Diet & Nutrition

NIPSNAP3B elevates mitochondrial biogenesis to attenuate lipid accumulation in childhood obesity via AMPK pathway.

OBJECTIVE: Childhood obesity (CO) has become a global epidemic, leading to rising burden of many diseases and premature death. Thus, this study was conducted to screen the mitochondria-associated biomarkers for patients with CO, as well as the involved molecular mechanism. METHODS: After downloading GSE29718 and GSE104815 datasets from GEO database, differential expression analysis was conducted t...

Research advances and outlook of bioactive peptides: integrating artificial intelligence, molecular simulation, and instrumental analysis techniques.

Due to their diverse physiological functions, bioactive peptides have attracted widespread attention in the fields of functional food development and biomedical applications. However, traditional methods for predicting and screening these peptides are often time-consuming, costly, and lack scalability, thereby hindering their large-scale development and application. This review examines how artifi...

Climate-Smart Slurry Management for Sustainable Crop Production in a Warming Future.

The annual nitrogen (N) production from livestock manure is comparable to that of synthetic N fertilizers used globally in croplands. Despite its reco...

Correction to: Combination of artificial intelligence and chest computed tomography to assess bone mineral density.

Sleep deprivation and epiretinal membrane risk: Machine learning findings from a nation-wide survey.

PURPOSE: This cross-sectional study explored the association between sleep deprivation and epiretinal membrane (ERM) using machine learning applied to...

The discordance of remnant cholesterol and low-density lipoprotein cholesterol as a predictor of diabetes, diabetic microvascular diseases, and cardiovascular disease.

BACKGROUND: The impact of discordance between remnant cholesterol (RC) and low-density lipoprotein cholesterol (LDL-c) on diabetes, diabetic kidney di...

Nanotechnology and machine learning synergies for improving the bioavailability and functional efficacy of dietary polyphenols.

Dietary polyphenols exhibit diverse bioactivities, but their clinical application is limited by poor bioavailability due to low solubility, rapid meta...

Associations between prenatal exposure to indoor air pollution and ambient particulate matter with infant growth.

Despite growing concern, the developmental effects of prenatal exposure to indoor and ambient particulate pollution remain poorly characterized. This ...

Combined effects of persistent organic pollutants and endocrine-disrupting chemicals on thyroid disease risk: A WQS-XGBoost analysis of US population data.

To assess the combined effects of mixed persistent organic pollutants and endocrine-disrupting chemicals on thyroid disease risk, we analyzed data fro...

Preoperative Neuroimaging Markers, Clinical Severity Measures, and Shunt Characteristics for Predicting Shunt Revision in Idiopathic Intracranial Hypertension: An Explainable Machine-Learning Study.

BACKGROUND AND PURPOSE: Surgical shunt placement is a common treatment for idiopathic intracranial hypertension (IIH) but is hampered by high revision...

Enhancing dietary management and nutritional analysis through deep learning: a multi-model approach for food classification and volume estimation.

Nutrition and diet play pivotal roles in fostering a healthy lifestyle. Effective dietary management requires precise identification and analysis of c...

Evolution of the gut microbiome in infancy: recent advances.

PURPOSE OF REVIEW: The early-life gut microbiome is a dynamic ecosystem that alongside other niches, such as the oral and skin microbiomes, undergoes ...

ShenLingBaiZhu powder ameliorates obesity and atherosclerosis by inhibiting inflammation and apoptosis through the suppression of the TLR4/NF-κB pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: ShenLingBaiZhu Powder (SLBZP) is a renowned traditional Chinese medicinal formula that has been historically and clini...

Machine Learning Prediction of Chronic Kidney Disease in Elderly MetS Patients Using NHANES 2011-2020 Data.

BACKGROUND: Chronic kidney disease (CKD) is getting more common in elderly people with metabolic syndrome, but early detection and risk prediction are...

Unveiling the relationship between stress-hyperglycemia ratio and cardiometabolic multimorbidity risk using interpretable machine learning.

BACKGROUND: Cardiometabolic multimorbidity (CMM) is the simultaneous manifestation of multiple cardiovascular and metabolic diseases, and it has arise...

Exploring artificial intelligence literacy's role in healthy behaviors and mental health.

Healthy behavior has long been linked to mental health outcomes. However, the role of artificial intelligence (AI) literacy in shaping healthy behavio...

Association of depressive symptoms with systemic immune-inflammation index and platelet parameters among survivors of myocardial infarction: a cross-sectional NHANES study enhanced by machine learning and SHAP analysis.

BACKGROUND: Inflammation is implicated in the elevated risk of depressive disorder following myocardial infarction (MI), with platelets serving as a k...

Evaluation of large language models in nutrition risk screening: a comparative analysis across 8 LLMs based on real-world EHR datasets.

Intelligent identification of osteoporosis on hip X-rays using vision transformer.

OBJECTIVE: This study aimed to develop and evaluate a deep learning model based on the Vision Transformer (ViT) architecture for the automatic classif...

Development and external validation of an interpretable machine learning-based model for obesity risk prediction in 2-18-year-old children and adolescents in Beijing and Tangshan.

BACKGROUND: The multifactorial mechanisms driving childhood obesity, a global public health challenge, are yet to be fully elucidated. We aimed to dev...