Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) often causes severe viral pneumonia, especially among older individuals and those with underlying health conditions. The C57BL/6 mouse is widely used to develop mouse models of obesity, diabetes, hypertension, and immune disorders, conditions that are associated with increased risk of severe COVID-19. Although many studies using these mouse models have examined the pathogenicity of SARS-CoV-2, COVID-19 pathogenesis remains poorly understood. In vivo imaging analysis using two-photon excitation microscopy is useful for elucidating the pathology of COVID-19, providing pathological insights that are not available from conventional histological analysis. However, there is no reporter SARS-CoV-2 that demonstrates pathogenicity in C57BL/6 mice and emits sufficient light intensity for two-photon in vivo imaging. Here, we generated SARS-CoV-2 expressing the fluorescent protein Venus to facilitate in vivo pathological studies using C57BL/6 mouse models. We generated a mouse-adapted strain of SARS-CoV-2, by performing sequential lung-to-lung passages in BALB/c mice, followed by in C57BL/6 mice. We observed that the C57BL/6-adapted SARS-CoV-2 (named MASCV2-p25) replicated efficiently in the lungs of C57BL/6 mice, causing fatal pneumonia. Histopathologic analysis revealed severe inflammation and infiltration of immune cells in the lungs of MASCV2-p25-infected C57BL/6J mice, not unlike that observed in COVID-19 patients with severe pneumonia. Subsequently, we generated a mouse-adapted reporter SARS-CoV-2 (named MASCV-Venus-p9) by inserting the fluorescent gene Venus into MASCV2-p25, and sequential lung-to-lung passages in C57BL/6 mice. C57BL/6 mice infected with MASCV2-Venus-p9 exhibited severe pneumonia similar to that induced by MASCV2-p25. In addition, two-photon excitation microscopy of the lungs of the infected C57BL/6J mice showed that the infected cells emitted sufficient levels of fluorescence for easy observation. These findings suggest that MASCV2-Venus-p9 will be useful for two photon in vivo imaging studies of the pathogenesis of severe COVID-19 and for the development of therapeutic agents for severe pneumonia.

In post-COVID-19 syndrome, clinical presentation of the nerve fiber dysfunction plays an important role. The possibility of autoantigen cross-mimicry of coronavirus infection and the peripheral nervous system need to be investigated. The bioinformatic analysis was applied to search for possible common protein sequences located in the immunological epitopes. Among the autoantigens of the human nervous system, fibroblast growth factor receptor protein 3, myelin protein P0, myelin protein P2, sodium channel protein type 9, alpha protein subunit, plexin-D1 protein and ubiquitin-carboxyl-terminal hydrolase protein of the L1 isoenzyme were selected. The “Alignmentaj” program was created. The UniProt database, Protein Data Bank and AlphaFold databases were used. The analysis of protein sequence similarities of spike glycoproteins in human coronaviruses revealed common pentapeptides of the MERS-CoV-2 virus with the fibroblast growth factor receptor 3 and myelin protein P2. Among seasonal coronaviruses, common peptide sequences were identified in HCoV-HKU-1 virus with sodium channel protein type 9 subunit alpha and Plexin-D1, HCoV-OС43 with Plexin-D1, as well as HCoV-NL63 with Plexin-D1 and Ubiquitin carboxyl-terminal hydrolase isozyme L1. The data obtained make it possible to identify new potential targets for the development of autoimmune reactions that occur against the background of the activity of highly pathogenic and seasonal coronaviruses.

To ensure high-quality care, operationalize resilience and fill the knowledge gap regarding how to improve the prerequisites for resilient performance, it is necessary to understand how adaptive capacity unfolds in practice. Coronavirus 2019 stress-tested complex healthcare systems, and intensive care was driven to an unprecedented escalation. The main aim of this research was to explain the escalation process of intensive care from a microlevel perspective, including expressions of resilient performance, intervening conditions at the micro-meso-macrolevels and short- and long-term consequences. A secondary aim was to provide clinical recommendations regarding how to optimize the prerequisites for resilient performance in intensive care. A grounded theory methodology was used. First-person stories from different healthcare professionals (n70) in two Swedish regions were analyzed using the constant comparative method. A novel conceptual model of the escalation process of intensive care emerged, and 41 clinical recommendations concerning the optimal prerequisites for resilient performance were identified. Escalation was conceptualized as a transition from threatening chaos to temporary order through a complex process of adaptation. To prepare for the future, the components space, stuff, staff, system and science with associated continuity plans must be implemented, anchored and communicated to actors at all levels of the system.

This study examines the psychological repercussions of the COVID-19 pandemic on a medical team in an Israeli general hospital. The research explores the professional quality of life, burnout symptoms, secondary traumatic stress, and mindfulness among team members across three distinct phases of the pandemic. Analysis was conducted for different subgroups based on job roles and seniority, allowing for an evaluation of the phase-specific effects on the ProQOL (Professional Quality of Life) and mindfulness. Results align with established crisis trajectories, encompassing honeymoon/heroic phases, inventory, disillusionment, and recovery. The findings demonstrate a negative correlation between compassion satisfaction and burnout, as well as between mindfulness and burnout/secondary traumatic stress. Remarkably, male doctors exhibit a more pronounced negative impact on mindfulness compared to their female counterparts, primarily comprising healthcare workers. Temporal analysis reveals significant differences in compassion satisfaction and mindfulness, with baseline measurements being notably higher. Furthermore, the study sheds light on the vulnerability of male doctors, emphasizing the crucial role of hospital management in conveying the message and implementing effective measures to support professional quality of life. These findings underscore the necessity of prioritizing the well-being of medical professionals, particularly male doctors who face unique challenges in seeking assistance.

Not in the history of transmissible illnesses has there been an infection as strongly associated with acute cerebrovascular disease as the novel human coronavirus, SARS-CoV-2. While the risk of stroke has known associations with other viral infections, such as influenza and human immunodeficiency virus, the risk of ischemic and hemorrhagic stroke related to SARS-CoV-2 is unprecedented. Furthermore, the coronavirus disease 2019 (COVID-19) pandemic has so profoundly impacted psychosocial behaviors and modern medical care that we have witnessed shifts in epidemiology and have adapted our treatment practices to reduce transmission, address delayed diagnoses, and mitigate gaps in health care. In this narrative review, we summarize the history and impact of the COVID-19 pandemic on cerebrovascular disease, and lessons learned regarding the management of patients as we endure this period of human history.

Public Health Officers' (PHO) experiences in reaction to the COVID-19 pandemic can be based on whether the PHO is passive or active. Therefore, the study’s objectives are to identify the types of experiences and analyse the predictors of proactive practical experiences in solving COVID-19 among PHOs in the upper southern region of Thailand. Methods: An explanatory mixed-methods approach was used to collect data, through questionnaires and online in-depth interviews. The study was conducted from August 4, 2020, to August 3, 2021. Results: The results included 60 PHOs from 60 PCUs in 6 provinces, with 41 (68.3%) females and an average age of 35.57 years (SD = 11.61). The PHOs’ knowledge, understanding, and participation experience aspects were mostly proactive rather than passive. Factors that significantly predicted proactive practical experiences included sex (ORadj = 1.52, 95% CI = 1.04–2.21), age (ORadj = 1.69, 95% CI = 1.16-2.48), married status (ORadj = 1.69, 95% CI = 1.16-2.48), education level (ORadj = 1.50, 95% CI = 1.02–2.20), and position for work (ORadj = 1.69, 95% CI = 1.16-2.48). Conclusions: PHOs’ knowledge, understanding, opinion, and participation experiences were significant predictors of practical experience. Primary health care systems should promote proactive experiences in all four aspects to increase proactive practical experiences.

During the infection by SARS-CoV-2, the virus is changing infected host cell into its own factory producing new viral particles. As infection progresses, infected cell undergoes many changes in various pathways. One of the events caused by changes is cytokine storm, which leads to the severe symptoms. In this study, we investigated transcriptomic changes caused by COVID-19 disease using RNA-seq data obtained from COVID-19-positive patients and COVID-19-negative donors. RNA-seq data were collected for the purpose of identification of potential biomarkers associated with a different course of the disease. Here, the first datasets of 96 samples were analyzed to validate the methods. The aim of this publication is to report pilot results. In search of potential biomarkers associated with different disease severity, we performed differential expression analysis of human transcriptome, focusing on COVID-19 positivity and symptom severity. Since we detected plenty of potential biomarkers, we performed KEGG enrichment analysis to get better view of altered pathways. Results show, that affected were pathways related to immune processes and response to infection, also multiple signaling pathways, while most of them were also reported to be influenced by SARS-CoV-2 infection in previous studies.

During the COVID-19 pandemic, online media were the most widely used source of scientific information. Often, they are also the only ones on science-related topics. Research has shown that much of the information available on the Internet about the health crisis lacked scientific rigor and that misinformation about health issues can pose a threat to public health. In turn, millions of Catholics were found to be demonstrating against vaccination against COVID-19 based on "false" and misleading religious arguments. This research analyses publications about the vaccine in Catholic online media with the aim of understanding the presence of information (and misinformation) in this community. An algorithm designed for each media outlet collected COVID-19 vaccine-related publications from 109 Catholic media outlets in five languages. In total, 970 publications were analysed for journalistic genres, types of headlines and sources of information. The results show that most publications are informative and most of their headlines are neutral. However, opinion articles have mostly negative headlines. Also, a higher percentage of the opinion authors come from the religious sphere and most of the sources cited are religious. Finally, 35% of the publications relate the vaccine to the framing issue of abortion.

Building on the job demands-resources (JD-R) and the allostatic load (AL) models, in this study we investigated the role of smart working (SW) in the longitudinal association between workload/job autonomy (JA) and a possible biomarker of work-related stress (WRS) in the hair, namely the cortisol to dehydroepiandrosterone sulphate (DHEA(S)) ratio, during the COVID-19 pandemic. Overall, 124 workers completed a self-report questionnaire (i.e., psychological data) at Time 1 (T1) and collected a strand of hair (i.e., biological data) three months later (Time 2, T2). Results from moderated multiple regression analysis showed that smart working at T1 was negatively associated with hair cortisol/DHEA(S) ratio at T2. Additionally, the interaction between workload and SW was significant, with workload at T1 being positively associated with hair cortisol/DHEA(S) ratio at T2 among smart workers. Overall, this study indicates that SW can be conceived as a double-edged sword, with both positive and negative consequences on employee well-being. Furthermore, our findings suggest that hair cortisol/DHEA(S) ratio is a promising biomarker of WRS. Practical implications that organizations and practitioners can adopt to promote organizational well-being are discussed.

COVID-19 pandemic-related pressures on primary care may have driven inappropriate continuation of antibiotic prescriptions. Yet prescribing modality (repeat/non-repeat) has not previously been investigated in a pandemic context. Using the OpenSAFELY-TPP analytics platform, we analysed repeat/non-repeat prescribing frequency in monthly patient cohorts between Jan 2020–2022. In-depth analysis was conducted on Jan 2020 (“pre-pandemic”) and Jan 2021 (“pandemic”) cohorts. Per-patient prescribing and clinical conditions were determined by searching primary care record data using clinical code lists. Repeat prescribing was defined as >=3 prescriptions in a 6 month lookback period. Associations between demographics (e.g. age, sex, geography) and repeat/non-repeat prescribing were explored using unadjusted risk ratios. Antibiotic prescribing declined from May 2020; non-repeat prescribing declined more strongly than repeat prescribing (maximum declines -26% vs -11%, respectively). In the pandemic cohort, older patients were at higher risk of prescribing (especially repeat prescribing). The most common clinical conditions for repeat prescribing were COPD comorbidity and urinary tract infection. Comorbidities were more common among repeat vs non-repeat prescribed patients. In the pandemic cohort, vs pre-pandemic, repeat and non-repeat prescribing for comorbidities generally declined less compared with shorter-term conditions (infections, including COPD exacerbation/lower respiratory tract infection). Our findings inform ongoing development of stewardship interventions in England..

Childhood hygiene education has resulted in individuals engaging in hand washing and mask wearing to cope with COVID-19. Individuals can form sustainable development-related habits through childhood education.

