Evaluation of the immunogenicity of auxotrophic Lactobacillus with CRISPR-Cas9D10A system-mediated chromosomal editing to express porcine rotavirus capsid protein VP4.

Porcine rotavirus (PoRV) is an important pathogen, leading to the occurrence of viral diarrhoea . As the infection displays obvious enterotropism, intestinal mucosal immunity is the significant line of defence against pathogen invasion. Moreover, as lactic acid bacteria (LAB) show acid resistance, bile salt resistance and immune regulation, it is of great significance to develop an oral vaccine. Most traditional plasmid delivery vectors use antibiotic genes as selective markers, easily leading to antibiotic accumulation. Therefore, to select a food-grade marker in genetically engineering food-grade microorganisms is vital. Based on the CRISPR-Cas9D10A system, we constructed a stable auxotrophic Lactobacillus paracasei HLJ-27 (Lactobacillus △Alr HLJ-27) strain. In addition, as many plasmids replicate in the host bacteria, resulting in internal gene deletions. In this study,we used a temperature-sensitive gene editing plasmidto insert the VP4 gene into the genome, yielding the insertion mutant strains VP4/△Alr HLJ-27, VP4/△Alr W56, and VP4/W56. This recombinant bacterium efficiently induced secretory immunoglobulin A (SIgA)-based mucosal and immunoglobulin G (IgG)-based humoral immune responses. These oral mucosal vaccines have the potential to act as an alternative to the application of antibiotics in the future and induce efficient immune responses against PEDV infection.

Severe/critical COVID-19 early warning system based on machine learning algorithms using novel imaging scores.

BACKGROUND: Early identification of severe/critical coronavirus disease 2019 (COVID-19) is crucial for timely treatment and intervention. Chest computed tomography (CT) score has been shown to be a significant factor in the diagnosis and treatment of pneumonia, however, there is currently a lack of effective early warning systems for severe/critical COVID-19 based on dynamic CT evolution. AIM: To develop a severe/critical COVID-19 prediction model using a combination of imaging scores, clinical features, and biomarker levels. METHODS: This study used an improved scoring system to extract and describe the chest CT characteristics of COVID-19 patients. The study also took into consideration the general clinical indicators such as dyspnea, oxygen saturation, alternative lengthening of telomeres (ALT), and androgen suppression treatment (AST), which are commonly associated with severe/critical COVID-19 cases. The study employed lasso regression to evaluate and rank the significance of different disease characteristics. RESULTS: The results showed that blood oxygen saturation, ALT, IL-6/IL-10, combined score, ground glass opacity score, age, crazy paving mode score, qsofa, AST, and overall lung involvement score were key factors in predicting severe/critical COVID-19 cases. The study established a COVID-19 severe/critical early warning system using various machine learning algorithms, including XGBClassifier, Logistic Regression, MLPClassifier, RandomForestClassifier, and AdaBoost Classifier. The study concluded that the prediction model based on the improved CT score and machine learning algorithms is a feasible method for early detection of severe/critical COVID-19 evolution. CONCLUSION: The findings of this study suggest that a prediction model based on improved CT scores and machine learning algorithms is effective in detecting the early warning signals of severe/critical COVID-19.

Machine Learning-Based Scoring System for Early Prognosis Evaluation of Patients with Coronavirus Disease 2019

