Diabetes

Selective and Sustainable Recovery of High-Value Metals from e-Waste via a Glucose-Mediated Hydrothermal Process.

The rapid fabrication of artificial intelligence-based hardware worldwide is intensifying the electronic waste (e-waste) crisis, threatening ecosystems and demanding urgent, sustainable solutions for metal recovery. Herein, a glucose-mediated hydrothermal strategy is reported for the efficient reclamation of high-value metals from complex e-waste. Glucose functions as a multifunctional ligand, est...

Integration of Continuous Glucose Monitoring With HbA1c to Improve the Detection of Prediabetes in Asian Individuals: Model Development Study.

BACKGROUND: Glycated hemoglobin (HbA1c) is a convenient tool to evaluate glycemic status but its ability to detect individuals at risk for type 2 diabetes is limited. OBJECTIVE: Exploiting the glycemic variability captured in continuous glucose monitoring (CGM), we used a well-characterized Asian cohort study from Singapore to assess whether utilizing CGM features in a machine learning model can i...

Integrating bulk and single-cell RNA sequencing identifies and validates lactylation-related signatures in diabetic foot ulcers.

Establishing a Diagnostic Model Based on Plasma CDR1as and Alpha-Synuclein for Mild Cognitive Impairment in Type 2 Diabetes.

Emerging evidence implicates cerebellar degeneration-related protein 1 antisense transcript (CDR1as) and alpha-synuclein (α-Syn) in diabetes and cogni...

MetaboNet: The Largest Publicly Available Consolidated Data Set for Type 1 Diabetes Management.

BACKGROUND: Progress in type 1 diabetes (T1D) algorithm development is limited by the fragmentation and lack of standardization across existing T1D ma...

Identifying Actionable Glucose Patterns in Type 1 and Type 2 Diabetes Using Continuous Glucose Monitoring and Algorithmic Pattern Recognition.

BACKGROUND: Continuous glucose monitoring (CGM) provides real-time glucose data, aiding diabetes management. Identifying glucose patterns is difficult...

Evaluation of large language models for carbohydrate counting in type 1 diabetes mellitus: a comparative study with patient estimations.

AIMS: To evaluate large language models (LLMs) accuracy in carbohydrate (CHO) counting (CC) and compare their performance with estimations by patients...

Lactate-albumin ratio predicts in-hospital mortality in critically Ill patients with congestive heart failure and diabetes.

OBJECTIVE: To evaluate the predictive utility of the initial lactate-to-albumin ratio (LAR) measured within 24 h of admission for in-hospital all-caus...

Comment on "Exploration of a Multimodal Machine Learning Model Integrating Ultrasound and Clinical Indicators for the Diagnosis of Diabetic Peripheral Neuropathy".

Prediction of trajectories and outcomes in early-stage metabolic dysfunction-associated steatotic liver disease: a narrative review.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most prevalent chronic liver disorder, with manifestations ranging from steato...

Inter-observer variability is unlikely to explain regional differences in retinopathy of prematurity in Norway.

PURPOSE: To test inter-observer variation of plus disease diagnoses among Norwegian ophthalmologists and treatment centres. METHODS: All ophthalmologi...

Omission and hallucination prevalence of clinical guidelines in diagnostic large language model outputs.

OBJECTIVE: Meaningful assessments of how large language models (LLMs) incorporate clinical guidelines require large-scale testing over many queries. H...

Prognostic value of stress hyperglycemia ratio, hemoglobin glycation index, and glycemic variability for postoperative atrial fibrillation: a machine learning-based prediction model.

Machine learning prediction of CKD progression in hyperglycemic elderly adults: a prospective community cohort study.

Hyperglycemia is a major risk factor for chronic kidney disease (CKD). This multicenter prospective study developed and validated a machine learning (...

Machine Learning Analysis of Serum Metabolomics for Multi-Disease Classification and Proteome-Metabolome Pathway Insights in T2D, IBD, and CRC.

Type 2 diabetes (T2D), inflammatory bowel disease (IBD), and colorectal cancer (CRC) share overlapping metabolic alterations that hinder early, diseas...

Machine learning analysis of continuous glucose monitoring identifies a novel dysglycemic phenotype found in most people with cystic fibrosis.

BACKGROUND: Cystic fibrosis related diabetes (CFRD) is a common complication in people with cystic fibrosis (PwCF), yet traditional diagnostic tools s...

Unsupervised Agglomerative Cluster Phenotyping of Young Patients With Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention.

BACKGROUND: Young patients with acute coronary syndrome (ACS) exhibit diverse demographic, clinical and angiographic characteristics. We hypothesized ...

Screening of metabolic-related biomarkers linking intervertebral disc degeneration and type 2 diabetes based on comprehensive bioinformatics analysis and machine learning.

BACKGROUND: Intervertebral disc degeneration (IVDD) is a prominent etiology of lower back pain. Type 2 diabetes (T2D), the most prevalent metabolic di...

Enhancing mesenteric vascular imaging with dual-energy CTA: a comparison of DLIR and ASIR-V using low contrast agent and low radiation dose protocols.

BACKGROUND: Timely diagnosis of mesenteric vascular diseases, especially acute mesenteric ischemia (AMI) due to embolism in the superior mesenteric ar...

Detection of young-onset type 2 diabetes using deep learning across primary and secondary care: a nationwide, retrospective cohort study.

BACKGROUND: Once considered a disease observed in older adults, type 2 diabetes is now increasingly seen in youth and adolescence. Young-onset (<40 ye...