Atrial fibrillation (AF) is a common rhythm disorder, a life-threatening complication of which is cardioembolic stroke leading to disability and death. This necessitates the search for early predictors of this pathology. P wave and PR interval abnormalities on electrocardiography (ECG) are associated with the AF risk. Neural networks are considered for rapid ECG analysis in routine practice and identifying the risks of AF occurrence and/or relapse. In recent years, advances in joint projects between medicine and artificial intelligence have made significant progress in the use of open ECG databases for deep machine learning of neural networks. These studies have shown that artificial intelligence makes it possible to identify predictors of AF, which will significantly reduce the risk of mortality due to thromboembolism. This paper reviews in detail the results of published studies that highlight the effectiveness of neural networks to improve AF risk assessment.

In the updated diagnostic criteria for arrhythmogenic cardiomyopathy (ACM) (2020 and 2022), magnetic resonance imaging (MRI) has become the preferred method for cardiac imaging. This is due to advances in MRI and the accumulation of evidence on its reliability. Non-invasive assessment of myocardial fibrotic replacement using late gadolinium enhancement techniques is a key innovation, which, along with histology data, was included in the category of "structural changes". The technique has demonstrated significance in identifying various ACM phenotypes (primarily the left ventricular one), in differential diagnostics and family screening of the disease. The relevance of MRI data has been proven in predicting the risks of adverse cardiovascular events, including sudden cardiac death. Some MRI techniques, such as T1 mapping and myocardial strain assessment, are under study, but they have already shown promise in studies on small groups. Obtaining and interpreting cardiac MRI data in patients with ACM requires not only standardized protocols and high experience of a radiologist, but also teamwork with cardiologists. The article summarizes the current capabilities of MRI in ACM and provides a practical approach to diagnosis and risk stratification.

Modern studies demonstrate that clonal hematopoiesis of indeterminate potential (CHIP) is a risk factor for the development and prognosis of heart failure (HF) of various origin. The pathophysiology and consequences of CHIP are gene-specific. The mechanisms involved in this process are complex and indicate the central role of systemic and myocardial inflammation, including the immune response dependent on the inflammasome/interleukin-1β/interleukin-6 cascade. CHIP and associated inflammatory pathways represent a powerful potential target, which rationales the research in the area of various HF stages and markers of this genetic phenomenon. A better understanding of the interactions between mutant clones, immune pathways, chronic inflammation and clinical implementation in HF may be important in the context of precision and personalized medicine.

Hypertrophic cardiomyopathy (HCM) is a diagnosis established in each case of left ventricular hypertrophy of unknown origin when the left ventricular wall is greater than or equal to 15 mm in one or more myocardial segments according to imaging data. The hereditary nature of HCM is no longer in doubt. But successful verification of HCM using genetic tests is 60% of cases. This fact makes it possible to believe that a search for new predictor genes for HCM is necessary. The review presents current literature data on mutations in genes associated with hypertrophic cardiomyopathy.

Pathological personality traits (anxiety, depressive, hypochondriacal) significantly worsen the treatment and rehabilitation of patients with acute myocardial infarction. The aim of the work was to study the influence of genetic characteristics of patients on psychological readaptation in patients with acute coronary pathology. The review lists the identified candidate genes that affect the depression occurrence in these patients and represent potential targets for therapeutic intervention. Nucleotide sequence variants associated with a poor response to antidepressants in this category of patients are discussed. The use of genetic methods in examination, further consideration of the individual characteristics of each patient when choosing therapy, prescribing a rehabilitation course will allow for an individual approach to each patient, which in turn should improve the prognosis of the disease.

A detailed characterization of the diversity, clonality, and antigen specificity of the T-cell repertoire contributes to the understanding of the adaptive immune response role in a wide range of diseases, including arteriosclerosis. This article discusses the differentiation of T-lymphocytes and the factors leading to their activation in atherosclerosis. Furthermore, the article discusses the data obtained during the analysis of T-cell repertoires in carotid and coronary artery atherosclerosis using new sequencing technologies, such as single-cell sequencing. The importance and peculiarity of studying the diversity of T-lymphocyte subphenotypes, their antigenic specificity, and their interaction with other cells in atherosclerosis are emphasized. The aim of this review was to synthesize data from studies examining the T-cell immune response in atherosclerosis, utilizing T-cell receptor sequencing techniques, including those based on single-cell sequencing technology.

