The origin and evolution of emerged swine acute diarrhea syndrome coronavirus with zoonotic potential.

Swine acute diarrhea syndrome coronavirus (SADS-CoV) is a newly discovered alphacoronavirus with zoonotic potential that causes diarrhea and vomiting mainly in piglets. Having emerged suddenly in 2017, the prevailing opinion is that the virus originated from HKU2, an alphacoronavirus whose primary host is bats, and at some unknown point achieved interspecies transmission via some intermediate. Here, we further explore the evolutionary history and possible cross-species transmission event for SADS-CoV. Coevolutionary analysis demonstrated that HKU2 may have achieved host switch via SADS-related (SADSr)-CoV, which was isolated from the genus Rhinolophus in 2017. SADS-CoV, HKU2, and SADSr-CoV share similar codon usage patterns and showed a lower tendency to use CpG, which may reflect a method of immune escape. The analyses of virus-host coevolution and recombination support SADSr-CoV is the direct source of SADS-CoV that may have undergone recombination events during its formation. Structure-based spike glycoprotein variance analysis revealed a more nuanced evolutionary pathway to receptor recognition for host switch. We did not find a possible positive selection site, and the dN/dS of the S gene was only 0.29, which indicates that the current SADS-CoV is slowly evolving. These results provide new insights that may help predict future cross-species transmission, and possibly surveil future zoonotic outbreaks and associated public health emergencies.

Effects of COVID-19 home quarantine on pregnancy outcomes of patients with gestational diabetes mellitus: a retrospective cohort study.

OBJECTIVE: This study aimed to evaluate the effects of the home quarantine on pregnancy outcomes of gestational diabetes mellitus (GDM) patients during the COVID-19 outbreak. METHODS: The complete electronic medical records of patients with GDM with home quarantine history were collected and classified into the home quarantine group from 24 February 2020 to 24 November 2020. The same period of patients with GDM without home quarantine history were included in the control group from 2018 to 2019. The pregnant outcomes of the home quarantine and control groups were systematically compared, such as neonatal weight, head circumference, body length, one-minute Apgar score, fetal macrosomia, and pre-term delivery. RESULTS: A total of 1358 patients with GDM were included in the analysis, including 484 in 2018, 468 in 2019, and 406 in 2020. Patients with GDM with home quarantine in 2020 had higher glycemic levels and adverse pregnancy outcomes than in 2018 and 2019, including higher cesarean section rates, lower Apgar scores, and higher incidence of macrosomia and umbilical cord around the neck. More importantly, the second trimester of home quarantine had brought a broader impact on pregnant women and fetuses. CONCLUSION: Home quarantine has aggravated the condition of GDM pregnant women and brought more adverse pregnancy outcomes during the COVID-19 outbreak. Therefore, we suggested governments and hospitals strengthen lifestyle guidance, glucose management, and antenatal care for patients with GDM with home quarantine during public health emergencies.

Micronutrient perspective on COVID-19: Umbrella review and reanalysis of meta-analyses.

INTRODUCTION: Micronutrients are clinically important in managing COVID-19, and numerous studies have been conducted, but inconsistent findings exist. OBJECTIVE: To explore the association between micronutrients and COVID-19. METHODS: PubMed, Web of Science, Embase, Cochrane Library and Scopus for study search on July 30, 2022 and October 15, 2022. Literature selection, data extraction and quality assessment were performed in a double-blinded, group discussion format. Meta-analysis with overlapping associations were reconsolidated using random effects models, and narrative evidence was performed in tabular presentations. RESULTS: 57 reviews and 57 latest original studies were included. 21 reviews and 53 original studies were of moderate to high quality. Vitamin D, vitamin B, zinc, selenium, and ferritin levels differed between patients and healthy people. Vitamin D and zinc deficiencies increased COVID-19 infection by 0.97-fold/0.39-fold and 1.53-fold. Vitamin D deficiency increased severity 0.86-fold, while low vitamin B and selenium levels reduced severity. Vitamin D and calcium deficiencies increased ICU admission by 1.09 and 4.09-fold. Vitamin D deficiency increased mechanical ventilation by 0.4-fold. Vitamin D, zinc, and calcium deficiencies increased COVID-19 mortality by 0.53-fold, 0.46-fold, and 5.99-fold, respectively. CONCLUSION: The associations between vitamin D, zinc, and calcium deficiencies and adverse evolution of COVID-19 were positive, while the association between vitamin C and COVID-19 was insignificant.REGISTRATION: PROSPERO CRD42022353953.

