A 10-valent composite mRNA vaccine against both influenza and COVID-19 (preprint)

The COVID-19 pandemic caused by SARS-CoV-2 viruses has had a persistent and significant impact on global public health for four years. Recently, there has been a resurgence of seasonal influenza transmission worldwide. The co-circulation of SARS-CoV-2 and seasonal influenza viruses results in a dual burden on communities. Additionally, the pandemic potential of zoonotic influenza viruses, such as avian Influenza A/H5N1 and A/H7N9, remains a concern. Therefore, a combined vaccine against all these respiratory diseases is in urgent need. mRNA vaccines, with their superior efficacy, speed in development, flexibility, and cost-effectiveness, offer a promising solution for such infectious diseases and potential future pandemics. In this study, we present FLUCOV-10, a novel 10-valent mRNA vaccine created from our proven platform. This vaccine encodes hemagglutinin (HA) proteins from four seasonal influenza viruses and two avian influenza viruses with pandemic potential, as well as spike proteins from four SARS-CoV-2 variants. A two-dose immunization with the FLUCOV-10 elicited robust immune responses in mice, producing IgG antibodies, neutralizing antibodies, and antigen-specific cellular immune responses against all the vaccine-matched viruses of influenza and SARS-CoV-2. Remarkably, the FLUCOV-10 immunization provided complete protection in mouse models against both homologous and heterologous strains of influenza and SARS-CoV-2. These results highlight the potential of FLUCOV-10 as an effective vaccine candidate for the prevention of influenza and COVID-19.

Antcin-B, a phytosterol-like compound from Taiwanofungus camphoratus inhibits SARS-CoV-2 3-chymotrypsin-like protease (3CL Pro ) activity in-silico and in vitro (preprint)

Antcins obtained from the fruiting bodies of Taiwanofungus camphoratus, have been traditionally used to treat infections, whereas their role in the SARS-CoV-2 3-chymotrypsin-like protease (3CLPro) remains unclear. We employed both in vitro and in silico approaches to understand the underlying chemical mechanism comprehensively. Our finding revealed that various antcins (A, B, C, H, I, and M) and non-antcins (citronellol and limonene) exhibited lower toxicity to cells than GC376, along with favorable drug-likeness based MTT assay and ADMET prediction. Molecular docking analysis predicted that antcin-B possessed the lowest binding affinity energy and interacts with key residues such as Glu169, Gln189, His41, Leu141, Asn142, Glu16, and His165 employing hydrophobic interaction, hydrogen bonding, and salt bridge. These interactions were further confirmed by molecular dynamics (MD) simulation, which demonstrated the formation of hydrogen bonds with Asn142 and Gly143 and bridge with Glu166 for approximately 40% and 70% of the simulation time, respectively. Indeed, in vitro, 3CLPro activity analysis supports the above notion that antcin-B significantly (96.39%) inhibits 3CLPro activity, which is highly comparable with a known antiviral drug GC367 (96.72%). Consequently, antcin-B could be considered for developing a potential drug candidate for inhibiting 3CLPro activity, thereby impeding reducing the severity of COVID-19 in patients.

AI-guided pipeline for protein-protein interaction drug discovery identifies a SARS-CoV-2 inhibitor (preprint)

Protein-protein interactions (PPIs) offer great opportunities to expand the druggable proteome and therapeutically tackle various diseases, but remain challenging targets for drug discovery. Here, we provide a comprehensive pipeline that combines experimental and computational tools to identify and validate PPI targets and perform early-stage drug discovery. We have developed a machine learning approach that prioritizes interactions by analyzing quantitative data from binary PPI assays and AlphaFold-Multimer predictions. Using the quantitative assay LuTHy together with our machine learning algorithm, we identified high-confidence interactions among SARS-CoV-2 proteins for which we predicted three-dimensional structures using AlphaFold Multimer. We employed VirtualFlow to target the contact interface of the NSP10-NSP16 SARS-CoV-2 methyltransferase complex by ultra-large virtual drug screening. Thereby, we identified a compound that binds to NSP10 and inhibits its interaction with NSP16, while also disrupting the methyltransferase activity of the complex, and SARS-CoV-2 replication. Overall, this pipeline will help to prioritize PPI targets to accelerate the discovery of early-stage drug candidates targeting protein complexes and pathways.

