31 research outputs found

    UNIVERSITY INTELLECTUAL CAPITAL FORMATION AND DEVELOPMENT

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    Purpose of the study: One of the most important terms to solve the problems of the education system is the educational institution’s intellectual capital, which significantly transforms the role and functions of the modern educator. The purpose of the article is to identify the essence of the University's intellectual capital and to justify the trajectory of its development, due to the needs and capabilities of education stakeholders. Methodology: Based on the methodology of education quality management the article justifies the leading role of quality education as an imperative of the University development. Intellectual capital is considered from the standpoint of organizational resources that determine the cost of the final product – the quality of education and the competitive position of the University; its development is carried out based on the project-target approach. Results: Modern requirements for the intellectual capital of the educational organization are revealed, the role and essence of pedagogical activity of teachers of higher education institutions in its formation are shown. The importance of continuous improvement of hard and soft competencies of University teachers as a way of incrementing intellectual capital is shown. The adaptive model’s design of University teachers’ career strategies based on design-target mechanisms is presented that determines the organizational development of the University. Applications of this study: The results determined the possibility to consider organizational and human knowledge and competence as a special type of investment to improve the functioning of the University. The recommendations for the construction of models of the University intellectual capital management are presented. The article is intended for employees of the education system, educators, researchers, and heads of the University departments. Novelty/Originality of this study: The contribution is made to the theory of the University’s social and cognitive management based on expanding the powers of quality management in the field of intellectual capital management

    Phosphorylation controls autoinhibition of cytoplasmic linker protein-170

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    Author Posting. © American Society for Cell Biology, 2010. This article is posted here by permission of American Society for Cell Biology for personal use, not for redistribution. The definitive version was published in Molecular Biology of the Cell 21 (2010): 2661-2673, doi:10.1091/mbc.E09-12-1036.Cytoplasmic linker protein (CLIP)-170 is a microtubule (MT) plus-end-tracking protein that regulates MT dynamics and links MT plus ends to different intracellular structures. We have shown previously that intramolecular association between the N and C termini results in autoinhibition of CLIP-170, thus altering its binding to MTs and the dynactin subunit p150Glued (J. Cell Biol. 2004: 166, 1003–1014). In this study, we demonstrate that conformational changes in CLIP-170 are regulated by phosphorylation that enhances the affinity between the N- and C-terminal domains. By using site-directed mutagenesis and phosphoproteomic analysis, we mapped the phosphorylation sites in the third serine-rich region of CLIP-170. A phosphorylation-deficient mutant of CLIP-170 displays an "open" conformation and a higher binding affinity for growing MT ends and p150Glued as compared with nonmutated protein, whereas a phosphomimetic mutant confined to the "folded back" conformation shows decreased MT association and does not interact with p150Glued. We conclude that phosphorylation regulates CLIP-170 conformational changes resulting in its autoinhibition.This work was supported by National Institutes of Health grant GM-25062 (to G.G.B.); Netherlands Organization for Scientific Research grants (to A. A. and N. G.); a Cancer Genomics Centre grant (to J.v.H.); and Presidential Program of Russian Academy of Sciences and RFBP grant 05-04-4915 (to E.S.N.)

    Detection of regulatory SNPs in human genome using ChIP-seq ENCODE data.

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    A vast amount of SNPs derived from genome-wide association studies are represented by non-coding ones, therefore exacerbating the need for effective identification of regulatory SNPs (rSNPs) among them. However, this task remains challenging since the regulatory part of the human genome is annotated much poorly as opposed to coding regions. Here we describe an approach aggregating the whole set of ENCODE ChIP-seq data in order to search for rSNPs, and provide the experimental evidence of its efficiency. Its algorithm is based on the assumption that the enrichment of a genomic region with transcription factor binding loci (ChIP-seq peaks) indicates its regulatory function, and thereby SNPs located in this region are more likely to influence transcription regulation. To ensure that the approach preferably selects functionally meaningful SNPs, we performed enrichment analysis of several human SNP datasets associated with phenotypic manifestations. It was shown that all samples are significantly enriched with SNPs falling into the regions of multiple ChIP-seq peaks as compared with the randomly selected SNPs. For experimental verification, 40 SNPs falling into overlapping regions of at least 7 TF binding loci were selected from OMIM. The effect of SNPs on the binding of the DNA fragments containing them to the nuclear proteins from four human cell lines (HepG2, HeLaS3, HCT-116, and K562) has been tested by EMSA. A radical change in the binding pattern has been observed for 29 SNPs, besides, 6 more SNPs also demonstrated less pronounced changes. Taken together, the results demonstrate the effective way to search for potential rSNPs with the aid of ChIP-seq data provided by ENCODE project

