Unraveling the Impact of COVID-19 Pandemic Dynamics on Commercial Water-Use Variation

Water use was impacted significantly by the COVID-19 pandemic. Although previous studies quantitatively investigated the effects of COVID-19 on water use, the relationship between water-use variation and COVID-19 dynamics (i.e., the spatial-temporal characteristics of COVID-19 cases) has received less attention. This study developed a two-step methodology to unravel the impact of COVID-19 pandemic dynamics on water-use variation. First, using a water-use prediction model, the water-use change percentage (WUCP) indicator, which was calculated as the relative difference between modeled and observed water use, i.e., water-use variation, was used to quantify the COVID-19 effects on water use. Second, two indicators, i.e., the number of existing confirmed cases (NECC) and the spatial risk index (SRI), were applied to characterize pandemic dynamics, and the quantitative relationship between WUCP and pandemic dynamics was examined by means of regression analysis. We collected and analyzed 6-year commercial water-use data from smart meters of Zhongshan District in Dalian City, Northeast China. The results indicate that commercial water use decreased significantly, with an average WUCP of 59.4%, 54.4%, and 45.7%during the three pandemic waves, respectively, in Dalian. Regression analysis showed that there was a positive linear relationship between water-use changes (i.e., WUCP) and pandemic dynamics (i.e., NECC and SRI). Both the number of COVID-19 cases and their spatial distribution impacted commercial water use, and the effects were weakened by restriction strategy improvement, and the accumulation of experience and knowledge about COVID-19. This study provides an in-depth understanding of the impact of COVID-19 dynamics on commercial water use. The results can be used to help predict water demand under during future pandemic periods or other types of natural and human-made disturbance.

VACtrac: enhancing access immunization registry data for population outreach using the Bulk Fast Healthcare Interoperable Resource (FHIR) protocol.

COVID-19 vaccination uptake has been suboptimal, even in high-risk populations. New approaches are needed to bring vaccination data to the groups leading outreach efforts. This article describes work to make state-level vaccination data more accessible by extending the Bulk Fast Healthcare Interoperability Resource (FHIR) standard to better support the repeated retrieval of vaccination data for coordinated outreach efforts. We also describe a corresponding low-foot-print software for population outreach that automates repeated checks of state-level immunization data and prioritizes outreach by social determinants of health. Together this software offers an integrated approach to addressing vaccination gaps. Several extensions to the Bulk FHIR protocol were needed to support bulk query of immunization records. These are described in detail. The results of a pilot study, using the outreach tool to target a population of 1500 patients are also described. The results confirmed the limitations of current patient-by-patient approach for querying state immunizations systems for population data and the feasibility of a Bulk FHIR approach.

Aptamers dimerization inspired biomimetic clamp assay towards impedimetric SARS-CoV-2 antigen detection.

Antigen-detecting rapid diagnostic testing (Ag-RDT) has contributed to containing the spread of SARS-CoV-2 variants of concern (VOCs). In this study, we proposed a biomimetic clamp assay for impedimetric SARS-CoV-2 nucleocapsid protein (Np) detection. The DNA biomimetic clamp (DNA-BC) is formed by a pair of Np aptamers connected via a T20 spacer. The 5'- terminal of the DNA-BC is phosphate-modified and then anchored on the surface of the screen-printed gold electrode, which has been pre-coated with Au@UiO-66-NH2. The integrated DNA-material sensing biochip is fabricated through the strong Zr-O-P bonds to form a clamp-type impedimetric aptasensor. It is demonstrated that the aptasensor could achieve Np detection in one step within 11 min and shows pronounced sensitivity with a detection limit of 0.31 pg mL-1. Above all, the aptasensor displays great specificity and stability under physiological conditions as well as various water environments. It is a potentially promising strategy to exploit reliable Ag-RDT products to confront the ongoing epidemic.

Customization of aptamer to develop CRISPR/Cas12a-derived ultrasensitive biosensor.

