Endocrinology

Emerging innovations in ophthalmic drug delivery for diabetic retinopathy: a translational perspective.

Diabetic retinopathy (DR) is a progressive microvascular complication of diabetes and a leading cause of vision impairment worldwide. Despite advancements in pharmacotherapy, challenges such as poor intraocular bioavailability, rapid drug clearance, and the restrictive blood-retinal barrier hinder effective treatment. Recent innovations in ophthalmic drug delivery systems offer promising solutions...

Modification and applications of glucose oxidase: optimization strategies and high-throughput screening technologies.

Glucose oxidase (GOD), an oxidoreductase (EC 1.1.3.4), catalyzes the oxidation of β-D-glucose to gluconic acid using molecular oxygen as the electron acceptor, with concomitant generation of hydrogen peroxide. Owing to its versatile catalytic properties, GOD has garnered significant attention across diverse fields, including food and beverage manufacture, agriculture, biosensors and biotechnology....

Integrating Artificial Intelligence in Thyroid Nodule Management: Clinical Outcomes and Cost-Effectiveness Analysis.

OBJECTIVE: The increasing incidence of thyroid nodules (TN) raises concerns about overdiagnosis and overtreatment. This study evaluates the clinical a...

Prediabetes phenotypes: can aetiology and risk profile guide lifestyle strategies for diabetes prevention?

INTRODUCTION: Type 2 diabetes (T2D) continues to worsen globally alongside rise in obesity. Asymptomatic dysglycaemia, which precedes T2D, provides op...

Accurate and real-time brain tumour detection and classification using optimized YOLOv5 architecture.

The brain tumours originate in the brain or its surrounding structures, such as the pituitary and pineal glands, and can be benign or malignant. While...

Identification and validation of epithelial‑mesenchymal transition‑related genes for diabetic nephropathy by WGCNA and machine learning.

Diabetic nephropathy (DN) is the main cause of end‑stage renal disease, with epithelial‑mesenchymal transition (EMT) serving a key role in its initiat...

Size-Specific Predictors for Malignancy Risk in Follicular Thyroid Neoplasms: Machine Learning Analysis.

BACKGROUND: Surgeons often face challenges in distinguishing between benign and malignant follicular thyroid neoplasms (FTNs), particularly small tumo...

Diagnostic immune-related markers for diabetic kidney disease: a bioinformatics and machine learning approach.

OBJECTIVE: Diabetic kidney disease (DKD) is a leading cause of chronic kidney disease, with chronic inflammation driving its progression. This study a...

Exhaled gas biomarkers: a non-invasive approach for distinguishing diabetes and its complications.

Exhaled gas detection offers a safe, convenient, and non-invasive clinical diagnostic method for preventing the progression of diabetes to complicatio...

Multiparametric ultrasound techniques are superior to AI-assisted ultrasound for assessment of solid thyroid nodules: a prospective study.

OBJECTIVES: To evaluate the diagnostic performance of multiparametric ultrasound (mpUS) and AI-assisted B-mode ultrasound (AI-US), and their potential...

MRI-based interpretable clinicoradiological and radiomics machine learning model for preoperative prediction of pituitary macroadenomas consistency: a dual-center study.

PURPOSE: To establish an interpretable and non-invasive machine learning (ML) model using clinicoradiological predictors and magnetic resonance imagin...

Integrated Nanopore and short-read RNA sequencing identifies dysregulation of METTL3- m6A modifications in endocrine therapy- sensitive and resistant breast cancer cells.

The role of epitranscriptomic changes in the development of acquired endocrine therapy (ET)- resistance in estrogen receptor α (ER) expressing breast ...

Exploring graph-based models for predicting active compounds against triple-negative breast cancer.

Breast cancer is among the most dominant and rapidly rising cancers, both in India and around the world. Triple-negative breast cancer (TNBC) is one o...

Transformer optimization with meta learning on pathology images for breast cancer lymph node micrometastasis.

Lymph node micro-metastasis represents the initial stage of breast cancer spread or metastasis. However, the limited size of these hidden lesions rest...

Diabetic retinopathy detection using adaptive deep convolutional neural networks on fundus images.

Diabetic retinopathy (DR) is an age-related macular degeneration eye disease problem that causes pathological changes in the retinal neural and vascul...

Differentiated thyroid cancer and positron emission computed tomography: when, how and why?

INTRODUCTION: Fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) has become an indispensable tool in oncology, offering ...

AI-enhanced patient-specific dosimetry in I-131 planar imaging with a single oblique view.

This study aims to enhance the dosimetry accuracy in I planar imaging by utilizing a single oblique view and Monte Carlo (MC) validated dose point ker...

Machine learning models using non-invasive tests & B-mode ultrasound to predict liver-related outcomes in metabolic dysfunction-associated steatotic liver disease.

Advanced metabolic-dysfunction-associated steatotic liver disease (MASLD) fibrosis (F3-4) predicts liver-related outcomes. Serum and elastography-base...

Enhancing diabetes risk prediction through focal active learning and machine learning models.

To improve the effectiveness of diabetes risk prediction, this study proposes a novel method based on focal active learning strategies combined with m...

The evolving therapeutic landscape of Graves' disease in adults: present and future.

The therapeutic landscape of Graves' hyperthyroidism has been rapidly evolving in the last few years. There has been a shift worldwide towards antithy...