This study evaluated the anti-inflammatory effects, protection of gut barrier integrity, and stimulation of phagocytosis in peripheral cells of a nutritional supplement based on a synergistic combination of yeast-based ingredients with a unique 1,3/1,6-glucan complex and a consortium of postbiotic Saccharomyces cerevisiae rich in selenium and zinc. The anti-inflammatory effect in Caco-2 cells in the presence and absence of a pro-inflammatory challenge (tumour necrosis factor alpha [TNF-α]/interferon gamma [IFN-ɣ]) showed statistically significant reductions of IFN-ɣ induced protein-10 (IP-10), and monocyte chemoattractant protein-1 (MCP-1) levels vs. controls (p < 0.001). Disruption of the gut integrity in the presence or absence of Escherichia coli (ETEC H10407) showed transepithelial electrical resistance (TEER) values higher in the ABB C1® group after 6 hours of testing. Spontaneous build-up of the gut epithelium monolayer over 22 days was also greater in the ABB C1® condition vs. a negative control. ABB C1® showed a significantly higher capacity to stimulate phagocytosis as compared with controls of algae β-1,3-glucan and yeast β-1,3/1,6 glucan (p < 0.001). This study supports the mechanism of action by which ABB C1® may improve the immune response and be useful to prevent infection and allergy in clinical practice.

The article describes how atherosclerosis and coronavirus disease 19 (COVID-19) may affect each other. The features of this comorbid pathogenesis at various levels (vascular, cellular and molecular) are considered. A bidirectional influence of these conditions is described: the presence of cardiovascular diseases affects different individual susceptibility to viral infection. In turn, SARS-CoV-2 can have a negative effect on the endothelium and cardiomyocytes, causing blood clotting, secretion of pro-inflammatory cytokines, and thus exacerbating the development of atherosclerosis. In addition to the established entry into cells via ACE2 принимая во внимание его влияние на, other mechanisms of SARS-CoV-2 entry are currently under investigation, for example, through CD147. Pathogenesis of comorbidity can be determined by the influence of the virus on various links which are meaningful for atherogenesis: generation of oxidized forms of LDL, launch of a cytokine storm, damage to the endothelial glycocalyx, and mitochondrial injury. The transformation of a stable plaque into an unstable one plays an important role in the pathogenesis of atherosclerosis complications and can be triggered by COVID-19. The impact of SARS-CoV-2 on large vessels such as aorta is more complex than previously thought considering its impact on vasa vasorum. Current information on the mutual influence of the medicines used in the treatment of atherosclerosis and acute COVID-19 is briefly summarized

RNA viruses exhibit a great tendency to mutate. Starting from 2019, the wild type that was labeled Hu-1 has during the last 3 years evolved to produce several dozen new variants, as a consequence of mutations. Mutations cause changes in empirical formulas of new virus strains, which lead to change in thermodynamic properties of biosynthesis and binding. These changes cause changes in the rate of reactions of binding of virus antigen to the host cell receptor and the rate of virus multiplication in the host cell. Changes in thermodynamic and kinetic parameters lead to changes in biological parameters of infectivity and pathogenicity. SARS-CoV-2 has starting from in 2019, until today, evolved towards increase in infectivity and maintaining constant pathogenicity, or for some variants a slight decrease in pathogenicity. In the case of Omicron BQ.1, BQ.1.1, XBB and XBB.1 variants pathogenicity is identical as in the Omicron BA.2.75 variant. On the other hand, infectivity of the Omicron BQ.1, BQ.1.1, XBB and XBB.1 variants is greater than those of previous variants. This will most likely result in the phenomenon of asymmetric coinfection, that is circulation of several variants in the population, some being dominant.

Biothermodynamics of viruses is among the youngest, but rapidly developing scientific disciplines. During the COVID-19 pandemic, it has closely followed the results published by molecular biologists. Empirical formulas were published for 50 viruses and thermodynamic properties for multiple viruses and virus variants, including all variants of concern of SARS-CoV-2, SARS-CoV, MERS-COV, Ebola virus, Vaccinia and Monkeypox virus. A review of development of biothermodynamics of viruses during the last several decades and intense development during the last 3 years has been described in this paper.

Burnout, a negative job-related psychological state particularly associated with the health professions, equates to a loss of valuable research in healthcare researchers. Team mindfulness, recognized to enhance personal fulfilment through work engagement, represents one important aspect found effective in reducing burnout. In a specific series of diverse membership academic meetings intended to reduce research burnout—employing writing prompts, doodling and continuous developmental feedback to do so—team mindfulness was demonstrated when conducted in person. Therefore, determining if team mindfulness is evident when holding such academic meetings online is relevant. When COVID-19 limitations required moving these academic meetings online, it was previously noted and reported that team mindfulness was affected in no longer being present during the first eighteen months of restrictions. To discover if this result persisted, question asking, doodles submitted and feedback responses were analyzed of the following year’s academic meetings for the same group, both quantitively and qualitatively. In finding the team mindfulness of these meetings additionally compromised the second full year, online practices actually found successful at creating and supporting team mindfulness—online games—are identified and considered. Concluding implications are noted and recommendations made regarding team mindfulness in reducing burnout for future online academic meetings.

In this empirical article, we argue that, while emergency remote teaching (ERT) may have achieved its goal of saving the academic years during the COVID-19 pandemic, it also constructed unintended pedagogical consequences that were possibly overlooked at the time of advocating it. The research question that the article attempted to answer is, what unintended pedagogical consequences did students and lecturers suffer because of the move to ERT at rural-based universities (RBUs) in South Africa? Drawing on students' and lecturers’ lived experiences of ERT, this article foregrounds unintended pedagogical consequences that arose at one RBU in South Africa during the transition from face-to-face teaching to ERT. Underpinned by the tenets of critical realism philosophy, as well as student integration theory, in-depth interviews with three lecturers and six students were conducted. The findings of the study indicate that home conditions, individual characteristics, pre-COVID-19 blended learning experiences, university training and support, and teaching, learning, and assessment practices and policies altogether contributed to the construction of unintended pedagogical consequences of ERT presented in this article. These consequences include (1) exclusion of low-income students in active teaching and learning, (2) equipping middle-class students with better chances of success than working-class students. (3) distressing female students and lecturers more than their male counterparts, and (4) unproductive assessment practices. This study may be beneficial to academics and policymakers from similar contexts in their plight to continue with remote teaching and assessment (RTA) beyond the pandemic.

Research has provided substantial evidence on the role of parents’ well-being in the quality of parent-child relationship and children’s adjustment. Parents’ stress and parental couple conflict have been linked to children’s adverse developmental outcomes. However, little is known about the factors that affect parent’s wellbeing when coping with multiple with stressors such as those brought by the recent COVID-19 global pandemic. Our study intended to examine the predictors of parental well-being looking at the contextual factors of COVID-19 home confinement, i.e. the use of digital media and parents’ domestic workload, and family resilience. Also, age and number of children were controlled as potential variables impacting parents’ well-being. A three-step hierarchical regression analysis was applied. The results showed that family resilience was a very strong predictor of parents’ well-being after controlling for any other variable. Parental couple’s conflict over the use of technology predicted lower levels of family well-being, while notably parent child-conflict and domestic workload were not associated with parents’ well-being. Additionally, age of children did play a role: the higher the mean age of children in the family the better the parents’ well-being. The findings are discussed in the light of their implications for research and practice.

SARS-CoV-2, is the cause of the COVID-19 pandemic which has claimed more than six million lives worldwide, devastating the economy and overwhelming healthcare systems globally. The development of new drug molecules and vaccines has played a critical role in managing the pandemic; however, new variants of concern still pose a significant threat as the current vaccines cannot prevent all infections. This situation calls for the collaboration of biomedical scientists and healthcare workers across the world. Repurposing approved drugs is an effective way of fast-tracking new treatments for recently emerged diseases. To this end, we have assembled and curated a database consisting of 7817 compounds from the Compounds Australia Open Drug collection. We developed a set of eight filters based on indicators of efficacy and safety that were applied sequentially to down-select drugs that showed promise for drug repurposing efforts against SARS-CoV-2. Considerable effort was made to evaluate approximately 14000 assay data points for SARS-CoV-2 FDA/TGA-approved drugs and provide an average activity score for 3539 compounds. The filtering process identified 12 FDA approved molecules with established safety profiles that have a plausible mechanism for treating COVID-19 disease. The methodology developed in our study provides a template for prioritising repurposable drug candidates that are safe, efficacious, and cost-effective for the treatment of COVID-19, long COVID, or any other future disease. We present our database in an easy-to-use interactive interface (CoviRx, https://www.covirx.org/) that was also developed to enable scientific community to access to the data of over 7000 potential drugs and to implement alternative prioritisation and down-selection strategies.

The recent COVID-19 pandemic has caused tremendous damage to social economy and people’s health. Some major issues fighting COVID-19 include early and accurate diagnosis and the shortage of ventilator machines for critical patients. In this work, we propose a closed-loop solution to deal with COVID-19: portable biosensing and wearable photoacoustic imaging for early and accurate diagnosis of infection and magnetically neuromodulation or minimally invasive electrical stimulation to replace the traditional ventilation. Proposed technique can guarantee ubiquitous and onsite detection, and electrical hypoglossal stimulator can be more effective in helping severe patients as well as reducing complications caused by ventilators.

This paper presents a computational approach designed to construct and query a literature-based knowledge graph for predicting novel drug therapeutics. The main objective is to offer a platform that discovers drug combinations from FDA-approved drugs and accelerates their investigations by domain scientists. Specifically, the paper introduced the following algorithms: (1) an algorithm for constructing the knowledge graph from drug, gene, and disease mentions in the biomedical literature; (2) an algorithm for vetting the knowledge graph from drug combinations that may pose a risk of drug interaction; (3) and two querying algorithms for searching the knowledge graph by a single drug or a combination of drugs. The resulting knowledge graph had 844 drugs, 306 gene/protein features, and 19 disease mentions. The original number of drug combinations generated was 2,001. We queried the knowledge graph to eliminate noise generated from chemicals that are not drugs. This step resulted in 614 drug combinations. When vetting the knowledge graph to eliminate the potentially risky drug combinations, it resulted in predicting 200 combinations. Our domain expert manually eliminated extra 54 combinations which left only 146 combination candidates. Our three-layered knowledge graph, empowered by our algorithms, offered a tool that predicted drug combination therapeutics for scientists who can further investigate from the viewpoint of drug targets and side effects.

The aim of this study was to investigate the spatio-temporal association between socio-economic deprivation and the incidence of COVID-19 and how this association changes through the seasons and due to the existence of restrictive public health measures. A retrospective observational study was conducted among COVID-19 cases that occurred in the Apulia region from 29 February 2020 to 31 December 2021, dividing the period into four phases with different levels of restrictions. A generalized estimating equations model was applied to test the independent effect of deprivation on the incidence rate of COVID-19, taking into account age, sex, and regional incidence rate as possible confounding effects and covariates such as season and levels of restrictions as possible modifying effects. The highest incidence rate was in areas with a Very High deprivation Index (DI) in winter (107.2 for 100,000 ab. ± 7.5), while in autumn, the highest Rate Ratio (RR) was estimated between Very High vs. Low DI (3.83, p<.001). During total lockdown, no RR between areas with different levels of DI was significant, while during soft lockdown, areas with Very High DI were more at risk than all other areas. The effects of social inequalities on incidence rate of COVID-19 change in as-sociation with the seasons and restrictions on public health. Disadvantaged areas showed a higher incidence rate of COVID-19 in the cold seasons and in the phases of soft lockdown.

