What we know and what we need to know about the origin of SARS-CoV-2

Symptom propagation in respiratory pathogens of public health concern: a review of the evidence

Symptom propagation occurs when the symptom set an individual experiences is correlated with the symptom set of the individual who infected them. Symptom propagation may dramatically affect epidemiological outcomes, potentially causing clusters of severe disease. Conversely, it could result in chains of mild infection, generating widespread immunity with minimal cost to public health. Despite accumulating evidence that symptom propagation occurs for many respiratory pathogens, the underlying mechanisms are not well understood. Here, we conducted a scoping literature review for 14 respiratory pathogens to ascertain the extent of evidence for symptom propagation by two mechanisms: dose-severity relationships and route-severity relationships. We identify considerable heterogeneity between pathogens in the relative importance of the two mechanisms, highlighting the importance of pathogen-specific investigations. For almost all pathogens, including influenza and SARS-CoV-2, we found support for at least one of the two mechanisms. For some pathogens, including influenza, we found convincing evidence that both mechanisms contribute to symptom propagation. Furthermore, infectious disease models traditionally do not include symptom propagation. We summarize the present state of modelling advancements to address the methodological gap. We then investigate a simplified disease outbreak scenario, finding that under strong symptom propagation, isolating mildly infected individuals can have negative epidemiological implications.

Analysing role of airborne particulate matter in abetting SARS-CoV-2 outbreak for scheming regional pandemic regulatory modalities

The mutating SARS-CoV-2 necessitates gauging the role of airborne particulate matter in the COVID-19 outbreak for designing area-specific regulation modalities based on the environmental state-of-affair. To scheme the protocols, the hotspots of air pollutants such as PM2.5, PM10, NH3, NO, NO2, SO2, and and environmental factors including relative humidity (RH), and temperature, along with COVID-19 cases and mortality from January 2020 till December 2020 from 29 different ground monitoring stations spanning Delhi, are mapped. Spearman correlation coefficients show a positive relationship between SARS-COV-2 with particulate matter (PM2.5 with r > 0.36 and PM10 with r > 0.31 and p-value <0·001). Besides, SARS-COV-2 transmission showed a substantial correlation with NH3 (r = 0.41), NO2 (r = 0.36), and NO (r = 0.35) with a p-value <0.001, which is highly indicative of their role in SARS-CoV-2 transmission. These outcomes are associated with the source of PM and its constituent trace elements to understand their overtone with COVID-19. This strongly validates temporal and spatial variation in COVID-19 dependence on air pollutants as well as on environmental factors. Besides, the bottlenecks of missing latent data, monotonous dependence of variables, and the role air pollutants with secondary environmental variables are discussed. The analysis set the foundation for strategizing regional-based modalities considering environmental variables (i.e., pollutant concentration, relative humidity, temperature) as well as urban and transportation planning for efficient control and handling of future public health emergencies.

Environmental spillover of emerging viruses: Is it true?

The concept of environmental "spillover" of pathogens to humans is widely used in the scientific literature about emerging diseases with the idea that it is scientifically proven. However, the exact characterization of the mechanism of spillover is simply lacking. A systematic review retrieved 688 articles using this term. The systematic analysis revealed an irreducible polysemy covering ten different definitions. It also demonstrated the absence of explicit definition in most of the articles, and even antinomies. A modeling analysis of the various processes described by these ten definitions showed that none of them corresponded to the complete trajectory leading to the emergence of a disease. There is no article demonstrating a mechanism of spillover. There are only ten articles proposing ideas on how a putative spillover could work but they merely are intellectual constructions. All other articles only reuse the term with no demonstration. It is essential to understand that since there is no scientific concept behind the "spillover", it might be dangerous to base public health and public protection against future pandemics on it.

COVID-19 knowledge deconstruction and retrieval: an intelligent bibliometric solution

COVID-19 has been an unprecedented challenge that disruptively reshaped societies and brought a massive amount of novel knowledge to the scientific community. However, as this knowledge flood continues surging, researchers have been disadvantaged by not having access to a platform that can quickly synthesize emerging information and link the new knowledge to the latent knowledge foundation. Aiming to fill this gap, we propose a research framework and develop a dashboard that can assist scientists in identifying, retrieving, and understanding COVID-19 knowledge from the ocean of scholarly articles. Incorporating principal component decomposition (PCD), a knowledge mode-based search approach, and hierarchical topic tree (HTT) analysis, the proposed framework profiles the COVID-19 research landscape, retrieves topic-specific latent knowledge foundation, and visualizes knowledge structures. The regularly updated dashboard presents our research results. Addressing 127,971 COVID-19 research papers from PubMed, the PCD topic analysis identifies 35 research hotspots, along with their inner correlations and fluctuating trends. The HTT result segments the global knowledge landscape of COVID-19 into clinical and public health branches and reveals the deeper exploration of those studies. To supplement this analysis, we additionally built a knowledge model from research papers on the topic of vaccination and fetched 92,286 pre-Covid publications as the latent knowledge foundation for reference. The HTT analysis results on the retrieved papers show multiple relevant biomedical disciplines and four future research topics: monoclonal antibody treatments, vaccinations in diabetic patients, vaccine immunity effectiveness and durability, and vaccination-related allergic sensitization.

Updated analysis to reject the laboratory-engineering hypothesis of SARS-CoV-2

A clear understanding of the origin of SARS-CoV-2 is important for future pandemic preparedness. Here, I provided an updated analysis of the type IIS endonuclease maps in genomes of alphacoronavirus, betacoronavirus, and SARS-CoV-2. Scenarios to engineer SARS-CoV-2 in the laboratory and the associated workload was also discussed. The analysis clearly shows that the endonuclease fingerprint does not indicate a synthetic origin of SARS-CoV-2 and engineering a SARS-CoV-2 virus in the laboratory is extremely challenging both scientifically and financially. On the contrary, current scientific evidence does support the animal origin of SARS-CoV-2.