In the pathogenesis of many inflammatory processes, an important role is played by a reaction cascade of various inflammasome types. The products of their activation are proinflammatory cytokines IL-1β and IL-18. These protein molecules can be secreted in two different ways as follows: by vesicular transport or by membrane pores, which subsequently leads to the secreting cell death. The role of inflammasome activation in cardiac tissue cells has not been sufficiently studied at present. However, there are some studies reflecting the association between the inflammasome cascade launch and cardiovascular diseases. Thus, inflammasome activation in cardiomyocytes can lead to electrolyte imbalance, which subsequently leads to ectopic foci in the cardiac tissue and cardiac arrhythmia. Triggering the inflammasome cascade in cardiac fibroblasts promotes fibrosis and myocardial tissue remodeling, which leads to disruption of heart functional activity. Inflammasome activation in coronary artery endothelial cells leads to endothelial dysfunction and atherogenesis. Thus, activation of various types of inflammasomes in cardiac tissue leads to cardiac pathology.

Coronary artery disease (CAD) and depression are characterized by high bilateral comorbidity, but its pathogenesis is practically not studied.

In the last decade, neurogenic mechanisms of the inflammatory response and brain-derived neurotrophic factor (BDNF), which can explain the relationship between depression and CAD, have been studied. The review summarizes the available information on BDNF role in the pathogenesis of CAD and depression, as well as their comorbid course for the period of 2019-2024. Based on the literature review, we identified the components and systems that are most promising for studying the BDNF role in the pathogenesis of these multifactorial diseases (genetics, inflammation, neuroinflammation, endothelial dysfunction and platelet hyperactivation, hypothalamic-pituitary-adrenal system, low-density lipoproteins and triglycerides). The review emphasizes the important role of BDNF in the development of depression in CAD and the need for further research in this area.

The review article considers key applications of artificial intelligence (AI) in cardiology. The review includes subsections devoted to weak and strong AI used in clinical practice and cardiology health provision. The article describes the application options for AI in the analysis of electrocardiography, echocardiography, sonography, computed tomography, magnetic resonance imaging, and positron emission tomography of the heart data. The article briefly describes the aspects of using machine learning and artificial intelligence to process ambulance calls from patients with cardiac complaints, and considers AI applications in preventive cardiology. The review considers the potential of AI in the analysis of data arrays obtained during tonometry, pulse wave velocity measurement, and in biochemical studies. The paper also formulates the principles of strong AI (large language models) in cardiology health provision, identifies the main problems and difficulties in implementing the latest technology, and provides a conceptual scheme for implementing AI technology in a cardiology center. This paper highlights the key limitations of the large language model technology, such as the lack of standard algorithms for collecting and reviewing data, lack of understanding of the context, the inability of models to form expert conclusions, and the emergence of many problematic ethical characteristics when using large language models.

Aim. To analyze and generalize inhospital outcomes of myocardial revascularization in patients with coronary artery calcification.

Material and methods. The primary selection yielded 470 publications, including 354 from the Pubmed database in English and 116 from the E-library database in Russian. Thirteen studies were selected that met the search criteria. Among them, 5 studies were for coronary artery bypass grafting (n=932) and 8 for endovascular intervention (n=5758). The endpoints were 30-day mortality and perioperative myocardial infarction (PMI).

Results. PMI incidence in patients with coronary artery calcification in percutaneous coronary intervention using atherectomy techniques is 4,4%, while inhospital mortality - 0,9%. PMI incidence in coronary artery bypass grafting using complex coronary interventions in this group of patients is 2,6%, while inhospital mortality - 0,7%.

Conclusion. Myocardial revascularization in patients with coronary calcification can be performed by endovascular and open approaches using advanced coronary surgery techniques. Inhospital outcomes seem satisfactory. Conclusions about the advantages of one method or another require comparative studies.