Socioeconomic conditions and social attitudes are known to represent epidemiological determinants. Credible knowledge on socioeconomic driving factors of the COVID-19 epidemic is still incomplete. Based on a linear random effects regression, a predictive model is derived to estimate COVID-19 incidence in German rural districts from local socioeconomic factors and popularity of political parties in terms of their share of vote. Thereby, time series provided by Germany's public health institute (Robert Koch Institute) of weekly notified 7-day incidences per 100,000 inhabitants per district from the outset of the epidemic in 2020 up to December 1, 2021, have been used to construct the dependent variable. Local socioeconomic conditions including share of votes, retrieved from the Federal Statistical Office of Germany, have been used as potential risk factors. Popularity of the right-wing party Alternative for Germany (AfD) bears a considerable risk of increasing COVID-19 incidence both in terms of predicting the maximum incidences during three epidemic periods (alternatively, cumulative incidences over the periods are used to quantify the dependent variable) and in a time-continuous sense. Thus, districts with high AfD popularity rank on top in the time-average regarding COVID-19 incidence. The impact of the popularity of the Free Democrats (FDP) is markedly intermittent in the course of time showing two pronounced peaks in incidence but also occasional drops. A moderate risk emanates from popularities of the Green Party (GRÜNE) and the Christian Democratic Union (CDU/CSU) compared to the other parties with lowest risk level. Socioeconomic parameters like \emph{per capita} income, proportions of protection seekers and social benefit claimants, and educational level have negligible impact. To the contrary, incidence significantly increases with population density. In order to effectively combat the COVID-19 epidemic, public health policymakers are well advised to account for social attitudes and behavioural patterns reflected in local popularities of political parties, which are conceived as proper surrogates for these attitudes. Whilst causal relations between social attitudes and the presence of parties remain obscure, the political landscape in terms of share of votes constitutes at least viable predictive "markers" relevant for public health policy making.

COVID-19 affects many organs in our body, including the heart and lungs. COVID-19 cases that require hospitalization often exhibit pulmonary hypertension (PH) due to changes in the lung microvasculature in which the blood vessels become stiff, damaged, or narrow, causing increased pulmonary arterial pressure. This review examines the hypothesis that PH can lead to right ventricular hypertrophy (RVH) as a long-lasting aftereffect of COVID-19. Recent studies have shown that significant percentages of hospitalized patients develop right ventricular hypertension and right ventricular dilatation (RVD), which may lead to right ventricular failure and death. Despite recommendations for echocardiogram reports to include right ventricular wall thickness to assess RVH, few published reports have reported this parameter. Relevant studies on animal models of PH in which the timing of PH can be precisely controlled suggest that one to three weeks of PH can cause RVH. Thus, according to the hypothesis proposed here COVID-19 patients who have long-lasting severe disease (e.g., needed to be on a ventilator for one or more weeks) accompanied by PH and RVD may develop RVH as a long-lasting sequela outlasting the infection itself. Echocardiogram studies of recovered COVID-19 patients may determine whether oft-reported cardiovascular sequelae include RVH.

Abstract: Background: Our goal was to evaluate whether wearing personal protective equipment (PPE) such as an N95, or a surgical mask during the (COVID-19) pandemic had really reduced the cases of influenza in the state of Wisconsin. Methods: Respiratory Virus Surveillance Reports from the Wisconsin Department of Health Services (DHS) and the Centers for Disease Control and Prevention (CDC) were used to compare the rates of Influenza during the seasons of 2018-2019 and 2020-2021. Results: The number of cases, hospitalizations, and mortality rates with Influenza had significantly decreased in the 2020-2021 season compared to the Influenza season of 2018-2019. Discussion: Reducing the burden of influenza illnesses, hospitalizations, and deaths on the health care system is imperative. Wearing masks should be addressed for the most vulnerable.

The COVID-19 pandemic affects all parameters, especially health care professionals, drugs and medical supplies. The KERRA is a mixed medicinal plant capsule that is used for the treatment of patients with high fever with food and drug administration approved by FDA Thailand. Recently, KERRA showed quicker recovery for COVID-19 patients. Therefore, it is possible that some ingredients in KERRA could inhibit SARS-CoV-2. In this study, two important replication-related enzymes in SARS-CoV-2, a main protease and an RNA-dependent RNA polymerase (RdRp), were used to study the effect of KERRA. The results showed that KERRA inhibited the SARS-CoV-2 main protease and SARS-CoV-2 RdRp with IC50 values of 49.91 ± 1.75 ng/mL and 36.23 ± 5.23 µg/mL, respectively. KERRA displayed no cytotoxic activity on macrophage cells at concentrations lower than 1 mg/mL and exhibited anti-inflammatory activity. Additionally, KERRA was against a feline coronavirus (feline infectious peritonitis [FIP]) infection with an EC50 value of 134.3 g/mL. This study supports the potential use of KERRA as a candidate drug for COVID-19.

Malaysia implemented a movement control order (MCO) to curb the spread of the SARS-CoV-2 virus in March 2020. Despite healthcare services remaining operational, rising COVID-19 infections and MCO restrictions have forced healthcare professionals to seek a compromise between service capacity and standard operating procedure compliance. A cross-sectional survey was conducted among public and private sector doctors, dentists and pharmacists to determine how lockdown measures impacted healthcare services. Responses from 413 doctors, 193 dentists, and 163 pharmacists were analysed. Pharmacy services remained mostly unaffected throughout the MCO. In contrast, operational capacities for surgical and dental services were severely affected during the MCO. All service sectors reported restricting patients or accompanying individuals at the workplace, reductions in staffing capacity, and shortened patient contact time at various degrees. Many pharmacy and medical participants reported supplying extended medication supplies to patients. Adoption of virtual healthcare services was generally poor. All private service sectors suffered financial losses ranging between 59 to 75%. Periodic assessments of the healthcare system throughout the pandemic are required to identify which patients have their treatment compromised so that healthcare managers and policy makers can plan and implement appropriate interventions that help alleviate pressure within the health system.

Background and Objectives: In the current Covid-19 pandemic, children below the age of 12 could manifest Covid-19 symptoms and serve as a reservoir for the virus in the community. The present study was conducted to evaluate the reactogenicity, and immunogenicity of BBIBP-CorV, prior to involving this age group in the vaccination program in the kingdom of Bahrain. Subjects and Methods: The study included 582 children from 3 to 12 years old of Bahraini and non-Bahraini nationality, all of which contributed to the reactogenicity study. Of those, 401 contributed to the immunogenicity study. All children received 2 doses of BBIBP-CorV inactivated virus 3 weeks apart. To assess reactogenicity, children were followed up for 5 weeks to evaluate any vaccine-related adverse events (AE). To assess immunogenicity, blood was collected on day 0 and day 35 to assess antibody titer against S, N, and neutralizing antibody. Results: Of the 582 participants, (45.4%) were female, (54.61%) were male, with 49% in 9-12 age group. Of the 401 children contributing to the immunogenicity study, 274 (68.3%) had no prior exposure to Covid-19. The overall incidence of AE was 27.7%. No significant difference was found among different age groups. The most frequent AE was local (at the injection site) and occurred in 16% of children, followed by fever in 9.3%. No serious adverse events were reported. The Seroconversion rate was 100% among children with no prior exposure to Covid-19. Children with previous Covid-19 exposure had higher averages of anti-S (2379 U/ml compared to 409.1), anti-N (177.6 U/ml compared to 30.9) and neutralizing antibody (93.7 U/ml compared to 77.1) than children with no prior exposure at day 35. Conclusions: Two doses of COVID-19 BBIBP-CorV on the subjects aged between 3 to 12 has good safety and tolerance and can induce an effective immune response and neutralizing antibody titer.

The recent covid crisis has proven important lessons for academia and industry regarding digital reorganization. Among fascinating lessons from these times is the huge potential of data analytics and artificial intelligence. The crisis exponentially accelerated the adoption of analytics and artificial intelligence, and this momentum is predicted to continue into the 2020s and over. Moreover, drug development is a costly and time-consuming business, and only a minority of approved drugs return the revenue that exceeds the research and development costs. As a result, there is a huge drive to make drug discovery cheaper and faster. With modern algorithms and hardware, it is not too surprising that the new technologies of artificial intelligence and other computational simulation tools can help drug developers. In only two years of covid research, many novel molecules have been designed/identified using artificial intelligence methods with astonishing results in terms of time and effectiveness. This paper will review the most significant research on artificial intelligence in the de novo drug design for COVID-19 pharmaceutical research.

The interactions between work and personal life are important for ensuring well-being especially during COVID-19 where the lines between work and home are blurred. Work-life interference/imbalance can result in work-related burnout, which has been shown to have negative effects on faculty members’ physical and psychological health. Although our understanding of burnout has advanced considerably in recent years, little is known about the effects of burnout on nursing faculty turnover intentions and career satisfaction. Thus, this study aimed to test a hypothesized model examining the effects of work-life inference on nursing faculty burnout (emotional exhaustion and cynicism), turnover intentions and ultimately, career satisfaction. A predictive cross-sectional design was used. An online national survey of nursing faculty members was administered throughout Canada in Summer 2021. Nursing faculty who held full-time or part-time positions in Canadian academic settings were invited via email to participate in the study. Data was collected from an anonymous survey housed on Qualtrics. Descriptive statistics and reliability estimates were computed. The hypothesized model was tested using structural equation modeling. Data suggest that work-life interference significantly increase burnout which contribute to both higher turnover intentions and lower career satisfaction. Turnover intentions in turn was negatively associated with career satisfaction. The findings add to the growing body of literature linking burnout to turnover and dissatisfaction, highlighting key antecedents and/or drivers of burnout among nurse academics. These results provide suggestions for suitable areas for the development of interventions and policies within the organizational structure to reduce the risk of burnout during and post-COVID-19 and improve faculty retention.

The confinement experienced due to the COVID-19 pandemic has prompted a rethink of the teaching-learning process to which teachers have responded without planning and instead using their resources. This study aims to analyze the relationships between work-family interactions, technostress, and perceived organizational support in teachers during the confinement period in Spain that began in March 2020. An online survey was administered to 640 pre-school, primary, and secondary school teachers. Positive reciprocal work-family interactions and their relationship with organizational support were found, with differences according to gender, with women showing a more negative perception of the impact on the family. There were no marked levels of technostress in the overall sample, although higher levels of perceived ineffectiveness and skepticism were found in teachers aged 46 years or older. Teachers in private and subsidized schools showed a higher level of perceived support than those in public schools. There is a need to continue this work to verify the values of these dimensions in other contexts and to apply institutional measures and public policies to improve these indicators in this group.

The emergence of the COVID-19 pandemic has propelled the use of alcohol-based hand sanitizers to the fore as a SARS-CoV-2 control measure. To be effective these products must comply with relevant quality parameters such as alcohol concentration, methanol limits and purity. The current study was designed to determine the quality of alcohol-based hand sanitizer products in the Nairobi metropolitan area. For this purpose, 74 commercially marketed samples were collected and subjected to analysis by gas chromatography. Only three samples (4.1%) complied with the regulatory specifications for alcohol content, methanol limits and pH. Five samples (6.8%) complied with the specification for alcohol content but did not meet methanol or pH limits. A total of 44 (59.5%) samples had methanol levels that exceeded threshold limits. Eleven samples (14.9%) were found with methanol substitution (i.e., methanol, instead of ethanol or isopropanol, was the main alcohol component). The results show that users of alcohol-based hand sanitizers are being exposed to substandard and falsified products which in addition to being non-efficacious pose harm due to unacceptable levels of toxic impurities. Regular, routine post-market surveillance is needed to prevent such products from reaching the market.

The present paper proposes a fractal analysis of the Covid-19 dynamics in 45 European countries. We introduce a new idea of using the box-counting dimension of the epidemiologic curves as a means of classifying the Covid-19 pandemic in the countries taken into consideration. The classification can be a useful tool in deciding upon the quality and accuracy of the data available. We also investigated the reproduction rate, which proves to have significant fractal features, thus enabling another perspective on this epidemic characteristic. Moreover, we studied the correlation between two meteorological parameters: global radiation and daily mean temperature and two Covid-19 indicators: daily new cases and reproduction rate. The fractal dimension differences between the analysed time series graphs could represent a preliminary analysis criterion, increasing research efficiency. Daily global radiation was found to be stronger linked with Covid-19 new cases than air temperature (with a greater correlation coefficient -0.386, as compared with -0.318), and consequently it is recommended as the first-choice meteorological variable for prediction models.