The concentrations of essential/toxic elements in serum of COVID-19 patients are not directly related to the severity of the disease

BACKGROUND

In recent months, the current COVID-19 pandemic has generated thousands of studies directly or indirectly related with this disease and/or the coronavirus SARS-CoV-2 causing the infection. On August 22, 2022, the database PUBMED included 287,639 publications containing the term COVID-19. However, in spite of the importance of trace elements in human health, including the immune system, data on the levels of metals/metalloids in COVID-19 patients is very limited.

METHODS

The concentrations of As, Cd, Cr, Cu, Hg, Fe, Mg, Mn, Pb, Se, V and Zn were determined by inductively coupled plasma-mass spectrometry (ICP-MS) in 126 serum samples of individuals infected with SARS-CoV-2, as well as in 88 samples of non-infected individuals. Participants were divided into four groups: i) individuals COVID-19 positive (COVID-19 +) with an asymptomatic infection course; ii) individuals suffering mild COVID-19; iii) individuals suffering severe COVID-19, and iv) individuals COVID-19 negative (COVID-19-) (control group). The occurrence of the analyzed metals/metalloids was evaluated along with the biochemical profile, including blood cell counts, lipids, proteins and crucial enzymes.

RESULTS

Serum levels of Mg, V, Cr, Cu, Cd, and Pb were higher in COVID-19 positive patients than those in the control group. Although no significant differences were observed between the different groups of patients, the concentrations of Cd, Pb, V and Zn showed a tendency to be higher in individuals with severe COVID-19 than in those showing mild symptoms or being asymptomatic. Arsenic and Hg were rarely detected, regardless if the subjects were infected by SARS-CoV-2, or not. The current results did not show significant differences in the levels of the rest of analyzed elements according to the severity of the disease (asymptomatic, mild and severe).

CONCLUSIONS

In spite of the results here obtained, we highlight the need to reduce the exposure to Cd, Pb and V to minimize the potential adverse health outcomes after COVID-19 infection. On the other hand, although a protective role of essential elements was not found, Mg and Cu concentrations were higher in severe COVID-19 patients than in non-infected individuals.

RADIC:A tool for diagnosing COVID-19 from chest CT and X-ray scans using deep learning and quad-radiomics

Deep learning (DL) algorithms have demonstrated a high ability to perform speedy and accurate COVID-19 diagnosis utilizing computed tomography (CT) and X-Ray scans. The spatial information in these images was used to train DL models in the majority of relevant studies. However, training these models with images generated by radiomics approaches could enhance diagnostic accuracy. Furthermore, combining information from several radiomics approaches with time-frequency representations of the COVID-19 patterns can increase performance even further. This study introduces "RADIC", an automated tool that uses three DL models that are trained using radiomics-generated images to detect COVID-19. First, four radiomics approaches are used to analyze the original CT and X-ray images. Next, each of the three DL models is trained on a different set of radiomics, X-ray, and CT images. Then, for each DL model, deep features are obtained, and their dimensions are decreased using the Fast Walsh Hadamard Transform, yielding a time-frequency representation of the COVID-19 patterns. The tool then uses the discrete cosine transform to combine these deep features. Four classification models are then used to achieve classification. In order to validate the performance of RADIC, two benchmark datasets (CT and X-Ray) for COVID-19 are employed. The final accuracy attained using RADIC is 99.4% and 99% for the first and second datasets respectively. To prove the competing ability of RADIC, its performance is compared with related studies in the literature. The results reflect that RADIC achieve superior performance compared to other studies. The results of the proposed tool prove that a DL model can be trained more effectively with images generated by radiomics techniques than the original X-Ray and CT images. Besides, the incorporation of deep features extracted from DL models trained with multiple radiomics approaches will improve diagnostic accuracy.

UncertaintyFuseNet: Robust uncertainty-aware hierarchical feature fusion model with Ensemble Monte Carlo Dropout for COVID-19 detection

The COVID-19 (Coronavirus disease 2019) pandemic has become a major global threat to human health and well-being. Thus, the development of computer-aided detection (CAD) systems that are capable of accurately distinguishing COVID-19 from other diseases using chest computed tomography (CT) and X-ray data is of immediate priority. Such automatic systems are usually based on traditional machine learning or deep learning methods. Differently from most of the existing studies, which used either CT scan or X-ray images in COVID-19-case classification, we present a new, simple but efficient deep learning feature fusion model, called U n c e r t a i n t y F u s e N e t , which is able to classify accurately large datasets of both of these types of images. We argue that the uncertainty of the model's predictions should be taken into account in the learning process, even though most of the existing studies have overlooked it. We quantify the prediction uncertainty in our feature fusion model using effective Ensemble Monte Carlo Dropout (EMCD) technique. A comprehensive simulation study has been conducted to compare the results of our new model to the existing approaches, evaluating the performance of competing models in terms of Precision, Recall, F-Measure, Accuracy and ROC curves. The obtained results prove the efficiency of our model which provided the prediction accuracy of 99.08% and 96.35% for the considered CT scan and X-ray datasets, respectively. Moreover, our U n c e r t a i n t y F u s e N e t model was generally robust to noise and performed well with previously unseen data. The source code of our implementation is freely available at: https://github.com/moloud1987/UncertaintyFuseNet-for-COVID-19-Classification.

