Preparation and identification of monoclonal antibodies against nucleocapsid protein of novel coronavirus (SARS-CoV-2)

[Objective] At present, a novel emerging Coronavirus Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has caused an epidemic in the world, seriously threatening human life and health. To establish a basis for a rapid detection method for SARS-CoV-2, the monoclonal antibodies targeting nucleocapsid (N)gene were prepared and identified in this study. [Methods] BA LB/c mice were immunized with purified SARS-CoV-2 N recombinant protein. After four times of immunization. the spleen cells of the mice were fused with SP2/0 myeloma cells. The positive hybridoma cell lines stably secreting monoclonal anti-body were screened through ELISA, and the reactivity of the monoclonal antibody was further determined by western blot and indirect immunofluorescence assay. [Results] After three subclones, two hybridoma cell lines designated as 2D11 and 8G6 were obtained. and the prepared antibodies showed good reactivity with the eukaryotic expression of SARS-CoV-2 N protein. [Conclusion] The monoclonal antibody manufactured in this study can be used for SARS-CoV-2 detection.

Determinants of Vaccine Acceptance against COVID-19 in China: Perspectives on Knowledge and DrVac-COVID19S Scale.

Background: This study determined the knowledge and attitudes regarding COVID-19 and assessed the acceptance of the COVID-19 vaccine among the Chinese population. Methods: An online and offline cross-sectional study was conducted from 1 to 18 June 2021 among the Chinese population. Demographic characteristics, attitudes, knowledge, values, impact, and autonomy regarding the COVID-19 vaccine were collected using questionnaire. The variables in our study were analyzed by Mann-Whitney test and chi-square test. Results: A total of 93.8% participants were willing to be vaccinated, 2.7% refused, and 3.5% hesitated. In regards to knowledge about the COVID-19 vaccine, 94.3% citizens surveyed knew about the spread of droplets and 65% had knowledge about surfaces touched by an infected person. In addition, 93.8% of participants had knowledge of the common symptoms related to COVID-19, such as fever and cough (93.8%), shortness of breath/anorexia/fatigue/nausea/vomiting/diarrhea (80.2%), and panic and chest tightness (69.4%). Most participants had a strong self-prevention awareness, such as washing hands regularly (92.1%) and wearing a facemask (94.1%). Besides, over ninety percent of respondents would report exposure to SARS-CoV-2 (96.6%) and exposure to symptoms possibility related to COVID-19 (92.9%). If necessary, most respondents would agree to isolate at home (93.5%) or an isolation in hospital (96.3%). Knowledge of COVID-19, including transmission, symptoms, protective measures, and vaccines itself, is associated with vaccination attitude. Values, perceived impacts, knowledge, and autonomy, assessed by the scale of DrVac-COVID19S, have also been revealed as important determinants to vaccine acceptance. Conclusions: Almost 93% of Chinese people surveyed in this study showed a willing attitude toward COVID-19 vaccination. Based on the above results, government and social workers can take measures from these perspectives to improve the vaccination attitude, so as to increase vaccine immunization rates.

A Perspective on the Role of Point-of-Care "Immuno-Triaging" to Optimize COVID-19 Vaccination Distribution in a Time of Scarcity.

Vaccine bears hope to bring COVID-19 pandemic under control. With limited supply, vaccines must be utilized efficiently to provide protection to those who need it most. Currently, no practical framework has been proposed to ensure fair vaccine allocation at individual level, which is a recognized problem. We propose here an evidence-based decision-making framework for COVID-19 vaccine appropriation that prioritizes vaccine doses to individuals based on their immunological status, or immuno-triaging. To ensure successful implementation of the proposed framework, point-of-care (POC) immunodiagnostic testing is needed to quickly ramp up the testing capability. Considerations for deploying POC immunodiagnostic testing at such a large scale are discussed. We hope that the proposed immunological decision-making framework for evidence-based COVID-19 vaccine appropriation provides an objective approach to ensure fair and efficient utilization of the scarce vaccine resource at the individual level that also maximizes the collective societal benefit.

iTRAQ-based proteome analysis of porcine group A rotavirus-infected porcine IPEC-J2 intestinal epithelial cells.