Taxonomical and ontological analysis of verified natural and laboratory human coronavirus hosts (preprint)

To fully understand COVID-19, it is critical to identify and analyze all the possible hosts of SARS-CoV-2 (the pathogen of COVID-19) and compare them with the hosts of other human coronaviruses. In this study, we collected, annotated, and performed taxonomical and ontological analysis of all the reported and verified hosts for all human coronaviruses including SARS-CoV, MERS-CoV, SARS-CoV-2, and four others that cause the common cold. A total of 37 natural hosts and 19 laboratory animal hosts of host human coronaviruses were identified based on experimental or clinical evidence. Our taxonomical ontology-based analysis found that all the verified susceptible natural and laboratory animals belong to therian mammals. Specifically, these 37 natural therian hosts include one wildlife marsupial mammal (i.e., Didelphis virginiana) and 36 Eutheria mammals (a.k.a. placental mammals). The 19 laboratory animal hosts are also classified as placental mammals. While several non-therian animals (including snake, housefly, zebrafish) were reported to be likely SARS-CoV-2 hosts, our analysis excluded them due to the lack of convincing evidence. Genetically modified mouse models with human Angiotensin-converting enzyme 2 (ACE2) or dipeptidyl peptidase-4 (DPP4) protein were more susceptible to virulent human coronaviruses with clear symptoms. Coronaviruses often became more virulent and adaptive in the mouse hosts after a series of viral passages in the mice. To support knowledge standardization and analysis, we have also represented the annotated host knowledge in the Coronavirus Infectious Disease Ontology (CIDO) and provided ways to automatically query the knowledge.

Airport terminal passenger forecast under the impact of COVID-19 outbreaks: A case study from China

Passengers significantly affect airport terminal energy consumption and indoor environmental quality. Accurate passenger forecasting provides important insights for airport terminals to optimize their operation and management. However, the COVID-19 pandemic has greatly increased the uncertainty in airport passenger since 2020. There are insufficient studies to investigate which pandemic-related variables should be considered in forecasting airport passenger trends under the impact of COVID-19 outbreaks. In this study, the interrelationship between COVID-19 pandemic trends and passenger traffic at a major airport terminal in China was analyzed on a day-by-day basis. During COVID-19 outbreaks, three stages of passenger change were identified and characterized, i.e., the decline stage, the stabilization stage, and the recovery stage. A typical "sudden drop and slow recovery” pattern of passenger traffic was identified. A LightGBM model including pandemic variables was developed to forecast short-term daily passenger traffic at the airport terminal. The SHapley Additive exPlanations (SHAP) values was used to quantify the contribution of input pandemic variables. Results indicated the inclusion of pandemic variables reduced the model error by 27.7% compared to a baseline model. The cumulative numbers of COVID-19 cases in previous weeks were found to be stronger predictors of future passenger traffic than daily COVID-19 cases in the most recent week. In addition, the impact of pandemic control policies and passengers' travel behavior was discussed. Our empirical findings provide important implications for airport terminal operations in response to the on-going COVID-19 pandemic.

SARS-CoV-2 exposure in Norwegian rats (Rattus norvegicus) from New York City (preprint)

Millions of Norway rats (Rattus norvegicus) inhabit New York City (NYC), presenting the potential for transmission of SARS-CoV-2 from humans to rats and other wildlife. We evaluated SARS-CoV-2 exposure among 79 rats captured from NYC during the fall of 2021. Results showed that 13 of 79 rats (16.5%) tested IgG or IgM positive, and partial genomes of SARS-CoV-2 were recovered from four rats that were qRT-PCR positive. Using a virus challenge study, we also showed that Alpha, Delta, and Omicron variants can cause robust infections in wild-type Sprague Dawley (SD) rats, including high level replications in the upper and lower respiratory tracts and induction of both innate and adaptive immune responses. Additionally, the Delta variant resulted in the highest infectivity. In summary, our results indicated that rats are susceptible to infection with Alpha, Delta, and Omicron variants, and rats in the NYC municipal sewer systems have been exposed to SARS-CoV-2. Our findings highlight the potential risk of secondary zoonotic transmission from urban rats and the need for further monitoring of SARS-CoV-2 in those populations.

