Machine Learning in Vascular Medicine: Optimizing Clinical Strategies for Peripheral Artery Disease.

Purpose Of Review: Peripheral Artery Disease (PAD), a condition affecting millions of patients, is often underdiagnosed due to a lack of symptoms in the early stages and management can be complex given differences in genetic and phenotypic characteristics. This review aims to provide readers with an update on the utility of machine learning (ML) in the management of PAD.

Recent Findings: Recent research leveraging electronic health record (EHR) data and ML algorithms have demonstrated significant advances in the potential use of automated systems, namely artificial intelligence (AI), to accurately identify patients who might benefit from further PAD screening.

Hybrid magnetic structures around spinning black holes connected to a surrounding accretion disk.

The hot accretion flow around Kerr black holes is strongly magnetized. Magnetic field loops sustained by a surrounding accretion disk can close within the event horizon. We performed particle-in-cell simulations in Kerr metric to capture the dynamics of the electromagnetic field and of the ambient collisionless plasma in this coupled configuration.

(Sub)stellar companions shape the winds of evolved stars.

Binary interactions dominate the evolution of massive stars, but their role is less clear for low- and intermediate-mass stars. The evolution of a spherical wind from an asymptotic giant branch (AGB) star into a nonspherical planetary nebula (PN) could be due to binary interactions. We observed a sample of AGB stars with the Atacama Large Millimeter/submillimeter Array (ALMA) and found that their winds exhibit distinct nonspherical geometries with morphological similarities to planetary nebulae (PNe).

Predisposing gene for early-onset prostate cancer, localized on chromosome 1q42.2-43.

There is genetic predisposition associated with >=10% of all cancer of the prostate (CaP). By means of a genomewide search on a selection of 47 French and German families, parametric and nonparametric linkage (NPL) analysis allowed identification of a locus, on chromosome 1q42.2-43, carrying a putative predisposing gene for CaP (PCaP).