Virome characterization of game animals in China reveals a spectrum of emerging pathogens

Wild animals may be closely related to the outbreak of infectious diseases in recent years. For example, it has been reported that there are closely related SARS-CoV and new coronavirus (SARS-CoV-2) in civet cats, raccoon dogs and pangolins. Therefore, it is of great significance to identify existing or potential pathogens in wild animals that may be in close contact with humans, in order to trace the origin of a specific epidemic and to carry out risk assessment of the most likely source of future epidemics.

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 Influence of Teacher-Student Interaction on the Effects of Online Learning: Based on a Serial Mediating Model.

During the COVID-19 pandemic, online education has become an important approach to learning in the information era and an important research topic in the field of educational technology as well as that of education in general. Teacher-student interaction in online education is an important factor affecting students' learning performance. This study employed a questionnaire survey to explore the influence of teacher-student interaction on learning effects in online education as well as the mediating role of psychological atmosphere and learning engagement. The study involved 398 college students studying at Chinese universities as the research object. Participants filled out a self-report questionnaire. The study found that (1) the level of teacher-student interaction positively affected students' learning effects (r = 0.649, p < 0.01). (2) The psychological atmosphere mediated the positive effect of the level of teacher-student interaction on learning effects with mediating effect value of 0.1248. (3) Learning engagement mediated the positive effect of teacher-student interaction on learning effects with a mediating effect value of 0.1539. (4) The psychological atmosphere and learning engagement play a chain-mediating role in the mechanism of teacher-student interaction affecting students' learning effects; that is, teacher-student interaction promotes students' learning engagement by creating a good psychological atmosphere, which, in turn, influences learning effects. The mediating effect value was 0.0403. The results indicate that teacher-student interaction not only directly affects students' learning effects but also influences students' learning effects through the mediating effect of the psychological atmosphere and learning engagement.

Virome characterization of game animals in China reveals a spectrum of emerging pathogens.

Game animals are wildlife species traded and consumed as food and are potential reservoirs for SARS-CoV and SARS-CoV-2. We performed a meta-transcriptomic analysis of 1,941 game animals, representing 18 species and five mammalian orders, sampled across China. From this, we identified 102 mammalian-infecting viruses, with 65 described for the first time. Twenty-one viruses were considered as potentially high risk to humans and domestic animals. Civets (Paguma larvata) carried the highest number of potentially high-risk viruses. We inferred the transmission of bat-associated coronavirus from bats to civets, as well as cross-species jumps of coronaviruses from bats to hedgehogs, from birds to porcupines, and from dogs to raccoon dogs. Of note, we identified avian Influenza A virus H9N2 in civets and Asian badgers, with the latter displaying respiratory symptoms, as well as cases of likely human-to-wildlife virus transmission. These data highlight the importance of game animals as potential drivers of disease emergence.

Dynamic landscape mapping of humoral immunity to SARS-CoV-2 identifies non-structural protein antibodies associated with the survival of critical COVID-19 patients.

A comprehensive analysis of the humoral immune response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential in understanding COVID-19 pathogenesis and developing antibody-based diagnostics and therapy. In this work, we performed a longitudinal analysis of antibody responses to SARS-CoV-2 proteins in 104 serum samples from 49 critical COVID-19 patients using a peptide-based SARS-CoV-2 proteome microarray. Our data show that the binding epitopes of IgM and IgG antibodies differ across SARS-CoV-2 proteins and even within the same protein. Moreover, most IgM and IgG epitopes are located within nonstructural proteins (nsps), which are critical in inactivating the host's innate immune response and enabling SARS-CoV-2 replication, transcription, and polyprotein processing. IgM antibodies are associated with a good prognosis and target nsp3 and nsp5 proteases, whereas IgG antibodies are associated with high mortality and target structural proteins (Nucleocapsid, Spike, ORF3a). The epitopes targeted by antibodies in patients with a high mortality rate were further validated using an independent serum cohort (n = 56) and using global correlation mapping analysis with the clinical variables that are associated with COVID-19 severity. Our data provide fundamental insight into humoral immunity during SARS-CoV-2 infection. SARS-CoV-2 immunogenic epitopes identified in this work could also help direct antibody-based COVID-19 treatment and triage patients.

