Machine Learning in Intravascular Ultrasound: Validating Automated Lesion Assessment for Complex Coronary Interventions.

Background: Intravascular ultrasound (IVUS) is essential for assessing complex coronary lesions, but remains underutilized in part due to difficulties in image interpretation. The AVVIGO IVUS Automated Lesion Assessment (ALA) software, which uses machine learning (ML) for automatic segmentation, promises to simplify lesion assessment. This study evaluated the agreement in stent size selection between ALA, an independent core laboratory (CL), and an expert interventional cardiologist (IC) for complex lesions.

Duplication Syndrome: AI-Based Diagnosis, Severity Scale Development and Correlation with Clinical and Molecular Variables.

: duplication syndrome (MDS) (MIM#300260) is a rare X-linked neurodevelopmental disorder. This study aims to (1) develop a specific clinical severity scale, (2) explore its correlation with clinical and molecular variables, and (3) automate diagnosis using the Face2gene platform. : A retrospective study was conducted on genetically confirmed MDS patients who were evaluated at a pediatric hospital between 2012 and 2024.

Electron-rich anilines as cleavable linkers for peptides.

We report the development of a new electron-rich aniline (ERA)-based cleavable linker. Anilines can be incorporated into peptides during SPPS and are stable to most reaction conditions. ERA-containing peptides can be cleaved rapidly in the presence of oxidants, such as DDQ, CAN, and NaIO, in 30 min at room temperature.