Atherosclerosis

Fcer1g and St3gal1: Macrophage-associated angiogenesis biomarkers and therapeutic targets in sepsis-induced acute lung injury.

BACKGROUND: Acute lung injury (ALI) involves the release of growth factors and inflammatory mediators from damaged pulmonary tissues, fostering endothelial cell proliferation, migration, and vascular lumen formation, thereby driving pathological angiogenesis. Macrophages contribute to angiogenesis and vascular homeostasis, but their dysregulation in pathological states worsens vascular dysfunction...

Enhancing the efficacy of Salvia miltiorrhiza and Ligusticum chuanxiong in the treatment of coronary heart disease: The value of poorly soluble components and nanocrystal self-stabilized solid emulsions.

BACKGROUND: The Salvia miltiorrhiza-Ligusticum chuanxiong herb pair is a classic combination in traditional Chinese medicine (TCM) formulation for coronary heart disease (CHD). However, currently marketed preparations primarily retain water-soluble components, while poorly water-soluble yet pharmacologically critical constituents (e.g., tanshinones, Ligusticum chuanxiong oil) are either excluded o...

Designing a machine learning model for predicting cardiovascular events using the triglyceride-glucose index: a cohort study.

INTRODUCTION: Cardiovascular diseases (CVD) are the leading cause of death in developing countries, imposing a significant burden on society. Early de...

Machine learning analysis of s-EASIX for predicting 30-day mortality in sepsis patients from MIMIC-IV.

Endothelial dysfunction is an important risk factor for the progression of sepsis. The simplified endothelial activation and stress index (s-EASIX) se...

Mothers against decapentaplegic homolog 4 as a proteomic hub in vascular remodeling and residual cardiovascular risk.

Translational cardiovascular medicine increasingly relies on systems-level approaches to uncover therapeutic targets that bridge molecular mechanisms ...

Vascularisation in 3D bioprinted models: emerging solutions engineering functional tissues and tumour models.

Three-dimensional (3D) bioprinting enables the fabrication of tissues with controlled architecture and cell composition, yet the formation of mature a...

Integrative network toxicology and molecular docking preliminarily explore the potential role of polystyrene microplastics in childhood obesity.

Childhood obesity is a severe global epidemic, and emerging evidence suggests environmental pollutants like polystyrene microplastics (PS-MPs) may dis...

Predicting Plaque Vulnerability Using Machine Learning-Enabled Nanoagents Sensitized Molecular High-Resolution Magnetic Resonance Imaging Data.

Molecular imaging based on paramagnetic nanoagents has emerged as an intriguing strategy to sensitize the local magnetic properties of pivotal patholo...

Environmental PET-microplastic exposure and risk of non-alcoholic fatty liver disease: An integrated computational toxicology and multi-omics study.

The escalating severity of global microplastic pollution has triggered significant public health concerns. Polyethylene terephthalate (PET), a ubiquit...

Automatic segmentation of coronary plaques in coronary CT angiography using neural networks.

Rapid and accurate detection of coronary plaques on CCTA is critical for timely CAD diagnosis but is limited by reader workload and interobserver vari...

Correlation between the high-density lipoprotein-to-low-density lipoprotein ratio and contrast-induced acute kidney injury: an analysis based on the in-hospital AKI electronic monitoring system.

BACKGROUND: Contrast-induced acute kidney injury (CI-AKI) is a common and serious complication that can occur following angiography procedures. Consid...

A machine learning model based on routine blood-derived indices for early arterial stiffness prediction in the community.

BACKGROUND: Increased arterial stiffness is a high-risk factor for cardiovascular diseases, making its early identification crucial. Based on data fro...

Environmental toxicant exposure and diabetes risk: An exposome-wide association study integrating mixture effects and molecular mechanisms.

Environmental toxicant exposure has emerged as a potential contributor to diabetes, yet systematic investigations integrating multiple chemicals and b...

Advancing Coronary Risk Assessment Through Combined Radiomic, Mechanical, and Hemodynamic Analysis.

PURPOSE: Detecting vulnerable coronary plaques through coronary computed tomography angiography (CCTA) is a crucial, yet challenging task. To date, mo...

Prolonging Sample Stability with Machine Learning Expands the Catalog of Tests Available for Mail-In Capillary Blood Collected At-Home.

Self-collection of biospecimens at-home, without specialized equipment or training, are increasingly being adopted in clinical practice due to conveni...

Comment on: "Assessing AI-generated patient leaflets on descemet membrane endothelial keratoplasty".

Association of allostatic load index with cognitive impairment in high-risk stroke populations.

BACKGROUND: Chronic psychosocial stress induces cumulative physiological dysregulation that accelerates biological aging and contributes to the develo...

Comparative machine learning models for early prediction of preterm birth from maternal serum biomarkers.

BACKGROUND: Preterm birth (PTB) is a major cause of neonatal morbidity and mortality. Inflammation and metabolic disruption are involved in its pathol...

Cerebrovascular 5D flow MRI.

BACKGROUND: 4D flow MRI facilitates quantification of cardiac phase-resolved blood velocity vector fields and has successfully been deployed to study ...

Features of B-mode ultrasound and contrast-enhanced ultrasound of carotid plaque based on deep learning enhance the prediction of vulnerable plaques associated with acute ischemic stroke.

OBJECTIVES: To develop an AI model using ultrasound features of carotid plaque for predicting the risk of acute ischemic stroke (AIS) and assess its e...