Doxorubicin (DOX) is a widely used anthracycline, but its clinical use is limited by dose-dependent cardiotoxicity. This experimental study evaluated the cardioprotective potential of empagliflozin (EMPA) against DOX-induced cardiotoxicity. Thirty healthy adult rats were randomized into five groups (n = 6): control (group I), EMPA (group II), EMPA + DOX (group III), DOX (group IV), and EMPA-preconditioning + DOX (group V). EMPA was administered orally at 10 mg/kg/day, either concomitantly with DOX or as a 14-day preconditioning course. Cumulative DOX exposure reached 15 mg/kg to establish a reproducible cardiotoxicity model. Serial electrocardiograms (ECGs) were recorded, blood samples were collected, and hearts were harvested for detailed histopathological analysis. Compared with the control group, group IV demonstrated significant QT/QTc prolongation and repolarization abnormalities, marked troponin elevation, and characteristic histological lesions, including cardiomyocyte vacuolization, loss of striations, diffuse inflammation, myocyte atrophy, and increased fibrosis. In groups receiving EMPA with DOX exposure (groups III and V), ECG changes were attenuated, troponin elevation was lower, and structural myocardial damage was substantially reduced, with better preservation of cardiomyocyte architecture and less fibrosis. These results suggest that EMPA provides significant cardioprotection against DOX-induced cardiotoxicity in rats, supporting further investigation of SGLT2 inhibitors in cardio-oncology.

This paper describes the design and preliminary implementation of a concurrent (parallel) model for teaching AI in medicine. This elective course was addressed to residents and final year medical students aiming to integrate in each lecture the theoretical notions with practical applications. The structure of the seven two hours classes comprised a first part with main AI concepts, such as machine learning, neural networks, decision support or generative models and a second part dedicated to invited presentations on clinical or research applications. The pedagogical objective was consolidation of conceptual understanding, keeping high audience interest by immediate contextualization. Quantitative analysis of the questionnaire data indicated good internal consistency of the evaluation instrument. No significant differences were observed across professional categories or baseline AI background levels. Perceived course impact was found to be associated with both theoretical understanding and application-oriented content. These results support the appropriateness of the concurrent teaching model for AI education in medicine. Integrating theoretical foundations with practical applications within each session appears to stimulate motivation and facilitate understanding of AI principles among clinically oriented learners.