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Inside a Metastatic Fracture: Molecular Bases and New Potential Therapeutic Targets.

Cancer medicine
INTRODUCTION: Bone metastases and pathological fractures significantly impact the prognosis and quality of life in cancer patients. However, clinical and radiological features alone have been shown to fail to predict skeletal related events of a bone...

Root of Prunus persica (taoshugen) ameliorated renal fibrosis by inhibiting TGF-β signaling via upregulating Pmepa1 in mice with unilateral ureter obstruction.

Journal of ethnopharmacology
ETHNOPHARMACOLOGICAL RELEVANCE: Various parts of Prunus persica (L.) Batsch (peach) exhibit medicinal properties and are utilized in traditional Chinese medicine (TCM) for therapeutic purposes. Notably, the root of P. persica, referred to as "taoshug...

Machine learning-based integration reveals immunological heterogeneity and the clinical potential of T cell receptor (TCR) gene pattern in hepatocellular carcinoma.

Apoptosis : an international journal on programmed cell death
The T Cell Receptor (TCR) significantly contributes to tumor immunity, whereas the intricate interplay with the Hepatocellular Carcinoma (HCC) microenvironment and clinical significance remains largely unexplored. Here, we aimed to examine the functi...

Deciphering the dark cancer phosphoproteome using machine-learned co-regulation of phosphosites.

Nature communications
Mass spectrometry-based phosphoproteomics offers a comprehensive view of protein phosphorylation, yet our limited knowledge about the regulation and function of most phosphosites hampers the extraction of meaningful biological insights. To address th...

Fine-Tuned Deep Transfer Learning Models for Large Screenings of Safer Drugs Targeting Class A GPCRs.

Biochemistry
G protein-coupled receptors (GPCRs) remain a focal point of research due to their critical roles in cell signaling and their prominence as drug targets. However, directly linking drug efficacy to the receptor-mediated activation of specific intracell...

Logic-based machine learning predicts how escitalopram attenuates cardiomyocyte hypertrophy.

Proceedings of the National Academy of Sciences of the United States of America
Cardiomyocyte hypertrophy is a key clinical predictor of heart failure. High-throughput and AI-driven screens have the potential to identify drugs and downstream pathways that modulate cardiomyocyte hypertrophy. Here, we developed LogiRx, a logic-bas...

Integrative analysis of signaling and metabolic pathways, immune infiltration patterns, and machine learning-based diagnostic model construction in major depressive disorder.

Scientific reports
Major depressive disorder (MDD) is a multifactorial disorder involving genetic and environmental factors, with unclear pathogenesis. This study aims to explore the pathogenic pathway of MDD and its relationship with immune responses and to discover i...

Oxidative Phosphorylation Pathway in Ankylosing Spondylitis: Multi-Omics Analysis and Machine Learning.

International journal of rheumatic diseases
INTRODUCTION: Ankylosing spondylitis (AS) is a chronic inflammatory disease affecting the axial skeleton, characterized by immune microenvironment dysregulation and elevated cytokines like TNF-α and IL-17. Mitochondrial oxidative phosphorylation (OXP...

Identification of hub biomarkers in coronary artery disease patients using machine learning and bioinformatic analyses.

Scientific reports
Understanding the molecular underpinnings of CAD is essential for developing effective therapeutic strategies. This study aims to identify and analyze differentially expressed hub biomarkers in the peripheral blood of CAD patients. Based on RNA-seq d...