Though there have been works highlighting the advantages and disadvantages of online learning, no study focused on university-level economics students. None of the studies explored students' opinions about improving the quality and effectiveness of online classes. Many used questionable samples, closed-ended questions, and all those researches were carried out at the beginning of online classes. In this paper, we overcome these limitations of earlier studies. Using a convenience sampling technique and open-ended questions, we collect data from 154 university-level economics students after being exposed to the online class for a year. Some advantages of online classes are: students can do classes from home without being exposed to health risks, easily accessible, flexible class schedule, students remained connected with the study, it saves costs, reduce the likelihood of semester loss, easy to understand, less stressful, and learning new technologies. Major problems from students' perspectives include network problems, difficulties in understanding the topic, unsuitable for mathematical courses, concentration problem, class not interactive, financial constraint, adverse health impacts, device issues, power outages, unfamiliarity with digital technology, internet problem, and unfixed class-schedule. Disadvantages outnumbered advantages. Students made several suggestions to improve the quality and effectiveness of online classes. Some of the vital suggestions are: using state-of-the-art digital tools, recording and uploading lectures, resolving internet issues, holding classes regularly, higher efforts to make the topics easier, resolving network issues, lowering class duration, institutional support, implementing a fixed class schedule, and introducing online evaluation system.

A distinctive feature of the SARS-CoV-2 spike protein is its ability to efficiently fuse cells, thus producing syncytia found in COVID-19 patients. This commentary proposes how this ability enables spike to cause COVID-19 complications as well as side effects of COVID-19 vaccines, and suggests how these effects can be prevented..

This study aimed to assess the differences in the importance and performance of health awareness in Korean middle school students according to the types of online physical education classes they attended during the coronavirus disease-2019 pandemic. Overall, 583 participants were selected using a convenience sampling method; the data were obtained through an online survey using Google forms. Frequency analysis, reliability analysis, independent sample t-test, and importance-performance analysis were performed. First, the differences between importance and performance were found to be the most for sleep and physical activity management, and the least for disease and hygiene management. In addition, both the groups demonstrated higher importance and performance for hygiene and disease management. There were significant differences in the importance and performance of all the sub-factors. Second, hygiene, disease management, and mental health management were found in quadrant I in both the groups, while physical activity, sleep, and dietary habit management were in quadrant III. No factors were in quadrant II and IV.

Advancements in deep learning and availability of medical imaging data have led to use of CNN based architectures in disease diagnostic assisted systems. In spite of the abundant use of reverse transcription-polymerase chain reaction (RT-PCR) based tests in COVID-19 diagnosis, CT images offer an applicable supplement with its high sensitivity rates. Here, we study classification of COVID-19 pneumonia (CP) and non-COVID-19 pneumonia (NCP) in chest CT scans using efficient deep learning methods to be readily implemented by any hospital. We report our deep network framework design that encompasses Convolutional Neural Networks (CNNs) and bidirectional Long Short Term Memory (biLSTM) architectures. Our study achieved high specificity (CP: 98.3%, NCP: 96.2% Healthy: 89.3%) and high sensitivity (CP: 84.0%, NCP: 93.9% Healthy: 94.9%) in classifying COVID-19 pneumonia, non-COVID-19 pneumonia and healthy patients. Next, we provide visual explanations for the CNN predictions with gradient-weighted class activation mapping (Grad-CAM). The results provided a model explainability by showing that Ground Glass Opacities (GGO), indicators of COVID-19 pneumonia disease, were captured by our CNN network. Finally, we have implemented our approach in three hospitals proving its compatibility and efficiency.

The availability of simple SARS-CoV-2 detection methods is crucial to contain the COVID-19 pandemic. This study examined whether a commercial LAMP assay can reliably detect SARS-CoV-2 genomes directly in respiratory samples without having to extract nucleic acids (NA) beforehand. Nasopharyngeal swabs (NPS, n = 220) were tested by real-time reverse transcription (RT)-PCR and with the LAMP assay. For RT-PCR, NA were investigated. For LAMP, NA from 26 NPS in viral transport medium (VTM) were tested. The other 194 NPS were analyzed directly without prior NA extraction [140 samples in VTM; 54 dry swab samples stirred in phosphate buffered saline]. Ten NPS were tested directly by LAMP using a sous-vide cooking unit. The isothermal assay demonstrated excellent specificity (100%) but moderate sensitivity (68.8%), with a positive predictive value of 1 and a negative predictive value of 0.65 for direct testing of NPS in VTM. The use of dry swabs, even without NA extraction, improved the analytical sensitivity; up to 6% of samples showed signs of inhibition. The LAMP could be performed successfully with a sous-vide cooking unit. This technique is very fast, requires little laboratory resources and can replace rapid antigen tests or verify reactive rapid tests on site.

Social media has become the most influential battleground for political and societal debate. The reach, the speed, and the fact that everybody can participate make this medium very popular but also highly manipulative, subject to biases and extremely precious to control. Misinformation spreads in an unforeseeable way. Sometimes it just follows usual non-malicious social interaction patterns, but often a targeted and designed-for-purpose manner. In this paper, we propose a novel method to identify the most effective opportunities to moderate the social media debate at a large scale using the properties of social signed graphs, such as structural balance. After building the topic universe for a particular political debate in a given time frame, we extract the most active and influential users and mine their position regarding the topic based on their interactions with other users. The result is a signed graph where each edge represents either support or challenge between a pair of users in the context of the topic. This graph can be modelled as an Ising model, with the goal of minimizing its energy state by using the advantages of Adiabatic Quantum Computing. Applying this principle, we use a Quantum Annealing implementation to solve the problem of finding the edges violating the structural balance of this graph, which in classic computing is known to be an NP-hard problem. We then provide a non-intrusive moderation technique for those violations to mitigate or increase the structural imbalance, depending on the desired strategy. The methodology is shown in the context of the COVID-19 skeptics’ debate in Twitter and implemented using a D-Wave 2000Q-6 quantum annealer.

Let us all take a moment to talk, once again, about this new coronavirus pandemic that the world has been facing since November 2019 and about its global response. After a short period marked by the pandemic underestimation risk by most governments, the Western world went nuts and overreacted, most probably so as not to be accused of inaction. In many cases, the overall benefits of the chosen policies were not sufficiently questioned, which resulted in many side effects on global health .The medical motto “primum non nocere”, a moral principle everyone should at least consider following, was evidently not taken into account. It has been overlooked, and the virus has become an obsession, to the extent that nearly everything else, even the most valuable things in life, is still now under appreciated if not simply ignored. This review highlighted facts against this simplistic, one-dimensional view.

Mental health and emotional responses to the effects of COVID-19 lockdown in sub-Saharan Africa (SSA) are of serious public health concern and may negatively affect the mental health status of people. Hence, this study assessed the prevalence of mental health symptoms as well as emotional reactions among sub-Saharan Africans (SSAs) and associated factors among SSAs during the COVID-19 lockdown period. This was a web-based cross-sectional, a study on mental health and emotional features from 2005 respondents in seven SSA countries. This study was conducted between April 27 and May 17, 2020 corresponding to the lockdown period in most SSA countries. Respondents aged 18 years and above and the self-reported symptoms were feeling anxious, being worried, angry, bored and frustrated. These were the main outcomes and were treated as dichotomous variables. Univariate and multivariate logistic regression analyses were used to identify the factors associated with these symptoms. We found that over half (52.2%) of the participants reported any of the mental health symptoms in SSA and the prevalence of feeling bored was 70.5% followed by feeling anxious (59.1%), being worried (57.5%), frustrated (51.5%) and angry (22.3%) during the COVID-19 pandemic. Multivariate analysis revealed that males, those aged >28 years, Central and Southern Africans, those who were not married, the unemployed, those living with more than six persons in a household, had higher odds of mental health and emotional symptoms. Similarly, people who perceived low risk of contracting the infection, and those who thought the pandemic would not continue after the lockdown had higher odds of mental health and emotional symptoms. Health care workers had lower odds for feeling angry than non-healthcare workers. During COVID-19 lockdown periods in SSA, about one in two participants reported mental health and emotional symptoms. Public health measures can be effectively used to identify target groups for prevention and treatment of mental health and emotional symptoms. Such interventions should be an integral component of SSA governments’ response and recovery strategies of any future pandemic.

This research is aimed at determining the characteristics of the current level of entrepreneurial potential of the Three Seas Initiative (3SI) countries, the ability to overcome the consequences of extraordinary events, such as COVID-19 and prospects for the return to an accelerated development once the destabiliser of the economic system, the coronavirus pandemic, has ceased. Eurostat, World Bank and the World Economic Forum data for 2015-2019 were used for the purpose of the research. The research was divided into three stages, i.e. assessment of economic development on the basis of a synthetic ratio of economic anchor development, for which a relative benchmark method based on spatial median (so-called L1 median or Weber point) was used, identification of conditions for the development of entrepreneurial capacity and statistical analysis showing the correlation between economic anchor measures and selected factors of the 3SI countries economic development. Our study found that the entrepreneurial capacity of the 3SI countries in 2015-2019 was determined by nine characteristics, belonging to six areas, i.e. local economy, demographic situation, social situation, trade exchange, innovation and tourism economy. The entrepreneurial potential of the 3SI countries was spatially diversified, and its development was determined, among others, by the entrepreneurial activity of residents (entrepreneurship index) and the conditions for running a business.

Epithelial characteristics underlying the differential susceptibility of chronic asthma to SARS-CoV-2 (COVID-19) and other viral infections are currently unclear. By revisiting transcriptomic data from patients with Th2 low versus Th2 high asthma, as well as mild, moderate and severe asthmatics, we characterized the changes in expression of human coronavirus and influenza viral entry genes relative to sex, airway location and disease endotype. We found sexual dimorphism in expression of COVID-19 genes ACE2, TMPRSS2, TMPRSS4, and SLC6A19. ACE2 receptor downregulation occurred specifically in females in Th2 high asthma, while proteases broadly assisting coronavirus and influenza viral entry, TMPRSS2 and TMPRSS4, were highly upregulated in both sexes. Overall, changes in COVID-19 gene expression were specific to Th2 high molecular endotype of asthma, and different by asthma severity and airway location. The downregulation of ACE2 (COVID-19, SARS) and ANPEP (HCoV-229E) viral receptors correlated with loss of club and ciliated cells in Th2 high asthma, while the increase in DPP4 (MERS-CoV), ST3GAL4, and ST6GAL1 (influenza) associated with an increase in goblet and basal activated cells. Overall, this study elucidates sex, airway location, disease endotype and changes in epithelial heterogeneity as factors underlying asthmatic susceptibility, or lack thereof, to COVID-19.

Objectives: There are limited data regarding the efficacy of methylprednisolone in patients with acute respiratory distress syndrome (ARDS) due to coronavirus disease 2019 (COVID-19) requiring invasive mechanical ventilation. We aimed to determine whether methylprednisolone increases the number of ventilator-free days (VFDs) among these patients. Design: Retrospective single-center study Setting: Intensive care unit Patients: All patients with ARDS due to confirmed SARS-CoV-2 infection and requiring invasive mechanical ventilation between 1 March and 29 May 2020 were included Interventions: None Measurements and Main Results: The primary outcome was ventilator-free days (VFDs) during the first 28 days, defined as being alive and free from mechanical ventilation. The primary outcome was analyzed with competing-risks regression based on Fine and Gray’s proportional subhazards model. Death before day 28 was considered to be the competing event. A total of 77 patients met the inclusion criteria. Thirty-two patients (41.6%) received methylprednisolone. The median dose was 1 mg.kg-1 (IQR: 1-1.3 mg.kg-1) and median duration of 5 days (IQR:5-7 days). Patients who received methylprednisolone had a mean 18.8 VFDs (95% CI, 16.6-20.9) during the first 28 days vs. 14.2 VFDs (95% CI, 12.6-16.7) in patients who did not receive methylprednisolone (difference, 4.61; 95% CI, 1.10-8.12; P = 0.001). In the multivariable competing-risks regression analysis and after adjusting for potential confounders (ventilator settings, prone position, organ failure support, severity of the disease, tocilizumab, and inflammatory markers), methylprednisolone was independently associated with a higher number of VFDs (subhazards ratio: 0.10, 95%CI: 0.02-0.45; p=0.003). Hospital mortality did not differ between the two groups (31.2% vs. 28.9%, p=0.82). Hospital length of stay was significantly shorter in the methylprednisolone group (24 days [IQR:15-41 days] vs. 37 days [IQR:23-52 days], p=0.046). The incidence of positive blood cultures was higher in patients who received methylprednisolone (37.5% vs. 17.8%, p=0.052). However, 91% of patients who received methylprednisolone also received tocilizumab. The number of days with hyperglycemia was similar in the two groups. Conclusions: Methylprednisolone was independently associated with increased VFDs and shortened hospital length of stay. The combination of methylprednisolone and tocilizumab was associated with a higher rate of positive blood cultures. Further trials are needed to evaluate the benefits and safety of methylprednisolone in moderate or severe COVID-19 ARDS.