Does airway pressure release ventilation offer new hope for treating acute respiratory distress syndrome?☆

Mechanical ventilation (MV) is an essential life support method for patients with acute respiratory distress syndrome (ARDS), which is one of the most common critical illnesses with high mortality in the intensive care unit (ICU). A lung-protective ventilation strategy based on low tidal volume (LTV) has been recommended since a few years;however, as this did not result in a significant decrease of ARDS-related mortality, a more optimal ventilation mode was required. Airway pressure release ventilation (APRV) is an old method defined as a continuous positive airway pressure (CPAP) with a brief intermittent release phase based on the open lung concept;it also perfectly fits the ARDS treatment principle. Despite this, APRV has not been widely used in the past, rather only as a rescue measure for ARDS patients who are difficult to oxygenate. Over recent years, with an increased understanding of the pathophysiology of ARDS, APRV has been reproposed to improve patient prognosis. Nevertheless, this mode is still not routinely used in ARDS patients given its vague definition and complexity. Consequently, in this paper, we summarize the studies that used APRV in ARDS, including adults, children, and animals, to illustrate the settings of parameters, effectiveness in the population, safety (especially in children), incidence, and mechanism of ventilator-induced lung injury (VILI) and effects on extrapulmonary organs. Finally, we found that APRV is likely associated with improvement in ARDS outcomes, and does not increase injury to the lungs and other organs, thereby indicating that personalized APRV settings may be the new hope for ARDS treatment.

Lymphocyte–C-reactive protein ratio can differentiate disease severity of COVID-19 patients and serve as an assistant screening tool for hospital and ICU admission

In this study, we aimed to explore whether lymphocyte–C-reactive protein ratio (LCR) can differentiate disease severity of coronavirus disease 2019 (COVID-19) patients and its value as an assistant screening tool for admission to hospital and intensive care unit (ICU). A total of 184 adult COVID-19 patients from the COVID-19 Treatment Center in Heilongjiang Province at the First Affiliated Hospital of Harbin Medical University between January 2020 and March 2021 were included in this study. Patients were divided into asymptomatic infection group, mild group, moderate group, severe group, and critical group according to the Diagnosis and Treatment of New Coronavirus Pneumonia (ninth edition). Demographic and clinical data including gender, age, comorbidities, severity of COVID-19, white blood cell count (WBC), neutrophil proportion (NEUT%), lymphocyte count (LYMPH), lymphocyte percentage (LYM%), red blood cell distribution width (RDW), platelet (PLT), C-reactive protein (CRP), alanine aminotransferase (ALT), aspartate aminotransferase (AST), serum creatinine (SCr), albumin (ALB), total bilirubin (TB), direct bilirubin (DBIL), indirect bilirubin (IBIL), and D-dimer were obtained and collated from medical records at admission, from which sequential organ failure assessment (SOFA) score and LCR were calculated, and all the above indicators were compared among the groups. Multiple clinical parameters, including LYMPH, CRP, and LCR, showed significant differences among the groups. The related factors to classify COVID-19 patients into moderate, severe, and critical groups included age, number of comorbidities, WBC, LCR, and AST. Among these factors, the number of comorbidities showed the greatest effect, and only WBC and LCR were protective factors. The area under the receiver operating characteristic (ROC) curve of LCR to classify COVID-19 patients into moderate, severe, and critical groups was 0.176. The cutoff value of LCR and the sensitivity and specificity of the ROC curve were 1,780.7050 and 84.6% and 66.2%, respectively. The related factors to classify COVID-19 patients into severe and critical groups included the number of comorbidities, PLT, LCR, and SOFA score. Among these factors, SOFA score showed the greatest effect, and LCR was the only protective factor. The area under the ROC curve of LCR to classify COVID-19 patients into severe and critical groups was 0.106. The cutoff value of LCR and the sensitivity and specificity of the ROC curve were 571.2200 and 81.3% and 90.0%, respectively. In summary, LCR can differentiate disease severity of COVID-19 patients and serve as a simple and objective assistant screening tool for hospital and ICU admission.

