Continuous evolution and emerging lineage of seasonal human coronaviruses: A multicenter surveillance study.

The seasonal human coronaviruses (HCoVs) have zoonotic origins, repeated infections, and global transmission. The objectives of this study are to elaborate the epidemiological and evolutionary characteristics of HCoVs from patients with acute respiratory illness. We conducted a multicenter surveillance at 36 sentinel hospitals of Beijing Metropolis, China, during 2016-2019. Patients with influenza-like illness (ILI) and severe acute respiratory infection (SARI) were included, and submitted respiratory samples for screening HCoVs by multiplex real-time reverse transcription-polymerase chain reaction assays. All the positive samples were used for metatranscriptomic sequencing to get whole genomes of HCoVs for genetical and evolutionary analyses. Totally, 321 of 15 677 patients with ILI or SARI were found to be positive for HCoVs, with an infection rate of 2.0% (95% confidence interval, 1.8%-2.3%). HCoV-229E, HCoV-NL63, HCoV-OC43, and HCoV-HKU1 infections accounted for 18.7%, 38.3%, 40.5%, and 2.5%, respectively. In comparison to ILI cases, SARI cases were significantly older, more likely caused by HCoV-229E and HCoV-OC43, and more often co-infected with other respiratory pathogens. A total of 179 full genome sequences of HCoVs were obtained from 321 positive patients. The phylogenetical analyses revealed that HCoV-229E, HCoV-NL63 and HCoV-OC43 continuously yielded novel lineages, respectively. The nonsynonymous to synonymous ratio of all key genes in each HCoV was less than one, indicating that all four HCoVs were under negative selection pressure. Multiple substitution modes were observed in spike glycoprotein among the four HCoVs. Our findings highlight the importance of enhancing surveillance on HCoVs, and imply that more variants might occur in the future.

Genomic representation predicts an asymptotic host adaptation of bat coronaviruses using deep learning.

Introduction: Coronaviruses (CoVs) are naturally found in bats and can occasionally cause infection and transmission in humans and other mammals. Our study aimed to build a deep learning (DL) method to predict the adaptation of bat CoVs to other mammals. Methods: The CoV genome was represented with a method of dinucleotide composition representation (DCR) for the two main viral genes, ORF1ab and Spike. DCR features were first analyzed for their distribution among adaptive hosts and then trained with a DL classifier of convolutional neural networks (CNN) to predict the adaptation of bat CoVs. Results and discussion: The results demonstrated inter-host separation and intra-host clustering of DCR-represented CoVs for six host types: Artiodactyla, Carnivora, Chiroptera, Primates, Rodentia/Lagomorpha, and Suiformes. The DCR-based CNN with five host labels (without Chiroptera) predicted a dominant adaptation of bat CoVs to Artiodactyla hosts, then to Carnivora and Rodentia/Lagomorpha mammals, and later to primates. Moreover, a linear asymptotic adaptation of all CoVs (except Suiformes) from Artiodactyla to Carnivora and Rodentia/Lagomorpha and then to Primates indicates an asymptotic bats-other mammals-human adaptation. Conclusion: Genomic dinucleotides represented as DCR indicate a host-specific separation, and clustering predicts a linear asymptotic adaptation shift of bat CoVs from other mammals to humans via deep learning.

Nurse and Patient Assessments of COVID-19 Care Quality in China: A Comparative Survey Study.

During the COVID-19 pandemic, the quality of nursing care was a concern due to nurses' overwhelming workload. A cross-sectional design was conducted to compare perceptions between nurses and patients about the quality of nursing care for COVID-19 patients and to explore factors associated with these perceptions. Data were collected during the COVID-19 pandemic from 17 March to 13 April 2020 in five hospitals in Wuhan, China. Perceptions of care quality were assessed among nurses and patients using the Caring Behaviors Inventory. Nurses rated the quality of caring behaviors higher than patients. Both nurses and patients rated technical caring behaviors at high levels and rated the item related to "spending time with the patient" the lowest, while patients rated it much lower than nurses. Nurses' sex, participation in ethical training organized by the hospital, professional title, being invited to Wuhan, and length of working experience in years were significantly associated with nurses' self-evaluated caring behaviors. Moreover, inpatient setting and communication mode were significantly associated with patients' self-evaluated caring behaviors.

Trafficked Malayan pangolins contain viral pathogens of humans.

