Plasma cell-free DNA promise monitoring and tissue injury assessment of COVID-19.

Coronavirus 2019 (COVID-19) is a complex disease that affects billions of people worldwide. Currently, effective etiological treatment of COVID-19 is still lacking; COVID-19 also causes damages to various organs that affects therapeutics and mortality of the patients. Surveillance of the treatment responses and organ injury assessment of COVID-19 patients are of high clinical value. In this study, we investigated the characteristic fragmentation patterns and explored the potential in tissue injury assessment of plasma cell-free DNA in COVID-19 patients. Through recruitment of 37 COVID-19 patients, 32 controls and analysis of 208 blood samples upon diagnosis and during treatment, we report gross abnormalities in cfDNA of COVID-19 patients, including elevated GC content, altered molecule size and end motif patterns. More importantly, such cfDNA fragmentation characteristics reflect patient-specific physiological changes during treatment. Further analysis on cfDNA tissue-of-origin tracing reveals frequent tissue injuries in COVID-19 patients, which is supported by clinical diagnoses. Hence, our work demonstrates and extends the translational merit of cfDNA fragmentation pattern as valuable analyte for effective treatment monitoring, as well as tissue injury assessment in COVID-19.

SARS-CoV-2 Omicron BA.5 infection recurrence after Paxlovid treatment: The first case report in Hunan Province. / 湖南省首例Paxlovidæ²»ç–—æ–°åž‹å† çŠ¶ç— æ¯’å¥¥å¯†å ‹æˆŽBA.5å˜å¼‚æ ªå¤é˜³ç— ä¾‹æŠ¥é“.

We report a case of coronavirus disease 2019 (COVID-19) patient who was cured by oral administration of nirmatrelvir/ritonavir (Paxlovid). The patient was treated with Paxlovid after being first infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron BA.5 variant. On the 11th day after SARS-CoV-2 nucleic acid test turned negative, SARS-CoV-2 nucleic acid test was positive again, and the threshold of nucleic acid cycle number was equivalent to that of the first infection. The results of two whole gene sequencing showed that it was the same virus strain infection, suggesting that the case was re-positive. Without specific treatment, SARS-CoV-2 nucleic acid detection in nasopharyngeal swab turned negative. It is not uncommon for Paxlovid to recover after treating COVID-19, and most of the patients can recover without specific treatment. However, it is necessary to further study the mechanism that may lead to the recovery of SARS-CoV-2.

Neutralization Activity against SARS-CoV-2 Variants after Booster Vaccination in Populations without COVID-19: A Meta-Analysis.

A number of SARS-CoV-2 variants that have evolved to have significant immune escape have emerged worldwide since the COVID-19 outbreak. The efficacy of prime vaccination is waning with the evolution of SARS-CoV-2, and the necessity of booster doses is more and more prominent. Therefore, this study aimed to compare the neutralization activity against the wild type and variants (Beta, Delta, and Omicron) in different prime-boost vaccination regimens. Electronic databases including PubMed, the Cochrane Library, Embase, medRxiv, Wanfang and CNKI were used to retrieve original studies. A total of 16 studies, 9 prime-boost vaccination regimes, and 3134 subjects were included in the meta-analysis and random effect models were used to estimate pooled neutralization titers. The neutralization activity against SARS-CoV-2 showed a significant decline with the evolution of the virus, especially in the populations primed with inactivated vaccines. For homologous immunization, only the populations boosted with mRNA vaccines consistently had a significant rise in neutralization titers (Beta: MD = 0.97; Delta: MD = 1.33; Omicron: MD = 0.74). While the heterologous immunization was more effective, the increment of neutralization titers against wild type, Beta, Delta and Omicron was 1.65 (95% CI: 1.32-1.96), 1.03 (95% CI: 0.53-1.54), 1.46 (95% CI: 1.07-1.85) and 1.15 (95% CI: 0.68-1.61), respectively. With the evolution of SARS-CoV-2, the effectiveness of prime immunization is waning. Although the administration of the booster dose could ameliorate the neutralization titers, homologous immunization regimens were gradually losing their effectiveness. Therefore, a heterologous booster dose is required, especially in populations primed with inactivated vaccines.

