Atherosclerosis

Guiding Preventive Care Strategies for Patients With Atherosclerotic Plaque on Coronary CTA: Primary Outcomes of the DECIDE Registry.

BACKGROUND: Artificial intelligence-enabled coronary plaque analysis (AI-CPA) has been shown to improve cardiovascular risk prediction. However, little is known about how these measures influence management. OBJECTIVES: This study sought to define changes in management guided by AI-CPA as compared with management guided by measures of nonobstructive and obstructive stenosis on coronary computed to...

DeepStackVEGF a stacking ensemble deep learning framework for vascular endothelial growth factor prediction.

Vascular Endothelial Growth Factor (VEGF) plays a central role in angiogenesis, regulating both physiological processes such as wound healing, tissue repair, and bone formation, and pathological events including tumor progression, metastasis, and diabetic retinopathy. Due to its crucial role in vascular biology, VEGF serves as an important therapeutic target in anti-angiogenic drug development and...

Investigation of Fatty Acid Metabolism-Associated Molecular CPOX and the Underlying Mechanism in Follicular Lymphoma.

Dysregulated lipid metabolism is a key driver of follicular lymphoma (FL). This study aimed to explore the lipid metabolism-related genes (LMRGs) and ...

Endothelial SMAD1-MCAM axis facilitates sunitinib resistance and progression of clear cell renal cell carcinoma via LAMB1-ITGB1 signaling.

Clear cell renal cell carcinoma (ccRCC) is characterized by high metastatic potential and frequent resistance to conventional therapies, highlighting ...

Comparison of conventional formulas and machine learning models for estimating serum low-density lipoprotein cholesterol.

BACKGROUND: Accurate estimation of low-density lipoprotein cholesterol (LDL-C) is essential for cardiovascular risk assessment and monitoring. Because...

Enhanced Transcytosis and Retention (ETR) of Drug Delivery Nanocarrier in Solid Tumors.

ConspectusTranscytosis, traditionally regarded as biological, constitutes an intrinsic and powerful pathway for macromolecule transport across endothe...

[Plasma proteomics in age-related macular degeneration].

BACKGROUND: Neovascular age-related macular degeneration (nAMD) shows a heterogeneous treatment response to anti-vascular endothelial growth factor (V...

Comprehensive Analysis of Bulk RNA-seq, Machine Learning, Mendelian Randomization, and Single-Cell Sequencing Unravels SLC22A3 as a Solute Carrier Superfamily-Associated Biomarker in Atherosclerosis.

Growing evidence implicates solute carrier (SLC) superfamily in atherosclerosis (AS) pathogenesis. This study identified SLC22A3 as a novel AS biomark...

Clinical and pathologic correlations of machine learning quantification of Aβ deposits across 3 brain regions of decedents with Alzheimer disease.

Machine learning enables scalable quantification of neuropathology, offering deeper phenotyping of Alzheimer's disease (AD). In this validation study,...

Unveiling Endotypes in Systemic Lupus Erythematosus Through Multi-Omic Analysis: Insights into Cardiovascular and Renal Complications.

BACKGROUND: Systemic lupus erythematosus (SLE) shows clinical and molecular heterogeneity, and cardiovascular (CV) complications and lupus nephritis (...

CKAN-ATHP: a predictor for antihypertensive peptides based on sample augmentation and loss improvement strategies using the convolutional Kolmogorov-Arnold network.

Antihypertensive peptides (AHTPs) are short-chain peptides derived from food or bioproteins through enzymatic hydrolysis, fermentation, or chemical sy...

Characterization of biomarker profiles in patients with coronary artery disease: A prospective coronary computed tomography angiography study.

BACKGROUND AND AIMS: Conventional biomarkers such as low-density lipoprotein (LDL) and high-density lipoprotein may fail to identify patients' risk fo...

Geometry-aware PointNet for rapid prediction of cerebral aneurysm hemodynamics.

BACKGROUND AND OBJECTIVE: Cerebral aneurysms affect 2-5% of the global population and pose a significant health risk upon rupture. While computational...

Decoding organ fibrosis: mechanistic insights and emerging therapeutic strategies.

Fibrosis is a maladaptive pathophysiological process characterized by excessive deposition of extracellular matrix resulting from dysregulated tissue ...

Adverse outcome pathway-informed machine learning for predicting vascular toxicity of emerging organic pollutants.

Emerging organic pollutants (EOPs) are increasingly detected in wastewater and pose potential vascular toxicity risks that remain inadequately assesse...

Deep learning-based vessel segmentation in non-contrast black-blood MRI for treated aneurysm follow-up: a comparative study with TOF-MRA and DSA.

Artificial Intelligence and Machine Learning Applications in Fibromuscular Dysplasia: Transforming Diagnosis, Risk Stratification, and Clinical Decision-Making.

Fibromuscular dysplasia (FMD) is a non-atherosclerotic vascular disorder with heterogeneous presentations, making diagnosis and management highly depe...

Reimagining Thomas Lewis's perspective: using artificial intelligence tools to predict cardiovascular risk from computed tomography.

Artificial intelligence (AI) is reshaping cardiovascular imaging, transforming it from a set of diagnostic tests into powerful tools of precision medi...

PAH-former: Transfer learning for efficient discovery of pulmonary arterial hypertension-associated genes.

BACKGROUND AND AIMS: Pulmonary arterial hypertension (PAH) is a severe disease with limited effective therapies, making the discovery of new therapeut...

Novel VSMC-associated biomarkers in intracranial aneurysm pathogenesis: a multi-omics and machine learning study.