Use of traditional Chinese medicine for the treatment and prevention of COVID-19 and rehabilitation of COVID-19 patients: An evidence mapping study.

Background: The potential effectiveness of traditional Chinese medicine (TCM) against "epidemic diseases" has highlighted the knowledge gaps associated with TCM in COVID-19 management. This study aimed to map the matrix for rigorously assessing, organizing, and presenting evidence relevant to TCM in COVID-19 management. Methods: In this study, we used the methodology of evidence mapping (EM). Nine electronic databases, the WHO International Clinical Trials Registry Platform (ICTRP) Search Portal, ClinicalTrials.gov, gray literature, reference lists of articles, and relevant Chinese conference proceedings, were searched for articles published until 23 March 2022. The EndNote X9, Rayyan, EPPI, and R software were used for data entry and management. Results: In all, 126 studies, including 76 randomized controlled trials (RCTs) and 50 systematic reviews (SRs), met our inclusion criteria. Of these, only nine studies (7.14%) were designated as high quality: four RCTs were assessed as "low risk of bias" and five SRs as "high quality." Based on the research objectives of these studies, the included studies were classified into treatment (53 RCTs and 50 SRs, 81.75%), rehabilitation (20 RCTs, 15.87%), and prevention (3 RCTs, 2.38%) groups. A total of 76 RCTs included 59 intervention categories and 57 efficacy outcomes. All relevant trials consistently demonstrated that TCM significantly improved 22 outcomes (i.e., consistent positive outcomes) without significantly affecting four (i.e., consistent negative outcomes). Further, 50 SRs included nine intervention categories and 27 efficacy outcomes, two of which reported consistent positive outcomes and two reported consistent negative outcomes. Moreover, 45 RCTs and 38 SRs investigated adverse events; 39 RCTs and 30 SRs showed no serious adverse events or significant differences between groups. Conclusion: This study provides evidence matrix mapping of TCM against COVID-19, demonstrating the potential efficacy and safety of TCM in the treatment and prevention of COVID-19 and rehabilitation of COVID-19 patients, and also addresses evidence gaps. Given the limited number and poor quality of available studies and potential concerns regarding the applicability of the current clinical evaluation standards to TCM, the effect of specific interventions on individual outcomes needs further evaluation.

Use of traditional Chinese medicine for the treatment and prevention of COVID-19 and rehabilitation of COVID-19 patients: An evidence mapping study

Background: The potential effectiveness of traditional Chinese medicine (TCM) against "epidemic diseases” has highlighted the knowledge gaps associated with TCM in COVID-19 management. This study aimed to map the matrix for rigorously assessing, organizing, and presenting evidence relevant to TCM in COVID-19 management. Methods: In this study, we used the methodology of evidence mapping (EM). Nine electronic databases, the WHO International Clinical Trials Registry Platform (ICTRP) Search Portal, ClinicalTrials.gov, gray literature, reference lists of articles, and relevant Chinese conference proceedings, were searched for articles published until 23 March 2022. The EndNote X9, Rayyan, EPPI, and R software were used for data entry and management. Results: In all, 126 studies, including 76 randomized controlled trials (RCTs) and 50 systematic reviews (SRs), met our inclusion criteria. Of these, only nine studies (7.14%) were designated as high quality: four RCTs were assessed as "low risk of bias” and five SRs as "high quality.” Based on the research objectives of these studies, the included studies were classified into treatment (53 RCTs and 50 SRs, 81.75%), rehabilitation (20 RCTs, 15.87%), and prevention (3 RCTs, 2.38%) groups. A total of 76 RCTs included 59 intervention categories and 57 efficacy outcomes. All relevant trials consistently demonstrated that TCM significantly improved 22 outcomes (i.e., consistent positive outcomes) without significantly affecting four (i.e., consistent negative outcomes). Further, 50 SRs included nine intervention categories and 27 efficacy outcomes, two of which reported consistent positive outcomes and two reported consistent negative outcomes. Moreover, 45 RCTs and 38 SRs investigated adverse events;39 RCTs and 30 SRs showed no serious adverse events or significant differences between groups. Conclusion: This study provides evidence matrix mapping of TCM against COVID-19, demonstrating the potential efficacy and safety of TCM in the treatment and prevention of COVID-19 and rehabilitation of COVID-19 patients, and also addresses evidence gaps. Given the limited number and poor quality of available studies and potential concerns regarding the applicability of the current clinical evaluation standards to TCM, the effect of specific interventions on individual outcomes needs further evaluation.