The COVID-19 pandemic has raised questions about the possible cross immunity resulting from common vaccination programs and SARS-CoV-2 infection. Therefore, the Spanish Obstetric Emergency group performed a multicenter prospective study on the vaccination status of Influenza and Tdap (diphtheria, tetanus and pertussis vaccine boost administered in adulthood) in consecutive cases of SARS-CoV-2 infection in a pregnancy cohort, in order to assess its possible association with the clinical presentation and severity of symptoms of SARS-CoV-2 infection, as well as to determine the factors that may affect vaccination adherence. 1,150 SARS-CoV-2 positive pregnant women from 78 Spanish hospitals were analyzed: 183 had not received either vaccine, 23 had been vaccinated for Influenza only, 529 for Tdap only and 415 received both vaccines. No association was observed between the vaccination status and the clinical presentation of SARS-CoV-2 infection and/or the severity of symptoms. However, a lower adherence to the administration of both vaccines was observed in the Latin-American subgroup. Based on the results above, we reinforce the importance of maternal vaccination programs in the actual pandemic. Health education campaigns should be specially targeted to groups less likely to participate in these programs, as well as for a future SARS-CoV-2 vaccination campaign.

A mechanical ventilation system is a big support for breathing complications, in which an external solution is quite necessary to keep oxygen compensation in the patients. Its knowledge is well widespread and different equipment has been developed. However, they are very expensive and their quantity in medical centers is not sufficient, especially in Peru. Hence, it has been required to develop new methods to provide oxygen by a low cost equipment; Protofy, a research group from Spain, designed one of the first low cost mechanical ventilation systems which was medically validated by its government. In this sense, a redesign of the mechanical ventilation system was carried out according to the local requirements and available technology, a different airbag resuscitator with different properties and geometry, but maintaining its working concept based on a cam compression mechanism. Sensors and a display were added to improve the performance with a control algorithm for the rotation frequency and to show the ventilation curves over time to the medical staff. It was necessary to develop a mathematical model to relate the behavior between ventilation curves for a patient and physical variables of the design, especially in the epidemic COVID 19, that many countries are dealing with at the time research is being conducted. The mechanical ventilation system was redesigned, fabricated, and tested measuring its ventilation curves over time. Results indicate that this redesign provides a sturdy equipment able to work during a longer lifetime than the original. The replicability of the ventilation curves behavior is assured, while the mechanism dimensions are adapted for a particular airbag resuscitator. The mathematical model of the whole system can predict satisfactorily the ventilation curves over time and was used to provide the air pressure, volume, and flow as a function of the rotation angle measured by sensors.

To better understand the genes with altered expression caused by infection with the novel coronavirus strain SARS-CoV-2 causing COVID-19 infectious disease, a tensor decomposition (TD)-based unsupervised feature extraction (FE) approach was applied to a gene expression profile dataset of the mouse liver and spleen with experimental infection of mouse hepatitis virus, which is regarded as a suitable model of human coronavirus infection. TD-based unsupervised FE selected 134 altered genes, which were enriched in protein-protein interactions with orf1ab, polyprotein, and 3C-like protease that are well known to play critical roles in coronavirus infection, suggesting that these 134 genes can represent the coronavirus infectious process. We then selected compounds targeting the expression of the 134 selected genes based on a public domain database. The identified drug compounds were mainly related to known antiviral drugs, several of which were also included in those previously screened with an in silico method to identify candidate drugs for treating COVID-19.

We aimed to explore student and staff perceptions and experiences of a pilot COVID-19 asymptomatic testing service (P-ATS) in a UK university campus setting. This was a mixed-method study comprised of an online survey, and thematic analysis of qualitative data from interviews and focus groups conducted at the end of the 12-week P-ATS programme. Ninety-nine students (84.8% female, 70% first year; 93.9% P-ATS participants) completed an online survey, 41 individuals attended interviews or focus groups, including 31 students (21 first year; 10 final year) and 10 staff. All types of testing and logistics were highly acceptable (virus: swab, saliva; antibody: finger prick) and 94.9% would participate again. Reported adherence to weekly virus testing was high (92.4% completed ≥6 tests; 70.8% submitted all 10 swabs; 89.2% completed ≥1 saliva sample) and 76.9% submitted ≥3 blood samples. Students tested to ‘keep campus safe’, ‘contribute to national efforts to control COVID-19’, and ‘protect others’. 31.3% had high anxiety as measured by the Generalized Anxiety Disorder scale (GAD-7) (27.1% of first year). Students with lower levels of anxiety and greater satisfaction with university communications around P-ATS were more likely to adhere to virus and antibody tests. Increased adherence to testing was associated with higher perceived risk of COVID-19 to self (virus) and others (antibody). Qualitative findings revealed 5 themes and 13 sub-themes: ‘emotional responses to COVID-19’, ‘university life during COVID-19’, ‘influences on testing participation’, ‘testing physical and logistical factors’ and ‘testing effects on mental wellbeing’. Asymptomatic COVID-19 testing (virus/antibodies) is highly acceptable to students and staff in a university campus setting. Clear communications and support for mental wellbeing is likely to be important for testing uptake and adherence. Strategies are needed to facilitate social connections and mitigate the mental health impacts of COVID-19 and self-isolation.

Severe Acute Respiratory Syndrome Coronavirus 2(SARS-CoV-2) is the virus that caused COVID-19 around the world. The disease starts off as a flu-like symptom and then eventually spreads in the human body.Infections are easily transmitted from human to human which makes it more severe among individuals. SARS-CoV-2 virus is in the same family of viruses SARS and MERS.As of today, there is no approved vaccine that can cure COVID-19. However, potential treatments showing promising improvement results among affected COVID-19 patients. In this review, the effectiveness of the current treatments for COVID-19 has been explored.

Background: The ongoing COVID-19 pandemic and subsequent lockdown have adversely affected global health care services to varying extent. Emergency Services were also affected along with elective surgeries, which were deferred to accommodate the added burden of COVID 19 affected patients, on the healthcare systems. We aimed to assess the change in delivery of essential and emergency surgeries due to the pandemic. Methodology: A research consortium led by WHO Collaboration Centre (WHOCC) for Research in Surgical Care Delivery in Low- and Middle-Income countries (LMIC), India, conducted this retrospective cross-sectional study with 12 recruited centers. All surgeries performed during the months of April 2020 were compared with those performed in April 2019. These surgeries were stratified into emergency and elective, and further categorized based on NHS surgery prioritization documents. Results: A total of 4396 surgeries were performed at these centers in April 2019 and 1216 surgeries were performed in same month during 2020, yielding a fall of 72.3% (1216 /4396).We found a 54% reduction in emergency surgeries and a 91% reduction in the elective surgeries. Number of cesarean sections reduced by 29.7% and fracture surgeries declined by 85.3% Laparotomies and surgeries for local soft tissue infections with necrotic tissue reduced by 71.7% and 69.5% respectively. Conclusion: Our study quantifies the effects of COVID 19 pandemic on surgical care delivery in India and documents that the overall surgical volume reduced by three fourths in the pandemic period. Emergency surgeries reduced to half when compared with pre-pandemic period. Cesarean section surgeries were affected the least by pandemic, whereas the fracture surgeries and laparotomies were affected the most.

late in December 2019 2019-nCoV was identified as the pathogen responsible for an outbreak of severe respiratory distress in Wuhan, China. The virus was detected in multiple countries during January, but it is believed widespread community transmission began late in February or early March. Since March the virus has caused over 100k confirmed deaths in the US, with some states more severely impacted, notably NY and NJ. Here I examine excess mortality at the national and state level from January through July 2020. I find that the increase in excess mortality began in late February, suggesting the pathogen was circulating undetected earlier than assumed. The timing and intensity of the increase in excess mortality varied across states, with two patterns emerging: an early, sharp increase reaching a peak during April-May, best exemplified by NY and NJ, and a shallower, sustained increase, reaching a peak in late July, observed mostly in the southern regions of the US.

Neuroinflammation, defined as inflammatory reactions mediated by cytokines, chemokines, reactive oxygen species, and secondary messengers in the central nervous system (CNS) including the brain and spinal cord is the basis of many neurological disorders. Recently, erythropoietin (EPO) has been considered and studied as a modulator of neuroinflammation. On this article minireview of pathophysiology of neuroinflammation and the neuroprotective effects of EPO is discussed and a case of subacute huge subdural hematoma with double mydriasis operated urgently, treated with low daily dose (vs high dose once or twice a month in the literature) of EPO and recovered fully and discharged home with good consciousness is reported. In addition, the probable unfavorable outcome of erythropoietin administration in patients with neuroinflammation in COVID-19 is considered.

The COVID-19 appears as a catastrophic health risk with psychological, emotional, social and relational implications. From the early stages of the virus spread, the elderly population was identified as the most vulnerable and the health authorities have rightly focused on such frailest population. Conversely, less attention was paid to emotional and psychological dimension of children and adolescents. Actually, they were less at risk quoad vitam or quoad valetudinem, nevertheless they had to face a reality of anxiety, fears and uncertainties. The current study investigated state anxiety and emotion awareness in a healthy sample of older adolescents, 84 females and 64 males, aged 17 to 19, during the pandemic lockdown, using Self-rating Anxiety Scale and the Italian Emotion Awareness Questionnaire. An unexpected anxious phenomenology, impacting the anxiety ideo-affective domain, was found, while the somatic symptomatology appeared to be less severe. The highest anxiety symptom were the breathing difficulties. These findings supported the hypothesis that the COVID-19 pandemic may be a risk condition for an increased state anxiety in older adolescents and suggest the need to provide 1. an effective, empathic communication system with the direct participation of older adolescents, 2. a psychological counseling service for stress management of adolescents.

We report the results of our study of approved drugs as potential treatments for COVID 19, based on the application of various bioinformatics predictive methods. The drugs studied include chloroquine, ivermectin, remdesivir, sofosbuvir, boceprevir, and α-difluoromethylornithine (DMFO). Our results indicate that these small molecules selectively bind to stable, kinetically active residues and residues adjoining them on the surface of proteins and inside protein pockets, and that some prefer hydrophobic over other active sites. Our approach is not restricted to viruses and can facilitate rational drug design, as well as improve our understanding of molecular interactions, in general.

Background: Coronavirus disease 2019 (COVID-19) is an ongoing pandemic and life-threatening highly infectious disease. The people of Bangladesh are at high risk of COVID-19 and have already experienced various socio-economic, health and psychological (mental) consequences. Particularly, mental health problems are dominantly reported in the literature and should be controlled. The main objective of this epidemiological study is to assess the mental distress and identify its determinants using online-based survey. Such information is urgently needed to develop feasible strategies for Bangladesh. Methods: An online survey was conducted for this study from May 01 to May 05, 2020. A total of 240 respondents provided self-reported online responses. Respondent’s mental distress was measured by the General Health Questionnaire 12 (GHQ-12) and by the self-rated mental health (SRMH) question. Various kinds of statistical analyses ranging from simple to multivariable logistic recession were performed using SPSS 23.0. Results: About 31.3% and 48.3% of respondents were mentally distressed by GHQ-12 and SRMH question, respectively. Logistic regression analysis revealed that mental distress was significantly higher among those respondents, whose usual activity was affected by the coronavirus (OR = 6.40, 95% CI: 1.87 - 21.90, p<0.001) and whose financial stress was increased due to lockdown (OR = 2.12, 95% CI: 1.01 – 4.46, p<0.05) on GHQ-12. Female sex (OR = 1.97, 95% CI: 1.03 – 3.75, p<0.05) and respondents with poor mental health before the outbreak (OR = 3.38, 95% CI: 1.18 – 9.72, p<0.05) were also significantly affected by mental distress on SRMH. Conclusions: At least thirty percent of the respondents were found to be mentally distressed. Some of the study findings, particularly significant determinants, should be considered while developing strategies to reduce the burden of mental distress among study respondents or similar group in Bangladesh.