Immunogenicity and Safety of Homologous and Heterologous Prime-Boost Immunization with COVID-19 Vaccine: Systematic Review and Meta-Analysis.

A prime-boost strategy of COVID-19 vaccines brings hope to limit the spread of SARS-CoV-2, while the immunogenicity of the vaccines is waning over time. Whether a booster dose of vaccine is needed has become a widely controversial issue. However, no published meta-analysis has focused on the issue. Therefore, this study assessed the immunogenicity and safety of the different combinations of prime-boost vaccinations. Electronic databases including PubMed, the Cochrane Library, Embase, medRxiv, Wanfang and CNKI were used to retrieve the original studies. A total of 28 studies, 9 combinations of prime-boost vaccinations and 5870 subjects were included in the meta-analysis, and random effect models were used to estimate pooled immunogenicity and safety. The immunity against COVID-19 after the prime vaccination waned over time, especially in the populations primed with inactivated vaccines, in which the seropositive rate of antibodies was only 28% (95% CI: 17-40%). Booster vaccination could significantly increase the antibody responses, and heterologous immunization was more effective than homologous immunization (neutralization titers: 1.65 vs. 1.27; anti-RBD IgG: 1.85 vs. 1.15); in particular, the combination of inactivated-mRNA vaccines had the highest antibody responses (neutralization titers: MRAW = 3.64, 95% CI: 3.54-3.74; anti-RBD IgG: 3.73, 95% CI: 3.59-3.87). Moreover, compared with the initial two doses of vaccines, a booster dose did not induce additional or severe adverse events. The administration of the booster dose effectively recalled specific immune responses to SARS-CoV-2 and increased antibody levels, especially in heterologous immunization. Considering the long-term immunogenicity and vaccine equity, we suggest that now, only individuals primed with inactivated vaccines require a booster dose.

An AAV vaccine targeting the RBD of the SARS-CoV-2 S protein induces effective neutralizing antibody titers in mice and canines.

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has resulted in catastrophic damage worldwide. Accordingly, the development of powerful, safe, easily accessible vaccines with long-term effectiveness is understood as an urgently needed countermeasure against this ongoing pandemic. Guided by this strong promise of using AAVs, we here designed, optimized, and developed an AAV-based vaccines (including AAV-RBD(max), AAV-RBD(wt), AAV-2xRBD, and AAV-3xRBD) that elicit strong immune responses against the RBD domain of the SARS-CoV-2 S protein. These immunogenic responses have proven long-lived, with near peak levels for at least six months in mice. Notably, the sera immunized with AAV-3xRBD vaccine contains powerful neutralizing antibodies against the SARS-CoV-2 pseudovirus. Further evidence proven that potent specific antibodies could also be elicited in canines after vaccination with AAV-3xRBD vaccine.

Has COVID-19 Changed China's Digital Trade?-Implications for Health Economics.

Digital technologies have played a significant role in the defense against the COVID-19 pandemic. This development raises the question of whether digital technologies have helped Chinese exports recover quickly and even grow. To answer this question, we study monthly data on Chinese exports to 40 countries/regions from January 2019 to June 2020 and covering 97 product categories. The study takes the COVID-19 outbreak as a natural experiment and treats digital trade products as the treatment group. Using a generalized difference-in-differences (DID) approach, we empirically investigate how this major global public health crisis and digital trade have influenced Chinese exports. Our empirical analysis reveals that the COVID-19 pandemic has inhibited China's export trade overall, digital trade has significantly promoted trade, and the supply mechanism has played a significant role in promoting the recovery of exports. Heterogeneity tests on destination countries/regions reveal that digital trade has significantly promoted exports to countries/regions with different income levels, with a more significant effect on low-risk destinations than on high-risk destinations. The sector heterogeneity test demonstrates that digital trade has enhanced the export recovery of sectors dealing in necessities for pandemic prevention. Other robustness tests, including parallel trend and placebo tests, support the above conclusions. Finally, we extend the research conclusions and discuss their implication for health economics and the practice of fighting COVID-19.

