Metabolic Syndrome

Transcriptomic analysis identifies novel ferroptosis-related biomarkers and therapeutic targets in pulmonary arterial hypertension.

BACKGROUND: Ferroptosis plays a significant role in pulmonary arterial hypertension (PAH), although its underlying mechanisms and key pathogenic genes remain unclear. METHODS: Transcriptomic data from human PAH and control lung tissue were obtained from the Gene Expression Omnibus (GEO) database, whereas ferroptosis-related genes (FRGs) were sourced from the MsigDb and FerrDb databases. Differenti...

Combinations of single gene predictors with AI-driven polygenic precision therapies in cardiovascular diseases.

Pharmacogenomics (PGx) is transforming how we treat cardiovascular disease (CVD) by enabling us to select and dose drugs based on our genetic profiles. The pharmacokinetics and pharmacodynamics of commonly prescribed cardiovascular drugs are greatly affected by gene-drug interactions, which improve the therapeutic outcome and reduce adverse drug reactions. This narrative review will summarize evid...

Biomarker-driven diagnostics and personalized treatment in polycystic ovary syndrome.

Polycystic Ovary Syndrome (PCOS) is a common and clinically heterogeneous endocrine disorder affecting approximately 4-20% of women worldwide. Its com...

From DNA to Drug Discovery AI Models for Cardiovascular Precision Medicine.

Cardiovascular diseases remain the world's leading cause of death-yet the molecular mechanisms linking genetic variation to clinical outcomes are stil...

Development of a machine learning model using systemic and ophthalmic parameters to detect sleep-disordered breathing in glaucoma patients.

PURPOSE: To develop and validate a machine-learning model using systemic and ophthalmic parameters that predicts sleep-disordered breathing (SDB) in p...

Classification of glucose profile in Japanese patients with type 1 diabetes and its association with complications.

CONTEXT: The importance of utilizing continuous glucose monitoring (CGM) to optimize glycemic profiles and thereby prevent the onset of diabetic compl...

A quarter-century of progress: innovations in lipid medicine that transformed cardiovascular prevention.

This TimeCapsule reviews the major transformations in lipid metabolism and cardiovascular disease prevention during the first quarter of the 21st cent...

Smartwatch-derived exercise metrics as predictors of early hypertension: a prospective observational study.

BACKGROUND: Early identification of individuals at risk for hypertension is essential for effective cardiovascular disease. Physiological and activity...

Cross-population validation of the TyG-ABSI index as a novel predictor for chronic obstructive pulmonary disease: an integrated analysis using logistic regression and explainable machine learning.

BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) is increasingly recognized as a systemic inflammatory condition closely linked to metabolic d...

Can AI chatbots effectively respond inquiries for patients with Pulmonary Arterial Hypertension about exercise and physical activity: A comparative study of three chatbots.

OBJECTIVE: The utilization of artificial intelligence-based chatbots in the healthcare field is increasingly prevalent. Nonetheless, the quality of re...

Integrated multi-omics and experimental validation reveal CSK and FBLN1 as key targets of stanozolol in accelerating atherosclerosis.

BACKGROUND: Stanozolol, a synthetic anabolic androgenic steroid (AAS) widely abused to enhance performance, has poorly defined toxicological mechanism...

Predicting End-Stage Renal Disease and Mortality in Chronic Kidney Disease Using Machine Learning: Retrospective Cohort Study.

BACKGROUND: Chronic kidney disease (CKD) is a global health burden characterized by heterogeneous progression trajectories. Without timely and appropr...

An explainable machine learning method for identifying key atherogenic lipid biomarkers in abdominal obesity among the Southern Chinese population.

BACKGROUND: Abdominal obesity (AO) significantly contributes to cardiometabolic diseases and poses an increasing public health challenge. Composite li...

Diagnostic performance of machine learning models versus established risk stratification for intracranial aneurysm rupture: a systematic review and bivariate meta-analysis.

BACKGROUND: Machine learning (ML) models have been proposed to improve the discrimination of intracranial aneurysm rupture status beyond established c...

Artificial intelligence for right ventricular assessment: current evidence and future directions.

PURPOSE OF REVIEW: Right ventricular size and function are vital to risk stratification in pulmonary hypertension, valvular disease, and congenital he...

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...

Explainable machine-learning model for coronary artery disease diagnosis in non-AMI patients: integrating inflammatory and traditional risk factors.

OBJECTIVE: To develop and interpret an explainable machine learning (ML) model integrating inflammatory biomarkers and traditional risk factors for th...

Happiness and hypertension prevalence: A global analysis.

The prevalence of hypertension around the world is high while hypertension control is relatively low. The objective of this study is to investigate th...

Associations of serum per- and polyfluoroalkyl substances (PFAS) mixture with the risk of chronic diseases: evidence from single‑ , multi-pollutant, and machine learning models.

Per- and polyfluoroalkyl substances (PFAS) are persistent chemicals commonly found in consumer products. Despite growing concern over their health eff...

High-quality dietary patterns reduce risk of advanced cardiovascular-kidney-metabolic syndrome: A cross-sectional NHANES study in US adults.

Evidence-based dietary strategies for mitigating Cardiovascular-kidney-metabolic (CKM) syndrome progression remain limited; therefore, we hypothesized...