Cardiac sarcoidosis remains a diagnostic challenge and requires differential diagnosis to exclude other potential causes of pathological changes. Difficulties in diagnosis stem from the unknown aetiology of the disease, as well as the non-specific nature of its clinical manifestations. The aim of this review is to analyse data published over the last decade concerning the diagnosis of cardiac sarcoidosis. Materials and Methods. This article presents a narrative review of contemporary literature on the diagnosis of cardiac sarcoidosis. A search for publications was conducted across international and domestic electronic databases, including PubMed, Scopus, Web of Science, Google Scholar, and eLIBRARY.RU. The following keywords and their combinations were used in both English and Russian: cardiac sarcoidosis, heart transplantation for sarcoidosis, diagnosis of sarcoidosis. Results. The review predominantly includes publications from 2016–2026, alongside earlier fundamental studies and international clinical guidelines that are pivotal for understanding the issue. Selection criteria encompassed systematic reviews, meta-analyses, professional society clinical guidelines, prospective and retrospective cohort studies, and large patient registries dedicated to the diagnosis, management, and prognosis of cardiac sarcoidosis. Conclusion: This review focuses on modern diagnostic modalities and the management strategy for patients with cardiac sarcoidosis, which represents one of the most severe and prognostically unfavourable manifestations of systemic sarcoidosis. Diagnosis is frequently delayed due to non-specific symptoms and the patchy distribution of granulomatous inflammation within the myocardium. Presented case reports clearly demonstrate the capabilities of contemporary diagnostics and treatment strategies for patients with cardiac sarcoidosis.

Cardiovascular pathology remains the leading cause of death in Russia, which determines the priority of correcting modifiable risk factors: high systolic blood pressure, poor nutrition, dyslipidemia. According to the 2023 clinical guidelines on lipid disorders, patients at very high cardiovascular risk should start on a combination of a statin and ezetimibe. A study was conducted on the adequacy of dyslipidemia correction in patients of the Northwestern Federal District in 2023. In order to assess the dynamics of prescribing initial combination therapy to patients with very high cardiovascular risk in 2025, we initiated a repeat study. Materials and methods. The study was conducted using a specially designed questionnaire: 165 patients in 2023 and 281 patients in 2025. The results were comparable to the large-scale, ESS-Russia (2012-2014), ARGO-3, ICEBERG, ESS-Russia-2 (2017) studies. Statistical significance was tested using Fisher's two-sample z-test. The results and their discussion. The number of patients with grade 1-3 obesity increased significantly (from 18.8% to 39.9%; z-criterion 4.62; p < 0.00001), and the proportion of overweight patients decreased (from 47.8% to 38.4%; z-criterion -1.95; p < 0.051). Patients with physical inactivity became significantly less common (60.0% vs. 38.4%; z-criterion 4.42; p < 0.00001). The number of patients with postinfarction cardiosclerosis increased significantly (9.6% vs. 37.2%; z-criterion 6.92; p < 0.00001). In 2025, statin monotherapy was prescribed to patients three times more often (94.7% vs 36.9%). There was a significant increase in prescribing the combined statin + ezetimibe regimen in the 2025 group (53.6% vs 0.0%). A control study of the lipidogram was performed in 74.8% of patients in 2025 and 78.1% in 2023, at the outpatient stage, correction of therapy was performed only in 17.0% of patients in 2025 and 16.3% in 2023. The target level of LDL-C < 1.4 mmol/L in 2023 was observed in 45 (34,9%), in 2025 - 113 (49,3%) cases. The significance of the obtained results is confirmed by the z-criterion 2,7 and the level p = 0,007. Conclusion. The paper considers ways to solve the problem of non-compliance of prescribed lipid-lowering therapy with clinical recommendations: the inclusion of ezetimibe and a fixed combination of statin + ezetimibe in the list of preferential drug provision, compliance with the requirements of follow-up of patients.

