Steroids

Identification of potential biomarkers for osteoporosis and chronic kidney disease through bioinformatics and machine learning algorithm.

OBJECTIVE: The purpose of this study is to identify hub genes associated with both osteoporosis (OP) and chronic kidney disease (CKD) through bioinformatics analysis, and to explore the potential pathogenetic mechanisms in OP and CKD through these hub genes. METHODS: We downloaded the GSE15072 and GSE56815 datasets from the GEO database as training sets, and GSE7158 and GSE70528 for validation. Di...

Engineered artificial antigen-presenting cells for tumor immunotherapy: Design strategies, clinical applications, and translational challenges.

Immunotherapy has long played a pivotal role in cancer treatment, and antigen-presenting cell (APC)-based immunotherapy represents a promising strategy, though its full potential remains to be realized. This therapy stimulates T cell activation and proliferation through APCs, producing therapeutic effects. However, the use of natural APCs in immunotherapy faces several limitations, including ineff...

Contemporary heart failure evidence in 2025: a joint summary of key trials from the European Journal of Heart Failure and ESC Heart Failure Journal.

Heart failure (HF) remains a major global health challenge, characterized by high morbidity, mortality, and healthcare costs despite substantial advan...

The Use of Statistical Shape and Appearance Modelling for Predicting Osteoporotic Fracture Risk.

PURPOSE OF REVIEW: Osteoporotic fractures remain a major cause of morbidity and mortality worldwide. Current clinical assessment metrics (e.g., bone m...

A prognostic model based on nucleotide metabolism genes in osteosarcoma.

Osteosarcoma typically arises during adolescence, posing a significant challenge. Despite comprehensive treatment strategies encompassing surgery, rad...

Interpretable LightGBM model for predicting postoperative gastrointestinal hemorrhage in elderly hip fracture patients: leveraging systemic inflammation and medication exposures for personalized risk stratification.

BACKGROUND: Postoperative gastrointestinal (GI) bleeding is a serious complication after hip fracture surgery in older adults, yet perioperative risk ...

An Integrated Clinical-Histopathologic Prediction Model for Cardiac Allograft Rejection: Translating Machine Learning into Clinical Risk Frameworks.

BACKGROUND: Cardiac allograft rejection (CAR) remains the leading cause of early graft failure after heart transplantation (HT). Current diagnostics, ...

Synthetic inducible bacteria normalize the microenvironment of refractory tumors, potentiating checkpoint inhibitor responses.

Immunotherapy has transformed cancer treatment but remains ineffective in many solid tumors, largely due to the immunosuppressive tumor microenvironme...

Assessing osteosarcopenia using automated multi-structure-segmentation and Hounsfield unit-based analysis of lumbar muscles and vertebral bodies on computed tomography.

Sarcopenia and osteoporosis are prevalent age-related conditions that substantially increase the risk of falls, fractures, and functional decline. Thi...

Identification and Screening of Lactate-Related Genes as Molecular Markers for Early Diagnosis of Steroid-Induced Osteonecrosis of the Femoral Head.

Steroid-induced osteonecrosis of the femoral head (SONFH) is a major cause of disability among young and middle-aged adults. However, current diagnosi...

Unsupervised clustering analysis reveals distinct postoperative cortisol trajectories following pituitary adenoma resection in Cushing's disease.

Rotenone impairs osteoclastogenesis by inhibiting cell migration: insights from machine learning.

PURPOSE: The migration and fusion of osteoclast precursors (OCPs) are critical steps in osteoclastogenesis and require substantial energy. Although ox...

Response to comment on "Assessing deep learning model performance in osteoporosis screening with lumbar spine radiographs".

Resolving the ambiguous binding site of quercetin at the calcineurin subunit junction using funnel metadynamics with deep learning collective variables.

Calcineurin represents a prominent target for immunosuppressive drugs, where conventional macrocyclic inhibitors utilize an immunophilin-dependent mec...

OCTN1 variants shape innate immunity and predict individual response to anti-TNFα in ulcerative colitis patients: An exploratory study.

BACKGROUND: Ulcerative colitis (UC) exhibits substantial heterogeneity in inflammatory pathways and therapeutic response. The organic cation transport...

Beyond HLA-Ia: A multidimensional framework for Neoantigen immunotherapy.

Glioblastoma (GBM) and other malignant gliomas are associated with aggressive progression, high recurrence rates, and poor long-term outcomes, while c...

DrugGPS: Attention-guided multimodal fusion for intelligent exploration of drug-target and drug-disease interactions.

BACKGROUND AND PURPOSE: Accurate prediction of drug-target interactions (DTIs) and drug-disease interactions (DDIs) are critical for accelerating the ...

Automated Eosinophil Quantification Using Deep Learning to Predict Therapy Escalation in Pediatric Ulcerative Colitis.

BACKGROUND: Emerging evidence implicates eosinophils as important modulators of disease activity and therapeutic response in ulcerative colitis. Autom...

A machine learning-driven framework integrating cell death and senescence signatures for multi-target drug design and immunotherapy optimization in ovarian cancer.

Ovarian cancer (OC) remains therapeutic challenge due to its complex molecular heterogeneity and therapy-induced adaptive resistance. While non-apopto...

Biological effects of ultrasonic cavitation in cancer therapy: from physics to mechanobiology.

The therapeutic efficacy of systemic treatments in cancer therapy is invariably limited by the biophysical barriers, including vascular endothelial ba...