Individual bat viromes reveal the co-infection, spillover and emergence risk of potential zoonotic viruses (preprint)

Bats are reservoir hosts for many zoonotic viruses. Despite this, relatively little is known about the diversity and abundance of viruses within bats at the level of individual animals, and hence the frequency of virus co-infection and inter-species transmission. Using an unbiased meta-transcriptomics approach we characterised the mammalian associated viruses present in 149 individual bats sampled from Yunnan province, China. This revealed a high frequency of virus co-infection and species spillover among the animals studied, with 12 viruses shared among different bat species, which in turn facilitates virus recombination and reassortment. Of note, we identified five viral species that are likely to be pathogenic to humans or livestock, including a novel recombinant SARS-like coronavirus that is closely related to both SARS-CoV-2 and SARS-CoV, with only five amino acid differences between its receptor-binding domain sequence and that of the earliest sequences of SARS-CoV-2. Functional analysis predicts that this recombinant coronavirus can utilize the human ACE2 receptor such that it is likely to be of high zoonotic risk. Our study highlights the common occurrence of inter-species transmission and co-infection of bat viruses, as well as their implications for virus emergence.

Clinical characteristics and factors influencing development of a pulmonary fungal infection in patients with severe respiratory diseases

Objectives: To examine the clinical characteristics, drug resistance, and factors influencing development of a pulmonary fungal infection in patients with severe respiratory diseases in order to provide a reference for clinical treatment.

Home Quarantine: A Double-Edged Sword During COVID-19 Pandemic for Hypertensive Disorders of Pregnancy and the Related Complications.

Object: COVID-19 pandemic and worldwide quarantine seriously affected the physical and mental health of the general public. Our study aimed to investigate the effects of the COVID-19 quarantine on pregnancy outcomes among pregnant women with hypertensive disorders of pregnancy (HDP). Methods: This single-center retrospective cohort study collected complete clinical data of HDP patients with a history of home quarantine in The First Affiliated Hospital of Chongqing Medical University (Chongqing, China) in 2020 as well as the patients without home quarantine in 2018 and 2019. Then, the maternal and neonatal outcomes of two subtypes of HDP, gestational hypertension (GH) and preeclampsia/eclampsia (PE/E), were analyzed over the three years. Results: The incidence of HDP increased from 0.84% in 2018 and 0.51% in 2019 to 2.30% in 2020. The data suggested that home quarantine was associated with higher gestational weight gain, obesity rates, blood pressure, and uric acid among the patients with HDP in 2020. Furthermore, HDP patients with a history of home quarantine may have worse neonatal outcomes, including lower newborn weight, shorter body length, lower Apgar score, and higher risk of fetal growth restriction. Conclusion: Our results suggested that COVID-19 quarantine may be a risk factor for poor pregnancy outcomes in HDP patients. Lifestyle guidance and antenatal care may be necessary for HDP patients with home quarantine in an epidemic outbreak.

Early prediction of noninvasive ventilation failure after extubation: development and validation of a machine-learning model.