Background The global spread of coronavirus disease 2019 (COVID-19) continues to threaten human health security, exerting considerable pressure on healthcare systems worldwide. While prognostic models for COVID-19 hospitalized or intensive care patients are currently available, prognostic models developed for large cohorts of thousands of individuals are still lacking. Methods Between February 4 and April 16, 2020, we enrolled 3,974 patients admitted with COVID-19 disease in the Wuhan Huo-Shen-Shan Hospital and the Maternal and Child Hospital, Hubei Province, China. (1) Screening of key prognostic factors: A univariate Cox regression analysis was performed on 2,649 patients in the training set, and factors affecting prognosis were initially screened. Subsequently, a random survival forest model was established through machine analysis to further screen for factors that are important for prognosis. Finally, multivariate Cox regression analysis was used to determine the synergy among various factors related to prognosis. (2) Establishment of a scoring system: The nomogram algorithm established a COVID-19 patient death risk assessment scoring system for the nine selected key prognostic factors, calculated the C index, drew calibration curves and drew training set patient survival curves. (3) Verification of the scoring system: The scoring system assessed 1,325 patients in the test set, splitting them into high- and low-risk groups, calculated the C-index, and drew calibration and survival curves. Results The cross-sectional study found that age, clinical classification, sex, pulmonary insufficiency, hypoproteinemia, and four other factors (underlying diseases: blood diseases, malignant tumor;complications: digestive tract bleeding, heart dysfunction) have important significance for the prognosis of the enrolled patients with COVID-19. Herein, we report the discovery of the effects of hypoproteinemia and hematological diseases on the prognosis of COVID-19. Meanwhile, the scoring system established here can effectively evaluate objective scores for the early prognoses of patients with COVID-19 and can divide them into high- and low-risk groups (using a scoring threshold of 117.77, a score below which is considered low risk). The efficacy of the system was better than that of clinical classification using the current COVID-19 guidelines (C indexes, 0.95 vs. 0.89). Conclusions Age, clinical typing, sex, pulmonary insufficiency, hypoproteinemia, and four other factors were important for COVID-19 survival. Compared with general statistical methods, this method can quickly and accurately screen out the relevant factors affecting prognosis, provide an order of importance, and establish a scoring system based on the nomogram model, which is of great clinical significance.

Status of mandatory treatment of mentally ill offenders without criminal responsibility in China: Information from 5,262 mandatory treatment judgments.

Background: To avoid public health risks, all governments ensure monitoring and treatment of mentally ill persons if they offend and assess their level of criminal responsibility. The Criminal Procedure Law of the People's Republic of China (2013) instituted special procedures. However, there are few articles in English which explain the implementation of mandatory treatment procedures in China. Methods: We collected 5,262 qualified documents from 2013 to 2021 from the China Judgments Documents Online. We analyzed social demographic characteristics, trial-related information as well as the mandatory treatment-related content, to investigate the mandatory treatment of China's mentally ill offenders without criminal responsibility, from 2013 to 2021. Simple descriptive statistics and chi-square tests were used to compare differences among several types of documents. Results: There was an overall change trend of the number of documents: increasing year by year from 2013 to 2019 after the implementation of the new law, but with sharp decrease in 2020 and 2021 during covid-19 pandemic. From 2013 to 2021, a total of 3,854 people had applications made for mandatory treatment, of whom 3,747 (97.2%) were given mandatory treatment, 107 (2.8%) had applications rejected. "Schizophrenia and other psychotic disorders" was the most common diagnosis in both groups and all offenders receiving mandatory treatment (3,747, 100.0%) were considered to have no criminal responsibility. A total of 1,294 patients had applications made for relief of mandatory treatment, of whom 827 (63.9%) were subsequently approved for relief, 467 (36.1%) were rejected. A total of 118 patients had applications for relief two or more times, and 56 (47.5%) were finally relieved. Conclusion: Our study presents the Chinese model of a criminal mandatory treatment system to the international community which has been in operation since the implementation of the new law. Legislatory changes and covid-19 pandemic can have effect on the number of mandatory treatment cases. Patients, their close relatives and mandatory treatment institutions have the right to apply for relief from mandatory treatment, but the final decision in China is taken by the court.

Moderating Role of Peer Pressure and Positive Learning Environment Between Career Calling and Academic Procrastination in Chinese Medical Students During Controlled COVID-19 Pandemic: A Cross-Sectional Study.