Pangolins are the most trafficked wild animal in the world according to the World Wildlife Fund. The discovery of SARS-CoV-2-related coronaviruses in Malayan pangolins has piqued interest in the viromes of these wild, scaly-skinned mammals. We sequenced the viromes of 161 pangolins that were smuggled into China and assembled 28 vertebrate-associated viruses, 21 of which have not been previously reported in vertebrates. We named 16 members of Hunnivirus, Pestivirus and Copiparvovirus pangolin-associated viruses. We report that the L-protein has been lost from all hunniviruses identified in pangolins. Sequences of four human-associated viruses were detected in pangolin viromes, including respiratory syncytial virus, Orthopneumovirus, Rotavirus A and Mammalian orthoreovirus. The genomic sequences of five mammal-associated and three tick-associated viruses were also present. Notably, a coronavirus related to HKU4-CoV, which was originally found in bats, was identified. The presence of these viruses in smuggled pangolins identifies these mammals as a potential source of emergent pathogenic viruses.

The association between perceived hospital ethical climate and self-evaluated care quality for COVID-19 patients: the mediating role of ethical sensitivity among Chinese anti-pandemic nurses.

BACKGROUND: The COVID-19 pandemic called for a new ethical climate in the designated hospitals and imposed challenges on care quality for anti-pandemic nurses. Less was known about whether hospital ethical climate and nurses' ethical sensitivity were associated with care quality. This study examined the association between the perceived hospital ethical climate and self-evaluated quality of care for COVID-19 patients among anti-pandemic nurses, and explored the mediating role of ethical sensitivity in this relationship. METHODS: A cross-sectional study was conducted through an online survey. A total of 399 anti-pandemic nurses from ten designated hospitals in three provinces of China were recruited to fill out an online survey. Multiple linear regression analysis and a bootstrap test were used to examine the relationships between ethical climate, ethical sensitivity and care quality. RESULTS: Nurses reported mean scores of 4.43 ± 0.577 (out of 5) for hospital ethical climate, 45.00 ± 7.085 (out of 54) for ethical sensitivity, and 5.35 ± 0.661 (out of 6) for self-evaluated care quality. After controlling for covariates, perceived hospital ethical climate was positively associated with self-evaluated care quality (direct effect = 0.710, 95% confidence interval [CI] 0.628, 0.792), and was partly mediated by ethical sensitivity (indirect effect = 0.078, 95% confidence interval [CI] 0.002, 0.145). CONCLUSIONS: Chinese nurses who cared for COVID-19 patients perceived high levels of hospital ethical climate, ethical sensitivity, and self-evaluated care quality. Positive perceptions of hospital ethical climate were both directly associated with a higher level of self-evaluated care quality and indirectly associated, through the mediation effect of ethical sensitivity among anti-pandemic nurses.

Transmission dynamics and the effects of non-pharmaceutical interventions in the COVID-19 outbreak resurged in Beijing, China: a descriptive and modelling study.

OBJECTIVE: To evaluate epidemiological characteristics and transmission dynamics of COVID-19 outbreak resurged in Beijing and to assess the effects of three non-pharmaceutical interventions. DESIGN: Descriptive and modelling study based on surveillance data of COVID-19 in Beijing. SETTING: Outbreak in Beijing. PARTICIPANTS: The database included 335 confirmed cases of COVID-19. METHODS: To conduct spatiotemporal analyses of the outbreak, we collected individual records on laboratory-confirmed cases of COVID-19 from 11 June 2020 to 5 July 2020 in Beijing, and visitor flow and products transportation data of Xinfadi Wholesale Market. We also built a modified susceptible-exposed-infected-removed model to investigate the effect of interventions deployed in Beijing. RESULTS: We found that the staff working in the market (52.2%) and the people around 10 km to this epicentre (72.5%) were most affected, and the population mobility entering-exiting Xinfadi Wholesale Market significantly contributed to the spread of COVID-19 (p=0.021), but goods flow of the market had little impact on the virus spread (p=0.184). The prompt identification of Xinfadi Wholesale Market as the infection source could have avoided a total of 25 708 (95% CI 13 657 to 40 625) cases if unnoticed transmission lasted for a month. Based on the model, we found that active screening on targeted population by nucleic acid testing alone had the most significant effect. CONCLUSIONS: The non-pharmaceutical interventions deployed in Beijing, including localised lockdown, close-contact tracing and community-based testing, were proved to be effective enough to contain the outbreak. Beijing has achieved an optimal balance between epidemic containment and economic protection.

