Endocrinology

Myocardial Fibrosis in Pediatric Heart Disease: Mechanisms, Imaging Biomarkers, Clinical Consequences, and Emerging Antifibrotic Therapies.

Myocardial fibrosis is increasingly recognized as a central determinant of adverse cardiac remodeling and long-term cardiovascular outcomes in children with congenital and acquired heart disease. Once considered an irreversible consequence of chronic myocardial injury, fibrosis is now understood to represent a dynamic biological process driven by persistent inflammation, neurohormonal activation, ...

The Minimum Frequency of Well-Day Capillary Blood Ketone Testing Needed to Predict 1-Month Diabetic Ketoacidosis Risk in Type 1 Diabetes.

OBJECTIVE: Independent of clinical risk factors, performing well-day capillary ketone monitoring over a month predicts near-term diabetic ketoacidosis (DKA) risk. We aimed to determine the minimum frequency of tests needed to maintain similar accuracy. RESEARCH DESIGN AND METHODS: Using regression and machine-learning gradient-boosted tree (GBT) models on the Empagliflozin as Adjunctive to Insulin...

Comment on "Radiomics and machine learning analysis of ultrasound images in Bethesda IV thyroid nodules: a retrospective monocentric study".

Risks of Major Adverse Kidney Events in Non-Hispanic Black Patients with Diabetes or Hypertension: A real-world cohort study.

INTRODUCTION: Chronic kidney disease (CKD) disproportionately burdens non-Hispanic Black (NHB) patients who experience a three- to four-fold higher ri...

Brain Tumor Classification from MRI Using Colormap-Based Vision Transformers on the BRISC2025 Dataset.

Accurate brain tumor classification from magnetic resonance imaging (MRI) is essential for supporting early diagnosis and treatment planning. While Vi...

Interpretable QSAR modelling for PPAR-γ agonist prediction by integrating a stacking strategy, docking, and MD simulations.

Peroxisome proliferator-activated receptor gamma (PPAR-γ) is a ligand-activated nuclear receptor involved in adipogenesis, glucose homeostasis, lipid ...

Integrated multi-omics, machine learning, network toxicology, and molecular docking reveal potential mechanisms underlying methyl 4-hydroxybenzoate-associated breast cancer.

Breast cancer (BC) represents a major public-health burden, and epidemiological evidence suggests a potential association with exposure to methyl 4-hy...

Machine learning-based prediction model for predicting the impact of insulin resistance on the risk of ischemic cardiomyopathy.

BACKGROUND: The triglyceride-to-high-density lipoprotein cholesterol (TG/HDL-C) ratio and triglyceride glucose-body mass (TyG-BMI) index are reliable ...

Distinct Conformational Switches Control WPD-Loop Dynamics Across Protein Tyrosine Phosphatase Subfamilies.

Protein Tyrosine Phosphatases (PTPs) regulate cellular signaling by balancing phosphotyrosine levels through a conserved WPD-loop that switches betwee...

Machine learning prediction models for diabetic kidney disease: A systematic review and meta-analysis.

BACKGROUND: Machine learning (ML) has emerged as a promising tool for predicting diabetic kidney disease (DKD), yet the performance and clinical utili...

Beyond plaque and stenosis: Coronary inflammation imaging with the fat attenuation index.

Pericoronary adipose tissue (PCAT) imaging has emerged as a promising noninvasive marker of coronary inflammation and an adjunctive risk-stratificatio...

Integrated machine-learning-assisted wearable platform for stress state assessment based on sweat cortisol and multimodal physiological biosensing.

External stimuli can induce stress-related physiological states characterized by rapid autonomic and cardiovascular fluctuations and slower endocrine-...

Development and Validation of an Interpretable Machine Learning Model for Predicting In-Hospital Mortality in Diabetic Patients with Sepsis-Associated Acute Kidney Injury.

BackgroundSepsis-associated acute kidney injury (SA-AKI) is a common and severe complication in critically ill patients, with poor prognosis. Diabetes...

Identification of Vital Genes Common to Dilated and Hypertrophic Cardiomyopathy Using Machine Learning and Bioinformatics.

BACKGROUND: Heart failure (HF) is a complex clinical syndrome and a leading cause of hospitalization and mortality worldwide, with significantly incre...

Glycosylation-Associated Macrophage Signatures Define a Diagnostic Model for Diabetic Retinopathy via Single-Cell Analysis.

PURPOSE: Diabetic retinopathy (DR) remains a leading cause of vision loss, with macrophages and glycosylation dysregulation implicated in DR pathogene...

A Two-Stage Hybrid Feature Selection and Ensemble Learning Framework With Explainable AI for Accurate PCOS Prediction.

BACKGROUND AND AIMS: Polycystic ovary syndrome (PCOS) is the most prevalent endocrine ailment impacting women of reproductive age, distinguished by on...

A narrative review of what cohorts have taught us and how they have laid the foundation for much of our understanding of type 2 diabetes.

This narrative review provides a historical perspective on how observational research on type 2 diabetes has been developed and consolidated over the ...

Integrating Environmental Exposure Profiles with Temporal Transcriptomics: An Explainable Machine Learning Model for Cardiovascular Disease Risk Prediction and Biological Validation.

BACKGROUND: Cardiovascular disease (CVD) pathogenesis is strongly associated with environmental exposures and metabolic factors. This study aimed to i...

Assessing the performance of three large language models in thyroid cancer tumour board decision-making.

Large language models (LLMs) have potential to support clinical decision-making, but their role in thyroid cancer multidisciplinary team (MDT) meeting...

Deep Learning-Based Classification of NIFTP and Invasive Encapsulated Follicular Variant of Papillary Thyroid Carcinoma Using Gross Pathology Images.

Non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) and invasive encapsulated follicular variant of papillary thyroi...