The ecosyndemic framework of the global environmental change and the COVID-19 pandemic

The ecosyndemic theory combines the concept of 'synergy' with 'epidemic' and the term "eco" implies the role of the environmental changes. Each of the conditions enhances the negative impacts of the other in an additive way making our society more vulnerable and heightening individual risk factors. In this study, we analyze the mutually reinforcing links between the environment and health from the complexity angle of the ecosyndemic theory and propose the characterization of the COVID-19 pandemic as ecosyndemic. We use the term 'ecosyndemic' because the global environmental change contributes to local-scale, regional-scale and global-scale alterations of the Earth's systems. These changes have their root causes in the way that people interact with the physical, chemical, and biotic factors of the environment. These interactions disturb nature and the consequences have feedbacks in every living organism.

Scientific evidence on the origin of SARS-CoV-2

Even reaching the end of the year 2022, there is still a controversy on the origin of the SARS-CoV-2 virus. This Virtual Special Issue (VSI), focused on the "Scientific evidence on the origin of SARS-CoV-2", was launched some months ago with the aim of stimulating the submission of new high quality scientific research papers on the matter, to shed light on it. As indicated in the call for papers, the Editors involved in the VSI were aware of the difficulties of presenting concluding facts on that issue, however, bearing in mind that some teams of researchers had started investigations regarding this subject, a VSI like this (searching for stimulating the scientific controversy while requiring scientific evidence), could help to elucidate complicated aspects, going a step ahead in this way. The Editors made a call encouraging interested teams of researchers having solid results to submit high quality manuscripts dealing with this crucial theme. We thought -and we still think-that it is of maximum interest for the scientific community, as well as for the whole society, now and probably for the future. The VSI have received 50 submissions, which could be considered a limited number highlighting the difficulties of elaborating new high-quality manuscripts providing solid evidence on the matter. After a careful peer-review, those manuscripts considered to reach the highest scientific value were accepted for publication. The Editors think that the set of papers included in this VSI constitute interesting and high-quality contributions, providing further scientific knowledge on this issue. In this editorial piece, the Editors make some comments on the papers published, including some additional reflections.

Anti-cancer Virotherapy in Russia: Lessons from the Past, Current Challenges and Prospects for the Future

The idea of using the lytic power of viruses against malignant cells has been entertained for many decades. However, oncolytic viruses gained broad attention as an emerging anti-cancer therapy only recently with the successful implementation of several oncolytic viruses to treat advanced melanoma. Here we review the history of oncolytic viruses in the Russian Federation and recent biotechnological advances in connection with the perspectives of their practical use against aggressive tumors such as glioblastoma or pancreatic cancer. A particular emphasis is made on novel applications of safe non-lytic virus-derived vectors armed with prodrug-converting enzyme transgenes. Rational improvement of oncotropism by conjugation with biopolymers and nanoformulations is also discussed.

Licht und Covid-19 — Ein Update

Licht, Laser und Akupunktur haben auch in der aktuellen Pandemie wichtige Beiträge zur Medizin geleistet. Hauptziel einer vor kurzem veröffentlichten Übersichtsarbeit war es zu untersuchen, wie Licht als therapeutische Methode während der durch COVID-19 ausgelösten Krise bislang eingesetzt wurde. Ein weiteres Ziel ist es, Wissenschaftlerinnen und Wissenschaftler sowie die Industrie zu ermutigen, schnell neue einfache Verfahren der Photobiomodulationstherapie (PBMT) und/oder photodynamischen Therapie (PDT) für zu Hause zu entwickeln. Die bisherigen Ergebnisse zeigten, dass PBMT teilweise erfolgreich bei SARSCoV-2-Infektionen angewendet werden kann und signifikante Verbesserungen bei Atemwegsentzündungen und dem allgemeinen klinischen Zustand der Patientinnen und Patienten ermöglichte. Die Anwendung nur in einer begrenzten Anzahl von Fällen impliziert die Notwendigkeit zukünftiger randomisierter, placebokontrollierter klinischer Studien, um die Wirkung von PBMT und PDT bei COVID-19 tatsächlich zu objektivieren. Bei dieser anhaltenden und herausfordernden Suche nach dem scheinbar nicht greifbaren Ende dieser Pandemie scheinen die PBMT und PDT nicht-invasive, leicht zugängliche, sichere und nebenwirkungsfreie Methoden zu sein.

Understanding risk factors of a new variant outburst through global analysis of Omicron transmissibility

The emergence of a new virus variant is generally recognized by its usually sudden and rapid spread (outburst) in a certain world region. Due to the near-exponential rate of initial expansion, the new strain may not be detected at its true geographical origin but in the area with the most favorable conditions leading to the fastest exponential growth. Therefore, it is crucial to understand better the factors that promote such outbursts, which we address in the example of analyzing global Omicron transmissibility during its global emergence/outburst in November 2021-February 2022. As predictors, we assemble a number of potentially relevant factors: vaccinations (both full and boosters), different measures of population mobility (provided by Google), estimated stringency of measures, the prevalence of chronic diseases, population age, the timing of the outburst, and several other socio-demographic variables. As a proxy for natural immunity (prevalence of prior infections in population), we use cumulative numbers of COVID-19 deaths. As a response variable (transmissibility measure), we use the estimated effective reproduction number (R_e) averaged in the vicinity of the outburst maxima. To select significant predictors of R_e, we use machine learning regressions that employ feature selection, including methods based on ensembles of decision trees (Random Forest and Gradient Boosting). We identify the young population, earlier infection onset, higher mobility, low natural immunity, and low booster prevalence as likely direct risk factors. Interestingly, we find that all these risk factors were significantly higher for Africa, though curiously somewhat lower in Southern African countries (where the outburst emerged) compared to other African countries. Therefore, while the risk factors related to the virus transmissibility clearly promote the outburst of a new virus variant, specific regions/countries where the outburst actually happens may be related to less evident factors, possibly random in nature.

