Diabetes

Integrative Proteomic and Machine Learning Analysis Identifies Novel Predictors and Risk Model for Diabetic Macrovascular Complications.

OBJECTIVE: Diabetic macrovascular complications continue to drive substantial morbidity, yet early detection tools and deeper mechanistic understanding remain scarce. This study aimed to pinpoint circulating protein biomarkers for diabetic macrovascular complications while elucidating their biological significance. METHODS: We combined proteome-wide Mendelian randomization (MR), Cox proportional h...

Urinary extracellular vesicle miRNA signature reflects pancreatic islet stress in type 2 diabetes.

INTRODUCTION: Type 2 diabetes (T2D) is a progressive metabolic disorder characterized by insulin resistance and progressive β-cell dysfunction. Early detection remains critical to prevent long-term complications. Urinary extracellular vesicle (ECV) microRNAs (miRNAs) have emerged as stable, non-invasive biomarkers with the potential to reflect systemic molecular alterations associated with metabol...

Comparative study on the predictive value of PNI and GNRI for all-cause mortality rates of elderly patients in cardiac care unit and cardiovascular intensive care unit.

BACKGROUND: The prognostic nutritional index (PNI) and geriatric nutritional risk index (GNRI) are reliable alternative biomarkers of nutrition. Howev...

Gut microbiome and metabolic health: mechanisms and precision interventions.

The gut microbiome is increasingly recognized as a fundamental regulator of metabolic health, shaping energy balance, insulin sensitivity, inflammator...

Deep learning-based early prediction of gestational diabetes mellitus through first-trimester placental texture analysis.

INTRODUCTION: This study aimed to develop a multi-parameter fusion model for early GDM risk prediction and validate its performance through external m...

AIGC-driven virtual patients for diabetes: a systematic review.

This systematic review (SR) examines the application of Artificial Intelligence-Generated Content (AIGC) in developing virtual patients (VPs) for diab...

Early prediction of gestational diabetes mellitus with clinical characteristics, cell-free DNA and genetic variants.

BACKGROUND: Gestational diabetes mellitus (GDM) remains a prevalent and heterogeneous pregnancy complication with limited strategies for early identif...

Metabolism-related genes CYP4F2, CYP8B1, and SP1 link type 2 diabetes mellitus and non-alcoholic fatty liver disease: A multi-omics and clinical validation study.

Technology in Diabetes: A Year in Review.

The past year has continued the rapid evolution of diabetes technology across the monitoring, delivery, analytics, and patient-support domains. Improv...

Beta cell microRNAs function as molecular hubs of type 1 diabetes pathogenesis and as biomarkers of diabetes risk.

AIMS/HYPOTHESIS: Clinically actionable biomarkers that accurately reflect the health status of the beta cell are needed to improve risk stratification...

Interpretable machine learning models based on CMR radiomics for predicting left ventricular diastolic dysfunction in patients with metabolic-associated steatotic liver disease and type 2 diabetes mellitus.

BACKGROUND: Obesity-induced left ventricular diastolic dysfunction (LVDD), associated with ectopic fat and dysfunctional epicardial adipose tissue (EA...

Modeling Diabetes Risk and Progression With Public Health Data: Ontology-Guided, Simulation-Capable Digital Twin Study.

BACKGROUND: Digital twins (DTs) offer a paradigm for health care by enabling data-driven, simulation-capable representations of individual health traj...

Clinical utility of BOLD-MRI in accurate diagnosis and prognostic evaluation of diabetic nephropathy: a prospective renal biopsy-based cohort study.

OBJECTIVES: To validate blood oxygen level-dependent MRI (BOLD-MRI) for non-invasive discrimination of diabetic nephropathy (DN) vs non-diabetic renal...

Traditional statistics and artificial intelligence-based prognostic models for predicting type 2 diabetes mellitus after gestational diabetes: a systematic review.

Unveiling novel biomarkers for diabetes-related complications through large-scale proteomics analysis: A FIELD sub-study.

BACKGROUND: Vascular complications of Type 2 diabetes (T2D) significantly contribute to its morbidity and mortality. Identifying robust biomarkers is ...

ZFP36-ferroptosis axis as a key renal protective pathway in diabetic kidney disease.

Diabetic Kidney Disease (DKD) is strongly related to ferroptosis, an iron-dependent form of programmed cell death characterized by the accumulation of...

Enhancing Vibrational Spectroscopy-Based Diagnosis through Bottom-Up Modeling: The Case of Infrared Absorption Spectrum of Urine.

Vibrational spectroscopy has become a valuable tool for biomedical applications. However, the technique generates large empirical spectral data sets, ...

International consensus on adolescent metabolic health: prevention of obesity and type 2 diabetes.

Enhanced diagnosis of diabetic retinopathy: integrating advanced algorithms for automated detection and classification.

AIM: To develop an automated diagnostic system for early detection of diabetic retinopathy (DR) using fundus images by identifying exudates, hemorrhag...

Referral uptake after diabetic retinopathy screening with artificial intelligence-assisted care pathways: a systematic review and meta-analysis.

Artificial intelligence (AI) is an accurate screening tool for diabetic retinopathy (DR), the leading cause of blindness among working-aged adults. Ho...