Steroids

Automated abdominal aortic calcification and trabecular bone score independently predict incident fracture during routine osteoporosis screening.

Abdominal aortic calcification (AAC), a marker of subclinical cardiovascular disease, has previously shown to be associated with low BMD and fracture. However, it remains unclear whether AAC is associated with trabecular bone score (TBS), a gray-level textural measure, or whether it predicts fracture risk independent of this measure. Here, we examined the cross-sectional association of AAC scored ...

Dual-Signal Amplification Strategy for Synchronous Monitoring of Stress Hormones and Metabolic Indicators.

The synchronous monitoring of stress hormones and metabolic indicators is crucial for long-term health management, yet it remains a significant challenge for wearable sensors, primarily due to the ultralow abundance of biomarkers in sweat and the vulnerability of weak electrochemical signals to interference. Herein, we report a wearable electrochemical sensor based on a dual-signal amplification s...

Identification of biomarkers associated with endoplasmic reticulum stress-related cell death in osteoporosis based on bulk and single-cell transcriptomic analyses and experimental validation.

Osteoporosis (OP) is a metabolic bone disease characterized by low bone mineral density (BMD), and its pathogenesis involves endoplasmic reticulum (ER...

Nanoparticle-based immunotherapeutic strategies to overcome cancer drug resistance: From biological barriers to artificial intelligence-driven design.

Although cancer immunotherapy has revolutionized oncology, its clinical efficacy remains substantially limited by both primary and acquired resistance...

Small-molecule binding and sensing with a designed protein family.

The de novo design of small-molecule-binding proteins holds great promise as a potential tool to develop sensors on-demand for arbitrary small molecul...

Proteomic profiling and pathway analyses reveal molecular signatures and immune networks in pediatric sepsis.

BACKGROUND: Sepsis remains a leading cause of childhood mortality worldwide. Most deaths occur within the first few days of presentation, underscoring...

A Deep Learning-Driven Framework Integrating Organoid-Based Functional Validation Identifies Universal Neoantigens from Recurrent Glioma Mutations.

Glioblastoma (GBM) is the most common malignant intracranial tumor in adults, with a median survival of only 16-20 months. Neoantigen therapy has show...

Path forward: Cryoablation for colorectal liver metastases.

PURPOSE: Colorectal liver metastases (CRLM) are a leading cause of mortality in patients with colorectal cancer. While surgical resection is the stand...

Harnessing the gut microbiota in extra-intestinal cancers: from causal evidence to immunotherapy strategies.

The gut microbiota (GM) has emerged as a key modulator of cancer development and therapeutic response beyond the gastrointestinal tract. In extra-inte...

Severe COVID-19 in the Republic of Korea: Epidemiology, Risk Factors, Therapeutics, and Prognostic Models From Nationwide Data.

Severe coronavirus disease 2019 (COVID-19) has posed ongoing clinical and public health challenges worldwide, with Korea providing a unique perspectiv...

TCR recognition of peptide-HLA class II complexes in autoimmunity: Structural insights for therapeutic targeting.

Autoimmune diseases encompass a broad spectrum of disorders in which self-reactive T and B cells breach immune tolerance and drive chronic tissue infl...

Machine learning derived ORC6 as a hub biomarker for predicting tumor microenvironment, prognoses, and therapeutic responses in lung adenocarcinoma.

The origin recognition complex (ORC) is a DNA-binding complex composed of six subunits involved in DNA replication in cancer cells. The prognostic and...

Effect of PET-MPs exposure on the toxicology of PCOS: a multi-platform computational toxicology investigation.

Polyethylene terephthalate microplastics (PET-MPs) function as endocrine-disrupting agents that interfere with steroidogenesis and folliculogenesis, p...

Precision oncology meets nanotechnology: AI-driven liposomal nanocarriers for enhanced cancer immunotherapy.

The integration of artificial intelligence (AI) with nanotechnology is redefining therapeutic strategies in cancer immunotherapy and chemotherapy. The...

Teriparatide reduces spinal neuroinflammatory phenotypes in ovariectomized rats revealed by an artificial intelligence-driven glial cell morphometry of bright-field tissue sections.

Osteoporosis frequently presents with lower back pain, often accompanied by hypersensitivity, even in the absence of vertebral fractures, suggesting t...

Integrated single-cell and bulk transcriptomics reveals STAB1 as a novel therapeutic target for ovarian cancer.

The immunosuppressive tumor microenvironment (TME) and intrinsic heterogeneity of ovarian cancer (OC) are primary drivers of therapeutic resistance an...

Artificial intelligence models for osteoporosis risk prediction in postmenopausal women with CKD: A cross-sectional analysis of NHANES 2005 to 2018.

Artificial intelligence (AI) can transform osteoporosis (OP) screening, but its application in high-risk, complex populations like postmenopausal wome...

Explainable Artificial Intelligence for Predicting Length of Stay and Treatment Response in Pediatric Asthma and Allergic Rhinitis: An Irregular Fuzzy Cellular Automata Approach Across Pre- and During-COVID-19 Periods.

OBJECTIVE: The COVID-19 pandemic significantly altered treatment strategies and healthcare utilization patterns in pediatric respiratory diseases. Giv...

Advancing diagnostic equity through artificial intelligence chest radiograph screening for osteoporosis in Asian populations.

Early identification of abnormal bone mineral density (BMD) through opportunistic screening is critical for preventing osteoporotic fractures. We vali...

The challenges of artificial intelligence in dermatology for the immunosuppressed patient.