Steroids

Machine Learning and Molecular Modeling Reveal HDAC6 as a Key Target of Tanshinone IIA in Multiple Myeloma.

Multiple myeloma (MM) is a malignant blood cancer marked by severe bone destruction and immune microenvironment disruption. Yet relapse and drug resistance remain major clinical challenges. Tanshinone IIA (TIIA) exhibits potent antitumor activity, but its molecular targets and mechanisms in MM remain unclear. Here, we systematically elucidate TIIA's pharmacological mechanisms in MM using network p...

Machine learning identifies ac4C-related prognostic signature and TUBA1C as therapeutic target in COAD.

To explore the role of N4-acetylcytidine (ac4C)-related genes (acRGs) in colon adenocarcinoma (COAD) and identify reliable prognostic biomarkers and potential therapeutic targets. Multi-source transcriptomic datasets (TCGA-COAD, GSE39582, GSE17536) and single-cell RNA-seq data were analyzed. Ten machine learning algorithms were integrated to construct an acRG-based prognostic signature (acRGBS). I...

Unsupervised machine learning with Cluster Analysis in patients with rheumatoid arthritis: insights in CV risk phenotypes from a multicentre Italian cohort.

Rheumatoid arthritis (RA) patients face increased cardiovascular (CV) risk, yet existing 10-year estimation tools often underperform. This study evalu...

AI for Opportunistic Identification of BMD and Bone Microarchitecture: A Narrative Review.

Artificial intelligence (AI) has rapidly transformed the potential for opportunistic assessment of bone mineral density (BMD) and bone microarchitectu...

Targeting GLUTs in Cancer: Mechanisms, Combination Strategies, and Translational Challenges.

Cancer cells exhibit metabolic reprogramming, most notably the Warburg effect, which underscores their heightened dependency on glucose uptake facilit...

Machine learning models for early detection of urinary tract infections in kidney transplant patients.

BACKGROUND: Renal transplantation is the preferred treatment for end-stage chronic kidney disease but requires lifelong immunosuppression, increasing ...

Peptide Therapeutics for Solid Tumors: Functional Classes, AI-Enhanced Discovery and Clinical Advances.

Solid tumors, the most prevalent form of malignancy, pose therapeutic challenges distinct from hematologic malignancies due to their complex biology, ...

Development of a Multimodal Machine Learning Model for Predicting Second Osteoporotic Vertebral Compression Fractures.

PURPOSE: Osteoporosis increases the probability of osteoporotic vertebral compression fractures (OVCF), and the resultant pain severely limits physica...

Artificial Intelligence in Xenotransplantation: A Prioritized Roadmap for Early Clinical Translation, Opportunities and Challenges.

Xenotransplantation represents a potential solution to the persistent global organ shortage, yet its clinical application remains stalled by complex i...

Machine Learning-Driven Bioprospecting of Cholinergic Medicinal Plants for Putative Leads Against Butyrylcholinesterase Towards Alzheimer's Care.

Butyrylcholinesterase (BChE) plays a key role in preserving appropriate cholinergic neurotransmission that is essentially altered in the brains of adv...

Deep learning approaches to predict femoral neck T-score and osteopenia/osteoporosis status from wrist accelerometry data.

Osteoporosis is a prevalent condition with substantial health and economic implications. Although physical activity is associated with bone health, th...

Application of Artificial Intelligence in Diagnosis and Management of Thyroid Disease.

Artificial intelligence (AI) is transforming thyroid care, with applications spanning ultrasound risk stratification, cytopathology, histopathology, r...

Myocardial Fibrosis in Pediatric Heart Disease: Mechanisms, Imaging Biomarkers, Clinical Consequences, and Emerging Antifibrotic Therapies.

Myocardial fibrosis is increasingly recognized as a central determinant of adverse cardiac remodeling and long-term cardiovascular outcomes in childre...

Comparison of dual-energy X-ray absorptiometry and lumbar radiographs using deep learning for osteoporosis diagnosis.

INTRODUCTION: Osteoporosis and osteopenia, characterized by reduced bone mineral density (BMD), increase fracture risk, particularly in older adults. ...

Generative AI and Clinicians Show Comparable Prognostic Reasoning From Clinical Narratives in Biologic-Treated CRSwNP.

OBJECTIVE: To compare the ability of large language models (LLMs) and otolaryngologists to identify prognostic signals from brief clinical vignettes i...

Integrated machine-learning-assisted wearable platform for stress state assessment based on sweat cortisol and multimodal physiological biosensing.

External stimuli can induce stress-related physiological states characterized by rapid autonomic and cardiovascular fluctuations and slower endocrine-...

Targeting Airway Remodeling in Severe Asthma: Is There a Window of Opportunity for Biologic Therapy Predicting Effects Using Causal Artificial Intelligence?

Airway remodeling is increasingly recognized as a major determinant of asthma progression, fixed airflow limitation, and long-term morbidity, particul...

Machine learning-based screening model for osteoporosis in Chinese postmenopausal women: a nationwide study with prospective fracture validation.

UNLABELLED: This study develops a machine learning model to predict osteoporosis in Chinese postmenopausal women. The model was trained using the larg...

Integrated multi-omics and functional analyses reveal a GDCA-TGR5-mediated immunometabolic signature in anorexia nervosa.

BACKGROUND: Anorexia nervosa (AN) is frequently accompanied by metabolic disturbances and immune dysregulation, yet its peripheral molecular mechanism...

A clinical decision support tool for accurate hip fracture prediction: A nationwide cohort study.

BACKGROUND: Although hip fractures are commonly associated with functional decline, increased morbidity, and mortality, accurate models for both short...