Impact of inactivated COVID-19 vaccines on lung injury in B.1.617.2 (Delta) variant-infected patients.

BACKGROUND: Chest computerized tomography (CT) scan is an important strategy that quantifies the severity of COVID-19 pneumonia. To what extent inactivated COVID-19 vaccines could impact the COVID-19 pneumonia on chest CT is not clear. METHODS: This study recruited 357 SARS-COV-2 B.1.617.2 (Delta) variant-infected patients admitted to the Second Hospital of Nanjing from July to August 2021. An artificial intelligence-assisted CT imaging system was used to quantify the severity of COVID-19 pneumonia. We compared the volume of infection (VOI), percentage of infection (POI) and chest CT scores among patients with different vaccination statuses. RESULTS: Of the 357 Delta variant-infected patients included for analysis, 105 were unvaccinated, 72 were partially vaccinated and 180 were fully vaccinated. Fully vaccination had the least lung injuries when quantified by VOI (median VOI of 222.4 cm3, 126.6 cm3 and 39.9 cm3 in unvaccinated, partially vaccinated and fully vaccinated, respectively; p < 0.001), POI (median POI of 7.60%, 3.55% and 1.20% in unvaccinated, partially vaccinated and fully vaccinated, respectively; p < 0.001) and chest CT scores (median CT score of 8.00, 6.00 and 4.00 in unvaccinated, partially vaccinated and fully vaccinated, respectively; p < 0.001). After adjustment for age, sex, comorbidity, time from illness onset to hospitalization and viral load, fully vaccination but not partial vaccination was significantly associated with less lung injuries quantified by VOI {adjust coefficient[95%CI] for "full vaccination": - 106.10(- 167.30,44.89); p < 0.001}, POI {adjust coefficient[95%CI] for "full vaccination": - 3.88(- 5.96, - 1.79); p = 0.001} and chest CT scores {adjust coefficient[95%CI] for "full vaccination": - 1.81(- 2.72, - 0.91); p < 0.001}. The extent of reduction of pulmonary injuries was more profound in fully vaccinated patients with older age, having underlying diseases, and being female sex, as demonstrated by relatively larger absolute values of adjusted coefficients. Finally, even within the non-severe COVID-19 population, fully vaccinated patients were found to have less lung injuries. CONCLUSION: Fully vaccination but not partially vaccination could significantly protect lung injury manifested on chest CT. Our study provides additional evidence to encourage a full course of vaccination.

Knowledge mapping analysis of mental health research on COVID-19.

Objective: A bibliometric analysis of COVID-19 is conducted to examine the developmental context, research hotspots, and frontiers of mental health. Methods: Using the Web of Science Core Collection (WOSCC), we have retrieved articles on mental health research related to COVID-19 which were published between 2019 and 2021. The coauthorship of countries, institutes, and authors was analyzed using VOSviewer 1.6.17, and the co-citation map of authors/references was analyzed as well. CiteSpace version 5.8.R3 was used to analyze keyword clusters and forecast research frontiers. Results: There were 8,856 articles retrieved, including 10,559 research institutes and 1,407 academic journals. The most published country and institutes were the United States (2190) and the University of London (373). Wang, Chengyu owned the highest co-citations (1810). Frontier topics can be identified by trending keywords, including "anxiety," "depression," "psychological distress," "quarantine," "post-traumatic stress disorder (PTSD)," "insomnia," and "Healthcare workers." Conclusion: The most common psychological problems of people during the epidemic are anxiety and depression. Insomnia and PTSD need to be solved under the normalization of the epidemic. GAD-7 and PHQ-9 scales are the most convenient and effective for screening anxiety and depression. Healthcare workers, older adults, and college students should be concerned, and social and family support is essential.

Knowledge mapping analysis of mental health research on COVID-19

Objective A bibliometric analysis of COVID-19 is conducted to examine the developmental context, research hotspots, and frontiers of mental health. Methods Using the Web of Science Core Collection (WOSCC), we have retrieved articles on mental health research related to COVID-19 which were published between 2019 and 2021. The coauthorship of countries, institutes, and authors was analyzed using VOSviewer 1.6.17, and the co-citation map of authors/references was analyzed as well. CiteSpace version 5.8.R3 was used to analyze keyword clusters and forecast research frontiers. Results There were 8,856 articles retrieved, including 10,559 research institutes and 1,407 academic journals. The most published country and institutes were the United States (2190) and the University of London (373). Wang, Chengyu owned the highest co-citations (1810). Frontier topics can be identified by trending keywords, including “anxiety,” “depression,” “psychological distress,” “quarantine,” “post-traumatic stress disorder (PTSD),” “insomnia,” and “Healthcare workers.” Conclusion The most common psychological problems of people during the epidemic are anxiety and depression. Insomnia and PTSD need to be solved under the normalization of the epidemic. GAD-7 and PHQ-9 scales are the most convenient and effective for screening anxiety and depression. Healthcare workers, older adults, and college students should be concerned, and social and family support is essential.

Enhanced inflammation and suppressed adaptive immunity in COVID-19 with prolonged RNA shedding.

Little is known regarding why a subset of COVID-19 patients exhibited prolonged positivity of SARS-CoV-2 infection. Here, we found that patients with long viral RNA course (LC) exhibited prolonged high-level IgG antibodies and higher regulatory T (Treg) cell counts compared to those with short viral RNA course (SC) in terms of viral load. Longitudinal proteomics and metabolomics analyses of the patient sera uncovered that prolonged viral RNA shedding was associated with inhibition of the liver X receptor/retinoid X receptor (LXR/RXR) pathway, substantial suppression of diverse metabolites, activation of the complement system, suppressed cell migration, and enhanced viral replication. Furthermore, a ten-molecule learning model was established which could potentially predict viral RNA shedding period. In summary, this study uncovered enhanced inflammation and suppressed adaptive immunity in COVID-19 patients with prolonged viral RNA shedding, and proposed a multi-omic classifier for viral RNA shedding prediction.