The CRISPR/Cas systems have provided wide biosensing applications. Particularly, the aptamer-involved CRISPR/Cas sensor system powerfully expanded to non-nucleic-acid targets. However, tailoring the sequence of the aptamer to explore the relationship between affinity and the activation of CRISPR/Cas12a trans-cleavage activity has not been reported yet. Herein, we developed a series of new aptamers toward the spike protein 1(S1) of SARS-CoV-2. Surface plasmon resonance measurements showed that the affinity of these aptamers to S1 was at the nM level. Subsequently, a "SET" effect (Sequence Essential Trans-cleavage activity) is discovered for the activation of CRISPR/Cas12a trans-cleavage activity. That is, an aptamer, as the activator, sequence needs to be tailored to activate CRISPR/Cas12a efficiently. A balance should be reached between affinity and activation ability. On the one hand, high affinity ensures target recognition performance, and on the other hand, activation can achieve adequate amplification and output of recognition signals. The optimized sequence (with 27 nucleotides, for short 27-nt) not only recognizes the target with a high affinity and specificity but also can trigger the CRISPR/Cas12a trans-cleavage activity efficiently, showing an excellent detection performance in electrochemical biosensors. The detection limit for SARS-CoV-2 S1 can be low at 1.5 pg mL-1. The new CRISPR/Cas12a-derived aptasensor also displays a remarkable ability to detect Beta, Delta, and Omicron variants but is selective toward other kinds of proteins. Above all, it is robust for point-of-care testing (POCT) in complex biological fluids, such as saliva, urine, and serum, and provides a universal and scalable detecting platform. Our results provide new insights into aptamer development and a different strategy for COVID-19 antigen detection and biosensor development.

Huaier effects on functional compensation with destructive ribosomal RNA structure after anti-SARS-CoV-2 mRNA vaccination. (preprint)

Although striking effects of vaccination strategy against COVID-19 world-wide, a long-term influence by sequential viral mRNA injections are unknown. We analysed biological alterations by total RNA sequencing in Pfizer-BioNTech vaccinated normal healthy volunteers and cancer patients, with or without adjuvant Huaier therapy. A significant destruction in ribosomal RNA structures was identified, enhanced by serial shots. Unlike the destruction caused by chemotherapy with platinum (II) complex, progressive destruction in 18S ribosome was identified even at 6 months after vaccination. The influence resulted in massive inhibition of translation and transcription, significantly in intra/inter neural signaling transfer and in lipid metabolism, related to ageing process. Huaier compensated these dysfunctions by miRNA-mediated transcriptional control, by typical activation in PI3K/AKT signaling pathway. Gene Ontology analysis revealed spontaneous virion production in number even after 3 months of the first vaccination. Present study indicated that the adjuvant therapy like Huaier compensates accelerated ageing process by mRNA vaccination.

The Prediction Model of Risk Factors for COVID-19 Developing into Severe Illness Based on 1046 Patients with COVID-19.

This study analyzed the risk factors for patients with COVID-19 developing severe illnesses and explored the value of applying the logistic model combined with ROC curve analysis to predict the risk of severe illnesses at COVID-19 patients' admissions. The clinical data of 1046 COVID-19 patients admitted to a designated hospital in a certain city from July to September 2020 were retrospectively analyzed, the clinical characteristics of the patients were collected, and a multivariate unconditional logistic regression analysis was used to determine the risk factors for severe illnesses in COVID-19 patients during hospitalization. Based on the analysis results, a prediction model for severe conditions and the ROC curve were constructed, and the predictive value of the model was assessed. Logistic regression analysis showed that age (OR = 3.257, 95% CI 10.466-18.584), complications with chronic obstructive pulmonary disease (OR = 7.337, 95% CI 0.227-87.021), cough (OR = 5517, 95% CI 0.258-65.024), and venous thrombosis (OR = 7322, 95% CI 0.278-95.020) were risk factors for COVID-19 patients developing severe conditions during hospitalization. When complications were not taken into consideration, COVID-19 patients' ages, number of diseases, and underlying diseases were risk factors influencing the development of severe illnesses. The ROC curve analysis results showed that the AUC that predicted the severity of COVID-19 patients at admission was 0.943, the optimal threshold was -3.24, and the specificity was 0.824, while the sensitivity was 0.827. The changes in the condition of severe COVID-19 patients are related to many factors such as age, clinical symptoms, and underlying diseases. This study has a certain value in predicting COVID-19 patients that develop from mild to severe conditions, and this prediction model is a useful tool in the quick prediction of the changes in patients' conditions and providing early intervention for those with risk factors.

