: > 4 ug/ml (> 22.8 umol/l, normal and above).\n", "Patients showed a widely distribution of plasma vitamin C levels in the total 284 dialysis patients. Vitamin C deficiency (< 2 ug/ml) was present in 95(33.45%) and insufficiency (2-4 ug/ml) in 88(30.99%). 73(25.70%) patients had plasma vitamin C levels within normal range (4-14 ug/ml) and 28(9.86%) at higher than normal levels (> 14 ug/ml). The similar proportion of different vitamin C levels was found in both MHD and CAPD groups. Plasma vitamin C level was inversely associated with hsCRP concentration (Spearman r = -0.201, P = 0.001) and positively associated with prealbumin (Spearman r = 0.268, P < 0.001), albumin levels (Spearman r = 0.161, P = 0.007). In multiple linear regression analysis, plasma vitamin C level was inversely associated with log(10)hsCRP (P = 0.048) and positively with prealbumin levels (P = 0.002) adjusted for gender, age, diabetes, modality of dialysis and some other confounding effects.\n", "\n", "Question: Is low levels of vitamin C in dialysis patients associated with decreased prealbumin and increased C-reactive protein?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, low levels of vitamin C in dialysis patients are associated with decreased prealbumin and increased C-reactive protein.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The malQ and glgP genes, respectively, annotated as putative 4-α-glucanotransferase and putative glycogen phosphorylase are located with a 29 nucleotide overlap on the Streptococcus mutans genome. We found that the glgP gene of this organism was induced with maltose, and the gene likely constituted an operon with the upstream gene malQ. This putative operon was negatively regulated with the malR gene located upstream from the malQ gene and a MalR-binding consensus sequence was found upstream of the malQ gene. S. mutans is not able to catabolize starch. However, this organism utilizes maltose degraded from starch in the presence of saliva amylase. Therefore, we hypothesized that the MalQ/GlgP system may participate in the metabolism of starch-degradation products.\n", "A DNA fragment amplified from the malQ or glgP gene overexpressed His-tagged proteins with the plasmid pBAD/HisA. S. mutans malQ and/or glgP mutants were also constructed. Purified proteins were assayed for glucose-releasing and phosphorylase activities with appropriate buffers containing maltose, maltotriose, maltodextrin, or amylodextrin as a substrate, and were photometrically assayed with a glucose-6-phosphate dehydrogenase-NADP system.\n", "Purified MalQ protein released glucose from maltose and maltotriose but did not from either maltodextrin or amylodextrin. The purified GlgP protein did not exhibit a phosphorylase reaction with maltose or maltotriose but generated glucose-1-phosphate from maltodextrin and amylodextrin. However, the GlgP protein released glucose-1-phosphate from maltose and maltotriose in the presence of the MalQ protein. In addition, the MalQ enzyme activity with maltose released not only glucose but also produced maltooligosaccharides as substrates for the GlgP protein.\n", "\n", "Question: Is the malQ gene essential for starch metabolism in Streptococcus mutans?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\n", "\"No, the malQ gene is not essential for starch metabolism in Streptococcus mutans, as the organism can utilize maltose degraded from starch in the presence of saliva amylase, and the GlgP protein can function in the presence of MalQ.\"\n", "Solutions: yes\n", "Score: 0.0\n", "Error reason: Computation result is incorrect.Questions: Context: Interleukin-17 (IL-17) is a proinflammatory cytokine that is most prominently produced by T-helper type 17 (Th17) cells, a distinct CD4+ T-helper cell subset. The aim of this study was to investigate the level of IL-17-producing cells in the breast cancer tumour microenvironment and its prognostic role.\n", "A total of 207 breast carcinoma specimens were assessed by IL-17 immunohistochemistry, and the findings were correlated with clinicopathological parameters. We found that increased numbers of IL-17-producing cells were correlated with high histological grade, negative ER/PR status, and triple-negative molecular subtypes segregated by immunoprofiles. However, they did not correlate with stage, tumour size, nodal status, HER2 status, or histological type. Patients with tumours with high numbers of IL-17-producing cells had shorter disease-free survival (DFS) than patients with tumours with low numbers of IL-17-producing cells (P < 0.01). In multivariate analysis, high IL-17 level [hazard ratio (HR) 2.24; 95% CI 1.06-4.75], advanced T stage (HR 2.73; 95% CI 1.30-5.73), positive HER2 status (HR 4.88; 95% CI 1.47-16.18) and triple-negative subtype (HR 7.46; 95% CI 1.38-40.36) were significant prognostic factors for DFS.\n", "\n", "Question: Is interleukin-17-producing cell infiltration in the breast cancer tumour microenvironment a poor prognostic factor?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, interleukin-17-producing cell infiltration in the breast cancer tumour microenvironment is a poor prognostic factor, as it is correlated with shorter disease-free survival.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: A highly polymorphic T homopolymer was recently found to be associated with late-onset Alzheimer's disease risk and age of onset.\n", "To explore the effects of the polymorphic polyT tract (rs10524523, referred as '523') on cognitive performance in cognitively healthy elderly individuals.\n", "One hundred eighty-one participants were recruited from local independent-living retirement communities. Informed consent was obtained, and participants completed demographic questionnaires, a conventional paper-and-pencil neuropsychological battery, and the computerized Cambridge Neuropsychological Test Automated Battery (CANTAB). Saliva samples were collected for determination of the TOMM40 '523' (S, L, VL) and the apolipoprotein E (APOE) (ɛ2, 3, 4) genotypes. From the initial sample of 181 individuals, 127 were eligible for the association analysis. Participants were divided into three groups based on '523' genotypes (S/S, S/L-S/VL, and L/L-L/VL-VL/VL). Generalized linear models were used to evaluate the association between the '523' genotypes and neuropsychological test performance. Analyses were adjusted for age, sex, education, depression, and APOE ɛ4 status. A planned subanalysis was undertaken to evaluate the association between '523' genotypes and test performance in a sample restricted to APOE ɛ3 homozygotes.\n", "The S homozygotes performed better, although not significantly, than the S/L-S/VL and the VL/L-L/VL-VL/VL genotype groups on measures associated with memory (CANTAB Paired Associates Learning, Verbal Recognition Memory free recall) and executive function (CANTAB measures of Intra-Extra Dimensional Set Shift). Follow-up analysis of APOE ɛ3 homozygotes only showed that the S/S group performed significantly better than the S/VL group on measures of episodic memory (CANTAB Paired Associates Learning and Verbal Recognition Memory free recall), attention (CANTAB Rapid Visual Information Processing latency), and executive function (Digit Symbol Substitution). The S/S group performed marginally better than the VL/VL group on Intra-Extra Dimensional Set Shift. None of the associations remained significant after applying a Bonferroni correction for multiple testing.\n", "\n", "Question: Does a homopolymer polymorphism in the TOMM40 gene contribute to cognitive performance in aging?\n", "\n", "Answer:\n", "Predictions: No, the study indicates that while there were some differences in cognitive performance associated with the TOMM40 polymorphism, none of the associations remained significant after applying a Bonferroni correction for multiple testing.\n", "Solutions: yes\n", "Score: 0.0\n", "Error reason: Computation result is incorrect.Questions: Context: The results for finding the deficit in the anterior cingulate (ACC) in schizophrenic patients (SZ) have been inconsistent according to the studies that used different Stroop tasks, which is unlike the deficit in the dorsolateral prefrontal cortex (DLPFC). In order to explore for the core region that's responsible for the selective attention deficit in SZ, we examined the results of a functional neuroimaging study, which involved the performance of the Stroop task using high or low prefrontal cortex related loads in SZ.\n", "Ten schizophrenic patients and healthy controls (HC) received functional magnetic resonance imaging (fMRI) during a Short/Long-term latency Stroop task. The changes in the neural activity were determined in well-known Stroop related regions of interest (ROIs) that consisted of the DLPFC, ACC, the parietal lobule and in the whole brain regions for both the main and interaction effects of latency, and the results of the short-term and long-term latency Stroop conditions were compared.\n", "The response times for both the congruency and latency effects were more prolonged in the schizophrenics than in the HC. For the congruency effect, the schizophrenics showed significantly less activation in the same site of the left DLPFC in both the short-term and long-term latency conditions, as compared with the HC. For the latency effect, the regions of the left-side language network were over- or under-activated in the schizophrenics, as compared with the HC. Any interaction effect was not found for both the behavioral and fMRI results.\n", "\n", "Question: Is dysfunction of the Left Dorsolateral Prefrontal Cortex Primarily Responsible for Impaired Attentional Processing in Schizophrenia?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\n", "\"Yes, the findings suggest that dysfunction of the Left Dorsolateral Prefrontal Cortex is primarily responsible for impaired attentional processing in schizophrenia, as indicated by the significantly less activation in this area during the Stroop task compared to healthy controls.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: In HFE-related hereditary hemochromatosis an inappropriately low hepatic expression of the iron-regulatory peptide hepcidin (encoded by HAMP) has been suggested to cause iron overload. The aim of the present study was to evaluate whether the hepatic expression of HAMP in relation to iron stores requires HFE or might involve other important iron-related genes including HJV (encoding hemojuvelin) and TFR2 (encoding transferrin receptor-2).\n", "Using quantitative RT-PCR, the iron-dependent hepatic expression patterns of HAMP, HJV, and TFR2 were evaluated in human and murine HFE-related hemochromatosis.\n", "The overall level of hepatic HAMP expression in human and murine HFE-related hemochromatosis is impaired but can still be modulated by iron stores. Moreover, we demonstrate an HFE-independent correlation between the expression of HAMP and TFR2 in mouse and human livers. On the other hand, a strong correlation between the hepatic expression of HAMP and HJV was only found in hemochromatosis patients and Hfe-deficient mice.\n", "\n", "Question: Do iron stores modulate hepatic hepcidin expression by an HFE-independent pathway?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, iron stores modulate hepatic hepcidin expression by an HFE-independent pathway.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Alcohol use disorders (AUDs) are a frequent comorbidity in a large percentage of people living with HIV/AIDS (PLWHA). PLWHA with comorbid AUDs are consistently found to perform poorly at most levels of the HIV treatment cascade, resulting in a higher likelihood of virologic nonsuppression. This has been partly attributed to lower rates of persistence with and adherence to antiretroviral therapies (ART). Focus groups of in-care PLWHA identify the need to suspend ART on drinking days because of the potential for toxicity and/or lack of therapeutic effectiveness. The aim of this study was to examine whether chronic binge alcohol (CBA) consumption decreases the effectiveness of uninterrupted ART, specifically that of nucleoside reverse-transcriptase inhibitors (NRTI) tenofovir and emtricitabine in suppressing viral replication, or results in drug toxicity in simian immunodeficiency virus (SIV)-infected rhesus macaques.\n", "Daily CBA or isocaloric sucrose (SUC) administration was initiated 3 months prior to intrarectal SIVmac251 inoculation and continued throughout the study period. ART was initiated 2.5 months after SIV infection and continued through the study period.\n", "CBA administration did not prevent or delay the ART-mediated reduction in viral load. Following ART, circulating levels of total protein and creatinine were significantly higher than baseline values in both SUC- and CBA-treated animals, but still within a normal range. No evidence of ART toxicity was observed in either CBA- or SUC-administered macaques.\n", "\n", "Question: Does chronic binge alcohol consumption diminish effectiveness of continuous antiretroviral suppression of viral load in simian immunodeficiency virus-infected macaques?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "No, chronic binge alcohol consumption does not diminish the effectiveness of continuous antiretroviral suppression of viral load in simian immunodeficiency virus-infected macaques.\n", "Solutions: no\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To investigate the potential role of peritoneal fluid activity for the local delivery of gonadal steroid hormones.\n", "Prospective clinical study.\n", "University hospital.\n", "Nine women undergoing tubal sterilization during laparoscopic surgery.\n", "Peritoneal fluid was collected during laparoscopic surgery by means of sterile cotton swabs on the surface of the peritoneum facing the ovary with an active corpus luteum and on the contralateral side, at the right and left paracolic gutter, and at the pouch of Douglas; simultaneous systemic blood sampling was performed.\n", "P was quantified by competitive immunochemical assay. Final steroid concentrations were calculated relative to the standard recovery rate.\n", "P concentrations in the peritoneum close to the corpus luteum were 4 times (range, 1.4-9.2) higher than in the other peritoneal samples and about 5 times (range, 3.9-9.5) higher than in the systemic blood.\n", "\n", "Question: Are peritoneal fluid concentrations of progesterone in women higher close to the corpus luteum compared with elsewhere in the abdominal cavity?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, peritoneal fluid concentrations of progesterone in women are higher close to the corpus luteum compared with elsewhere in the abdominal cavity.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: APACHE II (AP2) was developed to allow a systematic examination of intensive care unit outcomes in a risk adjusted manner. AP2 has been widely adopted in clinical trials to assure broad consistency amongst different groups. Although errors in calculating the true AP2 score may not be reducible below 15%, the self-canceling effect of random errors reduces the importance of such errors when applied to large populations. It has been suggested that a threshold AP2 score be used in clinical decision making for individual patients. This study reports the AP2 scoring errors of researchers involved in a large sepsis trial and models the consequences of such an error rate for individual severe sepsis patients.\n", "Fifty-six researchers with explicit training in data abstraction and completion of the AP2 score received scenarios consisting of composites of real patient histories. Descriptive statistics were calculated for each scenario. The standard deviations were calculated compared with an adjudicated score. Intraclass correlations for inter-observer reliability were performed using Shrout-Fleiss methodology. Theoretical distribution curves were calculated for a broad range of AP2 scores using standard deviations of 6, 9 and 12. For each curve, the misclassification rate was determined using an AP2 score cut-off of >or=25. The percentage of misclassifications for each true AP2 score was then applied to the corresponding AP2 score obtained from the PROGRESS severe sepsis registry.\n", "The error rate for the total AP2 score was 86% (individual variables were in the range 10% to 87%). Intraclass correlation for the inter-observer reliability was 0.51. Of the patients from the PROGRESS registry. 50% had AP2 scores in the range 17 to 28. Within this interquartile range, 70% to 85% of all misclassified patients would reside.\n", "\n", "Question: Does application of a population-based severity scoring system to individual patients result in frequent misclassification?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, the application of a population-based severity scoring system to individual patients results in frequent misclassification, as indicated by the reported error rate of 86% in the AP2 score.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Recently, we reported Na+/glucose co-transporter (SGLT1) expression in mouse and human heart. We speculated that SGLT1 might play an important role in ischemic preconditioning-induced cardioprotection. Therefore, the present study was designed to find the role of SGLT1 in ischemic preconditioning-induced cardioprotection.\n", "Hearts isolated from SD male rats were subjected to either ischemia-reperfusion injury (I/R) (15 min global ischemia followed by 20 min reperfusion) or ischemic preconditioning (IPC) (3 cycles of 2 min global ischemia separated by 3 min reperfusion) followed by I/R in presence and absence of phlorizin, an SGLT1 inhibitor.\n", "IPC increased membrane SGLT1 expression in rat heart as observed by immunoblotting and immunohistochemistry. Hearts from I/R group showed significant increase in oxidative stress levels and marked myocardial injury as compared to control. We also observed significant increase in apoptotic parameters in I/R heart, as measured by caspase-3 activity, TUNEL positive nuclei and gene expression analysis. Significant improvement in oxidative stress, apoptosis parameters and cardiac injury was observed in I/R hearts when subjected to IPC. However, all beneficial effects of preconditioning were lost when hearts were pre-treated with phlorizin.\n", "\n", "Question: Does inhibition of SGLT1 abrogate preconditioning-induced cardioprotection against ischemia-reperfusion injury?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, inhibition of SGLT1 abrogates preconditioning-induced cardioprotection against ischemia-reperfusion injury.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: We evaluated the impact of emergency physician (EP)-initiated primary percutaneous coronary intervention (PCI) via a single-group page on door to balloon (D2B) interval times in patients with ST-segment elevation myocardial infarction.\n", "Consecutive ST-segment elevation myocardial infarction patients presenting to the emergency department between February 2004 and September 2008 were divided into 4 groups: group 1, PCI performed on an ad hoc basis after cardiology consultation; group 2, primary PCI activated via a single-group page only on-call cardiology consultation; group 3, primary PCI with EP cardiac catheterization laboratory (CCL) activation via the same page strategy; group 4, prehospital CCL activation based on prehospital diagnostic electrocardiogram. Composite D2B and relevant time intervals were measured for each time group.\n", "A total of 295 consecutive patients undergoing emergent angiography were included. Times decreased for most time intervals from groups 1 to 4. Although there was no significant change in composite D2B or any measured interval time with the introduction of PCI after emergent cardiology consultation, each decreased significantly after implementing an EP-initiated PCI strategy except CCL2B (D2B 95 to 77 minutes, D2E 14 to 10 minutes, D2CCL 71 to 50 minutes). Further significant reductions in D2B time were achieved among all patients after the institution of emergency medicine services activation of the CCL (D2B 77 to 64 minutes, D2CCL 50 to 38 minutes, CCL2B 28 to 22 minutes).\n", "\n", "Question: Does emergency physician-initiated cath lab activation reduce door to balloon times in ST-segment elevation myocardial infarction patients?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, emergency physician-initiated cath lab activation reduces door to balloon times in ST-segment elevation myocardial infarction patients.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The study focuses on the influence of a probiotic supplement alone and in combination with a calcium supplement on faecal lactobacilli colonisation and beneficial health effects such as a lowering of blood cholesterol.\n", "Thirty-two men and women participated in the double-blind, placebo-controlled, cross-over study. All participants consumed a probiotic drink containing 10(10)CFU/d Lactobacillus paracasei (LPC37) for four weeks. In addition, one group consumed bread enriched with pentacalcium hydroxy-triphosphate (CaP; 1g Ca/d) and the other group had bread without CaP. After a two-week washout and a two-week placebo period, the intervention was switched for further four weeks.\n", "After intervention with LPC37+CaP, total cholesterol and LDL-cholesterol concentration in plasma decreased significantly compared to LPC37 and placebo. The faecal concentration of L. paracasei and that of all lactobacilli increased significantly after LPC37+CaP and LPC37 compared to placebo. Moreover, secondary bile acids in faeces increased significantly after LPC37+CaP intervention compared to placebo.\n", "\n", "Question: Does a combination of calcium phosphate and probiotics beneficially influence intestinal lactobacilli and cholesterol metabolism in humans?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, a combination of calcium phosphate and probiotics beneficially influences intestinal lactobacilli and cholesterol metabolism in humans.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: We evaluated the efficacy of ketorolac in suppressing postoperative bladder spasms after ureteroneocystostomy (ureteral reimplantation). Twenty-four pediatric patients undergoing intravesical ureteroneocystostomy were enrolled prospectively to receive either ketorolac or placebo via double-blinded randomization. Twelve patients in each group shared similar preoperative characteristics. All were maintained on an epidural infusion of bupivacaine (0.1%) with fentanyl (2 microg/mL) throughout the study. Patients were given either ketorolac (0.5 mg. kg(-1). dose(-1)) or placebo (equivalent volume saline) IV after surgery and every 6 h thereafter for 48 h. Parents were instructed to record bladder spasm episodes prospectively by using a standardized time-flow diary. Three patients (25%) in the ketorolac group experienced bladder spasms, compared with 10 patients (83%) in the placebo group (two-sided P < 0.05). The median severity score for the ketorolac group was 1.2 (mild = 1.0, severe = 3.0), compared with 2.6 for the placebo group (P = 0.003). We conclude that IV ketorolac reduces the frequency and severity of postoperative bladder spasms after intravesical ureteroneocystostomy.\n", "\n", "Question: Does ketorolac suppress postoperative bladder spasms after pediatric ureteral reimplantation?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, ketorolac suppresses postoperative bladder spasms after pediatric ureteral reimplantation.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Retrospective case report.\n", "Tertiary referral cochlear implant center.\n", "A 21-year-old woman was implanted with Advanced Bionics HiFocus Clarion device without complication. Five years later, the patient presented with dizziness, fluctuating implant performance, and facial pain.