The COVID-19 pandemic has shaken the world unprecedentedly, where it has affected the vast global population both socially and economically. The pandemic has also opened our eyes to the many threats that novel virus infections can pose for humanity. While numerous unknowns are being investigated in terms of the distributed damage that the virus can do to the human body, recent studies have also shown that the infection can lead to lifelong sequelae that could affect other parts of the body, and one example is the brain. As part of this work, we investigate how viral infection can affect the brain by modelling and simulating a neuron's behaviour under demyelination that is affected by the cytokine storm. We quantify the effects of cytokine-induced demyelination on the propagation of action potential signals within a neuron. We used information and communication theory analysis on the signal propagated through the axonal pathway under different intensity levels of demyelination to analyse these effects. Our simulations demonstrate that virus-induced degeneration can play a role in the signal power and spiking rate and the probability of releasing neurotransmitters and compromising the propagation and processing of information between the neurons. We also propose a transfer function that models these attenuation effects that degenerates the action potential, where this model has the potential to be used as a framework for the analysis of virus-induced neurodegeneration that can pave the way to improved understanding of virus-induced demyelination.

The COVID-19 pandemic has placed severe demands on healthcare facilities across the world, and in several countries, makeshift COVID-19 centres have been operationalised to handle patient overflow. In developing countries such as India, the public healthcare system (PHS) is organised as a hierarchical network with patient flows from lower-tier primary health centres (PHC) to mid-tier community health centres (CHC) and downstream to district hospitals (DH). In this study, we demonstrate how a network-based modelling and simulation approach utilizing generic modelling principles can (a) quantify the extent to which the existing facilities in the PHS can effectively cope with the forecasted COVID-19 caseload, whilst continuing to offer non-COVID-19 related care; and (b) inform decisions on capacity at makeshift COVID-19 Care Centres (CCC) to handle patient overflows. We apply the network-based modelling and simulation approach to an empirical study of a local PHS comprising ten PHCs, three CHCs, one DH and one makeshift CCC, and report operational outcomes for existing PHS capacity, and estimate the required capacity for the CCC under a specific pandemic response strategy. Our work contributes to the literature by demonstrating how the generic modelling approach finds extensive use in the development of simulations of multi-tier facility networks that may contain multiple instances of generic simulation models of facilities at each network tier. Further, our work provides a comprehensive demonstration of how healthcare facility network simulations can be leveraged for conducting capacity planning in health crises.

The CoVID-19 pandemic is showing a dramatic impact across the world. To the tragedy of the loss of human lives, we must add the great uncertainty that the new coronavirus is causing to our lives. Governments and public health authorities must be able to respond this emergency by taking the appropriate decisions for minimizing the impact of the virus. In the absence of an immediate solution, governments have concentrated their efforts on adopting non-pharmaceutical interventions for restricting the mobility of people and reducing the social contact. Health authorities are publishing most of data for supporting their interventions and policies. The geographic location of the cases is a vital information with exceptional value for analysing the spatio-temporal behaviour of the virus, doing feasible to anticipate potential outbreaks and to elaborate predictive risk mapping. In fact, a great number of media reports, research papers, and web-browsers have presented the COVID-19 disease spreading by using maps. However, processing and visualization of this sort of data presents some aspects that must be carefully reviewed. Based on our experience with fine-grained and detailed data related to COVID-19 in a Spanish region, we present a bunch of mapping strategies and good practices using geospatial tools. The ultimate goal is create appropriate maps at any spatial scale while avoiding conflicts with data such as those related to patients’ privacy.

Background: Mosquitoes of the genus Aedes are important invasive species contributing to the spread of chikungunya, dengue fever, yellow fever, Zika virus, and other dangerous vector-borne diseases. Aedes albopictus is native to southeast Asia with rapid expansion due to human activity, showing a wide distribution in the Korean peninsula. Aedes flavopictus is considered to be native to East Asia with a broad distribution in the region, including in the Korean peninsula. Gaining a better understanding of the genetic diversity of these species is critical for establishing strategies for disease prevention and vector control. Methods: : We obtained DNA from 148 specimens of Ae. albopictus and 166 specimens of Ae. flavopictus in Korea, and amplified two mitochondrial genes ( COI and ND5 ) to compare the genetic diversity and structure of the two species. Results: : We obtained a 658-bp sequence of COI and a 423-bp sequence of ND5 from the two mosquito species. We found low diversity and an insignificant population genetic structure in Ae. albopictus , and high diversity and an insignificant structure in Ae. flavopictus for these two mitochondrial genes. Ae. albopictus had less haplotypes with respect to the number of individuals, and a slight mismatch distribution was confirmed. By contrast, Ae. flavopictus had a large number of haplotypes compared with the number of individuals, and a large unimodal-type mismatch distribution was confirmed. Although the genetic structure of both species was insignificant, Ae. flavopictus exhibited higher genetic diversity than Ae. albopictus. Conclusions: : Ae. albopictus appears to be an introduced species, whereas Ae. flavopictus is an endemic species to the Korean peninsula, and the difference in genetic diversity between the two species is related to their adaptability and introduction history. As an endemic species, Ae. flavopictus is likely to have a larger population size than expected. Further studies on the genetic structure and diversity of these two mosquito species will provide useful data for vector control.