Cryo-EM analysis of the HCoV-229E spike glycoprotein reveals dynamic prefusion conformational changes.

Coronaviruses spike (S) glycoproteins mediate viral entry into host cells by binding to host receptors. However, how the S1 subunit undergoes conformational changes for receptor recognition has not been elucidated in Alphacoronavirus. Here, we report the cryo-EM structures of the HCoV-229E S trimer in prefusion state with two conformations. The activated conformation may pose the potential exposure of the S1-RBDs by decreasing of the interaction area between the S1-RBDs and the surrounding S1-NTDs and S1-RBDs compared to the closed conformation. Furthermore, structural comparison of our structures with the previously reported HCoV-229E S structure showed that the S trimers trended to open the S2 subunit from the closed conformation to open conformation, which could promote the transition from pre- to postfusion. Our results provide insights into the mechanisms involved in S glycoprotein-mediated Alphacoronavirus entry and have implications for vaccine and therapeutic antibody design.

Deployment of workforce in global health: what should be the priorities for China?

BACKGROUND: China has increasingly emerged as an important player in global health. However, compared to developed countries, China still lacks a sufficient health workforce for global health engagement with the necessary competencies required. The world has recognized that to solve global health issues, the role of China needs to be strengthened. The priorities for the deployment of the Chinese workforce in global health remain unclear. This study aims to identify the priorities of the deployment of Chinese global health workforce by exploring the core competencies for Chinese global health workforce, factors influencing the deployment and the approach of deployment. METHODS: Quantitative descriptive statistical analysis was applied to analyze the quantitative data. A total of 148 key respondents from 10 provinces in China conducting global health projects over the last 3 years were selected as the study subjects. A structured questionnaire was developed to collect the data on four aspects, including general information, core competencies, factors influencing deployment, and mode of deployment. The questionnaire was distributed to the respondents through an online survey. All original data were exported to Microsoft Excel 2010 to calculate the frequencies and percentages of each option. A descriptive analysis was carried out of the priorities of deployment of the Chinese global health workforce. RESULTS: More than half of the respondents (51.4%, 76/148) regarded "communication" as the most important competency of the Chinese global health workforce, while a large proportion of participants from Chinese embassies (50.0%, 6/12) and international organizations (75.0%, 12/16) believed that "professional skills" were paramount. In addition, 58.1% (86/148) of the participants agreed that incentive factors (salary, professional position, etc.) were the main factors that influenced deployment, whereas 75% (12/16) of participants from international organizations emphasized "security" as the most important determinant. In addition, 60.8% (90/148) of the participants thought that the deployment of staff should be based on the needs of the global health project implementation. CONCLUSIONS: This study highlights the deployment priorities of the Chinese global health workforce, including strengthening communication and professional skills, focusing on personal security and incentives, and catering to the project implementation. This study also highlights the importance of Chinese agencies in developing global health mindsets through global health practices and proactive integration within the global community.