\n", "Surgical exploration revealed a torn electrode silicon casing in conjunction with scar contraction bending the electrode against bony facial nerve canal at the facial recess. Suspension of the electrode such that the damaged portion was not in contact with mastoid cavity led to temporary resolution of symptoms. Explantation and reimplantation procedures were carried out 2 months later.\n", "Postexplantation device analysis by the manufacturer demonstrated silicone touch-up at the site of failure. Six years since reimplantation, the patient has remained symptom-free. It is very likely that the touch-up silicon weakened the electrode and, in conjunction with chronic scar contraction, led to the tear on the silicon casing.\n", "\n", "Question: Do cochlear implant electrode failure secondary to silicone touch-up during device manufacturing?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, cochlear implant electrode failure can occur secondary to silicone touch-up during device manufacturing, as indicated by the case report where silicone touch-up was associated with the weakening of the electrode and subsequent failure.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: While incidence, mortality, morbidity, and recurrence rates of C. difficile infection (CDI) among the critically ill have been investigated, the impact of its recurrence on 30-day rehospitalization (ReAd), an important policy focus, has not been examined.\n", "Secondary analysis of a multicenter retrospective cohort study Patients Adult critically ill patients who survived their index hospitalization complicated by CDI METHODS: CDI was defined by diarrhea or pseudomembranous colitis and a positive assay for C. difficile toxins A and/or B. CDI recurrence (rCDI) was defined as diarrhea, positive C. difficile toxin and need for retreatment after cessation of therapy. Descriptive statistics and a logistic regression examined ReAd rates and characteristics, and factors that impact it.\n", "Among 287 hospital survivors, 76 (26.5%) required ReAd (ReAd+). At baseline, the ReAd+ group did not differ significantly from the ReAd- group based on demographics, comorbidities, APACHE II scores, or ICU type. ReAd+ patients were more likely to have hypotension at CDI onset (48.7% vs 34.1%, P=.025) and to require vasopressors (40.0% vs 27.1%, P=.038); they were less likely to require mechanical ventilation (56.0% vs 77.3%, P<.001). A far greater proportion of ReAd+ than ReAd- had developed a recurrence either during the index hospitalization or within 30 days after discharge (32.89% vs 2.84%, P<.001). In a logistic regression, rCDI was a strong predictor of ReAd+ (adjusted odd ratio, 15.33, 95% confidence interval, 5.68-41.40).\n", "\n", "Question: Is clostridium difficile recurrence a strong predictor of 30-day rehospitalization among patients in intensive care?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, clostridium difficile recurrence is a strong predictor of 30-day rehospitalization among patients in intensive care.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Maternal gut microbiota and milk composition could modify offspring microbiota and therefore disease susceptibility. The effect of maternal high-protein (HP) or prebiotic diets on maternal milk composition and gut microbiota in rat dams and offspring was examined.\n", "Wistar rat dams were fed a control, HP (40% wt/wt), or high-prebiotic-fiber (21.6% wt/wt) (HF) diet throughout pregnancy and lactation. Pups were challenged with a high-fat/sucrose diet from 14.5 to 22.5 weeks of age. Dam milk was analyzed for fat, protein, and oligosaccharides (OS). Fecal microbiota was analyzed in dams at parturition and 2 weeks post-partum and in offspring at 5 and 22 weeks along with cecal digesta at termination.\n", "Maternal milk differed only in OS content, each diet group being distinguishable. HF1 and HP1 offspring had decreased plasma lipopolysaccharide compared with C1. Offspring sex, maternal diet, and time (5 weeks vs. 22 weeks of age) affected the microbial groups examined. Bifidobacteria was higher in HF dams and offspring.\n", "\n", "Question: Do maternal high-protein or high-prebiotic-fiber diets affect maternal milk composition and gut microbiota in rat dams and their offspring?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, maternal high-protein or high-prebiotic-fiber diets affect maternal milk composition and gut microbiota in rat dams and their offspring.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To determine whether lovastatin affects the epithelial-mesenchymal transition (EMT) in porcine lens epithelial cells (LECs) induced by transforming growth factor-β (TGF-β).\n", "Porcine LECs were cultured in Dulbecco's Modified Eagle Medium (DMEM) for 24 h. The cultured cells were then exposed or not exposed to lovastatin (10 µM) for 18 h and then stimulated with or not stimulated with TGF-β2 (5 ng/ml) for 24 h. The expression of α-smooth muscle actin (α-SMA), a marker of myofibroblasts, was determined by real-time PCR, and the expression of α-SMA protein was determined by Western blot. The effect of lovastatin on the expression of the mRNA of collagen type 1 (COL1) was determined by real-time PCR. To assess cell contractility, LECs were cultured in collagen gel with or without pretreatment of lovastatin and exposure of TGF-β2. The longest and shortest diameters of the gels were measured and the area was determined.\n", "Exposure of LECs to TGF-β2 increased the expression of the mRNA and protein of α-SMA and the mRNA of COL1A1. TGF-β2 increased the degree of contraction of collagen gel. These findings indicated that TGF-β2 promoted EMT, and the pretreatment of the LECs with lovastatin blocked these changes induced by TGF-β2.\n", "\n", "Question: Does lovastatin alter TGF-β-induced epithelial-mesenchymal transition in porcine lens epithelial cells?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, lovastatin alters TGF-β-induced epithelial-mesenchymal transition in porcine lens epithelial cells by blocking the changes induced by TGF-β2.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Hemorrhagic shock is the primary cause of morbidity and mortality in the intensive care units in patients under the age of 35. Several organs, including the lungs, are seriously affected by hemorrhagic shock and inadequate resuscitation. Excess free fatty acids have shown to trigger inflammation in various disease conditions. C75 is a small compound that inhibits fatty acid synthase, a key enzyme in the control of fatty acid metabolism that also stimulates fatty acid oxidation. We hypothesized that C75 treatment would be protective against hemorrhagic shock.\n", "Adult male Sprague-Dawley rats were cannulated with a femoral artery catheter and subjected to controlled bleeding. Blood was shed to maintain a mean arterial pressure of 30 mm Hg for 90 minutes, then resuscitated over 30 minutes with a crystalloid volume equal to twice the volume of shed blood. Fifteen minutes into the 30-minute resuscitation, the rats received either intravenous infusion of C75 (1 mg/kg body weight) or vehicle (20% dimethyl sulfoxide). Blood and tissue samples were collected 6 hours after resuscitation (ie, 7.5 hours after hemorrhage) for analysis.\n", "After hemorrhage and resuscitation, C75 treatment decreased the increase in serum free fatty acids by 48%, restored adenosine triphosphate levels, and stimulated carnitine palmitoyl transferase-1 activity. Administration of C75 decreased serum levels of markers of injury (aspartate aminotransferase, lactate, and lactate dehydrogenase) by 38%, 32%, and 78%, respectively. Serum creatinine and blood urea nitrogen were also decreased significantly by 38% and 40%, respectively. These changes correlated with decreases in neutrophil infiltration in the lung, evidenced by decreases in Gr-1-stained cells and myeloperoxidase activity and improved lung histology. Finally, administration of C75 decreased pulmonary mRNA levels of cyclooxygenase-2 and interleukin-6 by 87% and 65%, respectively.\n", "\n", "Question: Does inhibition of fatty acid synthase with C75 decrease organ injury after hemorrhagic shock?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, inhibition of fatty acid synthase with C75 decreases organ injury after hemorrhagic shock.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Papillary cancer is the most common neoplasm of the thyroid. The mainstay of treatment is thyroidectomy, but most patients are additionally treated with radioactive iodine (RAI). Its utility is controversial. This study seeks to determine whether RAI use affects patient outcome and to identify specific cohorts of patients that benefit from its use.\n", "The Surveillance, Epidemiology, and End Results (SEER) database is a large-scale sample of approximately 14% of the US population. It was used to identify patients with papillary carcinoma of the thyroid. Statistical analyses were used to compare prognostic factors such as lymph node status, age, tumor size, and treatment with RAI.\n", "A total of 14,545 patients were identified in SEER as having papillary cancer of the thyroid. Multivariate analysis showed significantly worse outcome in patients with age>45 years, tumor size >2 cm, lymph node disease, and distant metastases. Multivariate analysis failed to show RAI significantly affecting mortality. Survival between those not treated with RAI was similar to those whose treatment included it (P = 0.9176). Subgroup analysis identified patients older than 45 years with primary tumors >2 cm and disease in the lymph nodes with distant metastatic disease as the only group positively affected by RAI.\n", "\n", "Question: Is survival in patients with papillary thyroid cancer affected by the use of radioactive isotope?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"No, survival in patients with papillary thyroid cancer is not significantly affected by the use of radioactive iodine, except for a specific subgroup of patients.\"\n", "Solutions: no\n", "Score: 1.0\n", "The solution is correct.Questions: Context: An effective HIV vaccine will likely require induction of both mucosal and systemic cellular and humoral immune responses. We investigated whether intramuscular (IM) delivery of electroporated plasmid DNA vaccine and simultaneous protein vaccinations by intranasal (IN) and IM routes could be combined to induce mucosal and systemic cellular and humoral immune responses to a model HIV-1 CN54 gp140 antigen in mice.\n", "Co-immunisation of DNA with intranasal protein successfully elicited both serum and vaginal IgG and IgA responses, whereas DNA and IM protein co-delivery did not induce systemic or mucosal IgA responses. Cellular IFNγ responses were preserved in co-immunisation protocols compared to protein-only vaccination groups. The addition of DNA to IN protein vaccination reduced the strong Th2 bias observed with IN protein vaccination alone. Luminex analysis also revealed that co-immunisation with DNA and IN protein induced expression of cytokines that promote B-cell function, generation of TFH cells and CCR5 ligands that can reduce HIV infectivity.\n", "\n", "Question: Does plasmid DNA Vaccine Co-Immunisation modulate Cellular and Humoral Immune Responses Induced by Intranasal Inoculation in Mice?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, plasmid DNA Vaccine Co-Immunisation does modulate Cellular and Humoral Immune Responses Induced by Intranasal Inoculation in Mice.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To observe the effects of hydroxycamptothecin (HCPT) on the apoptosis of prostate cancer cell line PC-3 and to explore the possible mechanism.\n", "The influence of different concentrations (1 x 10(-1), 1 x 10(-2), 1 x 10(-3), 1 x 10(-4) mg/ml) of HCPT on PC-3 cell proliferation at different time (12, 24, 48 h) was determined by tetrazolium (MTT) assay. The morphologic changes of the apoptotic cells were observed by acridine orange/ethidium bromide dyeing. The DNA of the apoptotic cells was analyzed with agarose gel electrophoresis. The apoptosis rate of HCPT on prostate cancer cells was analyzed by flow cytometry (FCM).\n", "The growth of PC-3 was inhibited by HCPT in a time- and dose- dependent manner. The values of IC50 were 6.50 x 10(-2) mg/ ml (12 h), 2.35 x 10(-2) mg/ml (24 h) and 5.31 x 10(-3) mg/ml (48 h) respectively. The typical apoptotic cells under the fluorescence microscope showed budding phenomena and apoptotic bodies. And the DNA ladder was observed in ultraviolet light. FCM analysis showed that the apoptosis rate of PC-3 cells increased with the increasing dose of HCPT, which reached the peak (35.76%) at 1 x 10(-3) mg/ml.\n", "\n", "Question: Does [ Hydroxycamptothecin promote the apoptosis of prostate cancer cell line PC-3 ]?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, hydroxycamptothecin promotes the apoptosis of the prostate cancer cell line PC-3.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Acute pulmonary embolism (PE) may be rapidly fatal if not diagnosed and treated. IV heparin reduces mortality and recurrence of PE, but the relationship between survival and timing of anticoagulation has not been extensively studied.\n", "We studied 400 consecutive patients in the ED diagnosed with acute PE by CT scan angiography and treated in the hospital with IV unfractionated heparin from 2002 to 2005. Patients received heparin either in the ED or after admission. Time from ED arrival to therapeutic activated partial thromboplastin time (aPTT) was calculated. Outcomes included in-hospital and 30-day mortality, hospital and ICU lengths of stay, hemorrhagic events on heparin, and recurrent venous thromboembolism within 90 days.\n", "In-hospital and 30-day mortality rates were 3.0% and 7.7%, respectively. Patients who received heparin in the ED had lower in-hospital (1.4% vs 6.7%; P = .009) and 30-day (4.4% vs 15.3%; P < .001) mortality rates as compared with patients given heparin after admission. Patients who achieved a therapeutic aPTT within 24 h had lower in-hospital (1.5% vs 5.6%; P = .093) and 30-day (5.6% vs 14.8%; P = .037) mortality rates as compared with patients who achieved a therapeutic aPTT after 24 h. In multiple logistic regression models, receiving heparin in the ED remained predictive of reduced mortality, and ICU admission remained predictive of increased mortality.\n", "\n", "Question: Is early anticoagulation associated with reduced mortality for acute pulmonary embolism?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, early anticoagulation is associated with reduced mortality for acute pulmonary embolism.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The accumulation of neutrophils at inflammatory sites results in excessive release of toxic metabolites causing tissue injury. Proinflammatory cytokines may cause the breakdown of homeostasis of neutrophil numbers through inhibition of apoptosis.\n", "Neutrophils were isolated from healthy humans and from patients with multiple injuries on day of admission and during septic complications. Apoptosis was quantitated using propidium iodide fluorescence and the TUNEL method. Tyrosine phosphorylation was measured by flow cytometry.\n", "Neutrophil apoptosis was decreased (33.3 +/- 5.5%; p < 0.05) in injured patients with sepsis compared with healthy humans (87.2 +/- 3.0%) and injured patients without sepsis (76.0 +/- 2.0%). Serum from injured patients with sepsis inhibited (p < 0.05) apoptosis of neutrophils from healthy humans in a dose-dependent manner. Serum from healthy humans and from injured patients at admission was ineffective. Neutralization of granulocyte-colony stimulating factor, but not of granulocyte-macrophage-colony stimulating factor, in serum of injured patients with sepsis partially abrogated (+51.2%) serum induced prolongation of neutrophil life span. Reduction of neutrophil apoptosis was concomitant with increased tyrosine phosphorylation.\n", "\n", "Question: Do circulating mediators in serum of injured patients with septic complications inhibit neutrophil apoptosis through up-regulation of protein-tyrosine phosphorylation?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, circulating mediators in serum of injured patients with septic complications inhibit neutrophil apoptosis through up-regulation of protein-tyrosine phosphorylation.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: We investigated the pathophysiological changes in mice lacking α2-antiplasmin (α2-AP) and plasminogen activator inhibitor type-1 (PAI-1) genes, and elucidated the involvement of these inhibitors for fibrinolysis in immune response.\n", "The pathophysiological changes induced by a lack of both α2-AP and PAI-1 were investigated using double knockout (KO) mice. The lung, liver, kidney and spleen tissues from α2-AP/PAI-1-double KO mice were compared with those from wild-type (WT) mice. Furthermore, the bone marrow cells from α2-AP/PAI-1-double KO mice were transplanted into 10-Gy X ray irradiated WT mice, and then the effects of the transplantation were studied.\n", "Plasma IgE levels in the α2-AP/PAI-1-double KO mice increased with age and exceeded 1000 ng/mL after 6 months of age. The plasma cells that produced IgE were detected in perivascular assembled lymphocytes. In the α2-AP/PAI-1-double KO mice, perivascular lymphocyte infiltration was observed in the lung, liver, and kidneys and peribronchial lymphocyte infiltration was present in the lung. When the bone marrow cells from α2-AP/PAI-1-double KO mice were transplanted into 10-Gy X ray irradiated WT mice, the phenotypes of the recipients were similar to those of α2-AP/PAI-1-double KO mice.\n", "\n", "Question: Does lack of both α2-antiplasmin and plasminogen activator inhibitor type-1 induce high IgE production?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, the lack of both α12-antiplasmin and plasminogen activator inhibitor type-1 induces high IgE production, as indicated by the increase in plasma IgE levels exceeding 1000 ng/mL in α12-AP/PAI-1-double KO mice after 6 months of age.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Emergency medicine (EM) faculty often aim to improve resident performance by enhancing the quality and delivery of feedback. The acceptance and integration of external feedback is influenced by multiple factors. However, it is interpreted through the \"lens\" of the learner's own self-assessment. Ideally, following an educational activity with feedback, a learner should be able to generate and act upon specific learning goals to improve performance. Examining the source of generated learning goals, whether from one's self-assessment or from external feedback, might shed light on the factors that lead to improvement and guide educational initiatives. Using a standard oral board scenario, the objective of this study was to determine the effects that residents' self-assessment and specific feedback from faculty have on not only the generation of learning goals but also the execution of these goals for performance improvement.\n", "In this cross-sectional educational study at four academic programs, 72 senior EM residents participated in a standardized oral board scenario. Following the scenario, residents completed a self-assessment form. Next, examiners used a standardized checklist to provide both positive and negative feedback. Subsequently, residents were asked to generate \"SMART\" learning goals (specific, measurable, attainable, realistic, and time-bound). The investigators categorized the learning goals as stemming from the residents' self-assessments, feedback, or both. Within 4 weeks, the residents were asked to recall their learning goals and describe any actions taken to achieve those goals. These were grouped into similar categories. Descriptive statistics were used to summarize the data.\n", "A total of 226 learning goals were initially generated (mean ± SD = 3.1 ± 1.3 per resident). Forty-seven percent of the learning goals were generated by the residents' self-assessments only, while 27% were generated by the feedback given alone. Residents who performed poorly on the case incorporated feedback more often than high performers when generating learning goals. Follow-up data collection showed that 62 residents recalled 89 learning goals, of which 52 were acted upon. On follow-up, the numbers of learning goals from self-assessment and feedback were equal (25% each, 13 of 52), while the greatest number of reportedly executed learning goals came from self-assessments and feedback in agreement (40%).\n", "\n", "Question: Do emergency medicine residents ' self-assessments play a critical role when receiving feedback?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, emergency medicine residents' self-assessments play a critical role when receiving feedback, as they influence the generation of learning goals and the execution of those goals for performance improvement.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Chlorpromazine (CPZ), a commonly used antipsychotic drug, was found to play a neuroprotective role in various models of toxicity. However, whether CPZ has the potential to affect brain apoptosis in vivo is still unknown. The purpose of this study was to investigate the potential effect of CPZ on the apoptosis induced by exogenous stimuli.\n", "The ethanol treated infant rat was utilized as a valid apoptotic model, which is commonly used and could trigger robust apoptosis in brain tissue. Prior to the induction of apoptosis by subcutaneous injection of ethanol, 7-day-old rats were treated with CPZ at several doses (5 mg/kg, 10 mg/kg and 20 mg/kg) by intraperitoneal injection. Apoptotic cells in the brain were measured using TUNEL analysis, and the levels of cleaved caspase-3, cytochrome c, the pro-apoptotic factor Bax and the anti-apoptotic factor Bcl-2 were assessed by immunostaining or western blot.\n", "Compared to the group injected with ethanol only, the brains of the CPZ-pretreated rats had fewer apoptotic cells, lower expression of cleaved caspase-3, cytochrome c and Bax, and higher expression of Bcl-2. These results demonstrate that CPZ could prevent apoptosis in the brain by regulating the mitochondrial pathway.\n", "\n", "Question: Does chlorpromazine protect against apoptosis induced by exogenous stimuli in the developing rat brain?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, chlorpromazine protects against apoptosis induced by exogenous stimuli in the developing rat brain.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To investigate the best standardized uptake value (SUV) index for differentiation of adrenal metastases from adrenocortical adenomas using 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT).\n", "A total of 129 patients (82 males and 47 females; mean age 65.4 years) with extra-adrenal primary malignancies who had known or suspected adrenal lesions underwent FDG PET/CT examinations for detection, staging, re-staging, or recurrence of tumor. Among these patients, 45 adrenal lesions (22 adenomas and 23 metastases) in 41 patients were evaluated. The maximum SUVs for adrenal lesions (adrenal SUVmax) and mean liver and spleen SUVs were recorded, and the ratio of the adrenal SUVmax to the mean liver SUV (adrenal-to-liver SUV ratio) and that of the adrenal SUVmax to the mean spleen SUV (adrenal-to-spleen SUV ratio) were obtained. Diagnostic performances for the adrenal SUVmax, adrenal-to-liver SUV ratio, and adrenal-to-spleen SUV ratio were compared.\n", "The mean adrenal SUVmax, adrenal-to-liver SUV ratio, and adrenal-to-spleen SUV ratio were higher for adrenal metastases (8.4 ± 3.8, 3.0 ± 1.3, and 4.0 ± 1.9, respectively) than for adrenocortical adenomas (2.9 ± 1.0, 0.9 ± 0.3, and 1.3 ± 0.3, respectively) (P < 0.001). The area under the curve was higher for the adrenal-to-liver SUV ratio (0.99) than for the adrenal SUVmax (0.96) and adrenal-to-spleen SUV ratio (0.98). In the differentiation of adrenocortical adenomas and adrenal metastases, an adrenal-to-liver SUV ratio cutoff value of 1.37 yielded a sensitivity of 96% and specificity of 100%.\n", "\n", "Question: Is adrenal-to-liver SUV ratio the best parameter for differentiation of adrenal metastases from adenomas using 18F-FDG PET/CT?