Purpose: The COVID-19 pandemic sets specific circumstances that may accelerate academic procrastination behavior of medical students. Career calling is a protective factor that fights against academic procrastination and may further improve medical students' mental health and academic achievement. This study aims to determine the status of Chinese medical students' academic procrastination during controlled COVID-19 pandemic. Moreover, the study investigates the relationships and mechanisms among career calling, peer pressure, a positive learning environment, and academic procrastination. Patients and Methods: Data were collected from several Chinese medical universities through an anonymous cross-sectional survey of 3614 respondents (effective response rate = 60.0%). Using online questionnaires to collect the data and IBM SPSS Statistics 22.0 for statistical analysis. Results: The average score of academic procrastination of Chinese medical students was 2.62±0.86. This study proved the usage of peer pressure and positive learning environment as moderating roles of relationship between career calling and academic procrastination. Career calling was negatively correlated with academic procrastination (r = -0.232, p < 0.01), while it was positively correlated with peer pressure (r = 0.390, p < 0.01) and a positive learning environment (r = 0.339, p < 0.01). Moreover, academic procrastination was negatively correlated with peer pressure (r = -0.279, p < 0.01) and a positive learning environment (r = -0.242, p < 0.01). Peer pressure was positively correlated with a positive learning environment (r = 0.637, p < 0.01). Conclusion: The findings emphasize the importance of constructive peer pressure and a positive learning environment that discourages academic procrastination. Educators should highlight medical career calling education by offering related courses to fight against academic procrastination.

SARS-CoV-2 Variants Associated with Vaccine Breakthrough in the Delaware Valley through Summer 2021.

The severe acute respiratory coronavirus-2 (SARS-CoV-2) is the cause of the global outbreak of COVID-19. Evidence suggests that the virus is evolving to allow efficient spread through the human population, including vaccinated individuals. Here, we report a study of viral variants from surveillance of the Delaware Valley, including the city of Philadelphia, and variants infecting vaccinated subjects. We sequenced and analyzed complete viral genomes from 2621 surveillance samples from March 2020 to September 2021 and compared them to genome sequences from 159 vaccine breakthroughs. In the early spring of 2020, all detected variants were of the B.1 and closely related lineages. A mixture of lineages followed, notably including B.1.243 followed by B.1.1.7 (alpha), with other lineages present at lower levels. Later isolations were dominated by B.1.617.2 (delta) and other delta lineages; delta was the exclusive variant present by the last time sampled. To investigate whether any variants appeared preferentially in vaccine breakthroughs, we devised a model based on Bayesian autoregressive moving average logistic multinomial regression to allow rigorous comparison. This revealed that B.1.617.2 (delta) showed 3-fold enrichment in vaccine breakthrough cases (odds ratio of 3; 95% credible interval 0.89-11). Viral point substitutions could also be associated with vaccine breakthroughs, notably the N501Y substitution found in the alpha, beta and gamma variants (odds ratio 2.04; 95% credible interval of1.25-3.18). This study thus overviews viral evolution and vaccine breakthroughs in the Delaware Valley and introduces a rigorous statistical approach to interrogating enrichment of breakthrough variants against a changing background. IMPORTANCE SARS-CoV-2 vaccination is highly effective at reducing viral infection, hospitalization and death. However, vaccine breakthrough infections have been widely observed, raising the question of whether particular viral variants or viral mutations are associated with breakthrough. Here, we report analysis of 2621 surveillance isolates from people diagnosed with COVID-19 in the Delaware Valley in southeastern Pennsylvania, allowing rigorous comparison to 159 vaccine breakthrough case specimens. Our best estimate is a 3-fold enrichment for some lineages of delta among breakthroughs, and enrichment of a notable spike substitution, N501Y. We introduce statistical methods that should be widely useful for evaluating vaccine breakthroughs and other viral phenotypes.

Identification of a key glioblastoma candidate gene, FUBP3, based on weighted gene co-expression network analysis.

