SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel virus of the family Coronaviridae. The virus causes the infectious disease COVID-19. The biology of coronaviruses has been studied for many years. However, bioinformatics tools designed explicitly for SARS-CoV-2 have only recently been developed as a rapid reaction to the need for fast detection, understanding, and treatment of COVID-19. To control the ongoing COVID-19 pandemic, it is of utmost importance to get insight into the evolution and pathogenesis of the virus. In this review, we cover bioinformatics workflows and tools for the routine detection of SARS-CoV-2 infection, the reliable analysis of sequencing data, the tracking of the COVID-19 pandemic and evaluation of containment measures, the study of coronavirus evolution, the discovery of potential drug targets and development of therapeutic strategies. For each tool, we briefly describe its use case and how it advances research specifically for SARS-CoV-2. All tools are freely available online, either through web applications or public code repositories.

(1) Background: tuberculosis (TB) is considered one of the leading causes of death by a single in-fectious agent worldwide. This study aimed to identify hotspots of people diagnosed with tu-berculosis and abusive use of alcohol, tobacco and other drugs in communities through a geo-spatial intelligence application; (2) Methods: ecological study with a spatio-temporal approach. We considered tuberculosis cases diagnosed and registered in the Notifiable Diseases Information System, which presented information on alcoholism, smoking, and other drugs. Spatial Variations in Temporal Trends (SVTT) and scan statistics were applied for the identification of Hotspots; (3) Results: of 29.499 cases of tuberculosis were identified. And when we applied the STTT for al-coholism, three Hotspots were detected, one of which was protective (RR: 0.08 – CI95%: 0.02 – 0.32) and two at risk (RR:1.42 – CI95%: 1.11 – 1.73; RR: 1.39 - CI95%: 1.28 – 1.50). Regarding smoking, two risk clusters were identified (RR: 1.15 - CI95%: 1.01 – 1.30; RR: 1.68 - CI95%: 1.54 – 1.83). For other drugs, a risk cluster was found (RR: 1.13 - CI95%: 0.99 – 1.29) and two protections (RR: 0.70 - CI95%: 0.63 – 0.77; RR: 0.76 – CI95%: 0.65 – 0.89); (4) Conclusions: it was evidenced in the communities a problem of TB and drug addiction. Use disorder perhaps in a person's brain and behavior and leads to an inability to continue their treatment, putting the community at risk for TB.

The global pandemic of SARS-CoV-2, the causative viral pathogen of COVID-19, has driven the biomedical community to action – to uncover and develop anti-viral interventions. One potential therapeutic approach currently being evaluated in numerous clinical trials is the agent remdesivir, which has endured a long and winding developmental path. Remdesivir is a nucleotide analog prodrug that perturbs viral replication, originally evaluated in clinical trials to thwart the Ebola outbreak in 2014. Subsequent evaluation by numerous virology laboratories demonstrated the ability of remdesivir to inhibit coronavirus replication, including SARS-CoV-2. Here, we provide an overview of its mechanism of action, discovery, and the current studies exploring its clinical effectiveness.

With the increase of the Artificial Neural Network (ANN), machine learning has taken a forceful twist in recent times. One of the most spectacular kinds of ANN design is the Convolutional Neural Network (CNN). The Convolutional Neural Network (CNN) is a technology that mixes artificial neural networks and up to date deep learning strategies. In deep learning, Convolutional Neural Network is at the center of spectacular advances. This artificial neural network has been applied to several image recognition tasks for decades and attracted the eye of the researchers of the many countries in recent years as the CNN has shown promising performances in several computer vision and machine learning tasks. This paper describes the underlying architecture and various applications of Convolutional Neural Network.

With the goal of representing common denominators of aging in different organisms López-Otín et al. in 2013 described nine hallmarks of aging. Since then, this representation has become a major reference point for the biogerontology field. The template for the hallmarks of aging account originated from landmark papers by Hanahan and Weinberg (2000, 2011) defining first six and later ten hallmarks of cancer. Here we assess the strengths and weaknesses of the hallmarks of aging account. As a checklist of diverse major foci of current aging research, it has provided a useful shared overview for biogerontology during a time of transition in the field. It also seems useful in applied biogerontology, to identify interventions (e.g. drugs) that impact multiple symptomatic features of aging. However, while the hallmarks of cancer provide a paradigmatic account of the causes of cancer with profound explanatory power, the hallmarks of aging do not. A worry is that as a non-paradigm the hallmarks of aging have obscured the urgent need to define a genuine paradigm, one that can provide a useful basis for understanding the mechanistic causes of the diverse aging pathologies. We argue that biogerontology must look and move beyond the hallmarks to understand the process of aging.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes an outbreak of COVID-19 disease in humans with the aid of spike protein. It consists of a receptor-binding domain (RBD) that recognizes and binds to the host receptor angiotensin-converting enzyme 2 (ACE2). The aim of this study was to examine the mutational effect of spike protein on the sequence through an interaction study of the mutant spike protein and the human ACE2 protein at the structural level. A total of 17,227 spike proteins from Asia, Africa, Europe, Oceania, South America, and North America were compared to the Wuhan spike protein reference sequence (Wuhan-Hu-1). The structural and stability implications of D614G, N501Y, and S477N mutations were evaluated. The binding affinity between mutated RBD and human ACE2 protein was also studied. The D614G mutation may have originated in Germany, Europe based on the date of the first sample collection report. It is now widely circulated all over the world with most occurrences in North America. The mutations N501Y and S477N may have originated from Oceania based on the date of the first sample collection report and also have the highest occurrences in Oceania. Based on the computational analysis of mutational effects, the D614G, N501Y, and S477N mutations decreased stability and were tolerated. For disease propensity prediction, N501Y was more prone to disease compared to D614G, while S477N was not prone to disease. The mutation of D to G at position 614 and S to N at position 477 for secondary structure prediction shows no changes in secondary structure while remaining in the coil region, whereas the mutation of N to Y at position 501 changes from coil structure to extended strand. N501Y mutation has a higher affinity to human ACE2 protein compared to D614G and S477N based on a docking study. D614G spike mutation was identified to exist between the two hosts based on a comparison of SARS-CoV-2 derived between the mink and human. Further research is needed on the link between the mink mutation N501T and the mutation N501Y in humans, which has evolved as a separate variant.

Background: The purpose of this study was to examine the prevalence and effects of current smoking on adverse outcomes among hospitalized COVID-19 patients. Methods: We performed a systematic review of the literature (PubMed) for studies published until April 25. Studies were included into the analysis if they satisfied all of the following criteria: 1. To present hospitalized patients with COVID-19. 2. To classify patients into less and more severe disease, irrespective of the severity definition (defined as “adverse ourtcome”). 3. To present data on the smoking status, separately for each severity classification. We identified 18 (from a total of 1398) relevant studies. Pooled current smoking prevalence was compared with the gender-adjusted, population-based expected prevalence by calculating Prevalence Odds Ratio (POR). The association between current, compared to non-current and former, smoking and adverse outcome was examined by calculating Odds Ratio (OR). All analyses were performed using random-effects meta-analysis. Results: Among 6515 patients, 440 of whom were current smokers, the pooled prevalence of current smoking was 6.8% (95%CI: 4.8-9.1%) and the POR was 0.21 (95%CI: 0.16-0.26, P < 0.001). In Chinese studies only, the POR was 0.22 (95%CI: 0.17-0.27, P < 0.001). Current smokers were more likely to have an adverse outcome compared to non-current smokers (OR: 1.53, 95%CI: 1.06-2.20, P = 0.022). However, they were less likely to have an adverse outcome compared to former smokers (OR: 0.42, 95%CI: 0.27-0.74, P = 0.003). Conclusion: An unexpectedly low prevalence of current smoking was observed among hospitalized patients with COVID-19. Hospitalized current smokers had higher odds compared to non-current smokers but lower odds compared to former smokers for an adverse outcome. The possibility that nicotine may have a protective effect in COVID-19 which may be masked by smoking-related toxicity and by the abrupt cessation of nicotine intake when smokers are hospitalized should be explored.

COVID-19 (coronavirus disease 2019) is a public health emergency of international concern caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). As of this time, there is no known effective pharmaceutical, phytopharmaceutical or traditional medicine for cure or prevention of COVID-19, although it is urgently needed. In this review, based on the current understanding of the disease molecular mechanisms of novel Coronavirus SARS-CoV-2 and its closest relative SARS-CoV and other human Coronaviruses, I have identified some naturally occurring plant based substances and Ayurvedic medicinal herbs that could feasibly be tested as a matter of urgency for prevention as well as therapeutic option for COVID-19 in India and other parts of the world. I conclude that dried rhizome of Curcuma longa L. i.e. turmeric, and its active ingredient curcumin may be effective in preventing as well as cure the COVID-19 pandemic due to its proven antiviral activities, this however need to be tested by appropriate clinical trials as research priority.

Background: COVID-19 pandemic has pulled us all a few steps back, were we never shake hands or hug each other when we meet our friends and family after a gap, but instead we greet them by saying Namaste and joining our hands together. As we all know, COVID-19 spreads through air and the only way to shield ourselves is by maintaining a safe distance from one another. Methodology: In order to conduct a meta-analysis on the number of COVID-19 cases in Kerala and India, the data was retrieved from various sites hosted by the government bodies. The data for analysis was collected from May 2020 to July 2020. The average number of days required to reach every 5000 fresh cases were also calculated using this data. COVID-19 has affected all the economy holistically regardless of financial, behavioral, or societal aspects. Conclusion: Lifting of the lockdown in a step by step process keeping in mind the necessities for the nation was a thoughtful act, but the people who mistook this opportunity and did not remain in quarantine after coming from abroad was recognized as the reasons behind the sudden and uncontrolled rise in the number of COVID-19 cases in Kerala, India. The government authorities had no other option but to lift the restrictions to reduce the economic burdens that had already affected the daily wage worker and farmers prompting them to give up their lives.

Long-haul COVID-19 illness first gained widespread recognition among social support groups and later in scientific and medical communities. This illness is mysterious as it affects COVID-19 survivors at all levels of disease severity, even younger adults and children. While the precise definition may be lacking, the defining symptoms are fatigue, dyspnea, and headache that last for months after hospital discharge. The less typical symptoms may include cognitive impairments, chest and joint pains, myalgia, smell and taste dysfunctions, cough, mood changes, and gastrointestinal and cardiac issues. Presently, there is limited literature discussing the possible pathophysiology, risk factors, and treatments in long-haul COVID-19, which the current review aims to address. In brief, long-haul COVID-19 may be driven by long-term lung and brain damage and unresolved inflammation from multiple sources. The associated risk factors may include female sex, more than five early symptoms, early dyspnea, and specific biomarkers like D-dimer. While only rehabilitation training has been useful for long-haul COVID-19, therapeutics repurposed from mast cell activation syndrome, myalgic encephalomyelitis/chronic fatigue syndrome, and pulmonary fibrosis also hold potential. In sum, this review hopes to provide the current understanding of what is known about long-haul COVID-19.

COVID-19 has emerged as deadly pandemic worldwide with no vaccine or suitable antiviral drugs to prevent or cure the disease. Because of the time-consuming process to develop new vaccines or antiviral agents, there has been a growing interest in repurposing some existing drugs to combat SARS-CoV-2. Vitamin D is known to be protective against acute respiratory distress syndrome (ARDS), pneumonia and cytokine storm. Recently it has been used as a repurposed drug for the treatment of H5N1 virus-induced lung injury. Circumstantial evidences indicate that people with low level of vitamin D are more susceptible to SARS-CoV-2. Although, vitamin D was suggested to interfere with viral replication, its interaction with any SARS-CoV-2 protein is unexplored yet. Beside this, ivermectin, a well-known anti-parasitic agent, exhibits potent anti-viral activities in vitro against viruses such as HIV-1 and dengue. Very recently, ivermectin has been found to reduce viral load of SARS-CoV-2 in vitro. We have analyzed available structures of SARS-CoV-2 proteins to identify probable binding partner(s) of vitamin D and ivermectin through knowledge-based docking studies and figured out possible implication of their binding in SARS-CoV-2 infection. Our observations suggest that the non-structural protein nsp7 possesses a potential site to house 25-hydroxyvitamin D3 (VDY) or the active form of Vitamin D, calcitrol. Binding of vitamin D with nsp7 likely to hamper the formation of nsp7-nsp8 complex which is required to bind with RNA dependent RNA polymerase (RdRP), nsp12 for optimal function. On the other hand, potential binding site of ivermectin has been identified in the S2 subunit of trimeric spike(S) glycoprotein of SARS-CoV-2. We propose that deeply inserted mode of ivermectin binding at three inter-subunit junctions may restrict large scale conformational changes of S2 helices which is necessary for efficient fusion of viral and host membrane. Our study, therefore, opens up avenues for further investigations to consider vitamin D and ivermectin as potential drugs against SARS-CoV-2.

Introduction: An epidemic of Coronavirus Disease 2019 (COVID-19) begun in December 2019 in China, causing a Public Health Emergency of International Concern. Among raised questions, clinical, laboratory, and imaging features have been partially characterized in some observational studies. No systematic reviews have been published on this matter. Methods: We performed a systematic literature review with meta-analysis, using three databases to assess clinical, laboratory, imaging features, and outcomes of COVID-19 confirmed cases. Observational studies, and also case reports, were included and analyzed separately. We performed a random-effects model meta-analysis to calculate the pooled prevalence and 95% confidence interval (95%CI). Results: 660 articles were retrieved (1/1/2020-2/23/2020). After screening by abstract/title, 27 articles were selected for full-text assessment. Of them, 19 were finally included for qualitative and quantitative analyses. Additionally, 39 case report articles were included and analyzed separately. For 656 patients, fever (88.7%, 95%CI 84.5-92.9%), cough (57.6%, 40.8-74.4%) and dyspnea (45.6%, 10.9-80.4%) were the most prevalent manifestations. Among the patients, 20.3% (95%CI 10.0-30.6%) required intensive care unit (ICU), with 32.8% presenting acute respiratory distress syndrome (ARDS) (95%CI 13.7-51.8), 6.2% (95%CI 3.1-9.3) with shock and 13.9% (95%CI 6.2-21.5%) of hospitalized patients with fatal outcomes (case fatality rate, CFR).Conclusion: COVID-19 brings a huge burden to healthcare facilities, especially in patients with comorbidities. ICU was required for approximately 20% of polymorbid, COVID-19 infected patients and this group was associated with a CFR of over 13%. As this virus spreads globally, countries need to urgently prepare human resources, infrastructure, and facilities to treat severe COVID-19.

