Historical Evolutionary Dynamics and Phylogeography Analysis of Transmissible Gastroenteritis Virus and Porcine Deltacoronavirus: Findings from 59 Suspected Swine Viral Samples from China.

Since the beginning of the 21st century, humans have experienced three coronavirus pandemics, all of which were transmitted to humans via animals. Recent studies have found that porcine deltacoronavirus (PDCoV) can infect humans, so swine enteric coronavirus (SeCoV) may cause harm through cross-species transmission. Transmissible gastroenteritis virus (TGEV) and PDCoV have caused tremendous damage and loss to the pig industry around the world. Therefore, we analyzed the genome sequence data of these two SeCoVs by evolutionary dynamics and phylogeography, revealing the genetic diversity and spatiotemporal distribution characteristics. Maximum likelihood and Bayesian inference analysis showed that TGEV could be divided into two different genotypes, and PDCoV could be divided into four main lineages. Based on the analysis results inferred by phylogeography, we inferred that TGEV might originate from America, PDCoV might originate from Asia, and different migration events had different migration rates. In addition, we also identified positive selection sites of spike protein in TGEV and PDCoV, indicating that the above sites play an essential role in promoting membrane fusion to achieve adaptive evolution. In a word, TGEV and PDCoV are the past and future of SeCoV, and the relatively smooth transmission rate of TGEV and the increasing transmission events of PDCoV are their respective transmission characteristics. Our results provide new insights into the evolutionary characteristics and transmission diversity of these SeCoVs, highlighting the potential for cross-species transmission of SeCoV and the importance of enhanced surveillance and biosecurity measures for SeCoV in the context of the COVID-19 epidemic.

A Linear Relationship Between De Ritis Ratio and Mortality in Hospitalized Patients With COVID-19: A Secondary Analysis Based on a Large Retrospective Cohort Study

Background and aims Although some studies have identified a possible link between the De Ritis ratio and the mortality of patients with COVID-19, the predictive value and the optimal cut-value remain unclear. This study aimed to explore the correlation between the De Ritis ratio and mortality in hospitalized COVID-19 patients. Methods The data for this cohort study came from a retrospective cohort study that was carried out in a medical system in New York City. The primary outcome was the in-hospital mortality of included patients. The researchers ran multivariate Cox regression analyses, curve fitting, and subgroup analysis to support our findings. Overall survival in different De Ritis ratio groups was plotted as Kaplan–Meier survival curves. Results The study enrolled 4371 participants with COVID-19 from 1 March 2020 to 16 April 2020. The overall mortality was 24.8% (1082/4371). The curve fitting analyses indicated that the De Ritis ratio has a positive linear connection with mortality in COVID-19 patients. After adjusting for all covariates, participants with a De Ritis ratio ≥ 2 exhibited 1.29 times the risk of in-hospital mortality compared with those with a De Ritis ratio < 1 (HR 1.29, 95% CI 1.02–1.62, p=0.031). The P for trend was<0.05 for all models. Patients in the group with a De Ritis ratio ≥ 2 experienced the shortest survival time in the Kaplan–Meier survival analysis. Conclusion A higher baseline De Ritis ratio is correlated with a corresponding higher mortality among hospitalized people with COVID-19.

The Advances of Broad-Spectrum and Hot Anti-Coronavirus Drugs.

Coronaviruses, mainly including severe acute respiratory syndrome virus, severe acute respiratory syndrome coronavirus 2, Middle East respiratory syndrome virus, human coronavirus OC43, chicken infectious bronchitis virus, porcine infectious gastroenteritis virus, porcine epidemic diarrhea virus, and murine hepatitis virus, can cause severe diseases in humans and livestock. The severe acute respiratory syndrome coronavirus 2 is infecting millions of human beings with high morbidity and mortality worldwide, and the multiplicity of swine epidemic diarrhea coronavirus in swine suggests that coronaviruses seriously jeopardize the safety of public health and that therapeutic intervention is urgently needed. Currently, the most effective methods of prevention and control for coronaviruses are vaccine immunization and pharmacotherapy. However, the emergence of mutated viruses reduces the effectiveness of vaccines. In addition, vaccine developments often lag behind, making it difficult to put them into use early in the outbreak. Therefore, it is meaningful to screen safe, cheap, and broad-spectrum antiviral agents for coronaviruses. This review systematically summarizes the mechanisms and state of anti-human and porcine coronavirus drugs, in order to provide theoretical support for the development of anti-coronavirus drugs and other antivirals.

