Distribution of superconducting properties among metal hydrides was investigated using stateof-the-art computational simulation techniques. We proposed a search rule for high-T C metalhydrogen systems based on analysis of electronic structure of atomic s, d, f-orbitals. Results of actinides and lanthanides study show that they form highly symmetric superhydrides XH 7-9 at relatively low pressures. However, actinides do not exhibit high-temperature superconductivity (except for Th-H system) and should not be considered as materials appropriate for experimental studies, as well as all d m -elements with m > 4 including metal hydrides of the precious elements. A refinement rule based on monotonic behavior of the maximum achievable critical temperature as a function of d+f electrons, maxT C (N d+f ), was proposed for already known materials. Using this rule, the reported T C values for the higher hydrides in K-H, Zr-H, Hf-H and Ti-H systems were corrected. The dependences of maxT C on the group number, period, pressure, and phase composition of hydrides were investigated. Developed model enables to make new targeted predictions relating to existence of new superconducting compounds. For Mg-H, Sr-H, Ba-H, Cs-H, Rb-H, we predict the existence of new high-T C phases XH n with n ≥ 10. Electron doping of H-sublattice by pressure-driven delocalization of d,f-electrons is suggested as the key factor for determining superconductive properties of polyhydrides. Graphical abstract:

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Materials and methods. 253 patients with chronic hepatitis C (CHC) and liver cirrhosis were included in the study. Assessment of gene polymorphisms of genes involved in inflammatory reactions and antiviral immunity (IL-1β-511C/T, IL-10 -1082G/A, IL28B C/T, IL28B T/G, TNF-α -238G/A, TGF-β -915G/C, IL-6 -174G/C), activators of local hepatic fibrosis (AGT G-6A, AGT 235 M/T, ATR1 1166 A/C), hemochromatosis (HFE C282Y, HFE H63D), platelet receptors (ITGA2 807 C/T, ITGB3 1565 T/C), coagulation proteins and endothelial dysfunction (FII 20210 G/A, FV 1691G/A, FVII 10976 G/A, FXIII 103 G/T, eNOS 894 G/T, CYBA 242 C/T, FBG -455 G/A, PAI-675 5G/4G, MTHFR 677 C/T) was carried. Using Bayesian networks we studied the predictor value of clinical and laboratory factors for the following conditions - end points (EP): development of cirrhosis (EP1), fibrosis rate (EP2), presence of portal hypertension (EP3) and cryoglobulins (EP4). Results and discussion. In addition to traditional factors we have shown the contribution of the following mutations. Predicting EP1- liver cirrhosis - HFE H63D, C282Y, CYBA 242 C/T, AGT G-6G, ITGB31565 T/C gene mutations were significant. We also found a link between the rate of progression of liver fibrosis and gene polymorphisms of AGT G-6G, AGT M235T, FV 1691G/A, ITGB31565 T/C. Among the genetic factors associated with portal hypertension there are gene polymorphisms of PAI-I-675 5G/4G, FII 20210 G/A, CYBA 242 C/T, HFE H63D and Il-6 174GC. Cryoglobulins and cryoglobuliemic vasculitis (EP4) are associated with gene mutations MTHFR C677T, ATR A1166C and HFE H63D. Conclusion. The results obtained allow to detect the major pathophysiological and genetic factors which determine the status of the patient and the outcome of the disease, to clarify their contribution, and to reveal the significance of point mutations of genes that control the main routes of HCV course and progression.

Healthcare of the Russian Federation, Moscow, Russian Federation. 4 Russian Cardiology Research and Production Complex of the Ministry of Healthcare of the Russian Federation, Moscow, Russian Federation.The genome-wide analysis of genetic associations with lipid metabolism indicators was carried out using the technology of Bayesian networks (BN). It was performed to diagnose polygenic hypercholesterolemia on the basis of genetic data of the Russian population of patients. The data of 1,200 patients was analyzed. 196725 SNPs as well as clinical data, lipid prole indicators dierent types of cholesterol were obtained for each of them. The genome-wide association analysis (GWAS) and the statistical method of Pearson's chisquared test were used for the initial selection of the most signicant parameters. Two of the patient states related to a lipid metabolism were studied. These states are the level of LDL-C (low density lipoprotein) and the level of HDL-C (high density lipoprotein). The Bayesian networks having the simplest topology naive were used to predict the level of lipoprotein. The construction of ROC-curves and the calculation of the area under these curves (AUC) were used to assess a quality (reliability) of the prediction. AUC value increased from 0,5 for the initial BN to 0,9 after selecting of signicant parameters using the GWAS method or the Pearson one. A further increase in AUC to 0,99 and decrease in the number of prognostic parameters to 150 was performed using Bayesian network optimization with respect to the number of parameters-nodes. Here the optimized function was value of AUC. The ambiguity of obtaining prognostic parameters at various ways of initial reducing the number of network nodes using the methods of GWAS and Pirson is shown. Low values of AUC were obtained for an independent control group of patients, despite very good results on the quality of the predictions, which were obtained on the training set. Further application of the proposed methodology is possible after the substantial reduction of the number of SNPs on the base of the analysis of the respective molecular mechanisms.