The evolution of knowledge in biological and medical areas which made possible scientific and technological advances are attributed to anatomical studies, physiology and immunology in animals, contributing to the discovery of prophylactic measures and treatments of diseases that affect humans and animals. Currently, substitution is suggested by alternative methods that do not use laboratory animals, however in vitro methods may never be able to provide similar results to in vivo methods. Mice and rats are the most used animals in experimental researches, the anatomical, histological and genetic differences between species should be carefully evaluated, to better apply the study model and avoid unnecessary waste avoid. This study, aimed at an anatomical comparative and histological relationship between a rat´s and a mouse´s organs, is of great importance in experimental studies. For such, 30 Mus musculus (Swiss) mice and 15 Rattus norvegicus (Wistar) male and heterogenic rats, were used. All animals were kept free of pathogenic microorganisms, with the absence of surgical interventions that could cause anatomical and physiological changes. It was possible to observe significant anatomical and histological differences between spleens, brains, hearts, stomachs and intestines, livers, eyes, lungs and kidneys among species, which will serve as a basis to assist in choosing the most satisfactory research model. Few studies relate specific characteristics among laboratory animals, being restricted to a few veterinary and zoology books. The greater the organic, physiological and anatomical similarities are with the human being, the greater is the applicability of the animals in studies. However, it is not possible to lay down general rules to validate the extrapolation from one species to another.

The COVID-19 pandemic is due to infection caused by the novel SARS-CoV-2 that impacts the lower respiratory tract. The spectrum of symptoms ranges from asymptomatic infections to mild respiratory symptoms to the lethal form of COVID-19 which is associated with severe pneumonia, acute respiratory distress and fatality. At present, the global case fatality rate of COVID-19 laboratory confirmed cases is ~4.7% ranging from ~0.3-0.4% in Chile and Israel to ~10.8% in Italy. To address this global crisis, up-to-date information on the viral genomics and transcriptomics is crucial for understanding the origins and global dispersal of the virus, providing insight into viral pathogenicity, transmission and epidemiology, and enabling strategies for therapeutic interventions, drug discovery and vaccine development. Therefore, this review provides a comprehensive overview of COVID-19 epidemiology, genomic etiology, findings from recent transcriptomic map analysis, viral-human protein interactions, molecular diagnostics, and the current status of vaccine and novel therapeutic intervention development. Moreover, we provide an extensive list of resources that will help the scientific community access numerous types of databases related to SARS-CoV-2 OMICs and approaches to therapeutics related to COVID-19 treatment.

The current outbreak of the novel coronavirus also known as COVID-19 was declared as a public health emergency by the WHO where over a million people have been affected by the disease with over 50000 deaths till date. Social distancing is a method to minimize crowd interactions and prevent the spread of disease within groups of people. This is a common practice which has been carried out over generations to minimize the spread of virus by limiting its reproduction rate (R0) among communities. The article focuses on how social distancing has been used to deal previous pandemics globally and the issues that needs to be addressed to tackle the COVID-19 threat.

A novel coronavirus (SARS-CoV-2) that is initially found to trigger human severe respiratory illness in Wuhan City of China in 2019, has killed 2,718 people in China by February 26, 2020, and which has been recognized as a public health emergency of international concern as well. And the virus has spread to more than 38 countries around the world. However, the drug has not yet been officially licensed or approved to treat SARS-Cov-2 infection. NSP12-NSP7-NSP8 complex of SARS-CoV-2, essential for viral replication and transcription, is generally regarded as a potential target to fight against the virus. According to the NSP12-NSP7-NSP8 complex (PDB ID: 6NUR) structure of SARS, two homologous models were established for virtual screening in the present study, namely NSP12-NSP7 interface model and NSP12-NSP8 interface model. Seven compounds (Saquinavir, Tipranavir, Lonafarnib, Tegobuvir, Olysio, Filibuvir, and Cepharanthine) were selected for binding free energy calculations based on virtual screening and docking scores. All seven compounds can combine well with NSP12-NSP7-NSP8 in the homologous model, providing drug candidates for the treatment and prevention of SARS-CoV-2.

In humankind’s endeavor to explore beyond our planet and travel further into space, we are now at the threshold of an era in which it is possible to move to and from low Earth orbit (LEO) with increasing ease and reduced cost. Through the International Space Station (ISS) U.S. National Laboratory, investigators from industry, academia, and government can easily access the unique LEO environment on the ISS to conduct research and development (R&D) activities in ways not possible on Earth. A key advantage of the LEO environment for life sciences research is the ability to conduct experiments in sustained microgravity conditions. The ability to conduct long-term research in microgravity enables opportunities for novel, fundamental studies in tissue engineering and regenerative medicine, including research on stem cell proliferation and differentiation, biofabrication, and disease modeling using microphysiological systems (MPS) that build on prior research using simulated microgravity conditions (Grimm, D., et al. 2018). Over the last decade, space-based research has demonstrated that microgravity informs our knowledge of fundamental biology and accelerates advancements in health care and medical technologies (International Space Station 2019). The benefits provided by conducting biomedical research in LEO may lead to breakthroughs not achievable on Earth. We are now at a transition point, in which nations are changing their approach to space-based R&D. The focus is shifting from government-funded fundamental science toward the expansion of privately funded R&D with terrestrial application and economic value that will drive a robust marketplace for innovation and manufacturing in LEO. Making this long-term transition requires public-private participation and near-term funding to support critical R&D to leverage the benefits of the LEO environment and de-risk space-based research. Studies conducted on the ISS over the past several years have indicated that one area with potential significant economic value and benefit to life on Earth is space-based biomanufacturing, or the use of biological and nonbiological materials to produce commercially relevant biomolecules and biomaterials for use in preclinical, clinical, and therapeutic applications. We must take advantage of the remaining lifetime of the ISS as a valuable LEO platform to demonstrate this economic value and Earth benefit. By facilitating access to the space station, the ISS National Lab is uniquely positioned to enable the R&D necessary to bridge the gap between the initial discovery phase of space-based biomedical research and the development of a sustainable, investment-worthy biomanufacturing market in LEO supported by future commercial platforms. Through a joint effort, the Center for the Advancement of Science in Space (CASIS), which manages the ISS National Lab, and the University of Pittsburgh’s McGowan Institute for Regenerative Medicine brought together thought leaders from around the U.S. for a Biomanufacturing in Space Symposium that consisted of a series of working sessions to review data from past space-based tissue engineering and regenerative medicine research, discuss relevant current space-based R&D in this area, and consider potential future markets to address the questions: What are the most promising opportunities to leverage the ISS to advance space-based biomanufacturing moving forward? What are the current gaps or barriers that, if overcome, could clear pathways toward private investment in LEO as a valued site for research, development, and production activity? And, most importantly: For which opportunities do the most compelling value propositions exist? The goal of the Biomanufacturing in Space Symposium was to help identify the specific areas in which government and industry investment would be most likely to stimulate advancements that overcome barriers. This would lead to a more investment-ready landscape for private interests to enter the market and fuel exponential growth. The symposium was meant to serve as the first step in developing a roadmap to a sustainable market for biomanufacturing in space. The symposium identified and prioritized multiple key R&D opportunities to advance space-based biomanufacturing. These opportunities fall in the areas of disease modeling, stem cells and stem-cell-derived products, and biofabrication. Additionally, symposium participants highlighted the critical need for additional data to help validate and de-risk these opportunities and concluded that approaches such as automation, artificial intelligence (AI), and machine learning will be needed to produce and capture the required data. Symposium participants also came to a consensus that public-private partnerships and funding will be needed to advance the opportunities toward a biomanufacturing marketplace in LEO. This paper will summarize the current state of the science and technology on the ISS and in the fields of tissue engineering and regenerative medicine; provide an overview of biomanufacturing R&D in space to date; review the goals of the Biomanufacturing in Space Symposium; highlight the key commercial opportunities and gaps identified during the symposium; provide information on potential market sizes; and briefly discuss the next steps in developing a roadmap to biomanufacturing in space.

The detection of coronavirus (COVID-19) is now a critical task for the medical practitioner. The coronavirus spread so quickly between people and approaches 100,000 people worldwide. In this consequence, it is very much essential to identify the infected people so that prevention of spread can be taken. In this paper, the deep feature plus support vector machine (SVM) based methodology is suggested for detection of coronavirus infected patient using X-ray images. For classification, SVM is used instead of deep learning based classifier, as the later one need a large dataset for training and validation. The deep features from the fully connected layer of CNN model are extracted and fed to SVM for classification purpose. The SVM classifies the corona affected X-ray images from others. The methodology consists of three categories of Xray images, i.e., COVID-19, pneumonia and normal. The method is beneficial for the medical practitioner to classify among the COVID-19 patient, pneumonia patient and healthy people. SVM is evaluated for detection of COVID-19 using the deep features of different 13 number of CNN models. The SVM produced the best results using the deep feature of ResNet50. The classification model, i.e. ResNet50 plus SVM achieved accuracy, sensitivity, FPR and F1 score of 95.33%,95.33%,2.33% and 95.34% respectively for detection of COVID-19 (ignoring SARS, MERS and ARDS). Again, the highest accuracy achieved by ResNet50 plus SVM is 98.66%. The result is based on the Xray images available in the repository of GitHub and Kaggle. As the data set is in hundreds, the classification based on SVM is more robust compared to the transfer learning approach. Also, a comparison analysis of other traditional classification method is carried out. The traditional methods are local binary patterns (LBP) plus SVM, histogram of oriented gradients (HOG) plus SVM and Gray Level Co-occurrence Matrix (GLCM) plus SVM. In traditional image classification method, LBP plus SVM achieved 93.4% of accuracy.

Very well into the dawn of the fourth industrial revolution (industry 4.0), we hardly distinguish between what is artificial and what is natural (e.g. man-made virus and natural virus). Thus, the level of discombobulation among people, companies or countries is indeed unprecedented. The fact that industry 4.0 is explosively disrupting or retrofitting each and every industrial sector, makes industry 4.0 the famous buzzword amongst researchers today. However, the insight of industry 4.0 disruption in the industrial sectors remains ill-defined in both academic and non-academic literature. The present study aimed at identifying industry 4.0 neologisms, understanding the industry 4.0 disruption and illustrating the disruptive technologies convergence in the major industrial sectors. A total of 99 neologisms of industry 4.0 were identified. Industry 4.0 disruption in Education industry (Education 4.0), Energy industry (Energy 4.0), Agriculture industry (Agriculture 4.0), Healthcare industry (Healthcare 4.0), and Logistics industry (Logistics 4.0) are described. The convergence of 12 disruptive technologies including 3D printing, Artificial intelligence, Augmented reality, Big Data, Blockchain, Cloud computing, Drones, Internet of things, Nanotechnology, Robotics, Simulation and Synthetic biology in agriculture, healthcare and logistics industries are illustrated.

Decisions affecting the COVID-19 pandemic, by the individual and those with highest authority, are being made on the basis of unreliable data. Data about cases and deaths are collected daily but represent only a sample of reality. Statistics convert sample data into more reliable estimates. However, statistics have no magical powers; reliability requires dependable data. It is futile to rail against this darkness; COVID-19 is not a scientific experiment. However, we must do better both with data collection and data analysis. In this review, I focus on one element of the data, the asymptomatic case of COVID-19. Without reliable information about this number, decision makers are significantly blinded. By its nature, the asymptomatic case is hidden but contaminating to understanding COVID-19. The true case rate and death rate per case are unknowable without knowing the fraction of cases that are asymptomatic. The best estimate of asymptomatic cases is in the CDC document: COVID-19 Pandemic Planning Scenarios. For four different scenarios the estimates range from 10% to 70%, with the best estimate of 40% for asymptomatic cases. However, even the definition of the asymptomatic case is problematic. In simplest terms, two elements are required: an infection and no symptoms. How is “no symptoms” to be usefully defined? It appears to be analogous to pontificating about black swans from studying only white swans. It implies infection, but how is infection defined? Is it presence of the virus, replication of the virus, or presence of antibodies? Is asymptomatic disease an oxymoron? Without extensive, purposeful screening for specifically defined, essential symptoms and appropriate virus and antibody testing over time, the class of asymptomatic cases remains unknown. Current estimates range from <20% to ˃80%. If low, it can be ignored; if high, it dramatically and proportionately lowers the case rate and the death rate per case. Consequentially, the asymptomatic rate dramatically affects our societal and political responses. In this focused review, we assess the limitations of the published estimates, bring attention to the importance of obtaining accurate data, and exhort that high priority be given in the scientific community to understanding the issue, asymptomatic COVID-19 cases.

Coronavirus disease 2019 (COVID-19) was initially characterized as a respiratory illness. Neurological manifestations were reported mostly in severely affected patients. Routes for brain infection and the presence of virus particles in situ have not been well described, raising controversy about how the virus causes neurological symptoms. Here, we report the autopsy findings of a 1-year old infant with COVID-19. In addition to pneumonitis and multiple organ damage related to thrombosis, SARS-CoV-2 infected the choroid plexus, ventricles, and cerebral cortex. This is the first evidence of SARS-CoV-2 detection in an infant post-mortem brain.

There are limited proven therapies for the treatment of COVID-19. Vitamin C’s antioxidant, anti-inflammatory and immunomodulating effects, make it a potential therapeutic candidate, both for the prevention and amelioration of COVID-19 infection, and as an adjunctive therapy in the critical care of COVID-19, supporting anti-inflammatory treatment. This literature review focuses on vitamin C deficiency in respiratory infections including COVID-19; the mechanism of action in infectious disease and adrenal function supporting the anti-inflammatory actions of glucocorticosteroids: its role in preventing and treating colds and pneumonia and its role in treating sepsis and COVID-19. The evidence to date indicates that oral vitamin C (2-8g/d) may reduce incidence and duration of respiratory infections and intravenous vitamin C (2-24g/d) has been shown to reduce mortality, Intensive Care Unit and hospital stays, time on mechanical ventilation in severe respiratory infections. Further trials are urgently warranted. Given the favourable safety profile and low cost of vitamin C, and frequency of vitamin C deficiency in respiratory infections it may be worthwhile testing patients’ vitamin C status and treating accordingly with intravenous use within ICUs and orally with doses between 2 and 8g/day in hospitalised and infected persons.

In the end of April nearly 100 cases of children aged between 6 month and 9 years with Kawasaki like disease were reported (mostly in Europe) probably linked to COVID-19. With the increasing awareness of this condition the number of cases reported is increasing worldwide. We aim to sum up the known data about this new entity based on published data (in a case report, a series of 8 cases and in newspapers and society statement) and using our knowledge of classical Kawasaki disease. It seems to be a post infectious disease with an onset between 2-4 weeks after the infection, probably in genetically predisposed children aged between 6 month to 17 years. A very rough estimation of incidence based on current data from Bergamo, Italy, and New York State and a lot assumption is between 0.016% (95% CI:0.013-0.02%) - 0.31% (95% CI: 0.2-0.47%) of infected children. Clinical signs overlaps with Kawasaki disease in some children, but another feature is prominent gastrointestinal manifestations. For the 9 detailed patients most had incomplete presentation for Kawasaki disease (with a mean 1.7 (+/-1.2) criteria per patient for the 5 non fever criterion) and only one had a classical form. In some cases, presentation is closer to toxic shock syndrome or isolated myocarditis. Persistent fever seems to be constant and biological exploration are consistent with inflammation (elevated CRP, ferritin and D-Dimers). Management is described as supportive and children seem to improve rapidly, but can require cardiac or respiratory support. In date of 11 may 2020 there is 4 deaths confirmed linked to these new entities (1 in UK and 3 in New York). Paediatricians and general practitioners need to be aware of these possible evolution following COVID-19 infection. However it seems to be rare and children are probably still spared from most morbidities and mortality linked to COVID-19 infection .There are need of published detailed cohorts to better delineate these entities.

