Dyslipidemia

Identification of diagnostic biomarkers and dissecting immune microenvironment with crosstalk genes in the POAG and COVID-19 nexus.

An underlying association between primary open-angle glaucoma (POAG) and COVID-19 has been hypothesized, but the causal link and shared mechanisms remain unclear. This study integrates epidemiological and bioinformatics approaches to investigate their relationship, aiming to identify common molecular pathways and validate clinical correlations. Epidemiological data from 3,015 participants in the C...

Modelling key ecological factors influencing the distribution and content of silymarin antioxidant in Silybum marianum L.

The increasing demand for natural medicine has increased the significance of Silybum marianum as a valuable medicinal plant. It is used to restore liver cells; reduce blood cholesterol; prevent prostate, skin, and breast cancer; and protect cervical cells and kidneys. To identify ecological factors affecting the distribution and amount of silymarin in S. marianum three machine learning algorithms ...

Quantitative CT Imaging in Chronic Obstructive Pulmonary Disease.

Chronic obstructive pulmonary disease (COPD) is a highly heterogeneous condition characterized by diverse pulmonary and extrapulmonary manifestations....

Predicting carotid atherosclerosis in latent autoimmune diabetes in adult patients using machine learning models: a retrospective study.

BACKGROUND: Latent autoimmune diabetes in adults (LADA) is a slowly progressing form of diabetes with autoimmune origins. Patients with LADA are at an...

Network-based machine learning reveals cardiometabolic multimorbidity patterns and modifiable lifestyle factors: a community-focused analysis of NHANES 2015-2018.

Cardiometabolic Multimorbidity (CMM) has emerged as one of the primary threats to human health globally due to its high incidence, disability, and mor...

The value of triglyceride-glucose index-related indices in evaluating migraine: perspectives from multi-centre cross-sectional studies and machine learning models.

BACKGROUND: This study employed representative data from the U.S. and China to delve into the correlation among migraine prevalence, the triglyceride‒...

From lipids and inflammation to artificial intelligence-driven therapeutics: the 93rd European atherosclerosis society (EAS) congress 2025 in focus.

Gene therapy and genome editing for lipoprotein disorders.

Genetic factors play a critical role in the development of lipoprotein disorders, which significantly contribute to atherosclerotic cardiovascular dis...

Identification of pyroptosis related genes and subtypes in atherosclerosis using multiomic and single cell analysis.

Atherosclerosis (AS), the leading cause of cardiovascular diseases, is a chronic inflammatory disorder involving lipid metabolism, immune dysregulatio...

Screening biomarkers related to cholesterol metabolism in osteoarthritis based on transcriptomics.

Cholesterol metabolism-related genes (CMRGs) have been associated with osteoarthritis (OA), but their specific regulatory mechanisms remain unclear. T...

A machine learning-based framework for predicting metabolic syndrome using serum liver function tests and high-sensitivity C-reactive protein.

Metabolic Syndrome (MetS) comprises a clustering of conditions that significantly increase the risk of heart disease, stroke, and diabetes. Timely det...

Artificial intelligence in coronary CT angiography: transforming the diagnosis and risk stratification of atherosclerosis.

Coronary CT Angiography (CCTA) is essential for assessing atherosclerosis and coronary artery disease, aiding in early detection, risk prediction, and...

A hybrid approach to heart disease prediction using a fractional-order mathematical model and machine learning algorithm.

Heart disease remains one of the leading causes of morbidity and mortality worldwide, necessitating the development of more accurate and efficient dia...

Lipidomic profiling of human adiposomes identifies specific lipid shifts linked to obesity and cardiometabolic risk.

BACKGROUNDObesity, a growing health concern, often leads to metabolic disturbances, systemic inflammation, and vascular dysfunction. Emerging evidence...

Delving into Generalizable Label Distribution Learning.

Owing to the excellent capability in dealing with label ambiguity, Label Distribution Learning (LDL), as an emerging machine learning paradigm, has re...

Association Between Automated Coronary Artery Calcium From Routine Chest Computed Tomography Scans and Cardiovascular Risk in Patients With Colorectal or Gastric Cancer.

BACKGROUND: As cardiovascular disease (CVD) is the leading cause of noncancer mortality in colorectal or gastric cancer patients, it is essential to i...

Coarse Grain Preference, Gut Microbiota Features, in Relation to Hypertriglyceridemia in Constipation Patients: A Cross-Sectional Study.

Coarse grain (CG) benefits blood lipids involving gut microbiota regulations. Little is known about the relation between CG preference and blood lipid...

Can we identify individuals at risk to develop multiple myeloma? A machine learning-based predictive model.

Multiple myeloma evolves unnoticed over years, and when diagnosed, organ damage is common. Electronic health records (EHR) can help in developing pred...

The utility of an artificial intelligence model based on decision tree and evolution algorithm to evaluate steatotic liver disease in a primary care setting.

Many ways of classifying steatotic liver disease (SLD) with metabolic conditions have been proposed. Thus, SLD-related variables were verified using a...

Type 2 Diabetes Mellitus Remission, Dream or Reality? A Narrative Review of Current Evidence and Integrated Care Strategies.

Type 2 diabetes mellitus (T2DM) is a global health priority, with an estimated 629 million people projected to be affected by the year 2045. T2DM sign...