Has COVID-19 Changed China's Digital Trade?—Implications for Health Economics

Digital technologies have played a significant role in the defense against the COVID-19 pandemic. This development raises the question of whether digital technologies have helped Chinese exports recover quickly and even grow. To answer this question, we study monthly data on Chinese exports to 40 countries/regions from January 2019 to June 2020 and covering 97 product categories. The study takes the COVID-19 outbreak as a natural experiment and treats digital trade products as the treatment group. Using a generalized difference-in-differences (DID) approach, we empirically investigate how this major global public health crisis and digital trade have influenced Chinese exports. Our empirical analysis reveals that the COVID-19 pandemic has inhibited China's export trade overall, digital trade has significantly promoted trade, and the supply mechanism has played a significant role in promoting the recovery of exports. Heterogeneity tests on destination countries/regions reveal that digital trade has significantly promoted exports to countries/regions with different income levels, with a more significant effect on low-risk destinations than on high-risk destinations. The sector heterogeneity test demonstrates that digital trade has enhanced the export recovery of sectors dealing in necessities for pandemic prevention. Other robustness tests, including parallel trend and placebo tests, support the above conclusions. Finally, we extend the research conclusions and discuss their implication for health economics and the practice of fighting COVID-19.

Plasma cell-free RNA characteristics in COVID-19 patients.

The pathogenesis of COVID-19 is still elusive, which impedes disease progression prediction, differential diagnosis, and targeted therapy. Plasma cell-free RNAs (cfRNAs) carry unique information from human tissue and thus could point to resourceful solutions for pathogenesis and host-pathogen interactions. Here, we performed a comparative analysis of cfRNA profiles between COVID-19 patients and healthy donors using serial plasma. Analyses of the cfRNA landscape, potential gene regulatory mechanisms, dynamic changes in tRNA pools upon infection, and microbial communities were performed. A total of 380 cfRNA molecules were up-regulated in all COVID-19 patients, of which seven could serve as potential biomarkers (AUC > 0.85) with great sensitivity and specificity. Antiviral (NFKB1A, IFITM3, and IFI27) and neutrophil activation (S100A8, CD68, and CD63)-related genes exhibited decreased expression levels during treatment in COVID-19 patients, which is in accordance with the dynamically enhanced inflammatory response in COVID-19 patients. Noncoding RNAs, including some microRNAs (let 7 family) and long noncoding RNAs (GJA9-MYCBP) targeting interleukin (IL6/IL6R), were differentially expressed between COVID-19 patients and healthy donors, which accounts for the potential core mechanism of cytokine storm syndromes; the tRNA pools change significantly between the COVID-19 and healthy group, leading to the accumulation of SARS-CoV-2 biased codons, which facilitate SARS-CoV-2 replication. Finally, several pneumonia-related microorganisms were detected in the plasma of COVID-19 patients, raising the possibility of simultaneously monitoring immune response regulation and microbial communities using cfRNA analysis. This study fills the knowledge gap in the plasma cfRNA landscape of COVID-19 patients and offers insight into the potential mechanisms of cfRNAs to explain COVID-19 pathogenesis.

TREM-2 is a sensor and activator of T cell response in SARS-CoV-2 infection.

Limited understanding of T cell responses against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has impeded vaccine development and drug discovery for coronavirus disease 2019 (COVID-19). We found that triggering receptor expressed on myeloid cells 2 (TREM-2) was induced in T cells in the blood and lungs of patients with COVID-19. After binding to SARS-CoV-2 membrane (M) protein through its immunoglobulin domain, TREM-2 then activated the CD3ζ/ZAP70 complex, leading to STAT1 phosphorylation and T-bet transcription. In vitro stimulation with M protein-reconstituted pseudovirus or recombinant M protein, and TREM-2 promoted the T helper cell 1 (TH1) cytokines interferon-γ and tumor necrosis factor. In vivo infection of CD4­TREM-2 conditional knockout mice with murine coronavirus mouse hepatitis virus A-59 showed that intrinsic TREM-2 in T cells enhanced TH1 response and viral clearance, thus aggravating lung destruction. These findings demonstrate a previously unidentified role for TREM-2 in SARS-CoV-2 infection, and suggest potential strategies for drug discovery and clinical management of COVID-19.

