Global burden, risk factors, and projections of early-onset dementia: Insights from the Global Burden of Disease Study 2021.

Background: Despite increasing global awareness of dementia, reliable estimates of the disease burden associated with Early-Onset Dementia (EOD) remain insufficiently quantified. This study aims to estimate the disease burden of EOD, analyze the burden attributable to risk factors from 1990 to 2021, and project these trends to 2050 at global, regional, and national levels, providing essential data to inform public health policy.

Methods: By utilising data from the GBD 2021 database, this study analysed metrics such as age-standardized prevalence (ASPR), mortality (ASMR), and disability-adjusted life years (AS-DALYs) for EOD.

Ultrasound nanodroplets loaded with Siglec-G siRNA and FeO activate macrophages and enhance phagocytosis for immunotherapy of triple-negative breast cancer.

Background: The progression of triple-negative breast cancer is shaped by both tumor cells and the surrounding tumor microenvironment (TME). Within the TME, tumor-associated macrophages (TAMs) represent a significant cell population and have emerged as a primary target for cancer therapy. As antigen-presenting cells within the innate immune system, macrophages are pivotal in tumor immunotherapy through their phagocytic functions.

Clinical characteristics and prediction model of re-positive nucleic acid tests among Omicron infections by machine learning: a real-world study of 35,488 cases.

Background: During the Omicron BA.2 variant outbreak in Shanghai, China, from April to May 2022, PCR nucleic acid test re-positivity (TR) occurred frequently, yet the risk factors and predictive models for TR remain unclear. This study aims to identify the factors influencing Omicron TR and to develop machine learning models to predict TR risk.