ABSTRACT The speed at which several COVID-19 vaccines went from conception to receiving FDA and EMA approval for emergency use is an achievement unrivaled in the history of vaccine development. Mass vaccination efforts using the highly effective vaccines are currently underway to generate sufficient herd immunity and reduce transmission of the SARS-CoV-2 virus. Despite the most advanced vaccine technology, global recipient coverage, especially in resource-poor areas remains a challenge as genetic drift in naïve population pockets threatens overall vaccine efficacy. In this study, we described the production of insect-cell expressed SARS-CoV-2 spike protein ectodomain and examined its immunogenicity in mice. We demonstrated that, when formulated with CoVaccine HT™adjuvant, an oil-in-water nanoemulsion compatible with lyophilization, our vaccine candidates elicit a broad-spectrum IgG response, high neutralizing antibody titers, and a robust, antigen-specific IFN-γ secreting response from immune splenocytes in outbred mice. Our findings lay the foundation for the development of a dry-thermostabilized vaccine that is deployable without refrigeration.

Introduction SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) has caused a pandemic of historic proportions and continues to spread worldwide. Currently, there is no effective therapy against this virus. This article evaluated the in vitro antiviral effect of Atorvastatin against SARS-CoV-2 and also identified the interaction affinity between Atorvastatin and three SARS-CoV-2 proteins, using in silico structure-based molecular docking approach. Materials and methods The antiviral activity of Atorvastatin against SARS-CoV-2 was evaluated by three different treatment strategies using a clinical isolate of SARS-CoV-2. The interaction of Atorvastatin with Spike, RNA-dependent RNA polymerase (RdRp) and 3C-like protease (3CLpro) was evaluated by molecular docking. Results Atorvastatin showed anti-SARS-CoV-2 activity of 79%, 54.8%, 22.6% and 25% at 31.2, 15.6, 7.9, and 3.9 µM, respectively, by pre-post-treatment strategy. In addition, atorvastatin demonstrated an antiviral effect of 26.9% at 31.2 µM by pre-infection treatment. This compound also inhibited SARS-CoV-2 in 66.9%, 75%, 27.9% and 29.2% at concentrations of 31.2, 15.6, 7.9, and 3.9 µM, respectively, by post-infection treatment. The interaction of atorvastatin with SARS-CoV-2 Spike, RdRp and 3CL protease yielded a binding affinity of −8.5 Kcal/mol, −6.2 Kcal/mol, and −7.5 Kcal/mol, respectively. Conclusion Our study demonstrated the in vitro anti-SARS-CoV-2 activity of Atorvastatin, mainly against the late steps of the viral replicative cycle. A favorable binding affinity with viral proteins by bioinformatics methods was also shown. Due to its low cost, availability, well-established safety and tolerability, and the extensive clinical experience of atorvastatin, it could prove valuable in reducing morbidity and mortality from COVID-19. Importance The COVID-19 pandemic constitutes the largest global public health crisis in a century, with enormous health and socioeconomic challenges. Therefore, it is necessary to search for specific antivirals against its causative agent (SARS-CoV-2). In this sense, the use of existing drugs may represent a useful treatment option in terms of safety, cost-effectiveness, and timeliness. Atorvastatin is widely used to prevent cardiovascular events. This compound modulates the synthesis of cholesterol, a molecule necessary in different stages of the viral replicative cycle. Our study demonstrated the antiviral potential of atorvastatin against SARS-CoV-2, using an in vitro model. Furthermore, the ability of Atorvastatin to directly interfere with three viral targets (Spike, RdRp and 3CL protease) was demonstrated by bioinformatic methods. This compound is a well-studied, low-cost, and generally well-tolerated drug, so it could be a promising antiviral for the treatment of COVID-19.

