Diet & Nutrition

Integrating Taguchi design and machine learning models for trait stability and predicting forage quality in naturally occurring grass pea (Lathyrus spp.).

This study investigated the forage quality of four naturally occurring Lathyrus species (Lathyrus czeczottianus, L. pratensis, L. roseus, and L. rotundifolius subsp. miniatus), including one endemic taxon, collected from the Rize province of Turkey. Forage traits of two years were analyzed using the Taguchi design (TD) of experiment to determine trait stability and species-based differences and ro...

Association between oxidative balance score and cardiometabolic multimorbidity: differential mortality, mediation mechanisms, and machine learning insights.

BACKGROUND: Cardiometabolic multimorbidity (CMM) is a major global health burden associated with increased morbidity and mortality. The oxidative balance score (OBS), a composite measure of dietary and lifestyle factors related to oxidative balance, has not been systematically evaluated in relation to CMM and mortality. METHODS: We analyzed 11,365 NHANES participants. Logistic regression, Cox prop...

Lessons from Smart Cart 2.0: Considerations for integrating purchasing data into healthy eating interventions with AI approaches.

The increasing prevalence of chronic diseases related to suboptimal diet quality in the US and worldwide contributes to burgeoning healthcare costs an...

Screening for Periodontitis Using Blood Biomarkers and Demographic Data: A Machine Learning Study.

PURPOSE: Periodontitis is a common chronic disease associated with systemic conditions such as diabetes and cardiovascular disease. Diagnosis typicall...

A deep-learning framework reveals whole-body perturbations at cell level.

Many diseases, including obesity, have systemic effects that perturb multiple organ systems throughout the body1,2. However, tools for comprehensive, ...

Experimental and predictive analysis of pile raft foundation in clayey soils using machine learning and MATLAB tools.

This study demonstrates the performance of piled raft foundations in a variety of clay soils collected from four states in southern India. Comprehensi...

Intelligent monitoring technologies for food fermentation processes: transformation from traditional experience to multimodal approaches and challenges.

Fermentation is a key process in food manufacturing that determines product quality, safety, and nutrition. Traditional offline and manual monitoring ...

Discovery and engineering of UDP-glycosyltransferase and its applications in natural sweetener glycosylation.

With the growing health concern on sugar consumption, the high sweetness and low calorie natural sweeteners, such as steviol glycosides, mogrosides, g...

A Foundation Model for Wearable Movement Data in Mental Health Research.

Wearable movement data is collected by nearly all commercially available smartwatches and is a valuable resource for mental health research, reflectin...

Precision nutrition for the prevention and management of inflammatory bowel disease.

The rising disease burden of inflammatory bowel disease (IBD) parallels the changing dietary landscape accompanying industrialization, underscoring th...

From Single Conventional Regression to Ensemble Modeling: Relative Importance of the Healthy Eating Index-2015 Components in Relation to Adverse Pregnancy Outcomes.

The Healthy Eating Index (HEI) is widely used to assess diet quality, but certain contexts (e.g., pregnancy) may benefit from tailored versions. We ev...

Characterizing Airborne Particulate Matter During Late-Season Soybean Production Using SEM/EDX Automated Single Particle Analyses and Machine Learning: A Preliminary Study in the Mississippi Delta.

Airborne particulate matter (PM) may originate from exposed agricultural fields and activities during dry periods. A preliminary study assessed source...

A global mantle xenolith bulk-rock and paired-mineral dataset.

This data descriptor presents a globally compiled dataset of major element concentrations for mantle peridotite and pyroxenite xenoliths. The dataset ...

The body mass index of females in impressionist paintings: a contrast with modern ideals.

INTRODUCTION: Beauty standards have undergone profound changes over time, with historical depictions of the female body often favoring fuller figures,...

Predicting cardiovascular death in overweight/obese people with prediabetes using machine learning-a proof-of-concept study.

BACKGROUND: Individuals with prediabetes face an increased risk of cardiovascular (CV) complications, which can ultimately lead to premature mortality...

IL-HS: a deep inception-LSTM architecture for enhanced lithological mapping using EnMAP hyperspectral remote sensing data.

Accurate lithological mapping in semi-arid and geologically complex regions is crucial for advancing geoscientific understanding and guiding mineral e...

Interpretable machine learning methods based on oscillometry and electric modeling for the diagnostic of respiratory dysfunction in silicosis.

PURPOSE: Silicosis, the most dangerous and common lung illness associated with breathing in mineral dust, is a significant health concern. Although Re...

Obesity, microRNA circulating microRNA signatures reveal core and reversible dysregulations in obesity via machine learning.

Obesity is a complex metabolic disease characterized by systemic metabolic and inflammatory dysregulation, yet the molecular signatures underlying the...

Interpretable machine learning model integrating MRI-derived paraspinal muscle parameters for predicting new vertebral compression fractures after vertebral augmentation.

OBJECTIVES: To develop and validate interpretable machine learning (ML) models incorporating MRI-derived paraspinal muscle parameters to predict new v...

Development and validation of an explainable machine learning model using routine laboratory biomarkers for identifying prevalent MASLD: Evidence from two observational studies.

Although many predictive models for metabolic dysfunction-associated steatotic liver disease (MASLD) have been developed, their performance remains su...