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, the adrenal-to-liver SUV ratio is the best parameter for differentiation of adrenal metastases from adenomas using 18F-FDG PET/CT, as it has the highest area under the curve and provides excellent sensitivity and specificity.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Impaired sarcoplasmic reticulum (SR) Ca(2+) cycling and depressed contractility, a hallmark of human and experimental heart failure, has been partially attributed to increased protein phosphatase 1 (PP-1) activity, associated with down-regulation of its endogenous inhibitor-1. The levels and activity of inhibitor-1 are reduced in failing hearts, contributing to dephosphorylation and inactivation of key calcium cycling proteins. Therefore, we investigated the mechanisms that mediate decreases in inhibitor-1 by post-transcriptional modification.\n", "Bioinformatics revealed that 17 human microRNAs may serve as modulators of inhibitor-1. However, real-time PCR analysis identified only one of these microRNAs, miR-765, as being increased in human failing hearts concomitant with decreased inhibitor-1 levels. Expression of miR-765 in HEK293 cells or mouse ventricular myocytes confirmed suppression of inhibitor-1 levels through binding of this miR-765 to the 3'-untranslated region of inhibitor-1 mRNA. To determine the functional significance of miR-765 in Ca(2+) cycling, pri-miR-765 as well as a non-translated nucleotide sequence (miR-Ctrl) were expressed in adult mouse ventricular myocytes. The inhibitor-1 expression levels were decreased, accompanied by enhanced PP-1 activity in the miR-765 cardiomyocytes, and these reflected depressed contractile mechanics and Ca(2+) transients, compared with the miR-Ctrl group. The depressive effects were associated with decreases in the phosphorylation of phospholamban and SR Ca(2+) load. These miR-765 negative inotropic effects were abrogated in inhibitor-1-deficient cardiomyocytes, suggesting its apparent specificity for inhibitor-1.\n", "\n", "Question: Is up-regulation of micro-RNA765 in human failing hearts associated with post-transcriptional regulation of protein phosphatase inhibitor-1 and depressed contractility?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, the up-regulation of micro-RNA765 in human failing hearts is associated with post-transcriptional regulation of protein phosphatase inhibitor-1 and depressed contractility.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.\n", "{'name': 'context_analysis3328', 'description': 'Task to context_analysis3328. Takes question as input. Produces context as output.', 'inputs': [{'name': 'question', 'type': 'str', 'description': 'Input parameter question for context_analysis3328', 'required': False}], 'outputs': [{'name': 'context', 'type': 'str', 'description': 'Output parameter context from context_analysis3328', 'required': True}], 'prompt': '```xml\\n\"\"\"\\nAnalyze the context of the question step by step to ensure a relevant and accurate response. Begin by identifying key components of the question and any potential ambiguities. Explain your thought process clearly in the field, detailing how you arrived at your conclusions. Provide the final answer in the field, ensuring it directly addresses the clarified question. Format your output in XML, using {thought} and {answer}.\\n\"\"\"\\n```', 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"Think step by step to answer the question based on the question context. You should integrate context for answering. You should explain your thinking process in the 'thought' field, and provide the final answer in the 'answer' field.\\nFormat your output in xml format, such as xxx and xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[32m2026-01-06 08:45:54.463\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.319 | Total tokens: 6725209 | Current cost: $0.004 | Current tokens: 20934\u001b[0m\n", "\u001b[32m2026-01-06 08:45:55.774\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.320 | Total tokens: 6725375 | Current cost: $0.000 | Current tokens: 166\u001b[0m\n", "\u001b[32m2026-01-06 08:45:57.423\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.320 | Total tokens: 6726382 | Current cost: $0.000 | Current tokens: 1007\u001b[0m\n", "{'name': 'handle_ambiguities7850', 'description': 'Task to handle_ambiguities7850. Takes context as input. Produces clarified_question as output.', 'inputs': [{'name': 'context', 'type': 'str', 'description': 'Input parameter context for handle_ambiguities7850', 'required': False}], 'outputs': [{'name': 'clarified_question', 'type': 'str', 'description': 'Output parameter clarified_question from handle_ambiguities7850', 'required': True}], 'prompt': '```xml\\n\"\"\"\\nTo effectively answer the question, follow these steps:\\n\\n1. Analyze the context derived from `{context}` to identify any specific nuances or details that may influence the answer.\\n2. If ambiguities are present, clarify the question by addressing specific aspects that need further explanation or detail.\\n3. Integrate the clarified context into your reasoning process to ensure the answer is relevant and comprehensive.\\n4. Provide a clear and concise final answer in the `{answer}` field, ensuring it directly addresses the user\\'s inquiry and incorporates any necessary details or examples.\\n\\nFormat your output in XML format, using to explain your reasoning process and for the final response.\\n\"\"\"\\n```', 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"Think step by step to answer the question based on the question context. You should integrate context for answering. You should explain your thinking process in the 'thought' field, and provide the final answer in the 'answer' field.\\nFormat your output in xml format, such as xxx and xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n", "\u001b[32m2026-01-06 08:46:00.057\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.323 | Total tokens: 6747323 | Current cost: $0.004 | Current tokens: 20941\u001b[0m\n", "\u001b[32m2026-01-06 08:46:02.636\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.323 | Total tokens: 6747626 | Current cost: $0.000 | Current tokens: 303\u001b[0m\n", "\u001b[32m2026-01-06 08:46:05.334\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.324 | Total tokens: 6749073 | Current cost: $0.000 | Current tokens: 1447\u001b[0m\n", "{'name': 'generate_answer', 'description': 'Draft an answer using the retrieved context.', 'inputs': [{'name': 'question', 'type': 'str', 'description': 'The original question from the user.', 'required': True}], 'outputs': [{'name': 'draft_answer', 'type': 'str', 'description': 'A concise, direct answer to the question.', 'required': True}], 'prompt': '\"\"\"\\nYou can think to generate answers based on the provided {question}. Ensure that your response is clear and concise, considering whether a simple \"Yes\" or \"No\" is sufficient or if a more nuanced answer is required. If the {question} is ambiguous or lacks detail, indicate this in your response and suggest specific clarifying questions to gather more information. Format your final answer in the \\'answer\\' field as xxx. If the draft answer requires significant revision, note the necessary changes before proceeding to validation. Prioritize and weigh evidence carefully to enhance the reliability of your answer.\\n\"\"\"', 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"You can think to generate answers. You should provide the final answer (either Yes or No) in the 'answer' field. Format your answer in xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n", "\u001b[32m2026-01-06 08:46:07.622\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.327 | Total tokens: 6769940 | Current cost: $0.004 | Current tokens: 20867\u001b[0m\n", "\u001b[32m2026-01-06 08:46:10.527\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.328 | Total tokens: 6770262 | Current cost: $0.000 | Current tokens: 322\u001b[0m\n", "\u001b[32m2026-01-06 08:46:12.566\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.328 | Total tokens: 6771576 | Current cost: $0.000 | Current tokens: 1314\u001b[0m\n", "{'name': 'validate_answer9330', 'description': 'Task to validate_answer9330. Takes draft_answer as input. Produces validated_answer as output.', 'inputs': [{'name': 'draft_answer', 'type': 'str', 'description': 'Input parameter draft_answer for validate_answer9330', 'required': False}], 'outputs': [{'name': 'validated_answer', 'type': 'str', 'description': 'Output parameter validated_answer from validate_answer9330', 'required': True}], 'prompt': '\"\"\"\\nThink step by step to answer the question based on the context provided in {question}. Begin by identifying the key components, underlying issues, and any ambiguities within the question. In the \\'thought\\' field, explain your reasoning process, detailing how you arrived at your conclusions and addressing any complexities present in the question. If ambiguities are identified, clarify them before proceeding. Then, provide a clear and concise final answer in the \\'answer\\' field, ensuring it is directly relevant to the user\\'s needs. Format your output in XML format, such as {thought} and {answer}.\\n\"\"\"', 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"Think step by step to answer the question based on the question context. You should integrate context for answering. You should explain your thinking process in the 'thought' field, and provide the final answer in the 'answer' field.\\nFormat your output in xml format, such as xxx and xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n", "\u001b[32m2026-01-06 08:46:15.473\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.331 | Total tokens: 6792478 | Current cost: $0.004 | Current tokens: 20902\u001b[0m\n", "\u001b[32m2026-01-06 08:46:17.043\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.331 | Total tokens: 6792635 | Current cost: $0.000 | Current tokens: 157\u001b[0m\n", "\u001b[32m2026-01-06 08:46:18.915\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.332 | Total tokens: 6793819 | Current cost: $0.000 | Current tokens: 1184\u001b[0m\n", "{'name': 'evaluate_answer9619', 'description': 'Task to evaluate_answer9619. Takes validated_answer as input. Produces evaluation_score as output.', 'inputs': [{'name': 'validated_answer', 'type': 'str', 'description': 'Input parameter validated_answer for evaluate_answer9619', 'required': False}], 'outputs': [{'name': 'evaluation_score', 'type': 'str', 'description': 'Output parameter evaluation_score from evaluate_answer9619', 'required': True}], 'prompt': '\"\"\"\\nThink step by step to answer the question based on the context provided in {question}. Begin by analyzing the key components of the question to identify the main issue and any underlying factors. If the question is ambiguous, clarify the necessary details before proceeding. Integrate this context into your reasoning process. In the \\'thought\\' field, explain your reasoning, how you arrived at your conclusion, and any clarifications made. Provide the final answer in the \\'answer\\' field, ensuring it directly addresses the main issue identified. Format your output in XML format, such as {thought} and {answer}. Additionally, ensure that your answer is validated against predefined criteria for accuracy and relevance before finalizing it, and be prepared to revisit earlier steps based on the evaluation score if necessary.\\n\"\"\"', 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"Think step by step to answer the question based on the question context. You should integrate context for answering. You should explain your thinking process in the 'thought' field, and provide the final answer in the 'answer' field.\\nFormat your output in xml format, such as xxx and xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[32m2026-01-06 08:46:21.622\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.335 | Total tokens: 6814759 | Current cost: $0.004 | Current tokens: 20940\u001b[0m\n", "\u001b[32m2026-01-06 08:46:23.115\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.335 | Total tokens: 6814907 | Current cost: $0.000 | Current tokens: 148\u001b[0m\n", "\u001b[32m2026-01-06 08:46:26.025\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.336 | Total tokens: 6816236 | Current cost: $0.000 | Current tokens: 1329\u001b[0m\n", "{'name': 'feedback_loop7764', 'description': 'Task to feedback_loop7764. Takes evaluation_score, draft_answer as input. Produces improved_answer as output.', 'inputs': [{'name': 'evaluation_score', 'type': 'str', 'description': 'Input parameter evaluation_score for feedback_loop7764', 'required': False}, {'name': 'draft_answer', 'type': 'str', 'description': 'Input parameter draft_answer for feedback_loop7764', 'required': False}], 'outputs': [{'name': 'improved_answer', 'type': 'str', 'description': 'Output parameter improved_answer from feedback_loop7764', 'required': True}], 'prompt': '\"\"\"\\nThink step by step to answer the question based on the context derived from {question}. Begin by analyzing the context to identify any ambiguities or complexities in the inquiry. Then, integrate this context into your reasoning process to formulate a well-informed answer. In the \\'thought\\' field, explain your reasoning, including how the context influenced your answer. Provide the final answer in the \\'answer\\' field, ensuring it is clear and directly addresses the user\\'s question.\\nFormat your output in xml format, such as xxx and xxx.\\n\"\"\"', 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"Think step by step to answer the question based on the question context. You should integrate context for answering. You should explain your thinking process in the 'thought' field, and provide the final answer in the 'answer' field.\\nFormat your output in xml format, such as xxx and xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n", "\u001b[32m2026-01-06 08:46:37.184\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.339 | Total tokens: 6837174 | Current cost: $0.004 | Current tokens: 20938\u001b[0m\n", "\u001b[32m2026-01-06 08:46:39.737\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.339 | Total tokens: 6837438 | Current cost: $0.000 | Current tokens: 264\u001b[0m\n", "\u001b[32m2026-01-06 08:46:41.551\u001b[0m | \u001b[1mINFO \u001b[0m | 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"text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Evaluating workflow: 100%|██████████| 50/50 [01:26<00:00, 1.73s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "\u001b[32m2026-01-06 08:48:08.075\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.optimizers.qastructure_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m1057\u001b[0m - \u001b[1mStep 4 metrics: {'f1': 0.0, 'em': 0.0, 'acc': 0.94}\u001b[0m\n", "randomly update dataset\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[32m2026-01-06 08:48:13.444\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.353 | Total tokens: 6907348 | Current cost: $0.003 | Current tokens: 19751\u001b[0m\n", "\u001b[32m2026-01-06 08:48:15.459\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.356 | Total tokens: 6927113 | Current cost: $0.003 | Current tokens: 19765\u001b[0m\n", "\u001b[32m2026-01-06 08:48:17.165\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.360 | Total tokens: 6946865 | Current cost: $0.003 | Current tokens: 19752\u001b[0m\n", "\u001b[32m2026-01-06 08:48:19.101\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.360 | Total tokens: 6947521 | Current cost: $0.000 | Current tokens: 656\u001b[0m\n", "The identified issues across the workflows highlight several critical flaws: first, there is a consistent lack of integration between context analysis and answer generation, leading to disjointed responses; second, the validation process is poorly structured, with validation occurring before ambiguities are addressed, risking the acceptance of incorrect answers; third, there is no mechanism for revisiting context or questions post-evaluation, which could enhance answer refinement; fourth, the control flow is flawed, particularly with the placement of validation steps, which should follow evaluation to ensure accuracy; and finally, ambiguous prompts and unclear validation criteria contribute to the risk of presenting irrelevant or misleading answers, as evidenced by multiple instances of incorrect computations and misinterpretations in the execution history.\n", "\u001b[32m2026-01-06 08:48:20.942\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.360 | Total tokens: 6948357 | Current cost: $0.000 | Current tokens: 836\u001b[0m\n", "```python\n", "steps = [\n", " {'name': 'context_analysis3328', 'args': ['question'], 'outputs': ['context']},\n", " {'name': 'handle_ambiguities7850', 'args': ['context'], 'outputs': ['clarified_question']},\n", " {'name': 'generate_answer', 'args': ['clarified_question'], 'outputs': ['draft_answer']},\n", " {'name': 'validate_answer9330', 'args': ['draft_answer'], 'outputs': ['validated_answer']},\n", " {'name': 'evaluate_answer9619', 'args': ['validated_answer'], 'outputs': ['evaluation_score']},\n", " {'name': 'feedback_loop7764', 'args': ['evaluation_score', 'draft_answer'], 'outputs': ['improved_answer']}\n", "]\n", "```\n", "Questions: Context: To determine the utilization and cost of autologous blood that was donated preoperatively, and to compare it to the cost of employing intraoperative hemodilution to provide autologous blood for patients undergoing surgical procedures with a low risk for the need for transfusion.\n", "Retrospective chart review.\n", "University medical center.\n", "All ASA physical status I and II patients who underwent nononcologic gynecologic procedures and preoperatively donated autologous blood between July 1993 and June 1994.\n", "The utilization and overall cost of predonated autologous blood was determined. The cost for employing intraoperative hemodilution and potential cost saving was then calculated. Of the 234 units of preoperatively donated autologous blood, 38 units were returned to patients who had an estimated blood loss of at least 500 ml, 32 units returned to patients who had an estimated blood loss less than 500 ml, and 164 units were wasted. No patient received allogeneic blood. The estimated total cost for all preoperatively donated autologous blood was $23,274.62. Employing hemodilution for those same patients would have cost $5,574.74, and resulted in a potential 75.6% savings.\n", "\n", "Question: Is intraoperative hemodilution more cost-effective than preoperative autologous donation for patients undergoing procedures associated with a low risk for transfusion?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, intraoperative hemodilution is more cost-effective than preoperative autologous donation for patients undergoing procedures associated with a low risk for transfusion, as it resulted in a potential 75.6% savings.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The natural history of specific morphologic stages of chronic pancreatitis (CP) is not well defined. The aim of this study was to determine if worsening morphologic stages of CP are associated with poorer clinical outcomes.\n", "A retrospective analysis of 159 subjects with CP was performed. The baseline stage of CP was categorized according to the Cambridge classification. Pain was categorized as type A (intermittent acute), B (continuous), or combined. Exocrine failure was defined by steatorrhea; endocrine failure was characterized as diabetes mellitus. Complications were defined clinically.\n", "Pancreatic duct (PD) morphology was equivocal in 37.1%, minimal in 12.6%, moderate in 7.5%, and severe in 42.8% of the patients. Over a median follow-up period of 3.7 years, the risk of developing exocrine insufficiency and diabetes was 28% and 19%, respectively. Recurrent acute flares of pancreatitis predicted the development of exocrine insufficiency (P = .004). Severe PD morphology predicted the likelihood of having persistent pain (P = .008). Patients with concurrent type A and B pain and older age at diagnosis had a greater likelihood of having persistent pain (P = .021). The risk of developing bile duct stricture was higher in the advanced morphologic stages of CP (P = .005).\n", "\n", "Question: Do recurrent flares of pancreatitis predict development of exocrine insufficiency in chronic pancreatitis?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, recurrent flares of pancreatitis predict the development of exocrine insufficiency in chronic pancreatitis.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: This study aimed to show the effect of high glucose concentrations in combination with a pharmaceutical analog of the Na+/H+ antiport inhibitor, cariporide, on scavenger receptor CD36 expression, cell adhesion, and cell migration of human monocytes derived from obese and normal individuals.\n", "Monocytes were isolated from six healthy obese individuals and six healthy age- and sex-matched controls by use of whole blood Percoll sedimentation and plastic surface monocyte binding. The density of CD36 scavenger receptors on the surface of monocytes was assessed by the use of a fluorescent fluorescein isothiocyanate (FITC)-linked monoclonal antibody. Transmigration of monocytes through laminin-1-coated filters was performed on 5-microm pore Transwell culture inserts. Monocyte attachment to laminin was estimated by a solid phase assay.\n", "High glucose concentrations caused an increase in monocytes from normal and obese individuals in the expression of CD36 receptors and positively influenced monocyte migration and adhesion to laminin. Cariporide together with glucose counteracted these effects. The effects of migration and adhesion of monocytes to laminin were specific to glucose, because the effect was significantly higher when monocytes were incubated in the presence of 20 mM of glucose than in the presence of 20 mM of fructose. Monocytes from obese subjects showed greater response than in normal to all of the studied effects, with the highest response in laminin attachment.\n", "\n", "Question: Does cariporide counteract atherosclerosis-related functions in monocytes from obese and normal individuals?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, cariporide counteracts atherosclerosis-related functions in monocytes from both obese and normal individuals by inhibiting the effects of high glucose concentrations on CD36 expression, migration, and adhesion.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Phytoestrogen genistein may be useful to treat pulmonary arterial hypertension (PAH). However, its mechanism is still not clear. The aim of the present study was to confirm the therapeutic effects of phytoestrogen genistein on PAH in monocrotaline-induced rat model and to explore its mechanism.\n", "Sprague-Dawley male rats were randomly divided into 4 groups: control group (n=8), PAH group (n=8), genistein treament group with three different doses (n=8 in each dose group) and group of PI3K inhibitor LY294002. The rat model of PAH was induced by monocrotaline (MCT). The situation of survival of rats was observed. Pathological studies of lung and heart tissues were performed. Western-blot detection of P-Akt and P-eNOS expression levels in lung tissue was carried out. Nitrate reductase analysis was used to measure nitric oxide (NO) in lung tissue.\n", "Genistein treatment resulted in significant improvement in the speed of tricuspid regurgitation, diameter of pulmonary artery, mean pulmonary artery pressure and right ventricular hypertrophy index. Genistein treatment also resulted in significant improvement in the stenosis of pulmonary artery, proliferation of smooth muscle, right ventricular hypertrophy and myocardial hypertrophy. These therapeutic effects were more obvious with increasing dose of genistein. After genistein treatment, amelioration in survival rates of PAH rats was observed. PI3K inhibitor LY294002 could block these therapeutic effects. In rat lung tissue, P-Akt, P-eNOS and NO expressions were increased significantly in genistein treatment group when compared with PAH group (p<0.05, respectively). The increase in expression level of P-Akt, P-eNOS and NO was correlated with genistein dose. P-Akt, P-eNOS and NO expressions in lung tissue increased slightly in the PI3K inhibitor LY294002 group when compared with PAH group, but the difference was not statistically significant (p>0.05).