One-step multiple TaqMan real-time RT-PCR for simultaneous detection of swine diarrhea viruses

Objective: The aim of this study was to establish a one-step multiplex real-time RT-PCR method to simultaneously detect and quantify five swine diarrhea related viruses, PEDV, GARV, PDCoV, SADS-CoV and PTV, so as to provide an efficient and sensitive tool for rapid diagnosis and epidemiological investigation of porcine diarrhea. Method: The ORF3 gene sequences of several genotypes of PEDV were analyzed, and then the primers and probes were designed for detection of PEDV field strains by referring to the ORF3 genes, which contained deletion mutations in attenuated strains. The 5'-end conserved region of NSP5 genes of GARV G3, G4, G5 and G9 strains were analyzed for design of probes and primers. The specific primers and probes targeting to the conserved regions of PDCoV M, PTV 5'UTR and SADS-CoV N genes were designed for detection of the pathogens. The ROC curves were completed by referring to parameters that were set in RStudio. The specificity value, sensitivity value, and areas under the curves (AUC) and Youden value were calculated according to ROC curves to determine the cut-off CT value. The amplified fragments were cloned into pEASY-T1 vector. The standards prepared through in vitro transcription were named as cRNA-PEDV, cRNA-GARV, cRNA-PDCoV, cRNA-PTV and cRNA-SADS-CoV. The sensitivity, specificity and repeatability of one-step multiplex real-time RT-PCR were evaluated. Coincidence rate between this and another similar method were compared in the detection of clinical samples. Result: Both the annealing temperature and optimal concentrations of primers and probes were obtained for detection of the five pathogens. According to the ROC curve, the CT cut off values for detection of PEDV, GARV, PDCoV, PTV, and SADS-CoV were set as 35.78, 34.25, 34.98, 34.60, and 35.70, respectively. The detection sensitivity of this method for the five pathogens could reach 1..102 copies/L. The standard curves had a good linear relationship and the amplification efficiency was between 96.3% and 104%. The established method could not detect the PEDV vaccine strains and other swine infecting viruses and bacteria including TGEV, CSFV, PRV, PRRSV, S.choleraesuis, P.multocida, E.coli, S.suis and S.aureus. The repeatability test showed the range of intra-assay and inter-assay coefficients of variability: 0.22% to 3.08% and 0.89% to 4.0%, respectively. The detection coincidence rates of the established detection method and another similar method for the five pathogens in 242 clinical samples were 97.9%, 98.8%, 100%, 98.3% and 100% for PEDV, GARV, PDCoV, PTV and SADS-CoV, respectively. The Kappa values were all higher than 0.9. The method had advantage over a commercial diagnostic kit for detection of PEDV wild strains in accuracy. Detection results with clinical samples showed that positive rates of PEDV, GARV, PDCoV and PTV was 10.7% (26/242), 13.6% (33/242), 18.2% (44/242) and 14.5% (35/242), respectively, demonstrating the prevalence state of the four pathogens in Sichuan province in the years. SADS-CoV was not detectable in any areas, but the phenomenon of coinfection with different diarrhea causing viruses was common. Therefore, it was necessary to strengthen the surveillance of several porcine diarrhea viruses in Sichuan province for preventive control. Conclusion: In this study, a one-step multiplex real-time RT-PCR was established for simultaneous detection of PEDV wild strains, PDCoV, SADS-COV and GARV, PTV multiple genotypes, which provided an efficient and sensitive tool for the differential diagnosis and epidemiological investigation of swine diarrhea disease.

Engineering antiviral immune-like systems for autonomous virus detection and inhibition in mice.

The ongoing COVID-19 pandemic has demonstrated that viral diseases represent an enormous public health and economic threat to mankind and that individuals with compromised immune systems are at greater risk of complications and death from viral diseases. The development of broad-spectrum antivirals is an important part of pandemic preparedness. Here, we have engineer a series of designer cells which we term autonomous, intelligent, virus-inducible immune-like (ALICE) cells as sense-and-destroy antiviral system. After developing a destabilized STING-based sensor to detect viruses from seven different genera, we have used a synthetic signal transduction system to link viral detection to the expression of multiple antiviral effector molecules, including antiviral cytokines, a CRISPR-Cas9 module for viral degradation and the secretion of a neutralizing antibody. We perform a proof-of-concept study using multiple iterations of our ALICE system in vitro, followed by in vivo functionality testing in mice. We show that dual output ALICESaCas9+Ab system delivered by an AAV-vector inhibited viral infection in herpetic simplex keratitis (HSK) mouse model. Our work demonstrates that viral detection and antiviral countermeasures can be paired for intelligent sense-and-destroy applications as a flexible and innovative method against virus infection.

