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1.
Talanta ; 233: 122609, 2021 Oct 01.
Article in English | MEDLINE | ID: covidwho-1267932

ABSTRACT

Corona Virus Disease 2019 (COVID-19) is a highly infectious respiratory illness that was caused by the SARS-CoV-2. It spread around the world in just a few months and became a worldwide pandemic. Quick and accurate diagnosis of infected patients is very important for controlling transmission. In addition to the commonly used Real-time reverse-transcription polymerase chain reaction (RT-PCR) detection techniques, other diagnostic techniques are also emerging endlessly. This article reviews the current diagnostic methods for COVID-19 and discusses their advantages and disadvantages. It provides an important reference for the diagnosis of COVID-19.


Subject(s)
COVID-19 , COVID-19 Testing , Humans , Pandemics , Real-Time Polymerase Chain Reaction , SARS-CoV-2
2.
Zhongguo Huanjing Kexue = China Environmental Science ; 41(5):2028, 2021.
Article in English | ProQuest Central | ID: covidwho-1257860

ABSTRACT

Based on hourly concentration of PM2.5 and O3 during the epidemic period(January 24, 2020 to May 31, 2020) in Changsha, Zhuzhou and Xiangtan, the diurnal patterns, long-term persistence, multifractality and self-organization evolution dynamics of these two pollutants were studied to reveal the internal dynamic mechanism of the occurrence and evolution of heavy pollution events during the epidemic period. Firstly, the diurnal patterns of PM2.5 and O3 concentrations were investigated. It showed that O3 showed a single peak of high concentration in the daytime and low in the night, while PM2.5 showed a single lowest peak concentration in the day and high in the night, which was different from the pattern in non-epidemic periods. Furthermore, detrended fluctuation analysis(DFA), the multifractal detrended fluctuation analysis(MFDFA) and probability statistical analysis were applied to study the long-term persistence, multi-fractal structure of PM2.5 and O3 series. The results showed that PM2.5 and O3 series had significant long-term persistence characteristics and strong multi-fractal structures for the three cities. Meanwhile, detrended cross-correlation analysis(DCCA) and multifractal detrended cross-correlation analysis(MFDCCA) were conducted to estimate the cross-correlations between PM2.5 and O3 series. Long-term persistence as well as multifractal features at different time scales was also observed in PM2.5-O3 cross-correlations. Next, nonlinear analysis results obtained during epidemic period were compared with those obtained in the same periods of non-epidemic years of 2019 and 2018. Finally, based on the self-organized criticality(SOC) theory, the internal dynamic law of spatial and temporal evolution of PM2.5 and O3 series was discussed. Combined with the typical regional meteorological characteristics, it was found that the intrinsic dynamic mechanism of SOC may be one of the leading mechanisms of heavy air pollution episodes during the COVID-19 lockdown period. During the epidemic period, PM2.5 and O3 concentrations did not evolve independently but remained complex interactions. Under the stable meteorological conditions, the nonlinear coupling effect inside the air combined pollution might reach the dynamic critical state, thus, lead to the risk of heavy air pollution in Greater Changsha Metropolitan Region during the epidemic period.

3.
Natural Product Communications ; 16(2):1934578X21991714, 2021.
Article in English | Sage | ID: covidwho-1063109

ABSTRACT

To investigate the mechanism of action of components of Yinma Jiedu granules in the treatment of coronavirus disease 2019 (COVID-19) using network pharmacology and molecular docking. The main chemical components of Yinma Jiedu granules were collected in the literature and Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform database. Using the SwissTargetPrediction database, the targets of the active component were identified and further correlated to the targets of COVID-19 through the GeneCards database. The overlapping targets of Yinma Jiedu granules components and COVID-19 were identified as the research target. Using the Database for Annotation, Visualization and Integrated Discovery database to carry out the target gene function Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway annotation and Cytoscape 3.6.1 software was used to construct a ?component-target-pathway? network. The protein-protein interaction network was built using Search Tool for the Retrieval of Interacting Genes/Proteins database. Using Discovery Studio 2016 Client software to study the virtual docking of key protein and active components. One hundred active components were screened from the Yinma Jiedu Granules that involved 67 targets, including mitogen-activated protein kinase 3 (MAPK3), epidermal growth factor receptor, tumor necrosis factor, tumor protein 53, and MAPK1. These targets affected 109 signaling pathways including hypoxia-inducible factor-1, apoptosis, and Toll-like receptor signaling pathways. Molecular docking results showed that the screened active components have a strong binding ability to the key targets. In this study, through network pharmacology and molecular docking, we justified the multicomponent, multitarget, and multipathways of Yinma Jiedu Granules in the treatment of COVID-19.

