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Nonalcoholic fatty liver disease (NAFLD) poses an emerging threat topublic health. Nonalcoholic steatohepatitis (NASH) is reported to be the most rapidly rising cause of hepatocellular carcinoma in the western world. Recently, a new term has been proposed: metabolic dysfunction-associated steatotic liver disease (MASLD). The introduction of this new terminology has sparked a debate about the interchangeability of these terms. The pathogenesis of NAFLD/MASLD is thought to be multifactorial, involving both genetic and environmental factors. Among these factors, alterations in gut microbiota and gut dysbiosis have recently garnered significant attention. In this context, this review will further discuss the gut–liver axis, which refers to the bidirectional interaction between the human gut microbiota and the liver. Additionally, the therapeutic potential of probiotics, particularly next-generation probiotics and genetically engineered bacteria, will be explored. Moreover, the role of prebiotics, synbiotics, postbiotics, and phages as well as fecal microbiota transplantation will be analyzed. Particularly for lean patients with NAFLD/MASLD, who have limited treatment options, approaches that modify the diversity and composition of the gut microbiota may hold promise. However, due to ongoing safety concerns with approaches that modulate gut microbiota, further large-scale studies are necessary to better assess their efficacy and safety in treating NAFLD/MASLD.

Introduction Mining of electronic health record (EHRs) data is increasingly being implemented all over the world but mainly focuses on structured data. The capabilities of artificial intelligence (AI) could reverse the underusage of unstructured EHR data and enhance the quality of medical research and clinical care. This study aims to develop an AI-based model to transform unstructured EHR data into an organised, interpretable dataset and form a national dataset of cardiac patients.Methods and analysis CardioMining is a retrospective, multicentre study based on large, longitudinal data obtained from unstructured EHRs of the largest tertiary hospitals in Greece. Demographics, hospital administrative data, medical history, medications, laboratory examinations, imaging reports, therapeutic interventions, in-hospital management and postdischarge instructions will be collected, coupled with structured prognostic data from the National Institute of Health. The target number of included patients is 100 000. Natural language processing techniques will facilitate data mining from the unstructured EHRs. The accuracy of the automated model will be compared with the manual data extraction by study investigators. Machine learning tools will provide data analytics. CardioMining aims to cultivate the digital transformation of the national cardiovascular system and fill the gap in medical recording and big data analysis using validated AI techniques.Ethics and dissemination This study will be conducted in keeping with the International Conference on Harmonisation Good Clinical Practice guidelines, the Declaration of Helsinki, the Data Protection Code of the European Data Protection Authority and the European General Data Protection Regulation. The Research Ethics Committee of the Aristotle University of Thessaloniki and Scientific and Ethics Council of the AHEPA University Hospital have approved this study. Study findings will be disseminated through peer-reviewed medical journals and international conferences. International collaborations with other cardiovascular registries will be attempted.Trial registration number NCT05176769.

Cardiovascular (CV) events in patients with cancer can be caused by concomitant CV risk factors, cancer itself, and anticancer therapy. Since malignancy can dysregulate the hemostatic system, predisposing cancer patients to both thrombosis and hemorrhage, the administration of dual antiplatelet therapy (DAPT) to patients with cancer who suffer from acute coronary syndrome (ACS) or undergo percutaneous coronary intervention (PCI) is a clinical challenge to cardiologists. Apart from PCI and ACS, other structural interventions, such as TAVR, PFO-ASD closure, and LAA occlusion, and non-cardiac diseases, such as PAD and CVAs, may require DAPT. The aim of the present review is to review the current literature on the optimal antiplatelet therapy and duration of DAPT for oncologic patients, in order to reduce both the ischemic and bleeding risk in this high-risk population.