Artificial Intelligence in Computer-Aided Drug Design (CADD) Tools for the Finding of Potent Biologically Active Small Molecules: Traditional to Modern Approach.

Computer-Aided Drug Design (CADD) entails designing molecules that could potentially interact with a specific biomolecular target and promising their potential binding. The stereo- arrangement and stereo-selectivity of small molecules (SMs)--based chemotherapeutic agents significantly influence their therapeutic potential and enhance their therapeutic advantages. CADD has been a well-established field for decades, but recent years have observed a significant shift toward acceptance of computational approaches in both academia and the pharmaceutical industry.

Proteomics-Based Soluble Urokinase Plasminogen Activator Receptor Levels Are Associated With Incident Heart Failure Risk.

Background: Higher soluble urokinase plasminogen activator receptor (suPAR) levels are associated with adverse outcomes in chronic heart failure (HF).

Objectives: The authors assessed the association between proteomics-based suPAR levels and incident HF risk in the general population.

Methods: In 40,418 UK Biobank participants without HF or coronary artery disease at enrollment, the association between Olink-based suPAR levels measured as relative protein expression levels and incident all-cause, ischemic, and nonischemic HF was analyzed by competing-risk regression, while accounting for all-cause death as a competing risk.

Semi-supervised contour-driven broad learning system for autonomous segmentation of concealed prohibited baggage items.

With the exponential rise in global air traffic, ensuring swift passenger processing while countering potential security threats has become a paramount concern for aviation security. Although X-ray baggage monitoring is now standard, manual screening has several limitations, including the propensity for errors, and raises concerns about passenger privacy. To address these drawbacks, researchers have leveraged recent advances in deep learning to design threat-segmentation frameworks.