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Background: Artificial intelligence (AI) is present in preclinical, clinical and research work, in various branches of medicine. Researchers and teachers at school of medicines may have different ethical attitudes and perspectives about the implementation of AI systems in medicine., Methods: We conducted an online survey among researchers and teachers (RTs) at the departments and institutes of two Slovenian and four Croatian Schools of Medicine., Results: The sample included 165 and 214 researchers and teachers in Slovenia and Croatia, respectively. The sample of respondents in Slovenia and Croatia was comparable in demographical characteristics. All participants reported high emphasis on the bioethical principles when using artificial intelligence in medicine, its usefulness in certain circumstances, but also caution regarding companies providing AI systems and tools. Slovenian and Croatian researchers and teachers shared three similar perspectives on the use of AI in medicine-complying with highest ethical principles, explainability and transparency and usefulness of AI tools. Higher caution towards use of AI in medicine and effect on autonomy of physicians was expressed in Croatia, while in Slovenia high emphasis was put on understanding how AI works, but also the concerns regarding willingness and time of physicians to learn about AI., Conclusion: Slovenian and Croatian researchers and teachers share ethical attitudes and perspectives with international researchers and physicians. It is important to facilitate understanding of the implications of AI use in medicine and set a solid evidence-based ground to tackle ethical and legal issues., Competing Interests: The authors report no relevant conflicts of interest., (Copyright: © 2024 Grosek et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Aim: To assess the effectiveness of a brief educational intervention on prescribing first-line antibiotics in acute cystitis., Methods: This quasi-experimental before-after study was conducted over a period of eight months. We collected prescribing data related to urinary tract infections four months before the educational intervention and four months after it. Aggregate data on office visits, diagnoses, and issued prescriptions were collected from each practice's electronic medical records based on monthly reports., Results: Overall, 3581 prescriptions were issued: 1717 before and 1864 after the intervention. The total number of prescriptions increased by 8.5%. The use of first-line antibiotics increased by 21.2%, the use of fluoroquinolones decreased by 6.6%, while the use of beta-lactams remained unchanged. After the intervention, nitrofurantoin was the most prescribed first-line antibiotic. The proportion of women who were prescribed first-line antibiotic did not reach the acceptable range (80%-100%) according to the European Surveillance of Antimicrobial Consumption quality indicators. The proportion of fluoroquinolones (17.9%) use was well above the acceptable range (0%-5%)., Conclusion: A brief educational intervention proved to be a useful method in adopting better prescribing habits. Of particular importance is the considerable increase in the use of nitrofurantoin due to its reliable efficacy against multidrug-resistant urinary pathogens.

Administration of cytotoxic agents like doxorubicin (DOX) is restrained by the effects on different non-targeted/non-cancerous tissues, which instigates the development of nano-enabled drug delivery systems, among others. In this study, imaging mass spectrometry (IMS) was selected to examine the effects of DOX nanoformulations on non-targeted tissues. Chemical alterations induced by liposomal (LPS) and poly (lactic- co -glycolic acid) (PLG) nanoformulations were assessed against the ones induced by the conventional (CNV) formulation. Kidney cryosections of the treated and control Wistar rats were used as a model of the non-targeted tissue and analyzed by MALDI TOF IMS in the 200-1000 Da m / z range. Principal component analysis (PCA) and Volcano plots of the average mass spectra demonstrated a large overlap between treatments. However, the Venn diagram of significant m / z values revealed a nanoformulation-specific fingerprint consisting of 59 m / z values, which set them apart from the CNV formulation characterized by the fingerprint of 22 significant m / z values. Fingerprint m / z values that were putatively annotated by metabolome database search were linked to apoptosis, cell migration and proliferation. In CNV and PLG cases, false discovery rate adjusted ANOVA showed no differences in the spatial distribution of fingerprint m / z values between the histological substructures like glomeruli and convoluted tubules indicating their tissue-nonselective effect. LPS caused the least significant changes in m / z values and some of the LPS-specific fingerprint m / z values were primarily distributed in the glomeruli. The IMS based procedure successfully differentiated the effects of DOX formulations on the model non-targeted tissue, thus indicating the importance of IMS in effective drug development.