ABSTRACT Extracellular vesicles (EVs) are membrane-encapsulated structures released by cells which carry signaling factors, proteins and microRNAs that mediate intercellular communication. Accumulating evidence supports an important role of EVs in the progression of neurological conditions and both the spread and pathogenesis of infectious diseases. It has recently been demonstrated that EVs from Hepatitis C virus (HCV) infected individuals and cells contained replicative-competent viral RNA that was capable of infecting hepatocytes. Being a member of the same viral family, it is likely the Zika virus also hijacks EV pathways to package viral components and secrete vesicles that are infectious and potentially less immunogenic. As EVs have been shown to cross blood-brain and placental barriers, it is possible that Zika virus could usurp normal EV biology to gain access to the brain or developing fetus. Here, we demonstrate that Zika virus infected cells secrete distinct EV sub-populations with specific viral protein profiles and infectious genomes. Zika virus infection resulted in the enhanced production of EVs with varying sizes and density compared to those released from non-infected cells. We also show that the EV enriched tetraspanin CD63 regulates the release of EVs, and Zika viral genomes and capsids following infection. Overall, these findings provide evidence for an alternative means of Zika virus transmission and demonstrate the role of EV biogenesis and trafficking proteins in the modulation of Zika infection. Importance Zika virus is a re-emerging infectious disease that spread rapidly across the Caribbean and South America. Infection of pregnant women during the first trimester has been linked to microcephaly, a neurological condition where babies are born with smaller heads due to abnormal brain development. Babies born with microcephaly can develop convulsions and suffer disabilities as they age. Despite the significance of Zika virus, little is known about how the virus infects the fetus or causes disease. Extracellular vesicles (EVs) are membrane-encapsulated structures released by cells that are present in all biological fluids. EVs carry signaling factors, proteins and microRNAs that mediate intercellular communication. EVs have been shown to be a means by which some viruses can alter cellular environments and cross previously unpassable cellular barriers. Thus gaining a greater understanding of how Zika affects EV cargo may aid in the development of better diagnostics, targeted therapeutics and prophylactic treatments.

Arthropod-borne viruses (arboviruses) require replication across a wide range of temperatures to perpetuate. While vertebrate hosts tend to maintain temperatures of approximately 37°C - 40°C, arthropods are subject to ambient temperatures which can have a daily fluctuation of > 10°C. Temperatures impact vector competence, extrinsic incubation period, and mosquito survival unimodally, with optimum occurring at some intermediate temperature. In addition, the mean and range of daily temperature fluctuations influence arbovirus perpetuation and vector competence. The impact of temperature on arbovirus genetic diversity during systemic mosquito infection, however, is poorly understood. Therefore, we determined how constant extrinsic incubation temperatures of 25°C, 28°C, 32°C, and 35°C control Zika virus (ZIKV) vector competence and population dynamics within Aedes aegypti and Aedes albopictus mosquitoes. We also examined diurnally fluctuating temperatures which more faithfully mimic field conditions in the tropics. We found that vector competence varied in a unimodal manner for constant temperatures peaking between 28°C and 32°C for both Aedes species. Transmission peaked at 10 days post-infection for Aedes aegypti and 14 days for Aedes albopictus. The effect of diurnal temperature was distinct and could not have been predicted from constant temperature-derived data. Using RNA-seq to characterize ZIKV population structure, we identified that temperature alters the selective environment in unexpected ways. During mosquito infection, constant temperatures more often elicited positive selection whereas diurnal temperatures led to strong purifying selection in both Aedes species. These findings demonstrate that temperature has multiple impacts on ZIKV biology within mosquitoes, including major effects on the selective environment within mosquitoes. Author Summary Arthropod-borne viruses (arboviruses) have emerged in recent decades due to complex factors that include increases in international travel and trade, the breakdown of public health infrastructure, land use changes, and many other factors. Climate change also has the potential to shift the geographical ranges of arthropod vectors, consequently increasing the global risk of arbovirus infection. Changing temperatures may also alter the virus-host interaction, ultimately resulting in the emergence of new viruses and virus genotypes in new areas. Therefore, we sought to characterize how temperature (both constant and fluctuating) alters the ability of Aedes aegypti and Aedes albopictus to transmit Zika virus, and how it influences virus populations within mosquitoes. We found that intermediate temperatures maximize virus transmission compared to more extreme and fluctuating temperatures. Constant temperatures increased positive selection on virus genomes, while fluctuating temperatures strengthened purifying selection. Our studies provide evidence that in addition to altering VC, temperature significantly influences the selective environment within mosquitoes.

