Results 281 to 290 of about 265,213 (339)
MiR‐29a/b Suppresses CD8+ T Cell Effector Function and Intestinal Inflammation
Our findings suggest that miR‐29a/b is a critical regulator of CD8+ T cells, possibly via the Ifng‐JAK‐STAT signal in IBD patients and the upregulation of miR‐29a/b relieves the development of significant inflammation in the colon of DSS‐induced colitis‐affected mice.
Yingying Lin+27 more
wiley +1 more source
Association Between Muscle Quality Assessed by the 5-Repetition Sit-to-Stand Test and Falls in Community-Dwelling Older Adults in Japan: A Cross-Sectional Study. [PDF]
Takimoto K+3 more
europepmc +1 more source
ABSTRACT Background Head and neck cancer (HNC) significantly impacts older adults, with mortality influenced by multiple factors. The Multidimensional Prognostic Index (MPI), derived from comprehensive geriatric assessment (CGA), may improve risk stratification and clinical decision making. Methods An observational cohort study was conducted at Erasmus
Ajay T. Bakas+5 more
wiley +1 more source
Risk Factors for Non-Carbapenemase-Producing Carbapenem-Resistant <i>Enterobacterales</i> Infections: A Retrospective Cohort Study. [PDF]
Mabuchi S+4 more
europepmc +1 more source
Development and validation of PRE-FRA (PREdiction of FRAilty risk in community older adults) frailty prediction model. [PDF]
Lin T, Huang X, Wang X, Dai M, Yue J.
europepmc +1 more source
Pandemic Performance Measures of Resilience for Healthcare and Education in the Netherlands
ABSTRACT During the COVID‐19 pandemic, policymakers focused on improving health outcomes and safeguarding healthcare availability, which have led to negative consequences for other societal systems that persist today. The impact of these policies on health and non‐healthcare systems depends on the resilience of these systems, that is, the capability of
Sophie Hadjisotiriou+10 more
wiley +1 more source
Challenges, knowledge, and skills required for family caregivers of older adults with dementia: a qualitative study in Vietnam. [PDF]
Nguyen TTT+7 more
europepmc +1 more source
Saliva MicroAge is a machine learning‐based model designed to estimate biological age and assess health status using globally sourced salivary microbiome data. Trained on 4532 healthy samples, the model achieves high accuracy in predicting chronological age and captures health‐related deviations (MicroAgeGap) in various diseases.
Tiansong Xu+13 more
wiley +1 more source