Hospital ethical climate associated with the professional quality of life among nurses during the early stage of COVID-19 pandemic in Wuhan, China: A cross-sectional study.

OBJECTIVES: To describe the professional quality of life and explore its associated factors among nurses coming from other areas of China to assist with the anti-epidemic fight in Wuhan and especially examine whether the hospital ethical climate was independently associated with nurses' professional quality of life. METHODS: A cross-sectional online survey was conducted from March 2020 to April 2020. The nurses working in Wuhan from the other parts of China were the target population. The Professional Quality of Life Scale version 5, the Hospital Ethical Climate Survey, and a basic information sheet were used to collect data. Descriptive statistics, t-test, ANOVA, Pearson correlation, and multiple linear regression analysis were used to analyze the data. RESULTS: In total, 236 nurses participated in this study, and 219 valid questionnaires were analyzed. The average age of the participants was 31.2 ± 5.0 years. Most nurses were female (176/219; 80.4%) and married (145/219; 66.2%). In term of professional quality of life, nurses reported moderate (129/219; 58.9%) to high (90/219; 41.1%) levels of compassion satisfaction, low (119/219; 54.3%) to moderate (100/219; 45.7%) levels of burnout, and low (67/219; 36.0%) to high (10/219; 4.6%) levels of secondary traumatic stress. Regarding hospital ethical climate, nurses reported moderately high hospital ethical climates with an average score of 4.46. After controlling for socio-demographic characteristics, the multiple linear regression models showed that the hospital ethical climate subscale of "relationship with physicians" was independently associated with the compassion satisfaction (ß = 0.533, P < 0.01) and burnout (ß = -0.237, P < 0.05); the hospital ethical climate subscale of "relationship with peers" (ß = -0.191, P < 0.01) was independently associated with the secondary traumatic stress. CONCLUSIONS: During the early stage of the pandemic, nurses demonstrated moderate to high level of compassion satisfaction, low to moderate level of burnout, and all nurses experienced secondary traumatic stress. Nurses perceived a high level of hospital ethical climate, and the perceived hospital ethical climate played an important role in promoting nurses' professional quality of life during a life-threatening infectious disease pandemic.

Novel signaling pathways regulate SARS-CoV and SARS-CoV-2 infectious disease.

ABSTRACT: Severe acute respiratory syndrome coronavirus (SARS-CoV)-2 induces severe infection, and it is responsible for a worldwide disease outbreak starting in late 2019. Currently, there are no effective medications against coronavirus. In the present study, we utilized a holistic bioinformatics approach to study gene signatures of SARS-CoV- and SARS-CoV-2-infected Calu-3 lung adenocarcinoma cells. Through the Gene Ontology platform, we determined that several cytokine genes were up-regulated after SARS-CoV-2 infection, including TNF, IL6, CSF2, IFNL1, IL-17C, CXCL10, and CXCL11. Differentially regulated pathways were detected by the Kyoto Encyclopedia of Genes and Genomes, gene ontology, and Hallmark platform, including chemokines, cytokines, cytokine receptors, cytokine metabolism, inflammation, immune responses, and cellular responses to the virus. A Venn diagram was utilized to illustrate common overlapping genes from SARS-CoV- and SARS-CoV-2-infected datasets. An Ingenuity pathway analysis discovered an enrichment of tumor necrosis factor- (TNF-) and interleukin (IL)-17-related signaling in a gene set enrichment analysis. Downstream networks were predicted by the Database for Annotation, Visualization, and Integrated Discovery platform also revealed that TNF and TNF receptor 2 signaling elicited leukocyte recruitment, activation, and survival of host cells after coronavirus infection. Our discovery provides essential evidence for transcript regulation and downstream signaling of SARS-CoV and SARS-CoV-2 infection.

Analysis and consideration of registration information of global coronavirus disease 2019 clinical study