Outcomes of atrial fibrillation in patients with COVID-19 pneumonia: A systematic review and meta-analysis.

BACKGROUND: Recently, emerging evidence has suggested that atrial fibrillation (AF) has an epidemiological correlation with coronavirus disease 2019 (COVID-19). However, the clinical outcomes of AF in COVID-19 remain inconsistent and inconclusive. The aim of this study was to provide a comprehensive description of the impact of AF on the prognosis of patients with COVID-19 pneumonia. METHODS: Three electronic databases (PubMed, Embase, and Web of Science) were searched for eligible studies as of March 1, 2021. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were used to evaluate the associations between AF (preexisting and new-onset) and in-hospital mortality, post-discharge mortality, and ventilator use. RESULTS: A total of 36 individual studies were incorporated into our meta-analysis. The combined results revealed that preexisting AF was associated with increased in-hospital mortality (pooled OR: 2.07; 95% CI: 1.60-2.67; p < 0.001), post-discharge mortality (pooled OR: 2.69; 95% CI: 1.24-5.83; p < 0.05), and ventilator utilization (pooled OR: 4.53; 95% CI: 1.33-15.38; p < 0.05) in patients with COVID-19. In addition, our data demonstrated that new-onset AF during severe acute respiratory syndrome coronavirus 2 infection was significantly correlated with increased mortality (pooled OR: 2.38; 95% CI: 2.04-2.77; p < 0.001). CONCLUSIONS: The presence of AF is correlated with adverse outcomes in patients with COVID-19 pneumonia, which deserves increased attention and should be managed appropriately to prevent adverse outcomes.

Efficacy and Safety of COVID-19 Vaccines in Phase III Trials: A Meta-Analysis.

Nowadays, the vaccination with COVID-19 vaccines is being promoted worldwide, professionals and common people are very concerned about the efficacy and safety of COVID-19 vaccines. No published systematic review and meta-analysis has assessed the efficacy and safety of the COVID-19 vaccines based on data from phase III clinical trials. Therefore, this study has estimated the efficacy and safety of COVID-19 vaccines and the differences between vaccine types. PubMed, Embase, the Cochrane Library, CNKI, Wanfang, medRxiv databases and two websites were used to retrieve the studies. Random-effects models were used to estimate the pooled efficacy and safety with risk ratio (RR). A total of eight studies, seven COVID-19 vaccines and 158,204 subjects were included in the meta-analysis. All the vaccines had a good preventive effect on COVID-19 (RR = 0.17, 95% CI: 0.09-0.32), and the mRNA vaccine (RR = 0.05, 95% CI: 0.03-0.09) was the most effective against COVID-19, while the inactivated vaccine (RR = 0.32, 95% CI: 0.19-0.54) was the least. In terms of safety, the risk of overall adverse events showed an increase in the vaccine group after the first (RR = 1.46, 95% CI: 1.03-2.05) or second (RR = 1.52, 95% CI: 1.04-2.20) injection. However, compared with the first injection, the risk of local (RR = 2.64, 95% CI: 1.02-6.83 vs. RR = 2.25, 95% CI: 0.52-9.75) and systemic (RR = 1.33, 95% CI: 1.21-1.46 vs. RR = 1.59, 95% CI: 0.84-3.01) adverse events decreased after the second injection. As for the mRNA vaccine, the risk of overall adverse events increased significantly, compared with the placebo, no matter whether it was the first (RR = 1.83, 95% CI = 1.80-1.86) or the second (RR = 2.16, 95% CI = 2.11-2.20) injection. All the COVID-19 vaccines that have published the data of phase III clinical trials have excellent efficacy, and the risk of adverse events is acceptable. The mRNA vaccines were the most effective against COVID-19, meanwhile the risk and grade of adverse events was minimal, compared to that of severe symptoms induced by COVID-19.