BACKGROUND: Glioblastoma multiforme (GBM) is the most common aggressive malignant brain tumor. However, the molecular mechanism of glioblastoma formation is still poorly understood. To identify candidate genes that may be connected to glioma growth and development, weighted gene co-expression network analysis (WGCNA) was performed to construct a gene co-expression network between gene sets and clinical characteristics. We also explored the function of the key candidate gene. METHODS: Two GBM datasets were selected from GEO Datasets. The R language was used to identify differentially expressed genes. WGCNA was performed to construct a gene co-expression network in the GEO glioblastoma samples. A custom Venn diagram website was used to find the intersecting genes. The GEPIA website was applied for survival analysis to determine the significant gene, FUBP3. OS, DSS, and PFI analyses, based on the UCSC Cancer Genomics Browser, were performed to verify the significance of FUBP3. Immunohistochemistry was performed to evaluate the expression of FUBP3 in glioblastoma and adjacent normal tissue. KEGG and GO enrichment analyses were used to reveal possible functions of FUBP3. Microenvironment analysis was used to explore the relationship between FUBP3 and immune infiltration. Immunohistochemistry was performed to verify the results of the microenvironment analysis. RESULTS: GSE70231 and GSE108474 were selected from GEO Datasets, then 715 and 694 differentially expressed genes (DEGs) from GSE70231 and GSE108474, respectively, were identified. We then performed weighted gene co-expression network analysis (WGCNA) and identified the most downregulated gene modules of GSE70231 and GSE108474, and 659 and 3915 module genes from GSE70231 and GSE108474, respectively, were selected. Five intersection genes (FUBP3, DAD1, CLIC1, ABR, and DNM1) were calculated by Venn diagram. FUBP3 was then identified as the only significant gene by survival analysis using the GEPIA website. OS, DSS, and PFI analyses verified the significance of FUBP3. Immunohistochemical analysis revealed FUBP3 expression in GBM and adjacent normal tissue. KEGG and GO analyses uncovered the possible function of FUBP3 in GBM. Tumor microenvironment analysis showed that FUBP3 may be connected to immune infiltration, and immunohistochemistry identified a positive correlation between immune cells (CD4 + T cells, CD8 + T cells, and macrophages) and FUBP3. CONCLUSION: FUBP3 is associated with immune surveillance in GBM, indicating that it has a great impact on GBM development and progression. Therefore, interventions involving FUBP3 and its regulatory pathway may be a new approach for GBM treatment.

Assessment of basic reproductive number for COVID-19 at global level: A meta-analysis.

BACKGROUND: There are large knowledge gaps regarding how transmission of 2019 novel coronavirus disease (COVID-19) occurred in different settings across the world. This study aims to summarize basic reproduction number (R0) data and provide clues for designing prevention and control measures. METHODS: Several databases and preprint platforms were retrieved for literature reporting R0 values of COVID-19. The analysis was stratified by the prespecified modeling method to make the R0 values comparable, and by country/region to explore whether R0 estimates differed across the world. The average R0 values were pooled using a random-effects model. RESULTS: We identified 185 unique articles, yielding 43 articles for analysis. The selected studies covered 5 countries from Asia, 5 countries from Europe, 12 countries from Africa, and 1 from North America, South America, and Australia each. Exponential growth rate model was most favored by researchers. The pooled global R0 was 4.08 (95% CI, 3.09-5.39). The R0 estimates for new and shifting epicenters were comparable or even higher than that for the original epicenter Wuhan, China. CONCLUSIONS: The high R0 values suggest that an extraordinary combination of control measures is needed for halting COVID-19.

Impact of COVID-19 pandemic on acute pancreatitis presentations, management, and in-hospital outcomes: a single-center, retrospective observational study from the northeast of China.