Comparisons of Combined Oxidant Capacity and Redox-Weighted Oxidant Capacity in Their Association with Increasing Levels of COVID-19 Infection

Background: Ozone (O3) and nitrogen dioxide (NO2) are substances with oxidizing ability in the atmosphere. Only considering the impact of a single substance is not comprehensive. However, people's understanding of 'total oxidation capacity';(Ox) and 'weighted average oxidation';(Oxwt) is limited. Objectives: This investigation aims to assess the impact of Ox and Oxwt on the novel coronavirus disease (COVID-19). We also compared the relationship between the different calculation methods of Ox and Oxwt and the COVID-19 infection rate. Method: We recorded confirmed COVID-19 cases and daily pollutant concentrations (O3 and NO2) in 34 provincial capital cities in China. The generalized additive model (GAM) was used to analyze the nonlinear relationship between confirmed COVID-19 cases and Ox and Oxwt. Result: Our results indicated that the correlation between Ox and COVID-19 was more sensitive than Oxwt. The hysteresis effect of Ox and Oxwt decreased with time. The most obvious statistical data was observed in Central China and South China. A 10 µg m−3 increase in mean Ox concentrations were related to a 23.1% (95%CI: 11.4%, 36.2%) increase, and a 10 µg m−3 increase in average Oxwt concentration was related to 10.7% (95%CI: 5.2%, 16.8%) increase in COVID-19. In conclusion, our research results show that Ox and Oxwt can better replace the single pollutant research on O3 and NO2, which is used as a new idea for future epidemiological research.

Intention to get vaccinated against COVID-19 among nursing students: A cross-sectional survey.

BACKGROUND: As the COVID-19 pandemic continues, safe and effective vaccines with high coverage remain the most effective way of controlling the infection. Therefore, the intention to get vaccinated is a critical issue for nursing students because they will act as health care providers and educators due to their future profession. OBJECTIVES: This study aimed to explore factors associated with COVID-19 vaccination intention among Chinese nursing students. DESIGN: A cross-sectional online survey was used. PARTICIPANTS: A total of 1070 Chinese nursing students participated in this study. METHODS: The study used structured self-administered questionnaires to assess the effects of the following elements; sociodemographic factors, vaccination status, beliefs on general vaccination, beliefs and attitudes towards COVID-19 and COVID-19 vaccination, and COVID-19 vaccination intention. Hierarchical regression analysis was conducted to examine the relationship between these variables and COVID-19 vaccination intention. RESULTS: More than half (51.9%) of nursing students were willing to vaccinate against COVID-19, while 43.4% were uncertain and 4.7% were unwilling to get vaccinated. Increased likelihood of intention to get vaccinated was associated with positive beliefs towards general vaccination and COVID-19 vaccination, perceived less adverse effects following vaccination, the greater impact of COVID-19 on daily life, and less clinical practice experience in healthcare settings. Those hesitant to vaccinate raised concerns about the safety of vaccines, doubted the efficacy, believed that vaccination was unnecessary, or had insufficient information on COVID-19 vaccines. CONCLUSIONS: More efforts are needed to enhance vaccine confidence and increase the vaccination rates against COVID-19 in nursing students by organizing effective educational campaigns and establishing positive vaccination beliefs.

Analysis of the COVID-19 Epidemic Transmission Network in Mainland China: K-Core Decomposition Study.

BACKGROUND: Since the outbreak of COVID-19 in December 2019 in Wuhan, Hubei Province, China, frequent interregional contacts and the high rate of infection spread have catalyzed the formation of an epidemic network. OBJECTIVE: The aim of this study was to identify influential nodes and highlight the hidden structural properties of the COVID-19 epidemic network, which we believe is central to prevention and control of the epidemic. METHODS: We first constructed a network of the COVID-19 epidemic among 31 provinces in mainland China; after some basic characteristics were revealed by the degree distribution, the k-core decomposition method was employed to provide static and dynamic evidence to determine the influential nodes and hierarchical structure. We then exhibited the influence power of the above nodes and the evolution of this power. RESULTS: Only a small fraction of the provinces studied showed relatively strong outward or inward epidemic transmission effects. The three provinces of Hubei, Beijing, and Guangzhou showed the highest out-degrees, and the three highest in-degrees were observed for the provinces of Beijing, Henan, and Liaoning. In terms of the hierarchical structure of the COVID-19 epidemic network over the whole period, more than half of the 31 provinces were located in the innermost core. Considering the correlation of the characteristics and coreness of each province, we identified some significant negative and positive factors. Specific to the dynamic transmission process of the COVID-19 epidemic, three provinces of Anhui, Beijing, and Guangdong always showed the highest coreness from the third to the sixth week; meanwhile, Hubei Province maintained the highest coreness until the fifth week and then suddenly dropped to the lowest in the sixth week. We also found that the out-strengths of the innermost nodes were greater than their in-strengths before January 27, 2020, at which point a reversal occurred. CONCLUSIONS: Increasing our understanding of how epidemic networks form and function may help reduce the damaging effects of COVID-19 in China as well as in other countries and territories worldwide.