Immunogenicity and efficacy of COVID-19 vaccines in people living with HIV: a systematic review and meta-analysis

Objective Available data show that COVID-19 vaccines may be less effective in people living with HIV (PLWH), who are at increased risk of severe COVID-19. This meta-analysis aimed to compare immunogenicity and efficacy of COVID-19 vaccines in PLWH with healthy individuals. Methods Pubmed/Medline, EMBASE, and the Cochrane Library were searched. Risk ratios of seroconversion were separately pooled with the use of random effects meta-analysis, and systematic review without meta-analysis of SARS-CoV-2 antibody titer levels was performed after the first and second doses of a COVID-19 vaccine. Results Twenty-two studies with 6522 subjects met the inclusion criteria. After first vaccine dose, seroconversion in PLWH was comparable to that in healthy individuals. After a second dose, seroconversion was slightly lower in PLWH compared with healthy controls, and antibody titers did not seem to be significantly affected or reduced among participants of both groups. Conclusions COVID-19 vaccines show favorable immunogenicity and efficacy in PLWH. A second dose is associated with consistently improved seroconversion, although it is slightly lower in PLWH compared with healthy individuals. Additional strategies, such as a booster vaccination with mRNA COVID-19 vaccines, might improve seroprotection for these patients.

Commodity dynamism in the COVID-19 crisis: Are gold, oil, and stock commodity prices, symmetrical?

The current research intends to examine the commodities' dynamism connection with stock prices under the COVID-19 crisis. DCC-GARCH modeling was applied to the data of Asian economies, including China, India, Sri Lanka, Bangladesh, and Pakistan to achieve the study objectives. The study's results indicated a significant connection between gold prices with stock prices and oil prices with stock prices for all Asian stock markets. The results of the study constructs were symmetrical. In general, the connection grows with the frequency. The lowest frequency months contributed the most to the total relationship, followed by more than 12 months. Overall, gold and oil prices influence the Asian stock markets. These research findings can avoid contagion in times of economic uncertainty. This study also suggested policy implications for better decision-making of key stakeholders. Dynamic coefficient values were about 0.8 of β2 because nations' internal markets were more closely linked. There are also dynamic relationship factors between crude oil and foreign currency markets, where the correlations in India and China have always been around 0.

Analysis of intermediate hosts and susceptible animals of SARS-CoV-2 by computational methods

COVID-19, a disease caused by SARS-CoV-2 that produces major symptoms of pneumonia, has been a disaster worldwide. The traceability of SARSCoV- 2 and the discovery of susceptible animal species is crucial to halt viral transmission and explore the mechanism of cross-species transmission. We selected 82 representative ACE2 sequences from the 1000 sequences with the closest homology to the hACE2 protein. All selected ACE2 proteins were subjected to homology modeling. Potential natural and intermediate hosts, as well as animal species susceptible to SARS-CoV-2, were analyzed systematically by calculation of the binding free energy of ACE2 protein to the RBD of SARSCoV- 2. Primates, some wild Felidae, civets, goats, spotted hyenas and golden hamsters are susceptible to SARS-CoV-2 and may be potential intermediate hosts, whereas pangolins, birds and reptiles are unlikely to be intermediate hosts. Mice, rats and guinea pig are not susceptible to SARS-CoV-2. Given their possible susceptibility, non-human primates, goats and golden hamsters could potentially be used as experimental models to examine SARS-CoV-2 infection without transgenesis. Herein, possible candidates for the natural and intermediate hosts of SARS-CoV-2 are suggested, to provide guidance for subsequent studies.