Background: Since initially detected in late December 2019, the novel coronavirus disease 2019 (COVID-19) outbreak rapidly swept the world, which has profoundly affected healthcare system and clinical practice in the management of gastrointestinal diseases. Objectives: We aimed to evaluate the impact of COVID-19 pandemic on the pattern of hospital admissions and healthcare services for acute pancreatitis (AP). Design: We conducted a retrospective observational cohort study using the anonymized electronic medical records. Methods: This single-center, retrospective observational study from a regional medical center in the northeast of China included all consecutively admitted patients with AP from 23 January to 10 June 2020 (during the COVID-19 outbreak in Harbin), compared with the equivalent period of the previous year, in terms of demographics, clinical characteristics, and in-hospital outcomes. Results: In this article, we observed a reduction in AP admissions after the beginning of COVID-19 outbreak. With the prolonged time from symptom onset to hospitalization [32.0 (22.0-72.0) versus 18.0 (12.0-24.0) h; p < 0.001], a higher proportion of AP patients developed acute renal failure (14.0% versus 7.4%, p = 0.004) and acute necrotic collection (16.5% versus 11.2%; p = 0.038) in the COVID-19 era. The percentage of alcohol etiology significantly decreased after the implementation of social restriction measures (11.5% versus 20.4%; p = 0.002), whereas biliary etiology was numerically more common amidst the COVID-19 era (41.6% versus 32.6%; p = 0.014). No significant differences were found in the rates of intensive care unit admission and mortality between the two groups. Conclusion: This study preliminarily demonstrated the descending trend and delay in hospital presentations for AP during the outbreak of COVID-19. Given that the pandemic may persist for several years, adjustments of medical services according to the varying degrees of local breakouts are imperative to provide appropriate care for AP patients and diminish the risk of viral transmission. Registration: ClincialTrials.gov number ChiCTR2100043350.

Evaluation of pharmacist-led telemedicine medication management for hypertension established patients during COVID-19 pandemic: A pilot study.

Aim: To evaluate the impact of a telemedicine medication management service in patients with hypertension. Methods: Participants were allocated to either a telemedicine service (N = 173) or usual care (UC) (N = 179). The primary outcome was blood pressure (BP) reduction from baseline to the 6-month follow-up visit, the proportion of the target BP achievement, overall adherence to prescribed medication as well as a composite of non-fatal stroke, non-fatal myocardial infarction and cardiovascular death. Results: At 6 months, BP was controlled in 89.6% (n = 155) of intervention patients and 78.8% (n = 141) of UC patients (OR = 1.14, 95% CI = 1.04-1.25, P = 0.006), giving a mean difference of -6.0 (-13.0 to -2.5 mmHg) and -2.0 mmHg (-4.0 to -0.1 mmHg) in SBP and DBP, respectively. 17.9% (n = 31) of the patients in the intervention group were non-adherent with medications, compared with 29.1% (n = 52) in the UC group (P = 0.014). The composite clinical endpoints were reached by 2.9% in the intervention group and 4.5% in the control group with no significant differences (OR = 1.566, 95% CI = 0.528-4.646). Conclusion: Telemedicine medication management for hypertension management had led to better BP control and medication adherence improvement than UC during COVID-19 epidemic, resulting in a reduction of overall adverse cardiovascular events occurrence.

Development and immunogenicity evaluation of porcine deltacoronavirus inactivated vaccine with different adjuvants in mice.

Porcine deltacoronavirus (PDCoV) is a novel coronavirus that causes diarrhea in pigs of various ages, especially in suckling piglets, and there are no effective measures to prevent and control PDCoV currently. In this study, two adjuvants Al(OH)3 and ODN2395 working through different mechanisms were used to prepare inactivated PDCoV vaccines, and the immune effects of PDCoV inactivated vaccines were assessed in mice. From the results, we found that both PDCoV/Al(OH)3 vaccine and PDCoV/2395 vaccine could induce IgG and neutralizing antibodies with high levels in mice. At the same time, cytokines of IFN-γ, IL-4 and chemokine ligand of CXCL13 in serum were significantly increased after immunization, and reached the highest levels in PDCoV/2395 vaccine group, which suggested that PDCoV/2395 could promote the production of both Th1 and Th2 polarized cytokines. In addition, histopathological observations showed that vaccination helped mice resist PDCoV infection. These results indicated that both the two inactivated vaccines have good immune effects. Moreover, the PDCoV/2395 vaccine worked better than the PDCoV/Al(OH)3 vaccine for PDCoV/2395 having the good ability to induce both humoral and cellular immunogenicity. The PDCoV/2395 inactivated vaccine developed in this study might be an effective tool for the prevention of PDCoV infection.

Prevalence and associated factors of depressive symptoms among the young adults during the post-epidemic period - Evidence from the first wave of COVID-19 in Hubei Province, China.

