Search

Dilated cardiomyopathy (DCM) is a leading cause of heart failure, sudden cardiac death, and heart transplantation in young patients. The causes of DCM are varied and include genetic factors and metabolic, infectious, toxic and others factors. Today it is known that germline mutations in more than 98 genes can be associated with the occurrence of DCM. However, the penetrance of these genes often depends on a combination of factors, including modifiable ones, i.e. those that change under the influence of the environment. About 20–25% of genetically determined forms of DCM are due to mutations in the titin gene (TTN). Titin is the largest protein in the body, which is an important component of the sarcomer. Although titin is the largest protein in the human body, its role in the physiology of heart and disease is not yet fully understood. However, a mutation in the TTN gene may later represent a potential therapeutic target for genetic and acquired cardiomyopathy. Thus, the analysis of clinical cases of cardiomyopathy in patients with identified mutations in the TTN gene is of great scientific interest. The article presents a clinical case of manifestation of DCM in patient with a revealed pathogenic variant of mutation in the gene TTN and reverse left ventricular remodeling of the against the background of optimal therapy of heart failure in a subsequent outpatient observation.

This article presents the long-term (1952–2020) hydrometeorological observation dataset collected at the Lammin-Suo mire, Leningrad region, Russia. The Lammin-Suo mire is an active (currently peat forming) ombrotrophic mire with intensive peat accumulation and pine - shrub - Sphagnum microtopes, and is thus an example of the most common type of peatland in Eastern Fennoscandia. The data are representative of the wetland taiga region of north-west Russia and can be used to characterise the hydrometeorology and climate of peatland basins and to assess the response of hydrological cycling in peatland basins to changes in climate. The research at the Lammin-Suo Peatland Station focuses on hydrology, meteorology, soil processes and the landscape evolution of the peatland. The dataset includes air temperature, air humidity, atmospheric pressure, wind speed and direction, cloudiness, precipitation, evaporation, snow depth, peat temperature, peatland water level, groundwater level and temperature. Trend analysis shows a statistically significant warming of the air, peat and groundwater, an increase in precipitation, trends of increasing flow in some peatland streams and a decrease in snow cover duration and thickness. The article also provides an assessment of the water balance of the Lammin-Suo mire based on observational data. The database presented and described here is available for download at https://doi.org/10.5281/zenodo.5060039.

The study’s relevance is due to the need to identify the scale and channels of the spread of crises in the economy based on the use of the financial contagion methodology. Understanding the mechanism of spreading financial contagion from one industry to another can help develop anti-crisis measures and ensure stable economic indicators. The purpose of the study is to assess the intersectoral financial contagion in the Russian economy during the spread of the coronacrisis, as well as to correlate the estimates obtained with the actual incidence of COVID‑19 in the Russian Federation. The novelty of the research lies in the development of the methodology of financial contagion and its use in relation to sectors of the Russian economy, where they are considered transmitters and/or receivers of financial contagion. The methodology of advanced correlation analysis was used — the Forbes-Rigobon sliding test was implemented, which made it possible to assess the scale and intensity of financial contagion in the Russian economy. We used high-frequency data on 8 MICEX industry indices and on the incidence of COVID‑19 in the period 2020–2021. The result was quantitative assessments of financial contagion, which showed that such industries as metallurgy, oil and gas sector, consumer sector, electric power industry had the highest susceptibility to financial contagion. Telecommunications, the financial sector, chemicals and petrochemicals, and transport have demonstrated resistance to the pandemic shock. The most powerful transmitters of financial contagion were the electric power industry, metallurgy, transport, and the financial sector. In general, the financial contagion in 2020–2021 between the sectors of the Russian economy spread unevenly, in some cases and in certain periods, the ups and downs of financial infectivity went in parallel with the ups and downs of the real incidence of COVID‑19. The main conclusion was that during the pandemic, financial contagion spread with varying intensity, and individual industries manifested themselves either as receivers or transmitters of financial contagion. At the same time, there was no large-scale financial infection of the sectors of the Russian economy.

