Atherosclerosis

Screening and classification of anti-angiogenic VEGFR2 inhibitors with supervised machine learning, deep learning and molecular docking and molecular dynamics simulation.

Vascular Endothelial Growth Factor Receptor 2 (VEGFR2) is a critical therapeutic target in cancer due to its role in pathological angiogenesis and tumor progression. Despite available FDA-approved VEGFR2 tyrosine kinase inhibitors (TKIs), challenges like resistance, off-target toxicities, and low discovery success rates persist, necessitating more efficient and scalable approaches to identify nove...

Multimorbidity and major adverse cardiovascular events in antipsychotic users: Time-to-event prediction by explainable machine learning.

Antipsychotic treatment is associated with higher risk of major adverse cardiovascular events (MACEs), and risk may vary by multimorbidity and concomitant medications. Using Hong Kong electronic health records, we followed 26,274 MACE-free adults (18-65 years) with multimorbidity who initiated antipsychotics, capturing demographics, chronic conditions, and prior medication use. We applied a condit...

Generation of virtual abdominal aortic aneurysm shape evolution using a physics-based G&R model and its applications to aneurysm growth prediction.

The computational growth and remodeling (G&R) of aortic aneurysms has been extensively investigated to better understand vascular disease progression ...

CRISPR-Cas9 and next-generation gene editing strategies for therapeutic intervention of neurodegenerative pathways in Alzheimer's disease: a state-of-the-art review.

Alzheimer's disease (AD) is a progressive and multifactorial neurodegenerative disorder and the leading cause of dementia worldwide, characterized by ...

A deep learning approach to assess transendothelial cell trafficking performance.

Transendothelial migration (TEM), is a complex, multistep process impacted by diseases like autoimmune disorders and cancer. Deciphering aspects of th...

An explainable online frailty prediction model for community-dwelling older adults based on machine learning algorithms: a cross-sectional study based on retrospective health data.

BACKGROUND: Frailty is a significant health concern associated with diminished physiological reserves and increased healthcare burdens. Currently, eff...

EHR-derived cognitive load is associated with guideline-concordant statin initiation in primary care.

INTRODUCTION: Linking electronic health record (EHR) use to care quality may offer insights into potential interventions improving guideline adherence...

Exploratory prediction model for deep vein thrombosis in intensive care patients after anticoagulation therapy: An observational study.

BACKGROUND: Despite low-molecular-weight heparin (LMWH) prophylaxis, the incidence of deep vein thrombosis (DVT) remains high in intensive care unit (...

Retinal vascular phenotyping for early detection of coronary artery disease: quantitative assessment and diagnostic modelling.

OBJECTIVES: To investigate the association between quantitative retinal vascular parameters and coronary artery disease (CAD) and to evaluate the effi...

[Application of artificial intelligence to pharmacological and interventional treatment].

As in many other fields, artificial intelligence (AI) is transforming daily activities in cardiology. In pharmacological therapy, algorithms have been...

Single-Cell Transcriptomic Analysis of Chemotherapy-Induced Changes in Osteosarcoma With a Pyroptosis-Related Gene-Based Prognostic Model.

Osteosarcoma, the most common primary malignant bone tumour, presents significant treatment challenges due to its complex tumour microenvironment and ...

Identification of potential biomarkers for Polygonum multiflorum-induced liver injury in a clinical cohort: integrating machine learning of metabolomics with transcriptomic profiling.

ETHNOPHARMACOLOGICAL RELEVANCE: Polygonum multiflorum Thunb. (PM), synonymous with Reynoutria multiflora (Thunb.) Moldenke is known as He Shou Wu in t...

Recent advances in corneal specular microscopy image analysis through artificial intelligence.

Although conventional automated analysis of corneal specular microscopy images has historically been limited by reproducibility challenges in the pres...

Machine Learning-driven Prioritisation of Lipoprotein(a) Testing: Model Development and Validation.

AIMS: Elevated lipoprotein(a) [Lp(a)] is a common risk factor for cardiovascular disease (CVD) affecting ∼1.4 billion people globally, with novel trea...

Radiomics-Based Classification of Pathological Patterns in Common Carotid Artery Wall.

OBJECTIVES: Abnormal echogenic patterns such as the triple signal pattern can be identified in the common carotid artery (CCA) using ultrasound. These...

Using machine learning algorithms to predict MACE in peritoneal dialysis patients.

The study aimed to predict the risks of Major adverse cardiac events (MACE) in patients undergoing peritoneal dialysis (PD) with machine learning (ML)...

A Segatella Copri-centered Gut Microbiota-mediated Metabolic Dysregulation Associated with Transition from Asymptomatic to Symptomatic Intracranial Atherosclerosis.

The mechanisms underlying the continuum from asymptomatic intracranial atherosclerotic stenosis (aICAS) to symptomatic intracranial large-artery ather...

Endothelial cells recruit pro-inflammatory macrophage clusters via app-Cd74 exacerbating ICI-associated myocarditis.

Immune checkpoint inhibitor-related myocarditis (ICI-myocarditis) is a rare but highly threatening adverse reaction, and its pathogenesis is still unc...

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-t...