SARS-CoV-2 mRNA vaccination can entail chronic fatigue/dis-autonomy tentatively termed post-acute COVID-19 vaccination syndrome (PACVS). We explored receptor autoantibodies and interleukin-6 (IL-6) as somatic correlates of PACVS. Blood markers determined before and six months after first-time SARS-CoV-2-vaccination of healthy controls (N = 89, 71 females, mean/ median age 39/ 49 years) were compared with corresponding values of PACVS-affected persons (N= 191, 159 females, mean/median age: 40/39 years) exhibiting chronic fatigue/dis-autonomy (≥ three symptoms for ≥ five months after last SARS-CoV-2 mRNA vaccination) not due to SARS-CoV-2 infection and/or confounding diseases/medications. Normal vaccination response encompassed decreases of 11 receptor-antibodies (by 25 - 50 %, p < 0.0001), increases in two receptor-antibodies (by 15 - 25 %, p < 0.0001) and normal IL-6. In PACVS, serological vaccination-response appeared significantly (p < 0.0001) altered, allowing discrimination from normal post-vaccination state (sensitivity = 90%, p &lt; 0.0001) by increased angiotensin II type 1 receptor antibodies (cut-off ≤ 10.7 U/ml, ROC-AUC = 0.824 ± 0.027), decreased alpha-2B adrenergic receptor antibodies (cut-off ≥ 25.2 U/ml, ROC-AUC = 0.828 ± 0.025) and increased IL-6 (cut-off ≤ 2.3 pg/ml, ROC-AUC = 0.850 ± 0.022). PACVS is thus indicated as a somatic syndrome delineated/detectable by diagnostic blood markers

ABSTRACT. In this paper, we suggest a biomathematical numerical method for analysing mRNA nucleotides sequences based on UA/CG Fibonacci numbers proportions. This method is used to evaluate then compare the spike genes related to the main SARS-CoV2 VARIANTS currently circulating within the world population. The 10 main results proposed to be reproduced by peers are: 1/ SARS-CoV2 genome and spike evolution in one year 2020-2021. 2/ SARS-CoV2 Origins. 3/ Comparing 11 reference variants spikes. 4/ analysing 32 CAL.20C California variant patients spikes. 5/ Toward a meta mRNA Fibonacci gene end message code. 6/ Analysing S501 UK, S484 South Africa and « 2 mutations » INDIA variants. 7/ Suggesting a possible variants spike mRNA palindrome symmetry metastructure improving mRNA stability then infectiousness. 8/ Analysing Fibonacci Metastructures in the mRNA coding for the vaccines PFIZER and MODERNA. 9/ Does the CG-rich modification of the synonymous codons of the spikes of the 2 mRNA vaccines affect the expression and quantity of SARS-CoV2 antibodies? 10/ The exceptional case of the Brazilian variant P.1. Particularly, we suggest the following conjecture at mRNA folding level : CONJECTURE of SARS-CoV2 VARIANTS: The growth of long Fibonacci structures in the shape of "podiums" for almost all of the variants studied (UK, California, South Africa, India, etc.) suggests the probable folding of the Spike mRNA in the form of a "hairpin", which can strengthen the cohesion and the lifespan of this mRNA. Finally, we show that these kinds of Fibonacci matastructures disapear TOTALLY by analysing the published mRNA sequences of PFIZER and MODERNA vaccines. One fact is certain, the two mRNAs of the Moderna and Pfizer vaccines will result in a low functionality of the spike vaccine. This is because their designers by seeking greater stability, have doped to build CG rich sequences which, as soon as they are inserted into the human host, will, paradoxically, seek to mutate, like SARS-CoV2 variants, towards CG ==> UA forms in order to improve their STABILITY and LIFETIME. We conclude using new biomathematics theoretical methods (Master code and numerical standing waves), and comparing the Spikes of the two vaccines Moderna and Pfizer, that there will be very probable differences in stability and shelf life of the two respective mRNAs vaccines. However, “State of the Art” analyzes will disclose that their two protein sequences are strictly identical. By modified their synonymous codons using different strategies, no one can guarantee that the quantity of antibodies generated will be identical in the two cases. We wish to draw attention to the great ADAPTATION power - at the global scale of their genomes - of the most infectious VARIANTS, such as the BRAZIL 20J / 501Y.V3 variant (P.1). This is very worrying for the VACCINES <==> VARIANTS run: We demonstrate how the Brazilian variant P.1 which becomes uncontrollable in Brazil in April 2021 has a level of organization of long metastructures of 17,711 bases covering the genome which is 3.6 more important than that of the 2 reference genomes SARS-CoV2 and worldwide D614G. We suggest that this high level of overall structure of this variant contributes to the stability of this genome and, might explain its greater contagiousness.

An outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) occurred in China towards the end of 2019, and has spread rapidly ever since. Previous studies showed that some virus could affect the reproductive system and cause long-term complications. Recent studies exploring the source of SARS-CoV-2 using genomic sequencing have revealed that SARS-CoV-2 enters the host cells via the angiotensin-converting enzyme II (ACE2), the receptor that recognizes SARS-CoV. To investigate the expression of ACE2 and to explore the potential risk of infection in the reproductive system, we performed a thorough bioinformatic analysis on data from public databases involving RNA expression, protein expression, and single-cell RNA expression studies. The analyzed data showed high levels of ACE2 mRNA and protein expression in the testis and spermatids and equal levels of ACE2 expression in the uterus and lung. Comprehensive single-cell analysis identified ACE2 expression in the lung, testis, spermatids, and uterus. In conclusion, this study revealed the potential risk associated with the SARS-CoV-2 infection in the reproductive system and predicted that long-term complications might have a significant impact on the prevention and management of COVID-19, the disease caused upon infection with SARS-CoV-2.

This tutorial is organized into three major sections—viruses, vaccines and the race for a Covid-19 vaccine. The goal is to provide enough background on viruses, history of vaccines, and the science of vaccinology founded on the principles of immunity. The hope is that this will enable us to understand the challenges, methods and prospects for developing a safe and effective vaccine against SARS-CoV-2. Many important viruses such as smallpox, HIV, HCV and SARS-CoV-2 which is responsible for causing the Coronavirus disease 2019 (Covid-19) are presented in detail, which is then followed by a description of different vaccine development methods and strategies. The tutorial then discusses different candidate SARS-CoV-2 vaccines and provides specific details of many of the prospective vaccines on the leader-board which are undergoing clinical trials. The tutorial concludes with a realistic projection for a safe and effective vaccine against SARS-CoV-2 based on the historical scientific record.

SARS-CoV2 (corona virus) has spread globally at an unprecedented rate; so far, increasing SARS-CoV2-infected individuals have been identified. Although the situation in China is improving and is currently under control, the outbreak in other countries and its pandemic management is only beginning to develop. Based on 154 SARS-CoV2 genome sequence analyses, we used receptor–ligand docking to identify one potential point mutation (V354F) on the spike structure which enhances spike binding to ACE2 receptors underlying potential super infection. Importantly, the V354F site on spike S1 had been identified in 5/10 infected French patients living in Paris, who sharing 100% identical SARS-CoV2 genomes. With Covid-19 cases increasing rapidly in France that could lead to a new explosion, we suggest that the French government should identify all potential super spreaders and treat them accordingly. In summary, our study provides on of the measures to avoid the potential second worldwide explosion of SARS-CoV2.

Sentinel-1 SAR data preprocessing is essential for several earth observation applications, including land cover classification, change detection, vegetation monitoring, urban growth, natural hazards, etc. The information can be extracted from the 2x2 covariance matrix [C2] of Sentinel-1 dual-pol (VV-VH) acquisitions. To generate the covariance matrix from Sentinel-1 single look complex (SLC) data, several preprocessing steps are required. The ESA SNAP S-1 toolbox can be used to preprocess the data to generate a [C2] matrix. The polarimetric analysis in respective application fields often starts with the covariance matrix. However, due to limited availability of Sentinel-1 SLC data preprocessing workflow standards for polarimetric applications in contemporary research methods, downstream applications unable to comply with these workflows directly. In this paper, we propose a couple of generic practices to preprocess Sentinel-1 SLC data in SNAP S-1 toolbox, which would be beneficial for the radar remote sensing user community.

Crop-type mapping is an important intermediate step for cost-effective crop management at the field level, as an overview of all fields with a particular crop type can be used for monitoring or yield forecasting, for instance. Our study used a data set with 2400 fields and corresponding satellite observations from the federal state of Bavaria, Germany. The study classified corn, winter wheat, winter barley, sugar beet, potato, and winter rapeseed as the main crops grown in Upper Bavaria. We additionally experimented with a rejection class "Other", which summarised further crop types. Corresponding Sentinel-2 data included the normalised difference vegetation index (NDVI) and raw bands from 2016 to 2018 for each selected field. The influence of raw bands compared to NDVI was analysed and the classification algorithms, i.e. support vector machine (SVM) and random forest (RF), were compared. The study showed that the use of an index should be critically questioned and that raw bands provided a wider spectral bandwidth, which significantly improved the mapping of crop types. The results underline the use of RF with raw bands and achieved overall accuracies (OA) of up to 92%. We also predicted crop types in an unknown year with significantly different weather conditions and several months before the end of the growing season. Thus, the influence of climate anomalies and the accuracy depending on the time of prediction were assessed. The crop types of a test site and year without labels could be determined with an OA of up to 86%. The results demonstrate the usefulness of the proof-of-concept and its readiness for use in real applications.

The food system, the most important driver of planetary transformation, is in a deep crisis. Therefore, seeking a sustainable and socially-fair transition pathway becomes an issue of utmost priority for our own survival. The consideration of food as a commodity, a social construct that played a central role in driving this crisis, remains the uncontested narrative to lead the different transition pathways what seems rather contradictory. By exploring the normative values in the transition landscape, this paper seeks to understand how relevant is the hegemonic narrative of “food as commodity” and its alternative of “food as commons” to determine transition trajectories and food policy beliefs. Applying the Multi-level Perspective framework and developing the ill-studied “agency in transition”, this research enquired food-related professionals that belong to an online community of practice (N=95) on valuation of food dimensions and agency in food transitions to check whether the valuation of food is relevant to explain personal stances in transition. Results suggest the socially-constructed view of food as commodity is positively correlated to the gradual reforming attitude, whereas food as commons is positively correlated to the counter-hegemonic transformers regardless the self-defined position in the transition landscape (regime or niches). At personal level, there are multiple loci of resistance with counter-hegemonic attitudes in varied institutions of the regime and the innovative niches, many of them holding this discourse of food as commons. Conversely, alter-hegemonic attitudes are not positively correlated to this alternative discourse and they may inadvertently or purportedly reinforce the ‘‘neoliberal narrative’’. Food as commons, a different narrative whose rationale is explained in the paper, seems to be a relevant framework that could enrich the multiple transformative constituencies that challenge the industrial food system and therefore facilitate the convergence of movements that reject the commodification of food.

Background: On late December 2019, a viral pneumonia known as coronavirus disease 2019 (COVID-19), was originated from China and spread very rapidly in the world. Therefore, COVID-19 became a global concern and health problem. Methods: We presented four patients in this study. They were selected from patients who presented with pneumonia symptoms and were suspicious for COVID-19 and referred to the intended centers for COVID-19 diagnosis and management of Shiraz University of Medical Sciences in the south of Iran. Two nasopharyngeal and oropharyngeal throat swab samples were collected from each patient and tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection by real-time reverse-transcriptase–polymerase-chain-reaction (RT-PCR), and also samples were sent for influenza viruses and all the respiratory panel. Results: In the present report, four patients were diagnosed in the starting days of COVID-19 disease in our center in south of Iran with co-infection of SARS-CoV-2 and influenza virus. Conclusions: This co-infection of COVID-19 and influenza highlights the importance of considering SARS-CoV-2 PCR assay regardless of other positive findings for other pathogens in the primary test during the epidemic.

Almost half of the confirmed COVID-19 cases detected so far in the United Kingdom are part of a large cluster of 13 British nationals who tested positive for SARS-CoV-2 in the UK, Spain, and France. Transmissions among this cluster occurred at a ski resort in France, and originated from a single infected traveller returning from a conference in Singapore where he acquired the virus. At least 21 individuals were exposed to the virus, tested, and quarantined, with 13 of those testing positive between the period of 6th Feb and 15th Feb. Here, all publicly available information about the primarily UK/France cluster is consolidated, providing a complete and accessible summary of the cases and their connections. Notable in this cluster are the number of individuals infected, the apparent absence of any severe illness among those infected, and a case of a `delayed positive' test during isolation after initially testing negative, at least 7 days after last possible contact.

The fast spread of COVID-19 constitutes a worldwide challenge to the public health, educational, and trade systems, affecting the overall wellbeing of human societies. The high transmission and mortality rates of this virus, and the unavailability of a vaccine or treatment, resulted in the decision of multiple governments to enact measures of social distancing. Thus, it is of general interest to consider the validity of the proposal for keeping a social distancing of at least 2 m from other persons to avoid the spread of COVID-19. The exposure to the bioaerosol can result in the deposition of the pathogen in the respiratory tract of the host causing disease and an immunological response. In the atmospheric context, the work evaluates the effect of aerodynamic diameter (size) of particles in carrying RNA copies of the novel coronavirus. A SARS-CoV-2 carrier person talking, sneezing, or coughing at distance of 2 m can still provide a pathogenic bioaerosol load with submicron particles that remain viable in air for up to 3 hours for exposure of healthy persons near and far from the source in a stagnant environment. The deposited bioaerosol creates contaminated surfaces, which if touched can act as a path to introduce the pathogen by mouth, nose, or eyes and cause disease.

Reliable methods to confirm the diagnosis of COVID-19 are essential to the successful management and containment of the virus. Current diagnostic options are limited in type, supply, and reliability. This article explores the controversial unreliability of existing diagnostic methods and maintains that more reliable diagnostic methods, combinations, and sequencing are necessary to effectively assist in reducing the occurrence of discharge of the patient on false negative test results. This reduction would in effect reduce transmission of the disease.

In this era of technology, programming has become more significant than ever before. Python and C++ are both widely used programming languages. Python, the most popular programming language in today’s world, is a high-level object-oriented language whereas C++, the language behind most operating systems, is a low-level object-oriented language. In this paper, we present a comparative study of Python and C++. This paper discusses the introduction to these languages, their memory management techniques, and the reasons behind their program execution speed. Furthermore, we analyzed the execution time and memory used by multiple algorithms in both the languages with best, average, and worst cases. They are also compared with respect to the benefits and issues related to them. Results indicate that C++ is faster than Python in execution speed but Python serves as a better language for beginners due to its simplicity. Moreover, for the best results, the language should be selected according to the type of project.