Coronavirus disease (COVID-19) is a new discovered strain where WHO officially declares the disease as COVID-19 while the virus responsible for it called Severe Acute Respiratory Syndrome Coronavirus 2 or SARS-CoV-2. The incubation period of this disease is between 14 days. Ordinary clinical symptoms that reported around the world include fever, cough, fatigue, diarrhoea and vomiting as well as asymptomatic for certain people. Infection is spread mainly through broad droplets. In early March 2020, WHO again has announced that COVID-19 is a pandemic with currently no specific treatment. The potential use of SARS-COV-2 proteome as a vaccine candidate by analysing through B-cell and T-cell antigenicity by using a immunoinformatics approach as a vaccine development early stage. In this study, we used consensus sequence for SARS-COV-2 proteome that was retrieved from NCBI database. VaxiJen 2.0 was mainly used to identify the antigenic property of SARS-COV-2 proteins. IEDB then used to analyse the B-cell epitope, the presence of T cell immunogenic epitope in SARS-COV-2 proteins was obtained by using compromise method of MHC class I and II tools that accessible respectively using ProPred-1 server and MHC II Binding Prediction in IEDB database. The best epitopes of B and T-cell epitopes were predicted with high antigencity and the information is disseminated through web-based database resource (https://covid-19.omicstutorials.com/epitopes/). This study will be useful to find a new epitope-based candidate for SARS-COV-2. However, further study needs to be done for the next stages of vaccine development.

Children and young people (CYP) with neurodevelopmental disorders (NDDs) may be particularly vulnerable to adverse mental health effects due to the COVID-19 pandemic. We conducted a cross-sectional U.K parent-reported study from 2nd April-2nd June 2020, using the Strengths & Difficulties Questionnaire. CYP with NDDs (n=371) compared to neurotypical controls, had a higher prevalence of emotional symptoms (42% vs 15%), conduct problems (28% vs 9%), and lower prosocial behaviours (54% vs 22%). Those with attention-deficit/hyperactivity disorder showed inflated conduct, and those with autism spectrum disorder exhibited decreased prosocial behaviours. Females with ASD had higher emotional symptoms compared to males.

Background: The use of animal models for biomedical research provides us with a convenient and feasible route to establish causal relationships by recapitulating the temporal sequence of events in a controlled environment with a potential to manipulate the variables at multiple levels including genetic, protein, physiological or environmental. Objectives: The current review was conducted to gain insights into various animal models for the SARS-CoV-2 virus. Material and Methods: A literature review (PUBMED, PUBMED Central, PMC, Google Scholar, Google search engine) following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines performed in early April 2020 revealed 9 articles of interest. Search terms included covid 19, covid-19, novel corona virus, SARS-CoV-2, animal models, experimental models, laboratory models & covid 19 animal models. Two independent reviewers extracted the data; the third reviewer was involved in case of discrepancy. Results: SARS-CoV-2 shares an identical receptor binding domain with the SARS-CoV virus and has a superior binding affinity to the host ACE2. Based on this, the role of rhesus macaques, golden Syrian hamsters, transgenic hACE2 mice and ferrets as animal models have been studied. All four animals are susceptible to infection with SARS-CoV-2 with variable clinical presentation but universal recovery. The respiratory tract is primarily involved in all four models. Involvement of intestines was also seen in at least one study in each animal. Transfer to naïve animals in close contact has been documented in case of hamsters and ferrets. Seroconversion was documented in all although the role of convalescent sera was tested in hamsters only, with positive results though. Air-borne transmission was documented in ferrets and the possibility of feco-oral transmission was suggested for hamsters. The possibilities of recurrence and re-infection were ruled out by experiments upon the rhesus macaques. The fulfilment of Koch’s postulates has been highlighted. Discussion: The various studies available on animal models have been able to establish models of infection and transmission that recapitulate different aspects of disease in humans. However, the response between different animals and the same animal in different experiments is not completely coherent. Some of them do not manifest the disease clinically while others behave differently at molecular and immunological levels. Moreover, the physiology of these animals is not identical to human beings and the findings may not be extrapolated to human beings in an ‘as-is’ manner. Conclusions: The review acknowledges the achievements made by these experiments in a short span of time and highlighted the urgent need for a deeper dive in search of a quintessential animal model which can be studied for efficacy and safety of newer drugs and vaccines before a make-shift from the petri-dish to the human body can be contemplated.

The epidemic of Coronavirus Disease 2019 (COVID-19) have affected all the regions of the world, nevertheless, in some countries there is a lack of studies on its main clinical and epidemiological features. We analyzed the incidence, incidence rates, and evolution of COVID-19 cases in Honduras from February 18-April 24, 2020.Methods: Using daily epidemiological data from surveillance about COVID-19 in Honduras, we calculated the rates of incidence (cases/100,000 population), and developed at national, departmental, and municipal levels GIS-based maps.Results: February 18 - April 24, 2020, a sum of 3,169 suspected COVID-19 cases have been assessed by RT-PCR, 533 (16.8%) of them were positive, for an incidence rate of 5.73 cases/100,000 pop. The highest peak was reached on March 31 (48 cases). The department with the highest number of cases and incidence rate was Cortes (383 cases, 71.9% of the total, 21.45 cases/100,000 pop). Discussion: The pattern and evolution of COVID-19 epidemic in Honduras has been particularly focused in the major urban areas, San Pedro Sula and Tegucigalpa, the capital city. Studies using geographical information systems linked with clinical disease characteristics are necessary to attain accurate epidemiological data for public health systems. Such information is also useful for assessment of the evolution of the pandemic and monitoring interventions.

This paper surveys estimates of the transmission features of the novel coronavirus, and then proposes a model to address sample-selection bias in estimated determinants of infection. Containment assumptions of the infection forecasting models depend on assumed effects of policies and self-regulating behavior. In the commons dilemma of the pandemic, the perceived ‘low risks’ of unregulated marginal choices do not reflect the full social cost, implying non-pharmaceutical interventions (NPI) to reduce mortality can enhance social welfare. As more economic activity renews with liftings of restrictive NPI (RNPI), a critical question concerns the ability of milder NPI (MNPI) and voluntary precautions to mitigate the risk of greater infections and deaths while also limiting the pandemic’s economic damage and its social costs. Ineffective NPI could lead to continued COVID-19 waves and new types of crises, worsened expectations and delayed economic recoveries. From the central range of surveyed estimates of transmission and alternative herd-immunity-threshold estimates, a ‘worst-case’ virus guidepost suggests eventual deaths of around 25 to 41 million worldwide and 1.1 to 1.7 million in the U.S. needed to reach herd immunity with no vaccine or treatment. The most optimistic study surveyed (theoretical model from a non-reviewed preprint study) combined with the low end of the range of the estimated mortality rate suggests 6 to 9 million deaths worldwide and 250 to 370 thousand in the U.S. to reach herd immunity. Successes in the mix of NPI, treatments, and vaccine can limit the eventual global death toll of the virus. Improved estimation models for forecasting and decision making may assist in better targeting the local timings and mix of NPI. Diagnostic tests for the virus have been largely limited to symptomatic cases, causing possible sample selection bias. A recursive bivariate probit model of infection and testing is proposed along with several possible applications from cross-section or panel-data estimation. Multiple potential explanatory variables, data sources, and estimation needs are specified and discussed.

A recent manuscript (Zhou, P. et al. “A pneumonia outbreak associated with a new coronavirus of probable bat origin”, Nature 579, 270–273 (2020). https://doi.org/10.1038/s41586-020-2012-7) from Wuhan Institute of Virology claimed the identification of a bat coronavirus, RaTG13, which showed 96.2% genome homology with SARS-CoV-2. In this paper, we raise the puzzling observations surrounding the identification, characterization, unique genome features of this RaTG13 strain, as well as its 100% nucleotide identity in partial RdRp gene with another bat coronavirus strain BtCoV/4991. And the paper presented premature hypothesis of potential bat origin of SARS-CoV-2 while RaTG13 strain was not successfully isolated. We also present the concerns on the methodology, data quality and experiment procedures described in this paper. We call for the authors to provide additional data, to share related samples to be verified and further characterized by other scientists.

This paper aims to quantify the effect of the deadly novel coronavirus (COVID-19) pandemic outbreak on Chinese stock market performance. Shanghai Stock Exchange Composite Index and its component sector indices are examined in this study. The pandemic is represented by a lockdown dummy, new COVID-19 cases and a dummy for 3 February 2020. First, descriptive analysis is performed on these indices to compare their performances before and during the lockdown period. Next, regression analysis with Exponential Generalized Autoregressive Conditional Heteroscedasticity specification is estimated to quantify the pandemic effect on the Chinese stock market. This paper finds that health care, information technology and telecommunication services sectors were relatively more pandemic-resistant, while other sectors were more severely hurt by the pandemic outbreak. The extent to which each sector was affected by pandemic and sentiments in other financial and commodity markets were reported in details in this paper. The findings of this paper are resourceful for investors to avoid huge loss amid pandemic outburst and the China Securities Regulatory Commission in handling future pandemic occurrence to cool down excessive market sentiments.

Abstract: A primary action of vitamin D is regulation of gene transcription. Many cell types possess genes that make antimicrobial peptides (AMPS) (endogenous antibiotics), recently discovered to be regulated by vitamin D. Two examples are cathelicidin and beta defensins, both bioactive against many different bacteria, fungi, mycobacteria, parasites and viruses. The signal transduction pathway is triggered by sensing microorganisms via cell surface receptors, causing intracellular production of calcitriol (1,25(OH)2D) and vitamin D receptors, leading to upregulation of AMP production. Serum 25(OH)D concentrations required to sustain adequate AMP production to eradicate infections are unknown. Vitamin D3 is photosynthesized in skin in amounts ranging from 10,000 (250 mcg) to 25,000 (625 mcg) International Units (IU) from 7-dehydrocholesterol after whole-body exposure to one minimal erythemal dose (MED) of ultraviolet B (UVB) radiation, and is impacted by many factors including geographic localities, seasonal changes and skin pigmentation. We and others have reported extended daily oral dosing with these amounts of vitamin D3 safe. We routinely observe serum 25(OH)D concentrations below 20ng/ml on new admissions, which have been reported insufficient to sustain AMP production. In contrast serum 25(OH)D concentrations above 100ng/ml have been reported after serial UVB treatments for psoriasis. Little vitamin D naturally occurs in food, and insufficient sun exposure may be causing worldwide deficiency. We review evidence suggesting that higher daily intakes of vitamin D3 than the currently recommended 600 (15 mcg) IU/day may be necessary to sustain AMP production in the face of an overwhelming infection, particularly in non-Hispanic blacks, a high risk population suffering the worst outcomes from COVID-19. We propose that increased vitamin D supplementation could provide a safe and cost-effective way to protect all populations from infections, in particular those from pandemic COVID-19.

A growing number of studies suggest that SARS-CoV-2 could interfere with homeostatic mechanisms in the lung but the implications of this possible interference have not been fully explored in the literature. In this work, we examine the consequences that can be drawn from this hypothesis according to currently available knowledge. We suggest that one such consequence is the potential disruption of normal ventilation and perfusion of lung regions that may be distant from the infection sites. Loss of ventilation might result in local alveolar hypoxia and contribute to hypoxemia, which in turn could trigger homeostatic responses that enhance blood oxygenation by redistributing pulmonary blood circulation. Sudden changes in perfusion might then lead to the development of hydrostatic edema and eventually to vascular remodeling and inflammation. Therefore, the immune response might not be the only source of the substantial inflammation observed in lung tissues of patients with severe COVID-19, as is often assumed in the literature. The balance between the homeostatic and the immune reaction in each patient could account for the observed heterogeneity of the clinical manifestations of COVID-19.