Background: Since December 2019, the COVID-19 pandemic has changed the concept of medicine. This work aims to analyze the use of antibiotics in patients admitted to the hospital due to SARS-CoV-2 infection. Methods: This work analyzes the use and effectiveness of antibiotics in hospitalized patients with COVID-19 based on data from the SEMI-COVID-19 registry, an initiative to generate knowledge about this disease using data from electronic medical records. Our primary endpoint was all-cause in-hospital mortality according to antibiotic use. The secondary endpoint was the effect of macrolides on mortality. Results: Of 13,932 patients, antibiotics were used in 12,238. The overall death rate was 20.7% and higher among those taking antibiotics (87.8%). Higher mortality was observed with use of all antibiotics (OR 1.40, 95%CI 1.21-1.62; p<.001) except macrolides, which had a higher survival rate (OR 0.70, 95%CI 0.64-0.76; p<.001). The decision to start antibiotics was influenced by presence of increased inflammatory markers and any kind of infiltrate on an x-ray. Patients receiving antibiotics required respiratory support and were transferred to intensive care units more often. Conclusions: Bacterial co-infection was uncommon among COVID-19 patients, yet use of antibiotics was high. There is insufficient evidence to support widespread use of empiric antibiotics in these patients. Most may not require empiric treatment and if they do, there is promising evidence regarding azithromycin as a potential COVID-19 treatment.

Zika virus (ZIKV), without a vaccine or no effective treatment approved as yet, have globally spread since the past century. The infection caused by ZIKV in humans has changed progressively from mild to subclinical in the last years, causing epidemics with greater infectivity, tropism towards new tissues, and other related symptoms as a product of various emergent ZIKV-host cell interactions. However, it is still unknown why or how the RNA genome structure impacts those interactions in differential evolutionary origin strains. Moreover, genomic comparison of ZIKV strains from the sequence-based phylogenetic analysis is well known, but differences from RNA structure comparisons are less known. Thus, in order to understand the RNA genome variability of lineages of various geographic distributions better, 412 complete genomes in a phylogenomic scanning were used for studying the conservation of structured RNAs. We found specific genomic regions, which highlight their patterns of conserved RNA structures at the level of inter-geographical comparisons. We have proposed these structures as candidates for further experimental validation to establish their potential role in vital functions of the viral cycle of ZIKV and their possible associations with the singularities of different outbreaks that occurred in specific geographic regions.

Recently, administrative agencies around the world have engaged in a grand experiment to regulate new technologies: regulatory sandboxes. Regulatory sandboxes allow developers, in cooperation with an agency, to conduct limited tests of new technologies in real-world settings for the purpose of generating and sharing information about them. Thus far, however, “regulatory sandboxes”—as named— appear almost exclusively in the context of financial technologies, or FinTech. Whether regulatory sandboxes, in fact, exist elsewhere in administrative law would be a significant finding for both regulators and scholars; it would blunt criticisms that agencies are slow to respond to new technologies, provide regulators with an additional tool for governing new technologies, and suggest that lessons learned from current regulatory sandboxes are applicable elsewhere. This Article is the first to explore this broader view of regulatory sandboxes and develop a synoptic theory of them. To do so, it uses one of the most radical programs to introduce new technologies in US history: the US Food and Drug Administration’s (FDA’s) Emergency Use Authorization (EUA) program for COVID-19 treatments and vaccines. EUAs—like regulatory sandboxes but in stark contrast to typical FDA approval processes—focus on real-world deployment as a means for information gathering. EUAs are also technologically flexible and crafted with close input from the developer, among other features. Generalizing FDA’s experience with EUAs also provides lessons about the intersection of regulatory sandboxes with public trust in the agency, political interference, and the maintenance of regulatory standards. At the same time, FDA’s COVID–19 EUAs are exceptional in two senses: they touch upon the public health, widely considered to be exceptional subject matter in administrative law; and arose in the context of unprecedented global pandemic. Nonetheless, FDA’s experience with EUAs suggest regulatory sandboxes may be an underexplored and undertheorized feature of administrative governance of new technologies. Future work in the area should assess whether regulatory sandboxes exist under the rubric identified here, which technologies they regulate, and how those sandboxes operate.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) worldwide has increased the importance of computational tools to design a drug or vaccine in reduced time with minimum risk. Earlier studies have emphasized the important role of RNA-dependent RNA polymerase (RdRp) in SARS-CoV-2 replication as a potential drug target. In our study, comprehensive computational approaches were applied to identify potential compounds targeting RdRp of SARS-CoV-2. To study the binding affinity and stability of the phytocompounds from Phyllanthus emblica and Aegel marmelos within the defined binding site of SARS-CoV-2 RdRp, they were subjected to molecular docking, 100ns molecular dynamics (MD) simulation followed by post-simulation analysis. Further, to assess the importance of features involved in the strong binding affinity, molecular field-based similarity analysis was performed. Based on comparative molecular docking and simulation studies of the selected phytocompounds with SARS-CoV-2 RdRp revealed that, EBDGp possess stronger binding affinity (-23.32 kcal/mol) and stability than other phytocompounds and reference compound, Remdesivir (-19.36 kcal/mol). Molecular field-based similarity profiling has supported our study in the validation of the importance of the presence of hydroxyl groups in EBDGp, involved in increasing its binding affinity towards SARS-CoV-2 RdRp. Molecular docking and dynamic simulation results confirmed that EBDGp has better inhibitory potential than Remdesivir and can be an effective novel drug for SARS-CoV-2 RdRp. Furthermore, binding free energy calculations confirmed the higher stability of the SARS-CoV-2 RdRp-EBDGp complex. These results suggest that the EBDGp compound may emerge as a promising drug against SARS-CoV-2 and hence requires further experimental validation.