\n", "\n", "Question: Does genistein attenuate monocrotaline-induced pulmonary arterial hypertension in rats by activating PI3K/Akt/eNOS signaling?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, genistein attenuates monocrotaline-induced pulmonary arterial hypertension in rats by activating PI3K/Akt/eNOS signaling.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Tandem placement as part of low-dose-rate (LDR) brachytherapy boost for cervical cancer may be complicated by uterine perforation. The objective of this study was to describe a 10-year experience of using intraoperative ultrasound guidance in an attempt to minimize the risk of uterine perforation.\n", "Operative and inpatient records were reviewed to identify cases in which intraoperative ultrasound guidance was employed in order to assist tandem placement, and to determine whether clinical or radiographic findings subsequently suggested uterine perforation. Demographic factors were collected in order to determine the baseline risk of perforation within this population.\n", "Between 1998 and 2008, 71 patients underwent 110 ultrasound-guided placements of tandem applicators. The median age was 48 (range, 26-88) years, and 20% were older than 60 years. Disease stage was FIGO IB1 (n = 10), IB2 (n = 13), IIA (n = 4), IIB (n = 19), IIIA (n = 2), IIIB (n = 16), IVA (n = 5) and IVB (n = 2). The median gravidity was 3 (range 1-10) and median parity was 3 (range 0-10). Seven patients had a preimplant history of pelvic infection, four had a history of intrauterine contraceptive device use, and 10 had a prior history of Cesarean section delivery. Only one patient experienced infection that may have been attributable to tandem placement-associated uterine perforation. At median survivor follow-up of 34 months, 19 patients had died. The estimated 3-year disease-free and overall survival rates for the entire population were 60% and 66%, respectively.\n", "\n", "Question: Does ultrasound-guided tandem placement for low-dose-rate brachytherapy in advanced cervical cancer minimize risk of intraoperative uterine perforation?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, ultrasound-guided tandem placement for low-dose-rate brachytherapy in advanced cervical cancer minimizes the risk of intraoperative uterine perforation.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: We studied the intervention of nitric oxide (NO), prostacyclin and endothelium-derived hyperpolarizing factor (EDHF) in mediating responses to acetylcholine in thyroid arteries from euthyroid and methimazole-treated (MT) patients.\n", "Branches of the superior thyroid artery were obtained from 19 euthyroid patients and 17 MT patients (euthyroid at the time of surgery) undergoing total thyroidectomy or hemithyroidectomy. Artery rings were suspended in organ baths for isometric recording of tension.\n", "\n", "Question: Does nitric oxide mediate abnormal responsiveness of thyroid arteries in methimazole-treated patients?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, nitric oxide mediates abnormal responsiveness of thyroid arteries in methimazole-treated patients.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Mucociliary clearance (MCC) is an important mechanism of host defense in the upper and lower respiratory tract. Impaired MCC plays a critical role in the development and perpetuation of chronic rhinosinusitis (CRS). The aim of this investigation was to determine the influence of adenosine on nasal MCC, and to determine the receptors mediating this physiology in vivo.\n", "Prospective study using an animal model.\n", "Nasal MCC was measured by whole-nose scintigraphic acquisition in vivo. The effects of both endogenous and exogenous adenosine were investigated in wild-type and adenosine receptor knockout (A(2A)(-/-), A(2B)(-/-), A(2A)(-/-)A(2B)(-/-), and A(1)(-/- )A(3)(-/-)) mice.\n", "Exogenous adenosine aerosol robustly enhanced nasal MCC. The augmentation of MCC by adenosine was abolished in mice lacking both A(2A) and A(2B) receptors, but remained robust in mice lacking either A(2A) or A(2B) . Likewise, basal nasal MCC was reduced in mice lacking both the A(2A) and A(2B) receptors, but was statistically identical among wild-type mice and mice lacking either A(2A) or A(2B) .\n", "\n", "Question: Does adenosine increase nasal mucociliary clearance rate in mice through A2A and A2B adenosine receptors?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, adenosine increases nasal mucociliary clearance rate in mice through A2A and A2B adenosine receptors.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Hemopexin, an acute phase protein, can downregulate the angiotensin (ang) II type 1 receptor (AT1-R) in vitro. Whether hemopexin is involved in the responsiveness to ang II in vivo is unknown. Therefore, we tested whether variations in endogenous hemopexin activity are associated with the responsiveness of blood pressure to ang II in healthy volunteers.\n", "Healthy men (n = 33, age 26 ± 9) were studied in balance on low sodium (50 mmol Na per 24 h) and high sodium (200 mmol Na per 24 h) diet, respectively. After baseline measurements of blood pressure, ang II was infused at 0.3, 1 and 3 ng/kg per min for 1 h per dose. Hemopexin activity was measured at baseline in EDTA-plasma samples by an amidolytic assay with a chromogenic substrate suitable for hemopexin activity evaluation.\n", "During high sodium the hemopexin activity was lower; 1.6 × 10 (0.6 × 10 - 4.7 × 10) versus 2.8 × 10 (1.1 × 10 - 5.1 × 10) arbitrary units (P < 0.01) and the pressor response to 3 ng ang II/kg per minute larger than during low sodium (17.6 ± 6.5 versus 14.6 ± 6.9 mmHg, P < 0.01). Hemopexin activity negatively correlated with the pressor response to ang II during either type of sodium intake (high sodium: r = 0.42, P < 0.05; low sodium: r = 0.35, P < 0.05).\n", "\n", "Question: Is hemopexin activity associated with angiotensin II responsiveness in humans?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a major cause of juvenile sudden death and is characterized by fibro-fatty replacement of the right ventricle. Mutations in several genes encoding desmosomal proteins have been identified in ARVC. We speculated that αT-catenin, encoded by CTNNA3, might also carry mutations in ARVC patients. Alpha-T-catenin binds plakophilins and this binding contributes to the formation of the area composita, which strengthens cell-cell adhesion in contractile cardiomyocytes.\n", "We used denaturing high-performance liquid chromatography and direct sequencing to screen CTNNA3 in 76 ARVC patients who did not carry any mutations in the desmosomal genes commonly mutated in ARVC. Mutations c.281T > A (p.V94D) and c.2293_2295delTTG (p.del765L) were identified in two probands. They are located in important domains of αT-catenin. Yeast two-hybrid and cell transfection studies showed that the interaction between the p.V94D mutant protein and β-catenin was affected, whereas the p.del765L mutant protein showed a much stronger dimerization potential and formed aggresomes in HEK293T cells.\n", "\n", "Question: Are mutations in the area composita protein αT-catenin associated with arrhythmogenic right ventricular cardiomyopathy?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, mutations in the area composita protein αT-catenin are associated with arrhythmogenic right ventricular cardiomyopathy, as indicated by the identified mutations in ARVC patients and their effects on protein interactions.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To determine the activation of Mitogen activated protein (MAP) kinases in and around cartilage subjected to mechanical damage and to determine the effects of their inhibitors on impaction-induced chondrocyte death and cartilage degeneration.\n", "The phosphorylation of MAP kinases was examined with confocal microscopy and immunoblotting. The effects of MAP kinase inhibitors on impaction-induced chondrocyte death and proteoglycan (PG) loss were determined with fluorescent microscopy and 1, 9-Dimethyl-Methylene Blue (DMMB) assay. The expression of catabolic genes at mRNA levels was examined with quantitative real-time PCR.\n", "Early p38 activation was detected at 20 min and 1h post-impaction. At 24h, enhanced phosphorylation of p38 and extracellular signal-regulated protein kinase (ERK)1/2 was visualized in chondrocytes from in and around impact sites. The phosphorylation of p38 was increased by 3.0-fold in impact sites and 3.3-fold in adjacent cartilage. The phosphorylation of ERK-1 was increased by 5.8-fold in impact zone and 5.4-fold in adjacent cartilage; the phosphorylation of ERK-2 increased by 4.0-fold in impacted zone and 3.6-fold in adjacent cartilage. Furthermore, the blocking of p38 pathway did not inhibit impaction-induced ERK activation. The inhibition of p38 or ERK pathway significantly reduced injury-related chondrocyte death and PG losses. Quantitative Real-time PCR analysis revealed that blunt impaction significantly up-regulated matrix metalloproteinase (MMP)-13, Tumor necrosis factor (TNF)-α, and ADAMTS-5 expression.\n", "\n", "Question: Does mechanical impact induce cartilage degradation via mitogen activated protein kinases?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, mechanical impact induces cartilage degradation via mitogen activated protein kinases.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Barrett's esophagus (BE) is an asymptomatic, pre-malignant condition of the esophagus that can progress to esophageal adenocarcinoma (EAC). BE arises typically in individuals with long-standing gastroesophageal reflux disease (GERD). The neoplastic progression of BE has been extensively studied histologically and defined as a metaplasia- dyplasia- carcinoma sequence. However the genetic basis of this process is poorly understood. It is conceived that preclinical models of BE may facilitate discovery of molecular markers due to ease of longitudinal sampling. Clinical markers to stratify the patients at higher risk are vital to institute appropriate therapeutic intervention since EAC has very poor prognosis. We developed a dynamic in-vitro BE carcinogenesis (BEC) model by exposing naïve Barrett's epithelium cell line (BAR-T) to acid and bile at pH4 (B4), 5min/day for a year. The BEC model acquired malignant characteristics after chronic repeated exposure to B4 similar to the sequential progression of BE to EAC in vivo.\n", "To study cytogenetic changes during progressive transformation in the BEC model.\n", "We observed that the BAR-T cells progressively acquired several chromosomal abnormalities in the BEC model. Evidence of chromosomal loss (-Y) rearrangements [t(10;16) and dup (11q)] and clonal selection appeared during the early stages of the BEC model. Clonal selection resulted in a stabilized monoclonal population of cells that had a changed morphology and formed colony in soft agar. BAR-T cells grown in parallel without any exposure did not show any of these abnormalities.\n", "\n", "Question: Does prolonged exposure to acid and bile induce chromosome abnormalities that precede malignant transformation of benign Barrett 's epithelium?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, prolonged exposure to acid and bile induces chromosome abnormalities that precede malignant transformation of benign Barrett's epithelium.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Allergic asthma is caused by aberrant helper T (T(H)) type 2 immune responses in susceptible individuals, characterized by airway hyperresponsiveness, chronic airway inflammation, and mucus hypersecretion. Its prevalence continues to increase, but optimal treatment remains a challenge. The transcription factor T-bet is a master regulator of T(H)1 lineage commitment and strongly promotes interferon gamma expression during T(H)1 cell differentiation.\n", "The aim of this study was to explore the role of intranasal delivery of T-bet on the differentiation of T(H) cell subsets and airway inflammation in the ovalbumin (OVA)-induced mouse model of allergic airway inflammation.\n", "BALB/c mice were sensitized by intraperitoneal injection of OVA and challenged with nebulized OVA. Four days before the inhalation challenge, the sensitized mice were subjected to intranasal delivery of a recombinant adeno-associated virus vector carrying murine T-bet gene (AAV-T-bet). Expression of the transcription factors T-bet, GATA3, and Foxp3 was then assayed in the lungs, and airway histology was analyzed along with other inflammatory parameters, such as eosinophils and cytokines in bronchoalveolar lavage (BAL) fluid, and total and OVA-specific immunoglobulin (Ig) E in serum.\n", "Intranasal administration of AAV-T-bet efficiently balanced the T(H)1/T(H)2 transcription factor and cytokine profile and significantly decreased the number of eosinophils in BAL fluid. It also resulted in a reduction of peribronchial inflammation scores and serum IgE levels in OVA-sensitized and challenged mice during the effector phase.\n", "\n", "Question: Does intranasal delivery of T-bet modulate the profile of helper T cell immune responses in experimental asthma?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, intranasal delivery of T-bet modulates the profile of helper T cell immune responses in experimental asthma.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: There is evidence that some cases of patients with dementia with Lewy bodies (DLB) can demonstrate Alzheimer disease (AD) like reduced glucose metabolism without amyloid deposition. The aim of this study was to clarify whether regional hypometabolism is related to amyloid deposits in the DLB brain and measure the degree of regional hypometabolism.\n", "Ten consecutive subjects with DLB and 10 AD patients who underwent both Pittsburgh compound B (PiB)-PET and (18)F-fluoro-2-deoxyglucose (FDG)-PET were included in this study. Regional standardized uptake value ratio (SUVR)s normalised to cerebellar cortices were calculated in the FDG- and PiB-PET images.\n", "All AD patients and five DLB patients showed amyloid deposits (PiB positive). In the DLB group the parietotemporal and occipital metabolism were significantly lower than those in the AD group but there was no difference between the posterior cingulate hypometabolism between DLB and AD groups. There were no differences in regional glucose metabolism between PiB positive and negative DLB patients.\n", "\n", "Question: Is regional glucose metabolic reduction in dementia with Lewy bodies independent of amyloid deposition?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, regional glucose metabolic reduction in dementia with Lewy bodies is independent of amyloid deposition.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To determine in human articular chondrocytes the activity of Aldehyde dehydrogenase (ALDH), which are reported as stem/progenitor cell marker in various adult tissues and evaluate gene expression of ALDH1A isoforms.\n", "ALDH activity was evaluated by flow cytometry with Aldefluor™ assay in cells, isolated from human osteoarthritic (OA) cartilage. Its coexpression with surface markers was identified. Cells were sorted according to ALDH activity, and gene expression in sorted populations (ALDH(+) and ALDH(-)) was analyzed by RTq-PCR with Taqman(®) assay.\n", "About 40% of freshly isolated chondrocytes demonstrated ALDH activity that remarkably declined during monolayer culture. Markers CD54 and CD55 were significantly stronger expressed, while CD47, CD140b, CD146 and CD166 were depleted in ALDH-expressing (ALDH(pos)) cells. Gene expression analysis revealed significantly higher expression of chondrocyte-specific genes COL2A1, SOX9 and SERPINA1 and lower expression of osteogenic markers RUNX2 and osteocalcin (BGLAP) in sorted ALDH(+) fraction. COL1A1, ACAN, ALPL and stem cell markers NANOG, OCT4, SOX2 and ABCG2 did not differ remarkably between the populations. Genes of isoenzymes ALDH1A2, ALDH1A3 and ALDH2 were strongly expressed, while ALDH1A1 was weakly expressed in chondrocytes. Only ALDH1A2 and ALDH1A3 were significantly enriched in ALDH(+) fraction.\n", "\n", "Question: Do human articular chondrocytes with higher aldehyde dehydrogenase activity have stronger expression of COL2A1 and SOX9?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, human articular chondrocytes with higher aldehyde dehydrogenase activity have stronger expression of COL2A1 and SOX9.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Previous studies have shown that desflurane and isoflurane produce similar hemodynamic actions. This investigation examined the cardiovascular effects of desflurane and isoflurane in the presence or absence of dexmedetomidine, a highly selective alpha 2-adrenergic agonist that may be clinically useful as a premedicant or anesthetic adjuvant.\n", "Four groups, comprising 40 experiments, were performed using ten dogs that were chronically instrumented for measurement of aortic and left ventricular pressure, the maximum rate of increase of left ventricular pressure (dP/dtmax), diastolic coronary blood flow velocity, cardiac output, and subendocardial segment length. On separate experimental days, systemic and coronary hemodynamics were recorded, and plasma concentrations of catecholamines were measured with or without oral dexmedetomidine pretreatment (30 micrograms/kg) in the conscious state and after 15 min of equilibration at 1.0, 1.3, and 1.6 end-tidal MAC desflurane or isoflurane in a random fashion.\n", "In conscious dogs, dexmedetomidine significantly decreased heart rate, cardiac output, percent segment shortening (%SS), left ventricular dp/dtmax, myocardial oxygen consumption (as estimated by the pressure-work index), and plasma norepinephrine concentration. Concomitant increases in systemic and diastolic coronary vascular resistance were observed. Pretreatment with dexmedetomidine decreased peak increases in heart rate during desflurane and isoflurane anesthesia. Mean arterial pressure was reduced less by desflurane than by isoflurane in the absence of dexmedetomidine. This difference was abolished in dogs pretreated with dexmedetomidine. Desflurane, but not isoflurane, decreased cardiac output in dexmedetomidine-pretreated dogs when compared with untreated dogs. Concomitantly, systemic vascular resistance was greater in desflurane- versus isoflurane-anesthetized dogs pretreated with dexmedetomidine. No differences in myocardial contractility, as assessed by left ventricular dP/dtmax and %SS, were observed between desflurane and isoflurane groups in the absence or presence of dexmedetomidine.\n", "\n", "Question: Does dexmedetomidine alter the hemodynamic effects of desflurane and isoflurane in chronically instrumented dogs?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, dexmedetomidine alters the hemodynamic effects of desflurane and isoflurane in chronically instrumented dogs, as evidenced by changes in heart rate, cardiac output, and systemic vascular resistance in the presence of dexmedetomidine.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Recent studies have shown that prolonged Th2-type immune inflammation in the lung induces pulmonary arterial remodeling, in part through the induction of resistin-like molecule α (RELMα) expression. However, the role of interleukin-25 (IL-25; which promotes this inflammation) in the development of the pulmonary arterial remodeling remains unknown.\n", "Ovalbumin (OVA)-sensitized C57BL/6 mice were challenged with OVA inhalation 3 times a week for 3 weeks. The effects of neutralizing anti-IL-25 antibody on OVA-induced pulmonary arterial remodeling and RELMα expression in the lung were examined. The pulmonary arterial remodeling and RELMα expression in the lung were examined in lung-specific IL-25 transgenic mice (CC10 IL-25 mice) and CC10 IL-25 mice in a natural killer T (NKT) cell-deficient background (CC10 IL-25 NKT(-/-) mice).\n", "Repeated OVA inhalation induced pulmonary arterial wall thickening and the expression of IL-25 and RELMα mRNA in the lung in OVA-sensitized mice. Injection of neutralizing anti-IL-25 antibody inhibited OVA-induced pulmonary arterial wall thickening and RELMα expression in the lung. CC10 IL-25 mice, but not CC10 IL-25 NKT(-/-) mice, spontaneously developed pulmonary arterial wall thickening and RELMα expression in the lung at 6 months of age.\n", "\n", "Question: Does interleukin-25 induce pulmonary arterial remodeling via natural killer T cell-dependent mechanisms?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"No, interleukin-25 does not induce pulmonary arterial remodeling via natural killer T cell-dependent mechanisms, as indicated by the findings in CC10 IL-25 NKT(-/-) mice, which did not develop pulmonary arterial remodeling despite the presence of IL-25.\"\n", "Solutions: yes\n", "Score: 0.0\n", "Error reason: Computation result is incorrect.Questions: Context: Established biophysical neurone models have achieved limited success in reproducing electrophysiological responses to non-invasive stimulation of the human nervous system. This is related to our insufficient knowledge of the induced electric currents inside the human body. Despite the numerous research and clinical applications of non-invasive stimulation, it is still unclear which internal sites are actually affected by it.\n", "We performed multi-scale computer simulations that, by making use of advances in computing power and numerical algorithms, combine a microscopic model of electrical excitation of neurones with a macroscopic electromagnetic model of the realistic whole-body anatomy.\n", "The simulations yield responses consistent with those experimentally recorded following magnetic and electrical motor root stimulation in human subjects, and reproduce the observed amplitudes and latencies for a wide variety of stimulation parameters.\n", "\n", "Question: Do multi-scale simulations predict responses to non-invasive nerve root stimulation?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, multi-scale simulations predict responses to non-invasive nerve root stimulation.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To explore the association between serum levels of Sex Hormone Binding Globulin (SHBG) and the risk of developing prostate cancer (PCa) as well as high grade disease in men undergoing prostate biopsy.\n", "Between 2006 and 2012, we prospectively enrolled 740 patients with no history of PCa undergoing prostate biopsy. Before biopsy general data of the patient DRE, PSA and BMI were recorded. The risk of detecting cancer and high grade cancer was assessed as a function of SHBG using crude and adjusted logistic regressions.\n", "Serum levels of SHBG were not associated with an increased risk of PCa or high grade disease. Age (OR 1.027 95% CI 1.003-1.052 p = 0.027), DRE (OR 3.391 95% CI 2.258-5.092 p = 0.000) and PSA (OR 1.078 95% CI 1.037-1.120 p = 0.000) were found to be independent predictors of prostate cancer risk. Age (OR 1.051 95% CI 1.009-1.095 p = 0.016), DRE (OR 2.519 95% CI 1.384-4.584 p = 0.000), BMI (OR 1.098 95% CI 1.011-1.193 p = 0.027) and PSA (OR 1.074 95% CI 1.014-1.137 p = 0.015) were found to be independent predictors of high grade disease.\n", "\n", "Question: Are serum levels of sex hormone binding globulin ( SHBG ) predictive of prostate cancer diagnosis and aggressiveness : results from an Italian biopsy cohort?\n", "\n", "Answer:\n", "Predictions: No, serum levels of sex hormone binding globulin (SHBG) were not associated with an increased risk of prostate cancer diagnosis or aggressiveness in the study.