Diet & Nutrition

Evaluating the impact of metabolic indicators and scores on cardiovascular events using machine learning.

Cardiovascular diseases such as coronary artery disease, myocardial infarction, and heart failure impact millions of people annually globally and are a major cause of disease and death. This study explores the predictive capabilities of novel metabolic indices (TyG, HOMA-IR, TG/HDL-C, and VAI) for major adverse cardiovascular events (MACE) and analyzes their relationships with diabetes and cardiov...

Superionicity of oxygen-deficient davemaoite and its impact on the deep-Earth oxidation cycle.

Davemaoite (CaSiO perovskite) is an essential mineral in Earth's lower mantle, thought to be solidified directly from an early magma ocean. Despite its abundance, the impact of defects, particularly oxygen vacancies, on davemaoite's properties under mantle conditions has not been thoroughly investigated. Here, we use machine learning molecular dynamic simulations to examine the behavior of oxygen-...

Momentary dietary lapse prediction for obesity management: Developing the Eating Behaviour Lapse Inventory Survey Singapore (eBLISS) and a machine learning lapse prediction model.

BACKGROUND: As the obesity prevalence continues to rise, effective interventions that promote dietary adherence and address the intricate array of fac...

Longitudinal analysis of coal workers' pneumoconiosis using enhanced resolution-computed tomography images: unveiling patterns in lung structure, function, and clinical correlations.

RATIONALE: Pneumoconiosis, caused by prolonged exposure to mineral dust, leads to progressive structural and functional lung alterations. Quantitative...

A machine learning-based prediction of diabetic retinopathy using the Korea national health and nutrition examination survey (2008-2012, 2017-2021).

BACKGROUND: Machine learning technology that uses available clinical data to predict diabetic retinopathy (DR) can be highly valuable in medical setti...

Mild to moderate COPD, vitamin D deficiency, and longitudinal bone loss: the Multi-ethnic Study of Atherosclerosis.

OBJECTIVE: Despite the established association between chronic obstructive pulmonary disease (COPD) severity and risk of osteoporosis, even after acco...

Unlocking the potential of flavonoid biosynthesis through integrated metabolic engineering.

Flavonoids are a diverse class of plant polyphenols with essential roles in development, defense, and environmental adaptation, as well as significant...

Genomic advancements in goat breeding: enhancing productivity, disease resistance, and sustainability in India's rural economy.

Goats are vital to the rural economy of India, contributing significantly to livelihoods, nutrition, and agricultural sustainability. With a populatio...

Machine Learning with Ingredient-Level Food Trees Reveals Contributors to Systemic Inflammation Among Adults in the National Health and Nutrition Examination Survey, 2001-2010 and 2015-2018.

BACKGROUND: Methods for modeling the relationship between self-reported 24-hour dietary recalls and health outcomes are traditionally based on nutrien...

DRPM: An advanced predictive model for early diabetes detection and risk stratification.

Diabetes is a prevalent chronic disease that poses a significant burden on individuals and healthcare systems. Early diagnosis and effective managemen...

Age-Related Differences in Risk Factors for Long-Term Care Certification in Japan: A Decision Tree Analysis Spanning 3 Years.

Ensuring healthy aging and extending health span is critical, particularly in aging societies. This study analyzed patterns of risk for long-term care...

Tilorone attenuates high-fat diet-induced hepatic steatosis by enhancing BMP9-Smad1/5/8 signaling.

The prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) is rapidly increasing and is caused by excessive fat deposition in ...

Automated Body Composition Analysis Using DAFS Express on 2D MRI Slices at L3 Vertebral Level.

Body composition analysis is vital in assessing health conditions such as obesity, sarcopenia, and metabolic syndromes. MRI provides detailed images o...

Comprehensive analysis of the association between volatile organic compound pollutants and chronic kidney disease in hypertensive populations: insights from multi-omics approaches and identification of potential therapeutic targets.

Environmental pollutants, including volatile organic compounds (VOCs), are increasingly linked to chronic kidney disease (CKD), yet this association i...

Structure from motion-convolutional neural network model (SfM-CNN) achieved accurate portable Chinese dietary chemical composition estimation for dietary recall.

Accurately estimating the chemical composition of dietary intake is essential for health and nutrition management, especially in regions with complex ...

Enhancing liver disease diagnosis with hybrid SMOTE-ENN balanced machine learning models-an empirical analysis of Indian patient liver disease datasets.

INTRODUCTION: The liver is one of the vital organs of human body that performs some of the most crucial biological processes such as protein and bioch...

Predicting Mortality in Atrial Fibrillation Patients Treated with Direct Oral Anticoagulants: A Machine Learning Study Based on the MIMIC-IV Database.

Atrial fibrillation (AF) is a common arrhythmia linked to increased mortality and significant healthcare burden, especially in the elderly. Direct Or...

Improved estimation of forage nitrogen in alpine grassland by integrating Sentinel-2 and SIF data.

Nitrogen is an essential element for the growth and reproduction of vegetation in alpine grasslands and plays a vital role in determining the nutrient...

Bridging Genomic Research Disparities in Osteoporosis GWAS: Insights for Diverse Populations.

PURPOSE OF REVIEW: Genome-wide association studies (GWAS) have significantly advanced osteoporosis research by identifying genetic loci associated wit...

Accuracy of Using Weight and Length in Children under 24 mo to Screen for Early Childhood Obesity: A Systematic Review.

The global increase in early childhood overweight and obesity has prompted interest in early prediction of overweight and obesity to allow timely inte...