SARS-CoV-2 Serosurveys: How antigen, isotype and threshold choices affect the outcome (preprint)

Background: Evaluating the performance of SARS-CoV-2 serological assays and clearly articulating the utility of selected antigen, isotypes and thresholds is crucial to understanding the prevalence of infection within selected communities. Methods: This cross-sectional study, implemented in 2020, screened PCR-confirmed COVID-19 patients (n=86), banked pre-pandemic and negative donors (n=96), health care workers and family members (n=552), and university employees (n=327) for anti-SARS-CoV-2 receptor-binding domain (RBD), trimeric spike protein (S), and nucleocapsid protein (N) IgG and IgA antibodies with a laboratory developed Enzyme-Linked Immunosorbent Assay (ELISA) and tested how antigen, isotype and threshold choices affected the seroprevalence. The following threshold methods were evaluated: (i) mean + 3 standard deviations of the negative controls; (ii) 100% specificity for each antigen/isotype combination; and (iii) the maximal Youden index. Results: We found vastly different seroprevalence estimates depending on selected antigens, isotypes and the applied threshold method, ranging from 0.0% to 85.4%. Subsequently, we maximized specificity and reported a seroprevalence, based on more than one antigen, ranging from 9.3% to 25.9%. Conclusions: This study revealed the importance of evaluating serosurvey tools for antigen, isotype, and threshold-specific sensitivity and specificity, in order to interpret qualitative serosurvey outcomes reliably and consistently across studies.

Antibiotic-Induced Primary Biles Inhibit SARS-CoV-2 Endoribonuclease Nsp15 Activity in Mouse Gut

The gut microbiome profile of COVID-19 patients was found to correlate with a viral load of SARS-CoV-2, COVID-19 severity, and dysfunctional immune responses, suggesting that gut microbiota may be involved in anti-infection. In order to investigate the role of gut microbiota in anti-infection against SARS-CoV-2, we established a high-throughput in vitro screening system for COVID-19 therapeutics by targeting the endoribonuclease (Nsp15). We also evaluated the activity inhibition of the target by substances of intestinal origin, using a mouse model in an attempt to explore the interactions between gut microbiota and SARS-CoV-2. The results unexpectedly revealed that antibiotic treatment induced the appearance of substances with Nsp15 activity inhibition in the intestine of mice. Comprehensive analysis based on functional profiling of the fecal metagenomes and endoribonuclease assay of antibiotic-enriched bacteria and metabolites demonstrated that the Nsp15 inhibitors were the primary bile acids that accumulated in the gut as a result of antibiotic-induced deficiency of bile acid metabolizing microbes. This study provides a new perspective on the development of COVID-19 therapeutics using primary bile acids.

Widespread wildfires over the western United States in 2020 linked to emissions reductions during COVID‐19

Widespread wildfires struck the western United States in 2020, damaging properties and threating human lives. Meanwhile, the COVID‐19 pandemic spread across the globe, which disrupted human activities. Here, we investigate the effects of the emissions reductions during the pandemic on fire weather in 2020 over the western United States by using an earth system model together with observations. We show that reductions in aerosols dominate the increases in wildfire risks, whereas greenhouse gas decrease counteracts this influence. The aerosol emissions reductions increased surface air temperature and decreased precipitation and relative humidity due to a weakened moisture transport, which explains one‐third of the observed increase in wildfire risks during August–November over the western United States in 2020. This study suggests that COVID‐19‐related emissions reductions have an unexpected influence on wildfires, highlighting a different but important role of human activities in affecting wildfire risks. Key Points The impacts of COVID‐19 emissions reductions on weather conditions for wildfire over the western United States in 2020 were investigated The COVID‐19 emissions reductions increased surface air temperature and decreased precipitation and relative humidity Reductions in aerosols explain one‐third of the observed wildfire risk increase, whereas greenhouse gas decrease counteracts this influence

Risk assessment of public health emergencies concerned in the mainland of China, June 2021

