Atherosclerosis

Integrating single-cell multi-omics and machine learning to reveal triaptosis heterogeneity in clear cell renal cell carcinoma.

Triaptosis, an emerging form of cell death, remains poorly characterized in terms of its heterogeneity within clear cell renal cell carcinoma (ccRCC). Utilizing single-cell transcriptomics, we delineate a landscape of triaptosis heterogeneity and identify monocytes and macrophages as exhibiting the highest triaptosis activity, which further increases upon terminal differentiation. These high-activ...

Deep Learning Morphometric Analysis on Protocol Biopsies Predicts Future Graft Function.

INTRODUCTION: The predictive value of Banff classification in protocol transplant biopsies without specific lesions is limited. Morphometry provides precise data on microstructures, surpassing semiquantitative scores but is time-consuming. This study evaluates whether automated morphometric analysis with deep learning can predict glomerular filtration rate at 3 years using machine learning. METHOD...

Association between the endothelial activation and stress index and 28-day all-cause mortality in critically ill patients with chronic obstructive pulmonary disease: a retrospective cohort study and predictive model establishment based on machine learning.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) remains a major global health burden and is currently the third leading cause of death worldw...

Multi-omics data mining combined with experimental validation reveals ferroptosis- and autophagy-associated hub genes as diagnostic candidates and immune modulators in atherosclerosis.

BACKGROUND: Atherosclerosis (AS) is a chronic inflammatory vascular disease that can lead to severe cardiovascular events. Ferroptosis and autophagy h...

Prognostic Imaging Biomarkers in Diabetic Macular Edema Treated with Anti-VEGF: A Multicenter AI Perspective.

INTRODUCTION: This study aimed to identify optical coherence tomography (OCT) biomarkers at baseline and after the loading phase (LP) of antivascular ...

Multimodal deep learning prediction of treatment response to anti-vascular endothelial growth factor in diabetic macular oedema.

OBJECTIVE: To develop and validate a multimodal deep learning model that predicts treatment responses to intravitreal anti-vascular endothelial growth...

Research progress on biomarkers for acute kidney injury in children.

Pediatric acute kidney injury (AKI) often presents insidiously and progresses rapidly. Traditional diagnostic criteria based on serum creatinine and u...

Development and validation of a machine learning model to predict recurrence in polypoidal choroidal vasculopathy: a multicentre prospective study.

AIM: This study aims to develop and validate machine learning models for predicting recurrence in polypoidal choroidal vasculopathy (PCV) patients usi...

Sodium nitrite promotes atherosclerosis via IL-1β: Network toxicology and machine learning insights.

BACKGROUND: Atherosclerosis (AS) is a major global health burden. Sodium nitrite, a common environmental and dietary contaminant, has been implicated ...

Neutrophil extracellular traps-related biomarkers in idiopathic pulmonary arterial hypertension: A machine learning-based identification and experimental validation study.

Neutrophil extracellular traps (NETs) are increasingly recognized as critical mediators in vascular inflammation and remodeling, yet their molecular m...

3D Freehand Ultrasound Reconstruction of the Carotid Artery.

OBJECTIVE: Sensorless alignment of two-dimensional (2D) freehand ultrasound scans for three-dimensional US (3DUS) reconstruction offers significant ad...

Derivation and external validation of a deep learning model to predict changes in coronary plaque burden.

BACKGROUND: Predicting the progression/regression of coronary plaque burden is challenging. AIMS: We aimed to develop a deep learning model to forecas...

Deep Learning Radiomics Signature from Multicontrast MRI for Automated Identification of Symptomatic Carotid Plaques: A Multicenter Study.

BACKGROUND AND PURPOSE: Ischemic stroke poses a significant global health burden. Accurately identifying symptomatic carotid atherosclerotic plaques, ...

Deep Learning-based Automated Coronary Plaque Quantification: First Demonstration With Ultra-high Resolution Photon-counting Detector CT at Different Temporal Resolutions.

OBJECTIVES: The aim of this study was to evaluate the feasibility and reproducibility of a novel deep learning (DL)-based coronary plaque quantificati...

60 kVp Coronary CT Angiography as a Screening Tool on Asymptomatic Patients: An Initial Experience.

PURPOSE: To investigate the feasibility of using 60 kVp coronary CT angiography (CCTA) combined with deep learning-based CT reconstruction as a screen...

Network pharmacology and machine learning reveal multi-target mechanisms of poly herbal formulation against atherosclerosis.

BACKGROUND: Herbs, like Allium sativum, Ginkgo biloba and Nerium oleander are traditional medicinal plants that have been used to treat atherosclerosi...

Integrated plasma proteomics and metabolomics reveal immunometabolic pathways and predictive signatures for age-related eye diseases.

BACKGROUND AND AIMS: Age-related eye diseases (AREDs) share aging as a major risk factor, but the systemic molecular changes preceding disease onset r...

Multi-Omics and Machine Learning-Uncovered FLT1-Mediated Epithelial-Endothelial Crosstalk in Cellular Senescence Driving Clear Cell Renal Cell Carcinoma Malignancy.

Clear cell renal cell carcinoma (ccRCC) is distinguished by the absence of definitive diagnostic markers and efficacious treatment modalities, factors...

[Pit and fissure morphology and its implication for caries prevention and treatment].

Dental caries is a chronic and progressive destruction of dental hard tissue under the combined action of multiple factors, with the pits and fissures...

Multi omics and mechanistic investigation reveals CBFB as a prognostic biomarker in gastric cancer.

BACKGROUND: Gastric cancer is an aggressive malignancy with poor prognosis due to complex pathogenesis, underscoring the need for biomarkers and targe...