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Background: The challenges that viral pneumonia poses to the global public health system remain daunting. In this study, an analysis of publications on viral pneumonia over the past two decades was conducted. Through this work, we hope to provide inspiration for future research on viral pneumonia. Methods: We extracted all of the English publications relevant to viral pneumonia published during 1999-2019 from Web of Science. GraphPad Prism, CiteSpace, and VOSviewer were used to collect and analyze the publication trends in related fields. Results: We identified 2,006 publications with 62,155 citations as of February 16, 2021. The United States accounted for the largest number of publications (34.2%), with the highest number of citations (27,616) and the highest h-index (78). China ranked second in the number of publications. Ctr Dis Control & Prevent proved to be the center of research cooperation. Clinical Infectious Diseases included the most papers published relating to the topic of viral pneumonia. Chan KH published the most papers in this field (25), while an article from Fouchier RAM presented the highest citation frequency (1,275). Conclusions: According to the bibliometric analysis database and related software results, the United States dominates the field of viral pneumonia research. The key term extracted by VOS-viewer has shifted to "Diagnosis and management", indicating a new trend for viral pneumonia research.
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Objective To construct SARS-CoV-2 pseudovirus, optimize its preparation protocol, and apply it to the evaluation of antibody neutralization activity. Methods The optimized sequence of spike (S) gene of SARS-CoV-2 was synthesized, the pseudovirus titers were measured, and the expressed S protein was then detected by Western blot. Finally, quantitative ELISA was used to measure the serum IgG antibody titers in recipients who had received either one or two doses of COVID-19 inactivated vaccine. Meanwhile, the sera were tested for their reactivity with the pseudovirus using neutralization tests. Results S gene was confirmed to have been successfully cloned into the vector, generating the pcDNA3.1-S plasmid. Co-transfection of pNL4-3.Luc.R-E- and pcDNA3.1-S at a ratio of 2∶1 could lead to higher packing efficacy and pseudovirus titers. Expression of the S protein was verified by Western blot. Moreover, this SARS-CoV-2 pseudovirus showed a broad host infectivity in Vero, Huh7.5, A549-hACE2 and 293T-hACE2 cells, with the highest relative luciferase unit (RLU) in 293T-hACE2. Comparing the IgG levels measured by ELISA in sera collected from COVID-19 vaccine recipients, we observed a higher titer in those who received two doses of inactivated vaccine (S/CO=10.27±3.33), measured one week after the second shot. However, the IgG level significantly dropped（S/CO=2.36±2.25）half year post-vaccination. Amongst the serum samples tested, one with an S/CO of 10.32 could successfully inhibit the infection of SARS-CoV-2 pseudovirus in 293T-hACE2 cells at a dilution of 1/1 066. Conclusion We have established a method for preparing the SARS-CoV-2 pseudovirus, which can be used for detection of the neutralizing antibodies and the evaluation of humoral immune response post-vaccination. © 2022 Editorial Office of Chinese Journal of Schistosomiasis Control. All Rights Reserved.
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The emerging COVID-19 variants lead to a new wave of infections, spreading more rapidly with more severe illnesses. The adaptive immune system plays an essential role in the control and clearance of viral infection and influences clinical outcomes. However, the understanding of the adaptive immune responses to COVID-19 is not sufficient, which impedes the development progress of treatments and vaccines. To address this issue, we proposed a machine-learning-based method (termed as VDJ-Seg-Miner) to mine the underlying associations between the V(D)J gene segments of the T cell receptor in personalized immune repertoires and COVID-19 disease characteristics for immune system analysis. Our VDJ-Seg-Miner can interpretively reveal multiple associations between the V(D)J gene segments and COVID-19 disease characteristics and assign confidence scores to indicate its confidence in each revealed association. Furthermore, experimental results based on the real-world dataset suggested that the identified associations were highly consistent with those reported in previous work. © 2021 IEEE.