\n", "Solutions: no\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To determine the effects of potassium chloride 60 mmol/day supplementation on clinic and 24-h ambulatory blood pressure values in elderly untreated hypertensive patients.\n", "A double-blind randomized placebo-controlled crossover study lasting 8 weeks, following a 4-week run-in period.\n", "Outpatient clinic in a district general hospital.\n", "Eighteen untreated elderly hypertensive patients (mean age 75 years, range 66-79) with a systolic blood pressure of > or = 160 mmHg and/or a diastolic blood pressure of > or = 95 mmHg were recruited from the clinics of local general practitioners and from the current hospital outpatient department. Patients had not received any antihypertensive medication for at least 4 weeks before entry into the study.\n", "Before entry into the study, the daily dietary electrolyte intake of each individual was established and this was maintained during the run-in and intervention periods. Following a 4-week run-in period patients received potassium supplements or matching placebo, each for 4 weeks.\n", "The within-patient changes in clinic and 24-h ambulatory blood pressures at the end of each intervention period.\n", "After 4 weeks potassium supplementation compared with placebo there was a significant fall in supine clinic blood pressure, standing and 24-h ambulatory systolic blood pressure. There was no significant change in clinic standing diastolic blood pressure, 24-h ambulatory diastolic blood pressure or pulse rate. Plasma renin activity increased and body weight fell after potassium supplementation. Twenty-four-hour urinary potassium rose significantly, whereas urinary sodium excretion was unchanged.\n", "\n", "Question: Does potassium supplementation reduce clinic and ambulatory blood pressure in elderly hypertensive patients?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, potassium supplementation reduces clinic and ambulatory blood pressure in elderly hypertensive patients.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Transient B cell depletion with the monoclonal anti-CD20 antibody rituximab has shown favourable clinical responses in patients with rheumatoid arthritis (RA). Recently a characteristic regeneration pattern of B cell subpopulations has been reported. However, little is known about the impact of B-cell depletion on peripheral T cells in particular regulatory T cells.\n", "17 patients with RA having failed anti-TNF were treated with rituximab. Four colour staining was performed using CD19, CD3, CD4, CD8, CD16, CD56, CD25, HLA-DR, HLA-G and intracellular Foxp3 at five time points spanning up to 12 months after rituximab. In addition, quantification of the soluble form of the HLA class I molecule HLA-G by ELISA has been performed.\n", "Peripheral B cell depletion lasted 6 to 9 months. The absolute number of CD3+, CD4+ and CD8+ lymphocytes showed no significant changes up to 1 year after B-cell depletion compared to before therapy. Only the relative frequency for CD3 and CD4 showed a significant increase (p < 0.05). In particular, CD4+CD25++ and Foxp3 positive regulatory T cells remained constant. The percentage of HLA-G positive cells in the CD4+ or CD8+ population did not change significantly either. The amount of sHLA-G remained without significant changes.\n", "\n", "Question: Is frequency of regulatory T cells affected by transient B cell depletion using anti-CD20 antibodies in rheumatoid arthritis?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"No, the frequency of regulatory T cells remained constant after transient B cell depletion using anti-CD20 antibodies in rheumatoid arthritis.\"\n", "Solutions: no\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Kawasaki disease (KD) is a systemic vasculitis childhood disease frequently complicating coronary artery lesions (CALs). Recently, the gene encoding a disintegrin and metalloprotease 17 (ADAM17) was found to modify vascular pathology in humans by differentially regulating the transforming growth factor-β (TGF-β) signaling pathway, which affects KD/CAL susceptibility. To explore the potential role of ADAM17 in KD occurrence and outcomes, we investigated the association of 28 single nucleotide polymorphisms (SNPs) in ADAM17 and three pathway genes of TGF-β signaling with KD phenotypes in a Han Chinese population, including 392 KD patients and 421 non-KD controls. Three ADAM17 SNPs showed an association with KD risk, which was further confirmed by haplotype analysis. The effect of ADAM17 on KD was also shown by multi-variable logistic regression analysis. In two-locus model analyses with SNPs in ADAM17 and TGF-β signaling pathway genes, stronger compound effects on the risk of KD and secondary CAL formation were observed relative to comparable single SNPs.\n", "\n", "Question: Are genetic variants of ADAM17 implicated in the pathological process of Kawasaki disease and secondary coronary artery lesions via the TGF-β/SMAD3 signaling pathway?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, genetic variants of ADAM17 are implicated in the pathological process of Kawasaki disease and secondary coronary artery lesions via the TGF-β/SMAD3 signaling pathway.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: This study aimed to show that SHOX2 DNA methylation is a tumor marker in patients with suspected lung cancer by using bronchial fluid aspirated during bronchoscopy. Such a biomarker would be clinically valuable, especially when, following the first bronchoscopy, a final diagnosis cannot be established by histology or cytology. A test with a low false positive rate can reduce the need for further invasive and costly procedures and ensure early treatment.\n", "Marker discovery was carried out by differential methylation hybridization (DMH) and real-time PCR. The real-time PCR based HeavyMethyl technology was used for quantitative analysis of DNA methylation of SHOX2 using bronchial aspirates from two clinical centres in a case-control study. Fresh-frozen and Saccomanno-fixed samples were used to show the tumor marker performance in different sample types of clinical relevance.\n", "Valid measurements were obtained from a total of 523 patient samples (242 controls, 281 cases). DNA methylation of SHOX2 allowed to distinguish between malignant and benign lung disease, i.e. abscesses, infections, obstructive lung diseases, sarcoidosis, scleroderma, stenoses, at high specificity (68% sensitivity [95% CI 62-73%], 95% specificity [95% CI 91-97%]).\n", "\n", "Question: Is sHOX2 DNA methylation a biomarker for the diagnosis of lung cancer based on bronchial aspirates?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, SHOX2 DNA methylation is a biomarker for the diagnosis of lung cancer based on bronchial aspirates.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Current neonatal guidelines endorse both the two-thumb and the two-finger techniques for performing chest compressions. It remains unclear whether one method is superior to the other in achieving consistent depth.\n", "To compare the compression depth, variability, rate and finger placement of the two-thumb and two-finger techniques using a compression to ventilation (CV) ratio of 3:1.\n", "25 subjects (physicians and neonatal nurses) participated with compressions performed on a manikin. Subjects were video recorded. Evaluations included continuous compression administered for 60 s, followed by 2 min of compressions using a 3:1 CV ratio for each of the two techniques.\n", "Depth during 60 s of uninterrupted compressions was greater for the two-thumb than the two-finger technique (27.2±5.7 vs 22.1±4.6 mm; p=0.0008), variability was less (6.7%±3.2% vs 9.0%±2.8%; p=0.002) and rate was comparable (118±22 vs 116±24 compressions/min). With a 3:1 CV ratio, depth was greater for the two-thumb compared to the two-finger method (29±5.4 vs 23.7±5.8 mm; p=0.0009), variability was less (6.1%±2.9% vs 9.8%±3.1%; p=0.00002) and rate was comparable (192±26 vs 197±31 compressions/2 min). Correct positioning was accomplished more often with the two-thumb than the two-finger technique (21/25 vs 3/25; p=0.0005).\n", "\n", "Question: Is the two-thumb superior to the two-finger method for administering chest compressions in a manikin model of neonatal resuscitation?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, the two-thumb method is superior to the two-finger method for administering chest compressions in a manikin model of neonatal resuscitation.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The progression of prostate cancer is accompanied by a marked suppression of the immune system, including the apoptotic death of dendritic cells (DC) responsible for the induction of antitumor immunity. In this study, we evaluated whether prostate cancer might inhibit DC generation and maturation in vitro.\n", "DC were generated from peripheral blood monocytes in the presence of the human prostate cell line LNCaP or nonmalignant cells, and characterized by light microscopy, FACScan analysis, and ability to stimulate T-cell proliferation.\n", "Prostate cancer significantly inhibited the conversion of monocytes into DC, which was assessed by the expression of DC markers CD1a and CD83. These cells were weak stimulators of T-cell proliferation, suggesting that DC generated in the prostate cancer microenvironment are functionally inhibited.\n", "\n", "Question: Does human prostate cancer regulate generation and maturation of monocyte-derived dendritic cells?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, human prostate cancer regulates the generation and maturation of monocyte-derived dendritic cells by significantly inhibiting their conversion and function.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Color and pH of meat measured 24 h post mortem are common selection objectives in pig breeding programs. Several amino acid substitutions in PRKAG3 have been associated with various meat quality traits. In our previous study ASGA0070625, a SNP next to PRKAG3, had the most significant association with meat quality traits in the Finnish Yorkshire. However, the known amino acid substitutions, including I199V, did not show any association. The aims of this study were to characterize further variation in PRKAG3 and its promoter region, and to test the association between these variants and the pH and color of pork meat.\n", "The data comprised of 220 Finnish Landrace and 230 Finnish Yorkshire artificial insemination boars with progeny information. We sequenced the coding and promoter region of PRKAG3 in these and in three additional wild boars. Genotypes from our previous genome-wide scans were also included in the data. Association between SNPs or haplotypes and meat quality traits (deregressed estimates of breeding values from Finnish national breeding value estimation for pH, color lightness and redness measured from loin or ham) was tested using a linear regression model. Sequencing revealed several novel amino acid substitutions in PRKAG3, including K24E, I41V, K131R, and P134L. Linkage disequilibrium was strong among the novel variants, SNPs in the promoter region and ASGA0070625, especially for the Yorkshire. The strongest associations were observed between ASGA0070625 and the SNPs in the promoter region and pH measured from loin in the Yorkshire and between I199V and pH measured from ham in the Landrace. In contrast, ASGA0070625 was not significantly associated with meat quality traits in the Landrace and I199V not in the Yorkshire. Haplotype analysis showed a significant association between a haplotype consisting of 199I and 24E alleles (or g.-157C or g.-58A alleles in the promoter region) and pH measured from loin and ham in both breeds (P-values varied from 1.72 × 10⁻⁴ to 1.80 × 10⁻⁸).\n", "\n", "Question: Is a combination of two variants in PRKAG3 needed for a positive effect on meat quality in pigs?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, a combination of two variants in PRKAG3 is needed for a positive effect on meat quality in pigs, as indicated by the significant association of a haplotype consisting of 199I and 24E alleles with pH measured from loin and ham in both breeds.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: The attenuation of heart rate recovery after maximal exercise (ΔHRR) is independently impaired by obstructive sleep apnea (OSA) and metabolic syndrome (MetS). Therefore, we tested the hypotheses: (1) MetS + OSA restrains ΔHRR; and (2) Sympathetic hyperactivation is involved in this impairment.\n", "Cross-sectional study.\n", "We studied 60 outpatients in whom MetS had been newly diagnosed (ATP III), divided according to apnea-hypopnea index (AHI) ≥ 15 events/h in MetS + OSA (n = 30, 49 ± 1.7 y) and AHI < 15 events/h in MetS - OSA (n = 30, 46 ± 1.4 y). Normal age-matched healthy control subjects (C) without MetS and OSA were also enrolled (n = 16, 46 ± 1.7 y).\n", "Polysomnography, microneurography, cardiopulmonary exercise test.\n", "We evaluated OSA (AHI - polysomnography), muscle sympathetic nerve activity (MSNA - microneurography) and cardiac autonomic activity (LF = low frequency, HF = high frequency, LF/HF = sympathovagal balance) based on spectral analysis of heart rate (HR) variability. ΔHRR was calculated (peak HR minus HR at first, second, and fourth minute of recovery) after cardiopulmonary exercise test. MetS + OSA had higher MSNA and LF, and lower HF than MetS - OSA and C. Similar impairment occurred in MetS - OSA versus C (interaction, P < 0.01). MetS + OSA had attenuated ΔHRR at first, second, and at fourth minute than did C, and attenuated ΔHRR at fourth minute than did MetS - OSA (interaction, P < 0.001). Compared with C, MetS - OSA had attenuated ΔHRR at second and fourth min (interaction, P < 0.001). Further analysis showed association of the ΔHRR (first, second, and fourth minute) and AHI, MSNA, LF and HF components (P < 0.05 for all associations).\n", "\n", "Question: Does obstructive Sleep Apnea impair Postexercise Sympathovagal Balance in Patients with Metabolic Syndrome?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, obstructive sleep apnea impairs postexercise sympathovagal balance in patients with metabolic syndrome.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Poor fear conditioning characterizes adult psychopathy and criminality, but it is not known whether it is related to aggressive/antisocial behavior in early childhood.\n", "Using a differential, partial reinforcement conditioning paradigm, electrodermal activity was recorded from 200 male and female children at ages 3, 4, 5, 6, and 8 years. Antisocial/aggressive and hyperactive-inattentive measures were collected at age 8.\n", "Poor electrodermal fear conditioning from ages 3 to 8 years was associated with aggressive behavior at age 8 in both males and females.\n", "\n", "Question: Is reduced electrodermal fear conditioning from ages 3 to 8 years associated with aggressive behavior at age 8 years?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, reduced electrodermal fear conditioning from ages 3 to 8 years is associated with aggressive behavior at age 8 years.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: We hypothesized that experimental cystitis induced by substance P (SP) or E. coli lipopolysaccharide (LPS) would be less severe in mice rendered mast cell deficient by genetic manipulation.\n", "Two strains of mast-cell deficient mice (WBB6F1- kitW/kitW-v or kitW/kitW-v and WCB6F1-Sl/Sld or Sl/Sld) and their congenic, normal (+/+) counterparts were used. Cystitis was induced in female mice by intravenous injection of SP (0.1 ml.; 10(-6) M) or E. coli LPS (0.1 ml.; 2 mg./ml.), and inflammation was assessed by Evans blue dye extravasation. In a separate group of kitW/kitW-v and congenic normal mice, cystitis was induced by intravesical infusion of SP (0.05 ml.; 10(-5) M) or E. coli LPS (0.05 ml.; 100 microg./ml.) and compared with intravesical pyrogen-free saline (0.05 ml.; 0.9%). Severity of cystitis was determined by histological evaluation of the bladder wall 24 hours after intravesical infusions.\n", "Intravenous SP or LPS stimulated increased plasma extravasation in congenic normal mice but not in mast cell-deficient mice. Intravesical SP or LPS resulted in increased edema, leukocytic infiltration, and hemorrhage within the bladder wall in congenic normal mice, but the only histological evidence of inflammation in the bladders of kitW/kitW-v mice was increased hemorrhage in response to LPS.\n", "\n", "Question: Do mast cells mediate the severity of experimental cystitis in mice?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, mast cells mediate the severity of experimental cystitis in mice, as evidenced by the differences in inflammation severity between mast cell-deficient mice and their normal counterparts.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To evaluate if hyaluronic acid (HA)-bound spermatozoa surpassed conventional microscopy-selected spermatozoa in the status of sperm DNA integrity by acridine orange (AO) fluorescence staining.\n", "Spermatozoa obtained from couples with indication for the intracytoplasmic sperm injection (ICSI) procedure due to male infertility (n = 34) and control males with normal sperm parameters (n = 12) were analyzed using AO fluorescence staining after density-gradient centrifugation (DGC), polyvinylpyrrolidone (PVP)-microscopic selection, and HA-binding selection to determine sperm DNA integrity.\n", "Percentages of DNA intact spermatozoa with green fluorescence were significantly higher in both PVP-microscopic selected spermatozoa (82.1 ± 24.0%) and HA-bound spermatozoa (83.9 ± 21.1%) than in spermatozoa prepared by DGC (66.8 ± 24.0%). However, there was no significant difference between the PVP-sperm and HA-sperm groups. When the percentage of green fluorescent spermatozoa prepared by DGC fell initially below 68%, both PVP-microscopic and HA-binding selection failed to select over 90% spermatozoa with intact DNA for ICSI in the male infertility group. Compared to control males with normal sperm parameters (99.3 ± 1.8%), the proportion of green fluorescence sperm after HA-binding selection from couples with male infertility (83.9 ± 21.1%) did not reach the range of > 99% reported by Yagci et al.\n", "\n", "Question: Is the efficiency of conventional microscopic selection comparable to the hyaluronic acid binding method in selecting spermatozoa for male infertility patients?\n", "\n", "Answer:\n", "Predictions: No, the efficiency of conventional microscopic selection is not comparable to the hyaluronic acid binding method in selecting spermatozoa for male infertility patients, as both methods showed significantly higher percentages of DNA intact spermatozoa than DGC, but there was no significant difference between the PVP-sperm and HA-sperm groups.\n", "Solutions: yes\n", "Score: 0.0\n", "Error reason: Computation result is incorrect.Questions: Context: The incidence of many serious infectious diseases fundamentally decline as a success of consequent vaccination regimens. However, it is a matter of discussion if vaccination might cause unspecific negative side effects on the immune system. To answer this, we performed a clinical study on children with the question as to whether there is an enhanced frequency of infection diseases after vaccination or not.\n", "The study population (n=496) was randomized to a group of vaccinated children (first vaccination on the 60th day of life, n=201) and a group of unvaccinated children (first vaccination on the 90th day of life, n=295). Frequencies of unspecific, morbidity-related signs were recorded by the mothers with a diary card. These data were taken for further statistical analysis to determine if the factor \"vaccination\" does have a significant effect on the variable \"morbidity\".\n", "Various infectious disease-associated symptoms (vomiting, coughing, signs of rhinitis, restlessness, rash and pain) were significantly less often seen in vaccinated than in non-vaccinated children.\n", "\n", "Question: Is general non-specific morbidity reduced after vaccination within the third month of life -- the Greifswald study?\n", "\n", "Answer:\n", "Predictions: ### Final Output:\n", "\"Yes, general non-specific morbidity is reduced after vaccination within the third month of life according to the Greifswald study.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Cell adhesion molecules play a critical role in the invasion and metastasis of a variety of human tumors. Abnormal expression of VCAM-1 has been demonstrated to correlate with the malignant progression of gastric tumors, but the molecular mechanism underlying the VCAM-1-dependent metastasis has been rarely investigated. To explore the role for tumor cell-expressing adhesion molecules in the carcinoma-endothelium adhesion, we analyzed expression status of adhesion molecules in gastric cancer cells and its association with tumor cell capability of endothelial adhesion.\n", "Endothelial adhesion ability of gastric tumor cells was tested using calcein AM staining assay. Expression of cell surface proteins was determined by Western blot, flow cytometry, and immunofluorescence assays. RNAi-mediated knockdown of gene expression and neutralization with specific antibodies were utilized for functional analysis.\n", "One of three cell lines tested was identified to be adhesive to endothelial cells and express VCAM-1. Adherence ability of the cells was dramatically decreased by neutralization of surface VCAM-1. VCAM-1 was co-localized with Caveolin-1 and siRNA-mediated knockdown of Caveolin-1 expression significantly blocked the VCAM-1-dependent cell adhesion.\n", "\n", "Question: Is caveolin-1 associated with VCAM-1 dependent adhesion of gastric cancer cells to endothelial cells?\n", "\n", "Answer:\n", "Predictions: {\"draft_answer\": \"Yes, caveolin-1 is associated with VCAM-1 dependent adhesion of gastric cancer cells to endothelial cells, as the study indicates that VCAM-1 co-localizes with Caveolin-1 and that knockdown of Caveolin-1 significantly blocks VCAM-1-dependent cell adhesion.\"}\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: In animal and human autopsy studies of sepsis, CD4+ splenocytes either undergo apoptosis or are polarized to the Th2 effector subtype. In mice, these changes occur within 24 hours of the onset of sepsis. Preventing the loss of CD4+ T cells and the Th2-polarization of CD4+ T cells provides a significant survival advantage in mouse models of sepsis. The molecular mechanism(s) for the phenotypic changes of splenic CD4+ T cells in sepsis are not well understood.\n", "CD4+ splenocytes were enriched by negative selection from disaggregated spleens of septic and sham-operated mice at 6 and 24 hours after surgery. Phenotypic analysis using cell surface markers (CD25, CD44, CD62L, CD69), cytokine secretion in response to CD3/CD28 coligation, and whole genome microarray gene expression profiles were obtained for these cells.\n", "Consistent with previous reports, sepsis induced a progressive decrease in the number of CD4+ splenocytes and a time-dependent alteration in CD4+ T-cell phenotype. At 6 hours, when no differences in cell number or surface marker expression were observed, significant alterations in RNA abundance were measured for 498 probe sets. Ontologic classification of these genes indicated changes in cellular physiology. Pathway analysis indicated that T-cell receptor signaling and mitogen-activated protein kinase signaling were significantly altered by sepsis.\n", "\n", "Question: Do splenic CD4+ T cells have a distinct transcriptional response six hours after the onset of sepsis?\n", "\n", "Answer:\n", "Predictions: {\"draft_answer\": \"Yes, splenic CD4+ T cells have a distinct transcriptional response six hours after the onset of sepsis, as indicated by significant alterations in RNA abundance for 498 probe sets.