Steroids

Activated Cancer-Associated Fibroblasts Are Associated with Immunosuppression and Poor Prognosis in Clear Cell Renal Cell Carcinoma.

INTRODUCTION: Clear cell renal cell carcinoma (ccRCC) exhibits substantial heterogeneity within its tumor microenvironment, contributing to variable clinical outcomes. The prognostic significance and molecular characteristics of cancer-associated fibroblasts in ccRCC remain poorly defined. METHODS: We analyzed 736 ccRCC cases (203 institutional and 533 TCGA) to identify histologically distinct act...

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 health. Depression, anxiety, cognitive changes, and sleep disturbances are common during the menopausal transition, yet they are frequently underdiagnosed and undertreated, particularly in lowand middle-income countries. Emerging technologies, espec...

MAPPING THE MTOR PATHWAY IN LUNG TRANSPLANTATION: IS IT TIME FOR A BIOMARKER-DRIVEN PRECISION THERAPY?

Solid organ transplantation has revolutionized the treatment of end-stage diseases, yet long-term graft survival remains constrained by immune-mediate...

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...

A classification model for predicting corticosteroid and cyclosporin: A responsiveness in pediatric idiopathic uveitis.

BACKGROUND: To identify serum metabolic biomarkers that distinguish corticosteroid and cyclosporin A (CS & CsA) resistant pediatric idiopathic uveitis...

Dysregulated glucocorticoid-responsive immune genes in peripheral blood mononuclear cells as a shared molecular signature of autism spectrum disorder and irritable bowel syndrome.

BACKGROUND: Autism spectrum disorder (ASD) is frequently accompanied by gastrointestinal (GI) disturbances resembling irritable bowel syndrome (IBS). ...

Integrative profiling of senescence-associated cells and genes identifies UGT1A7 as a prognostic and therapeutic target in Lung squamous cell carcinoma.

Lung Squamous Cell Carcinoma (LUSC), a common subtype of non-small cell lung cancer, primarily occurs in elderly individuals and is closely linked to ...

Astragalus polysaccharide-based thermoresponsive hydrogel loaded with β-elemene nanoemulsion in combination with anti-PD-L1 therapy for triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is classified as an immunologically cold tumor, which markedly weakens the therapeutic efficacy of immune checkpo...

Using machine learning to discriminate non-classical 21-hydroxylase deficiency from polycystic ovary syndrome: an external validation study.

INTRODUCTION: Nonclassical 21-hydroxylase deficiency (NC21OHD) is a rare autosomal recessive disorder that is frequently misdiagnosed as polycystic ov...

Integrative transcriptomics, machine learning, and molecular docking derive a DAM-like macrophage signature for risk stratification and therapeutic nomination in glioblastoma.

Glioblastoma presents a significant challenge for drug development due to its complex immunosuppressive microenvironment. Identifying candidate therap...

Spatial transcriptome and single-cell reveal the role of sorbitol metabolism in hepatocellular carcinoma progression and tumor microenvironment.

BACKGROUND: Metabolic reprogramming represents a hallmark feature of hepatocellular carcinoma (HCC). As a crucial branch of the polyol pathway, the bi...

A predictive tool incorporating frailty scores for perioperative risk assessment in patients with spinal metastasis: a national retrospective cohort study.

BACKGROUND: Surgical treatment for spinal metastases is associated with high perioperative risk due to tumor burden, neurologic compromise, and limite...

Modeling Dyadic Interdependence in Endocrine Functioning: A Multilevel Machine Learning Study of Adults with Cancer and Their Caregivers.

OBJECTIVE: This study evaluated dyadic endocrine interdependence among cancer patients and their spousal caregivers using a machine learning (ML) fram...

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...

TREM2 in glioma: Reprogramming the immune microenvironment from mechanistic understanding to clinical translation (Review).

The poor prognosis of high‑grade gliomas, such as glioblastoma, is largely driven by a notably immunosuppressive tumor microenvironment (TME), wherein...

Prediction of Acromial and Scapular Spine Fractures After Reverse Total Shoulder Arthroplasty using Machine Learning: A Retrospective Cohort Study.

BACKGROUND: Acromial and scapular spine fractures (ASSF) are an uncommon but significant complication following reverse total shoulder arthroplasty (r...

Body composition's effect on the bone-vascular axis of osteoporosis discovered in AI-based CT analysis of COPD patients.

OBJECTIVES: This study aimed to investigate the effect of body composition on the inverse relationship between vertebral bone density (T12 BMD) and to...

Multi-omics and metabolic flux modeling reveal that macrophage CYP27A1-derived 26-hydroxycholesterol drives immunosuppression and cancer malignancy.

Emerging evidence indicates that aberrant cholesterol metabolism in macrophages plays a role in tumorigenesis, however, how specific metabolites relea...

Leveraging multimodal cancer immunotherapy to amplify the efficacy of oncolytic viruses.

Oncolytic viruses (OVs) represent a versatile platform for cancer immunotherapy, capable of selectively infecting and lysing tumor cells while trigger...

An explainable machine learning model for predicting one-year osteoporosis risk: development and validation in a prospective cohort.

OBJECTIVE: This study aimed to develop and validate an interpretable machine learning model using readily available biochemical indicators to predict ...