An updated review of the scientific literature on the origin of SARS-CoV-2

More than two and a half years have already passed since the first case of COVID-19 was officially reported (December 2019), as well as more than two years since the WHO declared the current pandemic (March 2020). During these months, the advances on the knowledge of the COVID-19 and SARS-CoV-2, the coronavirus responsible of the infection, have been very significant. However, there are still some weak points on that knowledge, being the origin of SARS-CoV-2 one of the most notorious. One year ago, I published a review focused on what we knew and what we need to know about the origin of that coronavirus, a key point for the prevention of potential future pandemics of a similar nature. The analysis of the available publications until July 2021 did not allow drawing definitive conclusions on the origin of SARS-CoV-2. Given the great importance of that issue, the present review was aimed at updating the scientific information on that origin. Unfortunately, there have not been significant advances on that topic, remaining basically the same two hypotheses on it. One of them is the zoonotic origin of SARS-CoV-2, while the second one is the possible leak of this coronavirus from a laboratory. Most recent papers do not include observational or experimental studies, being discussions and positions on these two main hypotheses. Based on the information here reviewed, there is not yet a definitive and well demonstrated conclusion on the origin of SARS-CoV-2.

SARS-CoV-2 Variants of Concern and Variations within Their Genome Architecture: Does Nucleotide Distribution and Mutation Rate Alter the Functionality and Evolution of the Virus?

SARS-CoV-2 virus pathogenicity and transmissibility are correlated with the mutations acquired over time, giving rise to variants of concern (VOCs). Mutations can significantly influence the genetic make-up of the virus. Herein, we analyzed the SARS-CoV-2 genomes and sub-genomic nucleotide composition in relation to the mutation rate. Nucleotide percentage distributions of 1397 in-house-sequenced SARS-CoV-2 genomes were enumerated, and comparative analyses (i) within the VOCs and of (ii) recovered and mortality patients were performed. Fisher's test was carried out to highlight the significant mutations, followed by RNA secondary structure prediction and protein modeling for their functional impacts. Subsequently, a uniform dinucleotide composition of AT and GC was found across study cohorts. Notably, the N gene was observed to have a high GC percentage coupled with a relatively higher mutation rate. Functional analysis demonstrated the N gene mutations, C29144T and G29332T, to induce structural changes at the RNA level. Protein secondary structure prediction with N gene missense mutations revealed a differential composition of alpha helices, beta sheets, and coils, whereas the tertiary structure displayed no significant changes. Additionally, the N gene CTD region displayed no mutations. The analysis highlighted the importance of N protein in viral evolution with CTD as a possible target for antiviral drugs.

RASCL: Rapid Assessment of Selection in CLades through molecular sequence analysis

An important unmet need revealed by the COVID-19 pandemic is the near-real-time identification of potentially fitness-altering mutations within rapidly growing SARS-CoV-2 lineages. Although powerful molecular sequence analysis methods are available to detect and characterize patterns of natural selection within modestly sized gene-sequence datasets, the computational complexity of these methods and their sensitivity to sequencing errors render them effectively inapplicable in large-scale genomic surveillance contexts. Motivated by the need to analyze new lineage evolution in near-real time using large numbers of genomes, we developed the Rapid Assessment of Selection within CLades (RASCL) pipeline. RASCL applies state of the art phylogenetic comparative methods to evaluate selective processes acting at individual codon sites and across whole genes. RASCL is scalable and produces automatically updated regular lineage-specific selection analysis reports: even for lineages that include tens or hundreds of thousands of sampled genome sequences. Key to this performance is (i) generation of automatically subsampled high quality datasets of gene/ORF sequences drawn from a selected "query" viral lineage; (ii) contextualization of these query sequences in codon alignments that include high-quality "background" sequences representative of global SARS-CoV-2 diversity; and (iii) the extensive parallelization of a suite of computationally intensive selection analysis tests. Within hours of being deployed to analyze a novel rapidly growing lineage of interest, RASCL will begin yielding JavaScript Object Notation (JSON)-formatted reports that can be either imported into third-party analysis software or explored in standard web-browsers using the premade RASCL interactive data visualization dashboard. By enabling the rapid detection of genome sites evolving under different selective regimes, RASCL is well-suited for near-real-time monitoring of the population-level selective processes that will likely underlie the emergence of future variants of concern in measurably evolving pathogens with extensive genomic surveillance.

An active learning-based approach for screening scholarly articles about the origins of SARS-CoV-2

To build a full picture of previous studies on the origins of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2), this paper exploits an active learning-based approach to screen scholarly articles about the origins of SARS-CoV-2 from many scientific publications. In more detail, six seed articles were utilized to manually curate 170 relevant articles and 300 nonrelevant articles. Then, an active learning-based approach with three query strategies and three base classifiers is trained to screen the articles about the origins of SARS-CoV-2. Extensive experimental results show that our active learning-based approach outperforms traditional counterparts, and the uncertain sampling query strategy performs best among the three strategies. By manually checking the top 1,000 articles of each base classifier, we ultimately screened 715 unique scholarly articles to create a publicly available peer-reviewed literature corpus, COVID-Origin. This indicates that our approach for screening articles about the origins of SARS-CoV-2 is feasible.

