Atherosclerosis

Construction and validation of a hypertensive nephropathy diagnostic model based on mitochondrial-related genes using machine learning combined with WGCNA.

BACKGROUND: Hypertensive nephropathy (HTN) arises from chronic hypertension and may potentially result in severe renal failure. Due to the absence of reliable and efficient biomarkers, the diagnosis of HTN is constrained. Mitochondrial-associated genes are closely associated with the pathogenesis of HTN. Our study aims to find new reliable diagnostic and therapeutic targets for HTN. METHODS: We ob...

Demonstrating the potential of untargeted hair proteomics for personalized biomarkers in stress-associated disorders.

Biomarker research in psychopathology increasingly employs high-dimensional Omics approaches. Yet, proteomics based on human hair remain largely unexplored, despite its potential to efficiently capture stable biological signals accumulated over weeks to months. This study leveraged machine learning to investigate the potential of the hair proteome-all detectable peptides and proteins-as a biomarke...

Anatomical, physiological and inflammatory characterization of nonculprit vessels in patients undergoing primary PCI for ST-elevation myocardial infarction in the presence of multivessel disease: Rationale and design of the PICNIC study.

BACKGROUND: Up to 50% of patients presenting with ST-elevation myocardial infarction (STEMI) have multivessel coronary artery disease (CAD). Randomize...

Identification of lymphangiogenesis-related diagnostic model for predicting abdominal aortic aneurysm onset and progression and validation of lymphopoiesis in abdominal aortic aneurysm.

This study aims to explore the lymphangiogenesis (LG)-related diagnostic markers of abdominal aortic aneurysm (AAA) through bioinformatics, as well as...

Enhanced prediction of breast cancer patient response to chemotherapy by integrating deconvolved expression patterns of immune, stromal and tumor cells.

The tumor microenvironment (TME) is a complex ecosystem of diverse cell types whose interactions govern tumor growth and clinical outcome. While multi...

Systematic post-translational modification genome wide identifies therapeutic targets for Alzheimer's disease: evidence from multi-cohort analysis.

BACKGROUND: The rapid increase in the incidence of Alzheimer's disease (AD) has raised concerns, given its profound effects on both society and the ec...

A Hybrid Model Combining U-Net and Transformers for Joint Segmentation and Beamforming of Plane-wave Ultrasound Images.

OBJECTIVE: Recent advancements in deep learning have shown significant potential in ultrasound imaging. However, most approaches focus solely on image...

AI-driven diagnosis of vulnerable intracranial atherosclerotic plaques using large language models and vision transformers: a multi-center study.

OBJECTIVES: High-resolution vessel wall imaging (HR-VWI) is essential for diagnosing vulnerable intracranial atherosclerotic plaques, but its interpre...

Multi-omics and machine learning framework reveals ABCG2 as a therapeutic target of Eleven Flavored Shenqi Tablets in clear cell renal cell carcinoma.

ETHNOPHARMACOLOGICAL RELEVANCE: Eleven Flavored Shenqi Tablets (EFST) is a classical multi-herbal prescription in traditional Chinese medicine, tradit...

International Consensuses and Guidelines on Diagnosing and Managing Coats Disease by the Academia Retina Internationalis (ARI), the Asia-Pacific Vitreo-retina Society (APVRS), and the Academy of the Asia-Pacific Professors of Ophthalmology (AAPPO).

PURPOSE: Coats disease is a rare, retinal vascular disorder characterized by telangiectasias, aneurysmal dilations, and progressive exudative retinal ...

Blood urea nitrogen-to-lipid ratios are novel indices inversely associated with anxiety: Insights from NHANES.

BACKGROUND: Anxiety is a highly prevalent mental disorder linked to metabolic and renal dysregulation. Blood urea nitrogen (BUN) and lipid profiles ha...

Age-specific modifiable determinants and nonlinear risk patterns of habitual low back pain in a large medical check-up cohort: a cross-sectional and longitudinal analysis.

BACKGROUND: Age-related mechanisms underlying habitual low-back pain (LBP) remain poorly defined, with most studies pooling heterogeneous populations ...

Artificial Intelligence-Based Algorithms Improve Care of Patients with AAA.

BACKGROUND: Timely detection and monitoring of abdominal aortic aneurysms (AAAs) are necessary to prevent ruptures and decrease mortality. Artificial ...

3D Convolutional Neural Network for Predicting Clinical Outcome from Coronary Computed Tomography Angiography in Patients with Suspected Coronary Artery Disease.

This study aims to develop and assess an optimized three-dimensional convolutional neural network model (3D CNN) for predicting major cardiac events f...

Uncovering the therapeutic potential of Si-Miao-Yong-An decoction in abdominal aortic aneurysm: An integrative study combining network pharmacology, machine learning, molecular docking and dynamics simulation.

Abdominal aortic aneurysm (AAA) is a progressive and life-threatening vascular disorder characterized by abnormal dilation of the abdominal aorta and ...

Development of an interpretable machine learning model to predict short-term bleeding risk in patients receiving dual antithrombotic therapy following cardiac surgery.

INTRODUCTION: Bleeding is a serious complication in cardiac surgery, especially among patients receiving combined anticoagulant and antiplatelet thera...

Artificial intelligence in age-related macular degeneration: Advancing diagnosis, prognosis, and treatment.

Age-related macular degeneration (AMD) is a leading cause of irreversible vision loss in older adults. While anti-vascular endothelial growth factor (...

Comparison of the Diagnostic Utility of Computed Tomography Angiography Head With and Without 3-Dimensional Volume-Rendered Images for Aneurysm Detection in Subarachnoid Hemorrhage Patients Versus Digital Subtraction Angiography.

BACKGROUND AND OBJECTIVES: Generating computed tomography (CT) angiography (CTA) 3-dimensional (3D) volume-rendered (3DVR) images can be time consumin...

Identification of key genes in intracranial aneurysm via WGCNA: insights into immune microenvironment and therapeutic targets.

BACKGROUND: Intracranial aneurysms (IA) are prevalent vascular lesions whose rupture causes subarachnoid hemorrhage with high disability and mortality...

Evaluation of deep learning models for anterior segment OCT image segmentation during scleral lens wear.

PURPOSE: The accurate segmentation of corneal and contact lens boundaries in anterior segment optical coherence tomography (AS-OCT) images provides es...