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
We develop a human-machine interaction via dashboard for COVID-19 data visualization in the regions of Russia and the world. In particular, it includes an adaptive-compartmental multi-parametric model of the epidemic spread, which is a generalization of the classical SEIR models;and a module for visualizing and setting the parameters of this model according to epidemiological data, implemented in a dashboard. Data for testing have been collected since March 2020 on a daily basis from open Internet sources and placed on a “data farm” (an automated system for collecting, storing and pre-processing data from heterogeneous sources) hosted on a remote server. The combination of the proposed approach and its implementation in the form of a dashboard with the ability to conduct visual numerical experiments and compare them with real data allows most accurately tune the model parameters thus turning it into an intelligent system to support a decision-making. That is a small step towards Industry 5.0. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
For cooling small volume compartments, the thermoelectric systems have a number of advantages over the classic compressor refrigerators. Their priority is due to the active components in their design - Peltier modules which are chemically inactive, have no moving parts and do not practically need maintenance [1-2]. The thermoelectric cooling systems have the potential to meet the requirements for storing and transportation of vaccines and other medical solutions at low temperatures posed by the global pandemic of Covid-19. The electrical systems in the vehicles are excellent prerequisite for compatibility with the thermoelectric refrigerators requiring stable power supply.The aim of the present work was to design, realize and study a prototype of a small scale mobile thermoelectric cooling system for negative temperatures based on Peltier modules. © 2021 IEEE.
ABSTRACT
A systemic approach to the study of a new multi-parameter model of the COVID-19 pandemic spread is proposed, which has the ultimate goal of optimizing the manage parameters of the model. The approach consists of two main parts: 1) an adaptive-compartmental model of the epidemic spread, which is a generalization of the classical SEIR model, and 2) a module for adjusting the parameters of this model from the epidemic data using intelligent optimization methods. Data for testing the proposed approach using the pandemic spread in some regions of the Russian Federation were collected on a daily basis from open sources during the first 130 days of the epidemic, starting in March 2020. For this, a so-called "data farm" was developed and implemented on a local server (an automated system for collecting, storing and preprocessing data from heterogeneous sources, which, in combination with optimization methods, allows most accurately tune the parameters of the model, thus turning it into an intelligent system to support management decisions). Among all model parameters used, the most important are: the rate of infection transmission, the government actions and the population reaction. © 2021, Mathematical Biology and Bioinformatics. AllRights Reserved