Metabolic Syndrome

Unraveling 'F' factor: towards a genetic-clinical framework for the musculoskeletal-heart crosstalk in metabolic aging.

BACKGROUND: The rising co-occurrence of cardiometabolic diseases and musculoskeletal degeneration poses a critical challenge to healthy aging, yet the shared biological mechanisms underlying this multimorbidity remain poorly defined. This study aimed to establish an integrative clinical-genetic framework to elucidate the common frailty factor, the 'F' factor, that captures the systemic vulnerabili...

Development and temporal external validation of a high-specificity XGBoost rule-in model for diabetes in middle-aged and older Korean adults.

Early identification of diabetes in older adults is essential for preventing complications, yet many high‑risk individuals remain undetected in community settings. Using recent cycles of the nationally representative Korea National Health and Nutrition Examination Survey (KNHANES 2020-2023), we developed and temporally validated an Extreme Gradient Boosting (XGBoost) model to rule-in diabetes amon...

Comorbidities for Predicting Progression Independent of Relapse Activity in Multiple Sclerosis Treated With B-Cell Depletion.

BACKGROUND: Progression independent of relapse activity (PIRA) has been shown to account for a majority of the disability accumulation in relapsing-re...

Artificial intelligence in cardio-kidney-metabolic care: Transforming integrated disease management through data-informed innovation.

Artificial intelligence (AI) is rapidly transforming the landscape of chronic medical conditions, such as cardio-kidney-metabolic (CKM) issues linked ...

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...

Triglyceride-Glucose-Waist-to-Weight Index: Novel Biomarker for Mild Cognitive Impairment in Older People With Sarcopenic Obesity.

BACKGROUND: Sarcopenic obesity (SO) is closely associated with mild cognitive impairment (MCI). However, traditional body composition-based diagnostic...

Literature Commentary June, 2026.

In this issue, the following 4 articles are reviewed by Drs. Mark L. Moster and Deborah I. Friedman, most of which include authors who are members of ...

Exploring the Lung-Liver Axis in Pulmonary Arterial Hypertension.

The liver's contribution to pulmonary arterial hypertension (PAH) pathogenesis remains unclear. We hypothesized that the liver promotes inflammatory i...

Deep learning-based CT-derived vertebral bone mineral density and metformin therapy: a longitudinal study in the Multi-Ethnic Study of Atherosclerosis.

OBJECTIVE: Evidence on metformin's skeletal effects remains conflicting. We emulated a target trial to evaluate associations between metformin therapy...

Prediction of low birth weight using machine learning-based analysis of environmental and maternal risk factors: insights from the Korean CHildren's ENvironmental health Study (Ko-CHENS).

Adverse birth outcomes such as low birth weight (LBW) increase the risk of metabolic disorders and hypertension later in life. Although previous studi...

Identification and multicenter validation of a 4-gene plasma signature for early recognition and risk assessment in hypertensive intracerebral hemorrhage.

Hypertensive intracerebral hemorrhage (ICH) is a devastating stroke subtype with high mortality and disability, yet reliable early risk biomarkers rem...

Explainable ensemble machine learning for predicting diabetes mellitus and identifying key risk factors: a population-based study in northern Bangladesh.

Diabetes mellitus (DM) is an escalating global public health concern, with a rapidly increasing burden in low- and middle-income countries, including ...

Gut microbial alterations and functional shifts in patients with hypertriglyceridemia: insights from a northwestern Chinese metagenomic study.

Although hypertriglyceridemia (HTG) is a significant contributor to lipid-associated pathologies such as atherosclerotic cardiovascular disease, its r...

Association between the development of sepsis and the BAR index in patients with acute pancreatitis: A retrospective investigation based on MIMIC-IV database.

Sepsis, as a severe complication of acute pancreatitis (AP), needs to be identified and treated as early as possible. The blood urea nitrogen-to-album...

Latent biochemical phenotypes delineate divergent health trajectories in older adults.

Ageing heterogeneity hampers prevention and care. We used routine biochemical panels and unsupervised learning to identify latent phenotypes in commun...

Cyclosporine in hematological disorders: mechanisms, clinical practice and emerging advances.

Cyclosporine A (CsA) functions as a calcineurin inhibitor that perturbs T cell activation via calcineurin-nuclear factor of activated T cells (CaN-NFA...

Capturing multi-disease states on a spectrum with machine learning and routine clinical data.

BACKGROUND: Diseases exist on spectra of risk factors, cellular perturbations, organ dysfunction, and clinical manifestations. It is unknown whether t...

Idiopathic Intracranial Hypertension Is Characterized by a Distinct Proteomic Profile.

OBJECTIVES: The pathophysiology of idiopathic intracranial hypertension (IIH) is poorly understood and disease-specific biomarkers are lacking. We aim...

RAS pathway activity subtypes identified by machine learning define prognostic and immune microenvironment characteristics in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD), the predominant histological subtype of non-small cell lung cancer, remains a leading cause of cancer-related ...

Machine learning-based prediction of hepatocellular carcinoma risk in steatotic liver disease: A nationwide cohort study.

BACKGROUND AND AIMS: Steatotic liver disease (SLD) has emerged as an important risk factor for hepatocellular carcinoma (HCC), often in the absence of...