Menopause

Machine learning-guided discovery of withangulatin A as a novel inducer of megakaryocytic differentiation through direct targeting of TYK2 in leukemia.

BACKGROUND: Leukemia is an aggressive hematological malignancy. Effective differentiation-inducing agents for non-acute promyelocytic leukemia (non-APL), especially those derived from natural products, remain unavailable. Withanolides isolated from Physalis angulata var. villosa possess diverse anticancer activities, yet their potential to induce leukemia cell differentiation has not been systemat...

Integration of metabolomics and machine learning algorithm for discovery of early diagnostic biomarkers of osteoporosis.

BACKGROUND: Osteoporosis (OP) is a prevalent metabolic bone disorder and a major public health concern characterized by reduced bone mass and bone microstructural deterioration. Early identification of osteoporosis and implementation of preventive interventions remain critical for reducing fracture risk and disease burden. Identifying plasma biomarkers reflecting metabolic alterations related to O...

Pharmacogenomics in oncology: mutation-targeted therapy and biomarker integration in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is the most common cancer-related cause of death among all countries globally, mostly because of late diagnosis, he...

The Role of Artificial Intelligence in Addressing Menopausal Mental Health Challenges.

Menopause marks a crucial transition in a woman's life and is often accompanied by physical and psychological changes that can adversely affect mental...

Bidirectional microbiota-cancer crosstalk: Emerging platforms for advanced diagnostics and precision therapeutics in oncology.

Cancer is among the major causes of morbidity and mortality worldwide, and current treatment methods are limited by various drawbacks such as drug res...

Environmental space similarity model maps dry red soil under limited samples in the Yuanmou Dry Hot Valley.

Obtaining sufficient field observations for natural resources in complex mountainous environments is often constrained by limited soil samples. Geogra...

Personalized survival prediction in elderly dialysis patients: integrating machine learning with traditional survival analysis.

BACKGROUND: Elderly patients undergoing kidney replacement therapy (KRT) face high mortality rates. Traditional statistical models describe overall su...

Disparities in severe infection risk associated with systemic lupus erythematosus: evidence from a causal forest analysis.

OBJECTIVES: Severe infections are a primary cause of morbidity and premature mortality in patients with Systemic Lupus Erythematosus (SLE). Although S...

Integration of inflammatory and nutritional biomarkers with machine learning enhances prediction of progesterone response in fertility-preserving endometrial carcinoma management.

BACKGROUND: Endometrial carcinoma (EC) and atypical endometrial hyperplasia (AEH) increasingly affect young women, posing challenges for fertility pre...

Non-advanced age-related macular degeneration: current concepts and future perspectives.

Non-advanced age-related macular degeneration (AMD), encompassing early and intermediate stages, represents a critical therapeutic window before irrev...

A deep learning model to predict objective response to TACE and TKI-based therapy in HBV-related uHCC.

TACE and TKI-based combination therapy shows promise for unresectable hepatocellular carcinoma (uHCC), but inter-patient heterogeneity requires reliab...

Agreement, calibration, and failure of three large language models as high-stakes multimodal ospe graders: a comparative psychometric analysis.

BACKGROUND: Medical education faces increasing demand for scalable grading solutions. Large language models have been proposed as automated graders fo...

Engineering EVs Via ZnBGs-Integrated 3D Dynamic Culture for Type II Diabetic Pressure Ulcer Therapy.

Pressure ulcers (PUs) under type II diabetic conditions pose a significant clinical challenge due to damage to the vascular and neural networks, a sit...

Artificial intelligence advancements for orthopaedic clinical reasoning: longitudinal assessment of newer models (ChatGPT-5, Grok-3, Gemini 2.5 Flash) compared to clinicians.

INTRODUCTION: This descriptive study aimed to longitudinally evaluate the performance of contemporary large language models - ChatGPT-5, Gemini 2.5 Fl...

Effects of 5D built environment and non-built-environment factors on injury crash risk: An interpretable machine learning analysis.

To identify the key determinants of traffic injury risk and clarify the relative roles of built environment factors and crash-context factors, this st...

GAN-Augmented Radiomics and Machine Learning for Post-Therapy GBM Progression Assessment.

OBJECTIVE: Differentiating true progression (TP) from pseudoprogression (PsP) in post-therapy of glioblastoma multiforme (GBM) remains a critical chal...

Interpretable machine learning model of contrast-enhanced CT radiomics for predicting post-BCG recurrence in high-grade non-muscle-invasive bladder cancer.

BACKGROUND AND PURPOSE: While intravesical Bacillus Calmette-Guérin Vaccine (BCG) instillation remains standard adjuvant therapy for high-grade non-mu...

M3FusionNet: Cross-cohort multimodal prediction of breast cancer biomarkers.

BACKGROUND: Accurate prediction of breast cancer biomarkers - including oestrogen receptor (ER), progesterone receptor (PR), human epidermal growth fa...

A Unified Molecular Graph and Protein Language Model Framework for Predicting Human Drug-Hormone Receptor Interactions with Structure-Aware Validation.

Hormones regulate many essential biological processes by interacting with specific receptors that control gene expression, metabolism, growth, and imm...

A comparative evaluation of large language models in diagnosis and treatment planning in restorative dentistry.

OBJECTIVE: With the advancement of artificial intelligence (AI), large language models (LLMs) have become an alternative source of information in dent...