INTRODUCTION: China emerged from the first wave of COVID-19 in a short period of time and returned to normal economic and living order nationwide, making China's entry into the post-COVID-19 epidemic period since April 2020. However, the COVID-19 epidemic had a great impact on young adults' psychological status and may continue into the post-epidemic period. The enormous economic, employment and entrepreneurship pressures of this period may exacerbate this negative impact. This study investigated the depression status of the young adults and put forward the suggestions on how to strengthen the psychological crisis intervention and social security to cultivate the resilience of the young adults after major public health emergencies. METHODS: This study conducted a questionnaire survey to identify the prevalence of depressive symptoms and explore the associated factors of depressive symptoms among 1069 young adults in X City, Hubei province in September 2020. And the multistage stratified random sampling method was used for sampling. Depressive symptoms were measured using the 10-item version of the Center for Epidemiological Studies Depression Scale (CES-D-10). Descriptive statistics and logistic regression analysis were adopted for statistical analysis. RESULTS: 1069 respondents (67.68% male; mean age = 28.87 ± 4.18 years; age range = 18-35 years) were included in final analyses. About 25.9% of the respondents reported depressive symptoms (CES-D-10 score = 7.28 ± 3.85). Age, marital status, employment status, monthly disposable income, the cognition, experience and social relationship of the COVID-19 epidemic, and regional discrimination were significantly associated with depressive symptoms. Being male (P = 0.025), age of 25-29 years (P = 0.011), having a household size with 4-5 (P = 0.01) and more than 8 (P = 0.012) family members, a little pessimism about the prospect of COVID-19 epidemic prevention and control (P = 0.044), often (P = 0.018) or always (P = 0.009) participation in anti-epidemic volunteer work were likely to lead to depressive symptoms. CONCLUSIONS: In the post-COVID-19 epidemic period, the psychological status of young people is generally stable, but some of them are depressed. Life, work and mental stress affect the generation of depressive symptoms among the young adults.

The Effectiveness Of Government Masking Mandates On COVID-19 County-Level Case Incidence Across The United States, 2020.

Evidence for the effectiveness of masking on SARS-CoV-2 transmission at the individual level has accumulated, but the additional benefit of community-level mandates is less certain. In this observational study of matched cohorts from 394 US counties between March 21 and October 20, 2020, we estimated the association between county-level public masking mandates and daily COVID-19 case incidence. On average, the daily case incidence per 100,000 people in masked counties compared with unmasked counties declined by 23 percent at four weeks, 33 percent at six weeks, and 16 percent across six weeks postintervention. The beneficial effect varied across regions of different population densities and political leanings. The most concentrated effects of masking mandates were seen in urban counties; the benefit of the mandates was potentially stronger within Republican-leaning counties. Although benefits were not equally distributed in all regions, masking mandates conferred benefit in reducing community case incidence during an early period of the COVID-19 pandemic.

Construction of Influenza Early Warning Model Based on Combinatorial Judgment Classifier: A Case Study of Seasonal Influenza in Hong Kong.

OBJECTIVE: The annual influenza epidemic is a heavy burden on the health care system, and has increasingly become a major public health problem in some areas, such as Hong Kong (China). Therefore, based on a variety of machine learning methods, and considering the seasonal influenza in Hong Kong, the study aims to establish a Combinatorial Judgment Classifier (CJC) model to classify the epidemic trend and improve the accuracy of influenza epidemic early warning. METHODS: The characteristic variables were selected using the single-factor statistical method to establish the influencing factor system of an influenza outbreak. On this basis, the CJC model was proposed to provide an early warning for an influenza outbreak. The characteristic variables in the final model included atmospheric pressure, absolute maximum temperature, mean temperature, absolute minimum temperature, mean dew point temperature, the number of positive detections of seasonal influenza viruses, the positive percentage among all respiratory specimens, and the admission rates in public hospitals with a principal diagnosis of influenza. RESULTS: The accuracy of the CJC model for the influenza outbreak trend reached 96.47%, the sensitivity and specificity change rates of this model were lower than those of other models. Hence, the CJC model has a more stable prediction performance. In the present study, the epidemic situation and meteorological data of Hong Kong in recent years were used as the research objects for the construction of the model index system, and a lag correlation was found between the influencing factors and influenza outbreak. However, some potential risk factors, such as geographical nature and human factors, were not incorporated, which ideally affected the prediction performance to some extent. CONCLUSION: In general, the CJC model exhibits a statistically better performance, when compared to some classical early warning algorithms, such as Support Vector Machine, Discriminant Analysis, and Ensemble Classfiers, which improves the performance of the early warning of seasonal influenza.

