THEORETICAL APPROACHES TO THE STUDY OF FUNCTIONS, STRUCTURE AND ELEMENTS OF THE SYSTEM OF PROFESSIONAL CULTURE OF CIVIL SERVANTS

The object of the research is the functions, structure and elements of civil servants’ professional culture system. It is undergoing transformation, following the changes that public administration undergoes under the influence of a service/client-centric development trend that meets current societal transformations and the possibilities of the technological revolution. The goal of the study is to systematize the range of mechanisms for developing a modern professional culture of civil service, primarily from the standpoint of client-centricity. The objectives are to identify the clientcentered governance values, highlighting the main characteristics of the modern professional civil service culture, which can be treated as the fundamental basis for its development; analyze modern tools for the formation and development of key values of civil servants, including, first of all, the values of the client-centered state. The research method is the review of scientific and professional sources from the standpoint of their reflecting the conceptual and instrumental aspects of the formation of the professional civil service culture. As a result, numerous characteristics of the modern professional civil service culture are identified, which can be attributed to the fundamental basis for the development of a client-centered culture and are based on the generalization of foreign and Russian experience. An ecosystem approach to the formation and development of components of a client-centered professional civil service culture is proposed. The novelty of this research work is determined by the lack of Russian or foreign scientific studies of tools that would be directly focused on the development of a client-centered professional culture, as well as the technologies through which these tools are to be used. Theprospects are related to the relevance of the introduction of client-centricity in the Russian government agencies, in accordance with the testing of respective tools, which began in 2022. They are also related to the need to update the scientific agenda of the professional culture formation with the issue of the productivity of introducing the values of client-centricity into the activities of government authorities

Features of statistical methods application in rating construction

The article is devoted to solving the problem of rating construction methodology, including issues of comparability in dynamics and inconsistency. The study analyzes approaches to the procedures for aggregating private components of the rating. Attention is focused on the shortcomings of ratings used in international and domestic practice as integral meters, among which are the incompleteness of information on the private components of ratings, an unacceptably high level of error in the development of ratings as integral meters and the lack of evaluation of their quality. The approach to rating construction on the basis of average weighted sum of ranks is offered. The ratio of the sum of the squares of the rank paired coefficients of the private rating to the total sum of the squares of the rank coefficients for all private ratings (the matrix of squares of rank correlations) is used as weights. The approach proposed by the authors, in contrast to the existing methodological approaches, makes it possible to build a rating in the absence of information about private components. The novelty of the study results lies in the method of estimating weights of private ratings as basic components of the rating. The article presents the results of construction a rating of the regions of the Central Federal District in Russia for achieving national goals in 2021 based on private ratings, which confirmed the adequacy of the proposed approach. The article may be of interest to a wide range of researchers in the field of statistics and regional economics

Face validity of four preference-weighted quality-of-life measures in residential aged care: a think-aloud study

Objective There is an increased use of preference-weighted quality-of-life measures in residential aged care to guide resource allocation decisions or for quality-of-care assessments. However, little is known about their face validity (i.e., how understandable, appropriate and relevant the measures are ‘on their face’ when respondents complete them). The aim of this study was to assess the face validity of four preference-weighted measures (i.e., EQ-5D-5L, EQ-HWB, ASCOT, QOL-ACC) in older people living in residential aged care. Methods Qualitative cognitive think-aloud interviews were conducted using both concurrent and retrospective think-aloud techniques. To reduce burden, each resident completed two measures, with the four measures randomised across participants. Audio recordings were transcribed and framework analysis was used for data analysis, based on an existing framework derived from the Tourangeau four-stage response model. Results In total, 24 interviews were conducted with residents living across three residential aged care facilities in Melbourne, Australia. Response issues were identified across all four measures, often related to comprehension and difficulty selecting a response level due to double-barrelled and ambiguous items that have different meanings in the residential aged care context. We also identified issues related to understanding instructions, non-adherence to the recall period, and noted positive responding that requires attention when interpreting the data. Conclusions Our findings provide further evidence on the appropriateness of existing measures, indicating numerous response issues that require further research to guide the selection process for research and practice

Efficacy and safety of ultra-low dose inhaled melphalan in the treatment of hospitalized patients with COVID-19

