We analyze cisplatin–DNA adducts (CDAs) and double‐strand breaks (DSBs) in a cell‐cycle‐dependent manner. We find that CDAs form similarly across all cell cycle phases. DSBs arise only in S‐phase. CDAs might not directly impair DSB repair, but S‐phase DSB lesions evolve in the presence of CDAs and disrupt repair in G2, also causing radiosensitization ...
Ye Qiu +10 more
wiley +1 more source
FKSUDDAPre: A drug-disease association prediction framework based on F-TEST feature selection and AMDKSU resampling with interpretability analysis. [PDF]
Zuo Y +6 more
europepmc +1 more source
Hijacking emergency granulopoiesis: Neutrophil ontogeny and reprogramming in cancer
Neutrophils are highly plastic innate immune cells; their functions in cancer extend beyond the tumour microenvironment. This Review summarises current understanding of neutrophil maturation and heterogeneity and highlights tumour‐induced granulopoiesis as a systemic programme that expands immature, immunosuppressive neutrophils via tumour‐derived ...
Gabriela Marinescu, Yi Feng
wiley +1 more source
Interpretable Feature Selection and Hybrid Deep Learning Models for Depressive Symptoms Prediction from Wearable Device Data. [PDF]
Ko J +9 more
europepmc +1 more source
Rethinking plastic waste: innovations in enzymatic breakdown of oil‐based polyesters and bioplastics
Plastic pollution remains a critical environmental challenge, and current mechanical and chemical recycling methods are insufficient to achieve a fully circular economy. This review highlights recent breakthroughs in the enzymatic depolymerization of both oil‐derived polyesters and bioplastics, including high‐throughput protein engineering, de novo ...
Elena Rosini +2 more
wiley +1 more source
Drug Repurposing in Glioblastoma Using a Machine Learning-Based Hybrid Feature Selection Approach. [PDF]
Tasci E, Camphausen K, Krauze AV.
europepmc +1 more source
Overview of molecular signatures of senescence and associated resources: pros and cons
Cells can enter a stress response state termed cellular senescence that is involved in various diseases and aging. Detecting these cells is challenging due to the lack of universal biomarkers. This review presents the current state of senescence identification, from biomarkers to molecular signatures, compares tools and approaches, and highlights ...
Orestis A. Ntintas +6 more
wiley +1 more source
Variability Regularized Feature Selection (VaRFS) for optimal identification of robust and discriminable features from medical imaging. [PDF]
Sadri AR +6 more
europepmc +1 more source
Unveiling patterns: an exploration of machine learning techniques for unsupervised feature selection in single-cell data. [PDF]
Chatterjee N +6 more
europepmc +1 more source

