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Acute myeloid leukaemia (AML) is a highly heterogeneous disease, which lead to various findings in transcriptomic research. This study addresses these challenges by integrating 34 datasets, including 26 control groups, 6 prognostic datasets and 2 single-cell RNA sequencing (scRNA-seq) datasets to identify 10,000 AML-related genes (ARGs). We focused on genes with low variability and high consistency and successfully discovered 191 AML signatures (ASs). Leveraging machine learning techniques, specifically the XGBoost model and our custom framework, we classified AML subtypes with both scRNA-seq and bulk RNA-seq data, complementing the ELN2022 classification approach. Our research also identified promising treatments for AML through drug repurposing, with solasonine showing potential efficacy for high-risk AML patients, supported by molecular docking and transcriptomic analyses. To enhance reproducibility and customizability, we developed CSAMLdb, a user-friendly database platform. It facilitates the reuse and personalized analysis of nearly all results obtained in this research, including single-gene prognostics, multi-gene scoring, enrichment analysis, machine learning risk assessment, drug repositioning analysis and literature abstract named entity recognition. CSAMLdb is available at http://www.csamldb.com., (© 2024 The Author(s). Journal of Cellular and Molecular Medicine published by Foundation for Cellular and Molecular Medicine and John Wiley & Sons Ltd.)

The application of ChatGPTin the medical field has sparked debate regarding its accuracy. To address this issue, we present a Multi-Role ChatGPT Framework (MRCF), designed to improve ChatGPT's performance in medical data analysis by optimizing prompt words, integrating real-world data, and implementing quality control protocols. Compared to the singular ChatGPT model, MRCF significantly outperforms traditional manual analysis in interpreting medical data, exhibiting fewer random errors, higher accuracy, and better identification of incorrect information. Notably, MRCF is over 600 times more time-efficient than conventional manual annotation methods and costs only one-tenth as much. Leveraging MRCF, we have established two user-friendly databases for efficient and straightforward drug repositioning analysis. This research not only enhances the accuracy and efficiency of ChatGPT in medical data science applications but also offers valuable insights for data analysis models across various professional domains. [ABSTRACT FROM AUTHOR]

Cardiac ischemia, hypoxia, arrhythmias, and heart failure share the common electrophysiological changes featured by the elevation of intracellular Ca2+ (Ca2+ overload) and inhibition of the inward rectifier potassium (IK1) channel. IK1 channel agonists have been considered a new type of anti‐arrhythmia and cardioprotective agents. We predicted using a drug repurposing strategy that tetramisole (Tet), a known anthelminthic agent, was a new IK1 channel agonist. The present study aimed to experimentally identify the above prediction and further demonstrate that Tet has cardioprotective effects. Results of the whole‐cell patch clamp technique showed that Tet at 1–100 μmol/L enhanced IK1 current, hyperpolarized resting potential (RP), and shortened action potential duration (APD) in isolated rat cardiomyocytes, while without effects on other ion channels or transporters. In adult Sprague–Dawley (SD) rats in vivo, Tet showed anti‐arrhythmia and anticardiac remodeling effects, respectively, in the coronary ligation‐induced myocardial infarction model and isoproterenol (Iso, i.p., 3 mg/kg/day, 10 days) infusion‐induced cardiac remodeling model. Tet also showed anticardiomyocyte remodeling effect in Iso (1 μmol/L) infused adult rat ventricular myocytes or cultured H9c2 (2‐1) cardiomyocytes. Tet at 0.54 mg/kg in vivo or 30 μmol/L in vitro showed promising protections on acute ischemic arrhythmias, myocardial hypertrophy, and fibrosis. Molecular docking was performed and identified the selective binding of Tet with Kir2.1. The cardioprotection of Tet was associated with the facilitation of IK1 channel forward trafficking, deactivation of PKA signaling, and inhibition of intracellular calcium overload. Enhancing IK1 may play dual roles in anti‐arrhythmia and antiventricular remodeling mediated by restoration of Ca2+ homeostasis. [ABSTRACT FROM AUTHOR]