ABSTRACT
Assessment of viral load levels in various biological samples taken from the respiratory tract can be an indicator of an ongoing process of active viral replication and may be used to monitor severe respiratory viral infections. The study of the relationship between SARS-CoV-2 viral load and immunological laboratory parameters is an important step in the search for clinical markers of COVID-19. The aim of this research was to quantify viral load in patients with COVID-19 and to identify the relationship between viral load and changes in the parameters of the cellular component of the immune system. A laboratory examination was carried out on 74 patients diagnosed with COVID-19, they were divided into 3 groups based on the severity of the disease: mild, moderate, severe. Total viral load in clinical samples was determined by the number of SARS-CoV-2 RNA copies per 100 copies of the reference RNaseP gene. A comprehensive assessment of the cellular component of the immune system was performed using flow cytometry and direct monoclonal antibodies, and the IL-6, and C-reactive protein concentrations were determined. We revealed a relationship between the development of serious clinical conditions in the patients with COVID-19, and the levels of viral load. High levels of viral RNA in biological samples correlate with main indicators of the T cell component of the immune system associated with disease severity. In a subgroup of patients with an extremely high viral load, strong positive correlations were found between the relative numbers of cytotoxic lymphocytes (CD3+CD8+), activated T lymphocytes (CD3+HLA-DR+), as well as absolute and relative numbers of activated B lymphocytes and NK cells (CD3-CD25+). Laboratory monitoring of the cellular component of the immune system, along with the assessment of viral loads, should improve early assessment of clinical condition in the patients with COVID-19. Changes in expression levels of activation markers on immune cells can be potentially viewed as indicators of recovery during COVID-19.Copyright © Nikitin Yu.V. et al., 2023 The article can be used under the Creative Commons Attribution 4.0 License.
ABSTRACT
Assessment of viral load levels in various biological samples taken from the respiratory tract can be an indicator of an ongoing process of active viral replication and may be used to monitor severe respiratory viral infections. The study of the relationship between SARS-CoV-2 viral load and immunological laboratory parameters is an important step in the search for clinical markers of COVID-19. The aim of this research was to quantify viral load in patients with COVID-19 and to identify the relationship between viral load and changes in the parameters of the cellular component of the immune system. A laboratory examination was carried out on 74 patients diagnosed with COVID-19, they were divided into 3 groups based on the severity of the disease: mild, moderate, severe. Total viral load in clinical samples was determined by the number of SARS-CoV-2 RNA copies per 100 copies of the reference RNaseP gene. A comprehensive assessment of the cellular component of the immune system was performed using flow cytometry and direct monoclonal antibodies, and the IL-6, and C-reactive protein concentrations were determined. We revealed a relationship between the development of serious clinical conditions in the patients with COVID-19, and the levels of viral load. High levels of viral RNA in biological samples correlate with main indicators of the T cell component of the immune system associated with disease severity. In a subgroup of patients with an extremely high viral load, strong positive correlations were found between the relative numbers of cytotoxic lymphocytes (CD3+CD8+), activated T lymphocytes (CD3+HLA-DR+), as well as absolute and relative numbers of activated B lymphocytes and NK cells (CD3-CD25+). Laboratory monitoring of the cellular component of the immune system, along with the assessment of viral loads, should improve early assessment of clinical condition in the patients with COVID-19. Changes in expression levels of activation markers on immune cells can be potentially viewed as indicators of recovery during COVID-19.Copyright © Nikitin Yu.V. et al., 2023 The article can be used under the Creative Commons Attribution 4.0 License.
ABSTRACT
To date, there is no consensus explaining the relationship between varying concentrations of IFNgamma and the severity of infection caused by SARS-CoV-2. The aim of this article was to analyze and formulate conclusions from the selected studies and publications, which, in sum, provide a potentially reasonable view on the role of IFNgamma in COVID-19 pathogenesis. This article highlights current data on the immunological role of IFNgamma which affects differentiation of naive T helper cells, acting as a polarizing factor. It activates the major histocompatibility complex (MHC) class I and II, by increasing the expression of MHC I/II subunits, inhibiting replication of the viral particles by initiating activation of interferon-stimulated genes followed by subsequent synthesis of antiviral proteins. Moreover, IFNgamma activates the production of cytokines by T cells, enhancing cytotoxic activity of the T killers. IFNgamma exerts immunostimulatory and immunomodulatory effects via STAT1, SOCS1 and PIAS genes, thus regulating activation of the JAK-STAT signaling pathway. A number of studies were considered where the patterns of changes in serum IFNgamma concentration were examined in viral infections and SARS-CoV-2. We performed a systemic analysis of the results of studies that showed a relationship between high concentrations of IFNgamma and COVID-19 severity. In a number of studies, the significantly high levels of IFNgamma in COVID-19 patients were often associated with a poor outcome of the disease. The median values of the IFNgamma concentration in severe COVID-19 were found to be significantly higher compared to the results obtained in the cases of moderate severity. It shows an increase, in parallel with viral load in the nasopharyngeal samples upon worsening of the clinical condition. Based on the data on the decreased IFNgamma concentrations in convalescent patients, the mechanism of antagonism between IFNgamma and IL-4 is considered, where the decreases serum concentrations of IFNgamma along with increasing level of IL-4 may be an indirect proof of normal adaptive immune response with subsequent development of antibodies to SARS-CoV-2 and gradual elimination of the virus from the body. Moreover, the evidence is discussed that the patients harboring some parasitic infections (Toxoplasma gondii, Cryptosporidium, Blastocystis hominis, Giardia duodenalis, Entamoeba histolytica) with persistently elevated level of IFNgamma are at reduced risk for severe course of COVID-19. Copyright © 2022, SPb RAACI.