CD147 antibody specifically and effectively inhibits infection and cytokine storm of SARS-CoV-2 variants (preprint)

SARS-CoV-2 and its variants are raging worldwide. Unfortunately, the global vaccination is not efficient enough to attain a vaccine-based herd-immunity and yet no special and effective drug is developed to contain the spread of the disease. Previously we have identified CD147 as a novel receptor for SARS-CoV-2 infection. Here, we demonstrated that CD147 antibody effectively inhibits infection and cytokine storm caused by SARS-CoV-2 variants. In CD147KO VeroE6 cells, infections of SARS-CoV-2, its variants (B.1.1.7, B.1.351) and pseudovirus mutants (B.1.1.7, B.1.351, B.1.525, B.1.526 (S477N), B.1.526 (E484K), P.1, P.2, B.1.617.1, B.1.617.2) were decreased. Meanwhile, CD147 antibody effectively blocked the entry of variants and pseudomutants in VeroE6 cells, and inhibited the expression of cytokines. A model of SARS-CoV-2-infected hCD147 transgenic mice was constructed, which recapitulated the features of exudative diffuse alveolar damage and dynamic immune responses of COVID-19. CD147 antibody could effectively clear the virus and alveolar exudation, resolving the pneumonia. We found the elevated level of cyclophilin A (CyPA) in plasma of severe/critical cases, and identified CyPA as the most important proinflammatory intermediate causing cytokine storm. Mechanistically, spike protein of SARS-CoV-2 bound to CD147 and initiated the JAK-STAT pathway, which induced expression of CyPA. CyPA reciprocally bound to CD147, triggered MAPK pathway and consequently mediated the expression of cytokine and chemokine. In conclusion, CD147 is a critical target for SARS-CoV-2 variants and CD147 antibody is a promising drug to control the new wave of COVID-19 epidemic.

Informatics for public health and health system collaboration: Applications for the control of the current COVID-19 pandemic and the next one.

Public health faces unprecedented challenges in its efforts to control COVID-19 through a national vaccination campaign. Addressing these challenges will require fundamental changes to public health data systems. For example, of the core data systems for immunization campaigns is the immunization information system (IIS); however, IISs were designed for tracking the vaccinated, not finding the patients who are high risk and need to be vaccinated. Health systems have this data in their electronic health records (EHR) systems and often have a greater capacity for outreach. Clearly, a partnership is needed. However, successful collaborations will require public health to change from its historical hierarchical information supply chain model to an ecosystem model with a peer-to-peer exchange with population health providers. Examples of the types of informatics innovations necessary to support such an ecosystem include a national patient identifier, population-level data exchange for immunization data, and computable electronic quality measures. Rather than think of these components individually, a comprehensive approach to rapidly adaptable tools for collaboration is needed.

Detecting SARS-CoV-2 in the Breath of COVID-19 Patients.

In the COVID-19 outbreak year 2020, a consensus was reached on the fact that SARS-CoV-2 spreads through aerosols. However, finding an efficient method to detect viruses in aerosols to monitor the risk of similar infections and enact effective control remains a great challenge. Our study aimed to build a swirling aerosol collection (SAC) device to collect viral particles in exhaled breath and subsequently detect SARS-CoV-2 using reverse transcription polymerase chain reaction (RT-PCR). Laboratory tests of the SAC device using aerosolized SARS-CoV-2 pseudovirus indicated that the SAC device can produce a positive result in only 10 s, with a collection distance to the source of 10 cm in a biosafety chamber, when the release rate of the pseudovirus source was 1,000,000 copies/h. Subsequent clinical trials of the device showed three positives and 14 negatives out of 27 patients in agreement with pharyngeal swabs, and 10 patients obtained opposite results, while no positive results were found in a healthy control group (n = 12). Based on standard curve calibration, several thousand viruses per minute were observed in the tested exhalations. Furthermore, referring to the average tidal volume data of adults, it was estimated that an exhaled SARS-CoV-2 concentration of approximately one copy/mL is detectable for COVID-19 patients. This study validates the original concept of breath detection of SARS-CoV-2 using SAC combined with RT-PCR.