Elucidating the role of environmental management of forests, air quality, solid waste and wastewater on the dissemination of SARS-CoV-2

The increasing frequency of zoonotic diseases is amongst several catastrophic repercussions of inadequate environmental management. Emergence, prevalence, and lethality of zoonotic diseases is intrinsically linked to environmental management which are currently at a destructive level globally. The effects of these links are complicated and interdependent, creating an urgent need of elucidating the role of environmental mismanagement to improve our resilience to future pandemics. This review focused on the pertinent role of forests, outdoor air, indoor air, solid waste and wastewater management in COVID-19 dissemination to analyze the opportunities prevailing to control infectious diseases considering relevant data from previous disease outbreaks. Global forest management is currently detrimental and hotspots of forest fragmentation have demonstrated to result in zoonotic disease emergences. Deforestation is reported to increase susceptibility to COVID-19 due to wildfire induced pollution and loss of forest ecosystem services. Detection of SARS-CoV-2 like viruses in multiple animal species also point to the impacts of biodiversity loss and forest fragmentation in relation to COVID-19. Available literature on air quality and COVID-19 have provided insights into the potential of air pollutants acting as plausible virus carrier and aggravating immune responses and expression of ACE2 receptors. SARS-CoV-2 is detected in outdoor air, indoor air, solid waste, wastewater and shown to prevail on solid surfaces and aerosols for prolonged hours. Furthermore, lack of protection measures and safe disposal options in waste management are evoking concerns especially in underdeveloped countries due to high infectivity of SARS-CoV-2. Inadequate legal framework and non-adherence to environmental regulations were observed to aggravate the postulated risks and vulnerability to future waves of pandemics. Our understanding underlines the urgent need to reinforce the fragile status of global environmental management systems through the development of strict legislative frameworks and enforcement by providing institutional, financial and technical supports.

SARS-CoV-2 origins: zoonotic Rhinolophus vs contemporary models

The question of the origin of coronavirus spread like wildfire ever since it wreaked havoc among humankind, and ever since the scientific community has worked tirelessly to trace the history of the virus. In this review, we have tried to compile relevant literature pertaining to the different theories of origin of SARS-CoV-2, hopefully without any bias, and we strongly support the zoonotic origin of the infamous SARS-CoV-2 in bats and its transfer to human beings through the most probable evolutionary hosts, pangolins and minks. We also support the contemporary 'Circulation Model' that simply mirrors the concept of evolution to explain the origin of the virus which, the authors believe, is the most rational school of thought. The most recent variant of SARS-CoV-2, Omicron, has been taken as an example to clarify the concept. We recommend the community to refer to this model for further understanding and delving deep into this mystery of the origin of SARS-CoV-2.

Sports Participation and Anti-Epidemic: Empirical Evidence on the Influence of Regular Physical Activity on the COVID-19 Pandemic in Mainland China

This study aims to investigate the effects and influencing mechanisms of regular physical activity (RPA) on the COVID-19 pandemic. Daily data from 279 prefecture-level cities in mainland China were collected from 1 January to 17 March 2020. A two-way fixed-effects model was used to identify the causal relationship between physical activity and COVID-19, while also considering factors such as patterns of human behavior and socioeconomic conditions. The instrumental variable (IV) approach was applied to address potential endogeneity issues for a more accurate causal identification, and the mediating effect model was applied to examine the mechanisms of the influence of physical activity on the epidemic. We found that regular physical activity significantly improves individual immunity, which, in turn, leads to a reduction in the probability of being infected with COVID-19. Furthermore, we investigated the heterogeneity of the influence, finding that the negative impact of physical activity on the pandemic is more pronounced in the absence of adequate medical resources, strong awareness of prevention among residents, and fully implemented public health measures. Our results provide empirical evidence for the mechanisms of influence of physical activity on the pandemic. We would suggest that not only should physical activity be actively practiced during the pandemic, but also long-term regular exercise habits should be consciously cultivated to improve the ability of the individual immune system to better cope with sudden outbreaks of emerging infectious diseases.

Covariance predicts conserved protein residue interactions important for the emergence and continued evolution of SARS-CoV-2 as a human pathogen

SARS-CoV-2 is one of three recognized coronaviruses (CoVs) that have caused epidemics or pandemics in the 21st century and that likely emerged from animal reservoirs. Differences in nucleotide and protein sequence composition within related β-coronaviruses are often used to better understand CoV evolution, host adaptation, and their emergence as human pathogens. Here we report the comprehensive analysis of amino acid residue changes that have occurred in lineage B β-coronaviruses that show covariance with each other. This analysis revealed patterns of covariance within conserved viral proteins that potentially define conserved interactions within and between core proteins encoded by SARS-CoV-2 related β-coronaviruses. We identified not only individual pairs but also networks of amino acid residues that exhibited statistically high frequencies of covariance with each other using an independent pair model followed by a tandem model approach. Using 149 different CoV genomes that vary in their relatedness, we identified networks of unique combinations of alleles that can be incrementally traced genome by genome within different phylogenic lineages. Remarkably, covariant residues and their respective regions most abundantly represented are implicated in the emergence of SARS-CoV-2 and are also enriched in dominant SARS-CoV-2 variants.

Viral Nucleases from Herpesviruses and Coronavirus in Recombination and Proofreading: Potential Targets for Antiviral Drug Discovery

In this review, we explore recombination in two very different virus families that have become major threats to human health. The Herpesviridae are a large family of pathogenic double-stranded DNA viruses involved in a range of diseases affecting both people and animals. Coronaviridae are positive-strand RNA viruses (CoVs) that have also become major threats to global health and economic stability, especially in the last two decades. Despite many differences, such as the make-up of their genetic material (DNA vs. RNA) and overall mechanisms of genome replication, both human herpes viruses (HHVs) and CoVs have evolved to rely heavily on recombination for viral genome replication, adaptation to new hosts and evasion of host immune regulation. In this review, we will focus on the roles of three viral exonucleases: two HHV exonucleases (alkaline nuclease and PolExo) and one CoV exonuclease (ExoN). We will review the roles of these three nucleases in their respective life cycles and discuss the state of drug discovery efforts against these targets.

