Atherosclerosis

Innovations In Artificial Intelligence-Guided Atherosclerosis Cardiovascular Imaging: From Detection to Prognosis.

High-density lipoprotein-related inflammatory ratios and coronary heart disease: A cross-sectional machine learning analysis of NHANES 2009 to 2020.

High-density lipoprotein (HDL)-related inflammatory ratios (monocyte-to-HDL cholesterol ratio [MHR], lymphocyte-to-HDL cholesterol ratio, neutrophil-to-HDL cholesterol ratio [NHR], platelet-to-HDL cholesterol ratio) represent composite biomarkers integrating lipid metabolism and inflammatory pathways. We developed machine learning models to evaluate their utility in coronary heart disease (CHD) cl...

AI-derived left-to-right cardiac chamber volume ratios in coronary artery calcium scans strongly predict heart failure.

AIMS: The AI-CVD initiative seeks to extract actionable insights from coronary artery calcium (CAC) scans beyond the traditional CAC score. We previou...

Beyond Percutaneous Coronary Intervention - Targeted Molecular Therapies for the Next Era of Coronary Care.

Coronary artery disease (CAD) remains the leading global cause of cardiovascular morbidity and mortality, driven by dysregulated lipid metabolism, chr...

Lessons learned from bat and rodent reservoir hosts of zoonotic viruses.

Zoonotic virus emergence is a continued threat to global health, though more than two-thirds originate in wildlife. Within natural reservoirs, bats an...

Immune gene MMP9 as a potential key mediator in TCDD exposure-associated atherosclerosis: An integrated study based on network toxicology and experimental validation.

BACKGROUND: 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is a highly toxic, recalcitrant persistent organic pollutant with ubiquitous environmental dist...

Perfusion-derived cerebral CT angiography with artificial intelligence iterative reconstruction as a replacement for routine cerebral CT angiography in acute ischemic stroke.

OBJECTIVES: To investigate the feasibility of replacing routine cerebral CT angiography (CTA) with CT perfusion (CTP)-derived cerebral CTA by using ar...

Cardiovascular outcomes and subclinical atherosclerosis in metabolic-associated steatotic liver disease: long-term follow-up from a specialized outpatient cohort.

BACKGROUND AND AIMS: Cardiovascular disease is the main cause of mortality in metabolic-associated steatotic liver disease (MASLD). This study evaluat...

Explainable machine learning for long-term cardiovascular disease risk prediction in Chinese middle-aged and older adults: a 9-year longitudinal cohort study with web-based risk calculator.

Cardiovascular disease represents the leading cause of mortality in China, accounting for over 40% of all deaths. Existing risk prediction models pred...

Tumor vessel phenotype in colorectal cancer microenvironment according to age at diagnosis.

BACKGROUND: Given the global issue of the rising incidence of early-onset colorectal cancer (CRC), we tested the hypothesis that tumor vasculature phe...

Interpretable machine learning analysis of routine blood biomarkers and derived indicators for predicting coronary heart disease in patients with carotid stenosis.

When Plaque Helps Us DECIDE.

Multi-omics integration reveals ANXA6-high γδ T cell-endothelial communication as a potential link between periodontitis and MASLD.

Periodontitis (PD) and metabolic dysfunction-associated steatotic liver disease (MASLD) were highly prevalent inflammatory disorders that frequently c...

Application of machine learning algorithms to predict and assess factors related to internal carotid siphon aneurysm occlusion treated with flow diversion.

Ameliorative effect of Rhus verniciflua Stokes on high-fat diet-induced obesity and advanced analysis with machine learning and deep learning-based network pharmacology.

AIMS: Obesity and metabolic dysfunction-associated steatotic liver disease (MASLD) arise from impaired redox and energy homeostasis, yet current thera...

A hybrid pipeline for carotid artery segmentation using YOLOv11n and contour models.

Carotid artery segmentation is critical for determining the degree of vascular disease, and for recommending treatment options. Early detection of car...

An interpretable machine learning model for early risk stratification of medium-to-giant coronary artery aneurysm in Kawasaki disease: development and external validation.

BACKGROUND: Medium-to-giant coronary artery aneurysm (MGCAA) represents the most severe complication of Kawasaki disease (KD) and remains difficult to...

Machine learning derived ORC6 as a hub biomarker for predicting tumor microenvironment, prognoses, and therapeutic responses in lung adenocarcinoma.

The origin recognition complex (ORC) is a DNA-binding complex composed of six subunits involved in DNA replication in cancer cells. The prognostic and...

Molecular mechanisms of exercise-induced improvements in Alzheimer's disease: a focus on lipid homeostasis.

Alzheimer's disease (AD) is the most prevalent type of dementia, and its pathophysiological mechanisms involve multiple factors, including genomic fac...

Mapping the subgingival HerBiome and HisBiome over the human healthspan.

BACKGROUND: Understanding the intricate relationship between sex, age, and the oral microbiome is crucial for deciphering the onset and progression of...