A nationwide evaluation of the prevalence of and risk factors associated with anxiety, depression and insomnia symptoms during the return-to-work period of coronavirus disease 2019 in China.

PURPOSE: To evaluate the prevalence of and risk factors associated with anxiety, depression, and insomnia symptoms during the return-to-work period of coronavirus disease 2019 in China. METHODS: The authors conducted a large-scale, nationwide, multicenter, cross-sectional study in China. A population-based quota and snowball sampling were designed to recruit a representative sample. Online questionnaires and telephone reviews were used to collect characteristics and assess psychological and sleep problems. Anxiety, depression, and insomnia symptoms were measured by the generalized anxiety disorder-7, patient health questionnaire-9, and insomnia severity index tools. RESULTS: A total of 42,000 participants were recruited from 15 centers, and 36,795 valid questionnaires were received. Generally, 18.3, 14.9, and 17.9% of the participants had anxiety, depression, and insomnia symptoms, respectively, and 2.2-2.7% had severe symptoms. Engaging in outside activity once in ≥ 30 days (OR = 2.719, OR = 2.074, OR = 2.225) and age 50-64 years (OR = 2.431, OR = 1.936, OR = 2.036) were common risk factors for anxiety, depression and insomnia symptoms. Living in Hubei Province (OR = 1.304, OR = 1.242) was a common risk factor for anxiety and insomnia symptoms. Working as frontline medical staff (OR = 2.150) was another risk factor for anxiety symptoms. The health education rate of the samples reached 98.9%. However, the psychological intervention rate was only 16.2%, and 2.5% received targeted interventions. CONCLUSIONS: An increasing number of people might have psychological and sleep problems. However, the current psychological interventions are not sufficient. Efforts should be made to strengthen interventions for high-risk populations.

Analysis and prediction of COVID-19 epidemic in South Africa.

The coronavirus disease-2019 (COVID-19) has been spreading rapidly in South Africa (SA) since its first case on 5 March 2020. In total, 674,339 confirmed cases and 16,734 mortality cases were reported by 30 September 2020, and this pandemic has made severe impacts on economy and life. In this paper, analysis and long-term prediction of the epidemic dynamics of SA are made, which could assist the government and public in assessing the past Infection Prevention and Control Measures and designing the future ones to contain the epidemic more effectively. A Susceptible-Infectious-Recovered model is adopted to analyse epidemic dynamics. The model parameters are estimated over different phases with the SA data. They indicate variations in the transmissibility of COVID-19 under different phases and thus reveal weakness of the past Infection Prevention and Control Measures in SA. The model also shows that transient behaviours of the daily growth rate and the cumulative removal rate exhibit periodic oscillations. Such dynamics indicates that the underlying signals are not stationary and conventional linear and nonlinear models would fail for long-term prediction. Therefore, a large class of mappings with rich functions and operations is chosen as the model class and the evolutionary algorithm is utilized to obtain the optimal model for long term prediction. The resulting models on the daily growth rate, the cumulative removal rate and the cumulative mortality rate predict that the peak and inflection point will occur on November 4, 2020 and October 15, 2020, respectively; the virus shall cease spreading on April 28, 2021; and the ultimate numbers of the COVID-19 cases and mortality cases will be 785,529 and 17,072, respectively. The approach is also benchmarked against other methods and shows better accuracy of long-term prediction.

Psychological distress and sleep problems when people are under interpersonal isolation during an epidemic: A nationwide multicenter cross-sectional study.