BACKGROUND: Noninvasive ventilation (NIV) has been widely used in critically ill patients after extubation. However, NIV failure is associated with poor outcomes. This study aimed to determine early predictors of NIV failure and to construct an accurate machine-learning model to identify patients at risks of NIV failure after extubation in intensive care units (ICUs). METHODS: Patients who underwent NIV after extubation in the eICU Collaborative Research Database (eICU-CRD) were included. NIV failure was defined as need for invasive ventilatory support (reintubation or tracheotomy) or death after NIV initiation. A total of 93 clinical and laboratory variables were assessed, and the recursive feature elimination algorithm was used to select key features. Hyperparameter optimization was conducted with an automated machine-learning toolkit called Neural Network Intelligence. A machine-learning model called Categorical Boosting (CatBoost) was developed and compared with nine other models. The model was then prospectively validated among patients enrolled in the Cardiac Surgical ICU of Zhongshan Hospital, Fudan University. RESULTS: Of 929 patients included in the eICU-CRD cohort, 248 (26.7%) had NIV failure. The time from extubation to NIV, age, Glasgow Coma Scale (GCS) score, heart rate, respiratory rate, mean blood pressure (MBP), saturation of pulse oxygen (SpO2), temperature, glucose, pH, pressure of oxygen in blood (PaO2), urine output, input volume, ventilation duration, and mean airway pressure were selected. After hyperparameter optimization, our model showed the greatest accuracy in predicting NIV failure (AUROC: 0.872 [95% CI 0.82-0.92]) among all predictive methods in an internal validation. In the prospective validation cohort, our model was also superior (AUROC: 0.846 [95% CI 0.80-0.89]). The sensitivity and specificity in the prediction group is 89% and 75%, while in the validation group they are 90% and 70%. MV duration and respiratory rate were the most important features. Additionally, we developed a web-based tool to help clinicians use our model. CONCLUSIONS: This study developed and prospectively validated the CatBoost model, which can be used to identify patients who are at risk of NIV failure. Thus, those patients might benefit from early triage and more intensive monitoring. TRIAL REGISTRATION: NCT03704324. Registered 1 September 2018, https://register. CLINICALTRIALS: gov .

Applying Machine Learning with Localized Surface Plasmon Resonance Sensors to Detect SARS-CoV-2 Particles.

The sudden outbreak of COVID-19 rapidly developed into a global pandemic, which caused tens of millions of infections and millions of deaths. Although SARS-CoV-2 is known to cause COVID-19, effective approaches to detect SARS-CoV-2 using a convenient, rapid, accurate, and low-cost method are lacking. To date, most of the diagnostic methods for patients with early infections are limited to the detection of viral nucleic acids via polymerase chain reaction (PCR), or antigens, using an enzyme-linked immunosorbent assay or a chemiluminescence immunoassay. This study developed a novel method that uses localized surface plasmon resonance (LSPR) sensors, optical imaging, and artificial intelligence methods to directly detect the SARS-CoV-2 virus particles without any sample preparation. The virus concentration can be qualitatively and quantitatively detected in the range of 125.28 to 106 vp/mL through a few steps within 12 min with a limit of detection (LOD) of 100 vp/mL. The accuracy of the SARS-CoV-2 positive or negative assessment was found to be greater than 97%, and this was demonstrated by establishing a regression machine learning model for the virus concentration prediction (R2 > 0.95).

COVID-19 Quarantine is a Risk Factor for Poor Pregnancy Outcomes in GDM Patients: A Retrospective Study (preprint)

Aims: : T his study was to evaluate the effects of the home quarantine on pregnancy outcomes of gestational diabetes mellitus (GDM) patients during the COVID-19 outbreak. Methods: : Thecomplete electronic medical records of GDM patients with home quarantine history were collected and classified into the home quarantine group from 24 February 2020 to 24 November 2020. The same period of GDM patients without home quarantine historywas included in the control group from 2018 and 2019. Results: : A total of 1358 GDM patients were included in the analysis, including 484 in 2018, 468 in 2019, and 406 in 2020. GDM patients with home quarantine in 2020 had higher glycemic levels and worse pregnancy outcomes than 2018 and 2019, including higher cesarean section rate,lower Apgar scores, and higher incidence of macrosomia and nuchal cord. More importantly, the second trimester of home quarantine had brought a broader impactto pregnant women and fetuses. Conclusion: Home quarantine has aggravated the condition of GDM pregnant women and brought more adverse pregnancy outcomes during the COVID-19 outbreak. Therefore, we suggested that governments and hospitals should strengthen lifestyle guidance, glucose management, and antenatal care for GDM patients with home quarantine during public health emergencies.

