Atherosclerosis

Exploration of an interpretable machine learning-based screening manner for low muscle mass among Chinese community-dwelling older adults using routine physical examination information.

BACKGROUND: With the accelerating aging of the global population, muscle health issue occurs commonly as an age-related process in older people. The conventional low muscle mass screening and diagnosis reliant on bulky and costly instruments, remain challenging for regular self-monitoring. If routine physical examination information from primary healthcare settings is integrated and analyzed using...

APOE genotype and the effect of statins on lipid outcomes: A meta-analysis.

AIM: APOE genotype may affect statin therapy response. We conducted a meta-analysis to update and quantify this association across various outcomes. METHODS: We searched seven databases (MEDLINE, Scopus, Web of Science, the Cochrane Library, APA PsycINFO, CINAHL Plus and ClinicalTrials.gov) on 9 May 2024. Screening and data extraction were performed by two reviewers and a machine learning tool (AS...

A machine learning model for optimizing treatment of patients with poorly controlled type 2 diabetes.

BACKGROUND: Cardiorenal-protective sodium-glucose cotransporter-2 inhibitors (SGLT-2i) and glucagon-like peptide-1 receptor agonists (GLP-1RA) lack se...

Early diagnosis of Alzheimer's Disease: Graph theoretical analysis of cerebellar network features based on 18F-AV45 PET.

Pathological and neuroimaging changes in the cerebellum of Alzheimer's disease (AD) patients have been well documented. However, the changes in cerebe...

Vascular Age: A narrative review of assessment methods, clinical applications, and future directions.

Cardiovascular disease (CVD) is the leading cause of death and disability globally, highlighting the importance of effective risk assessment and early...

Machine learning-predicted insulin resistance is a risk factor for 12 types of cancer.

Insulin resistance is suggested to be a risk factor for cancer; however, large-scale epidemiological evidence linking insulin resistance to cancer rem...

Self-powered in-stent restenosis diagnosis via magnetoelastic stents.

Widely used in millions of atherosclerosis treatments, conventional metal stents, although pervasive, only provide mechanical support to narrowed arte...

Reliable discrimination of type 1 and type 2 diabetes by flow-through leukocyte-endothelium interactions exploiting advanced hydrodynamic detection parameters.

Type 1 (T1D) and type 2 diabetes (T2D) are both associated with chronic inflammation and endothelial dysfunction, yet their discrimination based on co...

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 i...

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 Intracrania...

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...