Diet & Nutrition

Bone Mineral Density Loss After Kidney Transplantation: Metabolic Determinants, Diagnostic Approaches, and Preventive Strategies.

Mineral and bone disease (MBD) is a frequent complication after solid organ transplantation. The rapid decline in bone mineral density (BMD) during the first year after kidney transplantation reflects complex interactions between immunosuppressive therapy, metabolic factors and pre-existing chronic kidney disease (CKD)-MBD. This narrative review summarizes the magnitude and time course of BMD loss...

Epigenetic-Genetic Crosstalk at the Cancer-Diabetes Interface: Convergent Molecular Pathways, Multi-Omics Biomarkers, and Dual Therapeutic Targets.

The complex interdependence between cancer and diabetes has become a major subject of research in molecular medicine since multiple data points indicate that these two conditions have some molecular processes and regulatory pathways in common. The complex relationship between epigenetic and genetic modifications linking these two prevalent diseases was explored in this comprehensive study. Molecul...

Deep learning of multiplexed mitochondrial morphology identified natural compound combinations against skin photoaging.

BACKGROUND: Skin photoaging is primarily driven by mitochondrial dysfunction. Although natural products have demonstrated protective effects against U...

Deep learning analysis of ECGs detects Cardiovascular-Kidney-Metabolic syndrome burden in people with diabetes: a report from the Silesia Diabetes-Heart Project.

BACKGROUND: Cardiovascular-kidney-metabolic (CKM) syndrome refers to the co-occurrence of obesity, diabetes, chronic kidney disease (CKD), and cardiov...

MeLSI: Metric Learning for Statistical Inference in microbiome community composition analysis.

Microbiome beta diversity analysis relies on distance-based methods, including permutational multivariate analysis of variance (PERMANOVA) combined wi...

The future of DXA: How AI is transforming bone health diagnostics.

Dual-energy X-ray absorptiometry (DXA) remains the clinical gold standard for assessing bone mineral density (BMD), guiding diagnosis and therapeutic ...

A machine learning-based analysis of chronotype and sleep quality as predictors of mental distress in university students.

This cross-sectional study aimed to investigate the combined effects of chronotype, Mediterranean diet adherence, and sleep quality on mental distress...

Combined Effects and Potential Mechanisms of Multiple Metals Exposure on Coronary Artery Disease in the US Population: An Integrated Epidemiological and Network Toxicology Study.

Coronary artery disease (CAD) emerged as a major global health burden, but the relationship between multiple metals exposure and CAD and its toxicolog...

Predicting children's undernutrition and its association with women's asset ownership in Ethiopia: spatial machine learning.

Child undernutrition remains a critical public health concern, with prominent geographic and structural disparities in Ethiopia. Understanding how wom...

Association between sources of nutrition information and self-perceived nutrition competence of healthcare professionals: a cross-sectional study.

BACKGROUND: Healthcare professionals other than dietitians are widely perceived as credible sources of nutrition information by patients, despite many...

Identifying the ideal deep learning algorithm to quantify the threshold effect of parental smoking on child nutritional status in South Asia.

BACKGROUND: Accurate identification of modifiable risk factors for child malnutrition is of great importance in the formulation of policies to protect...

Feasibility of image-based 3D avatar anthropometry assessment of pediatric obesity: a pilot study.

UNLABELLED: The purpose of this study is to evaluate the feasibility and validity of 3D avatar-based anthropometry for assessing anthropometric indica...

An interpretable predictive model for depression risk in diabetic patients: A web-based application using NHANES data.

Depression is a common comorbidity in individuals with diabetes and is associated with adverse clinical outcomes. Early identification of high-risk in...

Machine learning-based early kidney stone risk classification in diabetic-hypertensive patients using obesity composite indices.

Kidney stone disease (KSD) is increasingly prevalent among patients with diabetes mellitus and hypertension. Obesity-related metabolic abnormalities m...

Generative artificial intelligence creates delicious, sustainable, and nutritious burgers.

Food choices shape both human and planetary health; yet, designing foods that are delicious, nutritious, and sustainable remains challenging. Here we ...

Associations of indoor bacterial, metabolomic, and other chemical exposures with allergic rhinitis in school-aged children.

BACKGROUND: The indoor environment has been implicated as a critical factor in the development of allergic diseases. However, the interplay among indo...

Association of glycolipid metabolism 6 factors index with cardiovascular and metabolic diseases, and its predictive value in disease progression.

BACKGROUND: The study aims to investigate the potential of glycolipid metabolism 6 factors (GLM6) and glycolipid metabolism 7 factors (GLM7) indexes i...

Model architecture dominates nutritional estimation accuracy in vision-language systems.

Vision-language models (VLMs) enable automated dietary assessment from food photographs, yet optimal deployment strategies remain unestablished. We ev...

Environmental constraints on freshwater red algae in Estonian streams: Insights from long-term observations and machine-learning models.

The division Rhodophyta (red algae) includes an inconspicuous and often overlooked component of benthic freshwater biota. In many cases, freshwater re...

Precision Nutrition and Chronic Disease: Integrating Genomics, Microbiome, and Digital Health for Personalized Dietary Interventions.

Chronic non-communicable diseases (NCDs), including cardiovascular disease, type 2 diabetes, obesity, and metabolic syndrome, account for more than 70...