Objective: To assess the risk of public health emergencies, both the indigenous ones and the imported ones, which might occur in the mainland of China in June 2021. Methods: An internet based expert counsel was conducted to analyze the surveillance data of public health emergencies and priority communicable diseases in China reported through different channels, and the experts in all provincial centers for disease control and prevention attended this video conference. Results: Generally speaking, it is predicted that the incidence of public health emergencies would be similar in June with May. The risk of imported cases and secondary infections of COVID-19 would continue to exist, but would be controllable. It is the high incidence season of severe fever with thrombocytopenia syndrome and most cases would be sporadic, however, the risk of cluster exits especially in previous epidemic areas. The incidences of food poisoning caused by toxic animal or plant or poisonous mushroom would increase significantly, and the incidences of food poisoning caused by microbe would be high. The earthquake-stricken areas such as Yunnan and Qinghai should further strengthen post-disaster public health responses. The potential flood-stricken areas predicted by the meteorological department need to pay attention to the risks of water-borne, food-borne and vector-borne diseases that may increase after the disaster. Conclusion: Special attention should be paid to COVID-19, and general attention should be paid to severe fever with thrombocytopenia syndrome, food poisoning and natural disaster.

Risk Factors Associated With Increased Anxiety Sensitivity in Children and Adolescents in Northwest China During COVID-19 Pandemic Lockdown

Purpose A large body of evidence has revealed that the sudden outbreak of public health emergencies induces dramatic effects on the mental health of the general public. We aimed to investigate the level of anxiety sensitivity and its risk factors in children and adolescents from northwest China during the COVID-19 pandemic lockdown in early 2020. Methods A cross-sectional survey was conducted through the Wenjuanxing platform using a convenience sampling method between 18 and 26 February 2020. The self-designed questionnaire contained sociodemographic characteristics, factors associated with the COVID-19 pandemic, and the Childhood Anxiety Sensitivity Index (CASI) scale. The data from 1,091 valid questionnaires from students aged 9–17 years were analyzed using ANOVA, multiple linear regression, and binary logistic regression. Results The average CASI scores were 11.47 ± 6.631, and 642 students (58.9%) had prominent anxiety sensitivity. Gender, education level, family members participating in anti-COVID-19 work, getting ill and needing medical help during the lockdown, feeling afraid or having heart palpitations on hearing things associated with COVID-19, believing that COVID-19 would have adverse impacts on themselves or their family in the future, and fear of infection were identified as significant factors for elevated levels of anxiety sensitivity (p < 0.05). We established a multiple linear regression model for the anxiety sensitivity score. Risk factors found for anxiety sensitivity in children and adolescents during the COVID-19 lockdown included studying in secondary or high school, becoming ill during the pandemic, feeling afraid or experiencing rapid heartbeat or palpitations on hearing about the COVID-19 pandemic, thinking that COVID-19 would have an adverse impact on themselves or their family in the future, and fear of infection. Conclusions During the COVID-19 pandemic and home quarantine, scores measuring the prevalence of anxiety sensitivity in children and adolescents from northwest China were elevated. We should develop measures that especially target possible risk factors to intervene against and prevent anxiety sensitivity in children and adolescents in both the current and future pandemics.

Natural resources commodity prices volatility: Evidence from COVID-19 for the US economy

Volatility in natural resources commodity prices is prevailing for a longer period. However, after the Covid-19 pandemic, most economical and financial markets were affected, and the natural resources commodity market was greatly affected. Besides, the pandemic's closing or postponement of the industrial sector further fuels uncertainty in the natural resources commodity market. Therefore, it is important to analyze whether volatility exists in natural resources commodity prices during the pandemic period? In this regard, the current study investigated price volatility in copper and crude oil prices during the Covid-19 while using the most recent and extended dataset from January 02, 2019, to October 08, 2021, in the case of the US. For empirical examination, this study used the breakpoint unit root test, which illustrates that the leveled data is non-stationary while the first differenced data is stationary, where both leveled and first differenced data demonstrate the breakpoints in time series. This study uses the threshold generalized autoregressive conditional heteroscedasticity (TGARCH) and exponential generalized autoregressive conditional heteroscedasticity (EGARCH) to analyze natural resource commodity price volatility. The empirical findings uncover that both variables are volatile during the Covid-19 pandemic. However, the negative shock of the Covid-19 pandemic makes the crude oil price more volatile relative to copper prices. Besides, the previous variances are also positively associated with the current variances of both variables. The findings also reveal that copper could be a safe haven for reducing volatility in natural resources. Based on the empirical findings, this study suggests ensuring macroeconomic stability and reconsidering the traditional price-fixing or price ceiling policies to tackle volatility in the Covid-19 pandemic.

