Results 201 to 210 of about 6,126,485 (362)
Interpreting the effects of DNA polymerase variants at the structural level
Using MAVISp and molecular dynamics simulations, we analyzed over 60 000 missense variants in POLE and POLD1 from ClinVar, COSMIC, cBioPortal, and saturation mutagenesis. Identified mechanistic indicators, including stability, binding, and long‐range, enable structural interpretation, providing ACMG‐like evidence for possible reclassification of VUS ...
Matteo Arnaudi +7 more
wiley +1 more source
Dormant cancer cells can hide in distant organs for years, evading treatment and the immune system. This review highlights how signals from the surrounding tissue and immune environment keep these cells inactive or trigger their reawakening. Understanding these mechanisms may help develop therapies to eliminate or control dormant cells and prevent ...
Kanishka Tiwary +1 more
wiley +1 more source
Automated classification of natural habitats using ground-level imagery. [PDF]
Tourian M +9 more
europepmc +1 more source
ImageNet classification with deep convolutional neural networks
A. Krizhevsky +2 more
semanticscholar +1 more source
Both cg12821679MAPRE3 methylation and MAPRE3 expression are significantly associated with overall survival (OS) of non‐small cell lung cancer. Meanwhile, MAPRE3 expression significantly modified the effect of smoking cessation on OS. Smoking cessation benefits OS merely for patients with high MAPRE3 expression.
Chao Chen +14 more
wiley +1 more source
An AI-driven framework for diabetic foot ulcer classification, segmentation, and depth estimation. [PDF]
Debnath S +5 more
europepmc +1 more source
A urine‐based digital PCR assay targeting two hotspot TERT promoter variants detected bladder cancer with high sensitivity and no false positives in this case–control cohort. The streamlined AbsoluteQ workflow outperformed Sanger sequencing and supports non‐invasive molecular testing for bladder cancer detection.
Anna Nykel +12 more
wiley +1 more source
Voice disorders classification using machine learning: a scoping review. [PDF]
Gupta R +6 more
europepmc +1 more source