\"}\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Naturally arising IgM antibodies (NAb) to apoptotic cell (AC) determinants are present from birth and can be further induced by AC challenge. In systemic lupus erythematosus, lower anti-AC NAb levels have been associated with higher disease activity. We have recently shown that a prototypical AC-specific IgM NAb can suppress proinflammatory responses to purified agonists of Toll-like receptors and block the in vivo induction of IgG immune complex (IC)-induced arthritis. Nuclear antigens, which activate dendritic cells (DCs), form complexes with IgG autoantibody, and these have been implicated in the pathogenesis of autoimmune disease. In this study, we sought to investigate potential roles of such NAb for regulating IC-mediated activation of DCs, which is believed to be involved in disease initiation and perpetuation.\n", "Bone marrow-derived myeloid DCs were stimulated with ICs composed of IgG autoantibody and chromatin or IgG autoantibody and RNA. Outcome was evaluated according to the production of inflammatory cytokines, as determined by enzyme-linked immunosorbent assay, and the expression of costimulatory molecules (markers of DC activation), as determined by flow cytometry. MAPK activation was evaluated by phospho-flow analysis and immunofluorescence microscopy.\n", "IgM anti-AC NAb dose-dependently suppressed the production of DNA IC- and RNA IC-induced interleukin-6 and DNA IC-induced tumor necrosis factor α, as well as the RNA IC-induced up-regulation of CD86 and CD40 on DCs. IgM NAb-mediated inhibition was associated with suppression of IC-mediated p38 MAPK activation and nuclear localization.\n", "\n", "Question: Does natural antibody to apoptotic cell membranes inhibit the proinflammatory properties of lupus autoantibody immune complexes?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, natural antibody to apoptotic cell membranes inhibits the proinflammatory properties of lupus autoantibody immune complexes.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: In previous studies, several strains of mice were used as chemical-induced skin irritation models to identify immunological hazards and elucidate the molecular and cellular mechanisms by which irritant dermatitis disease occur. BALB/c and C57BL/6 mice have been used for most of these experiments. Although there are some differences in the immune response to chemical allergens between these strains, few studies have been conducted to determine what regulatory factors contribute to these variations.\n", "To investigate the cause of high responses to skin irritation in C57BL/6 mice that are widely used to study atopic dermatitis, changes in various immune-related factors such as ear thickness, myeloperoxidase activity, lymph node weight, IgE concentration and cytokine concentration were measured in C57BL/6 and BALB/c mice following phthalic anhydride (PA) treatment.\n", "Based on analysis of the skin irritation, C57BL/6 mice showed a greater skin irritation to PA than BALB/c mice, although the IgE concentration and auricular lymph node weight did not contribute to this difference in the response. However, the concentration of several cytokines and chemokines (interleukin [IL]-6 and vascular endothelial growth factor [VEGF], keratinocyte-derived chemokine [KC] and regulated on activation normal T cell expressed and secreted [RANTES]) were significantly higher in C57BL/6 mice than BALB/c mice following treatment with PA.\n", "\n", "Question: Are iL-6 , VEGF , KC and RANTES a major cause of a high irritant dermatitis to phthalic anhydride in C57BL/6 inbred mice?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, the significantly higher concentrations of IL-6, VEGF, KC, and RANTES in C57BL/6 mice following treatment with phthalic anhydride suggest that these cytokines and chemokines may be a major cause of the high irritant dermatitis response in these mice.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Dual energy X-ray absorptiometry of the whole body and the lumbar spine was performed to study bone mineralisation before and after 1 year of recombinant human growth hormone (rhGH) treatment in ten children with chronic renal failure. At the start, median age was 7.3 years (range 2.0-8.8 years) and median glomerular filtration rate 15 ml/min per 1.73 m2 (range 7-41 ml/min per 1.73 m2). Total body mineral content (TBMC), lumbar spine mineral content (LBMC), total body bone mineral density (TBMD) and lumbar spine mineral density (LBMD) improved significantly (P < 0.05) after 1 year of treatment. Bone mineral data before and after treatment were compared with two groups of controls, i.e. ten healthy children matched for age and ten healthy children matched for height. Patients' TBMC, LBMC, TBMD and LBMD data before treatment were no different from those of height-matched controls; the same was true after 1 year of treatment except for the patients' significantly better LBMD (P < 0.05). When compared with age-matched controls, patients had significantly lower baseline TBMC and LBMC levels before treatment; after treatment LBMC was no longer different. However, there were no differences in TBMD or LBMD between patients and age-matched controls at baseline or after rhGH.\n", "\n", "Question: Does growth hormone treatment enhance bone mineralisation in children with chronic renal failure?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, growth hormone treatment enhances bone mineralisation in children with chronic renal failure, as indicated by the significant improvements in total body mineral content, lumbar spine mineral content, total body bone mineral density, and lumbar spine mineral density after treatment.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Neutrophil recruitment into glomerular tissues and reduced capillary wall integrity has been implicated in the development of vasculitic glomerulonephritis (VGN). This study investigated the stages and mechanisms through which neutrophil serine proteases (SPs), proteinase 3 (PR3) or elastase contribute to endothelial dysfunction.\n", "Protease-induced damage to endothelium and adhesion molecule upregulation was measured by viability assays and ELISA. Neutrophil/platelet adhesion to human glomerular and umbilical vein endothelium was assessed using in vitro adhesion assays.\n", "PR3 and elastase (1 µg/mL, 2 h) significantly induced neutrophil adhesion to endothelial cells (EnC) whilst PR3 also enhanced platelet-EnC interactions. This neutrophil adhesion was associated with enhanced P-selectin expression and required CXCL8 receptor involvement, and could be inhibited by blocking the P-selectin ligand PSGL-1. SPs induced damage in a time- and dose-dependent fashion, decreasing cell monolayer integrity followed by cell membrane integrity, inducing caspase-3 activation and p21 cleavage. However, SPs caused significant EnC damage with increasing concentrations and prolonged exposures.\n", "\n", "Question: Do neutrophil serine proteases mediate inflammatory cell recruitment by glomerular endothelium and progression towards dysfunction?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, neutrophil serine proteases mediate inflammatory cell recruitment by glomerular endothelium and progression towards dysfunction.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: Lung transplantation is severely limited by an inadequate supply of lungs from brain-dead donors. A potential solution is use of lungs from non-heart-beating donors (NHBDs) with retrieval at intervals after circulatory arrest and death. A warm ischemic period with concomitant reperfusion injury is a major limiting factor in the transplantation of lungs retrieved from NHBDs. We hypothesized that the administration of the nitric oxide-donor nitroglycerin to lungs from NHBDs would reduce ischemia-reperfusion injury by activation of guanylate cyclase to form guanosine 3',5'-cyclic monophosphate (cGMP).\n", "An in situ isolated perfused rat lung model was used. Lungs were retrieved from rats at varying intervals after circulatory arrest and death. Lungs were either ventilated with O(2) in situ or not ventilated. Lungs were reperfused at intervals after death with Earle's solution with or without nitroglycerin (0.1 mg/ml). Lung ischemia-reperfusion injury was assessed by capillary filtration coefficient, wet-to-dry lung weight ratio, and pulmonary hemodynamics. Tissue levels of adenine nucleotides and cGMP concentrations were measured by high-performance liquid chromatography and enzyme immunoassay, respectively.\n", "Reperfusion with nitroglycerin decreased capillary filtration coefficient compared with reperfusion without nitroglycerin at all post-mortem ischemic times, irrespective of pre-harvest ventilation. cGMP levels increased significantly with nitroglycerin-reperfusion and attenuated decreases in high-energy adenine nucleotides.\n", "\n", "Question: Does nitroglycerin reperfusion reduce ischemia-reperfusion injury in non-heart-beating donor lungs?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, nitroglycerin reperfusion reduces ischemia-reperfusion injury in non-heart-beating donor lungs.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To study the fibrinolytic pathways and their relationship with the contact system in women using combined oral contraceptives (COCs).\n", "Serial plasma samples were collected from 18 women before treatment with COCs containing 30 micrograms oestrogen during treatment cycles 3 and 6, and 2 weeks after stopping treatment. Fibrinolysis was measured before and after dextran sulphate mediated contact activation using fibrin plates.\n", "Fibrinolysis increased significantly during cycles 3 and 6 (from 77% to 100% and 113%, respectively, P < 0.01) and showed a further increase after dextran sulphate activation (from 134% to 158% and 167%, respectively, P < 0.01). Tissue-plasminogen activator, urokinase-plasminogen activator and plasminogen activator inhibitor did not change significantly. There were significant elevations of Factor XII (from 0.92 u/ml to 1.43 u/ml, P < 0.01) and prekallikrein (0.94 u/ml to 1.10 u/ml, P < 0.05) in cycle 3, which both remained high at cycle 6 (P < 0.01) and decreased after stopping the COC. Alpha-2-macroglobulin and C1-esterase inhibitor showed no significant change, but alpha-1-antitrypsin increased from 0.85 u/ml to 1.11 u/ml by cycle 3 (P < 0.01), and returned to near normal levels after stopping the COC.\n", "\n", "Question: Is contact factor mediated fibrinolysis increased by the combined oral contraceptive pill?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, contact factor mediated fibrinolysis is increased by the combined oral contraceptive pill, as indicated by the significant increases in fibrinolysis during treatment cycles and after dextran sulphate activation.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.Questions: Context: To examine the association between potassium level during the first half of pregnancy and the development of gestational diabetes mellitus (GDM) and hypertensive disorders in the second half of the pregnancy.\n", "The study population included all registered births between the years 2001-2007. The potassium levels during the first half of pregnancy were sorted by the following groups: K < 3.5 mEq/l; K = 3.5-3.99 mEq/l; and K > or = 4 mEq/l. The linear by linear chi(2)-test was used to determine the association between potassium level during the beginning of pregnancy and pregnancy complications.\n", "The study population included 8114 deliveries. A significant linear association was documented between potassium level in the first half of the pregnancy and the prevalence of GDM in the second half of the pregnancy: 6.3% in the K < 3.5 mEq/l group, 6.6% in the K = 3.5-3.99 mEq/l group and 8.2% in the K > 4 mEq/l group; (p = 0.008). A statistically significant for lower rates of severe pre-eclampsia was noted between the groups: 0.4% in the K < 3.5 mEq/l group, 0.9% in the K = 3.5-3.99 mEq/l group, 1.3% in the K = 4.0-4.99 mEq/l group and 1.5% in the K > or = 5 mEq/l group, (p = 0.027). Indeed, K > 5 mEq/l was noted as a significant risk factor for both, severe pre-eclampsia and for GDM. Using two multiple logistic regression models controlling for maternal age, potassium level was noted as an independent risk factor for both GDM and severe pre-eclampsia.\n", "\n", "Question: Is low potassium level during the first half of pregnancy associated with lower risk for the development of gestational diabetes mellitus and severe pre-eclampsia?\n", "\n", "Answer:\n", "Predictions: No, low potassium level during the first half of pregnancy is not associated with lower risk for the development of gestational diabetes mellitus and severe pre-eclampsia. In fact, the study indicates that higher potassium levels are associated with a higher prevalence of GDM and severe pre-eclampsia.\n", "Solutions: yes\n", "Score: 0.0\n", "Error reason: Computation result is incorrect.Questions: Context: The novel chemokine CXCL16 is involved in the development of atherosclerosis and coronary artery disease (CAD). However, the role of CXCL16 in atherosclerosis remains uncertain. This study was designed to investigate the relationship between CXCL16 and the severity of coronary artery stenosis.\n", "Using ELISA, we assayed the plasma CXCL16 concentration in 16 stable angina pectoris (SAP) patients, 53 acute coronary syndrome (ACS) patients, and 19 control patients. All patients underwent coronary angiography after admission. They were divided into four groups according to the quartile of CXCL16 level. Characteristics and the relationship between CXCL16 and the elements were studied in each group.\n", "CXCL16 levels in the ACS group were higher than controls and SAP group (p <0.01 vs. controls; p <0.05 vs. SAP group). Gensini score in the highest quartile group of CXCL16 level (group IV, CXCL16 >2.21 ng/mL) was significantly higher than in the lowest quartile group of CXCL16 level (group I, CXCL16 < or = 1.43 ng/mL) (p <0.001). Gensini score in group II (1.43 ng/mL or = 65) appeared lower than elsewhere, including China, but higher than reported past prevalence within the country. Functional disability on at least one of the 10 ADL items was independently associated with female sex, Indian ethnicity, older age, poor self-rated health, specific chronic diseases, cognitive impairment, sensory impairment, and living with others. The population attributable risks for leading modifiable factors were arthritis (12%) and cognitive impairment (14%).\n", "\n", "Question: Does prevalence and correlate of functional disability in multiethnic elderly Singaporeans?\n", "\n", "Answer:\n", "Predictions: **Final Output:**\n", "\"Yes, the study examines the prevalence and correlates of functional disability in multiethnic elderly Singaporeans.\"\n", "Solutions: yes\n", "Score: 1.0\n", "The solution is correct.\n", "{'name': 'context_analysis3328', 'description': 'Task to context_analysis3328. Takes question as input. Produces context as output.', 'inputs': [{'name': 'question', 'type': 'str', 'description': 'Input parameter question for context_analysis3328', 'required': False}], 'outputs': [{'name': 'context', 'type': 'str', 'description': 'Output parameter context from context_analysis3328', 'required': True}], 'prompt': '```xml\\n\"\"\"\\nAnalyze the context of the question step by step to ensure a relevant and accurate response. Begin by identifying key components of the question and any potential ambiguities. Explain your thought process clearly in the field, detailing how you arrived at your conclusions. Provide the final answer in the field, ensuring it directly addresses the clarified question. Format your output in XML, using {thought} and {answer}.\\n\"\"\"\\n```', 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"Think step by step to answer the question based on the question context. You should integrate context for answering. You should explain your thinking process in the 'thought' field, and provide the final answer in the 'answer' field.\\nFormat your output in xml format, such as xxx and xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[32m2026-01-06 08:48:22.957\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.363 | Total tokens: 6968332 | Current cost: $0.003 | Current tokens: 19975\u001b[0m\n", "\u001b[32m2026-01-06 08:48:25.449\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.364 | Total tokens: 6968650 | Current cost: $0.000 | Current tokens: 318\u001b[0m\n", "\u001b[32m2026-01-06 08:48:27.391\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.364 | Total tokens: 6969929 | Current cost: $0.000 | Current tokens: 1279\u001b[0m\n", "{'name': 'handle_ambiguities7850', 'description': 'Task to handle_ambiguities7850. Takes context as input. Produces clarified_question as output.', 'inputs': [{'name': 'context', 'type': 'str', 'description': 'Input parameter context for handle_ambiguities7850', 'required': False}], 'outputs': [{'name': 'clarified_question', 'type': 'str', 'description': 'Output parameter clarified_question from handle_ambiguities7850', 'required': True}], 'prompt': '```xml\\n\"\"\"\\nTo effectively answer the question, follow these steps:\\n\\n1. Analyze the context derived from `{context}` to identify any specific nuances or details that may influence the answer.\\n2. If ambiguities are present, clarify the question by addressing specific aspects that need further explanation or detail.\\n3. Integrate the clarified context into your reasoning process to ensure the answer is relevant and comprehensive.\\n4. Provide a clear and concise final answer in the `{answer}` field, ensuring it directly addresses the user\\'s inquiry and incorporates any necessary details or examples.\\n\\nFormat your output in XML format, using to explain your reasoning process and for the final response.\\n\"\"\"\\n```', 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"Think step by step to answer the question based on the question context. You should integrate context for answering. You should explain your thinking process in the 'thought' field, and provide the final answer in the 'answer' field.\\nFormat your output in xml format, such as xxx and xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n", "\u001b[32m2026-01-06 08:48:29.733\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.367 | Total tokens: 6989901 | Current cost: $0.003 | Current tokens: 19972\u001b[0m\n", "\u001b[32m2026-01-06 08:48:32.588\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.367 | Total tokens: 6990202 | Current cost: $0.000 | Current tokens: 301\u001b[0m\n", "\u001b[32m2026-01-06 08:48:37.881\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.368 | Total tokens: 6991902 | Current cost: $0.000 | Current tokens: 1700\u001b[0m\n", "{'name': 'generate_answer', 'description': 'Draft an answer using the retrieved context.', 'inputs': [{'name': 'question', 'type': 'str', 'description': 'The original question from the user.', 'required': True}], 'outputs': [{'name': 'draft_answer', 'type': 'str', 'description': 'A concise, direct answer to the question.', 'required': True}], 'prompt': '\"\"\"\\nYou can think to generate answers based on the provided {question}. Ensure that your response is clear and concise, considering whether a simple \"Yes\" or \"No\" is sufficient or if a more nuanced answer is required. If the {question} is ambiguous or lacks detail, indicate this in your response and suggest specific clarifying questions to gather more information. Format your final answer in the \\'answer\\' field as xxx. If the draft answer requires significant revision, note the necessary changes before proceeding to validation. Prioritize and weigh evidence carefully to enhance the reliability of your answer.\\n\"\"\"', 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"You can think to generate answers. You should provide the final answer (either Yes or No) in the 'answer' field. Format your answer in xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n", "\u001b[32m2026-01-06 08:48:40.398\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.371 | Total tokens: 7011827 | Current cost: $0.003 | Current tokens: 19925\u001b[0m\n", "\u001b[32m2026-01-06 08:48:43.187\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.371 | Total tokens: 7012114 | Current cost: $0.000 | Current tokens: 287\u001b[0m\n", "\u001b[32m2026-01-06 08:48:45.219\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.372 | Total tokens: 7013588 | Current cost: $0.000 | Current tokens: 1474\u001b[0m\n", "{'name': 'validate_answer9330', 'description': 'Task to validate_answer9330. Takes draft_answer as input. Produces validated_answer as output.', 'inputs': [{'name': 'draft_answer', 'type': 'str', 'description': 'Input parameter draft_answer for validate_answer9330', 'required': False}], 'outputs': [{'name': 'validated_answer', 'type': 'str', 'description': 'Output parameter validated_answer from validate_answer9330', 'required': True}], 'prompt': '\"\"\"\\nThink step by step to answer the question based on the context provided in {question}. Begin by identifying the key components, underlying issues, and any ambiguities within the question. In the \\'thought\\' field, explain your reasoning process, detailing how you arrived at your conclusions and addressing any complexities present in the question. If ambiguities are identified, clarify them before proceeding. Then, provide a clear and concise final answer in the \\'answer\\' field, ensuring it is directly relevant to the user\\'s needs. Format your output in XML format, such as {thought} and {answer}.\\n\"\"\"', 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"Think step by step to answer the question based on the question context. You should integrate context for answering. You should explain your thinking process in the 'thought' field, and provide the final answer in the 'answer' field.\\nFormat your output in xml format, such as xxx and xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n", "\u001b[32m2026-01-06 08:48:48.240\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.375 | Total tokens: 7033532 | Current cost: $0.003 | Current tokens: 19944\u001b[0m\n", "\u001b[32m2026-01-06 08:48:51.581\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.375 | Total tokens: 7033846 | Current cost: $0.000 | Current tokens: 314\u001b[0m\n", "\u001b[32m2026-01-06 08:48:54.371\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.375 | Total tokens: 7035362 | Current cost: $0.000 | Current tokens: 1516\u001b[0m\n", "{'name': 'evaluate_answer9619', 'description': 'Task to evaluate_answer9619. Takes validated_answer as input. Produces evaluation_score as output.', 'inputs': [{'name': 'validated_answer', 'type': 'str', 'description': 'Input parameter validated_answer for evaluate_answer9619', 'required': False}], 'outputs': [{'name': 'evaluation_score', 'type': 'str', 'description': 'Output parameter evaluation_score from evaluate_answer9619', 'required': True}], 'prompt': '\"\"\"\\nThink step by step to answer the question based on the context provided in {question}. Begin by analyzing the key components of the question to identify the main issue and any underlying factors. If the question is ambiguous, clarify the necessary details before proceeding. Integrate this context into your reasoning process. In the \\'thought\\' field, explain your reasoning, how you arrived at your conclusion, and any clarifications made. Provide the final answer in the \\'answer\\' field, ensuring it directly addresses the main issue identified. Format your output in XML format, such as {thought} and {answer}. Additionally, ensure that your answer is validated against predefined criteria for accuracy and relevance before finalizing it, and be prepared to revisit earlier steps based on the evaluation score if necessary.\\n\"\"\"', 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"Think step by step to answer the question based on the question context. You should integrate context for answering. You should explain your thinking process in the 'thought' field, and provide the final answer in the 'answer' field.