Monte Carlo simulations of polyion−macroion complexes. 1. Equal absolute polyion and macroion charges

Intermolecular structures of complexes formed between a charged polymer and a spherical and oppositely charged macroion have been studied by employing the primitive model solved by Monte Carlo simulations. The strong-complex case involving a polyion and a macroion with equal absolute charges and without small ions was considered. The influence of the polyion flexibility with a bare persistence length ranging from 7 to 1000 Å for four different systems characterized by different polyion linear charge densities and macroion sizes has been examined. Radial distributions, polyion bead complexation probabilities, loop, tail, and train characteristics, and energetic analysis have been performed. The strongest and most compact complex, involving a collapsed polyion wrapping the macroion, was formed for a semiflexible chain. As the stiffness was increased, this state was transformed into a range of different structures comprising “tennis ball seam”-like, solenoid, multiloop (“rosette”), and single-loop arrangements as well as structures involving only a single polyion-macroion contact region

Contemporary foreign language teachers training

The article deals with contemporary foreign language teacher’s training. Based on experience it is analyzed foreign language teacher’s training system in Russia and noted specific tendencies in teacher’s training and his/her personal qualities. The authors consider innovative approaches directed to contemporary teacher of the 21-st century who is a central facilitator of a foreign language educational process. Due to the research there were established the most effective learning techniques for development of teacher’s methodological thinking and his/her personal qualities formation (communication skills, empathy, creativity, reflexivity etc.

Forming and developing students’ communicative competence: from reading to speaking

The goal of the research is to define the effective ways of students’ foreign language communicative competence formation by means of reading and speaking activities within the university English course. The article focuses on the concept of communicative competence and the ways to form i

Assessment of Relative Risk for Periodontitis Progression Using Neural Network Modeling: Cohort Retrospective Study

Background. Currently accepted risk assessments of periodontitis progression are determinants of indirect stability: periodontal pockets, persistent bleeding of the gums, tooth mobility, local risk factors. In the era of case-oriented medicine, a relevant solution would be to choose periodontal therapy according to one-time consideration of the maximum available range of individual risk factors rather than on general clinical guidelines.Objectives. The study was aimed at determining the relative risk of periodontitis progression after active basic therapy using neural network modeling.Methods. A cohort retrospective study was performed on 109 patients of both sexes, aged 30 to 70 years, after basic treatment of chronic periodontitis (mild, moderate and severe) in the period from 1999 to 2016, who were on supportive periodontal therapy (SPT) for 5 years ≤SPT≤ 20 years. The authors considered data from objective examination of the periodontium and categorical indices (24 in total) assessed before treatment, 4–6 months after basic (active) treatment and 5 years ≤SPT≤ 20 years. Following the analysis of descriptive statistics, target quantitative indices were determined for prognostic modeling of treatment outcomes in periodontitis patients and calculating the residual risk of disease progression. Statistical processing of obtained data was carried out using the Statistica 13.3 package (Tibco, USA). Mean values of the indicators at different time points were compared by means of Wilcoxon’s and Signs criteria; Spearman’s rank correlation coefficient was used to evaluate relevance between predictors and target indicators. The level of statistical significance p = 0.05 was accepted in all cases of analysis. DataMining, an automated neural network of Statistica software, was used as a tool to build neural network models. The task of classifying the level of risk of disease progression was solved by means of ROC analysis. The prognostic potential of the model was assessed using sensitivity and specificity measures.Results. The heterogeneous dynamics of predictor variables describing the state of the periodontium was determined. The outcomes of regenerative periodontal surgery, regardless of gender, age of patients and comorbidities, significantly outperformed those of other approaches, due to the formation of a new dentogingival attachment, although to different extent. Another positive functional outcome was recorded in restoring the dentition integrity by implantation, without any mutually damaging effects. Since revealing the interrelationships between indicators is not equivalent to the predictive value, prognostic models were built for target indicators and stratification of the relative risk of periodontitis progression using automated neural networks. The networks with the best prognostic properties were selected out of 1000 automatically built and trained neural networks — double-layer perceptrons. The sensitivity of the relative risk prognostic model on the training, control and test samples made up 90%, 67%, 80%; the specificity of the model made up 81.481%, 85.714%, 100%. Overall, in the cohort, the sensitivity and specificity accounted for 85.937% and 86.666%. The area under the curve (ROC AUC) is 0.859.Conclusion. The use of an artificial intelligence algorithm for the construction of neural networks for target predictors and stratification of the relative risk of periodontitis progression has advantages over classical methods — it is instrumental in solving classification and regression problems with categorical and quantitative predictor variables using data of arbitrary nature of large and small volumes. The practical implementation of the study results is reflected in the development of a relative risk calculator based on a written computer program

Thrombotic storm, hemostasis disorders and thromboinflammation in COVID-19

The rate of thrombosis and disseminated intravascular coagulation (DIC) has been increasing in COVID-19 patients. Key features related to such condition include minimal or no risk of bleeding, moderate thrombocytopenia, high plasma fibrinogen as well as complement components level in the areas of thrombotic microangiopathy. The clinical picture is not typical for classic DIC. This review systematizes the pathogenetic mechanisms of hypercoagulation in sepsis and its extreme forms in patients with COVID-19. The latter consist of the thrombosis-related immune mechanisms, the complement activation, the macrophage activation syndrome, the formation of antiphospholipid antibodies, the hyperferritinemia, and the dysregulation of the renin-angiotensin system. Taking into consideration the pathogenetic mechanisms, the biomarkers had been identified related to the prognosis of the disease development. Patients with pre-existing cardiovascular disease and other risk factors, including obesity, diabetes, hypertension, and aging pose the peak risk of dying from COVID-19. We also summarize new data on platelet and endothelial dysfunction, immunothrombosis, and, as a result, thrombotic storm as essential components of COVID-19 severe features