Mapping Genetic Events of SARS-CoV-2 Variants

Genetic mutation and recombination are driving the evolution of SARS-CoV-2, leaving many genetic imprints which could be utilized to track the evolutionary pathway of SARS-CoV-2 and explore the relationships among variants. Here, we constructed a complete genetic map, showing the explicit evolutionary relationship among all SARS-CoV-2 variants including 58 groups and 46 recombination types identified from 3,392,553 sequences, which enables us to keep well informed of the evolution of SARS-CoV-2 and quickly determine the parents of novel variants. We found that the 5' and 3' of the spike and nucleoprotein genes have high frequencies to form the recombination junctions and that the RBD region in S gene is always exchanged as a whole. Although these recombinants did not show advantages in community transmission, it is necessary to keep a wary eye on the novel genetic events, in particular, the mutants with mutations on spike and recombinants with exchanged moieties on spike gene.

Celiac Disease and Targeting the Molecular Mechanisms of Autoimmunity in COVID Pandemic

Celiac disease (CD) comprises over 1% of the world’s population and is a chronic multisystem immune-mediated condition manifested by digestive and/or extradigestive symptoms caused by food intake of gluten. This review looked at the risk of children diagnosed with CD developing SARS-CoV-2 infection and possible severe forms of COVID-19. A better understanding of the interaction and effects of SARS-CoV-2 infection in CD is very important, as is the role of environmental and genetic factors, but especially the molecular mechanisms involved in modulating intestinal permeability with impact on autoimmunity. CD inspired the testing of a zonulin antagonist for the fulminant form of multisystem inflammatory syndrome in children (MIS-C) and paved the way for the discovery of new molecules to regulate the small intestine barrier function and immune responses. Original published works on COVID-19 and CD, new data and points of view have been analyzed because this dangerous virus SARS-CoV-2 is still here and yet influencing our lives. Medical science continues to focus on all uncertainties triggered by SARS-CoV-2 infection and its consequences, including in CD. Although the COVID-19 pandemic seems to be gradually extinguishing, there is a wealth of information and knowledge gained over the last two years and important life lessons to analyze, as well as relevant conclusions to be drawn to deal with future pandemics. Zonulin is being studied extensively in immunoengineering as an adjuvant to improving the absorption of new drugs and oral vaccines.

Celiac Disease and Targeting the Molecular Mechanisms of Autoimmunity in COVID Pandemic

Celiac disease (CD) comprises over 1% of the world's population and is a chronic multisystem immune-mediated condition manifested by digestive and/or extradigestive symptoms caused by food intake of gluten. This review looked at the risk of children diagnosed with CD developing SARS-CoV-2 infection and possible severe forms of COVID-19. A better understanding of the interaction and effects of SARS-CoV-2 infection in CD is very important, as is the role of environmental and genetic factors, but especially the molecular mechanisms involved in modulating intestinal permeability with impact on autoimmunity. CD inspired the testing of a zonulin antagonist for the fulminant form of multisystem inflammatory syndrome in children (MIS-C) and paved the way for the discovery of new molecules to regulate the small intestine barrier function and immune responses. Original published works on COVID-19 and CD, new data and points of view have been analyzed because this dangerous virus SARS-CoV-2 is still here and yet influencing our lives. Medical science continues to focus on all uncertainties triggered by SARS-CoV-2 infection and its consequences, including in CD. Although the COVID-19 pandemic seems to be gradually extinguishing, there is a wealth of information and knowledge gained over the last two years and important life lessons to analyze, as well as relevant conclusions to be drawn to deal with future pandemics. Zonulin is being studied extensively in immunoengineering as an adjuvant to improving the absorption of new drugs and oral vaccines.

GenomeBits insight into omicron and delta variants of coronavirus pathogen

We apply the new GenomeBits method to uncover underlying genomic features of omicron and delta coronavirus variants. This is a statistical algorithm whose salient feature is to map the nucleotide bases into a finite alternating (±) sum series of distributed terms of binary (0,1) indicators. We show how by this method, distinctive signals can be uncovered out of the intrinsic data organization of amino acid progressions along their base positions. Results reveal a sort of ‘ordered’ (or constant) to ‘disordered’ (or peaked) transition around the coronavirus S-spike protein region. Together with our previous results for past variants of coronavirus: Alpha, Beta, Gamma, Epsilon and Eta, we conclude that the mapping into GenomeBits strands of omicron and delta variants can help to characterize mutant pathogens.

Le virus SARS-CoV-2 n’a pas « d’origine »

Depuis le début de la pandémie de COVID-19, la question de l’origine de ce virus fait l’objet d’une vive polémique. C’est la question de « l’origine » qui est biaisée. Darwin a montré qu’il n’y a pas d’origine déterminée à aucune espèce animale ou végétale, simplement un processus évolutif et sélectif. Il en est de même pour les virus, il n’y a pas d’origine, mais un processus évolutif. Les virus circulent d’hôte à hôte, animaux ou humains. Les virus pandémiques circulent déjà chez l’homme et évoluent avant l’apparition d’une maladie. Ce processus évolutif se poursuit et donne naissance à des variants successifs. La solution n’est pas de cibler la maladie ou le possible agent causal, mais plutôt de cibler le processus d’émergence de la maladie lui-même.

There is no "origin" to SARS-CoV-2

Since the beginning of the COVID-19 pandemic in 2020 caused by SARS-CoV-2, the question of the origin of this virus has been a highly debated issue. Debates have been, and are still, very disputed and often violent between the two main hypotheses: a natural origin through the "spillover" model or a laboratory-leak origin. Tenants of these two options are building arguments often based on the discrepancies of the other theory. The main problem is that it is the initial question of the origin itself which is biased. Charles Darwin demonstrated in 1859 that all species are appearing through a process of evolution, adaptation and selection. There is no determined origin to any animal or plant species, simply an evolutionary and selective process in which chance and environment play a key role. The very same is true for viruses. There is no determined origin to viruses, simply also an evolutionary and selective process in which chance and environment play a key role. However, in the case of viruses the process is slightly more complex because the "environment" is another living organism. Pandemic viruses already circulate in humans prior to the emergence of a disease. They are simply not capable of triggering an epidemic yet. They must evolve in-host, i.e. in-humans, for that. The evolutionary process which gave rise to SARS-CoV-2 is still ongoing with regular emergence of novel variants more adapted than the previous ones. The real relevant question is how these viruses can emerge as pandemic viruses and what the society can do to prevent the future emergence of pandemic viruses.