Background: CD169 has been found overexpressed in the blood of COVID-19 patients and identified as a biomarker in the early disease. We have analysed CD169 in blood cells of COVID-19 patients to assess its role as predictive marker of the disease. Methods : The ratio of the CD169 Median median Fluorescence fluorescence Intensity intensity of CD169 between monocytes and lymphocytes (CD169 RMFI ) was analysed by flow cytometry in blood samples of COVID-19 patients (COV) and healthy donors (HD ) and correlated with immunophenotyping, inflammatory markers, cytokines mRNA expression, pulmonary involvement and disease progression. Results: CD169 RMFI increased in COV but not in HD. CD169 RMFI correlated with T-cell differentiation and exhaustion markers as well as with B cells maturation and differentiation. In vitro stimulation of PBMCs of HD with SARS-CoV-2 Spike spike protein induced CD169 RMFI together with IL-6 and IL-10 gene expression. Likewise, CD169 RMFI correlated with blood cytokine mRNA levels, inflammatory markers, and pneumonia severity in patients which that had not received any treatment at sampling. Notably, in untreated patients, CD169 RMFI reflected the respiratory outcome during hospitalization. Conclusion : Considering the immunological role of CD169 and its involvement during the infection and the progression of COVID-19, it could be considered as an early biomarker to evaluate disease progression and clinical outcome.

The basic idea is to expand the completed zeta function $\xi(s)$ in MacLaurin series (infinite polynomial), which can be further expressed as infinite product (Hadamard product) by conjugate complex roots. Finally, the functional equation $\xi(s)=\xi(1-s)$ leads to $(s-\alpha_i)^2 = (1-s-\alpha_i)^2, i \in \mathbb{N}$ with solution $\alpha_i= \frac{1}{2}, i \in \mathbb{N}$, where $\alpha_i$ are the real parts of the zeros of $\xi(s)$, i.e., $s_i =\alpha_i\pm j\beta_i, i\in \mathbb{N}$. Therefore, a proof of the Riemann Hypothesis is achieved.

The SARS-CoV-2 is a recently identified positive sense single stranded RNA virus and member of the coronavirus family of viruses. It is thought to be the etiological factor for the ongoing COVID-19 pandemic. This virus is thought to have originated from bats and acquired ability of human-to-human transmission. While SARS-CoV-2 is relatively benign, it has infected more than half a million people (as of March 29^th 2020) worldwide and the number of infected people continues to rise. More than 170 countries have reported COVID-19 positive cases. With a mortality rate of less than both the previous coronavirus outbreaks, COVID-19 has (conversely) caused the death of over 33,980 (as of 29^th March, 2020 at 22.00 hours EDT) people worldwide and the number is increasing. Given the enormous impact of this virus on human health and wellbeing and consequent devastating impacts on world trade, economics and quality of life, it is important to understand this virus better and get insight into its pathogenic mechanisms which will aid in devising effective measure to curb its spread and predict future pattern of its interaction with humans. Though very little is known about this SARS-CoV-2 but its mechanisms and patterns of spread can be speculated (with caution, nevertheless) from what we know about its closest relatives SARS-CoV-1 (responsible for SARS-2002 epidemic) and MERS-CoV (responsible for MERS-2012 epidemic). In the present review, we aim at bringing together the coherent and peer reviewed literature about the SARS-CoV-2 and its close relatives and try to understand its infection patterns and reconstruct its pathogenic mechanisms with anecdotes on diagnosis and future directions. We hope that this paper will serve the purpose of being a reliable source of information to scientists, clinicians and general public.

Background: Since the previous study dealing with the case fatality ratio and infection fatality ratio caused by COVID-19, the author has received many comments that prompted the question: "Why did an optimistic prognosis fail?" To answer this question, a more detailed and expanded analysis was carried out in a new study. Objective: To evaluate the dynamics of monthly numbers of cases, deaths, tests and CFR worldwide during three phases of the COVID-19 pandemic. Material and Methods: Twenty three sets of databases, dated the 22nd of each month from January 2020 to November 2021, for 213 countries were collected from the Worldometer website. The number of cases, deaths, tests, CFR, IFR, etc. were counted for various periods of time for each of the 213 countries, then results related to different periods of time were compared. Results: The analysis of the main epidemiological parameters led to the division of three phases of the global pandemic evolution. The first phase (23.01.20-22.07.20), the second phase (23.07.20-22.01.21) and the third phase (23.01.21-22.07.21) were different in terms of the number of tests performed, new cases, and mortality due to COVID-19. By the end of the second phase, the worldwide statistics indicated the imminent end of the pandemic, but the third phase was characterized by a sudden rise in the number of new cases and deaths that could not be explained rationally. The most dramatic evolution of the epidemic curve occurred in the countries where doctors had successfully battled COVID-19 during the first two phases of the pandemic. Conclusions: Despite the decrease in overall death numbers during the latest months analyzed, additional study is necessary to identify the cause for the increase in the number of new cases and deaths during the third phase of the pandemic. Only complete information regarding the positive and negative impact of medical and non-medical methods of diagnostics and prophylaxis of COVID-19 can help to organize effective measures to end the current pandemic and prevent a similar one from occurring in the future. Presumably, there are several causes of the negative evolution of the current pandemic, including the overreliance on PCR tests, application of non-specialized premises for quarantine and treatment, decrease in herd and individual immunity, inadequate change of therapeutic protocols, and ignoring prophylactic treatment. It can be suggested that the use of immunemodulatory drugs, for example, thymus extract or thymic peptides, in groups of people with compromised immunity is necessary, and prophylactic and therapeutic protocols should be changed from the 'standard' types to 'personalized' ones.

It is common knowledge that increasing CO₂ concentration plays a major role in enhancement of the greenhouse effect and contributes to global warming. The purpose of this study is to complement the conventional and established theory that increased CO₂ concentration due to human emissions causes an increase of temperature, by considering the reverse causality. Since increased temperature causes an increase in CO₂ concentration, the relationship of atmospheric CO₂ and temperature may qualify as belonging to the category of “hen-or-egg” problems, where it is not always clear which of two interrelated events is the cause and which the effect. We examine the relationship of global temperature and atmospheric carbon dioxide concentration at the monthly time step, covering the time interval 1980–2019, in which reliable instrumental measurements are available. While both causality directions exist, the results of our study support the hypothesis that the dominant direction is T → CO₂. Changes in CO₂ follow changes in T by about six months on a monthly scale, or about one year on an annual scale. We attempt to interpret this mechanism by involving biochemical reactions, as at higher temperatures soil respiration, and hence CO₂ emission, are increasing.

Cadaver bone is possibly the most common transplant material used today. Common types of cadaver bone transplants are freeze dried bone allografts and xenografts. In the case of freeze dried bone allograft transplants, it was theorized that these materials mineralize by way of osteoinduction and stimulating osteogenesis. However, these theories have been proven false. It has been proposed that these materials mineralize via osteoconduction however, there are no studies to support this hypothesis. This study was undertaken to determine how these transplants mineralize and what type of bone they produce. Materials and Methods: This study is a histological analysis of human cadaver bone graft healing from the incipient stages of mineralization through completed mineralization. All cadaver bone grafts used for evaluation in this study were particulate bone graft materials in the maxilla or mandible. No block grafts were evaluated. Results: The mineralization of cadaver bone transplants was produced by an inflammatory response to the transplanted tissue. The histologic findings of the mineralized bone produced by this process was sclerotic bone. No resorption of cadaver bone graft particles was found. When loaded the sclerotic bone was found to fail through an accumulation of microfractures.Conclusions: Particulate freeze-dried bone allografts and xenografts do not heal via the normal processes of mineralization. Cadaver bone grafts produce significant inflammation and are hypothesized to mineralize by a process termed antigenic ossification. The process of antigenic ossification produces sclerotic bone that is not capable of self-repair which can ultimately lead to bone failure.

New coronavirus (SARS-CoV-2) treatments and vaccines are under development to combat the COVID-19 disease. Several approaches are being used by scientists for investigation including 1) various small molecule approaches targeting RNA polymerase, 3C-like protease, and RNA endonuclease and 2) exploration of antibodies obtained from convalescent plasma from patients who have recovered from COVID-19. The coronavirus genome is highly prone to mutations that lead to genetic drift and escape from immune recognition; thus, it is imperative that sub-strains with different mutations are also accounted for during vaccine development. As the disease has grown to become a pandemic, new B-cell and T-cell epitopes predicted from SARS coronavirus have been reported. Using the epitope information along with variants of the virus, we have found several variants which might cause drifts. Among such variants, 23403A>G variant (p.D614G) in spike protein B-cell epitope is observed frequently in European countries such as the Netherlands, Switzerland and France.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the disease COVID-19 that has decimated the health and economy of our planet. The virus causes the disease not only in people but also in companion and wild animals. People with diabetes are at risk of the disease. As yet we do not know why the virus is highly successful in causing the pandemic within 3 months of its first report. The structural proteins of SARS include, membrane glycoprotein (M), envelope protein (E), nucleocapsid protein (N) and the spike protein (S). The structure and function of the most abundant structural protein of SARS-CoV-2, the membrane (M) glycoprotein is not fully understood. Using in silico analyses we determined the structure and potential function of the M protein. The M protein of SARS-CoV-2 is 98.6% similar to the M protein of bat SARS-CoV, maintains 98.2% homology with pangolin SARS-CoV, and has 90% homology with M protein of SARS-CoV; whereas, the similarity was only 38% with the M protein of MERS-CoV. In silico analyses showed that the M protein of SARS-CoV-2 has a triple helix bundle, form a single 3-transmembrane domain (TM), and are homologous to the prokaryotic sugar transport protein semiSWEET. SemiSWEETs are related to the PQ-loop family that function as cargo receptors in vesicle transport, mediates movement of basic amino acids across lysosomal membranes, and is also involved in phospholipase flippase function. The advantage and role of the M protein having a sugar transport-like structure is not clearly understood. The M protein of SARS-CoV-2 interacts with S, E and N protein. The S protein of the virus is glycosylated. It could be hypothesized that the sugar transporter-like structure of the M protein influences glycosylation of the S protein. Endocytosis is critical for the internalization and maturation of RNA viruses, including SARS-CoV-2. Sucrose is involved in endosome and lysosome maturation and may also induce autophagy, pathways that help in the entry of the virus. Overall, it could be hypothesized that the semiSWEET sugar transporter-like structure of the M protein may be involved in multiple functions that may aid in the rapid proliferation, replication and immune evasion of the SARS-CoV-2 virus. Biological experiments would validate the presence and function of the semiSWEET sugar transporter.

The prevalence of corona virus and the novel COVID-19 disease in the entire globe has exacerbated different impact on socioeconomic spectrum in the world, including water use pattern. Thus a research was conducted to examine the comparative use of water during pre- and post-COVID-19 lockdown pattern among post-primary schools in Iwo, Osun State, Nigeria. A survey was conducted among fifteen schools which were randomly selected, but with eight public and seven private schools for the investigation. Both descriptive and inferential statistical techniques were used in data analysis. The results revealed that the major source of water to the schools investigated is ground water which is obtained through hand-dug wells and boreholes. It was further discovered that there was increase in water use during post-COVID-19 lockdown era as a result of the directive by the government that clean water should be provided for hand-washing by all schools regardless of the owner to curtail the spread of COVID-19 disease in the country. One sample t-test also revealed that there was a significant difference in water use at (p<0.01) level. It is recommended that the government and other stakeholders in water sector to ensure that all-time and non-seasonal dependent source of water be provided rather than ground water source which is susceptible to variations in water yields from seasonal variations. This will enable continuous clean water supply, for all purposes, including COVID-19 protocols.

After the appearance of first cases of ‘pneumonia of unknown origin’ in the Wuhan city, China, during late 2019, the disease progressed fast. Its cause was identified as a novel coronavirus, named provisionally 2019-nCoV. Subsequently, an official name was given as SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus-2) by the International Committee on Taxonomy of Viruses (ICTV) study group. The World Health Organization (WHO) named the Coronavirus disease-2019 as COVID-19. The epidemics of COVID-2019 have been recorded over 113 countries/territories/areas apart from China and filched more than 4292 humans, affecting severely around 1,18,326 cases in a short span. The status of COVID-2019 emergency revised by the WHO within 42 days from Public Health International Emergency (January 30, 2020) to a pandemic (March 11, 2020). Nonetheless, the case fatality rate (CFR) of the current epidemic is on the rise (between 2-4%), relatively is lower than the previous SARS-CoV (2002/2003) and MERS-CoV (2012) outbreaks. Even though investigations are on its way, the researchers across the globe have assumptions of animal-origin of current SARS-CoV-2. A recent case report provides evidence of mild COVID-2019 infection in a pet dog that acquired COVID-2019 infection from his owner in Hong Kong. The news on travellers associated spread across the globe have also put many countries on alert with the cancellation of tourist visa to all affected countries and postponement of events where international visits were required. A few diagnostic approaches, including quantitative and differential real-time polymerase chain reaction assays, have been recommended for the screening of the individuals at risk. In the absence of any selective vaccine against SARS-CoV-2, re-purposed drugs are advocated in many studies. This article discourse the current worldwide situation of COVID-2019 with information on virus, epidemiology, host, the role of animals, effective diagnosis, therapeutics, preventive and control approaches making people aware on the disease outcomes.

The Covid-19 has hit Italy in February 2020 after its outbreak in China at the beginning of January. But why Italy first among Western countries? What are the conditions that made Italy more vulnerable and the first target of such disease? What characteristics and what diffusion patterns could be highlighted and hypothesized, from the outbreak to the end of March 2020, after containment measures - including a national lock down – were introduced? In this paper we try to provide some answers to these questions, analyzing the issue from the medical, geographical and planning points of view. In particular, we started from a hypothesis of very similar economic, geographical, climatic and environmental conditions of the areas of Wuhan – in Hubei Province in China, the outbreak of the epidemics – and the Po Valley area – in Italy – where most cases and deaths were registered. Adopting an ecological approach, we compared the spatial distribution and pattern of Covid-19-related mortality in Italy with several geographical, environmental and socio-economic variables at Provincial level, analyzing them by means of spatial analytical techniques as LISA – Local Indicators of Spatial Association. Possible evidence relating Covid-19 cases and Nitrogen-related pollutants and land take arise, particularly in the Po Valley area.