Therapeutic Effect of Macrophage-Derived Biomimetic Nanoparticles for Cytokine Release Syndrome (preprint)

Cytokine release syndrome (CRS) is a severe complication of infectious diseases such as coronavirus disease 2019 (COVID-19) that cause serious damage to public health. Currently, no effective therapeutic strategy exists for CRS treatment in clinic, and supportive therapy is still the main method. Here, we show the potential of macrophage membrane-biomimetic nanoparticles for CRS treatment. By fusing macrophage membrane on the surface of the PLGA skeleton, we constructed biomimetic nanoparticles that inherited the membrane receptors from the "parental" macrophages, enabling the neutralization of CRS-related cytokines. We compared three types of macrophage membranes to screen out more effective biomimetic nanoparticles for CRS treatment. Our results show that biomimetic nanoparticles containing M0 macrophage membrane can decrease the levels of pro-inflammatory cytokines involved in CRS to the greatest extent. In a mouse model of RNA virus analog-induced CRS, the macrophage membrane-biomimetic nanoparticles manifested significant therapeutic efficacy by reducing cytokine levels and alleviating organ damage.Funding Information: This work was supported by Scientific Research Project of Tongji University (22120200021), the National Natural Science Foundation of China (82073385 and 81803078), Shanghai Science and Technology Committee (20DZ2255200 and 21140901900).Declaration of Interests: The authors declare no conflict of interest.Ethics Approval Statement: All animal studies were approved under the guidelines of Tongji University Institutional Animal Care and Use Committee.

Reporting and methodological quality of COVID-19 systematic reviews needs to be improved: an evidence mapping.

OBJECTIVES: To assess the reporting and methodological quality of COVID-19 systematic reviews, and to analyze trends and gaps in the quality, clinical topics, author countries, and populations of the reviews using an evidence mapping approach. STUDY DESIGN AND SETTING: A structured search for systematic reviews concerning COVID-19 was performed using PubMed, Embase, Cochrane Library, Campbell Library, Web of Science, CBM, WanFang Data, CNKI, and CQVIP from inception until June 2020. The quality of each review was assessed using the Assessment of Multiple Systematic Reviews 2 (AMSTAR 2) checklist and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. RESULTS: In total, 243 systematic reviews met the inclusion criteria, over 50% of which (128, 52.7%) were from 14 developing countries, with China contributing the most reviews (76, 31.3%). In terms of methodological quality of the studies, 30 (12.3%) were of moderate quality, 63 (25.9%) were of low quality, and 150 (61.7%) were of critically low quality. In terms of reporting quality, the median (interquartile range) PRISMA score was 14 (10-18). Regarding the topics of the reviews, 24 (9.9%) focused on the prevalence of COVID-19, 69 (28.4%) focused on the clinical manifestations, 30 (12.3%) focused on etiology, 43 (17.7%) focused on diagnosis, 65 (26.7%) focused on treatment, 104 (42.8%) focused on prognosis, and 25 (10.3%) focused on prevention. These studies mainly focused on general patients with COVID-19 (161, 66.3%), followed by children (22, 9.1%) and pregnant patients (18, 7.4%). CONCLUSION: This study systematically evaluated the methodological and reporting quality of systematic reviews of COVID-19, summarizing and analyzing trends in their clinical topics, author countries, and study populations.

Molecular epidemiology analysis of early variants of SARS-CoV-2 reveals the potential impact of mutations P504L and Y541C (NSP13) in the clinical COVID-19 outcomes.