Objective: To analyze the registration characteristics of registered clinical research, and find the potential scientific and feasibility problems of clinical research on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), providing reference for the good management of follow-up research registration. Methods: The key words of coronavirus disease 2019 (COVID-19) were identified and retrieved from Chinese Clinical Trial Registry and ClinicalTrials website. The registration characteristics of ethical status, number of recruits, total time, number of groups, intervention, study endpoint type, withdrawal, randomized controlled trial (RCT), stage, registration type, provinces distribution and patients' condition were summarized. IBM SPSS 22.0 software was used to analyze the above characteristics. Results: A total of 400 registered clinical studies were collected. Among them, 59 studies were not ethically approved, 15 studies were withdrawn, and stages of 303 studies were unclear. The differences of the three registration characteristics on the two official websites were statistically significant (all P<0.05). Fourteen studies recruited more than 1 000 people, the total time of 189 studies exceeded 6 months, and the number of groups in 22 studies exceeded 4 groups. There was no significant difference in the three registration characteristics on the two official websites. Only 15 studies were industry-sponsored trial. Most registered clinical studies were distributed in Hubei Province. Conclusion: The awareness of Chinese investigator initiating trial registration has increased. However, by collating and analyzing the registration information, it is found that the study design is not rigorous, so it is necessary to strengthen the registration quality management and study design methodological demonstration.

Unclear but present danger: An asymptomatic SARS-CoV-2 carrier.

Superspreaders are critical infectious resources in multiple infectious diseases. They can be asymptomatic or present mild symptoms but can transmit pathogens to susceptible populations, leading to severe symptoms, and even death. Early identification of this population is extremely important to inhibit the spread of infectious diseases. Right now, the whole global world is suffering from a devastating infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this article, a superspreader cluster event in coronavirus disease 2019 (COVID-19) was identified by tracking contacting histories of infected patients. This cluster was found to be originated from an asymptomatic SARS-CoV-2 carrier, which resulted in 13 secondary cases getting infected. All the secondary patients presented with non-typical symptoms of COVID-19, such as fever, dry cough, and myalgia, one of which died of respiratory failure at the end. From this cluster, we learn that people with older ages, low immunity, multiple underlying diseases, especially pulmonary diseases, can contribute to a poor prognosis. Thus, asymptomatic superspreaders of COVID-19 can be extremely dangerous and must be handled time-efficiently.

Gene signatures of SARS-CoV/SARS-CoV-2-infected ferret lungs in short- and long-term models.

Coronaviruses (CoVs) consist of six strains, and the severe acute respiratory syndrome coronavirus (SARS-CoV), newly found coronavirus (SARS-CoV-2) has rapidly spread leading to a global outbreak. The ferret (Mustela putorius furo) serves as a useful animal model for studying SARS-CoV/SARS-CoV-2 infection and developing therapeutic strategies. A holistic approach for distinguishing differences in gene signatures during disease progression is lacking. The present study discovered gene expression profiles of short-term (3 days) and long-term (14 days) ferret models after SARS-CoV/SARS-CoV-2 infection using a bioinformatics approach. Through Gene Ontology (GO) and MetaCore analyses, we found that the development of stemness signaling was related to short-term SARS-CoV/SARS-CoV-2 infection. In contrast, pathways involving extracellular matrix and immune responses were associated with long-term SARS-CoV/SARS-CoV-2 infection. Some highly expressed genes in both short- and long-term models played a crucial role in the progression of SARS-CoV/SARS-CoV-2 infection, including DPP4, BMP2, NFIA, AXIN2, DAAM1, ZNF608, ME1, MGLL, LGR4, ABHD6, and ACADM. Meanwhile, we revealed that metabolic, glucocorticoid, and reactive oxygen species-associated networks were enriched in both short- and long-term infection models. The present study showed alterations in gene expressions from short-term to long-term SARS-CoV/SARS-CoV-2 infection. The current result provides an explanation of the pathophysiology for post-infectious sequelae and potential targets for treatment.

Identifying SARS-CoV-2-related coronaviruses in Malayan pangolins.

The ongoing outbreak of viral pneumonia in China and across the world is associated with a new coronavirus, SARS-CoV-21. This outbreak has been tentatively associated with a seafood market in Wuhan, China, where the sale of wild animals may be the source of zoonotic infection2. Although bats are probable reservoir hosts for SARS-CoV-2, the identity of any intermediate host that may have facilitated transfer to humans is unknown. Here we report the identification of SARS-CoV-2-related coronaviruses in Malayan pangolins (Manis javanica) seized in anti-smuggling operations in southern China. Metagenomic sequencing identified pangolin-associated coronaviruses that belong to two sub-lineages of SARS-CoV-2-related coronaviruses, including one that exhibits strong similarity in the receptor-binding domain to SARS-CoV-2. The discovery of multiple lineages of pangolin coronavirus and their similarity to SARS-CoV-2 suggests that pangolins should be considered as possible hosts in the emergence of new coronaviruses and should be removed from wet markets to prevent zoonotic transmission.