Background: Covid-19 was first reported in Wuhan, China in Dec 2019. Since then, it has been transmitted rapidly in China and the rest of the world. While Covid-19 transmission rate has been declining in China, it is increasing exponentially in Europe and America. Although there are numerous studies examining Covid-19 infection, including an archived paper looking into the meteorological effect, the role of outdoor air pollution has yet to be explored rigorously. It has been shown that air pollution will weaken the immune system, and increase the rate of respiratory virus infection. We postulate that outdoor air pollution concentrations will have a negative effect on Covid-19 infections in China, whilst lockdowns, characterized by strong social distancing and home isolation measures, will help to moderate such negative effect. Methods: We will collect the number of daily confirmed Covid-19 cases in 31 provincial capital cities in China during the period of 1 Dec 2019 to 20 Mar 2020 (from a popular Chinese online platform which aggregates all cases reported by the Chinese national/provincial health authorities). We will also collect daily air pollution and meteorology data at the city-level (from the Chinese National Environmental Monitoring Center and the US National Climatic Data Center), daily inter-city migration flows and intra-city movements (from Baidu). City-level demographics including age distribution and gender, education, and median household income can be obtained from the statistical yearbooks. City-level co-morbidity indicators including rates of chronic disease and co-infection can be obtained from related research articles. A regression model is developed to model the relationship between the infection rate of Covid-19 (number of confirmed cases/population at the city level) and outdoor air pollution at the city level, after taking into account confounding factors such as meteorology, inter- and intra-city movements, demographics, and co-morbidity and co-infection rates. In particular, we shall study how air pollution affects infection rates across different cities, including Wuhan. Our model will also study air pollution would affect infection rates in Wuhan before and after the lockdown. Expected findings: We expect there be a correlation between Covid-19 infection rate and outdoor air pollution. We also expect that reduced intra-city movement after the lockdowns in Wuhan and the rest of China will play an important role in reducing the infection rate. Interpretation: Infection rate is growing exponentially in major cities worldwide. We expect Covid-19 infection rate is related to the air pollution concentration, and is strongly dependent on inter- and intra-city movements. To reduce the infection rate, the international community may deploy effective air pollution reduction plans and social distancing policies.

The recently emerged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a major outbreak of coronavirus disease 2019 (COVID-19) and instigated a widespread fear and has threatened global health security. Although phenomenal efforts are in progress to effectively combat this COVID-19 outbreak. Still, no licensed antiviral drugs or vaccines are available, and treatment is limited to supportive care and few repurposed drugs. In this urgency situation, computational drug discovery methods provide both an alternative and a supplement to tiresome high-throughput screening, particularly in the hit-to-lead-optimization stage. Identification of small molecules that specifically target viral replication apparatus has shown the most successful strategy in antiviral drug discovery. The present study deals with the identification of potential compounds that specifically interact with SARS-CoV-2 vital proteins, including main protease (Mpro), Nsp12 RNA-dependent-RNA-polymerase (RdRp) and Nsp13 helicase. A constructive and integrated virtual screening efforts together with molecular dynamics simulations identified potential binding modes and favourable molecular interaction profile of corresponding compounds. Moreover, structurally important binding site residues in conserved motifs located inside the active site are elucidated, which displayed relative importance in ligand binding based on residual energy decomposition analysis. Although the current study lacks experimental validation, the structural information obtained from this computational study paved the way to identify and design specific targeted inhibitors to combat COVID-19 outbreak.

This paper reports on in-depth qualitative interviews conducted with 69 disabled people in England and Scotland, and with 28 key informants from infrastructure organisations in the voluntary and statutory sectors, about the impact of COVID-19, and measures taken to control it. Participants were recruited through voluntary organisations. As with everyone, the Pandemic has had a huge impact: we discuss the dislocations it has caused in everyday life; the failures of social care; the use of new technologies; and participants’ view on leadership and communication. We conclude with suggestions for urgent short term and medium term responses, so that the United Kingdom and other countries can respond better to this and other pandemics, and build a more inclusive world.

The Public Health Alliance for Genomic Epidemiology (PHA4GE) (https://pha4ge.org) is a global coalition that is actively working to establish consensus standards, document and share best practices, improve the availability of critical bioinformatic tools and resources, and advocate for greater openness, interoperability, accessibility and reproducibility in public health microbial bioinformatics. In the face of the current pandemic, PHA4GE has identified a clear and present need for a fit-for-purpose, open source SARS-CoV-2 contextual data standard. As such, we have developed an extension to the INSDC pathogen package, providing a SARS-CoV-2 contextual data specification based on harmonisable, publicly available, community standards. The specification is implementable via a collection template, as well as an array of protocols and tools to support the harmonisation and submission of sequence data and contextual information to public repositories. Well-structured, rich contextual data adds value, promotes reuse, and enables aggregation and integration of disparate data sets. Adoption of the proposed standard and practices will better enable interoperability between datasets and systems, improve the consistency and utility of generated data, and ultimately facilitate novel insights and discoveries in SARS-CoV-2 and COVID-19.

SARS-CoV-2, the novel coronavirus behind COVID-19 pandemic is acquiring new mutations in its genome. Although some mutations provide benefits to the virus against human immune response, a number of them may result in their reduced pathogenicity and virulence. By analyzing more than 3000 high-coverage, complete genome sequences deposited in the GISAID database, here I report a unique 28881-28883:GGG>AAC trinucleotide-bloc mutation in the SARS-CoV-2 genome that results in two sub-strains, described here as SARS-CoV-2g (28881-28883:GGG genotype) and SARS-CoV-2a (28881-28883:AAC genotype). Computational analysis and literature review suggest that this bloc mutation would bring 203-204:RG(arginine-glycine)>KR(lysine-arginine) amino acid changes in the nucleocapsid (N) protein affecting the SR (serine-arginine)-rich motif of the protein, a critical region for the transcription of viral RNA and replication of the virus. Thus, 28881-28883:GGG>AAC bloc-mutation is expected to modulate the pathogenicity of the SARS-CoV-2. Remarkably, SARS-CoV-2g and SARS-CoV-2a strains can be linked with the heterogeneity of COVID-19 cases across different regions within and between countries by analyzing existing data. Sequence analysis suggests that severely affected cities, such as Milan, Lombardy, New York, Paris have the predominant presence of SARS-CoV-2g strains, whereas less affected places like Abruzzo, Lyon, Valencia have a relatively higher presence of SARS-CoV-2a, an indication that the latter strain may contribute to the reduced cases of COVID-19. A similar relationship is observed when Netherlands, Portugal are compared with Spain, France and Germany. These analyses suggest that the SARS-CoV-2 has already evolved into a less infective SARS-CoV-2a affecting COVID-19 cases in different regions. The time a country or region needs to acquire SARS-CoV-2a strains may be indicative to the time it would need to overcome the peak of the COVID-19 cases. To confirm these assumptions, prompt retrospective and prospective epidemiological studies should be conducted in different countries to understand the course of pathogenicity of the SARS-CoV-2a and SARS-CoV-2g. Potential drugs can be designed targeting 28881-28883 region of the N protein to modulate virus pathogenicity.

During the current COVID-19 pandemic caused by SARS-CoV-2, clinicians and scientists are working assiduously to unravel its pathophysiology and find effective treatments. An impressive number of papers has been published on SARS-CoV-2, exposing the complexity of the disease, the tendency of scientists to form hypotheses within their area of expertise, and the lack of orchestration of research. Hypotheses and research findings mainly complement each other, though sometimes controversies can be discerned among various theories and study results. Our overview aims to portray the ‘big picture’ of COVID-19, visualising the interwovenness of different pathophysiological pathways, with a focus on cytokine-induced pathology, the sequelae of ACE2 downregulation, and thrombosis associated with microvascular injury. It aids in overseeing the effects of repurposed drugs on intended targets, but also alerts to the (adverse) effects on interacting pathways. The overview shows how comorbidities probably increase susceptibility to (severe) COVID-19 and provides the possible pathophysiological origin of signs, symptoms, and biochemical abnormalities.

In this paper we propose a novel self-supervised approach of keywords and keyphrases retrieval and extraction by an end-to-end deep learning approach, which is trained by contextually self-labelled corpus. Our proposed approach is novel to use contextual and semantic features to extract the keywords and has outperformed the state of the art. Through the experiment the proposed approach has been proved to be better in both semantic meaning and quality than the existing popular algorithms of keyword extraction. In addition, we propose to use contextual features from bidirectional transformers to automatically label short-sentence corpus with keywords and keyphrases to build the ground truth. This process avoids the human time to label the keywords and do not need any prior knowledge. To the best of our knowledge, our published dataset in this paper is a fine domain-independent corpus of short sentences with labelled keywords and keyphrases in the NLP community.

Global severity maps of ongoing dengue epidemic and COVID-19 pandemic do not overlap. Countries with high dengue endemicity (>1.5 million cases/year) are observably less hit by COVID-19 in terms of infection, transmission and mortality. Based on non-overlap of dengue and COVID-19 severity maps and evidence of SARS-CoV-2 serological cross-reactions with dengue, we wonder whether immediate immunization of susceptible populations in Europe, North America and Asia (China, Iran) with available live-attenuated dengue vaccines, will cue the anti-viral immune response to thwart COVID-19 (viral interference). Risk of developing post-vaccination “Antibody-dependent Enhancement” is low as dengue is not endemic in the aforesaid regions.

Introduction: The majority of epidemiological reports focus on confirmed cases of COVID-19. In this study, we aim to assess the health and well-being of adults not infected with Covid-19 after two months of quarantine in Morocco. Materials and methods: Two months after the declaration of quarantine in Morocco following the Covid-19 epidemic, we carried out a descriptive cross-sectional study of 279 Moroccan citizens. We used the Short Form Health Survey (SF-12) as a determinant of quality of life, which is based on eight dimensions of health. The data were collected using an electronic questionnaire distributed online. The participants also indicated their socio-demographic data, their knowledge and practices regarding the Covid-19 pandemic and whether they had chronic health problems. Results: The quality of life of all participants was moderately disrupted during the Covid-19 pandemic with a mental health score (MCS) of 34.49 (± 6.44) and a physical health score (PCS) of 36.10 (± 5.82). Participants with chronic diseases scored lower with 29.28 (± 1.23) in mental health (MCS) and 32.51 (± 7.14) in physical health (PCS). The seriousness of COVID-19 has an impact on the quality of life and health well-being of people and this impact is more marked in people with chronic health problems. Conclusion: Our results confirm the need to pay attention to the health of people who have not been infected with the virus. Our results also point out that uninfected people with chronic illnesses may be more likely to have well-being problems due to quarantine restrictions.

This paper gives an overview of the large-scale tectonic styles encountered in orogens worldwide. Thin-skinned and thick-skinned tectonics represent two end member styles recognized in mountain ranges. Both styles are encountered in former passive margins of continental plates. Thick-skinned style including the entire crust and possibly the lithospheric mantle are associated with intracontinental contraction. Delamination of subducting continental crust and horizontal protrusion of upper plate crust into the opening gap occurs in the terminal stage of continent-continent collision. Continental crust thinned prior to contraction is likely to develop relatively thin thrust sheets of crystalline basement. A true thin-skinned type requires a detachment layer of sufficient thickness. Thickness of the décollement layer as well as the mechanical contrast between décollement layer and detached cover control the style of folding and thrusting within the detached cover units. In subduction-related orogens, thin- and thick-skinned deformation may occur several hundreds of kilometers from the plate contact zone. Basin inversion resulting from horizontal contraction may lead to the formation of basement uplifts by the combined reactivation of pre-existing normal faults and initiation of new reverse faults. In most orogens thick-skinned and thin-skinned structures both occur and evolve with a pattern where nappe stacking propagates outward and downward

One notable features of the SARS-CoV-2 genome is that the spike protein of SARS-CoV-2 has a functional polybasic (furin) cleavage site (RRAR) at the S1–S2 boundary through the insertion of 12 nucleotides encoding PRRA. To date, the furin cleavage site (FCS) remains an experimentally uncharted territory both structurally and functionally. For instance, whether or not FCS is actually cleaved, before or after viral cell entry or exit, still remains to be experimentally investigated. With currently available structural data, this article presents a computational structural characterization of the FCS inserted into SARS-CoV-2 spike glycoprotein, and puts forward a set of structural hypothesis against the hypothesis of SARS-CoV-2 from purposeful manipulation: (1), the inserted FCS does not alter, neither stabilize nor de-stabilize, the overall structure of SARS-CoV-2 spike glycoprotein; (2), the net structural consequence of FCS is the insertion of a furin cleavage site into SARS-CoV-2 spike glycoprotein, whose S1 and S2 subunits will still be bonded together even if the FCS is actually cleaved by furin protease.

Biomolecular structure drives function, and computational capabilities have progressed such that the prediction and computational design of biomolecular structures is increasingly feasible. Because computational biophysics attracts students from many different backgrounds and with different levels of resources, teaching the subject can be challenging. One strategy to teach diverse learners is with interactive multimedia material that promotes self-paced, active learning. We have created a hands-on education strategy with a set of fifteen modules that teach topics in biomolecular structure and design, from fundamentals of conformational sampling and energy evaluation to applications like protein docking, antibody design, and RNA structure prediction. Our modules are based on PyRosetta, a Python library that encapsulates all computational modules and methods in the Rosetta software package. The workshop-style modules are implemented as Jupyter Notebooks that can be executed in the Google Colaboratory, allowing learners access with just a web browser. The digital format of Jupyter Notebooks allows us to embed images, molecular visualization movies, and interactive coding exercises. This multimodal approach may better reach students from different disciplines and experience levels as well as attract more researchers from smaller labs and cognate backgrounds to leverage PyRosetta in their science and engineering research. All materials are freely available at https://github.com/RosettaCommons/PyRosetta.notebooks.

Currently, there is no effective antiviral therapy recommended for the new coronavirus disease 2019 pneumonia (COVID-19). The purpose of this pilot study was to evaluate the safety of Ozonized Saline Solution (O₃SS) used as a complementary therapy in adult patients COVID-19. Twenty-five adult patients who were hospitalized with mild to severe COVID-19 symptoms, who met the inclusion criteria and were being treated from April 18^rd to April 26th, 2020, at the Viamed Virgen De La Paloma Hospital, Madrid, Spain were included in this study. Patients were allocated to receive standard care (SC) that included 200-400 mg hydroxychloroquine twice daily for 5-7 days plus Tocilizumab 400 mg twice daily for 5 days, low molecular weight heparin (LMWH) and 40 mg-60 mg metil-prednisone plus O₃SS, 200 mL, 3-5 µg/mL daily for 10 days. No control group was included, data were compared to clinical trials in this subject. Primary outcomes of treatment with O₃SS were an improvement of clinical symptoms and a reduction in mortality. Secondary end points evaluated included participant clinical status, laboratory examinations, and duration of viral shedding. None of the patients treated with SC + O₃SS died. Improvements in symptoms such as dyspnea, weakness, and reduction in body temperature were observed and corresponded with an improvement of laboratory finding including D-dimer, fibrinogen, LDH, and CRP. No side effects from the O₃SS treatment were observed. Conclusions: COVID-19 patients with mild to severe symptoms who received intravenous O₃SS as a complementary therapy demonstrated no side effects. This preliminary data will be served as base for a future study of the efficacy of this therapy.