Spatial Differentiation and Elements Influencing Urban Resilience in the Middle Reaches of the Yangtze River under the COVID-19 Pandemic

Since the outbreak of COVID-19 in Wuhan City, Hubei Province, in December 2019, the middle reaches of the Yangtze River became the key areas of the spread of the pandemic and association, and also as the urban economic recovery process after the pandemic eased, it provided an excellent opportunity to research urban resilience. From the viewpoint of urban social-ecological system resilience in public health emergencies, this study comprehensively applies the spatial econometrics, geodetector model, and other methods to investigate the urban resilience level, spatial differentiation, and dominant elements in the middle reaches of the Yangtze River under the impact of the pandemic. This study would aid in providing a scientific basis for sustainable spatial planning and governance. The results demonstrated that the urban resilience in the middle reaches of the Yangtze River had notable spatial agglomeration features, eight elements including tertiary industry proportion possessed a robust explanatory power to the spatial differentiation of urban resilience, and the explanatory power was markedly enhanced after the interaction between influential elements of economic and ecological subsystems. Thus, to upgrade the system cycle mechanism and augment the endogenous power for urban development, we need to focus more on the flow of innovative elements in central cities, the optimization of ecological and safe spatial patterns in Hunan and Hubei Provinces, and the innovation of sustainable supply chain in the entire region. [ABSTRACT FROM AUTHOR] Copyright of Discrete Dynamics in Nature & Society is the property of Hindawi Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The seroprevalence and kinetics of IgM and IgG in the progression of COVID-19.

BACKGROUND: SARS-CoV-2 is a novel coronavirus first recognized in late December 2019 that causes coronavirus disease 19 (COVID-19). Due to the highly contagious nature of SARS-CoV-2, it has developed into a global pandemic in just a few months. Antibody testing is an effective method to supplement the diagnosis of COVID-19. However, multicentre studies are lacking to support the understanding of the seroprevalence and kinetics of SARS-CoV-2 antibodies in COVID-19 epidemic regions. METHOD: A multicentre cross-sectional study of suspected and confirmed patients from 4 epidemic cities in China and a cohort study of consecutive follow-up patients were conducted from 29/01/2020 to 12/03/2020. IgM and IgG antibodies elicited by SARS-CoV-2 were tested by a chemiluminescence assay. Clinical information, including basic demographic data, clinical classification, and time interval from onset to sampling, was collected from each centre. RESULTS: A total of 571 patients were enrolled in the cross-sectional study, including 235 COVID-19 patients and 336 suspected patients, each with 91.9%:2.1% seroprevalence of SARS-CoV-2 IgG and 92.3%:5.4% seroprevalence of SARS-CoV-2 IgM. The seroprevalence of SARS-CoV-2 IgM and IgG in COVID-19 patients was over 70% less than 7 days after symptom onset. Thirty COVID-19 patients were enrolled in the cohort study and followed up for 20 days. The peak concentrations of IgM and IgG were reached on the 10th and 20th days, respectively, after symptom onset. The seroprevalence of COVID-19 IgG and IgM increased along with the clinical classification and treatment time delay. CONCLUSION: We demonstrated the kinetics of IgM and IgG SARS-CoV-2 antibodies in COVID-19 patients and the association between clinical classification and antibodies, which will contribute to the interpretation of IgM and IgG SARS-CoV-2 antibody tests and in predicting the outcomes of patients with COVID-19.

SARS-CoV-2 Proteome Microarray for Mapping COVID-19 Antibody Interactions at Amino Acid Resolution.

Comprehensive profiling of humoral antibody response to severe acute respiratory syndrome (SARS) coronavirus-2 (CoV-2) proteins is essential in understanding the host immunity and in developing diagnostic tests and vaccines. To address this concern, we developed a SARS-CoV-2 proteome peptide microarray to analyze antibody interactions at the amino acid resolution. With the array, we demonstrate the feasibility of employing SARS-CoV-1 antibodies to detect the SARS-CoV-2 nucleocapsid phosphoprotein. The first landscape of B-cell epitopes for SARS-CoV-2 IgM and IgG antibodies in the serum of 10 coronavirus disease of 2019 (COVID-19) patients with early infection is also constructed. With array data and structural analysis, a peptide epitope for neutralizing antibodies within the SARS-CoV-2 spike receptor-binding domain's interaction interface with the angiotensin-converting enzyme 2 receptor was predicted. All the results demonstrate the utility of our microarray as a platform to determine the changes of antibody responses in COVID-19 patients and animal models as well as to identify potential targets for diagnosis and treatment.

