Dyslipidemia

Association of cardiovascular-kidney-metabolic syndrome stages with MASLD prevalence and liver fibrosis severity: evidence from traditional and machine learning approaches.

INTRODUCTION: Cardiovascular-Kidney-Metabolic (CKM) syndrome reflects the convergence of cardiovascular, renal, and metabolic disorders. Metabolic dysfunction-associated steatotic liver disease (MASLD), as the hepatic phenotype of metabolic impairment, provides a critical link within this continuum. However, the association between CKM syndrome staging, MASLD prevalence, and liver fibrosis severit...

Automatic Detection of Subcellular-Scale Metabolic Dynamics via Spontaneous-Stimulated Raman Spatial Colocalization.

Cellular structural heterogeneity and low intrinsic contrast in label-free bright-field imaging hinder accurate localization of subcellular structures in nearly transparent specimens, thereby compromising both the precision and reproducibility of spontaneous Raman microscopy. Herein, we present a novel dual-modality, label-free three-dimensional (3D) automatic cell analysis platform that integrate...

Disease-specific crosstalk of Alistipes with lipoprotein profiles in overweight individuals at high cardiometabolic risk.

Metabolic syndrome (MS) and systemic lupus erythematosus (SLE) represent two pathophysiologically distinct chronic conditions associated with elevated...

Therapeutic potential of pharmacological components of Salvia miltiorrhiza against atherosclerosis: A preclinical systematic review and meta-analysis.

ETHNOPHARMACOLOGICAL RELEVANCE: Atherosclerosis (AS) severely threatens global health, while current therapies exhibit limitations. Recognized as a 's...

Diagnostic model and identification of IGFBP2 as an aging-related biomarker and therapeutic target for systemic sclerosis-associated interstitial lung disease through integrated bioinformatics and machine learning approaches.

BACKGROUND: Cellular senescence is a critical contributor to the pathogenesis of systemic sclerosis-associated interstitial lung disease (SSc-ILD). Ho...

Phenotypic clustering of cardiovascular risk profiles in systemic lupus erythematosus.

ObjectiveThis study aimed to identify distinct cardiovascular risk phenotypes in systemic lupus erythematosus (SLE) using an unsupervised cluster anal...

Data-driven subgroups for 3-year risk stratification of incident diabetes and complications in diabetes-free Chinese adults.

BACKGROUND: Substantial metabolic heterogeneity exists prior to the development of diabetes, creating opportunities for earlier and more precise inter...

A Cross-Sectional Study Based on Deep Learning to Explore the Effect of Triglyceride/Glucose Index on Periodontitis: An Analysis Based on the Large NHANES Database.

PURPOSE: Periodontitis is a common chronic inflammatory disease closely associated with metabolic syndrome. The triglyceride-glucose (TyG) index is a ...

Bioinformatics approach to identifying molecular targets of Danlou tablet against atherosclerosis: a machine learning pharmacology study.

This research aims to identify novel molecular targets and generate mechanistic hypotheses for Danlou Tablet (DLT) in the treatment of atherosclerosis...

Modularly-Assembled Smart Microneedle Platform for Machine Learning-Driven Personalized Health Monitoring.

Given the inherent complexity of metabolic pathways and disease-associated agents, next-generation healthcare necessitates wearable, non-invasive, and...

Cardiovascular Risk Assessment Tools in Chronic Kidney Disease.

Cardiovascular (CV) risk calculators estimate the likelihood of CV events by integrating factors such as age, sex, blood pressure, lipids, smoking, an...

Early Prediction of Adverse Stroke Outcomes using Non-clinical Factors and Missing Data: A Machine Learning Study.

Introduction Early prediction of stroke outcomes using prognostic tools may help clinical decision making and inform resource allocation. However, cli...

Effects of Lactiplantibacillus plantarum on moderate dyslipidemia before medication involving gut microbiota and host genetics.

In this 12-week trial, 136 participants with moderately dyslipidemia were randomly assigned to receive Lactiplantibacillus plantarum (LP) or placebo. ...

Unraveling key genes and mitochondrial-related mechanisms of atherosclerosis severity: explorations based on interpretable machine learning.

ANXA2, DBN1, ZNF385D, and IL6ST: Endothelial cell biomarkers linking atherosclerosis progression to immune microenvironment dysregulation.

BACKGROUND: Atherosclerosis (AS) is a complex cardiovascular disorder driven by endothelial cell dysfunction and immune microenvironment dysregulation...

Physics-informed graph neural networks for flow field estimation in carotid arteries.

Hemodynamic quantities are valuable biomedical risk factors for cardiovascular pathology such as atherosclerosis. Non-invasive, in-vivo measurement of...

Factors Associated with Machine Learning-Based Predictions of Retinal Aging Using Teleretinal Screening Images from Patients with Diabetes.

PURPOSE: To identify factors associated with accelerated retinal aging based on machine learning predictions of age using fundus images from teleretin...

Development and validation of a computed tomography myocardial perfusion imaging radiomic model for major adverse cardiovascular events prediction: a multicenter study.

AIMS: Accurate prediction of major adverse cardiovascular events (MACE) is crucial for risk stratification in patients with suspected coronary artery ...

Synergistic DBNDD1-GDF15 Signaling Activates the NF-κB Pathway to Promote Colorectal Cancer Progression.

UNLABELLED: Colorectal cancer is a highly lethal gastrointestinal tract malignancy whose pathogenesis and molecular drivers are not fully understood. ...

Development of an explainable machine learning model for predicting depression in adults with type 2 diabetes mellitus: A cross-sectional SHAP-based analysis of NHANES 2009-2023.

Depression (DEP) is a common yet underdiagnosed comorbidity in adults with type 2 diabetes mellitus (T2DM), worsening glycemic control and increasing ...