The ubiquitin-specific protease 2 (USP) belongs to the family of deubiquitinases and plays a critical role in tumors cells’ survival and therefore signifies an important therapeutic target. Previous studies have indicated promising efficacies of potent human USP2 inhibitors including, thiopurine analogues against SARS-CoV papain-like proteases (PLpro). The PLpro have significant functional implications in the innate immune response during SARS-CoV-2 infection and considered an important antiviral target. Both proteases share strikingly similar USP fold with right-handed thumb–palm–fingers structural scaffold and conserved catalytic triad Cys-His-Asp/Asn. In this urgency situation of COVID-19 outbreak, there is a lack of in-vitro facilities readily available to test SARS-CoV-2 inhibitors in whole-cell assays. Therefore, we adopted an alternate route to identify potential USP2 inhibitor through integrated structure-based virtual screening efforts. After a subsequent virtual screening protocol, the best compounds were selected and tested. The compound Z93 showed significant IC₅₀ value against Jurkat (9.67 µM) and MOTL-4 cells (11.8 µM). The binding mode of Z93 was extensively analyzed through molecular docking, followed by MD simulations, and molecular interactions were compared with SARS-CoV-2. The relative binding poses of Z93 fitted well in the binding site of both proteases and showed consensus π-π stacking and H-bond interactions with histidine and aspartate/asparagine residues of the catalytic triad. These results led us to speculate that compound Z93 might be the first potential chemical lead against SARS-CoV-2 PLpro, which warrants in-vitro evaluations.

The COVID-19 pandemic situation, disease intensity, weak healthcare facilities, unawareness, and misinformation led people to fear and anxiety in Bangladesh. This study intended to get peoples’ perception on psychosocial, socio-economic and environmental crisis amidst the pandemi. An online questionnaire was surveyed nationwide (respondents no.1066). Datasets were analyzed through the Principal Component Analysis (PCA), hierarchical Cluster Analysis (CA), Pearson’s correlation matrix (PCM), Linear regression analysis (LRA), and psychometric characteristics were included in the Classical Test Theory (CTT) analysis. There were good associations among the psychosocial, socio-economic and environmental parameters. A significant association between fear of COVID-19 with struggling healthcare system (p<0.05) was found. Also, negative association between fragile health system and government’s ability to deal with the pandemic (p<0.05) revealing poor governance. Again, a positive association of shutdown and social distancing with fear of losing life, and due to lack of health treatment (p<0.05) reveals that shut down hampers normal activities which may lead to mental and economic stress. However, a positive association of socio-economic impact of the shutdown with poor people’s suffering, the price hike of basic need, hamper of formal education (p<0.05) may lead to severe socio-economic and health crisis. There is a possibility of climate-induced disaster during/after the pandemic, which will create severe food insecurity (p<0.01). Daily wage earners and poors will suffer most by food and nutritional deficiency, and the country may face huge economic burden. Proper risk assessment and communications is needed to alleviate fear and anxiety. Thus, financial support and mental boosting is required.

On 9 March 2020, two cases of COVID-19 were reported in Burkina Faso. As of 10 April 2020, a total number of 484 cases (404 cases in the Kadiogo province) were reported nationwide. Real-time forecasts of COVID-19 are important to inform decision-making in the country. Here, we propose an approach that tests the performance of four models (Exponential Growth model, the Generalized Growth model (GGM), the Generalized Logistic Growth, and Richards Growth model) to select the model that best fit data and to generate short-term forecasting (5-, 10-, and 15-day forecasts from 11 to 25 April 2020) in Kadiogo, the epicenter of the outbreak. Using daily number of confirmed COVID-19 cases, the results suggests that GGM performed the best out of the 4 models. Overall, our GGM predictions suggested an average total number of cumulative cases of 514 (95% CI, 464–559), 629 (95% CI, 559–691), and 750 (95% CI, 661–840) between 11 to 15 April, 16 to 20 April, and 20 to 25 April 2020, respectively. COVID-19 in this province was best approximated by sub exponential growth rather than exponential or logistic growth. Current data suggest that COVID-19 cases would continue to increase over the next 15-days.

The beginning of 2020 has seen the emergence of coronavirus outbreak caused by a novel virus called SARS-CoV-2. The sudden explosion and uncontrolled worldwide spread of COVID-19 show the limitations of existing healthcare systems to timely handle public health emergencies. In such contexts, innovative technologies such as blockchain and Artificial Intelligence (AI) have emerged as promising solutions for fighting coronavirus epidemic. On the one hand, blockchain can combat pandemics by enabling early detection of outbreaks, protecting user privacy, and ensuring reliable medical supply chain during the outbreak tracking. On the other hand, AI provides intelligent solutions for identifying symptoms caused by coronavirus for treatments and supporting drug manufacturing. Motivated by these, in this paper we present an extensive survey on the use of blockchain and AI for combating coronavirus (COVID-19) epidemics based on the rapidly emerging literature. First, we introduce a new conceptual architecture which integrates blockchain and AI specific for COVID-19 fighting. Particularly, we highlight the key solutions that blockchain and AI can provide to combat the COVID-19 outbreak. Then, we survey the latest research efforts on the use of blockchain and AI for COVID-19 fighting in a wide range of applications. The newly emerging projects and use cases enabled by these technologies to deal with coronavirus pandemic are also presented. Finally, we point out challenges and future directions that motivate more research efforts to deal with future coronavirus-like epidemics.

The COVID-19 pandemic has great adverse impacts on personal life, the U.S. economy, and the world economy. Freezing all human activities is not a sustainable measure. Thus we want to develop a public intervention framework that allows people to resume personal and economic activities. In this article, we examined transmission routes, disease severity, personal vulnerability, available treatments, and person-person interactions to establish a general public intervention framework. We divide people into risk groups, non-risk group and group that may serve as viral transmitters, explore interactions between individual persons within each group and between different groups, and propose interaction behavior modifications to mitigate viral exposures. For the non-risk groups, we identified preventive measures that can help them avoid the most serious exposures and infections that pose higher death risks. The invention measures for the vulnerable groups include prior-exposure measures, heightened protective measures, interaction behavior changes, post-exposure remedial measures, and multiple factors treatments to reduce death and disability risks. The multiple interventions and two-ways defensive behavior modifications are expected to result in reduced rate of detectable infections and lowered disease severity for the vulnerable groups. In this framework, most human activities and economic activities can continue as normal. With time passing, the population acquires population immunity against the COVID-19 virus. Implementation of this intervention framework requires considerable resources and governmental effects while the multiple factors treatment protocol requires the support of health care professionals.

A literature review was conducted to summarize the frequency of the D-allele of the angiotensin-converting enzyme-1 in all countries with available data. Using an ecological study design limited to high income countries, we found that the country-level frequency of the D-allele was associated with increased COVID-19 incidence and mortality.

Background: A large percentage of deaths in an epidemic or pandemic can be due to overshoot of population (herd) immunity, either from the initial peak or from planned or unplanned exit from lockdown or social distancing conditions. Objectives: We study partial unlock or reopening interaction with seasonal effects in a managed epidemic to quantify overshoot effects on small and large unlock steps and discover robust strategies for reducing overshoot. Methods: We simulate partial unlock of social distancing for epidemics over a range of replication factor, immunity duration and seasonality factor for strategies targeting immunity thresholds using overshoot optimization. Results: Seasonality change must be taken into account as one of the steps in an easing sequence, and a two step unlock, including seasonal effects, minimizes overshoot and deaths. It may cause undershoot, which causes rebounds and assists survival of the pathogen. Conclusions: Partial easing levels, even low levels for economic relief while waiting on a vaccine, have population immunity thresholds based on the reduced replication rates and may experience overshoot as well. We further find a two step strategy remains highly sensitive to variations in case ratio, replication factor, seasonality and timing. We demonstrate a three or more step strategy is more robust, and conclude that the best possible approach minimizes deaths under a range of likely actual conditions which include public response.

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.

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.

The recent outbreak of coronavirus disease 2019 caused by the new coronavirus, SARS-CoV-2, has become an international emergency. Since there is no effective therapy for the treatment of this disease, drugs or vaccine that can prevent or cure the SARS-CoV-2 infection are urgently needed. The viral 3-chymotrypsin-like cysteine protease (3CLpro), which plays a key role in the replication of coronavirus, is a potential drug target for the development of anti-SARS-CoV-2 drugs. With the crystal structure of 3CLpro, we performed virtual screening from a small chemical library of a Traditional Chinese Medicine recipe- FuFang Zhenzhu Tiaozhi (FTZ). Five compounds with the best scores were screened and could be considered as potential hit compounds to be investigated further with bioassays for their anti-virus effects.

Abstract: COVID-19 Long Haulers, an estimated 3% to 12% of people infected globally with coronavirus having latter devasting symptoms 12 weeks after the initial infection is on the rise. We conducted a collaborative study with the long covid patient organization in Greece in order to estimate the prevalence, symptoms and problems that adult long haulers experience and then propose a management plan for these patients. Symptoms were obtained from 208 patients using unstructured qualitative free text entries in an anonymized online questionnaire. The majority of respondents (68.8%) were not hospitalized and had been diagnosed more than six months ago with lingering symptoms (66,8%). Eighteen different symptoms (fatigue, tachycardia, shortness of breath, parosmia etc) were mentioned in both hospitalized and community patients. Interestingly, patients with initial mild symptoms suffer from the same persistent symptoms as those who were hospitalized. Awareness of long covid sequelae seems to be low even among medical doctors. Treatment options incorporating targeted rehabilitation programs are either not available or still excluded from the management plan of long covid patients. Since long COVID is a multi-systemic entity, we propose a holistic interventional approach using a multidisciplinary medical team in order to securely and effectively diagnose and treat these specific patients. Academic and medical community must collaborate with long covid patients’ organizations so as to provide personalized medicine.

In this paper, the P versus NP problem is studied based on a six-dimensional space-time perspective. The gap between the P-class and NP-class arises from the relationship between time and the solution, as well as the answer that is independent of time. The complexity of solving a problem depends on the time dependence of the answer. Solving problems whose answers do not depend on the passage of time is very difficult and impossible. Like the description of the gravitational factor in Newtonian physics, NP class problems require different mathematical tools. Based on the generalization of physical facts in mathematics, based on six-dimensional space-time, a method to solve problem P versus NP problem has been stated. The results of this study offer a fresh insight into information processing that occurs independent of the passage of time.

In this work, a GaN-on-Si quasi-vertical Schottky diode was demonstrated on a locally grown n-GaN drift layer. The diode achieves a high current density of 2.5 kA/cm², a specific on-resistance RON,sp of 1.9 mΩ.cm² despite the crowding effect in quasi-vertical device and on/off current ratio (Ion/Ioff) of 1010. Temperature-dependent current-voltage characteristics have been measured in the range of 300-433 K to investigate the mechanisms of leakage conduction in the device. At near zero bias, thermionic emission (TE) was found to dominate. At voltage range from -1 to -10 V, electrons gain enough energy to excite into trap states, leading to the dominance of Frenkel-Poole emission (FPE). For a higher voltage range (-10V to -40V), the increased electric field promotes electron hopping along the threading dislocations in the “bulk” GaN layers, and thus, Variable Range Hopping becomes the main mechanism for the whole temperature range. This work provides an in-depth insight into the leakage conduction mechanisms on vertical GaN-on-Si Schottky barrier Diodes (SBDs) grown by localized epitaxy.

The correct selection of the value of p is a complex and iterative procedure that requires experience in the interpretation of the obtained interpolated maps. Inverse Distance Weighting is a method applied to the porosities of the K and L hydrocarbon reservoirs, discovered in the Neogene (Lower Pontian) subsurface sandstones in the northern Croatia (Pannonian Basin System). They represent small and large data samples. Also a standard statistical analysis of the data was made, followed by the qualitative-quantitative analysis of the maps, based on the selection of different values of the power distance exponent (p-value) for the K and L reservoirs maps. According to the qualitative analysis, for a small data set, p-value could be set on 1 or 2 giving the most optimal result, while for a large data set, a p value of 3 and 4 could be applied. By quantitative analysis, for the case of small data p=2 is recommended, resulting in a root mean square error value of 0.03458, a mean absolute error of 0.02013 and a median absolute deviation of 0.00546. Oppositely, a p-value of 3 and 4 is selected as appropriate for a large data set, with root mean square errors of 0.02435 and 0.02437, mean square errors of 0.01582 and 0.01509 and median absolute deviations 0.00896 and 0.00444. Eventually for a small data set, it is recommended to use a p-value of 2, and for a large data set, a p-value of 3 or 4.

