Dietary habits play a key role in chronic diseases, and higher annual consumption of fruit and vegetable may lower risk of dementia. Artificial intelligence predicts the lipid‐like compound α‐Amyrin (αA) from plants with edible peels as a drug candidate against Alzheimer's disease.
Shu‐Qin Cao +36 more
wiley +1 more source
A lncRNA-disease association prediction tool development based on bridge heterogeneous information network via graph representation learning for family medicine and primary care. [PDF]
Zhang P +6 more
europepmc +1 more source
Discovery of H2 Receptor Antagonists as Colistin Enhancers by Targeting Acid Stress Response
This study identifies YqgB as a key target for restoring colistin susceptibility in mcr‐positive pathogens under acidic conditions by remodeling phospholipid composition and reducing LPS modification. Deep learning‐based screening reveals H2 receptor antagonists as novel colistin adjuvants. Further investigations indicate that ranitidine and famotidine
Jinju Cai +7 more
wiley +1 more source
Graph Representation Learning for the Prediction of Medication Usage in the UK Biobank Based on Pharmacogenetic Variants. [PDF]
Qi B, Trakadis YJ.
europepmc +1 more source
Graph Representation Learning-Based Early Depression Detection Framework in Smart Home Environments. [PDF]
Kim J, Sohn M.
europepmc +1 more source
This study, through multi‐omics approaches and animal models, revealed that air pollutant PM10 exacerbates the progression of rheumatoid arthritis (RA) by suppressing FNBP1 expression and impairing the cytotoxic function of CD56dim NK cells. The “PM10–FNBP1–NK cells” axis provided novel insights into the environmental pathogenesis of RA and suggested ...
Runhan Zhao +11 more
wiley +1 more source
PreMode predicts mode-of-action of missense variants by deep graph representation learning of protein sequence and structural context. [PDF]
Zhong G +4 more
europepmc +1 more source
Dynamic Heterogeneous User Generated Contents-Driven Relation Assessment via Graph Representation Learning. [PDF]
Huang R, Chen Z, He J, Chu X.
europepmc +1 more source
Evaluating the Utilities of Foundation Models in Single‐Cell Data Analysis
This study delivers the first systematic, task‐level evaluation of single‐cell foundation models across eight core analytical tasks. By benchmarking 10 leading models with the scEval framework, it reveals where foundation models truly add value, where task‐specific methods still dominate, and provides concrete, reproducible guidelines to steer the next
Tianyu Liu +4 more
wiley +1 more source
stGuide advances label transfer in spatial transcriptomics through attention-based supervised graph representation learning. [PDF]
Xu Y +6 more
europepmc +1 more source

