Endocrinology

Machine Learning-Based Early Risk Stratification for Sepsis-Related Troponin-Defined Myocardial Injury Using Routine Metabolic Indicators.

BACKGROUND: Early recognition of sepsis-related myocardial injury during sepsis remains difficult, partly because harmonized echocardiographic phenotyping is often unavailable in retrospective critical-care datasets. Routine metabolic indicators, including the triglyceride-glucose (TyG) index and the triglyceride-to-HDL cholesterol (TG/HDL) ratio, may support early risk stratification, but their v...

Prevalence of hypertension and diabetes in Bangladesh: identifying gaps in awareness and misinformation.

OBJECTIVE: Non-communicable diseases (NCDs) are a growing health burden in low- and middle-income countries, with hypertension and poor glycaemic control being key contributors. This study aimed to assess the prevalence, awareness, and misinformation surrounding hypertension and diabetes in Bangladesh, identifying high-risk groups. METHODS: Data from the nationally representative 2022 Bangladesh D...

Current and Novel Biomarkers for Diagnosis and Subtyping of Primary Aldosteronism.

Primary aldosteronism is a common and potentially curable cause of secondary hypertension, yet it remains substantially underdiagnosed. Current diagno...

Assessing Quality, Readability, and Transparency of Online and AI-Generated Information on Type 2 Diabetes Mellitus: Cross-Sectional Exploratory Study.

BACKGROUND: Type 2 diabetes mellitus (T2DM) affects approximately 590 million people worldwide, and its management relies heavily on patient education...

Interpretable machine learning for predicting mild cognitive impairment in elderly patients with type 2 diabetes mellitus: model development and performance assessment.

Type 2 diabetes mellitus (T2DM) is a prevalent chronic condition, particularly in the elderly, and is associated with an increased risk of cognitive d...

Explainable Machine-Learning Model for Predicting Severe Obstructive Sleep Apnea in Patients Undergoing Metabolic Bariatric Surgery.

BACKGROUND: Severe obstructive sleep apnea (SOSA) is associated with an increased risk of perioperative complications in patients undergoing metabolic...

Association of Variability of Monthly Continuous Glucose Monitoring-Derived Metrics With Diabetic Kidney Disease in Type 1 Diabetes.

BACKGROUND: While HbA1c is the standard for monitoring long-term glycaemic control, it fails to capture glycaemic variability. We investigated the dis...

A pH-Calibrated Multi-Analyte MXene Aerogel Electrochemical Platform Assisted by Interpretable Machine Learning for CSF-Based Prescreening of Postoperative Bacterial Meningitis.

Rapid and reliable prescreening and early risk stratification of postoperative meningitis (PNM) remain challenging because clinical symptoms are nonsp...

Interpretable machine learning models predict cognitive impairment in adults aged 50 and over with diabetes: influence of dietary nutrients.

Introduction: diabetes mellitus increases the risk of cognitive impairment, but the role of dietary nutrients remains unclear. Objectives: to develop ...

Artificial intelligence-based ultrasound diagnosis of Hashimoto's thyroiditis: a systematic review and meta-analysis.

BACKGROUND: Hashimoto's thyroiditis (HT) is the most common autoimmune thyroid disorder, often diagnosed using ultrasound. However, conventional gray-...

Appraisal in ChatGPT-4's Accuracy in Estimating Thyroid Nodule Features and Cancer Risk From Ultrasound Images in Thyroidology.

Developmental neurotoxic effects of organophosphate flame retardants (OPFRs) across different life stages and the central role of pioneer transcription factors Neurog2/Ascl1 during the embryonic period.

In contemporary consumer products markets, organophosphorus flame retardants (OPFRs) are widely used, associated with non-carcinogenic health risks an...

Perithyroidal Adipose Tissue Drives Thyroid Tumorigenesis through Adipokine Signaling and Immune Suppression.

The perithyroidal adipose tissue (PAT), given its direct anatomical proximity to the thyroid gland, has long been postulated as a modulator of the thy...

Prism-refraction K-means polar lights optimizer-driven feature selection for accurate diabetes diagnosis.

This study developed a machine learning framework for stratifying abnormal glucose tolerance risk among outpatients presenting with foamy urine. It re...

An AI-Assisted Tool to Predict Continuous Glucose Monitor Adherence in Children With Type 1 Diabetes in Oman: Protocol for a Multiphase Mixed Methods Translational Study.

BACKGROUND: Type 1 diabetes mellitus (T1DM) in children requires sustained self-management to achieve glycemic targets. Continuous glucose monitoring ...

Interpretable single-cell machine learning identifies PINK1-centred mitophagy as a determinant of metabolic fitness in type 2 diabetes.

BACKGROUND: Progressive pancreatic β-cell dysfunction constitutes a hallmark of type 2 diabetes (T2D), yet the molecular programmes governing metaboli...

Integration of site-specific deep learning models for automated OAR segmentation in craniospinal proton therapy: a geometric and dosimetric analysis.

PURPOSE: This study evaluated the feasibility of integrating RayStation deep learning auto-segmentation (DLS) models-originally trained for adult head...

Enhanced MRI brain tumor segmentation with DNet and hybrid dice-weighted cross-entropy loss.

Localization of brain tumors via magnetic resonance imaging (MRI) is critically important for diagnosis, treatment, and surgical operations. This stud...

Variant-specific pharmacophoric shifts in glucagon-like peptide-1 receptor-orforglipron complexes revealed by Boltz-2 co-folding and membrane molecular dynamics.

BACKGROUND: Orforglipron (ORF), the first orally bioavailable non-peptide glucagon-like peptide-1 receptor (GLP-1R) agonist to complete Phase 3 clinic...

Additive effects of heat and volatile organic compounds co-exposure on metabolic syndrome: evidence from petrochemical workers in China.

OBJECTIVE: To investigate the independent and joint associations of heat and volatile organic compounds (VOCs) exposure with metabolic syndrome (MetS)...