BACKGROUND.: During the outbreak of coronavirus disease 2019 (COVID-19), people are under the dual pressure of interpersonal isolation and concerns about infection. An evaluation of people's psychological status and risk factors is needed to conduct target interventions. METHODS.: This was a nationwide, multicenter, cross-sectional study using quota and snowball sampling methods during the COVID-19 epidemic in China. Participants' characteristics and experiences were obtained by an online questionnaire and telephone review. Psychological distress and sleep problems were measured by the Generalized Anxiety Disorder-7, the Patient Health Questionnaire-9, and the Insomnia Severity Index. RESULTS.: A total of 23,500 participants were recruited, and 19,372 valid questionnaires were received from 11 centers. Overall, 11.0-13.3% of the participants had anxiety, depression, or insomnia symptoms, and 1.9-2.7% had severe symptoms. The prevalence of psychological and sleep problems has increased. Working as frontline medical staff (Odds Ratio OR = 3.406), living in Hubei Province (OR = 2.237), close contacts with COVID-19 (OR = 1.808), and age 35-49 years (OR = 1.310) were risk factors for anxiety symptoms; no outside activity for 2 weeks (OR = 2.167) and age 35-49 years (OR = 1.198) were risk factors for depression symptoms; and living in Hubei Province (OR = 2.376), no outside activity for 2 weeks (OR = 1.927), and age 35-49 years (OR = 1.262) were risk factors for insomnia symptoms. Only 1.9% of participants received counseling during the epidemic. CONCLUSIONS.: Psychological and sleep problems increased during interpersonal isolation due to COVID-19. Current psychological interventions are far from sufficient.

Status and influential factors of anxiety depression and insomnia symptoms in the work resumption period of COVID-19 epidemic: A multicenter cross-sectional study.

OBJECTIVE: In this study, the authors analyzed the status of anxiety depression and insomnia symptoms and influential factors in the work resumption period of Coronavirus disease 2019 (COVID-19). METHODS: A multicenter cross-sectional survey was conducted from March 2, 2020 to March 8, 2020 in Shandong Province, China, using quota sampling combined with snowball sampling. The Generalized Anxiety Disorder-7 (GAD-7), the Patient Health Questionnaire-9 (PHQ-9), and the Insomnia Severity Index (ISI) were used to assess the anxiety, depression, and insomnia symptoms. The multivariate logistic regression analysis was used to explore the influential factors. RESULTS: A total of 4000 invitations were sent from three centers, 3237 valid questionnaires were received. Based on GAD-7, PHQ-9, and ISI scales, 19.5%-21.7% of the participants had anxiety, depression, or insomnia symptoms; 2.9%-5.6% had severe symptoms. Besides, 2.4%, 4.8%, and 4.5% of the participants had anxiety-depression, anxiety-insomnia, or depression-insomnia combined symptoms. The scores of anxiety and insomnia symptoms, along with scores of depression and insomnia symptoms were positively correlated in these samples. Aged 50-64 years and outside activities once in ≥30 days were risk factors of anxiety, depression, and insomnia symptoms in common. During the epidemic, 17.4% of the participants had received psychological interventions, and only 5.2% had received individual interventions. CONCLUSIONS: The incidence of psychological distress increased during the outbreak of COVID-19 in the work resumption period than the normal period. Current psychological interventions were insufficient; target psychological interventions should be conducted in time.

Assessing risk factors for SARS-CoV-2 infection in patients presenting with symptoms in Shanghai, China: a multicentre, observational cohort study.

Background: The outbreak of COVID-19 has led to international concern. We aimed to establish an effective screening strategy in Shanghai, China, to aid early identification of patients with COVID-19. Methods: We did a multicentre, observational cohort study in fever clinics of 25 hospitals in 16 districts of Shanghai. All patients visiting the clinics within the study period were included. A strategy for COVID-19 screening was presented and then suspected cases were monitored and analysed until they were confirmed as cases or excluded. Logistic regression was used to determine the risk factors of COVID-19. Findings: We enrolled patients visiting fever clinics from Jan 17 to Feb 16, 2020. Among 53 617 patients visiting fever clinics, 1004 (1·9%) were considered as suspected cases, with 188 (0·4% of all patients, 18·7% of suspected cases) eventually diagnosed as confirmed cases. 154 patients with missing data were excluded from the analysis. Exposure history (odds ratio [OR] 4·16, 95% CI 2·74-6·33; p<0·0001), fatigue (OR 1·56, 1·01-2·41; p=0·043), white blood cell count less than 4 × 109 per L (OR 2·44, 1·28-4·64; p=0·0066), lymphocyte count less than 0·8 × 109 per L (OR 1·82, 1·00-3·31; p=0·049), ground glass opacity (OR 1·95, 1·32-2·89; p=0·0009), and having both lungs affected (OR 1·54, 1·04-2·28; p=0·032) were independent risk factors for confirmed COVID-19. Interpretation: The screening strategy was effective for confirming or excluding COVID-19 during the spread of this contagious disease. Relevant independent risk factors identified in this study might be helpful for early recognition of the disease. Funding: National Natural Science Foundation of China.

