Atherosclerosis

An allostatic load domain-specific metabolic profile in young adults: The African-PREDICT study.

Allostatic load scores (ALSs) quantify the cumulative physiological burden of sustained stress across neuro-endocrine, metabolic, cardiovascular and inflammatory domains; however ALS is heterogeneous in nature. Using domain-specific urinary metabolomic signatures may improve evaluation accuracy, provide an innovative alternative to stress characterization, identify early domain-specific perturbati...

Towards improved decision making of unruptured intracranial aneurysms using automated segmentation from MRA-TOF with iterative pseudo labeling.

OBJECTIVE: To enable accurate 3D morphological assessment and support clinical decision making, DIVA-seg: a Deep learning-based method for Intracranial Vessel and Aneurysm segmentation from MRA-TOF using a pseudo labeling approach was developed and validated. METHODS: Three MRA-TOF datasets were used: 1) labeled data for training (n=57) and testing (n=14), 2) unlabeled data for pseudo labels (n=51...

Association of cardiovascular-kidney-metabolic syndrome stages with MASLD prevalence and liver fibrosis severity: evidence from traditional and machine learning approaches.

INTRODUCTION: Cardiovascular-Kidney-Metabolic (CKM) syndrome reflects the convergence of cardiovascular, renal, and metabolic disorders. Metabolic dys...

Identification and experimental confirmation of TBC1D10C as a shared transcriptional link between abdominal aortic aneurysm and major depressive disorder.

BACKGROUND: Abdominal aortic aneurysm (AAA) and major depressive disorder (MDD) are prevalent conditions with substantial global health burdens. Growi...

Explainable ML for ACS culprit plaques: a multidimensional CCTA model highlighting hemodynamic increment.

To develop an interpretable, multi-parameter machine learning (ML) model that integrates plaque morphology, composition, perivascular inflammation, an...

Automatic Detection of Subcellular-Scale Metabolic Dynamics via Spontaneous-Stimulated Raman Spatial Colocalization.

Cellular structural heterogeneity and low intrinsic contrast in label-free bright-field imaging hinder accurate localization of subcellular structures...

Identification of VEGFB associated with NKT cells in diabetic foot ulcers: Single-cell analysis and machine learning.

The management options for diabetic foot are restricted, and the outlook is unfavorable. Immune cells have been implicated in diabetic foot ulcer (DFU...

Disease-specific crosstalk of Alistipes with lipoprotein profiles in overweight individuals at high cardiometabolic risk.

Metabolic syndrome (MS) and systemic lupus erythematosus (SLE) represent two pathophysiologically distinct chronic conditions associated with elevated...

Therapeutic potential of pharmacological components of Salvia miltiorrhiza against atherosclerosis: A preclinical systematic review and meta-analysis.

ETHNOPHARMACOLOGICAL RELEVANCE: Atherosclerosis (AS) severely threatens global health, while current therapies exhibit limitations. Recognized as a 's...

Predicting Persistent Renal Failure Necessitating Dialysis in Patients Undergoing Elective, Open Thoracoabdominal Aortic Aneurysm Repair.

BACKGROUND: Acute renal failure remains a significant complication after open thoracoabdominal aortic aneurysm (TAAA) repair and is associated with hi...

A simplified co-culture reveals altered cardiotoxic responses to doxorubicin in hPSC-derived cardiomyocytes in the presence of endothelial cells.

Cardiotoxicity is a significant challenge in cancer therapies, particularly with doxorubicin, a widely used anthracycline. More predictive in vitro mo...

Explainable machine learning model based on clinical and radiological features for predicting hematoma expansion or rebleeding after decompressive craniectomy in traumatic brain injury: a bicentric cohort study.

BACKGROUND: Hematoma expansion or rebleeding after decompressive craniectomy (DC) is a critical determinant of poor prognosis in traumatic brain injur...

Volume electron microscopy reveals heterogeneity of the hemostatic response in veins and arteries.

Intravital imaging studies have provided insights into the spatial and temporal variations of platelet activation and thrombin generation that occur d...

Synthetic, Population-Based Virtual Patient Database Using a Digital Twin of the Cardiovascular System.

PURPOSE: The goal is to develop a cardiovascular virtual patient database (VPD) combining physiological and demographic data to provide the foundation...

Predicting risk of ascending thoracic aortic aneurysm in asymptomatic adults using machine learning.

Most patients with ascending thoracic aortic aneurysms (ATAA) remain asymptomatic until they develop fatal complications, including aortic dissection ...

Phenotypic clustering of cardiovascular risk profiles in systemic lupus erythematosus.

ObjectiveThis study aimed to identify distinct cardiovascular risk phenotypes in systemic lupus erythematosus (SLE) using an unsupervised cluster anal...

Data-driven subgroups for 3-year risk stratification of incident diabetes and complications in diabetes-free Chinese adults.

BACKGROUND: Substantial metabolic heterogeneity exists prior to the development of diabetes, creating opportunities for earlier and more precise inter...

Radiomic features and carotid stenosis in periodontitis a two stage bootstrap and multimodal machine learning study.

Bioinformatics approach to identifying molecular targets of Danlou tablet against atherosclerosis: a machine learning pharmacology study.

This research aims to identify novel molecular targets and generate mechanistic hypotheses for Danlou Tablet (DLT) in the treatment of atherosclerosis...

Artificial intelligence-powered automatic coronary computed tomography angiography plaque quantification: comparison against optical coherence tomography.

AIMS: Coronary computed tomography angiography (CCTA) enables a non-invasive, comprehensive assessment of coronary artery disease, and artificial inte...