Adaptive consensus building in emergency group decision-making with hesitant fuzzy linguistic information: a perspective based on disappointment theory

In this article, an adaptive consensus model that considers individual disappointment emotion is proposed for emergency multi-attribute group decision-making (MAGDM) problems with hesitant fuzzy linguistic information. Subsequently, it is applied to choose the optimal emergency alternative(s) for the prevention and control of COVID-19 on a college campus. The main innovations and contributions of this article are as follows: (a) Individual modified perceived utility (MPU) based on disappointment theory is integrated into the determination of attribute weights and construction of consensus reaching process (CRP). (b) The MPU-based individual contribution degree and the MPU-based soft group consensus degree are developed. (c) The new emergency CRP mechanism not only considers the rewards and penalties of expert weights but also regards the adaptive updating of attribute weights. Compared with the existing emergency MAGDM models in a hesitant fuzzy linguistic environment, the proposed consensus model has some advantages in improving consensus efficiency and simulating uncertain psychological behavior.

Swine Enteric Coronavirus: Diverse Pathogen-Host Interactions.

Swine enteric coronavirus (SeCoV) causes acute gastroenteritis and high mortality in newborn piglets. Since the last century, porcine transmissible gastroenteritis virus (TGEV) and porcine epidemic diarrhea virus (PEDV) have swept farms all over the world and caused substantial economic losses. In recent years, porcine delta coronavirus (PDCoV) and swine acute diarrhea syndrome coronavirus (SADS-CoV) have been emerging SeCoVs. Some of them even spread across species, which made the epidemic situation of SeCoV more complex and changeable. Recent studies have begun to reveal the complex SeCoV-host interaction mechanism in detail. This review summarizes the current advances in autophagy, apoptosis, and innate immunity induced by SeCoV infection. These complex interactions may be directly involved in viral replication or the alteration of some signal pathways.

The Role of Mitophagy in Viral Infection.

Mitophagy, which is able to selectively clear excess or damaged mitochondria, plays a vital role in the quality control of mitochondria and the maintenance of normal mitochondrial functions in eukaryotic cells. Mitophagy is involved in many physiological and pathological processes, including apoptosis, innate immunity, inflammation, cell differentiation, signal transduction, and metabolism. Viral infections cause physical dysfunction and thus pose a significant threat to public health. An accumulating body of evidence reveals that some viruses hijack mitophagy to enable immune escape and self-replication. In this review, we systematically summarize the pathway of mitophagy initiation and discuss the functions and mechanisms of mitophagy in infection with classical swine fever virus and other specific viruses, with the aim of providing a theoretical basis for the prevention and control of related diseases.

Dual Co-Attention-Based Multi-Feature Fusion Method for Rumor Detection

Social media has become more popular these days due to widely used instant messaging. Nevertheless, rumor propagation on social media has become an increasingly important issue. The purpose of this study is to investigate the impact of various features in social media on rumor detection, propose a dual co-attention-based multi-feature fusion method for rumor detection, and explore the detection capability of the proposed method in early rumor detection tasks. The proposed BERT-based Dual Co-attention Neural Network (BDCoNN) method for rumor detection, which uses BERT for word embedding. It simultaneously integrates features from three sources: publishing user profiles, source tweets, and comments. In the BDCoNN method, user discrete features and identity descriptors in user profiles are extracted using a one-dimensional convolutional neural network (CNN) and TextCNN, respectively. The bidirectional gate recurrent unit network (BiGRU) with a hierarchical attention mechanism is used to learn the hidden layer representation of tweet sequence and comment sequence. A dual collaborative attention mechanism is used to explore the correlation among publishing user profiles, tweet content, and comments. Then the feature vector is fed into classifier to identify the implicit differences between rumor spreaders and non-rumor spreaders. In this study, we conducted several experiments on the Weibo and CED datasets collected from microblog. The results show that the proposed method achieves the state-of-the-art performance compared with baseline methods, which is 5.2% and 5% higher than the dEFEND. The F1 value is increased by 4.4% and 4%, respectively. In addition, this paper conducts research on early rumor detection tasks, which verifies the proposed method detects rumors more quickly and accurately than competitors.

