Performance of Noninvasive Tests for Metabolic Dysfunction-Associated Steatohepatitis and Liver Fibrosis Resolution after Bariatric Surgery.

Background: Noninvasive tests (NITs) to monitor metabolic dysfunction-associated steatohepatitis (MASH) progression and response to interventions are needed because of the risks of liver biopsy. A monocytes-based diagnostic test using perilipin-2 (PLIN2) and Ras-related protein-14 (RAB14) predict the severity of MASH and fibrosis. Here we compared the performances of PLIN2 and RAB14 with cytokeratin-18 (CK18) assessed by Ella™ or M65 ELISA in predicting MASH and fibrosis resolution following bariatric surgery in a longitudinal and histologically characterized cohort of individuals with obesity.

Enhancing door-to-door waste collection forecasting through ML.

We explore the application of machine learning (ML) techniques to forecast door-to-door waste collection, addressing the challenges in municipal solid waste (MSW) management. ML models offer a promising solution to optimize waste collection operations, especially amid growing urban populations and evolving waste generation rates. Leveraging comprehensive data from a northeastern Italian municipality, including various waste types, our study investigates ML algorithms' efficacy in predicting household waste collection requirements.

Percutaneous coronary saccular aneurysm exclusion.

Coronary artery aneurysms are a relatively uncommon finding during coronary angiography and can present certain challenges in terms of treatment options. This may be due to unclear underlying mechanisms and varying presentations, as well as a lack of large-scale outcome data. In this case report we present the successful use of percutaneous coronary intervention (PCI) in treating a 43-year-old male patient who presented with acute myocardial infarction and was discovered during angiography to have a saccular coronary aneurysm.