Million Veteran Program's response to COVID-19: Survey development and preliminary findings

BACKGROUND

In response to the novel Coronavirus Disease 2019 (COVID-19) pandemic, the Department of Veterans Affairs (VA) Million Veteran Program (MVP) organized efforts to better understand the impact of COVID-19 on Veterans by developing and deploying a self-reported survey.

METHODS

The MVP COVID-19 Survey was developed to collect COVID-19 specific elements including symptoms, diagnosis, hospitalization, behavioral and psychosocial factors and to augment existing MVP data with longitudinal collection of key domains in physical and mental health. Due to the rapidly evolving nature of the pandemic, a multipronged strategy was implemented to widely disseminate the COVID-19 Survey and capture data using both the online platform and mailings.

RESULTS

We limited the findings of this paper to the initial phase of survey dissemination which began in May 2020. A total of 729,625 eligible MVP Veterans were invited to complete version 1 of the COVID-19 Survey. As of October 31, 2020, 58,159 surveys have been returned. The mean and standard deviation (SD) age of responders was 71 (11) years, 8.6% were female, 8.2% were Black, 5.6% were Hispanic, and 446 (0.8%) self-reported a COVID-19 diagnosis. Over 90% of responders reported wearing masks, practicing social distancing, and frequent hand washing.

CONCLUSION

The MVP COVID-19 Survey provides a systematic collection of data regarding COVID-19 behaviors among Veterans and represents one of the first large-scale, national surveillance efforts of COVID-19 in the Veteran population. Continued work will examine the overall response to the survey with comparison to available VA health record data.

SARS-CoV-2 origin, myths and diagnostic technology developments

Background

After the first case of COVID-19 being announced in China in December 2019, various diagnostic technologies have been developed at unprecedented pace with the aim of providing a basis for accurate clinical intervention. However, some assays including CRISPR-based diagnostics and loop-mediated isothermal amplification (LAMP) have been less explored. As new COVID-19 technologies emerge, there is need for them to be assessed, validated and improved upon. Moreover, there is paucity of data on the essential factors governing the selection of an appropriate diagnostic approach within the correct timeframe. Myths and origin of SARS-CoV-2 remain to be controversial. Consequently, this review aims at exploring the current COVID-19 diagnostic technologies, performance evaluation, principles, suitability, specificity, sensitivity, successes and challenges of the technologies for laboratory and bedside testing.

Main Body

To date, there exist more publications on COVID-19 diagnostics as compared to the Zika virus. The SARS-CoV-2 virus genome profiles were readily available by 31st of December 2019. This was attributed to the fast-paced sharing of the epidemiological and diagnostics data of COVID-19. Timely profiling of the virus genome accelerated the development of diagnostic technologies. Furthermore, the rapid publication of studies that evaluated several diagnostic methods available provided baseline information on how the various technologies work and paved way for development of novel technologies.

Conclusion

Up to date, RT-PCR is the most preferred as compared to the other assays. This is despite the repeated false negatives reported in many of the study findings. Considering that COVID-19 has caused devastating effects on the economy, healthcare systems, agriculture and culture, timely and accurate detection of the virus is paramount in the provision of targeted therapy hence reducing chances of drug resistance, increased treatment costs and morbidity. However, information on the origin of SARS-CoV-2 still remains elusive. Furthermore, knowledge and perception of the patients toward management of SARS-CoV-2 are also paramount to proper diagnosis and management of the pandemic. Future implications of the misperceptions are that they may lead to increased non-compliance to SARS-CoV-2-related World Health Organization (WHO) policies and guidelines.

Periodically aperiodic pattern of SARS-CoV-2 mutations underpins the uncertainty of its origin and evolution

Various lineages of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) have contributed to prolongation of the Coronavirus Disease 2019 (COVID-19) pandemic. Several non-synonymous mutations in SARS-CoV-2 proteins have generated multiple SARS-CoV-2 variants. In our previous report, we have shown that an evenly uneven distribution of unique protein variants of SARS-CoV-2 is geo-location or demography-specific. However, the correlation between the demographic transmutability of the SARS-CoV-2 infection and mutations in various proteins remains unknown due to hidden symmetry/asymmetry in the occurrence of mutations. This study tracked how these mutations are emerging in SARS-CoV-2 proteins in six model countries and globally. In a geo-location, considering the mutations having a frequency of detection of at least 500 in each SARS-CoV-2 protein, we studied the country-wise percentage of invariant residues. Our data revealed that since October 2020, highly frequent mutations in SARS-CoV-2 have been observed mostly in the Open Reading Frame (ORF) 7b and ORF8, worldwide. No such highly frequent mutations in any of the SARS-CoV-2 proteins were found in the UK, India, and Brazil, which does not correlate with the degree of transmissibility of the virus in India and Brazil. However, we have found a signature that SARS-CoV-2 proteins were evolving at a higher rate, and considering global data, mutations are detected in the majority of the available amino acid locations. Fractal analysis of each protein's normalized factor time series showed a periodically aperiodic emergence of dominant variants for SARS-CoV-2 protein mutations across different countries. It was noticed that certain high-frequency variants have emerged in the last couple of months, and thus the emerging SARS-CoV-2 strains are expected to contain prevalent mutations in the ORF3a, membrane, and ORF8 proteins. In contrast to other beta-coronaviruses, SARS-CoV-2 variants have rapidly emerged based on demographically dependent mutations. Characterization of the periodically aperiodic nature of the demographic spread of SARS-CoV-2 variants in various countries can contribute to the identification of the origin of SARS-CoV-2.