In planning for upcoming mass vaccinations against COVID-19, many jurisdictions have proposed using primarily age-based rollout strategies, where the oldest are vaccinated first and the youngest last. In the wake of growing evidence that approved vaccines are effective at preventing not only adverse outcomes, but also infection (and hence transmission of SARS-CoV-2), we propose that such age-based rollouts are both less equitable and less effective than strategies that prioritize essential workers. We demonstrate that strategies that target essential workers earlier consistently outperform those that do not, and that prioritizing essential work-ers provides a significant level of indirect protection for older adults. This conclusion holds across numerous outcomes, including cases, hospitalizations, Long COVID, deaths and net monetary benefit, and over a range of possible values for the efficacy of vaccination against infection. Our analysis focuses on regimes where the pandemic continues to be controlled with distancing and other measures as vaccination proceeds, and where the vaccination strategy is expected to last for over the coming 6-8 months — for example British Columbia, Canada. In such a setting with a total population of 5M, vaccinating essential workers sooner is expected to prevent over 200,000 infections, over 600 deaths, and to produce a net monetary benefit of over $500M.

The effective reproduction number, R(t), is a central point in the study of infectious diseases. It establishes in an explicit way the extent of an epidemic spread process in a population. The current estimation methods for the time evolution of R(t), using incidence data, rely on the generation interval distribution, g(τ), which is usually obtained from empirical data or already known distributions from the literature. However, there are systems, especially highly heterogeneous ones, in which there is a lack of data and an adequate methodology to obtain g(τ). In this work, we use mathematical models to bridge this gap. We present a general methodology for obtaining an explicit expression of the reproduction numbers and the generation interval distributions provided by an arbitrary compartmental model. Additionally, we present the appropriate expressions to evaluate those reproduction numbers using incidence data. To highlight the relevance of such methodology, we apply it to the spread of Covid-19 in municipalities of the state of Rio de janeiro, Brazil. Using two meta-population models, we estimate the reproduction numbers and the contributions of each municipality in the generation of cases in all others. Our results point out the importance of mathematical modelling to provide epidemiological meaning of the available data.

Background: In recent years the invasive species Aedes albopictus , known as the Asian tiger mosquito, has undergone an extreme expansion by steady introductions as blind passengers in vehicles from the Mediterranean to South-West Germany. Nowadays, more than 15 established populations are known in the State of Baden-Württemberg and Palatine (South-West Germany) which locally constitute a significant nuisance and public health threat. Therefore, the species deserves special attention as vector of several arboviruses like dengue, Chikungunya or Zika virus. As a consequence, immediate surveillance and control activities against Aedes albopictus have been implemented in the infested areas under the auspice of health departments and regulatory offices. Methods: The control strategy comprises 3 columns: a) community participation (CP) based on detailed information for the elimination and sanitation of breeding sites as well as the use of fizzy Bti-tablets containing the pro-toxins of Bacillus thuringiensis israelensis (Bti); b) Door-to-Door (DtD) activities by trained staff including the application of Bti (Vectobac WG) at high dosages to achieve a sustained killing effect of the mosquito larvae; and c) the Sterile Insect Technique (SIT) to almost wipe out or eliminate the remaining Aedes albopictus population after intensive Bti-applications. In the laboratory and in semi-field tests, the different elements of the control strategy are evaluated and the efficacy of the integrated control strategy is assessed in routine treatments in the cities of Ludwigshafen (Palatine) and Freiburg (Baden-Württemberg) with special emphasis on the release of sterile Aedes /males. Results: Following our information campaigns, more than 60% of the residents were practicing CP focusing on environmental sanitation and the use of fizzy Bti tablets. Although CP is an essential element of the integrated control strategy, it was shown that the strongest asset in our programme was the DtD activity and the application of a water suspension of Vectobac WG (2700 ITU/mg) to all potential breeding sites at dosages of 10g/rainwater container and 2.5g/smaller container which provided an effect for more than a month. The mean time for the inspection and treatment of a property was 27 minutes. As a result of the larval source management, the container index for Aedes albopictus achieved no more than 0.5% in Ludwigshafen. The mean number of Aedes eggs/ovitrap in Ludwigshafen was 4,3 and in Freiburg -Metzgergrün (SIT area) 18.23 and Freiburg-Gartenstadt-Freiburg (Control area) 22,4 eggs/trap. After the strong reduction of the Aedes population by Bti-application, the weekly release of 1013 (Ludwigshafen) and 2320 (Freiburg) sterile Aedes albopictus males/ha from May until October resulted in an overall sterility by egg counts 82.61% ( (Ø60.52±42.88%) in Ludwigshafen and 62.68±28.21% in Freiburg compared to a natural sterility of 16.93±13.5% in the SIT untreated area. The field results are proven by the data achieved in cage tests in the laboratory. The mating of wild females with sterile males showed sterility rates of 87.53±9.15% whereas the sterility of eggs laid by females mated with unirradiated males was only 3.3±2.8%. The most effective ratio of wild to sterile males is 1:5. The overall sterility of about 83% in Ludwigshafen indicates that our goal to almost eradicate the Aedes albopictus population could be achieved. The hydrogen-peroxide bleaching technique allowed a quick assessment of embryogenesis. Conclusions: In this study, we clearly prove that an integrated control program based on a strict monitoring scheme is most effective when it comprises three columns, namely a) community participation, b) DtD activities including long-lasting Bti-larviciding of all possible breeding sites to strongly reduce the wild Aedes albopictus population as a basis for the successful application of SIT, and c) SIT to almost wipe out the Aedes albopictus population. The combination of Bti and SIT guarantees that two of the most selective, save and effective tools are employed against one of the most dangerous mosquito vector species Aedes albopictus , the Asian tiger mosquito.