4.
Natural Product Communications ; 15(12):1934578X20978025, 2020.
Article in English | Sage | ID: covidwho-970155

ABSTRACT

In the process of fighting against COVID-19 in China, Xingnaojing injection has been recommended for its clinical treatment, but the information about its active components and mechanism is still lacking. Therefore, in this work, using network pharmacology and molecular docking, we studied the active components of Xingnaojing injection having anti-COVID-19 properties. Using the DL parameter, TCMSP and CNKI databases were used to screen the active components of the Xingnaojing injection. Then, the SwissTargetPrediction webserver was used to collect the corresponding gene targets, and the gene targets related to COVID-19 were searched in the Genecards database. The DAVID database was used to enrich the function of gene targets, and the KOBAS3.0 database for the annotation of related KEGG pathways. The ?components?targets?pathways? network of Xingnaojing injection was constructed with Cytoscape 3.6.1 software. The protein?protein interaction networks were analyzed using the String database. Specific proteins, SARS-COV-2 3 Cl, ACE2, and the active components were imported into Discovery Studio 2016 Client for molecular docking studies. From the Xingnaojing injection, a total of 58 active components, including Divanillalaceton and Q27139023, were screened. These were linked to 53 gene targets including mitogen-activated protein kinase 1 (MAPK1), tumor necrosis factorTNF, epidermal growth factor receptor, MAPK3, and 196 signaling pathways related to COVID-19, such as apoptosis, C-type lectin receptor signaling pathway, and hypoxia-inducible factor 1 signaling pathway. Furthermore, molecular docking studies were performed to study potential binding between the key targets and selected active components. Xingnaojing injection exhibits anti-COVID-19 effects via multiple components, multiple targets, and multiple pathways. These results set a scientific basis for further elucidation of the anti-COVID-19 mechanism of Xingnaojing injection.

5.
J Med Virol ; 92(11): 2600-2606, 2020 11.
Article in English | MEDLINE | ID: covidwho-935122

ABSTRACT

To investigate the inflammatory factors and lymphocyte subsets which play an important role in the course of severe coronavirus disease 2019 (COVID-19). A total of 27 patients with severe COVID-19 who were admitted to Tongji Hospital in Wuhan from 1 to 21 February 2020 were recruited to the study. The characteristics of interleukin-1ß (IL-1ß), IL-2 receptor (IL-2R), IL-6, IL-8, IL-10, tumor necrosis factor-α (TNF)-α, C-reactive protein (CRP), serum ferritin and procalcitonin (PCT), and lymphocyte subsets of these patients were retrospectively compared before and after treatment. Before treatment, there was no significant difference in most inflammatory factors (IL-1ß, IL-2R, IL-6, IL-8, IL-10, CRP, and serum ferritin) between male and female patients. Levels of IL-2R, IL-6, TNF-α, and CRP decreased significantly after treatment, followed by IL-8, IL-10, and PCT. Serum ferritin was increased in all patients before treatment but did not decrease significantly after treatment. IL-1ß was normal in most patients before treatment. Lymphopenia was common among these patients with severe COVID-19. Analysis of lymphocyte subsets showed that CD4+ and particularly CD8+ T lymphocytes increased significantly after treatment. However, B lymphocytes and natural killer cells showed no significant changes after treatment. A pro-inflammatory response and decreased level of T lymphocytes were associated with severe COVID-19.


Subject(s)
COVID-19/immunology , Inflammation/immunology , Lymphocyte Subsets/immunology , Adult , Aged , Aged, 80 and over , Antiviral Agents/therapeutic use , CD4-Positive T-Lymphocytes/immunology , CD8-Positive T-Lymphocytes/immunology , COVID-19/therapy , China , Cytokines/blood , Cytokines/immunology , Female , Humans , Interleukins/blood , Lymphocyte Count , Male , Middle Aged , Prognosis , Retrospective Studies , Severity of Illness Index
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