Since severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused global pandemic with alarming speed, comprehensively analyzing the mutation and evolution of early SARS-CoV-2 strains contributes to detect and prevent such virus. Here, we explored 1962 high-quality genomes of early SARS-CoV-2 strains obtained from 42 countries before April 2020. The changing trends of genetic variations in SARS-CoV-2 strains over time and country were subsequently identified. In addition, viral genotype mapping and phylogenetic analysis were performed to identify the variation features of SARS-CoV-2. Results showed that 57.89% of genetic variations involved in ORF1ab, most of which (68.85%) were nonsynonymous. Haplotype maps and phylogenetic tree analysis showed that amino acid variations in ORF1ab (p.5828P > L and p.5865Y > C, also NSP13: P504L and NSP13: Y541C) were the important characteristics of such clade. Furthermore, these variants showed more significant aggregation in the United States (P = 2.92E-66, 95%) than in Australia or Canada, especially in strains from Washington State (P = 1.56E-23, 77.65%). Further analysis demonstrated that the report date of the variants was associated with the date of increased infections and the date of recovery and fatality rate change in the United States. More importantly, the fatality rate in Washington State was higher (4.13%) and showed poorer outcomes (P = 4.12E-21 in fatality rate, P = 3.64E-29 in death and recovered cases) than found in other states containing a small proportion of strains with such variants. Using sequence alignment, we found that variations at the 504 and 541 sites had functional effects on NSP13. In this study, we comprehensively analyzed genetic variations in SARS-CoV-2, gaining insights into amino acid variations in ORF1ab and COVID-19 outcomes.

An in-depth investigation of the safety and immunogenicity of an inactivated SARS-CoV-2 vaccine (preprint)

BACKGROUND In-depth investigations of the safety and immunogenicity of inactivated SARS-CoV-2 vaccines are needed. METHOD In a phase I randomized, double-blinded, and placebo-controlled trial involving 192 healthy adults 18-59 years of age, two injections of three different doses (50 EU, 100 EU and 150 EU) of an inactivated SARS-CoV-2 vaccine or the placebo were administered intramuscularly with a 2- or 4-week interval between the injections. The safety and immunogenicity of the vaccine were evaluated within 28 days. FINDING In this study, 191 subjects assigned to three doses groups or the placebo group completed the 28-day trial. There were 44 adverse reactions within the 28 days, most commonly mild pain and redness at the injection site or slight fatigue, and no abnormal variations were observed in 48 cytokines in the serum samples of immunized subjects. The serum samples diluted from 1:32 to 1:4096 and incubated with the virus did not show antibody-dependent enhancement effects (ADEs) with regard to human natural killer cells, macrophages or dendritic cells. At day 14, the seroconversion rates had reached 92%, 100% and 96% with geometric mean titers (GMTs) of 18.0, 54.5 and 37.1, and at day 28, the seroconversion rates had reached 80%, 96% and 92% with GMTs of 10.6, 15.4 and 19.6in 0, 14 and 0, 28 procedures, respectively. Seroconversion was associated with the synchronous upregulation of ELISA antibodies against the S protein, N protein and virion and a cytotoxic T lymphocyte (CTL) response. Transcriptome analysis shaped the genetic diversity of immune response induced by the vaccine. INTERPRETATION In a population aged 18-59 years, this inactivated SARS-CoV-2 vaccine was safe and immunogenic.

[Analysis on formula of Mongolian medicine for prevention of COVID-19].