Coronaviruses (CoV) are a family of RNA viruses that typically cause respiratory, enteric and hepatic diseases in animals and humans. Here, we used porcine epidemic diarrhea virus (PEDV) as a model of coronaviruses (CoVs) to illustrate the reciprocal regulation between CoVs infection and pyroptosis. For the first time, we clarified the molecular mechanism of porcine Gasdermin D (pGSDMD)-mediated pyroptosis and demonstrated that amino acids T239 and F240 within pGSDMD-p30 are critical for pyroptosis. Furthermore, 3C-like protease Nsp5 from SARS-CoV-2, MERS-CoV, PDCoV and PEDV can cleave human/porcine GSDMD at the Q193-G194 junction upstream of the caspase-1 cleavage site to produce two fragments which fail to trigger pyroptosis or inhibit viral replication. Thus, we provide clear evidence that coronoviruses may utilize viral Nsp5-GSDMD pathway to help their host cells escaping from pyroptosis, protecting the replication of the virus during the initial period, which suggest an important strategy for coronoviruses infection and sustain.

As courts throughout the country decide coronavirus-related liability issues, judges can look to claims that arose out of three recent health crises: the H1N1 pandemic, the Ebola crisis, and the Zika crisis. This Article makes a novel contribution to this emerging legal literature on the coronavirus pandemic by analyzing the cases that rose out of these crises and how these past decisions may apply to fact patterns that arise out of the current coronavirus pandemic.

Since its initial discovery in late 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of COVID19, has spread worldwide and despite significant research efforts, treatment options remain limited. Replication of SARS-CoV-2 in lung is associated with marked infiltration of macrophages and activation of innate immune inflammatory responses triggered, in part, by heightened production of interleukin-6 (IL-6) that recruits lymphocytes to the site of infection that amplify tissue injury. Antagonists of the glucocorticoid and androgen receptors have shown promise in experimental models of COVID19 and in clinical studies, because cell surface proteins required for viral entry, angiotensin converting enzyme 2 (ACE2) and the transmembrane serine protease 2 (TMPRSS2), are transcriptionally regulated by these receptors. We therefore postulated that the glucocorticoid (GR) and androgen receptor (AR) antagonist, PT150, would reduce infectivity of SARS-CoV-2 and prevent inflammatory lung injury in the Syrian golden hamster model of COVID19. Animals were infected intranasally with 2.5 × 10 4 TCID50/ml equivalents of SARS-CoV-2 (strain 2019-nCoV/USA-WA1/ 2020) and PT150 was administered by oral gavage at 30 and 100 mg/Kg/day for a total of 7 days. Animals were then examined at days 3, 5 and 7 post-infection (DPI) for lung histopathology, viral load and production of proteins regulating the initiation and progression of SARS-CoV-2 infection. Results of these studies indicated that oral administration of PT150 decreased replication of SARS-CoV-2 in lung, as well as expression of ACE2 and TMPRSS2 protein. Hypercellularity and inflammatory cell infiltration driven by macrophage responses were dramatically decreased in PT150-treated animals, as was tissue damage and expression of IL-6. Molecular modeling suggested that PT150 binds to the co-activator interface of the ligand binding domain of both AR and GR and thereby acts as an allosteric modulator and transcriptional repressor of these receptors. Phylogenetic analysis of AR and GR across multiple species permissive to SARS-CoV-2 infection revealed a high degree of sequence identity maintained across species, including human, suggesting that the mechanism of action and therapeutic efficacy observed in Syrian hamsters would likely be predictive of positive outcomes in patients. PT150 is therefore a strong candidate for further clinical development for the treatment of COVID19 across variants of SARS-CoV-2.

