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AIM: To assess the prevalence of chronic kidney disease (CKD), clinical and demographic characteristics and therapy profile in patients with type 2 diabetes admitted to multidisciplinary hospitals. CREDO (Cardio-REnal Diabetic cOmplications) trial was initiated for this purpose.MATERIALS AND METHODS: in a prospective observational multicenter study for the period from August 2022 to April 2023, data from 445 patients with type 2 diabetes hospitalized in multidisciplinary hospitals of the Moscow Department of Health were analyzed. The data was collected on a single visit. The design of the study did not involve any interventions in routine clinical practice, including the choice of a diagnostic or treatment method.RESULTS. The study included 445 patients with the main inclusion criteria — type 2 diabetes, age over 50 years, duration of diabetes more than 3 years. The prevalence of CKD was 90%, while in 43% the diagnosis of CKD was confirmed, in 43% it was detected for the first time, and in 7% the disease progressed. Patients with stage C2 and C3 (a and b), as well as with levels of A1 and A2 albuminuria, were most often identified. The percentage of patients in whom the albuminuria was not performed remained high — 46.2%. The highest incidence of CKD was observed in patients with inadequate glycemic control, having an HbA1c level of ≥9%. In the group with newly diagnosed CKD, sodium-glucose co-transporter-2 inhibitor (iSGLT-2) was received by 31.1% of patients, glucagon-like peptide-1 receptor agonists (GLP-1 RA) — 7.9% of patients. In the group with confirmed CKD — 30.7% and 9.4%, respectively.CONCLUSION: it has been shown that patients over the age of 50 with type 2 diabetes with a disease duration of more than 3 years are at a high risk of developing CKD — 90%. The results obtained convincingly confirm the possibility of detecting CKD and initiating nephroprotective therapy at the hospital stage.

Abstract Biomolecular condensates help cells organise their content in space and time. Cells harbour a variety of condensate types with diverse composition and many are likely yet to be discovered. Here, we develop a methodology to predict the composition of biomolecular condensates. We first analyse available proteomics data of cellular condensates and find that the biophysical features that determine protein localisation into condensates differ from known drivers of homotypic phase separation processes, with charge mediated protein-RNA and hydrophobicity mediated protein-protein interactions playing a key role in the former process. We then develop a machine learning model that links protein sequence to its propensity to localise into heteromolecular condensates. We apply the model across the proteome and find many of the top-ranked targets outside the original training data to localise into condensates as confirmed by orthogonal immunohistochemical staining imaging. Finally, we segment the condensation-prone proteome into condensate types based on an overlap with biomolecular interaction profiles to generate a Protein Condensate Atlas. Several condensate clusters within the Atlas closely match the composition of experimentally characterised condensates or regions within them, suggesting that the Atlas can be valuable for identifying additional components within known condensate systems and discovering previously uncharacterised condensates.

BACKROUND: Heart failure (HF) is in the first place in the structure of cardiovascular death in patients with type 2 diabetes mellitus (T2D). One of the factors determining the prognosis of patients with this pathology is hospitalization. The difficulties of managing patients are related to the heterogeneity of the population. In some cases, HF in patients with T2D remains undiagnosed, and data on the true frequency of HF in patients with T2D and their clinical and laboratory characteristics in real clinical practice remain limited.AIM: To assess the prevalence of HF, clinical and demographic characteristics and therapy profile in patients with T2D admitted to multidisciplinary hospitals.MATERIALS AND METHODS: A prospective observational multicenter study was conducted at the city clinical hospitals of the Moscow. For the period from August 2022 to April 2023, data from patients with T2D were analyzed. Data collection was carried out at one visit. The study design did not involve any intervention in routine clinical practice, including the choice of diagnostic method or treatment.RESULTS: The study included 445 patients in accordance with the main inclusion criteria - T2D, age over 50 years, duration of T2D more than 3 years. The incidence of HF in patients with type 2 diabetes at discharge was 76.6%. The diagnosis of HF was confirmed in 48.7% (n=217), newly diagnosed HF occurred in 27.9% (n=124) of cases, in 12.6% of patients (n=56) the diagnosis of HF was withdrawn, in 10.8% (n=48) of cases the diagnosis of HF was not established. The frequency of prescribing drugs at discharge was iSGLT-2 — 77.3% (n=344), statins — 86.7% (n= 386), MRAs — 23.1% (n=103), diure­tics — 46.1% (n=205).CONCLUSION: 76.6% of patients with T2D admitted to multidisciplinary Moscow hospitals were diagnosed with HF at discharge. The results obtained confirm the possibility of detecting HF and initiating cardioprotective therapy at the hospital stage, using inpatient clinical diagnostic examination, and patients with type 2 diabetes lasting more than 3 years and aged over 50 years can be classified as a high risk group for developing HF.

