Beyond predictive accuracy: A case for mechanism-informed, uncertainty-aware machine learning in food microbiology. [PDF]
Ezzaky Y, Yap EEL, Chen WN.
europepmc +1 more source
The VHL tumor suppressor at the crossroad of protein folding, aggregation, and cancer
Mutations, environmental stress, and chaperone dysfunction can destabilize pVHL, promoting its conversion from the native folded state into amyloid‐like assemblies. This transition may contribute to protein storage, cell dormancy, survival, and drug resistance.
Lara Abad +2 more
wiley +1 more source
An Interpretable Multi-Objective Machine Learning Framework for In Silico Prioritization of Anti-<i>Staphylococcus aureus</i> Antimicrobial Peptides. [PDF]
Xu J +5 more
europepmc +1 more source
Gut microbiota alterations in patients with non‐small‐cell lung cancer undergoing chemoradiotherapy
We investigated the impact of concurrent chemoradiotherapy (CRT) on the gut microbiota in patients with locally advanced non‐small‐cell lung cancer. Overall gut microbiota composition remained largely stable throughout CRT while antibiotic exposure may influence microbial diversity.
Hanne Marte Nymoen +19 more
wiley +1 more source
Interpretable Machine Learning Prediction of the Dielectric Constant and Bandgap of Polymers for Flexible Electronics. [PDF]
Gül F.
europepmc +1 more source
Extracellular vesicle (EV) lipidomic profiling of plasma and ascites from patients with high‐grade serous ovarian cancer and of ovarian cancer cell lines reveals enrichment of triglycerides (TGs), diacylglycerols (DGs), phosphatidylcholine (PCs), sphingomyelins (SMs), reflecting tumor metabolic reprogramming.
Shikha Rani +9 more
wiley +1 more source
Feasibility and diagnostic added value of a point of care mobile EEG system. [PDF]
Armand Larsen S +6 more
europepmc +1 more source
AResKGLM: a graph-grounded language-model framework for interpretable multi-hop antimicrobial resistance reasoning. [PDF]
Ren J +3 more
europepmc +1 more source
MorphoNet: An Interpretable Hierarchical Deep Learning Framework for Multi-Class Skin Lesion Classification Using Dermoscopic Morphology. [PDF]
Yao B, Jin A, Liu H, Li Q.
europepmc +1 more source

