Endocrinology

Integrative network toxicology and experimental evidence reveal mechanisms underlying diethyl phthalate-induced initiation and progression of endometrial cancer.

Diethyl phthalate (DEP) is a ubiquitous environmental endocrine-disrupting chemical (EDC). Epidemiological studies have suggested a potential association between DEP exposure and an increased risk of endometrial cancer (EC); however, its underlying molecular mechanisms remain largely unclear. Four GEO datasets were integrated, and differential expression analysis combined with weighted gene co-exp...

Prediction of malignancy and metastasis of thyroid cancer by combined feature sets through advanced machine learning.

Artificial Intelligence-based analysis of pre-eclampsia gene expression profiles for identification of novel potential pre-eclampsia diagnostic biomarkers.

Preeclampsia (PE) is a multifactorial and heterogeneous hypertensive disorder of pregnancy that poses significant diagnostic and therapeutic challenge...

Environmental bisphenols hijack the Hmox1 and Cdh1 to trigger premature ovarian insufficiency: A multi-omics investigation.

BACKGROUND: Bisphenols A (BPA), bisphenols F (BPF), and bisphenols S (BPS) are environmental endocrine disruptors linked to premature ovarian insuffic...

Modularly-Assembled Smart Microneedle Platform for Machine Learning-Driven Personalized Health Monitoring.

Given the inherent complexity of metabolic pathways and disease-associated agents, next-generation healthcare necessitates wearable, non-invasive, and...

Precision imaging and evolving therapies in paragangliomas and pheochromocytomas: from molecular diagnostics to imaging-guided management.

Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors originating from neural crest-derived chromaffin tissue, marked by clinica...

Personalized Diabetes Treatment Support Using Large Language Models Fine-Tuned on Electronic Health Records: Development and Evaluation Study.

BACKGROUND: Effective diabetes management requires individualized treatment strategies tailored to patients' clinical characteristics. With recent adv...

High-Resolution MRI Using Artificial Intelligence-Assisted Acceleration and Radial Dynamic Contrast Enhancement for Improved Detection of Pituitary Microadenomas in Cushing's Disease.

BACKGROUND AND PURPOSE: Accurate detection of pituitary microadenomas is critical for the diagnosis and treatment of Cushing's disease (CD). However, ...

Explainable AI-based analysis of human pancreas sections identifies traits of type 2 diabetes.

Type 2 diabetes (T2D) is a chronic disease currently affecting around 500 million people worldwide with often severe health consequences. Yet, histopa...

Individualized gamma knife radiosurgery prescription dosing for pituitary adenomas: development and internal validation of a feedforward neural network model.

BACKGROUND: Gamma Knife radiosurgery (GKRS) is an established treatment for pituitary adenomas yet prescription dose selection is often guided by clin...

Targeting the MPO/LCN2/GMPPB axis in IBS-depression comorbidity: Integrated multi-omics and bidirectional network pharmacology for precision diagnostics and therapeutics.

BACKGROUND: Irritable Bowel Syndrome (IBS) and Major Depressive Disorder (MDD) exhibit high comorbidity, driven by dysregulation of gut-brain axis int...

Which bot is best? Accuracy and readability of generative artificial intelligence assistant responses on adrenal nodules.

INTRODUCTION: Patients increasingly use generative artificial intelligence assistants (chatbots) for medical information. We examined surgeon-perceive...

PCOSFusionNet: Hybrid Deep Feature Fusion Network for PCOS Classification from Ultrasound Images of Ovaries.

Polycystic Ovary Syndrome (PCOS) is a leading cause of female infertility and is associated with various health complications, including preterm abort...

Factors Associated with Machine Learning-Based Predictions of Retinal Aging Using Teleretinal Screening Images from Patients with Diabetes.

PURPOSE: To identify factors associated with accelerated retinal aging based on machine learning predictions of age using fundus images from teleretin...

The Burden of Delayed Diabetic Retinopathy Management and Use of Artificial Intelligence-Driven Screening Tools: A Systematic Literature Review.

PURPOSE: Patients with diabetic retinopathy (DR) are at risk of visual deterioration owing to systemic and financial barriers in accessing appropriate...

LightGBM-guided discovery of mechanistic biomarkers in thyroid cancer: GALNT7 and SKP1P1 emerge as therapeutic targets.

Machine learning-assisted multi-aptamer encoding enables pattern-level discrimination of HbA1c in complex biological matrices.

Multidisciplinary Team Diagnosis and Treatment of well-differentiated thyroid carcinoma: Current Landscape and Future Prospects.

BACKGROUND: The incidence of thyroid cancer has increased markedly in recent years, largely driven by well-differentiated thyroid carcinoma (WDTC). WD...

Using Machine Learning to Identify Infant and Child Environmental and Biological Predictors of Callous-Unemotional Traits.

Callous-unemotional (CU) traits (i.e., blunted affect, low guilt) develop through the interplay of neurophysiological and environmental factors. Howev...

Developing and validating a machine learning model for predicting post-thrombolysis seizures in acute ischemic stroke.

Post-stroke seizures (PSS) manifests variably due to ischemic brain injury, yet its risk factors remain unclear. This study developed a machine learni...