Antiphospholipid Antibodies in Critically Ill Patients With COVID-19.

OBJECTIVE: Coagulopathy is one of the characteristics observed in critically ill patients with coronavirus disease 2019 (COVID-19). Antiphospholipid antibodies (aPLs) contribute to coagulopathy, though their role in COVID-19 remains unclear. This study was undertaken to determine the prevalence and characteristics of aPLs in patients with COVID-19. METHODS: Sera collected from 66 COVID-19 patients who were critically ill and 13 COVID-19 patients who were not critically ill were tested by chemiluminescence immunoassay for anticardiolipin antibodies (aCLs), anti-ß2 -glycoprotein I (anti-ß2 GPI) (IgG, IgM, and IgA), and IgG anti-ß2 GPI-domain 1 (anti-ß2 GPI-D1) and IgM and IgG anti-phosphatidylserine/prothrombin (anti-PS/PT) antibodies were detected in the serum by enzyme-linked immunosorbent assay. RESULTS: Of the 66 COVID-19 patients in critical condition, aPLs were detected in 31 (47% ). Antiphospholipid antibodies were not present among COVID-19 patients who were not in critical condition. The IgA anti-ß2 GPI antibody was the most commonly observed aPL in patients with COVID-19 and was present in 28.8% (19 of 66) of the critically ill patients, followed by IgA aCLs (17 of 66, or 25.8%) and IgG anti-ß2 GPI (12 of 66, or 18.2%). For multiple aPLs, IgA anti-ß2 GPI + IgA aCLs was the most common antibody profile observed (15 of 66, or 22.7%), followed by IgA anti-ß2 GPI + IgA aCL + IgG anti-ß2 GPI (10 of 66, or 15.2%). Antiphospholipid antibodies emerge ~35-39 days after disease onset. A dynamic analysis of aPLs revealed 4 patterns based on the persistence or transient appearance of the aPLs. Patients with multiple aPLs had a significantly higher incidence of cerebral infarction compared to patients who were negative for aPLs (P = 0.023). CONCLUSION: Antiphospholipid antibodies were common in critically ill patients with COVID-19. Repeated testing demonstrating medium to high titers of aPLs and the number of aPL types a patient is positive for may help in identifying patients who are at risk of developing cerebral infarction. Antiphospholipid antibodies may be transient and disappear within a few weeks, but in genetically predisposed patients, COVID-19 may trigger the development of an autoimmune condition similar to the antiphospholipid syndrome (APS), referred to as "COVID-19-induced APS-like syndrome." Long-term follow-up of COVID-19 patients who are positive for aPLs would be of great importance in understanding the pathogenesis of this novel coronavirus.

Serum Protein Profiling Reveals a Landscape of Inflammation and Immune Signaling in Early-stage COVID-19 Infection.

Coronavirus disease 2019 (COVID-19) is a highly contagious infection and threating the human lives in the world. The elevation of cytokines in blood is crucial to induce cytokine storm and immunosuppression in the transition of severity in COVID-19 patients. However, the comprehensive changes of serum proteins in COVID-19 patients throughout the SARS-CoV-2 infection is unknown. In this work, we developed a high-density antibody microarray and performed an in-depth proteomics analysis of serum samples collected from early COVID-19 (n = 15) and influenza (n = 13) patients. We identified a large set of differentially expressed proteins (n = 132) that participate in a landscape of inflammation and immune signaling related to the SARS-CoV-2 infection. Furthermore, the significant correlations of neutrophil and lymphocyte with the CCL2 and CXCL10 mediated cytokine signaling pathways was identified. These information are valuable for the understanding of COVID-19 pathogenesis, identification of biomarkers and development of the optimal anti-inflammation therapy.