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The 2019 novel coronavirus (SARS-CoV-2) pandemic has caused a global health emergency. The outbreak of this virus has raised a number of questions: What is SARS-CoV-2? How transmissible is SARS-CoV-2? How severely affected are patients infected with SARS-CoV-2? What are the risk factors for viral infection? What are the differences between this novel coronavirus and other coronaviruses? To answer these questions, we performed a comparative study of four pathogenic viruses that primarily attack the respiratory system and may cause death, namely, SARS-CoV-2, severe acute respiratory syndrome (SARS-CoV), Middle East respiratory syndrome (MERS-CoV), and influenza A viruses (H1N1 and H3N2 strains). This comparative study provides a critical evaluation of the origin, genomic features, transmission, and pathogenicity of these viruses. Because the coronavirus disease 2019 (COVID-19) pandemic caused by SARS-CoV-2 is ongoing, this evaluation may inform public health administrators and medical experts to aid in curbing the pandemic's progression.

The novel Coronavirus Disease (COVID-19) outbreak currently puts health care workers at high risk of both physical and mental health problems. This study aimed to identify the risk and protective factors for mental health outcomes in health care workers during coronavirus epidemics. A rapid systematic review was performed in three databases (March 24, 2020) and a current COVID-19 resource (May 28, 2020). Following study selection, study characteristics and effect measures were tabulated, and data were synthesized by using vote counting. Meta-analysis was not possible because of high variation in risk factors, outcomes and effect measures. Risk of bias of each study was assessed and the certainty of evidence was appraised according to the GRADE methodology. Out of 2605 references, 33 observational studies were selected and the identified risk and protective factors were categorized in ten thematic categories. Most of these studies (n = 23) were performed during the SARS outbreak, seven during the current COVID-19 pandemic and three during the MERS outbreak. The level of disease exposure and health fear were significantly associated with worse mental health outcomes. There was evidence that clear communication and support from the organization, social support and personal sense of control are protective factors. The evidence was of very low certainty, because of risk of bias and imprecision. Safeguarding mental health of health care workers during infectious disease outbreaks should not be treated as a separate mental health intervention strategy, but could benefit from a protective approach. This study suggests that embedding mental health support in a safe and efficient working environment which promotes collegial social support and personal sense of control could help to maximize resilience of health care workers. Low quality cross-sectional studies currently provide the best possible evidence, and further research is warranted to confirm causality.

Background It had been more than 5 years since the first case of Middle East Respiratory Syndrome coronavirus infection (MERS-CoV) was recorded, but no specific treatment has been investigated in randomized clinical trials. Results from in vitro and animal studies suggest that a combination of lopinavir/ritonavir and interferon-β1b (IFN-β1b) may be effective against MERS-CoV. The aim of this study is to investigate the efficacy of treatment with a combination of lopinavir/ritonavir and recombinant IFN-β1b provided with standard supportive care, compared to treatment with placebo provided with standard supportive care in patients with laboratory-confirmed MERS requiring hospital admission. Methods The protocol is prepared in accordance with the SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) guidelines. Hospitalized adult patients with laboratory-confirmed MERS will be enrolled in this recursive, two-stage, group sequential, multicenter, placebo-controlled, double-blind randomized controlled trial. The trial is initially designed to include 2 two-stage components. The first two-stage component is designed to adjust sample size and determine futility stopping, but not efficacy stopping. The second two-stage component is designed to determine efficacy stopping and possibly readjustment of sample size. The primary outcome is 90-day mortality. Discussion This will be the first randomized controlled trial of a potential treatment for MERS. The study is sponsored by King Abdullah International Medical Research Center, Riyadh, Saudi Arabia. Enrollment for this study began in November 2016, and has enrolled thirteen patients as of Jan 24-2018. Trial registration ClinicalTrials.gov, ID: NCT02845843 . Registered on 27 July 2016.

The MIRACLE trial (MERS-CoV Infection tReated with A Combination of Lopinavir/ritonavir and intErferon-β1b) investigates the efficacy of a combination therapy of lopinavir/ritonavir and recombinant interferon-β1b provided with standard supportive care, compared to placebo provided with standard supportive care, in hospitalized patients with laboratory-confirmed MERS. The MIRACLE trial is designed as a recursive, two-stage, group sequential, multicenter, placebo-controlled, double-blind randomized controlled trial. The aim of this article is to describe the statistical analysis plan for the MIRACLE trial. The primary outcome is 90-day mortality. The primary analysis will follow the intention-to-treat principle. The MIRACLE trial is the first randomized controlled trial for MERS treatment. Trial registration ClinicalTrials.gov, NCT02845843 . Registered on 27 July 2016.