ABSTRACT
To date, there is no consensus explaining the relationship between varying concentrations of IFNgamma and the severity of infection caused by SARS-CoV-2. The aim of this article was to analyze and formulate conclusions from the selected studies and publications, which, in sum, provide a potentially reasonable view on the role of IFNgamma in COVID-19 pathogenesis. This article highlights current data on the immunological role of IFNgamma which affects differentiation of naive T helper cells, acting as a polarizing factor. It activates the major histocompatibility complex (MHC) class I and II, by increasing the expression of MHC I/II subunits, inhibiting replication of the viral particles by initiating activation of interferon-stimulated genes followed by subsequent synthesis of antiviral proteins. Moreover, IFNgamma activates the production of cytokines by T cells, enhancing cytotoxic activity of the T killers. IFNgamma exerts immunostimulatory and immunomodulatory effects via STAT1, SOCS1 and PIAS genes, thus regulating activation of the JAK-STAT signaling pathway. A number of studies were considered where the patterns of changes in serum IFNgamma concentration were examined in viral infections and SARS-CoV-2. We performed a systemic analysis of the results of studies that showed a relationship between high concentrations of IFNgamma and COVID-19 severity. In a number of studies, the significantly high levels of IFNgamma in COVID-19 patients were often associated with a poor outcome of the disease. The median values of the IFNgamma concentration in severe COVID-19 were found to be significantly higher compared to the results obtained in the cases of moderate severity. It shows an increase, in parallel with viral load in the nasopharyngeal samples upon worsening of the clinical condition. Based on the data on the decreased IFNgamma concentrations in convalescent patients, the mechanism of antagonism between IFNgamma and IL-4 is considered, where the decreases serum concentrations of IFNgamma along with increasing level of IL-4 may be an indirect proof of normal adaptive immune response with subsequent development of antibodies to SARS-CoV-2 and gradual elimination of the virus from the body. Moreover, the evidence is discussed that the patients harboring some parasitic infections (Toxoplasma gondii, Cryptosporidium, Blastocystis hominis, Giardia duodenalis, Entamoeba histolytica) with persistently elevated level of IFNgamma are at reduced risk for severe course of COVID-19. Copyright © 2022, SPb RAACI.
ABSTRACT
One of the most significant and rapidly developing works in the field of data analysis is information flow management. Within the analysis targeted and stochastic dissemination patterns are studied. The solving of such problems is relevant due to the global growth in the amount of information and its availability for a wide range of users. The paper presents a study of dissemination of information messages in open networks on the example of COVID-19. The study was conducted with the use of visual analytics. Informational messages from the largest world and Russian information services, social networks and instant messengers were used as sources of information. Due to the large amount of information on the topic, the authors proposed a pattern of the wave-like dissemination of information on the example of topic clusters on the connection of COVID-19, hydroxychloroquine and 5G. The developed methods can be scaled up to analyze information events of various topics. © 2021 Copyright for this paper by its authors.
ABSTRACT
One of the most significant and rapidly developing fields of data analysis is information flow management. In the course of the analysis targeted and stochastic dissemination patterns are studied. The solving of such problems is daunting due to the global growth of the amount of information and its availability for a wide range of users. The paper presents a study of dissemination of information in open networks on the example of COVID-19. The study was conducted with the use of web scraping, methods of linguistic analysis and visual analytics. As sources of information variety of sources were used, such as the largest world and Russian information services, social networks and instant messengers. The paper considers statistical analysis of English media articles and posts form Twitter, dissemination of data flows between countries and information source. The developed methods can be scaled up to analyse information events of various topics. © 2021 National Research Nuclear University. All rights reserved.