Genetics of psycho-emotional well-being: genome-wide association study and polygenic risk score analysis

BackgroundPsycho-emotional well-being is essential for living a life of satisfaction and fulfillment. However, depression and anxiety have become the leading mental health issues worldwide, according to the World Health Organization. Both disorders have been linked to stress and other psychological factors. Their genetic basis remains understudied.MethodsIn 2020–2021, the psycho-emotional well-being of 30,063 Russians with no known psychiatric history was assessed using the Hospital Anxiety and Depression Scale (HADS) for general mental health and the HADS subscale A (anxiety) for anxiety. Following the original instructions, an anxiety score of ≥11 points was used as the anxiety threshold. A genome-wide association study was performed to find associations between anxiety and HADS/HADS-A scores using linear and logistic regressions based on HADS/HADS-A scores as binary and continuous variables, respectively. In addition, the links between anxiety, sociodemographic factors (such as age, sex, and employment), lifestyle (such as physical activity, sleep duration, and smoking), and markers of caffeine and alcohol metabolism were analyzed. To assess the risk of anxiety, polygenic risk score modeling was carried out using open-access software and principal component analysis (PCA) to simplify the calculations (ROC AUC = 89.4 ± 2.2% on the test set).ResultsThere was a strong positive association between HADS/HADS-A scores and sociodemographic factors and lifestyle. New single-nucleotide polymorphisms (SNPs) with genome-wide significance were discovered, which had not been associated with anxiety or other stress-related conditions but were located in genes previously associated with bipolar disorder, schizophrenia, or emotional instability. The CACNA1C variant rs1205787230 was associated with clinical anxiety (a HADS-A score of ≥11 points). There was an association between anxiety levels (HADS-A scores) and genes involved in the activity of excitatory neurotransmitters: PTPRN2 (rs3857647), DLGAP4 (rs8114927), and STK24 (rs9517326).ConclusionOur results suggest that calcium channels and monoamine neurotransmitters, as well as SNPs in genes directly or indirectly affecting neurogenesis and synaptic functions, may be involved in the development of increased anxiety. The role of some non-genetic factors and the clinical significance of physiological markers such as lifestyle were also demonstrated

Self-consistent field theory for the interactions between keratin intermediate filaments

Background: Keratins are important structural proteins found in skin, hair and nails. Keratin Intermediate Filaments are major components of corneocytes, nonviable horny cells of the Stratum Corneum, the outermost layer of skin. It is considered that interactions between unstructured domains of Keratin Intermediate Filaments are the key factor in maintaining the elasticity of the skin. Results: We have developed a model for the interactions between keratin intermediate filaments based on self-consistent field theory. The intermediate filaments are represented by charged surfaces, and the disordered terminal domains of the keratins are represented by charged heteropolymers grafted to these surfaces. We estimate the system is close to a charge compensation point where the heteropolymer grafting density is matched to the surface charge density. Using a protein model with amino acid resolution for the terminal domains, we find that the terminal chains can mediate a weak attraction between the keratin surfaces. The origin of the attraction is a combination of bridging and electrostatics. The attraction disappears when the system moves away from the charge compensation point, or when excess small ions and/or NMF-representing free amino acids are added. Conclusions: These results are in concordance with experimental observations, and support the idea that the interaction between keratin filaments, and ultimately in part the elastic properties of the keratin-containing tissue, is controlled by a combination of the physico-chemical properties of the disordered terminal domains and the composition of the medium in the inter-filament region. Keywords: Stratum corneum, Skin keratins, Intermediate filaments, Unstructured terminal domains, Bridging attractio

Mixed protein–polysaccharide interfacial layers : a self consistent field calculation study

Mixed interfacial films of protein and polysaccharide have been investigated using self consistent field (SCF) calculations. The colloidal interactions mediated by such composite layers between two approaching surfaces have been considered. Two types of systems have been studied: (a) covalently-bonded polysaccharide and protein, and (b) the excess presence of polysaccharide at the interface, occurring through electrostatic interaction with an already existing, oppositely charged, protein layer. Our calculations show that for covalently-bonded complexes, depending on the location of the protein–polysaccharide bond, the attachment of short uncharged chains to the protein can be detrimental to provision of repulsive colloidal forces by such complexes. We have attributed this to an increased tendency of the hybrid polymer to adopt bridging configurations in the gap between two nearby surfaces. For larger grafted chains this bridging effect is eliminated, and the expected enhanced steric stabilization of the protein–polysaccharide conjugate is achieved. For adsorbed films formed through electrostatic interactions between these two biopolymers, stronger repulsive forces between the surfaces are produced, at an intermediate level of charging for the polysaccharides. This has been related to a maximum level of adsorption of polysaccharide, as the number of charged segments of the chain is varied. The peak occurs at higher levels of charging as the salt concentration in the bulk solution is increased. We have also observed the experimentally-reported phenomenon of charge overcompensation, arising from adsorption of the polysaccharide chains onto the primary protein layer. The importance of the non-uniform charge distribution of the polysaccharide molecule, in providing an explanation for this effect, has been demonstrated