Redefining "masstige" luxury consumption in the post-COVID era.

The concept of "new luxury" has challenged the conventional marketing of luxury goods as prestigious, leading to greater expansion of mass luxury meaning. This has become more evident since the outbreak of COVID-19, which has been a catalyst for consumption in the luxury market. This paper investigates the mass marketing of luxury goods and explores the essence of masstige luxury consumption since the outbreak of COVID-19. An interpretive approach was conducted based on semi-structured, in-depth interviews with 31 participants. It analyzes four themes of mass luxury: self as content, self as process, self as context, and self-other. We further argue that the mass consumption of luxury reduces cognitive dissonance, with the pandemic resolving the dark side of conventional luxury consumption. Our findings provide important insights for both scholars and practitioners in the development of a more holistic understanding of masstige in the post-COVID era.

3-Dimensional Printed Alternative to the Standard Synthetic Flocked Nasopharyngeal Swabs Used for Coronavirus Disease 2019 Testing.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (COVID-19), can be detected in respiratory samples by real-time reverse transcriptase polymerase chain reaction (RT-PCR) or other molecular methods. Accessibility of diagnostic testing for COVID-19 has been limited by intermittent shortages of supplies required for testing, including flocked nasopharyngeal (FLNP) swabs. METHODS: We developed a 3-dimensional printed nasopharyngeal (3DP) swab as a replacement of the FLNP swab. The performance of 3DP and FLNP swabs were compared in a clinical trial of symptomatic patients at 3 clinical sites (n = 291) using 3 SARS-CoV-2 emergency use authorization tests: a modified version of the Centers for Disease Control and Prevention (CDC) RT-PCR Diagnostic Panel and 2 commercial automated formats, Roche Cobas and NeuMoDx. RESULTS: The cycle threshold-C(t)-values from the gene targets and the RNase P gene control in the CDC assay showed no significant differences between swabs for both gene targets (P = .152 and P = .092), with the RNase P target performing significantly better in the 3DP swabs (P < .001). The C(t) values showed no significant differences between swabs for both viral gene targets in the Roche cobas assay (P = .05 and P = .05) as well as the NeuMoDx assay (P = .401 and P = .484). The overall clinical correlation of COVID-19 diagnosis between all methods was 95.88% (Kappa 0.901). CONCLUSIONS: The 3DP swabs were equivalent to standard FLNP in 3 testing platforms for SARS-CoV-2. Given the need for widespread testing, 3DP swabs printed onsite are an alternate to FLNP that can rapidly scale in response to acute needs when supply chain disruptions affect availability of collection kits.

Global view on virus infection in non-human primates and implications for public health and wildlife conservation.

Viruses can be transmitted from animals to humans (and vice versa) and across animal species. As such, host-virus interactions and transmission have attracted considerable attention. Non-human primates (NHPs), our closest evolutionary relatives, are susceptible to human viruses and certain pathogens are known to circulate between humans and NHPs. Here, we generated global statistics on VI-NHPs based on a literature search and public data mining. In total, 140 NHP species from 12 families are reported to be infected by 186 DNA and RNA virus species, 68.8% of which are also found in humans, indicating high potential for crossing species boundaries. The top 10 NHP species with high centrality in the NHP-virus network include two great apes (Pan troglodytes, Pongo pygmaeus) and eight Old World monkeys (Macaca mulatta, M. fascicularis, M. leonina, Papio cynocephalus, Cercopithecus ascanius, C. erythrotis, Chlorocebus aethiops, and Allochrocebus lhoesti). Given the wide distribution of Old World monkeys and their frequent contact with humans, there is a high risk of virus circulation between humans and such species. Thus, we suggest recurring epidemiological surveillance of NHPs, specifically Old World monkeys that are in frequent contact with humans, and other effective measures to prevent potential circulation and transmission of viruses. Avoidance of false positives and sampling bias should also be a focus in future work.

