Bidirectional causal relationships between IgA nephropathy and COVID-19: genetic evidence from Mendelian randomization (preprint)

Purpose Previous studies have suggested that patients with IgA nephropathy (IgAN) was associated with an increased risk of coronavirus disease 2019 (COVID-19) infection. However, the findings were inconsistent, and whether there was a causality between IgAN and COVID-19 infection remains unknown. This study was performed to estimate the casual effect between IgAN and COVID-19 infection with the implementation of bidirectional Mendelian randomization (MR) analysis.Methods Genetic summary data of IgAN was derived from a large genome-wide association study (GWAS) that consisted of 14,361 cases and 43,923 controls. The genetic data of COVID-19 comprised of three phenotypes, including hospitalization, severity and infection, which had a population more than 20 million. The methods of inverse variance weighting (IVW), MR-Egger, weight median and weighted mode were applied for causal inference in MR analysis.Results In the forward direction, the IVW’s results proved that IgAN did not have causal relationships with hospitalization COVID-19 (OR = 1.077, 95%CI: 0.953–1.217, P = 0.236), severe COVID-19 (OR = 1.059, 95%CI: 0.878–1.278, P = 0.547) and COVID-19 infection (OR = 0.973, 95%CI: 0.929–1.109, P = 0.243). Furthermore, reverse MR analysis showed no evidence of causal associations of hospitalization COVID-19 (OR = 1.017, 95%CI: 0.968–1.069, P = 0.499), severe COVID-19 (OR = 1.005, 95%CI: 0.979–1.078, P = 0.781) and COVID-19 infection (OR = 1.030, 95%CI: 0.909–1.169, P = 0.641) with the risk of IgAN.Conclusion Our study does not support a casual association of IgAN with the risk of COVID-19 infection, nor does the causality between COVID-19 infection and IgAN risk.

SARS-CoV-2: An Updated Review Highlighting Its Evolution and Treatments.

Since the SARS-CoV-2 outbreak, pharmaceutical companies and researchers worldwide have worked hard to develop vaccines and drugs to end the SARS-CoV-2 pandemic. The potential pathogen responsible for Coronavirus Disease 2019 (COVID-19), SARS-CoV-2, belongs to a novel lineage of beta coronaviruses in the subgenus arbovirus. Antiviral drugs, convalescent plasma, monoclonal antibodies, and vaccines are effective treatments for SARS-CoV-2 and are beneficial in preventing infection. Numerous studies have already been conducted using the genome sequence of SARS-CoV-2 in comparison with that of other SARS-like viruses, and numerous treatments/prevention measures are currently undergoing or have already undergone clinical trials. We summarize these studies in depth in the hopes of highlighting some key details that will help us to better understand the viral origin, epidemiology, and treatments of the virus.

Development of a thermostable SARS-CoV-2 variant-based bivalent protein vaccine with cross-neutralizing potency against Omicron subvariants

SARS-CoV-2 variants have posed significant challenges to the hopes of using ancestral strain-based vaccines to address the risk of breakthrough infection by variants. We designed and developed a bivalent vaccine based on SARS-CoV-2 Alpha and Beta variants (named SCTV01C). SCTV01C antigens were stable at 25 oC for at least 6 months. In the presence of a squalene-based oil-in-water adjuvant SCT-VA02B, SCTV01C showed significant protection efficacy against antigen-matched Beta variant, with favorable safety profiles in rodents. Notably, SCTV01C exhibited cross-neutralization capacity against Omicron subvariants (BA.1, BA.1.1, BA.2, BA.3, and BA.4/5) in mice, superior to a WT (D614G)-based vaccine, which reinforced our previously published findings that SCTV01C exhibited broad-spectrum neutralizing potencies against over a dozen pre-Omicron variants and the Omicron BA.1 variant. In summary, variant-based multivalent protein vaccine could be a platform approach to address the challenging issues of emerging variants, vaccine hesitancy and the needs of affordable and thermal stable vaccines.

Efficacy and Safety of Lianhua Qingwen for Patients with COVID-19: A Systematic Review and Meta-Analysis.