Research Progress of Wastewater-based Epidemiology as an Early Warning System for COVID-19 Pandemic

The New Corona Virus Disease(COVID-19) has spread to almost all countries in the world with the cumulative number of confirmed cases reaching 100 million cases. Although the virus spread has been under control in China with occasional cases reported at this stage, there is still a huge risk of the epidemic rebound due to the external unfavorable situation. Before the virus vaccination covers a large group of people, an effective early warning system of COVID-19 outbreak is still the most needed technical means. In view of the presence of virus particles or genetic material(RNA) in the feces/urine of infected cases, Dutch researcher firstly proposed the idea of monitoring SARS-CoV-2 via wastewater-based epidemiology(WBE). So far, the preliminary studies have proved the feasibility of this technology on SARS-CoV-2 surveillance as an early warning. WBE may also characterize the virus transmission dynamics and trends, estimate the prevalence of infected cases, and even locate the infected cases. The present review firstly summarized the development and application of WBE technology in China. Then, a comprehensive analysis was conducted regarding so far what we know about WBE and what WBE can do for us in terms of SARS-CoV-2 surveillance. Finally, a standard protocol for WBE implementation and the areas for further research were presented. Overall, this work is expected to convey timely information and be a reference for the further epidemic control in China.

Is COVID-19 a high risk factor for lung cancer?: A protocol for systematic review and meta-analysis.

INTRODUCTION: COVID-19 has become a common threat to global human health and is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Some asymptomatic patients with early-stage lung cancer who have COVID-19 receive surgical treatment but develop severe pneumonia and other complications or even experience postoperative death, and they may have a worse prognosis compared with healthy individuals infected with COVID-19. However, there is no evidence that COVID-19 is a risk factor for lung cancer patients. This systematic review aims to evaluate the incidence and prognosis of COVID-19 in lung cancer patients and provide evidence-based medical support for clinical treatment. METHODS: We will search 6 medical databases to identify eligible studies published from the establishment of the database to the present. The quality of the included literature will be evaluated using the bias risk assessment tool in Cochrane 5.1.0, and a meta-analysis will be performed using Stata 14.0. Heterogeneity will be statistically assessed using χ2 tests. RESULTS: The study will integrate existing research findings to investigate the prevalence and severity rate of patients with lung cancer infected with SARS-CoV-2 and analyze the prognosis and adverse clinical outcomes in patients with or without COVID-19. CONCLUSION: The results of this study provide evidence to support whether COVID-19 is a risk factor for lung cancer and provide guidance for clinical prevention and treatment based on the evidence obtained in light of the unpredictable threat posed by COVID-19. ETHICS AND DISSEMINATION: Ethics approval is not required for this systematic review as it will involve the collection and analysis of secondary data. The results of the review will be reported in international peer-reviewed journals. PRORPERO REGISTRATION NUMBER: CRD42020195967.

Prostate cancer: a risk factor for COVID-19 in males?: A protocol for systematic review and meta analysis.

INTRODUCTION: COVID-19 is now a global pandemic. Although there are very few studies describing the characteristics of SARS-CoV-2 infections in patients with prostate cancer, these patients are likely to be more susceptible to COVID-19 than healthy people because of their immunosuppressed state. However, there is no evidence that prostate cancer is a risk factor for COVID-19. METHODS: We searched the Wanfang database, the China Science Journal Citation Report (VIP database), the China National Knowledge Infrastructure (CNKI), Web of Science, EMBASE, PubMed, and the Cochrane Library for studies related to the topic. We designed a standardized data extraction sheet and used Epidata software 3.1 for data extraction. In accordance with the Cochrane 5.1.0 standard, both a quality assessment and a risk assessment were carried out for the research meeting the inclusion criteria. The data were analyzed using Revman 5.3 and Stata 13.0 software. RESULTS: The study integrated existing research findings and a meta-analysis of the data to investigate the prevalence of prostate cancer in males infected with SARS-CoV-2 and the adverse clinical outcomes in male patients with or without COVID-19. CONCLUSION: The results of this research may provide a basis for judging if prostate cancer is a risk factor for males infected with SARS-CoV-2, and the findings can effectively help to prevent COVID-19 in patients with prostate cancer. ETHICS AND DISSEMINATION: Ethics approval is not required for this systematic review as it will involve the collection and analysis of secondary data. The results of the review will be reported in international peer-reviewed journals PRORPERO REGISTRATION NUMBER:: CRD42020194071.