This paper introduces new methods to analyze the changing progression of COVID-19 cases to deaths in different waves of the pandemic. First, an algorithmic approach partitions each country or state's COVID-19 time series into a first wave and subsequent period. Next, offsets between case and death time series are learned for each country via a normalized inner product. Combining these with additional calculations, we can determine which countries have most substantially reduced the mortality rate of COVID-19. Finally, our paper identifies similarities in the trajectories of cases and deaths for European countries and U.S. states. Our analysis refines the popular conception that the mortality rate has greatly decreased throughout Europe during its second wave of COVID-19; instead, we demonstrate substantial heterogeneity throughout Europe and the U.S. The Netherlands exhibited the largest reduction of mortality, a factor of 16, followed by Denmark, France, Belgium, and other Western European countries, greater than both Eastern European countries and U.S. states. Some structural similarity is observed between Europe and the United States, in which Northeastern states have been the most successful in the country. Such analysis may help European countries learn from each other's experiences and differing successes to develop the best policies to combat COVID-19 as a collective unit.

Biological processes at the cellular level are stochastic in nature, and the immune response system is no different. Therefore, models that attempt to explain this system need to also incorporate noise or fluctuations that can account for the observed variability. In this work, a stochastic model of the immune response system is presented in terms of the dynamics of the T cells and the virus particles. Making use of the Green's function and the Wilemski-Fixman approximation, this model is then solved to obtain the analytical expression for the joint probability density function of these variables in the early and late stages of infection. This is then also used to calculate the average level of virus particles in the system. Upon comparing the theoretically predicted average virus levels to those of COVID-19 patients, it is hypothesized that the long lived dynamics that are characteristic of such viral infections are due to the long range correlations in the temporal fluctuations of the virions. This model therefore provides an insight into the effects of noise on viral dynamics.

To predict interactions between human and viral proteins, we combine evolutionary sequence profile features with a Siamese convolutional neural network (CNN) architecture and a multi-layer perceptron (MLP). Our architecture outperforms various feature encodings-based machine learning and state-of-the-art prediction methods. As our main contribution, we introduce two types of transfer learning methods (i.e., ‘frozen’ type and ‘fine-tuning’ type) that reliably predict interactions in a target human-virus domain based on training in a source human-virus domain, by retraining CNN layers. Our transfer learning strategies can effectively apply prior knowledge transfer from large source dataset/task to small target dataset/task to improve prediction performance. Finally, we utilize the ‘frozen’ type of transfer learning to predict human-SARS-CoV-2 PPIs, indicating that our predictions are topologically and functionally similar to experimentally known interactions. Source code and datasets are available at https://github.com/XiaodiYangCAU/TransPPI/ .

Background SARS-CoV-2 related research has increased in importance worldwide since December 2019. Several new variants of SARS-CoV-2 have emerged globally, of which the most notable and concerning currently are the UK variant B.1.1.7, the South African variant B1.351 and the Brazilian variant P.1. Detecting and monitoring novel variants is essential in SARS-CoV-2 surveillance. While there are several tools for assembling virus genomes and performing lineage analyses to investigate SARS-CoV-2, each is limited to performing singular or a few functions separately. Results Due to the lack of publicly available pipelines, which could perform fast reference-based assemblies on raw SARS-CoV-2 sequences in addition to identifying lineages to detect variants of concern, we have developed an open source bioinformatic pipeline called HaVoC (Helsinki university Analyzer for Variants Of Concern). HaVoC can reference assemble raw sequence reads and assign the corresponding lineages to SARS-CoV-2 sequences. Conclusions HaVoC is a pipeline utilizing several bioinformatic tools to perform multiple necessary analyses for investigating genetic variance among SARS-CoV-2 samples. The pipeline is particularly useful for those who need a more accessible and fast tool to detect and monitor the spread of SARS-CoV-2 variants of concern during local outbreaks. HaVoC is currently being used in Finland for monitoring the spread of SARS-CoV-2 variants. HaVoC user manual and source code are available at https://www.helsinki.fi/en/projects/havoc and https://bitbucket.org/auto_cov_pipeline/havoc , respectively.

