Results 171 to 180 of about 29,999,610 (319)
A‐to‐I editing of miRNAs, particularly miR‐200b‐3p, contributes to HGSOC progression by enhancing cancer cell proliferation, migration and 3D growth. The edited form is linked to poorer patient survival and the identification of novel molecular targets.
Magdalena Niemira+14 more
wiley +1 more source
Salt rock creep deformation forecasting using deep neural networks and analytical models for subsurface energy storage applications. [PDF]
Shukla PK+4 more
europepmc +1 more source
This real‐world study of ROS1+ NSCLC highlights fusion diversity, treatment outcomes with crizotinib and lorlatinib, and in vitro experiments with resistance mechanisms. G2032R drives strong resistance to ROS1‐targeted TKIs, especially lorlatinib. Fusion partner location does not affect overall survival to crizotinib or lorlatinib. Findings support the
Fenneke Zwierenga+8 more
wiley +1 more source
A systematic review of mathematical and machine learning models of Avian Influenza. [PDF]
Huang S+7 more
europepmc +1 more source
YAP1::TFE3 mediates endothelial‐to‐mesenchymal plasticity in epithelioid hemangioendothelioma
The YAP1::TFE3 fusion protein drives endothelial‐to‐mesenchymal transition (EndMT) plasticity, resulting in the loss of endothelial characteristics and gain of mesenchymal‐like properties, including resistance to anoikis, increased migratory capacity, and loss of contact growth inhibition in endothelial cells.
Ant Murphy+9 more
wiley +1 more source
Machine learning and statistical inference in microbial population genomics. [PDF]
Sheppard SK+3 more
europepmc +1 more source
Emerging role of ARHGAP29 in melanoma cell phenotype switching
This study gives first insights into the role of ARHGAP29 in malignant melanoma. ARHGAP29 was revealed to be connected to tumor cell plasticity, promoting a mesenchymal‐like, invasive phenotype and driving tumor progression. Further, it modulates cell spreading by influencing RhoA/ROCK signaling and affects SMAD2 activity. Rho GTPase‐activating protein
Beatrice Charlotte Tröster+3 more
wiley +1 more source
A Statistical Learning-Based Clustering Model With Features Selection to Identify Dyslexia in School-Aged Children. [PDF]
Maiella M+3 more
europepmc +1 more source
We evaluated circulating tumor DNA (ctDNA) detection in advanced pancreatic cancer using DNA methylation, cell‐free DNA fragment lengths, and 5′ end motifs. Machine learning models were trained to estimate ctDNA levels from each feature and their combination.
Morten Lapin+10 more
wiley +1 more source