Results 241 to 250 of about 9,617,273 (323)

Deciphering Anti‐Cancer Drug Efficacy Through Nanomechanical Vibrations in Living Gastric Cancer Organoids

open access: yesAdvanced Science, EarlyView.
This study developed an efficacy assessment platform that integrates patient‐derived gastric cancer organoids, atomic force microscopy (AFM)‐based nanomechanical vibration detection, deep learning analysis, and organoid mechanical modeling. It detects picomolar drug effects within 0.1 s signal, achieves 97% classification accuracy, and offers non ...
Ting Zhang   +10 more
wiley   +1 more source

Development and Psychometric Assessment of a Measurement Instrument for Functioning and Function-Affecting Factors in Women With Breast Cancer: A Rasch Analysis Approach. [PDF]

open access: yesJ Eval Clin Pract
Jamshidihosseinabadi F   +9 more
europepmc   +1 more source

Artificial Intelligence‐Guided Phenotypic Drug Repurposing Against Streptococcus pneumoniae

open access: yesAdvanced Science, EarlyView.
Integrated artificial intelligence (AI) ensembles identify highly potent repurposed drugs against Streptococcus pneumoniae. Prospective virtual screening of 6747 drugs uncovers nine active candidates, including thiostrepton. This drug exhibits low picomolar potency and bypasses established resistance in multidrug‐resistant strains, demonstrating an ...
Joshua S. Fitch   +6 more
wiley   +1 more source

SemanticST: A Scalable Multi‐Contextual Graph Learning Framework for Uncovering Spatial Niches and Robust Multi‐Sample Integration in Spatial Transcriptomics

open access: yesAdvanced Science, EarlyView.
Technical limitations often let dominant signals overshadow rare cell types and fine‐grained heterogeneity in spatial transcriptomics. SemanticST, a graph neural network using multi‐semantic graph fusion and a novel min‐cut loss, recovers these subtle patterns.
Roxana Zahedi   +7 more
wiley   +1 more source

Machine Learning of Temperature‐Dependent Chemical Kinetics Using Parallel Droplet Microreactors

open access: yesAdvanced Science, EarlyView.
An integrated droplet microfluidics and machine learning framework enables high‐throughput characterization of temperature‐dependent reaction kinetics. Time‐resolved measurements from thousands of droplets train Neural ODE models that accurately predict nonlinear reaction dynamics across diverse thermal environments, bridging large‐scale ...
Mamoru Saita, Yutaka Hori
wiley   +1 more source

Home - About - Disclaimer - Privacy