Glycyrrhizic Acid Nanoparticles as Antiviral and Anti-inflammatory Agents for COVID-19 Treatment.

COVID-19 has been diffusely pandemic around the world, characterized by massive morbidity and mortality. One of the remarkable threats associated with mortality may be the uncontrolled inflammatory processes, which were induced by SARS-CoV-2 in infected patients. As there are no specific drugs, exploiting safe and effective treatment strategies is an instant requirement to dwindle viral damage and relieve extreme inflammation simultaneously. Here, highly biocompatible glycyrrhizic acid (GA) nanoparticles (GANPs) were synthesized based on GA. In vitro investigations revealed that GANPs inhibit the proliferation of the murine coronavirus MHV-A59 and reduce proinflammatory cytokine production caused by MHV-A59 or the N protein of SARS-CoV-2. In an MHV-A59-induced surrogate mouse model of COVID-19, GANPs specifically target areas with severe inflammation, such as the lungs, which appeared to improve the accumulation of GANPs and enhance the effectiveness of the treatment. Further, GANPs also exert antiviral and anti-inflammatory effects, relieving organ damage and conferring a significant survival advantage to infected mice. Such a novel therapeutic agent can be readily manufactured into feasible treatment for COVID-19.

Multi-platform omics analysis reveals molecular signature for COVID-19 pathogenesis, prognosis and drug target discovery.

Disease progression prediction and therapeutic drug target discovery for Coronavirus disease 2019 (COVID-19) are particularly important, as there is still no effective strategy for severe COVID-19 patient treatment. Herein, we performed multi-platform omics analysis of serial plasma and urine samples collected from patients during the course of COVID-19. Integrative analyses of these omics data revealed several potential therapeutic targets, such as ANXA1 and CLEC3B. Molecular changes in plasma indicated dysregulation of macrophage and suppression of T cell functions in severe patients compared to those in non-severe patients. Further, we chose 25 important molecular signatures as potential biomarkers for the prediction of disease severity. The prediction power was validated using corresponding urine samples and plasma samples from new COVID-19 patient cohort, with AUC reached to 0.904 and 0.988, respectively. In conclusion, our omics data proposed not only potential therapeutic targets, but also biomarkers for understanding the pathogenesis of severe COVID-19.

Helping Roles of Artificial Intelligence (AI) in the Screening and Evaluation of COVID-19 Based on the CT Images.

OBJECTIVE: The aim of this study was to explore the role of the AI system which was designed and developed based on the characteristics of COVID-19 CT images in the screening and evaluation of COVID-19. METHODS: The research team adopted an improved U-shaped neural network to segment lungs and pneumonia lesions in CT images through multilayer convolution iterations. Then the appropriate 159 cases were selected to establish and train the model, and Dice loss function and Adam optimizer were used for network training with the initial learning rate of 0.001. Finally, 39 cases (29 positive and 10 negative) were selected for the comparative test. Experimental group: an attending physician a and an associate chief physician a read the CT images to diagnose COVID-19 with the help of the AI system. Control group: an attending physician b and an associate chief physician b did the diagnosis only by their experience, without the help of the AI system. The time spent by each doctor in the diagnosis and their diagnostic results were recorded. Paired t-test, univariate ANOVA, chi-squared test, receiver operating characteristic curves, and logistic regression analysis were used for the statistical analysis. RESULTS: There was statistical significance in the time spent in the diagnosis of different groups (P<0.05). For the group with the optimal diagnostic results, univariate and multivariate analyses both suggested no significant correlation for all variables, and thus it might be the assistance of the AI system, the epidemiological history and other factors that played an important role. CONCLUSION: The AI system developed by us, which was created due to COVID-19, had certain clinical practicability and was worth popularizing.