Meplazumab treats COVID-19 pneumonia: an open-labelled, concurrent controlled add-on clinical trial (preprint)

Background: SARS-CoV-2 is a novel human coronavirus, there is no specific antiviral drugs. It has been proved that host-cell-expressed CD147 could bind spike protein of SARS-CoV-2 and involve in host cell invasion. Antibody against CD147 could block the infection of SARS-CoV-2. We aimed to assess the efficacy and safety of meplazumab, a humanized anti-CD147 antibody, as add-on therapy in patients with COVID-19 pneumonia. Methods: All patients received recommended strategy from Diagnosis and Treatment for 2019 Novel Coronavirus Diseases released by National Health Commission of China. Eligible patients were add-on administered 10 mg meplazumab intravenously at days 1, 2, and 5. Patients hospitalized in the same period were observed as concurrent control. The endpoints include virological clearance rate, case severity, chest radiographic, and laboratory test. This trial was approved by the Ethics Committee of Institution at the Tangdu hospital, and registered with ClinicalTrials.gov, NCT 04275245. Findings:17 patients were enrolled and assigned to meplazumab group between Feb 3, 2020 and Feb 10, 2020. 11 hospitalized patients served as concurrent control. Baseline characteristics were generally balanced across two groups. Compared to control group, meplazumab treatment significantly improved the discharged (p=0.006) and case severity (p=0.021) in critical and severe patients. The time to virus negative in meplazumab group was reduced than that in control group (median 3, 95%CI[1.5-4.5] vs. 13, [6.5-19.5]; p=0.014, HR=0.37, 95%CI[0.155-0.833]). The percentages of patients recovered to the normal lymphocyte count and CRP concentration were also increased remarkably and rapidly in meplazumab group. No adverse effect was found in meplazumab-treated patients. Interpretation:Meplazumab efficiently improved the recovery of patients with SARS-CoV-2 pneumonia with a favorable safety profile. Our results support to carry out a large-scale investigation of meplazumab as a treatment for COVID-19 pneumonia. Funding:National Science and Technology Major Project.

SARS-CoV-2 invades host cells via a novel route: CD147-spike protein (preprint)

Currently, COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been widely spread around the world; nevertheless, so far there exist no specific antiviral drugs for treatment of the disease, which poses great challenge to control and contain the virus. Here, we reported a research finding that SARS-CoV-2 invaded host cells via a novel route of CD147-spike protein (SP). SP bound to CD147, a receptor on the host cells, thereby mediating the viral invasion. Our further research confirmed this finding. First, in vitro antiviral tests indicated Meplazumab, an anti-CD147 humanized antibody, significantly inhibited the viruses from invading host cells, with an EC50 of 24.86 g/mL and IC50 of 15.16 g/mL. Second, we validated the interaction between CD147 and SP, with an affinity constant of 1.85x10-7M. Co-Immunoprecipitation and ELISA also confirmed the binding of the two proteins. Finally, the localization of CD147 and SP was observed in SARS-CoV-2 infected Vero E6 cells by immuno-electron microscope. Therefore, the discovery of the new route CD147-SP for SARS-CoV-2 invading host cells provides a critical target for development of specific antiviral drugs.