Real-time continuous glucose monitoring improves postoperative glucose control in people with type 2 diabetes mellitus undergoing coronary artery bypass grafting: A randomized clinical trial.

Background: Effective glycaemic control following cardiac surgery improves clinical outcomes, and continuous glucose monitoring (CGM) might be a valuable tool in achieving this objective. We investigated the effect of real-time CGM and telemonitoring on postoperative glycaemic control in people with type 2 diabetes (T2D) after coronary artery bypass grafting (CABG).

Methods: In this randomized clinical trial (RCT), adults with T2D undergoing CABG were assigned to either a test group utilizing real-time CGM (Dexcom G6) and telemetry for glycaemic control, or a control group with blinded CGM measures, relying on point-of-care measures.

Evaluation of the Safety and Impact of Heat-Treated KM2 Fermentation on Gut Microbiome Architecture.

Postbiotics, bioactive compounds from the fermentation process by probiotics, are gaining attention for their potential health benefits as safer alternatives to live probiotic microbes. is a well-studied probiotic species known for promoting gut health and immune modulation. However, the safety and effects of its postbiotic formulations on the gut microbiome structure remain less explored.

Improved Glycemic Control in Insulin-Treated Individuals With Poorly Controlled Type 2 Diabetes Through Combined Structured Education With Real-Time Continuous Glucose Monitoring.

Background: We evaluated the efficacy of structured individualized education combined with real-time continuous glucose monitoring (rt-CGM, Dexcom G6) in improving glycemic outcomes in insulin-treated adults with poorly controlled type 2 diabetes (T2D).

Methods: This multicenter, 16-week, single-arm study included 66 adults with T2D (multiple daily insulin [MDI]: 33; basal insulin: 33) with a ≥7.8%.

Whole genome sequencing analysis of enteropathogenic from human and companion animals in Korea.

Importance: This study is essential for comprehending the zoonotic transmission, antimicrobial resistance, and genetic diversity of enteropathogenic (EPEC).

Objective: To improve our understanding of EPEC, this study focused on analyzing and comparing the genomic characteristics of EPEC isolates from humans and companion animals in Korea.

Methods: The whole genome of 26 EPEC isolates from patients with diarrhea and 20 EPEC isolates from companion animals in Korea were sequenced using the Illumina HiSeq X (Illumina, USA) and Oxford Nanopore MinION (Oxford Nanopore Technologies, UK) platforms.

A two-level resolution neural network with enhanced interpretability for freeway traffic forecasting.

Deep learning models are widely used for traffic forecasting on freeways due to their ability to learn complex temporal and spatial relationships. In particular, graph neural networks, which integrate graph theory into deep learning, have become popular for modeling traffic sensor networks. However, traditional graph convolutional networks (GCNs) face limitations in capturing long-range spatial correlations, which can hinder accurate long-term predictions.