    Determining the Opinions of University Students on the Education They Receive with Technology During the Pandemic Process

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    In this study, it was aimed to determine the opinions of university students studying in the Department of Electrical Engineering about the distance education process they received during the pandemic. The quantitative research method was used in the research. The research consisted of 390 volunteer university students studying at 16 universities in Russia; the universe of the research was determined as the distance education system and the sample was determined as ‘Microsoft Teams’. In order to collect the data of the research, a measurement tool called ‘technology use’ developed by the researchers was used and applied. For the measurement tool, help was received from experts in the field and have worked in these fields. The data were shared with university students via an online questionnaire and their participation was ensured and collected. When looking at the research, it was stated that university students frequently used their distance education centre infrastructure with Microsoft Teams infrastructure in the distance education process and they used Microsoft Teams elements in the activities. When the results of the research are discussed, they stated that the technology levels of the university students were high; that they learned the whiteboard and electric fields in the classroom activities; and that the topics covered and the questions solved in the lessons were high with the re-watch method

    A variety of SNP effects on binding of the corresponding oligonucleotides to nuclear proteins from K562 cells.

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    <p>rs79734816:C>T (<i>A</i>), rs2071002:A>C (<i>B</i>), and rs74393987:C>T (<i>C</i>) change the number and intensity of bands, while rs75996864:G>T (<i>D</i>) affect only band intensity, and 7961894:C>T (<i>E</i>) do not have any. Changes in the binding of allelic variants with the nuclear proteins are indicated by arrows.</p

    enrichment of S<sub>gwas</sub> sample and its high-confidence derivatives, S<sub>pV</sub>, S<sub>OR</sub> and S<sub>int</sub>, as well as S<sub>r</sub> sample with putative rSNPs as a function of cut-off number of overlapping TF binding loci (<i>i</i>) for defining OTFRs.

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    <p>500 bootstrap iterations were performed for each point. The resulting standard deviations and confidence intervals are shown by error bars and colour-filled areas,respectively. The subsamples of S<sub>gwas</sub> were generated with filtering of SNPs by P-value <1 e–7 (S<sub>pV</sub>), OR>3 and <0.3 (S<sub>OR</sub>), and by both criteria (S<sub>int</sub>). S<sub>gwas</sub> sample was extracted from NHGRI GWAS catalog.</p

    Antimicrobial Resistance and Comparative Genomic Analysis of Elizabethkingia anophelis subsp. endophytica Isolated from Raw Milk

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    Elizabethkingia anophelis is an emerging multidrug-resistant pathogen that causes severe nosocomial and community-acquired infections worldwide. We report the first case of E. anophelis isolation in Russia and the first isolation from raw cow&rsquo;s milk. The ML-44 demonstrated resistance to 28 antimicrobials of 33 tested in the disk-diffusion test. Whole genome-based phylogeny showed ML-44 strain clustered together with the F3201 strain isolated from a human patient in Kuwait in 1982. Both strains were a part of the &ldquo;endophytica&rdquo; clade. Another clade was formed by subsp. anophelis strains. Each of the E. anophelis compared genomes carried 18 to 21 antibiotic resistance determinants. The ML-44 chromosome harbored nine efflux system genes and three beta-lactamase genes, along with six other antimicrobial resistance genes. In total, 72 virulence genes were revealed. The set of virulence factors was quite similar between different E. anophelis strains and included LPS and capsule encoded genes, type IV pili, oxidative stress response genes, and genes encoding TIVSS and TVISS effectors. The particular interest caused the mip and zmp1 gene homologs, which can be essential for intracellular survival. In sum, our findings suggest that raw milk might be a source of E. anophelis harboring a set of virulence factors and a broad resistance to generally used antimicrobials

    The used approach to genome-wide selection of rSNPs.

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    <p>Computational analysis was applied to identify the SNPs in the most likely regulatory regions of the human genome and predict rSNPs for experimental verification.</p
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