In this article, we investigate how the irregular insolation of two low-elevated Svalbard glaciers exerts effect on rates of their surface melting. We compare the spatial distribution of rates of the surface lowering of glaciers Vøringbreen (0.76 km2) and Aldegondabreen (5.5 km2), both are located near Barentsburg settlement in the western part of Nordenskiöld Land (the Spitsbergen Island). As an approximation of the solar radiation flux, we used the potential incoming solar radiation calculated by the ArcticDEM digital elevation model for the period July 15–September 15, which is a typical time of ice ablation in the region under consideration. Motions of both glaciers are extremely slow, which allows assuming that lowering of their surfaces are identical to the rates of surface melting. We have found that both glaciers are distinctly divided into two parts, more and less sunlit. The spatial pattern of insolation of the Vøringbreen glacier is controlled by the shading of the walls surrounding the cirque, while the Aldegondabreen one due to its concave shape has two different areas with a more southern and more northern exposure. The lowering of the surface shows that the more and less illuminated parts differ significantly in ice ablation. The maximum differences in melting caused by the irregular insolation are 2.1 m of ice depth over five years for the Aldegondabreen Glacier (2008–2013 and 2013–2018) and 2.2 m over six years for the Vøringbreen Glacier (2013–2019), that is 40, 30 and 25% of the total values of the surface depression for the corresponding periods. Within every 50-meter altitude interval, correlation coefficients between surface ablation and insolation vary from –0.33 to –0.62 for the Aldegondabreen and from –0.50 to –0.92 for the Vøringbreen glacier. When compared with the vertical gradient of the ice melting, the variability of ablation caused by the irregular insolation correspond to a difference in altitudes of 45–50 m in vertical for the Aldegondabreen and 60 m for Vøringbreen. These values are significant taking into account the small altitudinal range of the glaciers in that part of Spitsbergen.

Abstract Background 7 T cardiac magnetic resonance imaging (MRI) studies may enable higher precision in clinical metrics like cardiac function, ventricular mass, and more. Higher precision may allow early detection of functional impairment and early evaluation of treatment responses in clinical practice and pre-clinical studies. Methods: Seven female German Landrace pigs were scanned prior to and at three time points (3–4 days, 7–10 days, and ~60 days) post myocardial infarction using a whole body 7 T system and three radiofrequency (RF) coils developed and built in-house to accompany animal growth. Results: The combination of dedicated RF hardware and 7 T MRI enables a longitudinal study in a pig model of acute and chronic infarction, providing consistent blood tissue contrast and high signal-to-noise ratio (SNR) in measurements of cardiac function, as well as low coefficients of variation (CoV) for ejection fraction (CoVintra-observer: 2%, CoVinter-observer: 3.8%) and infarct size (CoVintra-observer: 8.4%, CoVinter-observer: 3.8%), despite drastic animal growth. Conclusions: Best results are achieved via manual segmentation. We define state-of-the-art procedures for large animal studies at 7 T.

Abstract Identifying high-affinity antibodies in human serum is challenging due to extremely low number of circulating B cells specific to the desired antigens. Delays caused by a lack of information on the immunogenic proteins of viral origin hamper the development of therapeutic antibodies. We propose an efficient approach allowing for enrichment of high-affinity antibodies against pathogen proteins with simultaneous epitope mapping, even in the absence of structural information about the pathogenic immunogens. To screen therapeutic antibodies from blood of recovered donors, only pathogen transcriptome is required to design an antigen polypeptide library, representing pathogen proteins, exposed on the bacteriophage surface. We developed a two-dimensional screening approach enriching lentiviral immunoglobulin libraries from the convalescent or vaccinated donors against bacteriophage library expressing the overlapping set of polypeptides covering the spike protein of SARS-CoV-2. This platform is suitable for pathogen-specific immunoglobulin enrichment and allows high-throughput selection of therapeutic human antibodies.

Introduction. The structure of dihydroquercetin (DHQ) is characterized by two chiral centers at positions 2 and 3 of the benzopyran cycle, resulting in possible diastereomers: trans- and cis-isomers. Therefore, the development of methods for qualitative and quantitative control of DHQ diastereomers in analyzed samples is essential for patient safety management. Nuclear magnetic resonance (NMR) spectroscopy is one of the physicochemical methods that can be used for this purpose.Aim. The study objective was to accumulate the analytical and structural characteristics of cis-DHQ by NMR spectroscopy of the spheroidal form of this flavonoid (DHQs).Materials and Methods. 1D 1H, 1H,1H-COSY, 1H,1H-NOESY, and 1H,13C-HSQC NMR spectra were acquired at 298 K on an 800 MHz NMR spectrometer equipped with a TXI triple resonance probe. The number of scans was 32. The mixing time in the NOESY experiment was 400 ms. The 1H and 13C were analyzed using CcpNmr software. The dihedral angles were calculated by applying the Karplus equation.Results and discussion. In trans-DHQ, the chemical shift values for H2 and H3 are 4.93 ppm and 4.52 ppm, respectively, and in cis-DHQ they are 5.31 ppm and 4.20 ppm, respectively. The spin-spin coupling constants between H2 and H3 of trans- and cis-DHQ are 12.00 Hz and 2.40 Hz, respectively. Thus, the dihedral angles for the trans- and cis-isomers are 154° and 64°, respectively. We found that DHQs contains 12.5 % of the cis-isomer.Conclusion. Our experiments confirmed that NMR spectroscopy can discriminate between trans- and cis-DHQ based on the chemical shift values for the cross-peaks of H2 and H3. The second major finding was that this method can be considered as a more selective quantitative analysis than HPLC with UV detection without reference. One of the most important results of this study for drug development is the updated information on the structural parameters of DHQ diastereomers in the liquid phase.

