Diet & Nutrition

Design and validation of renal stone detection using multi-architecture feature extraction with deep sequential learning model on axial computed tomography images.

Kidney stone disease is a significant public health threat, with its prevalence escalating due to evolving dietary habits, rising rates of obesity, other medical conditions, and the use of certain supplements. A kidney stone, otherwise known as a renal calculus, is a solid mass of crystallized minerals that aggregates within the kidneys. The proper identification of this renal condition is vital b...

Systematic discovery of enzyme promiscuity in Escherichia coli using in vitro metabolomics.

Metabolic enzymes have traditionally been regarded as highly specific catalysts; however, many can catalyze multiple reactions. To systematically investigate the prevalence of such enzyme promiscuity, we used nontargeted metabolomics to measure dynamic metabolite ion profiles in in vitro assays with 667 successfully purified Escherichia coli enzymes in a natural intracellular metabolome extract. N...

Letter to the Editor: expanding the artificial intelligence-nutrition integration framework to address implementation gaps.

A TyG-UHR-based machine learning model for screening lean MAFLD: development and external validation.

BACKGROUND: Lean metabolic dysfunction-associated fatty liver disease (MAFLD) is increasingly recognized but often goes unnoticed during health checku...

Exploring the Bone-Vascular Axis: AI-Augmented Chest CT Analysis in COPD Highlights Association Between Vertebral Bone Density and Arterial Calcifications.

OBJECTIVES: Artificial intelligence (AI) tools enable automated assessment of vertebral bone mineral density (BMD), coronary artery calcification (CAC...

Predicting 28-day all-cause mortality in critically ill ischemic stroke patients using white blood cell-to-hemoglobin ratio and dual-feature selection machine learning models.

BACKGROUND: The white blood cell-to-hemoglobin ratio (WHR) is a composite biomarker of inflammation and nutrition, but its prognostic role in critical...

Early Identification of Mobility Limitations in Community-Dwelling Middle-Aged and Older Adults: Development of a Prediction Model Based on a Prospective Cohort.

BACKGROUND: With the aging of the global population, preventing the onset of mobility limitations is considered a worldwide public health priority. OB...

Metabolic-inflammatory burden predicts mortality in heart failure across population and ICU cohorts.

BACKGROUND: Systemic metabolic and inflammatory disturbances play a critical role in the pathogenesis and prognosis of heart failure (HF). However, it...

Interpretable machine learning with SHAP analysis identifies redox-modulating dietary antioxidants for predicting accelerated biological aging.

BACKGROUND: Aging is a complex biological process characterized by progressive functional decline across multiple physiological systems, and biologica...

Genomic variation drives plant flavor diversification.

Plant flavor diversity arises from genomic variation across species and cultivars, yet the mechanisms linking natural genomic variation to flavor-rela...

Dataset documentation for responsible AI: analysis of suitability and usage for health datasets.

Artificial Intelligence (AI) is rapidly transforming healthcare, but also raising concerns about algorithmic biases that mostly stem from the training...

Molecular basis of precision nutrition: Food components, microbiome-derived metabolites, and multi-omics modeling.

Metabolic disorders, including obesity, type 2 diabetes, metabolic syndrome, and fatty liver disease, reflect multifactorial interactions among diet, ...

Communication-Based Teaching on Childhood Obesity and the Planetary Health Diet in Medical Education: Proof-of-Concept Study Comparing 4 Information Sources.

BACKGROUND: Childhood obesity constitutes a complex medical and psychosocial challenge that requires both nutritional knowledge and sensitive, relatio...

Unveiling the drivers of groundwater quality in an industrial plain: An integrated hydrogeochemical and stacking ensemble learning approach.

Understanding the hydrochemical evolution and primary chemical components governing groundwater quality in industrial regions is crucial for sustainab...

Quantum-Enabled Approaches to Precision Nutrition: Linking Molecular Interactions with Metabolic Prediction.

Precision nutrition aims to tailor dietary guidance to individual biology, yet current methods struggle to integrate complex molecular and multi-omic ...

Beyond Weight Loss: Obesogenic Memory as Biological Hysteresis in Adipose Tissue Revealed by AI Semantic Mapping With an Exportable Core Corpus.

BACKGROUND: Obesity is commonly viewed as a reversible condition primarily driven by excess body weight. Increasing evidence, however, suggests that a...

Comprehensive cross-cohort analysis reveals global gut microbiome signatures of celiac disease.

BACKGROUND: Celiac disease affects ~1-2% of people and remains incurable, requiring lifelong dietary restriction. The gut microbiome is thought to con...

A Machine-Learning Assisted Genetic Risk Score Identifies Improved Weight Loss After Endoscopic Sleeve Gastroplasty.

BACKGROUND AND AIMS: Obesity remains an epidemic associated with significant health consequences. Endoscopic sleeve gastroplasty (ESG) can lead to sig...

Progress in the application of high internal phase emulsions in weight-loss food development: Mechanisms, effects, applications and integration with artificial intelligence.

High internal phase emulsions (HIPEs) are characterized by unique structural properties and are widely used in food science, pharmaceuticals, material...

Artificial intelligence in nutritional assessment and decision making.

PURPOSE OF THE REVIEW: Artificial intelligence (AI) has become an non contourable tool in clinical nutrition practice. This review proposes to discuss...