Impact of the COVID-19 pandemic on food production and animal health

BACKGROUND

Severe acute respiratory coronavirus syndrome 2 (SARS-CoV-2) is the etiological agent of coronavirus disease 2019 (COVID-19). SARS-CoV-2 was first detected in Wuhan, China and spread to other countries and continents causing a variety of respiratory and non-respiratory symptoms which led to death in severe cases.

SCOPE AND APPROACH

In this review, we discuss and analyze the impact of the COVID-19 pandemic on animal production systems and food production of meat, dairy, eggs, and processed food, in addition to assessing the impact of the pandemic on animal healthcare systems, animal healthcare quality, animal welfare, food chain sustainability, and the global economy. We also provide effective recommendations to animal producers, veterinary healthcare professionals, workers in animal products industries, and governments to alleviate the effects of the pandemic on livestock farming and production systems.

KEY FINDINGS AND CONCLUSIONS

Port restrictions, border restrictions, curfews, and social distancing limitations led to reduced quality, productivity, and competitiveness of key productive sectors. The restrictions have hit the livestock sector hard by disrupting the animal feed supply chain, reducing animal farming services, limiting animal health services including delays in diagnosis and treatment of diseases, limiting access to markets and consumers, and reducing labor-force participation. The inhumane culling of animals jeopardized animal welfare. Egg smashing, milk dumping, and other animal product disruptions negatively impacted food production, consumption, and access to food originating from animals. In summary, COVID-19 triggered lockdowns and limitations on local and international trade have taken their toll on food production, animal production, and animal health and welfare. COVID-19 reverberations could exacerbate food insecurity, hunger, and global poverty. The effects could be massive on the most vulnerable populations and the poorest nations.

SARS-CoV-2 and the Host Cell: A Tale of Interactions

The ability of a virus to spread between individuals, its replication capacity and the clinical course of the infection are macroscopic consequences of a multifaceted molecular interaction of viral components with the host cell. The heavy impact of COVID-19 on the world population, economics and sanitary systems calls for therapeutic and prophylactic solutions that require a deep characterization of the interactions occurring between virus and host cells. Unveiling how SARS-CoV-2 engages with host factors throughout its life cycle is therefore fundamental to understand the pathogenic mechanisms underlying the viral infection and to design antiviral therapies and prophylactic strategies. Two years into the SARS-CoV-2 pandemic, this review provides an overview of the interplay between SARS-CoV-2 and the host cell, with focus on the machinery and compartments pivotal for virus replication and the antiviral cellular response. Starting with the interaction with the cell surface, following the virus replicative cycle through the characterization of the entry pathways, the survival and replication in the cytoplasm, to the mechanisms of egress from the infected cell, this review unravels the complex network of interactions between SARS-CoV-2 and the host cell, highlighting the knowledge that has the potential to set the basis for the development of innovative antiviral strategies.

Positive association between outdoor air pollution and the incidence and severity of COVID-19. A review of the recent scientific evidences

In June 2020, we published a review focused on assessing the influence of various air pollutants on the transmission of SARS-CoV-2, and the severity of COVID-19 in patients infected by the coronavirus. The results of most of those reviewed studies suggested that chronic exposure to certain air pollutants might lead to more severe and lethal forms of COVID-19, as well as delays/complications in the recovery of the patients. Since then, a notable number of studies on this topic have been published, including also various reviews. Given the importance of this issue, we have updated the information published since our previous review. Taking together the previous results and those of most investigations now reviewed, we have concluded that there is a significant association between chronic exposure to various outdoor air pollutants: PM2.5, PM10, O3, NO2, SO2 and CO, and the incidence/risk of COVID-19 cases, as well as the severity/mortality of the disease. Unfortunately, studies on the potential influence of other important air pollutants such as VOCs, dioxins and furans, or metals, are not available in the scientific literature. In relation to the influence of outdoor air pollutants on the transmission of SARS-CoV-2, although the scientific evidence is much more limited, some studies point to PM2.5 and PM10 as potential airborne transmitters of the virus. Anyhow, it is clear that environmental air pollution plays an important negative role in COVID-19, increasing its incidence and mortality.

Irisin, Exercise, and COVID-19

Muscle and adipose tissue produce irisin during exercise. Irisin is thermogenic adipomyokine, improves glucose and lipid metabolism, and ameliorates the effects of obesity-driven inflammation, metabolic syndrome, and diabetes. In addition, exercise-induced irisin activates anti-inflammatory pathways and may play an essential role in improving the outcomes of inflammatory conditions, such as coronavirus disease (COVID-19). COVID-19 infection can activate different intracellular receptors and modulate various pathways during the course of the disease. The cytokine release storm (CRS) produced is significant because it promotes the context for systemic inflammation, which increases the risk of mortality in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV2). In addition, viral infection and the resulting organ damage may stimulate the mitogen-activated protein kinase(MAPK) and toll-like receptor 4 (TLR4)/toll interleukin receptor (TIR)-domain-containing adaptor (MyD88) pathways while negatively modulating the AMP-activated protein kinase (AMPK) pathway, leading to increased inflammatory cytokine production. Exercise-induced irisin may counteract this inflammatory modulation by decreasing cytokine production. Consequently, increased irisin levels, as found in healthy patients, may favor a better prognosis in patients with SARS-CoV2. This review aims to explore the molecular mechanisms underlying the anti-inflammatory properties of irisin in mitigating CRS and preventing severe outcomes due to infection with SARS-CoV2.