Development of an Early Warning Model for Predicting the Death Risk of Coronavirus Disease 2019 Based on Data Immediately Available on Admission.

Introduction: COVID-19 has overloaded worldwide medical facilities, leaving some potentially high-risk patients trapped in outpatient clinics without sufficient treatment. However, there is still a lack of a simple and effective tool to identify these patients early. Methods: A retrospective cohort study was conducted to develop an early warning model for predicting the death risk of COVID-19. Seventy-five percent of the cases were used to construct the prediction model, and the remaining 25% were used to verify the prediction model based on data immediately available on admission. Results: From March 1, 2020, to April 16, 2020, a total of 4,711 COVID-19 patients were included in our study. The average age was 63.37 ± 16.70 years, of which 1,148 (24.37%) died. Finally, age, SpO2, body temperature (T), and mean arterial pressure (MAP) were selected for constructing the model by univariate analysis, multivariate analysis, and a review of the literature. We used five common methods for constructing the model and finally found that the full model had the best specificity and higher accuracy. The area under the ROC curve (AUC), specificity, sensitivity, and accuracy of full model in train cohort were, respectively, 0.798 (0.779, 0.816), 0.804, 0.656, and 0.768, and in the validation cohort were, respectively, 0.783 (0.751, 0.815), 0.800, 0.616, and 0.755. Visualization tools of the prediction model included a nomogram and an online dynamic nomogram (https://wanghai.shinyapps.io/dynnomapp/). Conclusion: We developed a prediction model that might aid in the early identification of COVID-19 patients with a high probability of mortality on admission. However, further research is required to determine whether this tool can be applied for outpatient or home-based COVID-19 patients.

Recombinant angiopoietin-like protein 4 attenuates intestinal barrier structure and function injury after ischemia/reperfusion.

BACKGROUND: Intestinal barrier breakdown, a frequent complication of intestinal ischemia-reperfusion (I/R) including dysfunction and the structure changes of the intestine, is characterized by a loss of tight junction and enhanced permeability of the intestinal barrier and increased mortality. To develop effective and novel therapeutics is important for the improvement of outcome of patients with intestinal barrier deterioration. Recombinant human angiopoietin-like protein 4 (rhANGPTL4) is reported to protect the blood-brain barrier when administered exogenously, and endogenous ANGPTL4 deficiency deteriorates radiation-induced intestinal injury. AIM: To identify whether rhANGPTL4 may protect intestinal barrier breakdown induced by I/R. METHODS: Intestinal I/R injury was elicited through clamping the superior mesenteric artery for 60 min followed by 240 min reperfusion. Intestinal epithelial (Caco-2) cells and human umbilical vein endothelial cells were challenged by hypoxia/ reoxygenation to mimic I/R in vitro. RESULTS: Indicators including fluorescein isothiocyanate-conjugated dextran (4 kilodaltons; FD-4) clearance, ratio of phosphorylated myosin light chain/total myosin light chain, myosin light chain kinase and loss of zonula occludens-1, claudin-2 and VE-cadherin were significantly increased after intestinal I/R or cell hypoxia/reoxygenation. rhANGPTL4 treatment significantly reversed these indicators, which were associated with inhibiting the inflammatory and oxidative cascade, excessive activation of cellular autophagy and apoptosis and improvement of survival rate. Similar results were observed in vitro when cells were challenged by hypoxia/reoxygenation, whereas rhANGPTL4 reversed the indicators close to normal level in Caco-2 cells and human umbilical vein endothelial cells significantly. CONCLUSION: rhANGPTL4 can function as a protective agent against intestinal injury induced by intestinal I/R and improve survival via maintenance of intestinal barrier structure and functions.