BACKGROUND: Corona virus disease 2019 (COVID-19) has spread around the world since its outbreak, and there is no ascertained effective drug up to now. Lianhua Qingwen (LHQW) has been widely used in China and overseas Chinese, which had some advantages in the treatment of COVID-19. OBJECTIVE: To evaluate the efficacy and safety of LHQW for COVID-19 by conducting a systematic review with meta-analysis. METHODS: A comprehensive literature search was conducted in 12 electronic databases from their establishment to October 30, 2021. Note Express 3.2.0 was used for screening of trials, and the data was independently extracted in duplicate by 2 researchers. The risk of bias of randomized controlled trials (RCTs) and retrospective studies were assessed by using the Cochrane collaboration tool and Newcastle Ottawa Scale, respectively, followed by data analysis using RevMan 5.3. The RCTs or retrospective studies to treat COVID-19 using LHQW were included. The intervention measures in the experimental group were LHQW alone or combined with chemical drugs (LCWC), and that in the control group were chemical drugs (CDs). Outcome measures included computed tomography (CT) recovery rate, disappearance rates of primary (fever, cough, fatigue), respiratory, gastrointestinal and other symptoms, exacerbation rate and adverse reaction. Subgroup analysis was conducted according to whether LHQW was combined with CDs and the different treatment methods in the control group. RESULTS: Nine trials with 1,152 participants with COVID-19 were included. The CT recovery rates of LHQW and LCWC were 1.36 and 1.32 times of CDs, respectively (P<0.05). Compared with CDs, LCWC remarkably increased the disappearance rates of fever, cough, fatigue, expectoration, shortness of breath, and muscle soreness (P<0.05). LHQW also obviously decreased the exacerbation rate, which was 0.45 times of CDs alone (P<0.05). There was no obvious difference between LCWC and CDs in adverse reaction (P>0.05). CONCLUSIONS: LHQW was more suitable for treating COVID-19 patients with obvious expectoration, shortness of breath and muscle soreness. LHQW had advantages in treating COVID-19 with no obvious exacerbation. (PROSPERO No. CRD42021235937).

Urban-regional disparities in mental health signals in Australia during the COVID-19 pandemic: a study via Twitter data and machine learning models

This study establishes a novel empirical framework using machine learning techniques to measure the urban-regional disparity of the public's mental health signals in Australia during the pandemic, and to examine the interrelationships amongst mental health, demographic and socioeconomic profiles of neighbourhoods, health risks and healthcare access. Our results show that the public's mental health signals in capital cities were better than those in regional areas. The negative mental health signals in capital cities are associated with a lower level of income, more crowded living space, a lower level of healthcare availability and more difficulties in healthcare access.

Uncovering physical and attitudinal barriers to adherence to precautions for preventing the transmission of covid-19 and anxiety level of people in wuhan: 2 months after the lockdown

BACKGROUND: Wuhan, the epicenter of the coronavirus diseases 2019 outbreak, was locked down on January 23, 2020. We aimed to investigate the barriers to the physical prevention, negative attitudes, and anxiety levels. METHODS: A online cross-sectional survey was conducted with the people living in Wuhan between March 12th and 23rd, 2020. RESULTS: Of a total of 2411 complete responses, the mean and standard deviation for the total physical prevention barriers score was 19.73 (standard deviation +/- 5.3;range 12-45) out of a possible score of 48. Using a cut-off score of 44 for the State-Trait Inventory score, 79.9% (95% confidence interval [CI]: 78.2-81.5) of the participants reported moderate to severe anxiety during the early phase of the outbreak, and 51.3% (95% CI 49.2-53.3) reported moderate to severe anxiety after the peak of coronavirus diseases 2019 was over (during the study period). Comparing anxiety levels in the early phase of the outbreak and after the peak of the outbreak, 58.5% (95% CI 56.5-60.5) recorded a decreased anxiety. Females reported a higher likelihood of having decreased levels of anxiety than males (odds ratio = 1.78, 95% CI 1.48-2.14). Low negative attitudes score were associated with a higher decrease in anxiety (odds ratio = 1.59, 95% CI 1.33-1.89). CONCLUSIONS: The attitudinal barriers to prevention of transmission of coronavirus diseases 2019 are more prominent than physical prevention barriers after the peak of coronavirus diseases 2019. High anxiety levels even after the peak warrant serious attention. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

The emergence of inter-clade hybrid SARS-CoV-2 lineages revealed by 2D nucleotide variation mapping (preprint)

I performed whole-genome sequencing on SARS-CoV-2 collected from COVID-19 samples at Mayo Clinic Rochester in mid-April, 2020, generated 85 consensus genome sequences and compared them to other genome sequences collected worldwide. I proposed a novel illustrating method using a 2D map to display populations of co-occurring nucleotide variants for intra- and inter- viral clades. This method is highly advantageous for the new era of big-data when high-throughput sequencing is becoming readily available. Using this method, I revealed the emergence of inter-clade hybrid SARS-CoV-2 lineages that are potentially caused by homologous genetic recombination.