The COVID-2019 disease caused by the SARS-CoV-2 virus (aka 2019-nCoV) has raised significant health concerns in China and worldwide. While novel drug discovery and vaccine studies are long, repurposing old drugs against the COVID-2019 epidemic can help identify treatments, with known preclinical, pharmacokinetic, pharmacodynamic, and toxicity profiles, which can rapidly enter Phase 3 or 4 or can be used directly in clinical settings. In this study, we presented a novel network based drug repurposing platform to identify potential drugs for the treatment of COVID-2019. We first analysed the genome sequence of SARS-CoV-2 and identified SARS as the closest disease, based on genome similarity between both causal viruses, followed by MERS and other human coronavirus diseases. Using our AutoSeed pipeline (text mining and database searches), we obtained 34 COVID-2019-related genes. Taking those genes as seeds, we automatically built a molecular network for which our module detection and drug prioritization algorithms identified 24 disease-related human pathways, five modules and finally suggested 78 drugs to repurpose. Following manual filtering based on clinical knowledge, we re-prioritized 30 potential repurposable drugs against COVID-2019 (including pseudoephedrine, andrographolide, chloroquine, abacavir, and thalidomide) . We hope that this data can provide critical insights into SARS-CoV-2 biology and help design rapid clinical trials of treatments against COVID-2019.

In this review, we address issues that relate to the rapid “Warp Speed” development of vaccines to counter the COVID-19 pandemic. We review the antibody response that is triggered by SARS-CoV-2 infection of humans, and how it may inform vaccine research. The isolation and properties of neutralizing monoclonal antibodies from COVID-19 patients provide additional information on what vaccines should try to elicit. The nature and longevity of the antibody response to coronaviruses are relevant to the potency and duration of vaccine-induced immunity. We summarize the immunogenicity of leading vaccine candidates tested to date in animals and humans, and discuss the outcome and interpretation of virus-challenge experiments in animals. By far the most immunogenic vaccine candidates for antibody responses are recombinant proteins, which are not included in the initial wave of “Warp Speed” immunogens. A substantial concern for SARS-CoV-2 vaccines is adverse events, which we review by considering what was seen in studies of SARS-CoV-1 and MERS-CoV vaccines. We conclude by outlining the possible outcomes of the “Warp Speed” vaccine program, which range from the hoped-for rapid success to a catastrophic adverse influence on vaccine uptake generally.

The global coronavirus (COVID-19) pandemic has created a whole new set of risks in construction industries generating unprecedented delays, disruptions, and uncertainty on construction projects, and has forced the industries in adopting more sophisticated technologies while combating the reduced workforce on job sites. Further, the post-pandemic era of construction is expected to be a lot different as the industries will embrace the technology as the augmentation and collaboration strategy. Thus, it will be extremely hard to sustain for construction industries in the absence of effective risk management. The existing risk plans need to be inspected for their capability of handling new risks arising from COVID-19 and the project managers will need to make the necessary revisions as needed. This paper discusses on past (NORM), present (NEW NORM), and future (Post COVID-19 NORM) of the construction industry and highlights key strategies for managing projects and construction risks during and post COVID-19 pandemic.

This paper presents an exact solution to the Timoshenko beam theory (TBT) for first-order analysis, second-order analysis, and stability. The TBT covers cases associated with small deflections based on shear deformation considerations, whereas the Euler–Bernoulli beam theory (EBBT) neglects shear deformations. Thus, the Euler–Bernoulli beam is a special case of the Timoshenko beam. The moment-curvature relationship is one of the governing equations of the EBBT, and closed-form expressions of efforts and deformations are available in the literature. However, neither an equivalent to the moment-curvature relationship of EBBT nor closed-form expressions of efforts and deformations can be found in the TBT. In this paper, a moment-shear force-curvature relationship, the equivalent in TBT of the moment-curvature relationship of EBBT, was presented. Based on this relationship, first-order and second-order analyses were conducted, and closed-form expressions of efforts and deformations were derived for various load cases. Furthermore, beam stability was analyzed and buckling loads were calculated. Finally, first-order and second-order element stiffness matrices were determined.

Background: Gut-Brain-Axis provides bidirectional communicational route; imbalance of which can have pathophysiological consequences. It is a frontier in autism research, affects 85% of autistic children (NIH report). Their microbiome has few overall microbes and smaller number of health promising microbes than their neurotypical peers. We hypothesize autism gut might play a role in manifestation of autism behaviours and on treatment, can revert back to normal behaviour considerably. The aim is to better understand to what degree gut microbiota of autism subjects differs from controls and identify bacterial species present exclusively in autism. Materials and Methods: 16s-rRNA-sequence of autism-subjects were retrieved from the American Gut Project Archive. Taxonomic assignment was inferred by similarity based methods using Quantitative Insights Into Microbial Ecology (QIIME). Species abundance was characterized and co-occurrence network was built to infer species interaction using measures of diversity. Statistical parameters were considered to validate the findings. Result: A total of 206 (1.8%) of American Gut Project datasets onstituted of autistic samples. Various bacteria such as Akkermansia sp., and Prevotella sp., were harboured in higher abundance in autistic children with statistical significance than in controls. Conclusion: These findings indicate connecting-link between gut-microbiome-brain-axis and autistic behaviour which can result in improved management

Large-scale hydrological modeling in China is challenging given the sparse meteorological stations and large uncertainties associated with atmospheric forcing data.Here we introduce the development and use of the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) in the Heihe River Basin(HRB) for improving hydrologic modeling, by leveraging the datasets from the China Meteorological Administration Land Data Assimilation System (CLDAS)(including climate data from nearly 40000 area encryption stations, 2700 national automatic weather stations, FengYun (FY) 2 satellite and radar stations). CMADS uses the Space Time Multiscale Analysis System (STMAS) to fuse data based on ECWMF ambient field and ensure data accuracy. In addition, compared with CLDAS, CMADS includes relative humidity and climate data of varied resolutions to drive hydrological models such as the Soil and Water Assessment Tool (SWAT) model. Here, we compared climate data from CMADS, Climate Forecast System Reanalysis (CFSR) and traditional weather station (TWS) climate forcing data and evaluatedtheir applicability for driving large scale hydrologic modeling with SWAT. In general, CMADS has higher accuracy than CFRS when evaluated against observations at TWS; CMADS also provides spatially continuous climate field to drive distributed hydrologic models, which is an important advantage over TWS climate data, particular in regions with sparse weather stations. Therefore, SWAT model simulations driven with CMADS and TWS achieved similar performances in terms of monthly and daily stream flow simulations, and both of them outperformed CFRS. For example, for the three hydrological stations (Ying Luoxia, Qilian Mountain, and ZhaMasheke) in the HRB at the monthly and daily Nash-Sutcliffe efficiency ranges of 0.75-0.95 and 0.58-0.78, respectively, which are much higher than corresponding efficiency statistics achieved with CFSR (monthly: 0.32-0.49 and daily: 0.26 – 0.45). The CMADS dataset is available free of charge and is expected to a valuable addition to the existing climate reanalysis datasets for deriving distributed hydrologic modeling in China and other countries in East Asia.

Abstract: COVID-19 in 2020 brought challenges to the Brazilian public health system with an emerging virus with respiratory contagion called SARS-CoV-2. There are few studies in Brazil and in some countries, on the increased incidence of certain viral respiratory infections, includ-ing H1N1 and coronavirus and their association with low levels of vitamin D, zinc and iron. The aim of this study was to demonstrate that the deficit of vitamin D, zinc and iron has an impact on the infectious process of patients with COVID-19 and to establish new forms of prevention for the worsening of COVID-19 in the human body. Data were collected from medical records and test results from patients being followed up during the treatment period for COVID-19. Patients with low blood levels of vitamin D, zinc and iron during the treatment period of COVID-19 had a higher percentage of worsening and complications requiring hospitalization in intensive care beds. The ingestion of vitamin D, zinc and iron in the treatment period of patients with COVID-19 in addition to being an immunological protector against SARS-CoV-2 and alleviating the process of worsening the disease can also act as a biomarker in cases of this disease.

Since the first case of 2019 novel coronavirus disease (COVID-19) detected on Jan 30, 2020, in India, the number of cases rapidly increased to 3819 cases including 106 deaths as of 5 April 2020. Taking this into account, in the present work, we are studying a Bats-Hosts-Reservoir-People transmission fractional-order COVID-19 model for simulating the potential transmission with the thought of individual social response and control measures by the government. The real data available about infectious cases from $14^{th}$ March to $26^{th}$ March 2020 is analysed and accordingly various parameters of the model are estimated or fitted. The Picard successive approximation technique and Banach's fixed point theory have been used for verification of the existence and stability criteria of the model. Numerical computations are done utilizing the iterative Laplace transform method. In the end, we illustrate the obtained results graphically. The purpose of this study is to estimate the effectiveness of preventive measures, predicting future outbreaks and potential control strategies using the mathematical model.

The City of Meycauayan is considered as one of the most polluted cities in the developing world on the account of industrial discharges of toxic materials to the environment. This work investigated the sources of the heavy metal pollution by analyzing soil and sediment samples for heavy metals (Cr, Hg, Ni, and Pb) together with selected environmental indicators (TN, TOM, and TP) located along the Meycauayan River. Hierarchical cluster analysis (HCA), principal components analysis (PCA), and Pearson correlation analysis (CA) were used to identify the sources of the metals. Results showed delineated locations of severe levels of heavy metal pollution downstream because of the concentration of industrial activities. Cr contributed more than any other heavy metals analyzed due to proliferation of tanneries discharging untreated wastewaters to the river. Significant inputs of Pb and Hg from Pb-acid battery recycling and gold smelting industries were also found. Risk assessments indicated severe levels of heavy metal pollution where industrial activities are concentrated. The mean Cr, Pb, Ni, and Hg in the sampling locations have mean incidences of toxicity of 91.7 %, 53.6 %, 27.7 %, and 70.0 %, respectively. Our study showed a serious need to address heavy metal pollution in Meycauayan.

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a frequent, debilitating and still enigmatic disease. There is a broad overlap in the symptomatology of ME/CFS and the Post-COVID Syndrome (PCS). A fraction of the PCS patients develops the full clinical picture of ME/CFS. New observations in microvessels and blood from patients suffering from PCS have appeared and include microclots and malformed pathological blood cells. Capillary blood flow is impaired not only by pathological blood components but also by prothrombotic changes in the vascular wall, endothelial dysfunction, and expression of adhesion molecules in the capillaries. These disturbances can finally cause a low capillary flow and even capillary stasis. A low cardiac stroke volume due to hypovolemia and the inability of the capacitance vessels to adequately constrict to deliver the necessary cardiac preload generate an unfavorable low precapillary perfusion pressure. Furthermore, a predominance of vasoconstrictor over vasodilator influences exists, in which sympathetic hyperactivity and endothelial dysfunction play a strong role, causing constriction of resistance vessels and of precapillary sphincters which leads to a fall in capillary pressure behind the sphincters. The interaction of these two precapillary cardiovascular mechanisms causing a low capillary perfusion pressure is hemodynamically highly unfavorable in the presence of a primary capillary stasis already caused by the pathological blood components and their interaction with the capillary wall, to severely impair organ perfusion. The detrimental coincidence of the microcirculatory with the precapillary cardiovascular disturbances may constitute the key disturbance of the Post-COVID-19 syndrome and finally lead to ME/CFS in pre-disposed patients because the interaction causes a particular kind of perfusion disturbance - capillary ischemia-reperfusion - which has a high potential of causing mitochondrial dysfunction by inducing sodium- and calcium-overload in skeletal muscles. The latter in turns worsens the vascular situation by the generation of reactive oxygen species to close a vicious cycle from which the patient can hardly escape.

Italian, Spanish, French vs German, Austrian or Norwegian COVID-19 tracks? Antibiotics might have a partial impact on COVID-19 death rates in various countries. Our working hypotheses based on recent publications is that that antibiotics may be a major factor that negatively affects patients’ immune system during viral infections. We are all aware that there is no specific and effective medical treatment for COVID-19 so far. However, we know that our immune system is the only efficient weapon that fights against this syndrome right now. In fact, antibiotics are very often prescribed to prevent secondary infections following an antiviral immune response. Various antibiotic therapies have also been commonly applied to support COVID-19 treatments in China and Italy. Unfortunately, the frequent antibiotic off-site targets include mitochondria that are genetically and evolutionary closely linked to bacteria. Mitochondria are multifunctional organelles responsible for bioenergetics in nearly all our cells, acting as signaling hubs in antiviral and antibacterial immune responses. Several studies have demonstrated that mitochondria are vulnerable to antibacterial treatments, interrupting their physiology. Inhibition of these processes by antibiotics might render the immune system less capable of fighting acute COVID-19 viral infections. Some antibiotics, including those prescribed for COVID-19 in Wuhan, have been shown to inhibit the synthesis of mitochondrial DNA. The question is whether antibiotics support such a treatment or weaken patient immune responses in this case. This hypothesis should be evaluated based on comparative clinical data that seem to be unavailable at the moment. Possibly the COVID-19 risk group should be extended to all patients being treated with antibiotics, including those who finished antibiotic therapies days up to several months before SARS-CoV-2 infection. We therefore urge health service response groups to evaluate the impact of antibiotics on COVID-19 recovery vs death retrospective data. We would like to motivate international, national and local health authorities to share available clinical treatment data, discuss and optimize treatment strategies.

A single dose of psilocybin, a psychedelic and serotonin 2A receptor (5-HT2AR) agonist, may be associated with antidepressant effects. The mechanism behind its antidepressive action is unknown but could be linked to increased synaptogenesis and down-regulation of cerebral 5-HT2AR. Here, we investigate if a single psychedelic dose of psilocybin changes synaptic vesicle protein 2A (SV2A) and 5-HT2AR density in the pig brain. Twenty-four awake pigs received either 0.08 mg/kg psilocybin or saline intravenously. Twelve pigs (n=6/intervention) were euthanized one day post-injection, while the remaining twelve pigs were euthanized seven days post-injection (n=6/intervention). We performed autoradiography on hippocampus and prefrontal cortex (PFC) sections with [3H]UCB-J (SV2A), [3H]MDL100907 (5-HT2AR antagonist) and [3H]Cimbi-36 (5-HT2AR agonist). One day post psilocybin injection, we observed 4.4% higher hippocampal SV2A density and lowered hippocampal and PFC 5-HT2AR density (-15.21% to -50.19%). These differences were statistically significant in the hippocampus for all radioligands and in PFC for [3H]Cimbi-36 only. Seven days post-intervention, there was still significantly higher SV2A density in hippocampus (+9.24%) and PFC (+6.1%) whereas there were no longer any differences in 5-HT2AR density. Our findings suggest that psilocybin’s antidepressive actions are linked to increased persistent synaptogenesis and possibly also to an acute decrease in 5-HT2AR density.