Coronaviruses such as SARS-CoV-2 regularly infect host tissues that express antiviral proteins (AVPs) in abundance. Understanding how they evolve to adapt or evade host immune responses is important in the effort to control the spread of infection. Two AVPs that may shape viral genomes are the zinc finger antiviral protein (ZAP) and the apolipoprotein B mRNA editing enzyme-catalytic polypeptide-like 3 (APOBEC3). The former binds to CpG dinucleotides to facilitate the degradation of viral transcripts while the latter frequently deaminates C into U residues which could generate notable viral sequence variations. We tested the hypothesis that both APOBEC3 and ZAP impose selective pressures that shape the genome of an infecting coronavirus. Our investigation considered a comprehensive number of publicly available genomes for seven coronaviruses (SARS-CoV-2, SARS-CoV, and MERS infecting Homo sapiens , Bovine CoV infecting Bos taurus , MHV infecting Mus musculus , HEV infecting Sus scrofa , and CRCoV infecting Canis lupus familiaris ). We show that coronaviruses that regularly infect tissues with abundant AVPs have CpG-deficient and U-rich genomes; whereas those that do not infect tissues with abundant AVPs do not share these sequence hallmarks. Among the coronaviruses surveyed herein, CpG is most deficient in SARS-CoV-2 and a temporal analysis showed a marked increase in C to U mutations over four months of SARS-CoV-2 genome evolution. Furthermore, the preferred motifs in which these C to U mutations occur are the same as those subjected to APOBEC3 editing in HIV-1. These results suggest that both ZAP and APOBEC3 shape the SARS-CoV-2 genome: ZAP imposes a strong CpG avoidance, and APOBEC3 constantly edits C to U. Evolutionary pressures exerted by host immune systems onto viral genomes may motivate novel strategies for SARS-CoV-2 vaccine development.

The coronavirus disease 2019 (COVID-19) pandemic has highlighted the need for rapid and sensitive protein detection and quantification in simple and robust formats for widespread point-of-care applications. Here, we report on nanobody-functionalized organic electrochemical transistors with a modular architecture for the rapid quantification of single-molecule-to-nanomolar levels of specific antigens in complex bodily fluids. The sensors combine a solution-processable conjugated polymer in the transistor channel and high-density and orientation-controlled bioconjugation of nanobody–SpyCatcher fusion proteins on disposable gate electrodes. The devices provide results after 10 min of exposure to 5 μl of unprocessed samples, maintain high specificity and single-molecule sensitivity in human saliva and serum, and can be reprogrammed to detect any protein antigen if a corresponding specific nanobody is available. We used the sensors to detect green fluorescent protein, and severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and Middle East respiratory syndrome coronavirus (MERS-CoV) spike proteins, and for the COVID-19 screening of unprocessed clinical nasopharyngeal swab and saliva samples with a wide range of viral loads. Organic electrochemical transistors functionalized with antigen-specific nanobodies can rapidly detect attomolar-to-nanomolar levels of the antigens in complex bodily fluids.

“Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)”, the novel coronavirus, is responsible for the ongoing worldwide pandemic. “World Health Organization (WHO)” assigned an “International Classification of Diseases (ICD)” code—“COVID-19”-as the name of the new disease. Coronaviruses are generally transferred by people and many diverse species of animals, including birds and mammals such as cattle, camels, cats, and bats. Infrequently, the coronavirus can be transferred from animals to humans, and then propagate among people, such as with “Middle East Respiratory Syndrome (MERS-CoV)”, “Severe Acute Respiratory Syndrome (SARS-CoV)”, and now with this new virus, namely “SARS-CoV-2”, or human coronavirus. Its rapid spreading has sent billions of people into lockdown as health services struggle to cope up. The COVID-19 outbreak comes along with an exponential growth of new infections, as well as a growing death count. A major goal to limit the further exponential spreading is to slow down the transmission rate, which is denoted by a “spread factor (f)”, and we proposed an algorithm in this study for analyzing the same. This paper addresses the potential of data science to assess the risk factors correlated with COVID-19, after analyzing existing datasets available in “ourworldindata.org (Oxford University database)”, and newly simulated datasets, following the analysis of different univariate “Long Short Term Memory (LSTM)” models for forecasting new cases and resulting deaths. The result shows that vanilla, stacked, and bidirectional LSTM models outperformed multilayer LSTM models. Besides, we discuss the findings related to the statistical analysis on simulated datasets. For correlation analysis, we included features, such as external temperature, rainfall, sunshine, population, infected cases, death, country, population, area, and population density of the past three months—January, February, and March in 2020. For univariate timeseries forecasting using LSTM, we used datasets from 1 January 2020, to 22 April 2020.