Introduction. The article studies patent activity in the regions of Russia. The relevance of the research in this area is determined by the importance of the innovation component in economic growth, as well as by the established targets in the Concept of Technological Development of the Russian Federation for the period up to 2030. The aim of the study is to identify possible types and directions of patent policy for different groups of Russian regions on the basis of patent activity factors. Materials and Methods. The empirical material for the analysis includes data from the World Intellectual Property Organization (WIPO) and the Federal State Statistics Service (FSSS) for 2012‒2021. We use linear regression to identify the key factors affecting the patent activity of the regions. The method of hierarchical clustering allowed us to identify groups of regions according to their patent activity. Results. The linear regression showed the statistically significant dependence of regional patent activity on I-activity level of organizations, the number of active fixed broadband Internet subscribers per 100 population and the average of internal costs for research and development per 1 organization in the region. The hierarchical clustering distinguished 5 clusters of regions: “The Leader”, “Innovation centers”, “Regions of high manufacturability”, “Old R&D regions” and “Regions-outsiders”. The authors also formulate definitions of the regional patent policy and the national patent policy and present typologies of state patent policy. Discussions and Conclusions. Based on empirical and theoretical analysis, recommendations on further directions for the development of active patent policies were given to groups of regions. The results of the study can be applied in the development and implementation of scientific and technological regional development strategies, and will also be useful to specialists and government officials involved in regulating patent activity in the regions.

BackgroundThe precision child and youth mental health (PCYMH) paradigm has great potential to transform CYMH care and research, but there are numerous concerns about feasibility, sustainablity, and equity. Implementation science and evaluation methodology, particularly participatory logic models created with stakeholders, may help catalyze PCYMH-driven system transformation. This paper aims to: (1) report results of a PCYMH logic model scoping review; (2) present a case study illustrating creation of a participatory logic model for a PCYMH start-up; and (3) share the final model plus lessons learned.MethodsPhase 1: Preparation for the logic model comprised several steps to develop a preliminary draft: scoping review of PCYMH logic models; two literature reviews (PCYMH and implementation science research); an environmental scan of our organization's PCYMH research; a gap analysis of our technological capability to support PCYMH research; and 57 stakeholder interviews assessing PCYMH perspectives and readiness. Phase 2: Participatory creation of the logic model integrated Phase 1 information into a draft from which the final logic model was completed through iterative stakeholder co-creation.ResultsPhase 1: The scoping review identified 0 documents. The PCYMH literature review informed our Problem and Impact Statements. Reviewing implementation and evaluation literature resulted in selection of the Reach, Effectiveness, Adoption, Implementation, Maintenance (RE-AIM) and Behavior Change Wheel (BCW) frameworks to guide model development. Only 1.2% (5/414) of the organization's research projects involved PCYMH. Three technological infrastructure gaps were identified as barriers to developing PCYMH research. Stakeholder readiness interviews identified three themes that were incorporated into the draft. Phase 2: Eight co-creation cycles with 36 stakeholders representing 13 groups and a consensus decision-making process were used to produce the final participatory logic model.ConclusionsThis is the first study to report the development of a participatory logic model for a PCYMH program, detailing involvement of stakeholders from initial planning stages to the final consensus-based product. We learned that creating a participatory logic model is time- and labour-intensive and requires a multi-disciplinary team, but the process produced stakeholder-program relationships that enabled us to quickly build and implement the PCYMH start-up. Our processes and final model can inform similar efforts at other sites.