\\nFormat your output in xml format, such as xxx and xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[32m2026-01-06 08:49:01.087\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.379 | Total tokens: 7055332 | Current cost: $0.003 | Current tokens: 19970\u001b[0m\n", "\u001b[32m2026-01-06 08:49:04.121\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.379 | Total tokens: 7055644 | Current cost: $0.000 | Current tokens: 312\u001b[0m\n", "\u001b[32m2026-01-06 08:49:06.969\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.379 | Total tokens: 7057326 | Current cost: $0.000 | Current tokens: 1682\u001b[0m\n", "{'name': 'feedback_loop7764', 'description': 'Task to feedback_loop7764. Takes evaluation_score, draft_answer as input. Produces improved_answer as output.', 'inputs': [{'name': 'evaluation_score', 'type': 'str', 'description': 'Input parameter evaluation_score for feedback_loop7764', 'required': False}, {'name': 'draft_answer', 'type': 'str', 'description': 'Input parameter draft_answer for feedback_loop7764', 'required': False}], 'outputs': [{'name': 'improved_answer', 'type': 'str', 'description': 'Output parameter improved_answer from feedback_loop7764', 'required': True}], 'prompt': '\"\"\"\\nThink step by step to answer the question based on the context derived from {question}. Begin by analyzing the context to identify any ambiguities or complexities in the inquiry. Then, integrate this context into your reasoning process to formulate a well-informed answer. In the \\'thought\\' field, explain your reasoning, including how the context influenced your answer. Provide the final answer in the \\'answer\\' field, ensuring it is clear and directly addresses the user\\'s question.\\nFormat your output in xml format, such as xxx and xxx.\\n\"\"\"', 'prompt_template': {'class_name': 'StringTemplate', 'instruction': \"Think step by step to answer the question based on the question context. You should integrate context for answering. You should explain your thinking process in the 'thought' field, and provide the final answer in the 'answer' field.\\nFormat your output in xml format, such as xxx and xxx.\"}, 'system_prompt': 'You are a helpful and highly intelligent assistant.', 'parse_mode': 'xml', 'parse_func': None, 'parse_title': None, 'tool_names': None, 'tools': None}\n", "\u001b[32m2026-01-06 08:49:11.112\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.383 | Total tokens: 7077283 | Current cost: $0.003 | Current tokens: 19957\u001b[0m\n", "\u001b[32m2026-01-06 08:49:13.883\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.383 | Total tokens: 7077575 | Current cost: $0.000 | Current tokens: 292\u001b[0m\n", "\u001b[32m2026-01-06 08:49:16.403\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.models.model_utils\u001b[0m:\u001b[36mupdate_cost\u001b[0m:\u001b[36m87\u001b[0m - \u001b[1mTotal cost: $1.383 | Total tokens: 7078905 | Current cost: $0.000 | Current tokens: 1330\u001b[0m\n", "\u001b[32m2026-01-06 08:49:16.405\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.optimizers.qastructure_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m1054\u001b[0m - \u001b[1mEvaluate the workflow at step 5 ...\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Evaluating workflow: 2%|▏ | 1/50 [00:02<02:00, 2.47s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 4%|▍ | 2/50 [00:03<01:24, 1.76s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 6%|▌ | 3/50 [00:07<02:10, 2.77s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 8%|▊ | 4/50 [00:09<01:42, 2.24s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 10%|█ | 5/50 [00:10<01:34, 2.10s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 12%|█▏ | 6/50 [00:12<01:20, 1.83s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 14%|█▍ | 7/50 [00:13<01:14, 1.72s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 16%|█▌ | 8/50 [00:15<01:17, 1.84s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 18%|█▊ | 9/50 [00:17<01:07, 1.64s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 20%|██ | 10/50 [00:18<01:04, 1.62s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 22%|██▏ | 11/50 [00:19<00:59, 1.52s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 24%|██▍ | 12/50 [00:21<00:57, 1.51s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 26%|██▌ | 13/50 [00:22<00:51, 1.40s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 28%|██▊ | 14/50 [00:23<00:48, 1.34s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 30%|███ | 15/50 [00:25<00:46, 1.32s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", 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[00:33<00:49, 1.67s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 42%|████▏ | 21/50 [00:34<00:44, 1.53s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 44%|████▍ | 22/50 [00:36<00:41, 1.50s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 46%|████▌ | 23/50 [00:37<00:39, 1.48s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 48%|████▊ | 24/50 [00:39<00:38, 1.50s/it]" ] }, { "name": "stdout", 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"text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Evaluating workflow: 100%|██████████| 50/50 [01:20<00:00, 1.61s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "\u001b[32m2026-01-06 08:50:36.917\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.optimizers.qastructure_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m1057\u001b[0m - \u001b[1mStep 5 metrics: {'f1': 0.0, 'em': 0.0, 'acc': 0.92}\u001b[0m\n", "randomly update dataset\n", "\u001b[32m2026-01-06 08:50:36.923\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.optimizers.qastructure_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m1064\u001b[0m - \u001b[1mReach the maximum number of steps 5. Stop the optimization.\u001b[0m\n", "\u001b[32m2026-01-06 08:50:36.923\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.optimizers.qastructure_optimizer\u001b[0m:\u001b[36moptimize\u001b[0m:\u001b[36m1067\u001b[0m - \u001b[1mRestore the best graph from the snapshot ...\u001b[0m\n", "\u001b[32m2026-01-06 08:50:36.924\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.optimizers.qastructure_optimizer\u001b[0m:\u001b[36mrestore_best_graph\u001b[0m:\u001b[36m1216\u001b[0m - \u001b[1mRestore the best graph from snapshot with metrics {'f1': 0.0, 'em': 0.0, 'acc': 0.98} ...\u001b[0m\n", "\u001b[32m2026-01-06 08:50:36.926\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.optimizers.qastructure_optimizer\u001b[0m:\u001b[36mrestore_best_graph\u001b[0m:\u001b[36m1216\u001b[0m - \u001b[1mRestore the best graph from snapshot with metrics {'f1': 0.0, 'em': 0.0, 'acc': 0.98} ...\u001b[0m\n", "\u001b[32m2026-01-06 08:50:36.926\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mevoagentx.workflow.workflow_graph\u001b[0m:\u001b[36msave_module\u001b[0m:\u001b[36m1204\u001b[0m - \u001b[1mSaving SequentialWorkFlowGraph to debug/optimized_ourmethod_gpt4omini_5step_generate_new_call3.json\u001b[0m\n", "\u001b[32m2026-01-06 08:50:36.932\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.agents.customize_agent\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m92\u001b[0m - \u001b[33m\u001b[1mBoth `prompt` and `prompt_template` are provided in `CustomizeAgent`. `prompt_template` will be used.\u001b[0m\n", "\u001b[32m2026-01-06 08:50:36.935\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.agents.customize_agent\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m92\u001b[0m - \u001b[33m\u001b[1mBoth `prompt` and `prompt_template` are provided in `CustomizeAgent`. `prompt_template` will be used.\u001b[0m\n", "\u001b[32m2026-01-06 08:50:36.938\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.agents.customize_agent\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m92\u001b[0m - \u001b[33m\u001b[1mBoth `prompt` and `prompt_template` are provided in `CustomizeAgent`. `prompt_template` will be used.\u001b[0m\n", "\u001b[32m2026-01-06 08:50:36.941\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.agents.customize_agent\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m92\u001b[0m - \u001b[33m\u001b[1mBoth `prompt` and `prompt_template` are provided in `CustomizeAgent`. `prompt_template` will be used.\u001b[0m\n", "\u001b[32m2026-01-06 08:50:36.944\u001b[0m | \u001b[33m\u001b[1mWARNING \u001b[0m | \u001b[36mevoagentx.agents.customize_agent\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m92\u001b[0m - \u001b[33m\u001b[1mBoth `prompt` and `prompt_template` are provided in `CustomizeAgent`. `prompt_template` will be used.\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\n", "Evaluating workflow: 0%| | 1/500 [00:22<3:08:34, 22.67s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 0%| | 2/500 [00:45<3:10:44, 22.98s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 1%| | 3/500 [01:09<3:12:15, 23.21s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 1%| | 4/500 [01:35<3:21:20, 24.35s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 1%| | 5/500 [01:54<3:06:21, 22.59s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 1%| | 6/500 [02:16<3:03:15, 22.26s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 1%|▏ | 7/500 [02:36<2:57:09, 21.56s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 2%|▏ | 8/500 [02:55<2:49:13, 20.64s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "\u001b[32m2026-01-06 08:53:46.790\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 2%|▏ | 9/500 [03:09<2:33:14, 18.73s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 2%|▏ | 10/500 [03:33<2:46:34, 20.40s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 2%|▏ | 11/500 [03:53<2:44:16, 20.16s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "\u001b[32m2026-01-06 08:54:46.941\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 2%|▏ | 12/500 [04:09<2:34:38, 19.01s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 3%|▎ | 13/500 [04:35<2:50:29, 21.01s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 3%|▎ | 14/500 [04:57<2:51:53, 21.22s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 3%|▎ | 15/500 [05:18<2:52:16, 21.31s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 3%|▎ | 16/500 [05:38<2:48:20, 20.87s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 3%|▎ | 17/500 [06:02<2:54:00, 21.62s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 4%|▎ | 18/500 [06:20<2:47:03, 20.80s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 4%|▍ | 19/500 [06:38<2:39:53, 19.95s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 4%|▍ | 20/500 [06:57<2:36:44, 19.59s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 4%|▍ | 21/500 [07:17<2:37:45, 19.76s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 4%|▍ | 22/500 [07:38<2:40:22, 20.13s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 5%|▍ | 23/500 [08:02<2:49:18, 21.30s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 5%|▍ | 24/500 [08:22<2:46:17, 20.96s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 5%|▌ | 25/500 [08:44<2:47:54, 21.21s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 5%|▌ | 26/500 [09:03<2:42:36, 20.58s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "\u001b[32m2026-01-06 08:59:55.909\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 5%|▌ | 27/500 [09:18<2:29:13, 18.93s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 6%|▌ | 28/500 [11:13<6:14:34, 47.62s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 6%|▌ | 29/500 [11:37<5:17:04, 40.39s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 6%|▌ | 30/500 [11:57<4:28:57, 34.33s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 6%|▌ | 31/500 [12:15<3:49:36, 29.37s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 6%|▋ | 32/500 [12:35<3:28:34, 26.74s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 7%|▋ | 33/500 [12:55<3:12:40, 24.76s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 7%|▋ | 34/500 [13:16<3:03:43, 23.65s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 7%|▋ | 35/500 [13:38<2:59:33, 23.17s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 7%|▋ | 36/500 [13:59<2:53:33, 22.44s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 7%|▋ | 37/500 [14:21<2:52:48, 22.39s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 8%|▊ | 38/500 [14:44<2:52:16, 22.37s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 8%|▊ | 39/500 [15:05<2:48:16, 21.90s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 8%|▊ | 40/500 [15:23<2:40:58, 21.00s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "\u001b[32m2026-01-06 09:06:18.321\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 8%|▊ | 41/500 [15:41<2:32:28, 19.93s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 8%|▊ | 42/500 [16:03<2:36:55, 20.56s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "\u001b[32m2026-01-06 09:06:56.809\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 9%|▊ | 43/500 [16:19<2:27:14, 19.33s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 9%|▉ | 44/500 [16:42<2:34:13, 20.29s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 9%|▉ | 45/500 [17:04<2:38:31, 20.90s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 9%|▉ | 46/500 [17:23<2:32:15, 20.12s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 9%|▉ | 47/500 [17:42<2:29:49, 19.84s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 10%|▉ | 48/500 [18:08<2:43:48, 21.74s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 10%|▉ | 49/500 [18:31<2:45:24, 22.01s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "\u001b[32m2026-01-06 09:09:25.933\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 10%|█ | 50/500 [18:48<2:35:57, 20.80s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 10%|█ | 51/500 [19:09<2:36:06, 20.86s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 10%|█ | 52/500 [19:36<2:49:21, 22.68s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 11%|█ | 53/500 [20:00<2:51:38, 23.04s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 11%|█ | 54/500 [20:22<2:48:25, 22.66s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 11%|█ | 55/500 [20:40<2:36:35, 21.11s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 11%|█ | 56/500 [21:03<2:40:29, 21.69s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 11%|█▏ | 57/500 [21:24<2:40:25, 21.73s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "\u001b[32m2026-01-06 09:12:18.039\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 12%|█▏ | 58/500 [21:41<2:27:45, 20.06s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 12%|█▏ | 59/500 [22:06<2:38:57, 21.63s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 12%|█▏ | 60/500 [22:23<2:29:17, 20.36s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "\u001b[32m2026-01-06 09:13:06.107\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input to LLMOutputParser.parse should be a str, but found .\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 12%|█▏ | 61/500 [22:29<1:56:04, 15.86s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 12%|█▏ | 62/500 [22:51<2:09:31, 17.74s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 13%|█▎ | 63/500 [23:11<2:13:47, 18.37s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 13%|█▎ | 64/500 [23:31<2:18:38, 19.08s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 13%|█▎ | 65/500 [23:53<2:23:23, 19.78s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 13%|█▎ | 66/500 [24:20<2:38:51, 21.96s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 13%|█▎ | 67/500 [24:42<2:38:15, 21.93s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 14%|█▎ | 68/500 [25:07<2:46:14, 23.09s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 14%|█▍ | 69/500 [25:32<2:49:56, 23.66s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 14%|█▍ | 70/500 [25:54<2:44:52, 23.00s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 14%|█▍ | 71/500 [26:15<2:39:51, 22.36s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 14%|█▍ | 72/500 [26:39<2:43:04, 22.86s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 15%|█▍ | 73/500 [27:01<2:40:24, 22.54s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683178.050527943)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683179.07634965)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683180.685161646)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683183.082069)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683184.271448169)])']\n", "connector: \n", "Unclosed client session\n", "client_session: 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session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683176.424474369)])']\n", "connector: \n", "Unclosed connector\n", "connections: ['deque([(, 1683181.610081393)])']\n", "connector: \n", "Unclosed connector\n", "connections: ['deque([(, 1683188.958803108)])']\n", "connector: \n", "Unclosed connector\n", "connections: ['deque([(, 1683194.369437685)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683195.6717998)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683196.74431676)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683198.600699844)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683202.112442783)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683204.716923031)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683205.901664275)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683208.475331321)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683209.676363953)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683210.887952113)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683212.031167527)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed client session\n", "client_session: \n", "Unclosed client session\n", "client_session: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683201.10944613)])']\n", "connector: \n", "Unclosed connector\n", "connections: ['deque([(, 1683203.224104624)])']\n", "connector: \n", "Unclosed connector\n", "connections: ['deque([(, 1683207.135694045)])']\n", "connector: \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Unclosed connector\n", "connections: ['deque([(, 1683213.165123451)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683214.785522377)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683216.018921047)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683217.2876483)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683218.676421612)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683219.539487487)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683223.198200725)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683224.153275089)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683226.670311611)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683228.52363616)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683230.153898293)])']\n", "connector: \n", "Unclosed client session\n", "client_session: 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"client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683236.888088226)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683239.748945691)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683240.733595566)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683241.94532727)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683244.44042586)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683245.629340742)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683246.544044332)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683248.097387979)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683249.839248629)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed client session\n", "client_session: \n", "Unclosed client session\n", "client_session: \n", "Unclosed client session\n", "client_session: \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Unclosed connector\n", "connections: ['deque([(, 1683238.392609394)])']\n", "connector: \n", "Unclosed connector\n", "connections: ['deque([(, 1683243.301185294)])']\n", "connector: \n", "Unclosed connector\n", "connections: ['deque([(, 1683251.190558035)])']\n", "connector: \n", "Unclosed connector\n", "connections: ['deque([(, 1683252.531315023)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683253.575181904)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683256.647301007)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683258.78640294)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683260.160335511)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683261.207404925)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683263.260878712)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683264.574976274)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683265.876726079)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683267.088278809)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683268.28476149)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed client session\n", "client_session: \n", "Unclosed client session\n", "client_session: \n", "Unclosed client session\n", "client_session: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1683254.615938194)])']\n", "connector: \n", "Unclosed connector\n", "connections: ['deque([(, 1683255.755613443)])']\n", "connector: \n", "Unclosed connector\n", "connections: ['deque([(, 1683262.04375509)])']\n", "connector: \n", "Unclosed connector\n", "connections: ['deque([(, 1683270.541858282)])']\n", "connector: \n", "Unclosed 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connector\n", "connections: ['deque([(, 1720313.81660315)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720314.825853662)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720316.56349694)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720320.402664274)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720318.303467769)])']\n", "connector: \n", "Unclosed connector\n", "connections: ['deque([(, 1720304.939011237)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720297.886254729)])']\n", "connector: \n", "Unclosed connector\n", "connections: 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"output_type": "stream", "text": [ "Unclosed connector\n", "connections: ['deque([(, 1720333.115968982)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720334.514468862)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720335.912841918)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720337.592544313)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720338.53230809)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720340.592025935)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720342.199627416)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720322.206327783)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720408.962270425)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720412.949348192)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720415.36942969)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720417.178882918)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720420.276206666)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720422.105329787)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed client session\n", "client_session: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720410.634096791)])']\n", "connector: \n", "Unclosed connector\n", "connections: ['deque([(, 1720418.251140569)])']\n", "connector: \n", "Unclosed connector\n", "connections: ['deque([(, 1720423.780221657)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720426.125878567)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720427.183952742)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720429.593190798)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720431.455496006)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720435.184590112)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720437.413314184)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720438.799024949)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720440.487264535)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720446.766063335)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720448.146312162)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720451.500437333)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Unclosed