Diabetes

Clinical Implications and Research Progress of Salivary Biomarkers for Endocrine and Metabolic Disorders.

AIMS: Similar to blood, saliva contains a broad range of biomarkers and may offer a non-invasive, repeatable specimen for endocrine and metabolic assessment. This review aims to synthesise and evaluate recent advances in the clinical translation of salivary biomarkers, while providing a critical assessment of the diagnostic reliability and clinical potential of key salivary biomarkers. MATERIALS A...

Development and validation of a machine learning-based prediction model for malnutrition risk in peritoneal dialysis patients: a multi‑center retrospective study.

PURPOSE: To develop and validate a machine learning (ML)‑based model for predicting malnutrition risk in patients undergoing maintenance peritoneal dialysis (PD) using routinely available clinical and laboratory data. METHODS: A multicenter retrospective cohort study was conducted. Adults with end-stage renal disease who received PD for at least 90 days were enrolled from two tertiary hospitals. M...

Deep Learning-Derived Retinal Age Detects Cognitive Impairment.

PURPOSE: To investigate the association between deep learning-derived retinal age and cognitive function and to evaluate whether retinal age outperfor...

Plant-based diet quality and risk of age-related eye diseases: evidence from multi-cohorts with multi-omics insights.

Plant-based diets may influence age-related eye diseases (AREDs), but whether ocular benefits depend on diet quality remains unclear. We examined asso...

Patient-specific modeling identifies metabolic interventions for reversing glucose use reprogramming in alcohol-associated hepatitis.

Alcoholic hepatitis (AH) is an acute form of alcohol-associated liver disease with very few treatment options. Recent studies highlighted liver metabo...

Single-cell-based analysis establishes C1QA-mediated promotion of high glucose-induced tubular epithelial injury via ERS in DN.

BACKGROUND: Diabetic nephropathy (DN) poses a growing worldwide health challenge as a leading cause of end-stage renal disease, a condition that arise...

Nutritional Characteristics of Foods With Addictive Potential: A Machine-Learning Approach.

Objectives. To identify nutritional characteristics associated with the perceived addictive potential of commonly consumed foods in the US food supply...

Personalized Type 1 Diabetes Management: Reinforcement Learning-Based Insulin Dosing and Glucose Forecasting.

BACKGROUND: Optimizing insulin dosing and predicting future glucose levels for people with type 1 diabetes is challenging due to the dynamic nature of...

Diabetes Management Through Glucose Dynamics Analysis Network: A Novel Approach for Accurate Blood Glucose Level Forecasting.

BACKGROUND: Accurate real-time prediction of blood glucose (BG) levels is essential for improving insulin-dosing decision support systems, including c...

Characterization of vascular tortuosity throughout the murine oxygen-induced retinopathy model of ischemic retinopathy.

Vascular tortuosity (VT) is a critical biomarker of disease progression and decision to treat ischemic retinal disorders, particularly retinopathy of ...

Proteomic signatures of early retinal neurodegeneration in type 2 diabetes mellitus.

BACKGROUND: Retinal neurodegeneration is an early and independent feature of diabetic retinal disease and has been proposed as a window into the syste...

Transcriptome sequencing combined with experimental verification to explore potential key genes related to uric acid in diabetic retinopathy.

PURPOSE: Diabetic retinopathy (DR), a major microvascular complication of diabetes and leading global blindness cause, involves uric acid (UA) in its ...

Early Prediction of Diabetic Macular Edema via Machine Learning Survival Analysis on Checkup Data.

PURPOSE: To predict the risk of diabetic macular edema (DME) onset and to identify features of the risk subgroups. DESIGN: Population-based observatio...

Unraveling 'F' factor: towards a genetic-clinical framework for the musculoskeletal-heart crosstalk in metabolic aging.

BACKGROUND: The rising co-occurrence of cardiometabolic diseases and musculoskeletal degeneration poses a critical challenge to healthy aging, yet the...

Development and temporal external validation of a high-specificity XGBoost rule-in model for diabetes in middle-aged and older Korean adults.

Early identification of diabetes in older adults is essential for preventing complications, yet many high‑risk individuals remain undetected in commun...

The Validity and Reliability of Artificial Intelligence Chatbots in the Self-management of Diabetes.

Artificial intelligence (AI) chatbots are increasingly used to support diabetes self-management, yet their validity and reliability require systematic...

Exploring the potential targets and mechanisms of artemisinin in the treatment of diabetic kidney disease using network pharmacology and molecular docking.

Diabetic kidney disease (DKD) is a secondary glomerular disease caused by diabetes, and its incidence is increasing annually. Artemisinin is an organi...

Nanostructured electrode materials and flexible-substrate engineering for wearable multi-analyte biosensors in diabetes monitoring and personalized care: a comprehensive review.

This review examines the convergence of wearable biosensors and artificial intelligence (AI) in personalized diabetes care. It addresses the limitatio...

Development of autoencoder-guided attention-LSTM models for predicting nocturnal hypoglycemia risk in Type 1 Diabetes.

OBJECTIVE: Nocturnal hypoglycemia (NH) is a major, often undetected risk for individuals with Type 1 Diabetes (T1DM). Current prediction models lack s...

Artificial intelligence in cardio-kidney-metabolic care: Transforming integrated disease management through data-informed innovation.

Artificial intelligence (AI) is rapidly transforming the landscape of chronic medical conditions, such as cardio-kidney-metabolic (CKM) issues linked ...