Diet & Nutrition

Publisher Correction: Machine Learning Models for Predicting Significant Liver Fibrosis in Patients with Severe Obesity and Nonalcoholic Fatty Liver Disease.

Nutrigenomics in precision livestock and poultry farming: Enhancing productivity, welfare, and sustainability through gene-tailored diets.

Nutrigenomics has emerged as a valuable framework for improving precision livestock and poultry production by elucidating how diet interacts with genetic and molecular pathways to shape animal performance, health, product quality, and sustainability. This review provides a structured synthesis of current research on nutrigenomic applications across major livestock and poultry species, focusing on ...

Multi-omics-based machine learning model predicts response and guides treatment in Crohn disease: a case study in nutritional therapy.

BACKGROUND: Biomarkers are needed to predict treatment response and guide therapeutic decisions in Crohn disease (CD). We aimed to develop and validat...

Co-morbid biomarkers for sarcopenic obesity associated with gut microbiota metabolites: From burden to treatment.

BACKGROUND: The detrimental cycle of sarcopenic obesity (SO) significantly reduces quality of life in older adults, while the mechanisms are still unc...

The Use of Statistical Shape and Appearance Modelling for Predicting Osteoporotic Fracture Risk.

PURPOSE OF REVIEW: Osteoporotic fractures remain a major cause of morbidity and mortality worldwide. Current clinical assessment metrics (e.g., bone m...

Accuracy of large language model-based artificial intelligence tools for equine topics.

BACKGROUND: Artificial intelligence (AI) platforms are becoming increasingly popular as resources for equine information. However, these platforms gen...

The association of systemic inflammatory indices with all-cause mortality risks in patients with COPD: A cohort study based on machine learning.

This study aimed to comprehensively assess the prognostic value of routinely obtained blood-based systemic inflammatory indices in predicting all-caus...

A Bilingual AI-Based Chatbot for Nutrition Education in a Food Is Medicine Intervention for High-Risk Pregnant Women: Design and Development Study.

BACKGROUND: Conversational agents (artificial intelligence [AI]-based chatbots) offer a novel approach to health interventions by providing personaliz...

AI-Driven Farm-To-Fork Biofilm Detection and Control in Aquatic Foods: From Industry 4.0 to Industry 5.0.

Aquatic foods are essential sources of protein and micronutrients and play a critical role in global nutrition, trade, and livelihoods. However, their...

Research priorities for improved pandemic and epidemic intelligence.

Pandemic and epidemic intelligence integrates surveillance data with contextual knowledge to assess health risks and inform public health decisions. A...

The Correlations and Predictive Capabilities of the "Life's Essential 8" With Respect to All-Cause Mortality and Cardiovascular Disease Mortality Risks in Individuals Experiencing Sleep Disorders: A Prospective Cohort Study From the NHANES (2005-2014).

BACKGROUND: Life's Essential 8 (LE8) is a framework for assessing cardiovascular health (CVH). Individuals with sleep disorders face an elevated risk ...

Current Status of Smart Technology Applications and Food Safety Implications in Precision Millet Fermentation: A Critical Review.

Millet fermentation has gained significant attention due to its numerous health benefits, owing to its higher dietary fiber and gluten-free properties...

Intestinal alkaline phosphatase and gut health: insights into homeostasis, barrier protection, and immune signaling.

Intestinal alkaline phosphatase (IAP) is a brush border enzyme critical for maintaining gut homeostasis by detoxifying bacterial endotoxins, regulatin...

Time-Dynamic AI Models to Predict Quality of Life in Patients With Breast Cancer: Development and Validation Study Using the EORTC BALANCE Cohort.

BACKGROUND: Patients with breast cancer often experience health-related quality of life (HRQoL) impairments that remain difficult to predict on an ind...

A Fine-Tuned Multimodal AI Chatbot for Dietary Health and Nutrition, Purrfessor: Development and Mixed Methods Evaluation.

BACKGROUND: The integration of Large Language and Vision Assistant models with food and nutrition data enables multimodal meal analysis and contextual...

Assessing osteosarcopenia using automated multi-structure-segmentation and Hounsfield unit-based analysis of lumbar muscles and vertebral bodies on computed tomography.

Sarcopenia and osteoporosis are prevalent age-related conditions that substantially increase the risk of falls, fractures, and functional decline. Thi...

Data-driven prioritization of high-risk individuals for weight loss interventions.

New obesity medications have demonstrated efficacy in trials, but their real-world deployment is partly limited by the absence of approaches that iden...

Phase-dependent nutrient requirements of broiler breeder hens for day-old chick production in a field study using interpretable machine learning.

Day-old chick output from broiler breeder flocks is a key determinant of efficiency in the global poultry industry and is highly sensitive to breeder ...

Patient-Specific Constitutive Models Based on Biaxial and Microstructural Characterisation of Fresh Human Gastric Tissue.

PURPOSE: As obesity has reached pandemic proportions worldwide, improving technical solutions for its treatment requires robust planning and numerical...

Diagnosis of Acromegaly.

The clinical presentation of acromegaly reflects systemic effects of chronic GH and IGF-I excess. Diagnostic delay frequently ranges from 6 to 10 year...