Methyltransferase-like 3 modulates severe acute respiratory syndrome coronavirus-2 RNA N6-methyladenosine modification and replication (preprint)

The coronavirus disease 2019 pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is an ongoing global public crisis. Although viral RNA modification has been reported based on the transcriptome architecture, the types and functions of RNA modification are still unknown. In this study, we evaluated the roles of RNA N6-methyladenosine (m6A) modification in SARS-CoV-2. Our methylated RNA immunoprecipitation sequencing (MeRIP-Seq) analysis showed that SARS-CoV-2 RNA contained m6A modification. Moreover, SARS-CoV-2 infection not only increased the expression of methyltransferase-like 3 (METTL3) but also altered its distribution. Modification of METTL3 expression by short hairpin RNA or plasmid transfection for knockdown or overexpression, respectively, affected viral replication. Furthermore, the viral key protein RdRp interacted with METTL3, and METTL3 was distributed in both the nucleus and cytoplasm in the presence of RdRp. RdRp appeared to modulate the sumoylation and ubiquitination of METTL3 via an unknown mechanism. Taken together, our findings demonstrated that the host m6A modification complex interacted with viral proteins to modulate SARS-CoV-2 replication.

Evaluation and improvement of the emergency capacity of medical staff for COVID-19: A cross-sectional study in China (preprint)

Background: Coronavirus disease 2019 (COVID-19) has spread to 216 countries and territories around the world. Most studies on response to public health emergencies, focus on health systems, local governments or medical organizations, but fewer studies focus on individuals. However, medical staff are the core strength for responding to public health emergencies. The aims of this study are to investigate the status of medical staff’s emergency capacity during the pandemic and to provide intellectual support to further enhance medical staff's ability to ensure the smooth operation of medical rescue. Methods: This study conducted a cross-sectional survey of four hospitals designated to treat patients with COVID-19 in China. Based on the emergency capacity system of medical staff for infectious diseases, an improved Emergency Preparedness Information Questionnaire was used to evaluate the emergency capacity of medical staff. Linear regression and one-way analysis of variance were used to test the differences in the emergency capacity of medical staff. Spearman correlation analysis was used to study the correlation between the self-efficacy and emergency capacity of medical staff. Results: The overall emergency capacity of the surveyed medical staff was at a medium level. There was a correlation between emergency capacity and age, working years, position, educational background and the area where medical staff worked. Emergency capacity was not related to the hospital grade. Emergency capacity was significantly related to whether medical staff had participated in frontline pandemic prevention work. There was also a positive correlation between emergency capacity and the self-efficacy of medical staff. Conclusions: The results highlight the importance of the training mechanism for emergency personnel. The emergency input for public health emergencies should be increased to improve the emergency capacity of medical staff. In addition, it is necessary to pay attention to the mental health of medical staff.

Mechanism of duplex unwinding by coronavirus nsp13 helicases (preprint)

The current COVID-19 pandemic urges in-depth investigation into proteins encoded with coronavirus (CoV), especially conserved CoV replicases. The nsp13 of highly pathogenic MERS-CoV, SARS-CoV-2, and SARS-CoV exhibit the most conserved CoV replicases. Using single-molecule FRET, we observed that MERS-CoV nsp13 unwound DNA in discrete steps of approximately 9 bp when ATP was used. If another NTP was used, then the steps were only 4 to 5 bp. In dwell time analysis, we detected 3 or 4 hidden steps in each unwinding process, which indicated the hydrolysis of 3 or 4 dTTP. Based on crystallographic and biochemical studies of CoV nsp13 helicases, we modeled an unwinding mechanism similar to the spring-loaded mechanism of HCV NS3 helicase, although our model proposes that flexible 1B and stalk domains, by allowing a lag greater than 4 bp during unwinding, cause the accumulated tension on the nsp13-DNA complex. The hinge region between two RecA-like domains in SARS-CoV-2 nsp13 is intrinsically more flexible than in MERS-CoV nsp13 due to the difference of a single amino acid, which causes the former to induce significantly greater NTP hydrolysis. Our findings thus establish a blueprint for determining the unwinding mechanism of a unique helicase family. O_LIWhen dTTP was used as the energy source, 4 hidden steps in each individual unwinding step after 3 - 4 NTP hydrolysis were observed. C_LIO_LIAn unwinding model of MERS-CoV-nsp13 which is similar to the spring-loaded mechanism of HCV NS3 helicase, except the accumulation of tension on nsp13/DNA complex is caused by the flexible 1B and stalk domains that allow a lag of 4-bp in unwinding. C_LIO_LIComparing to MERS-CoV nsp13, the hinge region between two RecA-like domains in SARS-CoV-2 nsp13 is intrinsically more flexible due to a single amino acid difference, which contributes to the significantly higher NTP hydrolysis by SARS-CoV-2 nsp13. C_LI

