Appropriateness of Antiplatelet Therapy and Proton Pump Inhibitor Prescribing in End-Stage Kidney Disease: A Retrospective Quality Investigation Study.

Background: Patients with end-stage kidney disease (ESKD) have high rates of gastrointestinal bleeding due to several risk factors including platelet dysfunction, comorbid illness, and use of antiplatelet medications. Proton pump inhibitors (PPIs) reduce gastrointestinal bleeding and are recommended for high-risk patients such as those prescribed dual antiplatelet therapy (DAPT). Whether inappropriate duration of DAPT therapy and/or lack of appropriate PPI use contribute to the known elevated risk of gastrointestinal bleeding in hemodialysis patients is not known.

Temporal trends in disability adjusted life year and mortality for colorectal cancer attributable to a high red meat diet in China from 1990 to 2021: an analysis of the global burden of disease study 2021.

Background: High red meat consumption is a main modifiable risk factor for colorectal cancer mortality (CRC), but its attributable disease burden remains unclear in China. We aimed to analyze the temporal trends in CRC deaths and disability-adjusted life years (DALYs) attributable to high red meat consumption in China from 1990 to 2021 and to predict the disease burden in the next 15 years.

Methods: Data was obtained from the Global Burden of Disease (GBD) 2021 study.

Rational design of uniform SiO-based afterglow microparticles for photonic crystals.

Despite recent advancements in organic phosphors, the synthesis of monodisperse afterglow microparticles (MPs) suitable for creating photonic crystals remains challenging. The SiO matrix is an attractive host material for activating the long-lived emissions of doped molecules due to several factors, including its cross-linked polymer-like structure, abundance of -OH groups, robustness, and presence of numerous emitter defects. However, the Stöber method struggles to produce monodisperse molecule-doped SiO MPs due to the complexity of the system.

Double-target self-supervised clustering with multi-feature fusion for medical question texts.

Background: To make the question text represent more information and construct an end-to-end text clustering model, we propose a double-target self-supervised clustering with multi-feature fusion (MF-DSC) for texts which describe questions related to the medical field. Since medical question-and-answer data are unstructured texts and characterized by short characters and irregular language use, the features extracted by a single model cannot fully characterize the text content.

Methods: Firstly, word weights were obtained based on term frequency, and word vectors were generated according to lexical semantic information.

Dynamic Modulation of Afterglow Emission in Polymeric Phosphors via Inverse Opal Photonic Structures.

Tuning the afterglow of polymeric phosphors is critical for advancing their use in optical data storage and display technologies. Despite advancements in polymer matrix design and dopant engineering, achieving dynamic control over afterglow intensity remains a significant challenge. In this study, a novel approach is introduced for dynamically tuning the afterglow of polymeric phosphors by integrating them into an inverse opal photonic structure.