Exposure to SARS-CoV-2 generates T-cell memory in the absence of a detectable viral infection.

T-cell immunity is important for recovery from COVID-19 and provides heightened immunity for re-infection. However, little is known about the SARS-CoV-2-specific T-cell immunity in virus-exposed individuals. Here we report virus-specific CD4+ and CD8+ T-cell memory in recovered COVID-19 patients and close contacts. We also demonstrate the size and quality of the memory T-cell pool of COVID-19 patients are larger and better than those of close contacts. However, the proliferation capacity, size and quality of T-cell responses in close contacts are readily distinguishable from healthy donors, suggesting close contacts are able to gain T-cell immunity against SARS-CoV-2 despite lacking a detectable infection. Additionally, asymptomatic and symptomatic COVID-19 patients contain similar levels of SARS-CoV-2-specific T-cell memory. Overall, this study demonstrates the versatility and potential of memory T cells from COVID-19 patients and close contacts, which may be important for host protection.

Thinking and teaching adjustment of Virus Biology upon fighting against COVID-19

COVID-19 is threatening the public health in China and oversea in the spring of 2020. During fighting against COVID-19, course teaching of Virus Biology for bachelor students in the school of life sciences has been adjusted to the new situation in the following aspects, aiming to help students establish scientific and rational viewpoints on the pandemic situation: Besides applying online teaching mode instead of offline mode, teaching contents on virology, epidemiology and public health were strengthened further. Besides the special speech on COVID-19 in the beginning of the new semester, a 5-min talk on COVID-19 has been presented for whole semester. These measurements during teaching of Virus Biology helped students understand scientifically and rationally this pandemic caused by virus infection and spreading. These teaching adjustments were necessary to inspire more interest in virology amongst students, epidemiology and public health, and will be improved with the change of this epidemic situation in China and oversea.

Factors associated with a SARS-CoV-2 recurrence after hospital discharge among patients with COVID-19: systematic review and meta-analysis.

BACKGROUND: The proportion of recurrences after discharge among patients with coronavirus disease 2019 (COVID-19) was reported to be between 9.1% and 31.0%. Little is known about this issue, however, so we performed a meta-analysis to summarize the demographical, clinical, and laboratorial characteristics of non-recurrence and recurrence groups. METHODS: Comprehensive searches were conducted using eight electronic databases. Data regarding the demographic, clinical, and laboratorial characteristics of both recurrence and non-recurrence groups were extracted, and quantitative and qualitative analyses were conducted. RESULTS: Ten studies involving 2071 COVID-19 cases were included in this analysis. The proportion of recurrence cases involving patients with COVID-19 was 17.65% (between 12.38% and 25.16%) while older patients were more likely to experience recurrence (weighted mean difference (WMD)=1.67, range between 0.08 and 3.26). The time from discharge to recurrence was 13.38 d (between 12.08 and 14.69 d). Patients were categorized as having moderate severity (odds ratio (OR)=2.69, range between 1.30 and 5.58), while those with clinical symptoms including cough (OR=5.52, range between 3.18 and 9.60), sputum production (OR=5.10, range between 2.60 and 9.97), headache (OR=3.57, range between 1.36 and 9.35), and dizziness (OR=3.17, range between 1.12 and 8.96) were more likely to be associated with recurrence. Patients presenting with bilateral pulmonary infiltration and decreased leucocyte, platelet, and CD4+ T counts were at risk of COVID-19 recurrence (OR=1.71, range between 1.07 and 2.75; WMD=-1.06, range between -1.55 and -0.57, WMD=-40.39, range between -80.20 and -0.48, and WMD=-55.26, range between -105.92 and -4.60, respectively). CONCLUSIONS: The main factors associated with the recurrence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) after hospital discharge were older age, moderate severity, bilateral pulmonary infiltration, laboratory findings including decreased leucocytes, platelets, and CD4+ T counts, and clinical symptoms including cough, sputum production, headache, and dizziness. These factors can be considered warning indicators for the recurrence of SARS-CoV-2 and might help the development of specific management strategies.