Purpose: Schirmer Strips and Conjunctival swabs are used in ophthalmology for tears and fluids collection. During the COVID-19 pandemic, one of the biggest challenges is accurate diagnosis, and it is known that, in some cases, ocular manifestations are one of the first symptoms. In this context, this study has the objective of raising scientific evidence that highlights the use of Schirmer strips and conjunctival swabs as a method of sample collection for viral analysis to support future research on this theme. Methods: A literature search was conducted in the PubMed, Web of Science and BVS databases, following the Scoping Review protocol defined by Joanna Briggs Institute (JBI) after the guiding question “Is it possible to detect viruses on the ocular surface with Schirmer Test and/or conjunctival swab?”. Results: A total of 418 studies were identified, and after discerning analysis, 36 English written studies were selected. Three researchers analyzed studies after virus research, collection methods, and sample analysis. Publications were mainly on adenovirus, herpes simplex virus and SARS-CoV-2, and there is also evidence of ocular detection of more viruses types. Conjuntival swab analyzed through Polymerase Chain Reaction (PCR) or Reverse Transcriptase-PCR (RT-PCR) were the most used methods. Conclusions: Studies have generally been conducted to understand viral infection, to develop accurate diagnostic methods and to follow the patients’ response to treatment. Most studies were performed with a small number of patients and lacked clear definitions of collection time and viral persistence since the onset of diseases. Viruses can be detected on the ocular surface through the analysis of Schirmer strips and conjunctival swabs. However, additional studies with larger populations and time permanence are necessary to develop more assertive conclusions on the theme.

Most vertebrate RNA viruses show pervasive suppression of CpG and UpA dinucleotides, closely resembling the dinucleotide composition of host cell transcriptomes. In contrast, CpG suppression is absent in both invertebrate mRNA and RNA viruses that exclusively infect arthropods. Arthropod-borne (arbo) viruses are transmitted between vertebrate hosts by invertebrate vectors and thus encounter potentially conflicting evolutionary pressures in the different cytoplasmic environments. Using a newly developed Zika virus (ZIKV) model, we have investigated how demands for CpG suppression in vertebrate cells can be reconciled with potentially quite different compositional requirements in invertebrates, and how this affects ZIKV replication and transmission. Mutant viruses with synonymously elevated CpG or UpA dinucleotide frequencies showed attenuated replication in vertebrate cell lines, which was rescued by knockout of the zinc-finger antiviral protein (ZAP). Conversely, in mosquito cells, ZIKV mutants with elevated CpG dinucleotide frequencies showed substantially enhanced replication compared to wildtype. Host-driven effects on virus replication attenuation and enhancement were even more apparent in mouse and mosquito models. Infections with CpG-or UpA-high ZIKV mutants in mice did not cause typical ZIKV-induced tissue damage and completely protected mice during subsequent challenge with wildtype virus, which demonstrates their potential as live-attenuated vaccines. In contrast, the CpG-high mutants displayed enhanced replication in Aedes aegypti mosquitoes and a larger proportion of mosquitoes carried infectious virus in their saliva. These findings show that mosquito cells are also capable of discriminating RNA based on dinucleotide composition. However, the evolutionary pressure on the CpG dinucleotides of viral genomes in arthropod vectors directly opposes the pressure present in vertebrate host cells, which provides evidence that an adaptive compromise is required for arbovirus transmission. This suggests that the genome composition of arthropod-borne flaviviruses is crucial to maintain the balance between high-level replication in the vertebrate host and persistent replication in the mosquito vector.

Neurological complications of infection by the mosquito-borne Zika virus (ZIKV) include Guillain-Barré syndrome (GBS), an acute inflammatory demyelinating polyneuritis. GBS was first associated with recent ZIKV epidemics caused by the emergence of ZIKV Asian lineage in South Pacific. Here, we hypothesize that ZIKV-associated GBS relates to a molecular mimicry between viral envelope E (E) protein and neural proteins involved in GBS. Analysis of ZIKV epidemic strains showed that glycan loop (GL) region of the E protein includes an IVNDT motif which is conserved in voltage-dependent L-type calcium channel subunit alpha-1C (Cav1.2) and Heat Shock 70 kDa protein 12A (HSP70 12A). Both VSCC-alpha 1C and HSP70 12A belong to protein families which have been associated with neurological autoimmune diseases in central nervous system. The purpose of our in silico analysis is to point out that IVNDT motif of ZIKV E-GL region should be taken in consideration for the development of safe and effective anti-Zika vaccines by precluding the possibility of adverse neurologic events including autoimmune diseases such as GBS.