Results 201 to 210 of about 6,178,785 (249)
External Validation Cannot Participate in Selecting a Rheumatoid Arthritis Diagnostic Model [Letter]. [PDF]
Chen Q.
europepmc +1 more source
Thioredoxin‐2 Alleviates Osteoporosis by Restraining FOXO3a Nuclear Translocation
Endothelial TRX2 preserves bone homeostasis by retaining FOXO3a at mitochondria and limiting TRAIL production. Loss of TRX2 or oxidative stress releases FOXO3a for nuclear translocation, increasing endothelial TRAIL secretion and driving osteoclast formation and bone loss.
Chi Zhan +10 more
wiley +1 more source
Combination of Chenpi and Banxia alleviates synovial inflammation in a rat model of rheumatoid arthritis by targeting the JNK/AP-1 signaling pathway. [PDF]
Zhang W +9 more
europepmc +1 more source
HECTD1 emerges as an upstream amplifier of Th17 metabolic programming by promoting K63‐linked ubiquitination of IGF2BP3 and enhancing HIF‐1α translation. HIF‐1α reciprocally drives HECTD1 transcription, establishing a positive regulatory loop that sustains glycolysis and Th17 differentiation.
Shuiyu Xu +12 more
wiley +1 more source
Peedanil Gold attenuates IL-6-mediated articular pathologies in a collagen antibody-induced murine model of rheumatoid arthritis. [PDF]
Balkrishna A +4 more
europepmc +1 more source
Clinical symptoms offer a window into multimorbidity. A macro‐micro heterogeneous graph neural network integrates clinical records with biomedical knowledge to improve patient‐level symptom‐disease association learning and visit‐level multimorbidity completion.
Yiheng Ye +15 more
wiley +1 more source
Automating AI Discovery for Biomedicine Through Knowledge Graphs and Large Language Models Agents
This work proposes a novel framework that automates biomedical discovery by integrating knowledge graphs with multiagent large language models. A biologically aligned graph exploration strategy identifies hidden pathways between biomedical entities, and specialized agents use this pathway to iteratively design AI predictors and wet‐lab validation ...
Naafey Aamer +3 more
wiley +1 more source
MetaPaCS: A Novel Meta‐Learning Framework for Pancreatic Cancer Subtype Identification
We have developed MetaPaCS, an ensemble meta‐learning framework for reliable prediction of pancreatic cancer subtypes with high accuracy. MetaPaCS is capable of capturing subtype‐specific distinct gene expression patterns and drug‐disease associations for pancreatic cancer.
Nick B. Peterson +4 more
wiley +1 more source