Societal Impact Statement Humankind is facing both climate and biodiversity crises. This article proposes the foundations of a scheme that offers tradable credits for combined aboveground and soil carbon and biodiversity. Multidiversity—as estimated based on high‐throughput molecular identification of soil meiofauna, fungi, bacteria, protists, plants and other organisms shedding DNA into soil, complemented by acoustic and video analyses of aboveground macrobiota—offers a cost‐effective method that captures much of the terrestrial biodiversity. Such a voluntary crediting system would increase the quality of carbon projects and contribute funding for delivering the Kunming‐Montreal Global Biodiversity Framework. Summary Carbon crediting and land offsets for biodiversity protection have been developed to tackle the challenges of increasing greenhouse gas emissions and the loss of global biodiversity. Unfortunately, these two mechanisms are not optimal when considered separately. Focusing solely on carbon capture—the primary goal of most carbon‐focused crediting and offsetting commitments—often results in the establishment of non‐native, fast‐growing monocultures that negatively affect biodiversity and soil‐related ecosystem services. Soil contributes a vast proportion of global biodiversity and contains traces of aboveground organisms. Here, we outline a carbon and biodiversity co‐crediting scheme based on the multi‐kingdom molecular and carbon analyses of soil samples, along with remote sensing estimation of aboveground carbon as well as video and acoustic analyses‐based monitoring of aboveground macroorganisms. Combined, such a co‐crediting scheme could help halt biodiversity loss by incentivising industry and governments to account for biodiversity in carbon sequestration projects more rigorously, explicitly and equitably than they currently do. In most cases, this would help prioritise protection before restoration and help promote more socially and environmentally sustainable land stewardship towards a ‘nature positive’ future.

Raman spectroscopy, renowned for its unique ability to provide a molecular fingerprint, is an invaluable tool in industry and academic research. However, various constraints often hinder the measurement process, leading to artifacts and anomalies that can significantly affect spectral measurements. This review begins by thoroughly discussing the origins and impacts of these artifacts and anomalies stemming from instrumental, sampling, and sample-related factors. Following this, we present a comprehensive list and categorization of the existing correction procedures, including computational, experimental, and deep learning (DL) approaches. The review concludes by identifying the limitations of current procedures and discussing recent advancements and breakthroughs. This discussion highlights the potential of these advancements and provides a clear direction for future research to enhance correction procedures in Raman spectral analysis.

African swine fever (ASF) is an emerging disease caused by the African swine fever virus (ASFV), which is a great threat to the swine industry worldwide. Currently registered vaccines that have demonstrated protection against the homologous ASFV strains are live attenuated vaccines based on recombinant ASFV strains with the deletions of virulence-associated genes. In this study, we evaluated the deletion of the A137R gene in the ASFV virulent Stavropol_01/08 strain isolated in Russia in 2008. Our animal experiment results demonstrated that the deletion of the A137R gene did not lead to the full attenuation of this strain, and increasing the dose of the A137R-deletion mutant during infection led to the death of 87.5% of the infected animals. In this report, we also demonstrated that immunofluorescence (IFA) and Western blotting assays based on the recombinant p11.5 protein can be used to detect antibodies in animals infected with the attenuated ASFV variants of several genotypes/serotypes. Both assays were specific to ASFV p11.5 protein and showed negative results when examining the sera of the non-infected animals or those infected with the A137R-deletion mutant. Therefore, we propose to use the p11.5 protein along with other previously proposed ASFV proteins, such as CD2v, as negative antigenic DIVA markers for an attenuated ASF vaccine.

The "purpose" of this study was to find out how students and teachers perceive the automation of the specialists' professional training process and the impact factors of perceiving the learning activity of such kind by students and faculty. The experimental model of automated learning was based on an express course in the academic subjects "Roman Private Law" and "Latin (Latin Law Phraseology)". The following methods were used to analyze the quantitative data: Chi-Square statistical method and triangulation. STATA Software was used to process the data. An online Text Analyzer utility was used to process the answers of the focus group respondents to determine the research categories. Automation of the professional training process has a positive impact on education and greatly enhances the opportunities for both teachers and students making it possible to effectively solve the key task of higher education -- to teach the student an autonomous learning, as it forms the skills of managing their own time, self-organization, self-motivation, and reflection. Automation of the professional training process through the use of innovative pedagogical technologies brings about a number of new opportunities and advantages, such as: "prominence" (detailed elaboration of professional processes with different levels), "interactivity" (ability to control and influence the process), "focusing" (allows to remove distracting factors, to concentrate on the material). In the proposed automated model, Chatbot can be programmed so that the course participant will not feel the difference between the language of the real person and the machine. Queries that cannot be processed by Chatbot are answered by the course administrator/moderator via email. This model can be adapted and upgraded to teach other professionally oriented theoretical and applied courses. In addition, Chatbot can be used by higher education institutions in managing a university admissions process to provide applicants with information about admission requirements, programmes, specialties, etc.