BackgroundPopulation studies are essential for gathering critical disease prevalence data. Automated pathogenicity assessment tools enhance the capacity to interpret and annotate large amounts of genetic data. In this study, we assessed the prevalence of cancer-associated germline variants in Russia using a semiautomated variant interpretation algorithm.MethodsWe examined 74,996 Russian adults (Group 1) and 2,872 long-living individuals aged ≥ 90 years (Group 2) for variants in 28 ACMG-recommended cancer-associated genes in three steps: InterVar annotation; ClinVar interpretation; and a manual review of the prioritized variants based on the available data. Using the data on the place of birth and the region of residence, we determined the geographical distribution of the detected variants and tracked the migration dynamics of their carriers.ResultsWe report 175 novel del-VUSs. We detected 232 pathogenic variants, 46 likely pathogenic variants, and 216 del-VUSs in Group 1 and 19 pathogenic variants, 2 likely pathogenic variants, and 16 del-VUSs in Group 2. For each detected variant, we provide a description of its functional significance and geographical distribution.ConclusionThe present study offers extensive genetic data on the Russian population, critical for future genetic research and improved primary cancer prevention and genetic screening strategies. The proposed hybrid assessment algorithm streamlines variant prioritization and pathogenicity assessment and offers a reliable and verifiable way of identifying variants of uncertain significance that need to be manually reviewed.

The metasurfaces have shown great potential for miniaturizing conventional optics while offering extended flexibility. Recently, there has been considerable interest in using algorithms to generate meta-atom shapes for these metasurfaces, as they offer vast design freedom and not biased by the human intuition. However, these complex designs significantly increase the difficulty of fabrication. To address this, we introduce a design process that rigorously enforces the fabricability of both the material-filled (fill) and empty (void) regions in a metasurface design. This process takes into account specific constraints regarding the minimum feature size for each region. Additionally, it corrects any violations of these constraints across the entire device, ensuring only minimal impact on performance. Our method provides a practical way to create metasurface designs that are easy to fabricate, even with complex shapes, hence improving the overall production yield of these advanced meta-optical components.

Introduction: Morphofunctional changes of the circulatory system organs detected in athletes may remain without due attention, as clinical (phenotypic) signs of pathological abnormalities are very similar to manifestations of cardiovascular system adaptation to intensive physical loads. The aim of the study is to propose a personalized algorithm for biomedical support of professional athletes with abnormalities and diseases of the circulatory organs based on clinical and genomic data.Materials and methods: The results of in-depth medical examination (2021-2023) of 15,464 athletes who are members of Russian sports teams were analyzed. The structure of circulatory system diseases according to the codes of the International Classification of Diseases, 10th revision (ICD-10), which were included in the summary report of the last examination, was analyzed. Fifty athletes with abnormalities and diseases of the circulatory system organs, experiencing different degrees of intensity of dynamic and static loads in accordance with the Mitchell classification, were selected from the study sample for full genome sequencing and subsequent clinical interpretation of the obtained data.Results: In the study sample the number of people with pathologic conditions of the circulatory system organs amounted to 6 946 people (45 %). Mitchell classification groups had statistically significant differences with respect to the prevalence of 10 diseases of the circulatory system organs. In 50 DNA samples of professional athletes, 5 probably pathogenic variants (10%), 19 variants with uncertain clinical significance (38%), relevant to the phenotype of a monogenic disease with circulatory system organ damage, were detected.Conclusion: Molecular genetic testing is an effective tool for differential diagnostics of pathologic and adaptive changes in the organs of the circulatory system. Carrying causative genes in combination with clinical signs allows to change the tactics of medical and biological support of an athlete according to the proposed algorithm.

Abstract Cardiac magnetic resonance (CMR) imaging allows precise non-invasive quantification of cardiac function. It requires reliable image segmentation for myocardial tissue. Clinically used software usually offers automatic approaches for this step. These are, however, designed for segmentation of human images obtained at clinical field strengths. They reach their limits when applied to preclinical data and ultrahigh field strength (such as CMR of pigs at 7 T). In our study, eleven animals (seven with myocardial infarction) underwent four CMR scans each. Short-axis cine stacks were acquired and used for functional cardiac analysis. End-systolic and end-diastolic images were labelled manually by two observers and inter- and intra-observer variability were assessed. Aiming to make the functional analysis faster and more reproducible, an established deep learning (DL) model for myocardial segmentation in humans was re-trained using our preclinical 7 T data (n = 772 images and labels). We then tested the model on n = 288 images. Excellent agreement in parameters of cardiac function was found between manual and DL segmentation: For ejection fraction (EF) we achieved a Pearson’s r of 0.95, an Intraclass correlation coefficient (ICC) of 0.97, and a Coefficient of variability (CoV) of 6.6%. Dice scores were 0.88 for the left ventricle and 0.84 for the myocardium.