It is well established that ventricular arrhythmia (VA) is relatively common during pregnancy and carries different clinical significance depending on the presence or absence of structural heart disease (SHD). In women with SHD, VA more often reflects electrical and hemodynamic myocardial instability and is associated with an increased risk of heart failure, life-threatening tachyarrhythmias, hospitalization, and adverse obstetric and perinatal outcomes. In contrast, in women with a structurally normal heart, VA is predominantly idiopathic and has traditionally been considered benign. However, the physiological changes of pregnancy, including increased circulating blood volume, activation of neurohormonal mechanisms, and alterations in the electrophysiological properties of the myocardium, may modify the course of VA and its potential impact on both maternal and fetal outcomes. Quantitative assessment of arrhythmic burden is therefore of particular importance. VA burden is defined as the proportion of ventricular ectopic complexes relative to the total number of heartbeats during the monitoring period and is assessed primarily by Holter ECG monitoring. Recent studies in pregnant women without SHD suggest a possible association between a high VA burden and certain obstetric and fetal/neonatal complications; however, the threshold values associated with individual adverse outcomes vary considerably. Current pregnancy risk stratification models, including mWHO 2.0 and CARPREG II, do not incorporate ventricular ectopic burden as an independent parameter. This review compares data from studies including pregnant women with VA both with and without SHD, discusses potential mechanisms underlying adverse outcomes and the role of serial Holter ECG monitoring, and highlights the limitations of the current evidence base. Prospective studies with standardized assessment of arrhythmic burden, evaluation of VA dynamics across pregnancy trimesters, and long-term postpartum follow-up are needed to identify new risk predictors and improve individualized risk stratification

Background. Home blood pressure monitoring (HBPM) is recommended both for confirming the diagnosis of hypertension (HTN) and for monitoring treatment efficacy. The recommendation of the treating physician plays a key role in promoting active and correct HBPM. Objective. To assess the frequency of HBPM recommendations by cardiologists for outpatients with HTN, identify factors associated with HBPM recommendation, and develop a machine learning–based predictive model of HBPM recommendation using electronic medical record (EMR) data. Materials and methods. A retrospective analysis of EMR data from 44,358 outpatients with HTN seen by cardiologists in 2018–2024 was conducted. A predictive model was developed using the LightGBM algorithm based on structured clinical and demographic parameters and text features from the “Diagnosis Description” field (TF-IDF). Model performance was evaluated on a test set (70 % of 2018–2023 data) and an out-of-time validation set (OOT, 2024 data). Topic modeling (LDA) was applied to analyze recommendation structure. Results. HBPM recommendation was present in 40,180 patients (90.6 %). The machine learning model demonstrated high performance: test set AUC-ROC = 0.809, accuracy = 0.954, sensitivity = 0.810; OOT set AUC-ROC = 0.840, accuracy = 0.979, sensitivity = 0.837. Text features from diagnosis descriptions made the highest contribution (gain = 11,315.1), followed by age (3,461.8) and ICD code (3,138.4). Excluding text reduced AUC-ROC to 0.655–0.673. Higher probability of HBPM prescription was associated with younger age, advanced HTN stage, and uncontrolled blood pressure. LDA identified 6 topics; HBPM was mentioned in most. Conclusion. Cardiologists recommend HBPM to most patients with HTN. The decision to recommend HBPM is associated with objective indicators of disease severity and age. The developed predictive model accurately identifies patients for whom HBPM is indicated and can serve as a foundation for clinical decision support systems.

Ionizing radiation has a pronounced nephrotoxic effect, initiating a cascade of pathophysiological processes leading to the development of radiation nephropathy (RN) and renal failure. This review is devoted to an analysis of the current state of research in the field of identifying metabolomic biomarkers that allow for early diagnosis and prediction of radiationinduced kidney damage under external irradiation. The paper systematizes literature data obtained using mass spectrometry (MS) and nuclear magnetic resonance (NMR) regarding changes in the profiles of lowmolecularweight metabolites in urine. The main focus is on profound disturbances in purine metabolism (primarily due to the accumulation of xanthine and hypoxanthine), critical shifts in the tricarboxylic acid cycle (TCA), reflecting mitochondrial dysfunction, as well as an imbalance in the lipid profile, including the accumulation of acylcarnitines. These metabolic alterations are key indicators of oxidative stress and proximal tubule dysfunction, and the degree of their severity directly correlates with clinical and dosimetric parameters. The review provides a detailed examination of critical dose thresholds: moderate functional changes manifest when the absorbed dose to the kidneys exceeds 4 Gy, while irreversible structural degradation and manifest RN develop when the threshold of 10 Gy is exceeded. The authors emphasize that the introduction of metabolomic profiling into clinical practice can radically improve the effectiveness of monitoring the condition of patients who have undergone radiation exposure. Unlike classical protein damage markers (NGAL, KIM1), which are sensitive only at late stages, dynamic patterns of acylcarnitines, TCA cycle intermediates, and purine metabolites make it possible to carry out early biodosimetry. This makes it possible not only to detect the fact of radiation damage but also to assess the received radiation dose in the very first hours after exposure, enabling timely nephroprotective therapy.