A Novel Amplification-free SARS-CoV-2 Point-of-care Nucleic Acid Detection System based on Hybrid Capture Fluorescence Immunoassay (preprint)

Herein we presented a novel, rapid and amplification-free SARS-CoV-2 nucleic acid detection system based on hybrid capture fluorescence immunoassay (HC-FIA) technology. The usage of the monoclonal antibody S9.6 in recognizing DNA-RNA double-stranded hybrids enabled the conversion of nucleic acid testing into immunofluorescence carrying on a simple lateral flow dipstick. The established HC-FIA also exhibited satisfactory sensitivity, specificity and great robustness. The clinical evaluation of HC-FIA kit and fluorescence reading device are further processed in three hospitals independently. The results of 734 samples from 670 subjects indicated high consistency between our HC-FIA and quantitative polymerase chain reaction based commercially available kit or clinical diagnosis according to Kappa statistics. Altogether, HC-FIA related method and commercial test kit show unparalleled advantages as time saving, amplification-free, high throughput and portable POCT molecular diagnosis, which facilitates its application as on-site Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acid detection in epidemic prevention and control worldwide, especially during the outbreak.

Observing Responses to the COVID-19 Pandemic using Worldwide Network Cameras (preprint)

COVID-19 has resulted in a worldwide pandemic, leading to "lockdown" policies and social distancing. The pandemic has profoundly changed the world. Traditional methods for observing these historical events are difficult because sending reporters to areas with many infected people can put the reporters' lives in danger. New technologies are needed for safely observing responses to these policies. This paper reports using thousands of network cameras deployed worldwide for the purpose of witnessing activities in response to the policies. The network cameras can continuously provide real-time visual data (image and video) without human efforts. Thus, network cameras can be utilized to observe activities without risking the lives of reporters. This paper describes a project that uses network cameras to observe responses to governments' policies during the COVID-19 pandemic (March to April in 2020). The project discovers over 30,000 network cameras deployed in 110 countries. A set of computer tools are created to collect visual data from network cameras continuously during the pandemic. This paper describes the methods to discover network cameras on the Internet, the methods to collect and manage data, and preliminary results of data analysis. This project can be the foundation for observing the possible "second wave" in fall 2020. The data may be used for post-pandemic analysis by sociologists, public health experts, and meteorologists.

The relationship of COVID-19 severity with cardiovascular disease and its traditional risk factors: A systematic review and meta-analysis (preprint)

Background: Whether cardiovascular disease (CVD) and its traditional risk factors predict severe coronavirus disease 2019 (COVID-19) is uncertain, in part, because of potential confounding by age and sex. Methods: We performed a systematic review of studies that explored pre-existing CVD and its traditional risk factors as risk factors of severe COVID-19 (defined as death, acute respiratory distress syndrome, mechanical ventilation, or intensive care unit admission). We searched PubMed and Embase for papers in English with original data ([≥]10 cases of severe COVID-19). Using random-effects models, we pooled relative risk (RR) estimates and conducted meta-regression analyses. Results: Of the 661 publications identified in our search, 25 papers met our inclusion criteria, with 76,638 COVID-19 patients including 11,766 severe cases. Older age was consistently associated with severe COVID-19 in all eight eligible studies, with RR >~5 in >60-65 vs. <50 years. Three studies showed no change in the RR of age after adjusting for covariate(s). In univariate analyses, factors robustly associated with severe COVID-19 were male sex (10 studies; pooled RR=1.73, [95%CI 1.50-2.01]), hypertension (8 studies; 2.87 [2.09-3.93]), diabetes (9 studies; 3.20 [2.26-4.53]), and CVD (10 studies; 4.97 [3.76-6.58]). RR for male sex was likely to be independent of age. For the other three factors, meta-regression analyses suggested confounding by age. Only four studies reported multivariable analysis, but most of them showed adjusted RR ~2 for hypertension, diabetes, and CVD. No study explored renin-angiotensin system inhibitors as a risk factor for severe COVID-19. Conclusions: Despite the potential for confounding, these results suggest that hypertension, diabetes, and CVD are independently associated with severe COVID-19 and, together with age and male sex, can be used to inform objective decisions on COVID-19 testing, clinical management, and workforce planning.