The greatest pandemic of the century, COVID-19, is an ongoing global public health problem. With a clinically approved treatment available only for those who are acutely ill and are hospitalized, the control of this disease in the general population is still largely dependent on the preventive measures issued by the World Health Organization. Among the general control measures other than immunization with the COVID-19 vaccines, handwashing with soap and water has been emphasized the most because it is cost-effective and easily accessible to the general public. Studies have reported that soaps offer unique chemical properties that can completely destroy enveloped viruses. However, the general public seems to be still uncertain about whether soaps can shield us from a highly contagious disease such as COVID-19. In an attempt to help eliminate the uncertainty, we analyzed the mechanisms underlying the efficacy of soap and its prospect for preventing the spread of COVID-19. In this paper, we provide an overview of the history and characteristics of the SARS-CoV-2 virus, the current global COVID-19 situation, the possible mechanisms of the deactivation of viruses by soaps, and the potential effectiveness of soap in eliminating coronaviruses including SARS-CoV-2.

This document outlines best practice recommendations for an acute care physiotherapy for patients with COVID-19, with an emphasis on critical care rehabilitation including the patients in extra corporeal membrane Oxygenation (ECMO) support, developed for practice in Qatar but adaptable within any settings. This recommendation is the result of a combination of systematic evidence search, subsequent critical evaluation of retrieved evidence and consensus process. The agreed recommendations were integrated into a physiotherapy clinical reasoning algorithm. It includes recommendations on physiotherapy referral, screening, management categories and best practice recommendations. It is intended for use by physiotherapists and other relevant stakeholders in the acute care setting caring for adult patients with suspected and/or confirmed COVID-19.

Draconian defensive measures have been implemented to combat the COVID-19 pandemic outbreak. These important measures constitute a vital current priority but do little to increase communal immunity and avoid future outbreaks. A longer-term exit strategy for a sustainable return to normalcy has yet to be identified. The development of vaccines or effective therapeutics could largely solve the problem, but their timely development cannot be guaranteed. In this setting, and under the expected societal isolation fatigue from extended social distancing, we here propose the idea that at some point after the outbreak’s peak, hospitals, in addition to providing care for infected people who need it, could also be involved in the development of a controlled exit strategy designed to avoid future outbreaks. We postulate that controlled voluntary deliberate infection in a hospital setting and under continuous and close medical observation may offer a safer alternative compared to random en-masse exposure. We discuss potential risks and benefits, highlighting the need for careful consideration of the associated critical ethical issues.

Urban green spaces provide a range of environmental and health benefits, which may become even more critical during times of crisis such as the current COVID-19 pandemic. However, with a radical shift in mobility, additional concerns over safety, and access temporarily restricted during the implementation of social distancing policies, the experience and use of urban green spaces may be reduced. This is particularly concerning for densely populated cities like New York, considered the first U.S. epicenter or vanguard of the outbreak. To better understand the impact of COVID-19 on the perception and use of urban green spaces, we conducted a social survey during the early months of the Covid-19 pandemic in New York City (May 13 - June 15, 2020). The results of the survey show respondents continued to use urban green spaces during the pandemic and consider them to be more important for mental and physical health than before the pandemic began. However, the study revealed a pattern of concerns residents have about green space accessibility and safety, and found key differences between the concerns and needs of different populations, suggesting a crucial role for inclusive decision-making, support for additional management strategies, and urban ecosystem governance that reflect the differential values, needs and concerns of communities across the City. As urban centers face looming budget cuts and reduced capacity, this study provides some empirical evidence to illustrate the value of urban green spaces as critical urban infrastructure, and may have implications for funding, policy, and management, of urban green spaces in NYC, with potential applications to other cities, particularly during times of crisis.

Lutein, a plant-derived xanthophyl-carotenoid, is an exceptional antioxidant and anti-inflammatory constituent found in food. Elevated concentrations of lutein found in human blood and plasma, due to high dietary intake, are beneficial against eye disease and improve cardiometabolic health. Lutein plays an important protective role against the development of neurological disorders, including Alzheimer’s disease (AD), multiple sclerosis (MS) and Parkinson’s disease (PD). It has also been shown to be beneficial for liver, kidney and respiratory health. Lutein, acting as a very strong antioxidant, can alleviate oxidative stress and downgrade reactive oxygen species (ROS). Oxidative stress is one of the key pathogenic mechanisms in post-COVID and mRNA vaccine injury syndromes. Recent in silico studies suggest that lutein and other naturally derived antioxidants, by docking at the site where the SARS-CoV-2 spike protein (SP) binds to the angiotensin enzyme type 2 (ACE2) receptor, may neutralize the SP-ACE2 interactions. Lutein can be added to a detoxification regimen to aid in clearing Spike protein and relieving symptoms. In agreement with Hippocrates’ dictum to “Let food be thy medicine,” this review establishes dietary lutein as a valuable therapy in the treatment of post-COVID syndrome, mRNA vaccine injury syndromes, and a wide range of other chronic illnesses.

In regions lacking genomic data, analysis of sequences from the early stages of an outbreak can provide important insights into the diversity of pathogens present. Following the detection of the first imported case of COVID-19 in the Northern sector of Ghana on 13^th March 2020, we have now molecularly characterized and phylogenetically analysed sequences including three (3) complete genomes of the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) isolated from nine (9) patients observed in Ghana. Eight (8) of these patients reported with a recent history of foreign travel and one (1) with no history of foreign travel. We performed high throughput sequencing for 9 samples following the determination of high concentration of viral RNA. In addition, we estimated the potential impact that long distance transportation of samples to testing centres may have on sequencing outcomes. Here, two samples that were closest in terms of viral RNA concentration but transported from sites which are over 400km apart were assessed. All sequences were compared to previous sequences from Ghana and representative sequences from regions where our patients had previously travelled. Complete genomes were obtained for three (3) sequences and with another near complete genome with a coverage of 95.6%. Sequences with coverage in excess of 80% were found to belong to three lineages namely A, B.1 and B.2. Our sequences clustered in two different clades with the majority falling within a clade composed of sequences from sub-Saharan Africa. Less RNA fragmentation was seen in sample KATH23 which was collected 9km compared with sample TTH6 which was collected and transported over a distance of 400km to the testing site. The clustering of several sequences from sub-Saharan Africa suggests regional circulation of the viruses in the subregion. Importantly, there may be the need to decentralize testing sites and build more capacity across Africa to boost the sequencing output of the subregion.

Fermenter is a vessel that maintains optimum environment for the development of significant microorganism used in large scale fermentation process and the commercial production of products like Alcoholic beverages, Enzymes, Antibiotics, Organic acids etc. The fermenter aims to produce biological product like vaccines and hormones, it is necessary to monitor and control the different parameters like external and internal mass transfer, heat transfer, fluid velocity, shear stress, agitation speed, aeration rate, cooling rate or heating intensity, and the feeding rate, nutrients, base or acid valve. Fermentation in the fermenter are accomplished in several configuration and these simple configurations are batch, fed-batch and continuous fermentation process. Fermentation process is carried out in small or large size fermenter depending on product quantity. The selection of the suitable process depends on the fermentation kinetics, type of microorganism used and process economic aspects. Improved modelling tools, reactor operation and reactor design in bioreactor is because of mass transfer behavior and it is important for reaction rate maximizing, throughput rates optimization and cost minimizing. The fermenter design, fermentation process, types of the fermenter that are used in industries and heat and mass transfer in fermenter is discussed.

Severe acute respiratory syndrome novel coronavirus 2 (SARS-CoV-2) has caused the global pandemic as COVID-19, which is the most notorious global public health crisis in the last 100 years. SARS-CoV-2 is composed of four structural proteins and several non-structured proteins. The multi-facet nucleocapsid (N) protein is the major component of structural proteins of CoVs, However, there are no dedicated genomic, sequences and structural analyses focusing on potential roles of N protein. Hence, there is an urgent requirement of a detailed study on N protein of SARS-CoV-2. Herein, we are presenting a comprehensive study on N protein from SARS-CoV-2. We have identified seven motifs conserved in the three major domains namely N-terminal domain, linker regions and the C-terminal domains. Out of seven motifs, six motifs are conserved across different members of coronaviridae, while motif4 is specific for SARS CoVs with potential amyloidogenic properties. Additionally, we report this protein has large patches of disordered regions flanking with these seven motifs. These motifs are hubs of epitopes with 67 experimentally verified epitopes from related viruses. We report the presence of three nuclear localization signals (NLS1-NLS3 mapped to 36-41, 256-26, and 363-389 residues, respectively) and two nuclear export signals (NES1-NLS2 from 151-161 and 217-230 residues, respectively) in the N protein of SARS-CoV-2. These deciphered two Q-patches as Q-patch1 and Q-patch2, mapped in the regions of 266-306, and 361-418 residues, which potentially help in the aggregation of the viral proteins along with ²¹⁹LALLLLDR²²⁶ patch. Additionally, we have identified 14 antiviral drugs potentially binding to seven motifs of N-proteins using docking-based drug discovery methods.

Space-time evolution is briefly explained by using the 3-dimensional quantized space model (TQSM) based on the 4-dimensional (4-D) Euclidean space. The energy (mass), charges and absolute time are newly defined based on the 4-D Euclidean space. The photons and gravitons are understood as the 2-D space fluctuations along the space axes and 1-D time fluctuations along the time axis, respectively. This indicates that the electromagnetic (EM) and gravitational (G) waves can be unified into the so called gravityelectromagnetic (GEM) wave which has both space and time fluctuations. The photon with zero force fields is the 2EM wave because an EM wave corresponds to a charged fermion. The dark matter bosons, weak force bosons, strong force bosons are the 1-D time fluctuations which can be expressed by the G waves. This indicates that all five forces are unified by the GEM wave. It is called as the super unification theory in the present work. And the force carrying bosons and mesons are, for the first time, proposed as the possible candidates of the magnetic monopoles like the fermions and baryons are the electric monopoles. The signs of the magnetic charges quantized as q_m=cq are newly defined. The big bang is understood by the space-time evolution of the 4-D Euclidean space but not by the sudden 4-D Minkowski space-time creation. The big bang process created the matter universe with the positive energy and the partner anti-matter universe with the negative energy from the CPT symmetry.

The discovery of a simple numerical formula for the projection of all the atomic mass of life-sustaining CONHSP bioatoms leads to the emergence of a set of Nested CODES unifying all the biological, genetic and genomic components by unifying them from bioatoms up to 'to whole genomes. In particular, we demonstrate the existence of a digital meta-code common to the three languages ​​of biology that are RNA, DNA and amino acid sequences. Through this meta-code, genomic and proteomic images appear almost analogous and correlated. The analysis of the textures of these images then reveals a binary code as well as an undulatory code whose analysis on the human genome makes it possible to predict the alternating bands constituting the cariotypes of the chromosomes. The application of these codes to perspectives in astrobiology, in Cancers basic research and the emergence of binary codes and regions of local stability (voting process), whose fractal nature we demonstrate, is illustrated.

Background: The COVID 19 pandemic and associated public health measures have disrupted the lives of people around the world. It is already evident that the direct and indirect psychological and social effects of the COVID 19 pandemic are insidious and affect the mental health of young children and adolescents now and will in the future. The aim and objectives of this knowledge-synthesis study were to identify the impact of the pandemic on children’s and adolescent’s mental health and to evaluate the effectiveness of different interventions employed during previous and the current pandemic to promote children’s and adolescent’s mental health. Methodology: We conducted the systematic review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and included experimental randomized, nonrandomized controlled trials; observational studies; and qualitative studies. Results: Of the 5,828 articles that we retrieved, 18 articles met the inclusion criteria. We thematically analyzed and put up the major findings under the thematic areas of impact of pandemic on children and adolescent’s mental health. These studies reported that pandemics cause stress, worry, helplessness, and social and risky behavioral problems among children and adolescents (e.g., substance abuse, suicide, relationship problems, academic issues, absenteeism from work). Interventions such as art-based programs, support services, and clinician-led mental health and psychosocial services effectively decrease mental health issues among children and adolescents. Conclusion: Children and adolescents are more likely to experience high rates of depression and anxiety during and after a pandemic. It is critical that future researchers explore effective mental health strategies that are tailored to the needs of children and adolescents. Explorations of effective channels regarding the development and delivery of evidence-based, age-appropriate services are vital to lessen the effects and improve long-term capacities for mental health services for children and adolescents.

Background: World Health Organization (WHO) declared that COVID-19 as a pandemic on March 11, 2020. There is sudden need of statistical modeling due to onset of COVID-19 pandemic across the world. But health planning and policy requirements the estimates of disease problem form clinical data. Objective: To predict recovery rate, cases load rate on the basis of cumulative confirmed Novel Corona virus (NCV) cases, recovered cases and deaths form COVID-19 in India. Methods: The reported COVID-19 cases in the country were obtained from website (https://datahub.io/core/covid-19#resource-covid-19_zip/). The cumulative NCV confirmed cases; recovery cases and deaths were used for estimating recovery rate, cases load rate and death rate till date 24 April 2020. Results: A total of 24530 NCV confirmed cases were reported nationwide in India on 24 April 2020. It is found that the recovery rate increased 22% and case load rate decreased 74%. Death rate is found to be very low 3%. The difference of cases load rate and recovery rate (delta) coincide at 50 % then NCV cases expected would be declined. Conclusion: The epidemic in the country was mainly caused by the importation of India. Lockdown as restricting the migration of population and decided to quarantine of population may greatly reduce the risk of continued spread of the epidemic in India. This study predicts that by 20 May 2020, the cases load rate lesser than recovery rate there after COVID-19 patients would be started to reducing.

To define and evaluate the areas of consideration concerning in identifying the critical factors that top universities in Nueva Ecija, Philippines can be used for triangulating the courses of actions that can be applied to improve the current practices of universities towards its combat to the COVID–19 disease is the primary objective of this study. The researchers used a descriptive design of methodology by using questionnaire–checklist to scientifically describe the situation, problems, phenomenon, or program, or provide information about certain issues related to the virus outbreak. The respondents of the study were faculty and staff of five established universities in Nueva Ecija, Philippines wherein the researchers employed a non–probability sampling technique to be logically assumed as the representative of the entire population. The results of the study shown that the top universities in Nueva Ecija have made efforts to ensure the safety of university workers by complying with the Inter–Agency Task Force (IATF) protocols. It can be inferred, in reality, that there are some areas that must be improved especially when it comes to ensuring the welfare of the personnel who are still reporting to work even in this time of the pandemic. The researchers suggested an enhancement plan that can be adapted by these universities to resolve the concerns of the faculty and staff especially in reducing the spread of the virus without sacrificing the day–to–day transactions of the academic institutions.

