Prevention

PMB-NN: Physiology-centered hybrid AI for personalized hemodynamic monitoring from photoplethysmography.

BACKGROUND AND OBJECTIVE: Continuous monitoring of blood pressure (BP) and hemodynamic parameters such as peripheral resistance (R) and arterial compliance (C) are critical for early vascular dysfunction detection and therapy optimization. While photoplethysmography (PPG) wearables has gained widespread popularity, existing data-driven methods for BP estimation lack physiological interpretability....

Multi-omics analysis identifies CD48 and ITIH5 as potential diagnostic biomarkers and therapeutic targets for metabolic disorders associated with obesity.

BACKGROUND: Obesity-driven metabolic disorders involve pathological remodeling of white adipose tissue (WAT), wherein fibroblasts coordinate fibrosis and inflammation. This study aimed to characterize fibroblast transcriptional heterogeneity, identify fibrosis-inflammation mediators, and discover diagnostic and therapeutic targets. METHODS: Single-cell (GSE155960) and bulk (GSE205668) RNA-seq data...

VAV3 is associated with atherosclerosis and ox-LDL-induced endothelial dysfunctional remodeling.

BACKGROUND: Atherosclerosis is a major cause of ischemic stroke and is characterized by complex immune-metabolic dysregulation. VAV3, a Rho guanine nu...

Symptom burden in dialysis patients: determinants and impact on mortality.

BACKGROUND: Symptom burden in chronic kidney disease (CKD) patients has a negative impact on functional status and quality of life. Despite the high p...

Longitudinal serum uric acid transition patterns and their clinical, genetic, and dietary determinants: prospective prediction of incident hyperuricemia and gout in a Korean population-based cohort.

BACKGROUND: Longitudinal serum uric acid (SUA) transition patterns and their clinical, genetic, and dietary determinants remain poorly characterized. ...

Image-based consensus molecular subtypes and colon cancer recurrence: Understanding the impact of lifestyle factors across subtypes of colon cancer.

AIM: We investigated associations between consensus molecular subtype (CMS) and colon cancer recurrence, and explored how the inflammatory potential o...

Development of an artificial intelligence prediction model for moderate-to-severe COPD exacerbations using continuous multiple unobtrusive sensors: protocol of a multicentre prospective observational study.

INTRODUCTION: Exacerbations, impaired health-related quality of life (HRQoL) and reduced exercise capacity increase the risk of hospitalisations and d...

Plant-based diet quality and risk of age-related eye diseases: evidence from multi-cohorts with multi-omics insights.

Plant-based diets may influence age-related eye diseases (AREDs), but whether ocular benefits depend on diet quality remains unclear. We examined asso...

A systematic review of molecular signaling in the muscle-brain-gut axis: exercise-induced myokines and microbial metabolites as key mediators.

Exercise physiology is evolving from an organ-based framework toward a systems-level understanding, where molecular interactions between muscle, brain...

Personalized Type 1 Diabetes Management: Reinforcement Learning-Based Insulin Dosing and Glucose Forecasting.

BACKGROUND: Optimizing insulin dosing and predicting future glucose levels for people with type 1 diabetes is challenging due to the dynamic nature of...

A data-informed multidimensional composite score for stress assessment.

Occupations such as the military, emergency responders, and athletes demand acute physical, cognitive and psychosocial effort. Individuals in these ro...

Artificial intelligence readiness in Pakistan's medical and dental education: training-phase decline, a knowledge-practice paradox, and the role of digital determinants of health.

BACKGROUND: We assessed AI knowledge, attitudes, and use among medical and dental students in Pakistan, a lower-middle-income country (LMIC), and iden...

Mental health in early pregnancy: Interplay of objectively measured lifestyles, gut microbiota, and metabolomics.

Prenatal anxiety symptoms (AS) and depression symptoms (DS) in early pregnancy substantially impact maternal-infant health, but their pathophysiologic...

Using Machine Learning to Analyze the Predictors of Life Satisfaction: Focus on Lifestyle Attitudes and Psychological Factors.

OBJECTIVES: Life satisfaction is an essential indicator of quality of life, and enhancing it can contribute to individual well-being strategies. Becau...

Can Artificial Intelligence Chatbots Plan Therapeutic Ketogenic Diets for Children With Epilepsy?

RATIONALE: Ketogenic Diet Therapy (KDT) is an effective but complex treatment for paediatric drug-resistant epilepsy. Access to trained dietitians lim...

MALICoT: A pilot cross-sectional study analyzing the effects of power training and age on endomysium content and fiber area in the soleus muscle of adult males.

The cross-sectional Master Athletic Laboratory Study of Intramuscular Connective Tissue (MALICoT, DRKS00015764) examined effects of athletic exercise ...

Digital and technology-enabled approaches in dietary assessment: addressing bias, error, and feasibility in population- and community-based research.

Dietary intake data are essential for understanding diet-disease relationships, informing policy, and evaluating nutrition interventions. This is part...

Integration of network pharmacology, deep learning, and molecular biology reveals the efficacy of Citrus aurantium L. var. amara Engl. blossom extract in ameliorating diabetic osteoporosis.

ETHNOPHARMACOLOGICAL RELEVANCE: Diabetic osteoporosis (DOP) is a type of metabolic bone disease. Blossom of Citrus aurantium L. var. amara Engl. (CAVA...

Enhydrin from yacon attenuates atherosclerosis by modulating the FABP5/PPARγ/ABCA1 axis: An integrated multi-omics and in vivo validation.

Dysregulated lipid metabolism drives atherosclerosis (AS). Yacon, an Andean lipid-modulating tuber, exerts anti-AS potential, but mechanisms remain un...

Diet, Diarrhoea and Maternal Factors Associated With Wasting in Ghanaian Children Aged 6-23 Months: A Machine Learning Predictive Approach Using the 2022 Demographic and Health Survey.

OBJECTIVES: This study estimates the prevalence of wasting and examines associated factors among children aged 6-23 months in Ghana from a machine-lea...