Early CT manifestations and short-term evolution of coronavirus disease-2019 (preprint)

Objectives: This study explored the features of coronavirus disease-2019 (COVID-19) with the aim of improving clinical diagnosis.Methods: We retrospectively analyzed the clinical and CT data of 85 patients with COVID-19 who were diagnosed between January 20, 2020 and February 20, 2020. The imaging findings, clinical and laboratory data were evaluated.Results: Of the 85 patients, five had mild symptoms, 60 had moderate symptoms, and 20 had severe symptoms. Sixty-nine patients had direct or indirect contact history, while 16 patients (19%) had no obvious epidemiological history. Eighty-five patients had prominent respiratory symptoms, while 70 patients (82%) had moderate to low fever. There were no obvious lung abnormalities in CT images of patients with mild symptoms. Common chest CT manifestations in patients with moderate or severe symptoms were ground glass opacity (GGO) (16%); GGO combined with grid (39%) or consolidation (32%); and air bronchogram sign (13%). In these patients, lesions were mostly distributed in the lower lobes of the lungs, and most were located in the periphery; pleural effusion was rare. Within 3 days after onset, GGO (23%) and GGO combined with grid (45%) were the most common manifestations in CT images; GGO combined with grid (35%) and/or consolidation (41%) were the main manifestations in CT images at 5–10 days after onset.Conclusions: Common CT manifestations of COVID-19 were GGO alone and GGO combined with grid and/or consolidation. Short-term increases in ranges of lesions or consolidation areas may indicate disease aggravation.

Distribution of the COVID-19 epidemic and correlation with population emigration from Wuhan, China.

BACKGROUND: The ongoing new coronavirus pneumonia (Corona Virus Disease 2019, COVID-19) outbreak is spreading in China, but it has not yet reached its peak. Five million people emigrated from Wuhan before lockdown, potentially representing a source of virus infection. Determining case distribution and its correlation with population emigration from Wuhan in the early stage of the epidemic is of great importance for early warning and for the prevention of future outbreaks. METHODS: The official case report on the COVID-19 epidemic was collected as of January 30, 2020. Time and location information on COVID-19 cases was extracted and analyzed using ArcGIS and WinBUGS software. Data on population migration from Wuhan city and Hubei province were extracted from Baidu Qianxi, and their correlation with the number of cases was analyzed. RESULTS: The COVID-19 confirmed and death cases in Hubei province accounted for 59.91% (5806/9692) and 95.77% (204/213) of the total cases in China, respectively. Hot spot provinces included Sichuan and Yunnan, which are adjacent to Hubei. The time risk of Hubei province on the following day was 1.960 times that on the previous day. The number of cases in some cities was relatively low, but the time risk appeared to be continuously rising. The correlation coefficient between the provincial number of cases and emigration from Wuhan was up to 0.943. The lockdown of 17 cities in Hubei province and the implementation of nationwide control measures efficiently prevented an exponential growth in the number of cases. CONCLUSIONS: The population that emigrated from Wuhan was the main infection source in other cities and provinces. Some cities with a low number of cases showed a rapid increase in case load. Owing to the upcoming Spring Festival return wave, understanding the risk trends in different regions is crucial to ensure preparedness at both the individual and organization levels and to prevent new outbreaks.

Deep learning-based model for detecting 2019 novel coronavirus pneumonia on high-resolution computed tomography: a prospective study in 27 patients (preprint)

Background: Computed tomography (CT) is the preferred imaging method for diagnosing 2019 novel coronavirus (COVID19) pneumonia. Our research aimed to construct a system based on deep learning for detecting COVID-19 pneumonia on high resolution CT, relieve working pressure of radiologists and contribute to the control of the epidemic. Methods: For model development and validation, 46,096 anonymous images from 106 admitted patients, including 51 patients of laboratory confirmed COVID-19 pneumonia and 55 control patients of other diseases in Renmin Hospital of Wuhan University (Wuhan, Hubei province, China) were retrospectively collected and processed. Twenty-seven consecutive patients undergoing CT scans in Feb, 5, 2020 in Renmin Hospital of Wuhan University were prospectively collected to evaluate and compare the efficiency of radiologists against 2019-CoV pneumonia with that of the model. Findings: The model achieved a per-patient sensitivity of 100%, specificity of 93.55%, accuracy of 95.24%, PPV of 84.62%, and NPV of 100%; a per-image sensitivity of 94.34%, specificity of 99.16%, accuracy of 98.85%, PPV of 88.37%, and NPV of 99.61% in retrospective dataset. For 27 prospective patients, the model achieved a comparable performance to that of expert radiologist. With the assistance of the model, the reading time of radiologists was greatly decreased by 65%. Conclusion: The deep learning model showed a comparable performance with expert radiologist, and greatly improve the efficiency of radiologists in clinical practice. It holds great potential to relieve the pressure of frontline radiologists, improve early diagnosis, isolation and treatment, and thus contribute to the control of the epidemic.