An outbreak of a pandemic COVID-19 disease caused by a novel coronavirus SARS-CoV-2 has posed a serious threat to human health and the economy of the whole world. Bangladesh is one of the most densely populated countries in the world, which has also come under the attack of this viral disease. This perspective report aimed to describe the responses of Bangladesh to tackle the COVID-19, particularly on how Bangladesh is dealing with this novel viral disease with limited resources. The first case of a COVID-19 patient was detected in Bangladesh on March 8, 2020. Since then, a total of 2,144 peoples are officially reported as COVID-19 infected with 84 deaths. To combat the COVID-19, the government has taken various steps to tackle the epidemic outbreak of it such as diagnosis of the suspected cases, quarantine of doubted people and isolation of infected patients, local or regional lockdown, grant general leave from all offices for staying home of people, increase public awareness and enforce social distancing and so on. In addition, to address the socio-economic situations, the government announced several financial stimulus packages of about USD 11.17 billion. However, very limited diagnostic facilities, health workers, resources such as hospital beds, personal protective equipment, intensive care unit, and ventilators in the hospitals along with limited public unawareness are the major challenges for Bangladesh to tackle the situation effectively. This report described the responses of Bangladesh to tackle the COVID-19 and discusses prevailing challenges to mitigate this highly contagious disease with limited resources.

In Wikipedia, articles about various topics can be created and edited independently in each language version. Therefore, quality of information about the same topic depends on language. Any interested user can improve an article and that improvement may depend on popularity of the article. The goal of this study is to show what topics are best represented in different language versions of Wikipedia using results of quality assessment for over 39 million articles in 55 languages. In this paper, we also analyze how popular are selected topics among readers and authors in various languages. We used two approaches to assign articles to various topics. First, we selected 27 main multilingual categories and analyzed all their connections with sub-categories based on information extracted from over 10 million categories in 55 language versions. To classify the articles to one of the 27 main categories we took into account over 400 million links from articles to over 10 million categories and over 26 million links between categories. In the second approach we used data from DBpedia and Wikidata. We also showed how the results of the study can be used to build local and global rankings of the Wikipedia content.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has resulted in the current COVID-19 pandemic. Worldwide this disease has infected around 1.5 million individuals with a mortality rate ranging from 5 to 10%. It has also imposed extreme challenges on global health, economy, and social behavior. Due to the unavailability of therapeutics, several efforts are going on in the drug discovery to control the SARS-CoV-2 viral infection. The main protease (M^Pro) plays a critical role in viral replication and maturation, thus can serve as the primary drug target. To understand the structural evolution of M^Pro, we have performed phylogenetic and SSN analysis, that depicted divergence of Coronaviridae M^Pro in five clusters specific to viral hosts. This clustering was also corroborated with the comparison of M^Pro structures. Furthermore, it has been observed that backbone and binding site conformations are conserved despite variation in some of the residues. This conservation can be exploited to repurpose available viral protease inhibitors against SARS-CoV-2 M^Pro. In agreement with this, we performed screening of the custom-made library of ~7100 molecules including active ingredients present in the Ayurvedic anti-tussive medicines, anti-viral phytochemicals and synthetic anti-virals against SARS-CoV-2 M^Pro as the primary target. We identified several natural molecules that strongly binds to SARS-CoV-2 M^Pro among which top seven molecules are d-Viniferin, Myricitrin, Taiwanhomoflavone A, Lactucopicrin 15-oxalate, Nympholide A, Biorobin and Phyllaemblicin B. Most of the predicted lead molecules are from Vitis vinifera, also reported for anti-tussive and/or antiviral activities. These molecules also showed strong binding with other main targets RdRp and hACE-2. We anticipate that our approach for identification of multi-target-directed ligand will provide new avenues for drug discovery against SARS-CoV-2 infection.

The process of senescence (aging) is largely determined by the action of wild-type genes. For most organisms, this does not reflect any adaptive function of senescence, but rather evolutionary effects of declining selection against genes with deleterious effects later in life. To understand aging requires an account of how evolutionary mechanisms give rise to pathogenic gene action and late-life disease, that integrates evolutionary (ultimate) and mechanistic (proximate) causes into a single explanation. A well-supported evolutionary explanation by G.C. Williams argues that senescence can evolve due to pleiotropic effects of alleles with antagonistic effects on fitness and late-life health (antagonistic pleiotropy, AP). What has remained unclear is how gene action gives rise to late-life disease pathophysiology. One ultimate-proximate account is T.B.L. Kirkwood’s disposable soma theory. Based on the hypothesis that stochastic molecular damage causes senescence, this reasons that aging is coupled to reproductive fitness due to preferential investment of resources into reproduction, rather than somatic maintenance. An alternative and more recent ultimate-proximate theory argues that aging is largely caused by programmatic, developmental-type mechanisms. Here ideas about AP and programmatic aging are reviewed, particularly those of M.V. Blagosklonny (the hyperfunction theory) and J.P. de Magalhães (the developmental theory), and their capacity to make sense of diverse experimental findings is described.

COVID-19 greatly challenges human beings in the health sector and leaves behind a large amount of medical waste that poses many potential threats to the environment. In this paper, we compiled relevant data released by official agencies and the media, and conducted data supplementation based on previous studies to calculate the net value of medical waste production in Hubei Province during COVID-19 with the help of a neural network model. Then, we reviewed the data related to the environmental impact of medical waste per unit and designed four scenarios to estimate the environmental impact of new medical waste generated during the epidemic. The results showed that at a medical waste generation rate of\ 0.\ 5\ kg/(\ bed\ \cdot\ d) COVID-19 resulted in a net increase in medical waste volume of about 3366.99 tons in Hubei Province. In the four scenario assumptions, if the medical waste brought by COVID-19 is completely incinerated, it will have a large impact on the air quality. If it is disposed by distillation sterilization, it will produce a large amount of wastewater and waste residue. Based on the results of the study, three policy recommendations are proposed in this paper: strict control of medical wastewater discharge, reduction and transformation of the emitted acidic gases, and attention to the emission of metallic nickel in exhaust gas and chloride in soil. These policy recommendations provide a scientific basis for controlling medical waste pollution.

In this paper, we discuss major issues of mathematics teaching and learning in Nepal. The issues coming from theories such as social and radical constructivism suggest that teachers are not trained to use such approach in teaching mathematics, and there is a lack of teaching aids and materials and technological tools. The issues related to social aspects are gender issues, language issues, social justice issues, and issues related to the achievement gap. The cultural issues are related to the diversity of language and ethnicity. The issues related to political aspects are equity and access, economic status, pedagogical choice, and professional organizations and unions. The issues related to technology include the technological skills, use of technology, and affordance. Finally, we suggest that all the stakeholders should pay attention to resolving these issues by improving the curriculum, training teachers, resourcing the classroom with locally made and new technological tools.

Along with the Coronavirus pandemic, another crisis has manifested itself in the form of mass fear and panic phenomena, fuelled by incomplete and often inaccurate information. There is therefore a tremendous need to address and better understand COVID-19's informational crisis and gauge public sentiment, so that appropriate messaging and policy decisions can be implemented. In this research article, we identify public sentiment associated with the pandemic using Coronavirus specific Tweets and R statistical software, along with its sentiment analysis packages. We demonstrate insights into the progress of fear-sentiment over time as COVID-19 approached peak levels in the United States, using descriptive textual analytics supported by necessary textual data visualizations. Furthermore, we provide a methodological overview of two essential machine learning classification methods, in the context of textual analytics, and compare their effectiveness in classifying Coronavirus Tweets of varying lengths. We observe a strong classification accuracy of 91% for short Tweets, with the Naive Bayes method. We also observe that the logistic regression classification method provides a reasonable accuracy of 74% with shorter Tweets, and both methods showed relatively weaker performance for longer Tweets. This research provides insights into Coronavirus fear sentiment progression, and outlines associated methods, implications, limitations and opportunities.

Nearly three months have passed since the emergence of the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), which caused the rapidly spreading Coronavirus Disease 2019 (COVID-19) pandemic. To date, there have been more than 550,000 confirmed cases and more than 25,000 deaths globally caused by COVID-19. Chinese health authorities, where the virus emerged, have taken prompt strict public health measures to control and prevent the spread of the outbreak. In the kingdom of Saudi Arabia, unprecedented precautionary strict measures were applied to slow virus entry and to mitigate the risk of the outbreak. Here, we review the experience learned during the Middle East Respiratory Syndrome Coronavirus (MERS-CoV) epidemic in Saudi Arabia, which has been in the country since 2012, and is expected to have helped the country to be well prepared for the current COVID-19 pandemic. We also discuss the country readiness, improvement in research and development, and the unprecedented rapid precautionary measures that have been taken by the Saudi government thus far.

The SARS-CoV-2 was confirmed to cause the regional outbreak of coronavirus disease 2019 (COVID-19) in Wuhan, China. The 3C-like protease (3CL^pro), an essential enzyme for viral replication, is a valid target to compacts SARS-CoV and MERS-CoV. In this research, an integrated library consisting of 1000 compounds from Asinex Focused Covalent (AFCL) library and 16 FDA-approved protease inhibitors were screened against SARS-CoV-2 3CL^pro. Top compounds with significant docking scores and making stable interactions with catalytic dyad residues were obtained. The screening results in identification of compound 621 from AFCL library as well as Paritaprevir and Simeprevir from FDA-approved protease inhibitors as potential inhibitors of SARS-CoV-2 3CL^pro. The mechanism and dynamic stability of binding between the identified compounds and SARS-CoV-2 3CL^pro were characterized using 50 nanoseconds (ns) molecular dynamic (MD) simulation approach. The identified compounds are potential inhibitors worthy of further development as SARS-CoV-2 3CLpro inhibitors/drugs. Importantly, the identified FDA-approved therapeutics could be ready for clinical trials to treat infected patients and help to curb the COVID-19.

Recent clinical SARS-CoV-2 studies link diabetes, cardiovascular disease, and hypertension to increased disease severity. In the US, racial and ethnic minorities and low socioeconomic status (SES) individuals are more likely to have increased rates of these comorbidities, lower baseline health, limited access to care, increased perceived discrimination, and limited resources, all of which increase their vulnerability to severe disease and poor health outcomes from SARS-CoV-2. Previous studies demonstrated the disproportionate impact of pandemic and seasonal influenza on these populations, due to these risk factors. This paper reviews increased health risks and documented health disparities of racial and ethnic minorities and low SES individuals in the US. Pandemic response must prioritize these marginalized communities to minimize the negative, disproportionate impacts of SARS-CoV-2 on them and manage spread throughout the entire population. This paper concludes with recommendations applicable to healthcare facilities and public officials at various government levels.

The global pandemic caused by the new SARS-COV-2 coronavirus makes it necessary to search for drugs for its control. Within of this research it has been known that the ivermectin drug, a FDA-approved drugs which is formulated as an 80:20 mixture of ivermectin B1a and B1b and used commonly for parasitic infections, has an inhibitory effect on viruses, includes SARS-COV-2 at in vitro level. In the particular case of SARS-COV-2 its mechanism of action remains elusive and controversial. Interestingly, the energy of interaction of ivermectin with any of the proteins the SARS-CoV-2 and the possible structural alterations at the protein level that this drug can cause have not been reported. In this sense, we carried out a bioinformatics study with docking strategies and molecular dynamics to predict the binding and disturbance induced by ivermectin in proteins associated with SARS-CoV-2. We use DockThor and Molegro docking scores. The DockThor server and myPresto software were used to build complexes and dynamics studies, respectively. The results obtained suggested that ivermectin is capable of docking with the 3CL protease and the HR2 domain, and may promote structural changes in these proteins by inducing unfolding/folding. Specifically, ivermectin brings protease to a significantly more deployed conformational state and the HR2 domain to a more compact state compared to the native state. Finally, it is shown that B1a and B1b macrocyclic lactones have a behavior different from to each target protein. These results suggest a possible inhibitory effect against SARS-CoV-2 due to a synergistic role of this drug to spontaneously bind to two important proteins involve in the proliferation of this virus. However, more studies are required on this possible mechanism of action.

Origins of the time, mass, electric charges and magnetic monopoles are explained. The energies, electric charges and magnetic charges of the particles are defined as E = cDtDV and |q| = cDt = E/DV, and |q_m| = c²Dt, respectively, for the 3-D quantized spaces warped along the time axis direction of ct in the 4-D Euclidean space. The energy (or mass) and charges (or electric charges and magnetic charges) are the vectors along the time axis of ct in the 4-D Euclidean space. This new concept is closely connected to the wave function of the quantum mechanics. The electric charges, magnetic charges and energies have the property of the space direction independence. Magnetic monopoles (charges) are the force carrying bosons with the inside electric field time loop. Electric monopoles are the elementary fermions. Photon space fluctuations are explained with the quantized magnetic charges.

In the paper, the authors consider the generating functions of the Hermite polynomials and their squares, present explicit formulas for higher order derivatives of the generating functions of the Hermite polynomials and their squares, which can be viewed as ordinary differential equations or derivative polynomials, find differential equations that the generating functions of the Hermite polynomials and their squares satisfy, and derive explicit formulas and recurrence relations for the Hermite polynomials and their squares.

Three-dimensional quantized space model is newly introduced. Quantum mechanics and relativity theory are explained in terms of the warped three-dimensional quantized spaces with the quantum time width (Dt=t_q). The energy is newly defined as the 4-dimensional space-time volume of E = cDtDV in the present work. It is shown that the wave function of the quantum mechanics is closely related to the warped quantized space shape with the space time-volume. The quantum entanglement and quantum wave function collapse are explained additionally. The special relativity theory is separated into the energy transition associated with the space-time shape transition of the matter and the momentum transition associated with the space-time location transition. Then, the quantum mechanics and the general relativity theory are about the 4-dimensional space-time volume and the 4-dimensional space-time distance, respectively.

Large population passages of the SARS-CoV-2 in the past two and a half years have allowed the circulating virus to accumulate an increasing number of mutations in its genome. The most recently emerging Omicron subvariants have the highest number of mutations in the Spike (S) protein gene and these mutations mainly occur in the receptor-binding domain (RBD) and the N-terminal domain (NTD) of the S gene. The eCDC and the WHO recommend partial Sanger sequencing of the SARS-CoV-2 S gene RBD and NTD on the PCR-positive samples in diagnostic laboratories as a practical means of determining the variants of concern to monitor a possible increased transmissibility, increased virulence, or reduced effectiveness of vaccines against them. The author’s diagnostic laboratory has implemented the eCDC/WHO recommendation by sequencing a 398-base segment of the N gene for the definitive detection of SARS-CoV-2 in clinical samples, and sequencing a 445-base segment of the RBD and a 490-509-base segment of the NTD for variant determination. This paper presents 5 selective cases to illustrate the challenges of using Sanger sequencing to diagnose Omicron subvariant when the samples harbor a high level of co-existing minor subvariant sequences with multi-allelic single nucleotide polymorphisms (SNPs) or possible recombinant Omicron subvariants containing a BA.1 NTD and a BA.2 RBD, which can only be detected by using specially designed PCR primers. The current large-scale surveillance programs using next-generation sequencing (NGS) do not face similar problems because NGS focuses on deriving consensus sequence.