Endocrinology

Self-supervised spectral-temporal denoising for dynamic deuterium metabolic imaging.

Dynamic deuterium metabolic imaging (DMI) enables time-resolved mapping of cerebral glucose metabolism in vivo, yet its intrinsically low SNR often renders voxel-wise metabolite quantification unstable-particularly at early repetitions. Low-rank denoising is widely used in MR spectroscopic imaging (MRSI)/DMI to improve robustness, but very low-SNR regimes and dynamic studies remain challenging. Se...

Matrix-Aware Electrochemical Sensing: A Neural Network Approach to Deciphering Medium-Specific Surface Dynamics.

Accurate monitoring in complex biofluids remains challenging due to unpredictable skin - electrode interfacial interference and matrix-dependent impedance variations. Here, we present an intelligent enzymatic microneedle platform that achieves calibration-efficient, matrix-adaptive, and drift-resilient high-fidelity sensing through a Nafion-shielded dual-mode architecture and an explainable feedfo...

Diabetes Care in 2050: A Human-Centered Road Map From Time in Range to Time in Happiness.

By 2050, diabetes care should transform into a human-centered, technology-augmented ecosystem focused on well-being. In this work, we first present a ...

Dual-View Thyroid Ultrasound Classification via Dual Knowledge Distillation.

OBJECTIVE: Thyroid ultrasound diagnosis in clinical practice typically relies on both transverse and longitudinal views of the same lesion. However, m...

Enhancing the performance of diabetic retinopathy grading models using synthetic images.

PURPOSE: To determine whether strictly curated synthetic images can improve grading performance in diabetic retinopathy (DR) diagnosis within limited ...

GENERALIZABILITY OF DEEP LEARNING MODELS FOR REFERABLE DIABETIC RETINOPATHY DETECTION: A CROSS-POPULATION STUDY.

PURPOSE: To evaluate cross-population performance of deep learning models for referable diabetic retinopathy (DR) detection and assess whether inclusi...

Machine learning-based identification of lactate metabolism-associated biomarkers in non-alcoholic fatty liver disease.

To determine lactate metabolism-associated biomarkers for non-alcoholic fatty liver disease (NAFLD). Based on NAFLD datasets from the gene expression ...

Integrative Transcriptomic Analysis Identifies a Key Candidate Gene Bridging Inflammation and DNA Repair in Endometriosis.

BACKGROUND: Endometriosis is a chronic, estrogen-dependent inflammatory disorder characterized by the ectopic implantation of endometrial-like tissue....

Enhanced prediction of coronary heart disease risk in diabetic patients via Machine learning incorporating multiple inflammatory and metabolic indices: A study with Dual-Cohort validation.

BACKGROUND: Coronary heart disease (CHD) remains a leading cause of mortality worldwide, with individuals with diabetes mellitus (DM) facing markedly ...

Development and validation of a LightGBM based machine learning model for predicting postoperative erectile dysfunction after robot assisted radical prostatectomy: a multicenter cohort study.

Postoperative erectile dysfunction remains a highly debilitating complication following robot assisted radical prostatectomy for localized prostate ca...

An Attention-Based Transformer Algorithm Integrated with YOLO Framework for Lesion Localization and Detection Diabetic Retinopathy.

Diabetic Retinopathy (DR) is one of the major causes of vision loss among diabetic patients across the globe, and it is a major challenge to the publi...

From Structure to Selectivity: Integrating CADD and AIDD in Rational Medicinal Chemistry Strategies for DYRK1A Inhibitor Discovery.

Dual specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A), a member of the CMGC kinase family, regulates diverse cellular processes and i...

Bioinformatics, Machine Learning and Functional Validation Reveal Mitophagy-Related FABP5 and HMOX1 as Diagnostic and Therapeutic Targets in Polycystic Ovary Syndrome.

Polycystic Ovary Syndrome (PCOS) is a heterogeneous endocrine-metabolic disorder characterized by ovulatory dysfunction, hyperandrogenism, and insulin...

Explainable machine learning model for early prediction of ICU death in chronic heart failure with pulmonary infection.

OBJECTIVE: To develop and validate a machine learning model for predicting ICU mortality in CHF patients with pulmonary infection. METHODS: Clinical d...

Comprehensive evaluation of angiogenesis-associated genes in papillary thyroid cancer using bulk RNA and single-cell sequencing data.

OBJECTIVE: The objective of this study is to explore the expression patterns of angiogenesis-related genes in papillary thyroid cancer (PTC) to enhanc...

UK recommendations for Ki-67 immunohistochemical staining and interpretation in breast cancer.

Ki-67 is a well-established marker of tumour proliferation and an important prognostic and predictive biomarker in breast cancer, particularly in horm...

Integrating omics and artificial intelligence in pediatric environmental health: tools, challenges, and cohort-based insights.

BACKGROUND: Early childhood is a critical developmental period during which exposure to multiple environmental chemicals is common and increasingly re...

A combi-elasto ultrasound based deep learning model on liver fibrosis staging for suspected MASLD/MASH patients.

OBJECTIVES: Metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH) weakened the ...

Integrated statistical and machine-learning optimization for enhanced heparosan production by Lactococcus lactis.

Lactococcus lactis SH6 was engineered for heterologous heparosan production, and its growth medium was optimized using a combination of experimental d...

Low vitamin D status and cardiometabolic trait clustering in a primary-care adult cohort: association analysis and exploratory explainable machine-learning classification.

BACKGROUND: Low serum 25-hydroxyvitamin D (25(OH)D) commonly co-exists with obesity and adverse cardiometabolic traits. However, its cross-sectional a...