Virtually Enhancing Public Engagement During the Pandemic: Measuring the Impact of Virtual Reality Powered Immersive Videos on Corporate Social Responsibility Communication

Many companies have applied virtual reality (VR), a new and popular technology, to their corporate social responsibility (CSR) activities. This study examines how 360-degree VR-powered videos might further enhance consumers? engagement in CSR activities and facilitate business outcomes during a crisis setting. The researchers conducted an online survey study, during the coronavirus (COVID-19) pandemic, with 1422 representative U.S. residents and applied the structural equation modeling for data analysis. Results indicated that the four categories of gratifications-sought (i.e., being there, enhancement, interaction, and fun) on 360-degree VR-powered videos could all positively influence CSR engagement;in contrast, CSR skepticism would reduce such engagement online. Corporate social responsibility engagement further improved the organization-public relationships (OPRs) and ultimately influenced consumers? word-of-mouth toward the company. Theoretical and practical implications of these findings were discussed.

Development and characterization of neutralizing antibodies against SRAS-CoV-2 (preprint)

Background The novel coronavirus disease 2019(COVID-19) caused by SARS-CoV-2 that belongs to betacoronaviruseis, and is an enveloped, single and positive-stranded RNA virus. In this study, we describe the production and characterization of four monoclonal antibodies (mAb) with neutralization activities.Methods Thirteen mAbs that identified positive were characterized by neutralization assays, binding affinities identification, and ELISA to evaluate the immunocompetence. The genes of neutralizing antibodies were sequenced and analyzed.Results All mAbs recognized two different epitopes respectively, including RBD and hFc, and the binding affinities are also different. Four of nine mAbs that can recognize the epitopes of RBD are conformation neutralizing antibodies that have high binding affinity and neutralization ability. Based on the sequencing, the mAbs are unique antibodies with specificity.Conclusions We characterized thirteen monoclonal antibodies, four of which are neutralizing antibodies and identified unique antibodies with specificity. The results highlight the promise of antibody-based therapeutics and provide the structural basis of rational vaccine design.

Clinical Analysis of Kidney Injury in Elderly Patients with COVID-19

Objective: The aim of the study was to analyze the clinical features of elderly patients with coronavirus disease 2019 (COVID-19) and to explore the relationship between COVID-19 patients and kidney injury. Methods: A total of 188 elderly patients with confirmed COVID-19 enrolled in this study were hospitalized for at least 1 week in the Central Theater Command General Hospital of Chinese People's Liberation Army from January 3, 2020 to March 14, 2020. The recorded information included clinical data and results of kidney-related laboratory tests. Retrospective analysis was performed. Results: The median age of the patients was 69 years (interquartile range 65–78, range: 60–97 years);31.4% were 60–74 years old, and 68.6% were over 75 years old. A total of 12.8% and 18.6% of the patients were in critical and severe stages of COVID-19, respectively. The proportions of patients using mechanical ventilators and deaths were 9.5% and 8.5%, respectively. A total of 26.1% and 8.5% of the patients showed mild elevation of blood urea nitrogen (BUN) and serum creatinine (SCr) levels at admission. A total of 18.6% and 5.9% of the patients had elevated BUN and SCr 1 week after admission, respectively. A total of 3.1% of the patients were diagnosed with acute kidney injury, and 75% of those patients had chronic kidney disease before admission. Compared with the patients aged 60–74 years, those over 75 years exhibited significantly increased proportions of elevated BUN levels, critical illness, use of mechanical ventilated, and death. Multivariate logistic regression analysis revealed that an elevated BUN level at admission and 1 week after admission were independent risk factors for death in the elderly patients with COVID-19. Conclusion: There were more critical cases and a high mortality in elderly patients with COVID-19. An increased BUN level was an independent risk factor for death in elderly patients with COVID-19.