ChloroDBPFinder: Machine Learning-Guided Recognition of Chlorinated Disinfection Byproducts from Nontargeted LC-HRMS Analysis.

High-resolution mass spectrometry (HRMS) is a prominent analytical tool that characterizes chlorinated disinfection byproducts (Cl-DBPs) in an unbiased manner. Due to the diversity of chemicals, complex background signals, and the inherent analytical fluctuations of HRMS, conventional isotopic pattern (Cl/Cl), mass defect, and direct molecular formula (MF) prediction are insufficient for accurate recognition of the diverse Cl-DBPs in real environmental samples. This work proposes a novel strategy to recognize Cl-containing chemicals based on machine learning.

Intracoronary Imaging in the Detection of Vulnerable Plaques.

Coronary artery disease is the result of atherosclerotic changes to the coronary arterial wall, comprising endothelial dysfunction, vascular inflammation and deposition of lipid-rich macrophage foam cells. Certain high-risk atherosclerotic plaques are vulnerable to disruption, leading to rupture, thrombosis and the clinical sequelae of acute coronary syndrome. Though recognised as the gold standard for evaluating the presence, distribution and severity of atherosclerotic lesions, invasive coronary angiography is incapable of identifying non-stenotic, vulnerable plaques that are responsible for adverse cardiovascular events.