connector\n", "connections: ['deque([(, 1720449.994075804)])']\n", "connector: \n", "Unclosed connector\n", "connections: ['deque([(, 1720441.893832949)])']\n", "connector: \n", "Unclosed client session\n", "client_session: \n", "Unclosed client session\n", "client_session: \n", "Unclosed client session\n", "client_session: \n", "Unclosed connector\n", "connections: ['deque([(, 1720433.487682144)])']\n", "connector: \n", "Unclosed connector\n", "connections: ['deque([(, 1720443.294341263)])']\n", "connector: \n", "Unclosed connector\n", "connections: ['deque([(, 1720444.919592672)])']\n", "connector: \n", "Evaluating workflow: 15%|█▍ | 74/500 [27:25<2:43:25, 23.02s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "\u001b[32m2026-01-06 09:18:19.682\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 15%|█▌ | 75/500 [27:42<2:31:18, 21.36s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 15%|█▌ | 76/500 [28:12<2:49:03, 23.92s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 15%|█▌ | 77/500 [28:34<2:44:27, 23.33s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 16%|█▌ | 78/500 [29:00<2:50:05, 24.18s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 16%|█▌ | 79/500 [29:23<2:46:40, 23.75s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 16%|█▌ | 80/500 [29:49<2:51:15, 24.47s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 16%|█▌ | 81/500 [30:10<2:42:38, 23.29s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 16%|█▋ | 82/500 [30:31<2:39:03, 22.83s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 17%|█▋ | 83/500 [30:55<2:40:18, 23.07s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "\u001b[32m2026-01-06 09:21:50.474\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 17%|█▋ | 84/500 [31:13<2:29:19, 21.54s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 17%|█▋ | 85/500 [31:35<2:30:25, 21.75s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 17%|█▋ | 86/500 [31:57<2:29:00, 21.60s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 17%|█▋ | 87/500 [32:19<2:29:51, 21.77s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 18%|█▊ | 88/500 [32:38<2:24:14, 21.01s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 18%|█▊ | 89/500 [32:59<2:24:47, 21.14s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 18%|█▊ | 90/500 [33:21<2:25:19, 21.27s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 18%|█▊ | 91/500 [33:44<2:28:12, 21.74s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "\u001b[32m2026-01-06 09:24:37.796\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 18%|█▊ | 92/500 [34:00<2:17:18, 20.19s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 19%|█▊ | 93/500 [34:22<2:20:47, 20.76s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 19%|█▉ | 94/500 [34:43<2:20:39, 20.79s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 19%|█▉ | 95/500 [35:03<2:19:01, 20.60s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 19%|█▉ | 96/500 [35:42<2:54:15, 25.88s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 19%|█▉ | 97/500 [36:03<2:44:30, 24.49s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 20%|█▉ | 98/500 [36:22<2:33:39, 22.93s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "\u001b[32m2026-01-06 09:27:15.331\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 20%|█▉ | 99/500 [36:38<2:18:45, 20.76s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "\u001b[32m2026-01-06 09:27:29.799\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 20%|██ | 100/500 [36:52<2:05:49, 18.87s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 20%|██ | 101/500 [37:16<2:15:24, 20.36s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 20%|██ | 102/500 [37:39<2:19:01, 20.96s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 21%|██ | 103/500 [38:00<2:18:55, 21.00s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 21%|██ | 104/500 [38:22<2:21:34, 21.45s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 21%|██ | 105/500 [38:43<2:19:31, 21.19s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 21%|██ | 106/500 [39:04<2:19:16, 21.21s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 21%|██▏ | 107/500 [39:25<2:19:00, 21.22s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 22%|██▏ | 108/500 [39:55<2:34:29, 23.65s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 22%|██▏ | 109/500 [40:16<2:30:43, 23.13s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 22%|██▏ | 110/500 [40:52<2:55:23, 26.98s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 22%|██▏ | 111/500 [41:17<2:50:52, 26.36s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "\u001b[32m2026-01-06 09:32:11.681\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 22%|██▏ | 112/500 [41:34<2:32:06, 23.52s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "\u001b[32m2026-01-06 09:32:31.299\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 23%|██▎ | 113/500 [41:54<2:24:09, 22.35s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 23%|██▎ | 114/500 [42:14<2:20:21, 21.82s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "\u001b[32m2026-01-06 09:33:07.313\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 23%|██▎ | 115/500 [42:30<2:07:43, 19.91s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 23%|██▎ | 116/500 [42:52<2:11:33, 20.56s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "\u001b[32m2026-01-06 09:33:45.732\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 23%|██▎ | 117/500 [43:08<2:03:08, 19.29s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 24%|██▎ | 118/500 [43:27<2:00:55, 18.99s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 24%|██▍ | 119/500 [43:47<2:02:51, 19.35s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 24%|██▍ | 120/500 [44:06<2:02:08, 19.29s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "\u001b[32m2026-01-06 09:35:03.583\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! 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Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 26%|██▌ | 131/500 [47:50<2:06:05, 20.50s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 26%|██▋ | 132/500 [48:11<2:08:05, 20.88s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 27%|██▋ | 133/500 [48:35<2:12:18, 21.63s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 27%|██▋ | 134/500 [49:00<2:18:21, 22.68s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 27%|██▋ | 135/500 [49:19<2:11:07, 21.55s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 27%|██▋ | 136/500 [49:40<2:10:53, 21.58s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 27%|██▋ | 137/500 [50:04<2:14:04, 22.16s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "\u001b[32m2026-01-06 09:40:57.810\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 28%|██▊ | 138/500 [50:20<2:03:16, 20.43s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 28%|██▊ | 139/500 [50:42<2:04:47, 20.74s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 28%|██▊ | 140/500 [51:05<2:08:00, 21.34s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 28%|██▊ | 141/500 [51:27<2:10:07, 21.75s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 28%|██▊ | 142/500 [51:49<2:09:09, 21.65s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 29%|██▊ | 143/500 [52:09<2:05:41, 21.13s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 29%|██▉ | 144/500 [52:30<2:06:09, 21.26s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 29%|██▉ | 145/500 [52:55<2:12:43, 22.43s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": 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21.13s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 31%|███ | 155/500 [56:14<2:00:36, 20.98s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 31%|███ | 156/500 [56:34<1:58:48, 20.72s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 31%|███▏ | 157/500 [56:56<2:01:01, 21.17s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 32%|███▏ | 158/500 [57:17<2:00:52, 21.21s/it]" ] }, { "name": "stdout", 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[1:06:05<1:55:10, 21.80s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "\u001b[32m2026-01-06 09:56:58.640\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 37%|███▋ | 184/500 [1:06:21<1:45:37, 20.06s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 37%|███▋ | 185/500 [1:06:43<1:47:32, 20.48s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 37%|███▋ | 186/500 [1:07:03<1:46:19, 20.32s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 37%|███▋ | 187/500 [1:07:21<1:42:51, 19.72s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 38%|███▊ | 188/500 [1:07:42<1:45:06, 20.21s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 38%|███▊ | 189/500 [1:08:05<1:48:24, 20.91s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "\u001b[32m2026-01-06 09:58:58.134\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 38%|███▊ | 190/500 [1:08:21<1:40:12, 19.39s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 38%|███▊ | 191/500 [1:08:46<1:49:06, 21.18s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 38%|███▊ | 192/500 [1:09:05<1:45:44, 20.60s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 39%|███▊ | 193/500 [1:09:27<1:46:49, 20.88s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "\u001b[32m2026-01-06 10:00:22.186\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 39%|███▉ | 194/500 [1:09:45<1:41:57, 19.99s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 39%|███▉ | 195/500 [1:10:06<1:43:54, 20.44s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 39%|███▉ | 196/500 [1:10:29<1:46:41, 21.06s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 39%|███▉ | 197/500 [1:10:54<1:53:18, 22.44s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 40%|███▉ | 198/500 [1:11:16<1:52:17, 22.31s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "\u001b[32m2026-01-06 10:02:11.397\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 40%|███▉ | 199/500 [1:11:34<1:44:46, 20.89s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 40%|████ | 200/500 [1:11:54<1:43:26, 20.69s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 40%|████ | 201/500 [1:12:17<1:47:00, 21.47s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 40%|████ | 202/500 [1:12:37<1:43:06, 20.76s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "\u001b[32m2026-01-06 10:03:29.197\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 41%|████ | 203/500 [1:12:52<1:34:27, 19.08s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 41%|████ | 204/500 [1:13:11<1:34:40, 19.19s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 41%|████ | 205/500 [1:13:34<1:39:00, 20.14s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 41%|████ | 206/500 [1:13:54<1:39:12, 20.25s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 41%|████▏ | 207/500 [1:14:22<1:49:54, 22.51s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 42%|████▏ | 208/500 [1:14:43<1:48:03, 22.20s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "\u001b[32m2026-01-06 10:05:42.633\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 42%|████▏ | 209/500 [1:15:05<1:47:11, 22.10s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 42%|████▏ | 210/500 [1:15:28<1:47:31, 22.25s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 42%|████▏ | 211/500 [1:15:46<1:41:22, 21.05s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 42%|████▏ | 212/500 [1:16:09<1:44:19, 21.73s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 43%|████▎ | 213/500 [1:16:34<1:48:23, 22.66s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 43%|████▎ | 214/500 [1:16:53<1:41:50, 21.37s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 43%|████▎ | 215/500 [1:17:15<1:42:52, 21.66s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 43%|████▎ | 216/500 [1:17:41<1:48:27, 22.91s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 43%|████▎ | 217/500 [1:18:02<1:46:29, 22.58s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 44%|████▎ | 218/500 [1:18:27<1:48:28, 23.08s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 44%|████▍ | 219/500 [1:18:50<1:48:42, 23.21s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 44%|████▍ | 220/500 [1:19:09<1:42:24, 21.94s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 44%|████▍ | 221/500 [1:19:36<1:48:03, 23.24s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "\u001b[32m2026-01-06 10:10:29.507\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 44%|████▍ | 222/500 [1:19:52<1:38:22, 21.23s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 45%|████▍ | 223/500 [1:20:15<1:40:05, 21.68s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 45%|████▍ | 224/500 [1:20:37<1:40:33, 21.86s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 45%|████▌ | 225/500 [1:21:00<1:41:49, 22.22s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 45%|████▌ | 226/500 [1:21:22<1:40:37, 22.04s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 45%|████▌ | 227/500 [1:21:41<1:35:52, 21.07s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 46%|████▌ | 228/500 [1:21:59<1:32:17, 20.36s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 46%|████▌ | 229/500 [1:22:23<1:35:56, 21.24s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "\u001b[32m2026-01-06 10:13:17.122\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 46%|████▌ | 230/500 [1:22:40<1:30:02, 20.01s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 46%|████▌ | 231/500 [1:22:59<1:29:11, 19.90s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 46%|████▋ | 232/500 [1:23:27<1:39:47, 22.34s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 47%|████▋ | 233/500 [1:23:49<1:38:38, 22.17s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 47%|████▋ | 234/500 [1:24:10<1:36:53, 21.86s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 47%|████▋ | 235/500 [1:24:36<1:41:46, 23.05s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 47%|████▋ | 236/500 [1:24:58<1:40:17, 22.79s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 47%|████▋ | 237/500 [1:25:24<1:43:54, 23.71s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "\u001b[32m2026-01-06 10:16:17.342\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! 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Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 50%|████▉ | 248/500 [1:29:04<1:22:48, 19.72s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 50%|████▉ | 249/500 [1:29:27<1:26:30, 20.68s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "\u001b[32m2026-01-06 10:20:20.872\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! 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Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 52%|█████▏ | 258/500 [1:32:45<1:26:46, 21.52s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 52%|█████▏ | 259/500 [1:33:10<1:30:37, 22.56s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 52%|█████▏ | 260/500 [1:33:33<1:30:00, 22.50s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 52%|█████▏ | 261/500 [1:33:54<1:28:05, 22.12s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 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21.34s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 58%|█████▊ | 291/500 [1:45:12<1:15:32, 21.69s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 58%|█████▊ | 292/500 [1:45:43<1:25:03, 24.54s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "\u001b[32m2026-01-06 10:36:37.677\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 59%|█████▊ | 293/500 [1:46:00<1:17:23, 22.43s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 59%|█████▉ | 294/500 [1:46:21<1:15:31, 22.00s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 59%|█████▉ | 295/500 [1:46:47<1:19:17, 23.21s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 59%|█████▉ | 296/500 [1:47:09<1:17:01, 22.65s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 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{ "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 60%|██████ | 301/500 [1:49:05<1:15:17, 22.70s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 60%|██████ | 302/500 [1:49:33<1:20:10, 24.30s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 61%|██████ | 303/500 [1:49:57<1:19:05, 24.09s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 61%|██████ | 304/500 [1:50:21<1:19:07, 24.22s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", 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\u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 63%|██████▎ | 313/500 [1:53:38<1:06:25, 21.31s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 63%|██████▎ | 314/500 [1:54:05<1:10:48, 22.84s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 63%|██████▎ | 315/500 [1:54:30<1:12:23, 23.48s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 63%|██████▎ | 316/500 [1:54:54<1:12:51, 23.76s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 63%|██████▎ | 317/500 [1:55:18<1:12:13, 23.68s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "\u001b[32m2026-01-06 10:46:10.301\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 64%|██████▎ | 318/500 [1:55:33<1:04:15, 21.18s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 64%|██████▍ | 319/500 [1:55:50<1:00:03, 19.91s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 64%|██████▍ | 320/500 [1:56:13<1:02:56, 20.98s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 64%|██████▍ | 321/500 [1:56:38<1:05:43, 22.03s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "\u001b[32m2026-01-06 10:47:30.762\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 64%|██████▍ | 322/500 [1:56:53<59:35, 20.09s/it] " ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "\u001b[32m2026-01-06 10:47:46.549\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 65%|██████▍ | 323/500 [1:57:09<55:27, 18.80s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 65%|██████▍ | 324/500 [1:57:32<58:39, 20.00s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "\u001b[32m2026-01-06 10:48:27.121\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! 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Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 68%|██████▊ | 342/500 [2:03:50<58:27, 22.20s/it] " ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 69%|██████▊ | 343/500 [2:04:11<57:16, 21.89s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "\u001b[32m2026-01-06 10:55:03.199\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! 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Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 83%|████████▎ | 414/500 [2:30:48<29:57, 20.91s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 83%|████████▎ | 415/500 [2:31:10<30:05, 21.24s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 83%|████████▎ | 416/500 [2:31:32<30:09, 21.55s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 83%|████████▎ | 417/500 [2:31:54<30:15, 21.87s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 84%|████████▎ | 418/500 [2:32:18<30:28, 22.30s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 84%|████████▍ | 419/500 [2:32:36<28:27, 21.08s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "\u001b[32m2026-01-06 11:23:30.132\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 84%|████████▍ | 420/500 [2:32:53<26:21, 19.76s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 84%|████████▍ | 421/500 [2:33:14<26:33, 20.17s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 84%|████████▍ | 422/500 [2:33:35<26:28, 20.36s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 85%|████████▍ | 423/500 [2:33:56<26:22, 20.55s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 85%|████████▍ | 424/500 [2:34:19<27:04, 21.37s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 85%|████████▌ | 425/500 [2:34:42<27:12, 21.76s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 85%|████████▌ | 426/500 [2:35:07<28:17, 22.94s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n", "\u001b[32m2026-01-06 11:25:59.683\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! 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Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 90%|████████▉ | 448/500 [2:43:10<17:59, 20.76s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 90%|████████▉ | 449/500 [2:43:29<17:04, 20.08s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 90%|█████████ | 450/500 [2:43:51<17:19, 20.79s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "\u001b[32m2026-01-06 11:34:44.716\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! 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1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 92%|█████████▏| 459/500 [2:47:07<14:48, 21.67s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 92%|█████████▏| 460/500 [2:47:31<15:04, 22.61s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 92%|█████████▏| 461/500 [2:47:53<14:31, 22.34s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 92%|█████████▏| 462/500 [2:48:14<13:55, 21.99s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { 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21.79s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 99%|█████████▉| 496/500 [3:00:50<01:28, 22.05s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 99%|█████████▉| 497/500 [3:01:12<01:06, 22.15s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "\u001b[32m2026-01-06 11:52:06.859\u001b[0m | \u001b[31m\u001b[1mERROR \u001b[0m | \u001b[36mevoagentx.workflow.workflow\u001b[0m:\u001b[36masync_execute\u001b[0m:\u001b[36m104\u001b[0m - \u001b[31m\u001b[1mAn Error occurs when executing the workflow: The input type is invalid! Valid types: [str, dict, list].\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 100%|█████████▉| 498/500 [3:01:29<00:41, 20.76s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 0.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\r", "Evaluating workflow: 100%|█████████▉| 499/500 [3:01:51<00:20, 20.93s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Evaluating workflow: 100%|██████████| 500/500 [3:02:10<00:00, 21.86s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "metrics {'f1': 0, 'em': 0.0, 'acc': 1.0}\n", "Evaluation metrics: {'f1': 0.0, 'em': 0.0, 'acc': 0.568}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "\n", "optimizer.evaluator.dataname = 'hotpotqa'\n", "optimizer.optimize(dataset=benchmark,provided_scorer=True)\n", "optimizer.restore_best_graph()\n", "optimizer.save(\"debug/optimized_ourmethod_gpt4omini_5step_generate_new_call3.json\")\n", "\n", "# evaluate the optimized SEW workflow\n", "\n", "optimizer.evaluator.dataname = 'hotpotqa'\n", "with suppress_logger_info():\n", " metrics = optimizer.evaluate(dataset=benchmark, eval_mode=\"test\")\n", "print(\"Evaluation metrics: \", metrics)" ] }, { "cell_type": "code", "execution_count": 30, "id": "e6202b58", "metadata": { "scrolled": true }, "outputs": [], "source": [ "# optimizer.save(\"debug/optimized_ourmethod_gpt4omini_optzall.json\")\n", "# optimizer.save(\"debug/optimized_ourmethod_gpt4omini_optzall_generate_critic_refine.json\")" ] }, { "cell_type": "code", "execution_count": 32, "id": "10a154db", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'f1': 0.0, 'em': 0.0, 'acc': 0.568}" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "metrics" ] }, { "cell_type": "code", "execution_count": 53, "id": "77738053", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'f1': 0.0, 'em': 0.0, 'acc': 0.49}" ] }, "execution_count": 53, "metadata": {}, "output_type": "execute_result" } ], "source": [ "metrics" ] }, { "cell_type": "code", "execution_count": null, "id": "1906d2d6", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "91d65c86", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "de4cbf65", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "cfe8c3e3", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "f4b6f7ff", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.13" } }, "nbformat": 4, "nbformat_minor": 5 }