Background. One of the most important components of COVID-19 therapy is the suppression of the hyperergic immune response. There is an urgent need of creating the optimal tactics of efficient and safe anti-inflammatory therapy. A new method of treatment of COVID-19 with inhalation of ultra-low (non-cytotoxic) doses of the alkylating drug melphalan is proposed, based on previous experimental, preclinical, and clinical data on its use in severe bronchial asthma.The aim. To evaluate the efficacy and safety of inhalation of ultra-low doses of melphalan in hospitalized patients with COVID-19-associated lung damage.Materials and methods. A prospective, open, controlled, blind for the central expert study was conducted. Sixty adult patients were included, 30 patients were consecutively admitted to the hospital and received nebulized inhalations of 0.1 mg of melphalan for 7 days. Thirty patients of the control group were selected by an independent expert retrospectively using the computer algorithm for selecting «close» patients based on the «case-control» principle. The primary endpoints were the dynamics on the WHO Clinical Improvement Scale and the dynamics of dyspnea according to the modified Borg scale, secondary – assessment of adverse events, dynamics of indicators of clinical, biochemical blood tests, lungs computed tomography data from the beginning of inhalations in the melphalan group and from the corresponding day in the control group.Results. Inhalations of melphalan led to a significant improvement in the clinical condition of patients according to the WHO scale, decrease in the intensity of dyspnea on day 7 of treatment and by the time of discharge, a significant anti-inflammatory effect. Adverse events and dynamics of laboratory parameters did not differ from the control group.Conclusion. The method of treatment of COVID-19 by inhalation of ultra-low doses of the alkylating drug melphalan is safe and leads to a significant clinical improvement of hospitalized patients with COVID-19-associated lung damage

Predicting mostly disordered proteins by using structure-unknown protein data

BACKGROUND: Predicting intrinsically disordered proteins is important in structural biology because they are thought to carry out various cellular functions even though they have no stable three-dimensional structure. We know the structures of far more ordered proteins than disordered proteins. The structural distribution of proteins in nature can therefore be inferred to differ from that of proteins whose structures have been determined experimentally. We know many more protein sequences than we do protein structures, and many of the known sequences can be expected to be those of disordered proteins. Thus it would be efficient to use the information of structure-unknown proteins in order to avoid training data sparseness. We propose a novel method for predicting which proteins are mostly disordered by using spectral graph transducer and training with a huge amount of structure-unknown sequences as well as structure-known sequences. RESULTS: When the proposed method was evaluated on data that included 82 disordered proteins and 526 ordered proteins, its sensitivity was 0.723 and its specificity was 0.977. It resulted in a Matthews correlation coefficient 0.202 points higher than that obtained using FoldIndex, 0.221 points higher than that obtained using the method based on plotting hydrophobicity against the number of contacts and 0.07 points higher than that obtained using support vector machines (SVMs). To examine robustness against training data sparseness, we investigated the correlation between two results obtained when the method was trained on different datasets and tested on the same dataset. The correlation coefficient for the proposed method is 0.14 higher than that for the method using SVMs. When the proposed SGT-based method was compared with four per-residue predictors (VL3, GlobPlot, DISOPRED2 and IUPred (long)), its sensitivity was 0.834 for disordered proteins, which is 0.052–0.523 higher than that of the per-residue predictors, and its specificity was 0.991 for ordered proteins, which is 0.036–0.153 higher than that of the per-residue predictors. The proposed method was also evaluated on data that included 417 partially disordered proteins. It predicted the frequency of disordered proteins to be 1.95% for the proteins with 5%–10% disordered sequences, 1.46% for the proteins with 10%–20% disordered sequences and 16.57% for proteins with 20%–40% disordered sequences. CONCLUSION: The proposed method, which utilizes the information of structure-unknown data, predicts disordered proteins more accurately than other methods and is less affected by training data sparseness

Влияние воспаления и мутаций митохондриального генома на клеточные механизмы атерогенеза

Atherosclerosis is a leading cause of cardiovascular diseases. It is responsible for heart attacks and strokes due to the critical narrowing of the arteries. Atherosclerosis is an inflammatory disease that affects various arteries in the human body. The pathological process is accompanied by the focal thickening of the intima of the affected arteries. The last contributes to plaques building up as the disease progresses. The exploration of atherosclerotic mosaicism, either local or focal, is regarded as one of the most promising research areas. Many hypotheses have been suggested to explain this phenomenon. We suppose that mosaic atherosclerotic lesions are caused by genetic variations. Variations in the nuclear and mitochondrial genes of the arterial wall cells affect the development of atherosclerosis. The presence of these variations may be considered as novel markers suggesting the disease predisposition, its progression, and potential prognosis.В настоящее время одним из наиболее распространенных возрастных заболеваний является атеросклероз коронарных артерий, впоследствии вызывающий заболевания сердечно-сосудистой системы. Инфаркт и инсульт - осложнения атеросклеротического процесса вследствие критического сужения артерий соответствующей локализации. Атеросклероз представляет собой воспалительное заболевание и поражает различные артерии в организме человека. Патологический процесс сопровождается очаговым утолщением интимы пораженных артерий, в которых по мере прогрессирования заболевания образуются атеросклеротические бляшки. Одним из перспективных направлений изучения патогенеза атеросклероза является исследование мозаичности атеросклеротических поражений, их локального или очагового характера. В настоящее время существует множество гипотез, объясняющих этот феномен, но, на наш взгляд, наиболее убедительным представляется генетическое обоснование мозаичности атеросклеротических поражений. Вариации в генах ядра и митохондрий клеток артериальной стенки, безусловно, влияют на развитие атеросклероза. Выявление таких изменений можно рассматривать для оценки предрасположенности к заболеванию, его прогрессирования и прогноза

Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multi-national data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar was found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-negligible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic