Osteoporosis

Application of machine learning for sex-specific risk prediction of coronary artery calcification.

BACKGROUND AND AIMS: Sex-related differences in coronary artery calcium (CAC) burden and risk are well known but often ignored in traditional models. We aimed to determine whether sex-specific machine learning (ML) improves CAC risk prediction using routine clinical data. METHODS AND RESULTS: In this cross-sectional study, adults (n = 446) referred for coronary computed tomography angiography were...

Automated Abdominal Aortic Calcification Scores and Atherosclerotic Cardiovascular Disease in the UK Biobank Imaging Study.

BACKGROUND: Abdominal aortic calcification (AAC) is a subclinical measure of atherosclerotic cardiovascular disease (ASCVD). AAC can be captured on lateral spine images obtained from bone density machines during routine osteoporosis screening. Identifying individuals with AAC provides a new opportunity to prevent disease progression. OBJECTIVES: The aim of the study was to externally validate a ma...

Lipoprotein(a) Selectively Associates with Vulnerable Coronary Plaque Phenotypes in Comparison with Other Established Risk Markers.

AIMS: Lipoprotein(a) [Lp(a)] is an inherited cardiovascular risk factor. However, its association with coronary plaque characteristics beyond traditio...

Automated Classification of Store-Operated Calcium Entry Activity and Disease Conditions in Murine Skeletal Muscle Images Using Machine Learning.

INTRODUCTION/AIMS: Accurate detection of pathophysiology from tissue images is critical for appropriate diagnoses and treatments of muscular dystrophi...

Bacterial fructan-metabolizing enzymes: modular architecture and biotechnological potential.

Bacterial fructan-metabolizing enzymes exhibit substantial structural and mechanistic diversity to support their biotechnological uses. Recent finding...

Mechanistic insights into heart failure progression and therapeutic target discovery through plasma microRNA profiling: Findings from HOMAGE.

BACKGROUND: Identifying early pathobiological mechanisms associated with the onset and progression of heart failure (HF) could guide development of pr...

Bridging Microscopic Dynamics and Macroscopic Fate: A Molecular Dynamics-Machine Learning Approach for Predicting PFAS Solid-Liquid Distribution in Soils and Sediments.

Per- and polyfluoroalkyl substances (PFAS) are persistent global contaminants, posing challenges to predicting their environmental fate. The solid-liq...

Deciphering Multitarget Mechanisms of Phytochemical Flavonoids From Traditional Chinese Medicine: Emerging Insights Into Osteoporosis Therapeutics.

Osteoporosis is a common metabolic bone disorder characterized by reduced bone mass and compromised skeletal microstructure, increasing fracture risk....

Prognostic value of deep learning-based coronary artery calcium score and quantitative pneumonia burden in patients hospitalized with COVID-19.

An online non-radiographic osteoporosis prediction calculator constructed using interpretable machine learning.

Prediction of renal cell carcinoma: Development and validation of machine learning model.

Renal cell carcinoma (RCC) is the leading cause of urinary system morbidity and mortality. Early identification is crucial for improving RCC patient o...

The multi-omics and Mendelian randomization analyses unveiled potential marker genes in the progression of glioblastoma.

In glioma research, identifying key molecules for predicting patient prognosis is challenging due to high heterogeneity. This study explores the corre...

Clinical and economic impact of deep learning-enhanced opportunistic osteoporosis screening using chest radiographs with and without the osteoporosis self-assessment tool for Asians (OSTA).

UNLABELLED: Opportunistic analysis of chest radiographs with deep learning detects osteoporosis cost-effectively in women aged ≥ 50 years in Singapore...

Current Status of AI-Assisted Screening for Opportunistic Osteoporosis.

Acetyl tributyl citrate as a new risk factor for osteoporosis: An integrated study from multi-level toxicological assessment and experimental validation.

This study aimed to elucidate the toxicological effects and underlying mechanisms of the plasticizer acetyl tributyl citrate (ATBC) on osteoporosis (O...

Retinal Coronary Artery Calcium Scoring - A Scalable Tool for Life Insurers.

BACKGROUND.—: Cardiovascular risk estimation for life insurance underwriting relies on risk estimation from conventional metrics: age, sex, smoking st...

Symptom status and non-calcified plaque burden across CAC strata: insights from AI-based CCTA quantification.

To investigate whether non-calcified coronary plaque (NCP) volume differs between symptomatic versus asymptomatic individuals across strata of coronar...

Coronary atherosclerosis on AI-based plaque analysis in patients with chest pain and calcium score zero.

Fibroblast-like cells accumulate late in human coronary atherosclerosis contributing to necrotic core formation.

AIMS: Proliferation of arterial smooth muscle cells (SMCs) and their modulation to alternative mesenchymal phenotypes is central to atherosclerotic le...

Construction of musculoskeletal quantitative model based on deep learning and study of musculoskeletal relationship in patients with osteoporosis.

INTRODUCTION: Lumbar CT and MRI scans are helpful for osteoporosis (OP) screening. Deep learning enhances the efficiency and accuracy of musculoskelet...