Atherosclerosis

Integrative machine learning reveals interplay between epithelial and endothelial cells elevates mixed heavy metal-related colorectal cancer risk.

Heavy metal contamination has become an emerging global health concern, yet the promoting effects of mixed heavy metal exposure on colorectal cancer risk remains poorly understood. In this study, plasma concentrations of 25 heavy metals were obtained from an in-house elemental database comprising both colorectal cancer patients and healthy controls, and exposure concentrations were then defined ba...

Bridging discovery and clinical science: A framework for advancing atherosclerosis research using innovative models.

Atherosclerotic cardiovascular disease (ASCVD) is a leading cause of death, with substantial residual risk persisting despite current lipid-lowering, antithrombotic, antihypertensive, weight-management, and anti-inflammatory therapies. This unmet clinical need reflects the multifactorial and heterogeneous nature of ASCVD, which is not fully captured by traditional discovery approaches. Recent adva...

Integrative multi-omics and machine learning reveal glycolysis-related biomarkers driving vascular remodeling in pulmonary arterial hypertension.

Metabolic reprogramming toward aerobic glycolysis, a phenomenon analogous to the Warburg effect, is increasingly recognized as a hallmark of pulmonary...

Optimizing heart failure care: A machine learning-based prediction of hospital length of stay for heart failure patients.

BACKGROUND: Heart failure represents a significant global health burden, with prolonged length of stay (LoS) tied to increased mortality and costs. Ac...

The role of nitrogen dioxide in the prevalence of adverse cardiovascular and cerebrovascular diseases in China: a national multi-pollutant geospatial analysis.

INTRODUCTION: Cardiovascular and cerebrovascular diseases (CCVDs) pose a severe global health threat, particularly among middle-aged and elderly popul...

Attitudes toward artificial intelligence tools in university students: associations with body appreciation and e-healthy diet literacy - implications for digital health education.

BACKGROUND: This cross-sectional study aimed to determine attitudes toward the use of artificial intelligence tools, body appreciation, and e-healthy ...

Machine learning identifies a NETs-related four-gene diagnostic signature for abdominal aortic aneurysm.

Abdominal aortic aneurysm (AAA) is a chronic degenerative disease characterized by localized aortic dilation and persistent inflammation. While neutro...

Biomarker-Guided Strategies for Tumor Vasculature: From Imaging Advances to Novel Therapeutic Interventions.

The tumor vasculature is a dynamic and heterogeneous component of the tumor microenvironment (TME) that influences tumor progression, immune infiltrat...

Disorganization of inner retinal layers and disruption of outer retinal layers as predictors of anti-vascular endothelial growth factor treatment outcomes in diabetic macular edema: A scoping review.

We systematically map the evidence on optical coherence tomography (OCT) biomarkers-mainly disorganization of the retinal inner layers (DRIL), disrupt...

Uric Acid to HDL-C Ratio as a Novel Biomarker for Sarcopenia: A National Study with Machine Learning Insights.

BACKGROUND: Sarcopenia is a major age-related health burden. Although the uric acid to high-density lipoprotein cholesterol ratio (UHR) has been linke...

Predicting intracranial angioplasty failure using vessel wall MRI habitat radiomics and deep learning: a multicenter study.

BACKGROUND: Primary balloon angioplasty (PBA) is a promising strategy for symptomatic intracranial atherosclerotic stenosis but carries the risk of pr...

Machine Learning for Cardiovascular Prevention Prescriptions: Real-World vs. Synthetic Data.

Cardiovascular diseases remain the leading cause of death worldwide, primarily driven by atherosclerosis, which is targeted by lipid-lowering agents s...

Identifying Clinical Predictors of Diabetes and Prediabetes: An Explainable AI Approach Using Primary Care Electronic Medical Records.

Prediabetes (PD), a reversible metabolic condition that precedes type 2 diabetes (T2DM), carries a high risk of progression to T2DM, but can be effect...

Upregulation of the Mitophagy-Related Gene EXOSC4 Is Associated with Immune Dysregulation in Spinal Cord Injury.

Spinal cord injury (SCI) profoundly impairs patients' quality of life and imposes a substantial economic burden on society, often resulting in irrever...

Temporal In Vitro Models of Skin Wound Healing Components: A Cell-Specific Framework for Acute and Chronic Repair Mechanisms.

SIGNIFICANCE: Wound healing is as much about opportunity (Gk. Karios) and sequence (Gk. Chronos). The sequential healing responses involve concerted r...

NATURal history of coronary PlaquE on cardiac computed tomography in individuals without MACE or lipid-lowering therapy: NATURE-CTstudy.

BACKGROUND: Coronary artery disease (CAD) progression has been examined mainly in cohorts enriched for major adverse cardiovascular events (MACE), a h...

Immune Checkpoint Inhibitor-Associated Cardiovascular Toxicity: Mechanisms, Clinical Manifestations, and Clinical Impact.

Immune checkpoint inhibitors (ICIs) represent a class of novel anticancer agents that enhance T cell-mediated recognition and elimination of tumor cel...

Machine learning reveals microbiome differences by periodontitis severity.

Periodontitis is a chronic inflammatory disease driven by microbial dysbiosis, yet the microbial signatures associated with severity remain incomplete...

Cascade-amplified 2D ultrathin hexagonal Cu-doped LDO nanozyme for multiplexed wearable monitoring of sweat metabolites.

Sweat-based metabolic monitoring offers a non-invasive alternative to blood tests, but its clinical utility is limited by the limited catalytic effici...

Deep Learning-Based Automated Coronary Plaque Quantification with Ultra-high Resolution Photon-Counting Detector CT at Different Spatial Resolutions.

RATIONALE AND OBJECTIVES: To evaluate the impact of varying spatial resolutions on image quality, and deep-learning (DL) based quantification of coron...