Background. Detection of blast cells in peripheral blood is crucial for the diagnosis, monitoring, and evaluation of treatment efficacy in hematological diseases. The introduction of digital morphology can improve the standardization of laboratory processes; however, the results of automatic preclassification require evaluation of their comparability with expert morphological assessment. Objective. To evaluate the comparability of the results of automatic blast cell preclassification and counting using the Mindray MC-80 digital morphology analyzer with the results of expert morphological verification of digital images of peripheral blood smears. Materials and Methods. The study included 205 patients with various hematological pathologies and the presence of blasts in their peripheral blood. Blast cell counts were assessed using the Mindray MC-80 and by expert verification by a morphologist. Statistical analysis included Spearman correlation, Passing-Bablok regression, and Bland-Altman analysis. Results. Blasts were detected in all smears by expert morphological verification, while automatic counting detected them in 95.1 % of cases. A highly statistically significant correlation was found between the methods: r=0.806; p<0.0001. Mindray MC-80 statistically significantly overestimated the blast count compared to EV. According to the regression model constructed on the Bland-Altman plot, the average difference between the results of Mindray MC-80 automatic preclassification and expert verification was 2.1 cells (95 % CI of the mean difference 1.2–3.0) with an average blast count of 0.5 per 200 leukocytes and increased to 5.5 cells (95 % CI of the mean difference 3.3–7.7) with an average blast count of 29.5 per 200 leukocytes. The regression limits of agreement, calculated as the 95 % predictive interval for individual differences, ranged from –5.4 to +9.6 cells and from –2.2 to +13.2 cells for the indicated levels, respectively. Conclusion. Mindray MC-80 can be used for preliminary digital pre-classification and screening detection of blasts; however, automated counting requires mandatory expert verification by a morphologist, especially when making clinical decisions near diagnostic thresholds.

Primary cell cultures are an indispensable tool in fundamental research within modern cell biology. Their value lies in their close physiological resemblance to in vivo conditions, which significantly enhances the reliability and translational relevance of experimental data. However, the broad application of primary cells in vitro is constrained by their finite proliferative capacity, culminating in cellular senescence, which poses substantial challenges for long-term and highly reproducible studies. Cellular senescence represents a complex, multifaceted cellular response to diverse stimuli. Consequently, it is broadly classified into replicative senescence, oncogene-induced senescence (OIS), and stress-induced premature senescence. Each of these senescence modalities exhibits distinct molecular signatures, and elucidating these features is crucial for understanding how to bypass the cellular proliferative barrier through immortalization. Classical immortalization strategies, such as the ectopic expression of the telomerase catalytic subunit (TERT) or the introduction of viral oncogenes (e.g., SV40 Large T-antigen, HPV16 E6/E7) and proto-oncogenes, are highly effective but carry significant limitations. These include the inherent risk of oncogenic transformation and the alteration of the native cellular phenotype. Consequently, contemporary approaches such as conditional immortalization, non-integrating delivery systems, and combinatorial strategies are gaining prominence. These methods aim to sustain a high proliferative potential while preserving maximal phenotypic fidelity to the original primary cells. This review systematizes current knowledge regarding the distinct modalities of cellular senescence. It provides a comprehensive analysis of both primary and auxiliary immortalization techniques, critically evaluating their respective advantages and limitations. Furthermore, it characterizes contemporary immortalized cell lines with a specific focus on their phenotypic stability and translational potential in regenerative medicine, tissue engineering, 3D cell culture models, and preclinical pharmacology. The analysis presented herein is primarily based on data published within the last 15 years.