Results 171 to 180 of about 20,846,472 (359)
Treatment-Free Remission Era: BCR-ABL1 mRNA Transcript Level <5% at 3 Months Predicts 24-Month Deep Molecular Response and Better Survival [PDF]
Lisi Huang +11 more
openalex +1 more source
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
Ixazomib inhibits proteasome‐mediated degradation of topoisomerase I induced by irinotecan, thereby restoring drug sensitivity and promoting tumor cell death in colorectal cancer. Irinotecan, a topoisomerase I (topoI) inhibitor, is widely used for colorectal cancer, but resistance remains a major clinical challenge.
Yuho Ebata +10 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
The Uncoupling of CT Dose and Noise. [PDF]
McCollough CH, Leng S, Yu L.
europepmc +1 more source
Learning Deep Architectures for AI
Yoshua Bengio
semanticscholar +1 more source
Radiotherapy (RT) response depends on the DNA repair capacity of tumor and host cells. We show that circulating tumor cell (CTC) counts and apoptosis rates before and after RT predict treatment response and outcome, which can be accessed via easily accessible liquid biopsy approaches. Created in BioRender. Wikman, H.
Yvonne Goy +10 more
wiley +1 more source
The impact of a novel deep learning reconstruction algorithm on image quality in ultralow-dose CT: a quantitative phantom study. [PDF]
Su T, Jia Y, Shen Y, Zhang H.
europepmc +1 more source