Porcine rotavirus (PoRV), particularly group A, is one of the most important swine pathogens, causing substantial economic losses in the animal husbandry industry. To improve understanding of host responses to PoRV infection, we applied isobaric tags for relative and absolute quantification (iTRAQ) labeling coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to quantitatively identify the differentially expressed proteins in PoRV-infected IPEC-J2 cells and confirmed the differentially accumulated proteins (DAPs) expression differences by performing RT-qPCR and Western blot analysis. Herein, in PoRV- and mock-infected IPEC-J2 cells, relative quantitative data were identified for 4724 proteins, 223 of which were DAPs (125 up-accumulated and 98 down-accumulated). Bioinformatics analyses further revealed that a majority of the DAPs are involved in numerous crucial biological processes and signaling pathways, such as metabolic process, immune system process, amino acid metabolism, energy metabolism, immune system, MHC class I peptide loading complex, Hippo signaling pathway, Th1 and Th2 cell differentiation, antigen processing and presentation, and tubule bicarbonate reclamation. The cellular localization prediction analysis indicated that these DAPs may be located in the Golgi apparatus, nucleus, peroxisomal, cytoplasm, mitochondria, extracellular, plasma membrane, and endoplasmic reticulum (ER). Expression levels of three up-accumulated (VAMP4, IKBKE, and TJP3) or two down-accumulated (SOD3 and DHX9) DAPs upon PoRV infection, were further validated by RT-qPCR and Western blot analysis. Collectively, this work is the first time to investigate the protein profile of PoRV-infected IPEC-J2 cells using quantitative proteomics; these findings provide valuable information to better understand the mechanisms underlying the host responses to PoRV infection in piglets. SIGNIFICANCE: The proteomics analysis of this study uncovered the target associated with PoRV-induced innate immune response or cellular damage, and provided relevant insights into the molecular functions, biological processes, and signaling pathway in these targets. Out of these 223 DAPs, the expression levels of three up-accumulated (VAMP4, IKBKE, and TJP3) and two down-accumulated (SOD3 and DHX9) DAPs upon PoRV infection, have been further validated using RT-qPCR and Western blot analysis. These outcomes could uncover how PoRV manipulated the cellular machinery, which could further our understanding of PoRV pathogenesis in piglets.

The utility of digital pathology in improving the diagnostic skills of pathology trainees in commonly encountered pigmented cutaneous lesions during the COVID-19 pandemic: A single academic institution experience.

Digital pathology has become an integral part of pathology education in recent years, particularly during the COVID-19 pandemic, for its potential utility as a teaching tool that augments the traditional 1-to-1 sign-out experience. Herein, we evaluate the utility of whole slide imaging (WSI) in reducing diagnostic errors in pigmented cutaneous lesions by pathology fellows without subspecialty training in dermatopathology. Ten cases of 4 pigmented cutaneous lesions commonly encountered by general pathologists were selected. Corresponding whole slide images were distributed to our fellows, along with two sets of online surveys, each composed of 10 multiple-choice questions with 4 answers. Identical cases were used for both surveys to minimize variability in trainees' scores depending on the perceived level of difficulty, with the second set being distributed after random shuffling. Brief image-based teaching slides as self-assessment tool were provided to trainees between each survey. Pre- and post-self-assessment scores were analyzed. 61% (17/28) and 39% (11/28) of fellows completed the first and second surveys, respectively. The mean score in the first survey was 5.2/10. The mean score in the second survey following self-assessment increased to 7.2/10. 64% (7/11) of trainees showed an improvement in their scores, with 1 trainee improving his/her score by 8 points. No fellow scored less post-self-assessment than on the initial assessment. The difference in individual scores between two surveys was statistically significant (p = 0.003). Our study demonstrates the utility of WSI-based self-assessment learning as a source of improving diagnostic skills of pathology trainees in a short period of time.

Identification and Prediction of Novel Clinical Phenotypes for Intensive Care Patients With SARS-CoV-2 Pneumonia: An Observational Cohort Study.

Background: Phenotypes have been identified within heterogeneous disease, such as acute respiratory distress syndrome and sepsis, which are associated with important prognostic and therapeutic implications. The present study sought to assess whether phenotypes can be derived from intensive care patients with coronavirus disease 2019 (COVID-19), to assess the correlation with prognosis, and to develop a parsimonious model for phenotype identification. Methods: Adult patients with COVID-19 from Tongji hospital between January 2020 and March 2020 were included. The consensus k means clustering and latent class analysis (LCA) were applied to identify phenotypes using 26 clinical variables. We then employed machine learning algorithms to select a maximum of five important classifier variables, which were further used to establish a nested logistic regression model for phenotype identification. Results: Both consensus k means clustering and LCA showed that a two-phenotype model was the best fit for the present cohort (N = 504). A total of 182 patients (36.1%) were classified as hyperactive phenotype, who exhibited a higher 28-day mortality and higher rates of organ dysfunction than did those in hypoactive phenotype. The top five variables used to assign phenotypes were neutrophil-to-lymphocyte ratio (NLR), ratio of pulse oxygen saturation to the fractional concentration of oxygen in inspired air (Spo2/Fio2) ratio, lactate dehydrogenase (LDH), tumor necrosis factor α (TNF-α), and urea nitrogen. From the nested logistic models, three-variable (NLR, Spo2/Fio2 ratio, and LDH) and four-variable (three-variable plus TNF-α) models were adjudicated to be the best performing, with the area under the curve of 0.95 [95% confidence interval (CI) = 0.94-0.97] and 0.97 (95% CI = 0.96-0.98), respectively. Conclusion: We identified two phenotypes within COVID-19, with different host responses and outcomes. The phenotypes can be accurately identified with parsimonious classifier models using three or four variables.