The epidemic situation of coronavirus disease 2019(COVID-19) is developing rapidly in the world, and the influence is serious. In this study, the prescription of Mongolian medicine to prevent new type of COVID-19 was investigated. Based on the second edition and the third edition of COVID-19 Mongolian Medicine Prevention and Treatment Guidance Program issued by the Inner Mongolia Autonomous Region Health Commission, using Excel 2007, SPSS Modeler 18, SPSS Statistics 25, Cytoscape 3.7.1 statistical software as a tool, the association rules analysis and cluster analysis of Mongolian medicine included in the standard were carried out. Among the 45 prophylactic prescriptions included in the standard, a total of 34 high-frequency drugs using frequency ≥5 were used, of which Carthami Flos(21 times, 4.46%), Chebulae Fructus(20 times, 4.26%), Moschus(13 times, 2.77%), Myristicae Semen(12 times, 2.55%), Santali Albi Lignum(12 times, 2.55%), and Bovis Calculus(12 times, 2.55%) were the most common. The main drugs for the prevention of COVID-19 were Liang(13 times, 38.23%), Wen(9 times, 26.47%), the flavor was Ku(20 times, 34.48%), Xin(13 times, 22.41%), Gan(11 times, 18.97%), the most used drugs treating hot evil(99 times, 32.46%), treatment of "Heyi" drugs(51 times, 16.72%), treatment of "Badagan" drugs(40 times, 13.11%), treatment of "sticky" drugs(37 times, 12.13%), and a cough, eliminating phlegm and antiasthmatic(31 times, 10.16%), the association rule analysis found that the highest association intensity of the drug pair combination of 11. Clustering analysis using the cluster analysis of inter-group join method found a total of 8 categories. In this study, 45 prescriptions of Mongolian medicine for the prevention of COVID-19 were collec-ted and further analyzed, hoping to provide new ideas for clinical diagnosis and treatment.

Amino acid variation analysis of surface spike glycoprotein at 614 in SARS-CoV-2 strains.

As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to disperse globally with worrisome speed, identifying amino acid variations in the virus could help to understand the characteristics of it. Here, we studied 489 SARS-CoV-2 genomes obtained from 32 countries from the Nextstrain database and performed phylogenetic tree analysis by clade, country, and genotype of the surface spike glycoprotein (S protein) at site 614. We found that virus strains from mainland China were mostly distributed in Clade B and Clade undefined in the phylogenetic tree, with very few found in Clade A. In contrast, Clades A2 (one case) and A2a (112 cases) predominantly contained strains from European regions. Moreover, Clades A2 and A2a differed significantly from those of mainland China in age of infected population (P = 0.0071, mean age 40.24 to 46.66), although such differences did not exist between the US and mainland China. Further analysis demonstrated that the variation of the S protein at site 614 (QHD43416.1: p.614D>G) was a characteristic of stains in Clades A2 and A2a. Importantly, this variation was predicted to have neutral or benign effects on the function of the S protein. In addition, global quality estimates and 3D protein structures tended to be different between the two S proteins. In summary, we identified different genomic epidemiology among SARS-CoV-2 strains in different clades, especially in an amino acid variation of the S protein at 614, revealing potential viral genome divergence in SARS-CoV-2 strains.

Sex-specific clinical characteristics and prognosis of coronavirus disease-19 infection in Wuhan, China: A retrospective study of 168 severe patients.

To confirm the relationship between sex and the progression of Coronavirus Disease-19 (COVID-19), and its potential mechanism, among severe patients. For this retrospective study, we included 168 consecutive severe patients with pathogen-confirmed COVID-19 who were hospitalized between January 16th and February 4th, 2020, at Tongji Hospital in Wuhan, China. Clinical characteristics, laboratory parameters, and outcomes were compared and analyzed between males and females. In the present study, we analyzed 168 severe patients with COVID-19, including 86 males and 82 females, and 48 patients (28.6%) were diagnosed as critically ill. Of 86 male patients, 12.8% (11/86) died and 75.6% (65/86) were discharged; of 82 female patients, 7.3% (6/82) died and 86.6% (71/82) were discharged. Eleven laboratory parameters showed significant differences between male and female patients, and six of them were higher during the whole clinical course in patients who died than in patients who were discharged. In adjusted logistic regression analysis, males with comorbidities presented a higher risk of being critically ill than males without comorbidities (OR = 3.824, 95% CI = 1.279-11.435). However, this association attenuated to null in female patients (OR = 2.992, 95% CI = 0.937-9.558). A similar sex-specific trend was observed in the relation between age and critically ill conditions. We highlighted sex-specific differences in clinical characteristics and prognosis. Male patients appeared to be more susceptible to age and comorbidities. Sex is an important biological variable that should be considered in the prevention and treatment of COVID-19.