The emergence of a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and more recently, the independent evolution of multiple SARS-CoV-2 variants has generated renewed interest in virus evolution and cross-species transmission. While all known human coronaviruses (HCoVs) are speculated to have originated in animals, very little is known about their evolutionary history and factors that enable some CoVs to co-exist with humans as low pathogenic and endemic infections (HCoV-229E, HCoV-NL63, HCoV-OC43, HCoV-HKU1), while others, such as SARS-CoV, MERS-CoV and SARS-CoV-2 have evolved to cause severe disease. In this review, we highlight the origins of all known HCoVs and map positively selected for mutations within HCoV proteins to discuss the evolutionary trajectory of SARS-CoV-2. Furthermore, we discuss emerging mutations within SARS-CoV-2 and variants of concern (VOC), along with highlighting the demonstrated or speculated impact of these mutations on virus transmission, pathogenicity, and neutralization by natural or vaccine-mediated immunity.

The COVID-19 pandemic has strengthened the interest in the biological mechanisms underlying the complex interplay between infectious agents and the human host. The spectrum of phenotypes associated with the SARS-CoV-2 infection, ranging from the absence of symptoms to severe systemic complications, raised the question as to what extent the variable response to coronaviruses (CoVs) is influenced by the variability of the hosts’ genetic background. To explore the current knowledge about this question, we designed a systematic review encompassing the scientific literature published from Jan. 2003 to June 2020, to include studies on the contemporary outbreaks caused by SARS-CoV-1, MERS-CoV and SARS-CoV-2 (namely SARS, MERS and COVID-19 diseases). Studies were eligible if human genetic variants were tested as predictors of clinical phenotypes. An ad hoc protocol for the rapid review process was designed according to the PRISMA paradigm and registered at the PROSPERO database (ID: CRD42020180860). The systematic workflow provided 32 articles eligible for data abstraction (28 on SARS, 1 on MERS, 3 on COVID-19) reporting data on 26 discovery cohorts. Most studies considered the definite clinical diagnosis as the primary outcome, variably coupled with other outcomes (severity was the most frequently analysed). Ten studies analysed HLA haplotypes (1 in patients with COVID-19) and did not provide consistent signals of association with disease-associated phenotypes. Out of 22 eligible articles that investigated candidate genes (2 as associated with COVID-19), the top-ranked genes in the number of studies were ACE2 , CLEC4M (L-SIGN), MBL , MxA ( n = 3), ACE , CD209 , FCER2 , OAS-1 , TLR4 , TNF-α ( n = 2). Only variants in MBL and MxA were found as possibly implicated in CoV-associated phenotypes in at least two studies. The number of studies for each predictor was insufficient to conduct meta-analyses. Studies collecting large cohorts from different ancestries are needed to further elucidate the role of host genetic variants in determining the response to CoVs infection. Rigorous design and robust statistical methods are warranted.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is causing a pandemic of coronavirus disease 2019 (COVID-19). The worldwide transmission of COVID-19 from human to human is spreading like wildfire, affecting almost every country in the world. In the past 100 years, the globe did not face a microbial pandemic similar in scale to COVID-19. Taken together, both previous outbreaks of other members of the coronavirus family (severe acute respiratory syndrome (SARS-CoV) and middle east respiratory syndrome (MERS-CoV)) did not produce even 1% of the global harm already inflicted by COVID-19. There are also four other CoVs capable of infecting humans (HCoVs), which circulate continuously in the human population, but their phenotypes are generally mild, and these HCoVs received relatively little attention. These dramatic differences between infection with HCoVs, SARS-CoV, MERS-CoV, and SARS-CoV-2 raise many questions, such as: Why is COVID-19 transmitted so quickly? Is it due to some specific features of the viral structure? Are there some specific human (host) factors? Are there some environmental factors? The aim of this review is to collect and concisely summarize the possible and logical answers to these questions.