Lactoferrin for the treatment of COVID-19 (Review).

The coronavirus disease 2019 (COVID-19) outbreak was caused by infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The clinical outcomes of elderly individuals and those with underlying diseases affected by COVID-19 are serious, and may result in acute respiratory distress syndrome (ARDS) and even mortality. Currently, the clinical treatments for COVID-19 mostly involve symptom alleviation measures and non-specific broad spectrum antiviral drugs, as highly effective antiviral drugs and vaccines are not yet available. Lactoferrin (LF) is a safe iron-binding glycoprotein that is present in the milk of the majority of mammals and exhibits broad-spectrum antiviral activity, including against coronaviruses. In addition, LF also exhibits anti-inflammatory, anti-infective and immune-regulating properties, which are in line with the treatment requirements for SARS-CoV-2 infection. Therefore, the use of LF may be of value in the prevention and/or management of COVID-19. The aim of the present review was to summarize the previous reports on the antiviral properties of LF and compare these with the characteristics of SARS-CoV-2 infection, in order to determine whether LF could be used to assist in the prevention of COVID-19 and to investigate the possible underlying mechanisms governing its mode of action.

Early type I IFN blockade improves the efficacy of viral vaccines.

Type I interferons (IFN-I) are a major antiviral defense and are critical for the activation of the adaptive immune system. However, early viral clearance by IFN-I could limit antigen availability, which could in turn impinge upon the priming of the adaptive immune system. In this study, we hypothesized that transient IFN-I blockade could increase antigen presentation after acute viral infection. To test this hypothesis, we infected mice with viruses coadministered with a single dose of IFN-I receptor-blocking antibody to induce a short-term blockade of the IFN-I pathway. This resulted in a transient "spike" in antigen levels, followed by rapid antigen clearance. Interestingly, short-term IFN-I blockade after coronavirus, flavivirus, rhabdovirus, or arenavirus infection induced a long-lasting enhancement of immunological memory that conferred improved protection upon subsequent reinfections. Short-term IFN-I blockade also improved the efficacy of viral vaccines. These findings demonstrate a novel mechanism by which IFN-I regulate immunological memory and provide insights for rational vaccine design.

Prediction of Number of Cases of 2019 Novel Coronavirus (COVID-19) Using Social Media Search Index.

Predicting the number of new suspected or confirmed cases of novel coronavirus disease 2019 (COVID-19) is crucial in the prevention and control of the COVID-19 outbreak. Social media search indexes (SMSI) for dry cough, fever, chest distress, coronavirus, and pneumonia were collected from 31 December 2019 to 9 February 2020. The new suspected cases of COVID-19 data were collected from 20 January 2020 to 9 February 2020. We used the lagged series of SMSI to predict new suspected COVID-19 case numbers during this period. To avoid overfitting, five methods, namely subset selection, forward selection, lasso regression, ridge regression, and elastic net, were used to estimate coefficients. We selected the optimal method to predict new suspected COVID-19 case numbers from 20 January 2020 to 9 February 2020. We further validated the optimal method for new confirmed cases of COVID-19 from 31 December 2019 to 17 February 2020. The new suspected COVID-19 case numbers correlated significantly with the lagged series of SMSI. SMSI could be detected 6-9 days earlier than new suspected cases of COVID-19. The optimal method was the subset selection method, which had the lowest estimation error and a moderate number of predictors. The subset selection method also significantly correlated with the new confirmed COVID-19 cases after validation. SMSI findings on lag day 10 were significantly correlated with new confirmed COVID-19 cases. SMSI could be a significant predictor of the number of COVID-19 infections. SMSI could be an effective early predictor, which would enable governments' health departments to locate potential and high-risk outbreak areas.