In this study, a detailed analysis of the use of standardized deformation models is carried out to calculate the design characteristics of reinforced concrete elements, such as crack resistance. For theoretical verification of the values of the moment of cracking, calculation methods based on the use of a nonlinear deformation model are used.A theoretical study of cracking moment using a non-linear deformation model shows that the application of a two-line diagram of concrete deformation allows to obtain the most accurate values of cracking moment.

African swine fever (ASF) is a lethal hemorrhagic disease of Suidae, i.e., domestic pigs and wild boars, caused by African swine fever virus (ASFV). The development of cross-protective vaccines against ASF is imperative for effective disease control, particularly in regions where ASF is endemic, potentially featuring multiple circulating ASFV isolates. The investigation of non-hemadsorbing naturally attenuated isolates and laboratory recombinant strains with a deletion in the EP402R gene has attracted interest. Our study aimed to assess the impacts of various administration routes and doses of the naturally attenuated ASFV-PSA-1NH (immunotype IV, genotype I) isolate on the manifestation of clinical signs of ASF and the level of protection against the heterologous ASFV-Stavropol 01/08 strain (seroimmunotype VIII, genotype II). The results demonstrated that the intranasal administration of a low dose of ASFV-PSA-1NH to pigs minimized the clinical signs of ASF and established a high level of protection against the heterologous strain ASFV-Stavropol 01/08. Despite the challenges in standardizing the dosage for intranasal administration, this approach appears as a viable alternative in ASF vaccination.

The study on the posibility of the use of the optimal glass compositions for vitrification of an imitator of vat residues of liquid radioactive waste from nuclear power plants with VVER-1000 reactors was carried out. The main process parameters such as vitrification temperature, strength, corrosion resistance, absence of crystalline phases, minimization of glass-forming additives and inclusion the maximum amount of waste were analyzed. It has been established that the melting temperature of lead-borosilicate glass matrices was 1150 °C, which satisfies the requirements for vitrification of low- and medium-level waste. The ultimate compressive strength of the obtained samples of glass matrices was 136.0 MPa. In addition, it has been shown that lead-borosilicate glass matrices are the most resistant to leaching. The cesium leaching rate was 1.5·10-5 g/cm2·day.

On the materials of the state archives of Samara, Kazan, Cheboksary and on published historical sources the article analyzes the preparations for the celebrations dedicated to the 300th anniversary ofthe Romanov dynasty. It is shownthat preparationsforthe holidaytook on a universal character, all segments of the population, independent of class, national, religious affiliation, were involved in the process of this preparation. Programs of celebrations are analyzed, they depended on a specific city, its material capabilities and the composition of the population. The festive program could include additional elements that differ in cities on the Volga. The author concludes that such large-scale festive events covering all segments of the population were an attempt to consolidate Russian society around the monarchy and the figure of Emperor Nicholas II after the revolutionary events of 1905–1907 and in the context of the beginning of a new social rise.

Abstract The effectiveness of therapeutic monoclonal antibodies (mAbs) against variants of the SARS-CoV-2 virus is highly variable. As target recognition of mAbs relies on tight binding affinity, we assessed the affinities of five therapeutic mAbs to the receptor binding domain (RBD) of wild type (A), Delta (B.1.617.2), and Omicron BA.1 SARS-CoV-2 (B.1.1.529.1) spike using microfluidic diffusional sizing (MDS). Four therapeutic mAbs showed strongly reduced affinity to Omicron BA.1 RBD, whereas one (sotrovimab) was less impacted. These affinity reductions correlate with reduced antiviral activities suggesting that affinity could serve as a rapid indicator for activity before time-consuming virus neutralization assays are performed. We also compared the same mAbs to serological fingerprints (affinity and concentration) obtained by MDS of antibodies in sera of 65 convalescent individuals. The affinities of the therapeutic mAbs to wild type and Delta RBD were similar to the serum antibody response, indicating high antiviral activities. For Omicron BA.1 RBD, only sotrovimab retained affinities within the range of the serum antibody response, in agreement with high antiviral activity. These results suggest that serological fingerprints provide a route to evaluating affinity and antiviral activity of mAb drugs and could guide the development of new therapeutics.

This study presents a mathematical description of the solid fraction aggregation process in the presence of a flocculant and its result. The basis is a population balance equation. The model is realized in Python language. Verification was carried out using red mud from the investigated enterprise; Flomin AL P 99 VHM was used as a flocculant. The mean square deviation for the parameter “mean aggregate diameter” is equal to 19.88 μm. The time required for the model calculation is about 3 min. The time spent on modeling depends on the number of calculation channels. In this study, 40 channels (20 with PSD source data, and 20 with empty values required for the calculation) were used for the calculation. The time spent on the model calculation is much shorter than the inertia via each of the communication channels for the studied symmetric radial type thickener. A user interface is developed, where the input parameters are the initial pulp particle size distribution, viscosity and density of pulp in the thickener, particle surface area, concentration and flow rate of flocculant, concentration of solid particles, inner diameter and height of the feed well, and simulation time. The result of the simulation is particle size distribution in the feed well of the washer and the mean flocculus diameter.