Mesoporous silica nanoparticles (MSNs) can be used as carrier materials for the controlled release of pesticides while reducing their negative environmental impact. In this study, we screened an active ingredient, p-cymene (PC), with an excellent inhibitory effect on rice bacterial blight. Subsequently, the PC was successfully loaded onto MSNs via physisorption(PC@MSNs). PC@MSNs, characterized by a regular spherical shape, smooth surface, and an MSN average size of 262.9 nm, achieved an 8.6 % drug loading capacity. The release kinetics of the PC from the PC@MSNs demonstrated a sustained release (288 h) pattern influenced by drug diffusion. The efficacy of the PC@MSNs against Xanthomonas oryzae pv. Oryzae paralleled those of PC. Acute toxicity assays re-vealed that the PC@MSNs were less toxic to aquatic life (LC50=257.867 mg/L) and that the formu-lation showed no adverse effects on rice seedling growth. In summary, these results suggest that PC@MSNs can broaden PC's application scope in managing rice diseases.

Given a set of distinct non-negative integers X^n and a target certificate S in parametrized form: ∃X^k⊆X^n,∑_(x_i∈X^k)▒x_i =S (k=|X^k |,n=|X^n |). We present a polynomial solution of the subset sum problem with time complexity T≤O(kn)≤O(n^2) and space complexity S≤O(((n-1)n)/2)≤O(n^2 ), so that P = NP.

Clopidogrel is one of the most prescribed antiplatelet drugs for cardiovascular diseases prevention. Clopidogrel is a prodrug metabolised by CYP2C19 in active metabolites with anti-aggregant effect. Pharmacogenetic variants such as CYP2C19*2 variant can alter the anti-aggregant effect of clopidogrel leading to a higher risk of cardiovascular disease relapse. The aim of this study was to evaluate the prescription characteristics of CYP2C19 pharmacogenetics in patients on clopidogrel treatment, based on a specific query in a clinical data warehouse. We evaluated the demographics of patients, prescribers, medical indications, CYP2C19 pharmacogenetic tests and therapeutic changes. Neurologists were the main prescribers of CYP2C19 pharmacogenetic tests associated with clopidogrel treatment in a context of suspicion of stroke relapse. Pharmacogenetic tests were mainly prescribed a posteriori to clopidogrel prescription. Clopidogrel pharmacogenetic resistance was associated with the prescription of lysine acetylsalicylate in substitution of clopidogrel. Clear clinical practice guidelines are needed to position CYP2C19 pharmacogenetic testing for patients on clopidogrel treatment.

Electrocardigraphy remains as a first-line evaluation method for cardiac function, recording the electrical activity of the heart from the body surface. Since atrial activation is seen on the ECG as P-wave, several factors are known to impact the appearance of the P-wave, such as direction of electric impulse, conduction abnormalities and anatomical characteristics of the atria. The aim of this retrospective study was to find statistically significant associations between anatomy of pulmonary veins (PVs) osberved in cardiac computed tomography (CT) and P-wave appearance during sinus rhythm on resting ECG. For each patient, a resting 12-lead ECG was recorded, the field of analysis was P wave – its’ duration, morphology and axis. The evaluation of the CT scan recordings was performed by creating 3D models of the left atrium and analyzing anatomy of the PVs and left atrial appendage (LAA). Noteworthy correlations were found: anatomy of the left PVs showed an association with LAA volume, LAA morphology and P-wave notching in lead II. The right PVs demonstrated relation with P wave axis and amplitude. Although these correlations cannot be classified as strong, they may play a role in significant scientific discoveries in future research projects.

The scope of this study was twofold: first, to introduce a new method in examining measurement invariance, especially with large-scale studies where a large number of group comparisons are involved: the alignment approach, where only configural invariance is necessary to achieve measurement invariance. Second, to evaluate the psychometric robustness of this approach using real-life data. Particularly, we applied this approach to examine whether the factor structure of a cognitive ability test (PGAT) exhibits measurement invariance across the 26 universities of the Kingdom of Saudi Arabia. The sample consisted of 9,849 graduate students from 26 universities around the Kingdom. The results indicated a robust configural model suggesting that the P-GAT subscales were invariant across the 26 universities. Finally, the aligned factor mean values were estimated, and factor mean comparisons of every group’s mean with all other group means were conducted for both cognitive domains (Verbal and Quantitative). In both domains, King Saud University had the highest mean score among all universities. Moreover, its mean factor score was significantly higher than any other university besides Dammam University. On the other hand, several universities allocated at the northern and Southern borders of the country exhibited the lowest factor mean scores.

Panax ginseng C. A. Meyer (P. ginseng), has been widely used in traditional Chinese medicine (TCM). It contains a number of chemical components and possesses a variety of pharmacological activities. Alzheimer's disease (AD) is neurodegenerative disease that creates a huge burden on the lives and health of individuals. In recent years, studies have indicated that the chemical components of P. ginseng, especially ginsenosides, play a pronounced positive role in the prevention and treatment of neurological diseases. This review aimed to summarize currently studies on chemical components and the mechanisms action in AD intervention treatment of P. ginseng, especially ginsenosides. In this review, the components of P. ginseng and their respective active effects were first introduced. Then the key molecular mechanisms and signaling pathways of P. ginseng were introduced, and its different active ingredients in the prevention and treatment of Alzheimer's disease-related pathogenesis were also summarized from the pathogenesis of AD Aβ generation and aggregation, hyperphosphorylation of tau protein，oxidant stress，neuroinflammation，mitochondrial damage，disorder of neurotransmitter and gut microbiota. Signaling pathway networks related to the action of ginseng active ingredients was constructed, which could serve as a therapeutic target for Alzheimer's disease. In addition to a detailed report on P. ginseng in improving Alzheimer's disease-related pathogenesis, the application of the current technology, spatial metabonomics in AD therapeutics and diagnostics were later discussed. Spatial metabonomics could be applied to investigate the multi-target intervention of P. ginseng on Alzheimer's disease. Research perspectives for the study of P. ginseng in the treatment of Alzheimer's disease were provided for further studies.

The research is a deep study of the CBOE Volatility Index (VIX), which represent the market sentiments of the S & P 500 Index (SPX) over a period of 33 years. It evaluates how the two indexes perform in the stock market crash and how reliable VIX is in predicting market sentiments. The research distributes the market rally in two forms, and one is a trust rally, when investors are happy to see the market in a stable form, and investors' sentiments are positive towards the stock market. Second is a fear rally, where investors' sentiments are negative, and their outlook is bearish for various reasons. It observes the pattern of rallies, like the longest trust or fear rally, in which year and its duration. The research analyzes data to reach a meaningful conclusion and various inferences that can be drawn from the study of historical data.

When 2−1/Q<p≤2, we establish the C^{0,1} and C^{1,α}-regularities of weak solutions to quasi-linear p-Laplacian type non-homogeneous equations in the Heisenberg group.

Paenibacilli are efficient producers of potent agents against bacterial and fungal pathogens, which are of great interest both for therapeutic applications in medicine as well as in agrobiotechnol-ogy. Lipopeptides produced by such organisms play a major role in their inactivation potential. In this work we investigated two lipopeptide complexes, the fusaricidins and the polymyxins, produced by Paenibacillus polymyxa strains DSM 32871 and M1 by MALDI-TOF mass spectrometry. The fusaricidins show potent antifungal activities and are distinguished by an unusual variabil-ity. For strain DSM 32871 we identified numerous yet unknown variants mass spectrometrically. DSM 32871 produces polymyxins of type E (colistins), while M1 forms polymyxins P. For both strains novel, but not yet completely characterized polymyxin species were detected, which pos-sibly are glycosylated. These compounds may be of interest therapeutically, because polymyxins attain increasing attention as last-resort antibiotics against multiresistant pathogenic Gram-negative bacteria. In addition, the volatilomes of DSM 32781 and M1 were investigated with a GC-MS approach using different cultivation media. Production of volatile organic com-pounds (VOCs) was strain and medium dependent. In particular, strain M1 manifested as an effi-cient VOC-producer that exhibited formation of 25 volatiles in total. A characteristic feature of Paenibacilli is the formation of volatile pyrazine derivatives.

The trace element selenium (Se) is taken up from the diet and becomes metabolized mainly by hepatocytes. Selenoprotein P (SELENOP) constitutes the liver-derived Se transporter. Biosynthesis of extracellular glutathione peroxidase (GPx3) in kidney depends on SELENOP-mediated Se supply. We hypothesized that Se status may serve as a useful prognostic marker for outcome in patients undergoing liver transplantation. Serum samples from patients were routinely collected before and after transplantation. Concentration of serum SELENOP and total Se as well as GPx3 activity were determined by standardized tests and related to survival, aetiology and pre-operative Child-Pugh and Model for End-Stage Liver Disease Scores. A total of 314 serum samples from 78 transplanted patients were available for analysis. The Se and SELENOP concentrations were on average below the reference ranges of healthy subjects. Patients with ethanol toxicity-dependent aetiology showed particularly low SELENOP and Se concentrations and GPx3 activity. Longitudinal analysis indicated declining Se concentrations in non-survivors. We conclude that severe liver disease necessitating organ replacement is characterized by a pronounced Se deficit before, during and after transplantation. A recovering Se status after surgery is associated with positive prognosis, and an adjuvant Se supplementation may thus support convalescence.

In developed countries, especially the big-sized ones like Australia and the USA, a car is almost an inevitable necessity to carry out daily activities. Due to this, used cars have become a great alternative to brand new cars because of their cost effectiveness. In this work, estimation of prices of used cars based on numerous factors is studied statistically. Data is based on prices of used cars sold across Australia. Statistical methods like correlation and permutation tests using linear regression model, exact tests and non-parametric bootstrapping is implemented to study the relationship of price with mileage and year of manufacture of the car using p-values and null hypothesis. Predictions are also made on the price by calculating a 95% confidence interval (CI) of median prices in small portions of the dataset. The study presents potential ideas for understanding correlation between variables and parameters in business studies.

Epigallocatechin-3-gallate (EGCG) is the most abundant polyphenol in green tea. In this study, the effects of dietary EGCG on oxidative stress and the metabolism and toxicity of acetaminophen in liver were investigated. Rats were fed the diets with (0.54 %) or without EGCG supplementation for four weeks and were then intraperitoneally injected with acetaminophen (1g/kg). Results showed EGCG lowered hepatic oxidative stress and cytochrome P450 (CYP) 1A2, 2E1, and 3A, and UDP-glucurosyltransferase activities prior to acetaminophen injection. After acetaminophen challenge, the elevations in plasma alanine aminotransferase activity and histological changes in liver were ameliorated by EGCG treatment. EGCG reduced acetaminophen-induced apoptosis by increasing the Bax/Bcl2 ratio in liver. EGCG mildly increased autophagy by increasing the LC3B II/I ratio. Lower hepatic acetaminophen-glutathione and acetaminophen-protein adducts contents were observed after EGCG treatment. EGCG increased glutathione peroxidase and NAD(P)H quinone 1 oxidoreductase activities and reduced organic anion-transporting polypeptides 1a1 expression in liver after acetaminophen treatment. Our results indicate that EGCG may lower oxidative stress and reduce the metabolism and toxicity of acetaminophen. The reductions in CYP-mediated acetaminophen bioactivation and uptake transporter, as well as enhanced antioxidant enzyme activity, may limit the accumulation of toxic products in liver and thus lower hepatotoxicity

Copulas are useful tools for modeling the dependence structure between two or more variables. Copulas are becoming a quite flexible tool in modeling dependence among the components of a multivariate vector, in particular to predict losses in insurance and finance. In this article, we study the dependence structure of some well-known real life insurance data (with two components mainly) and subsequently identify the best bivariate copula to model such a scenario via VineCopula package in R. Associated structural properties of these bivariate copulas are also discussed.

In this paper, we introduced many new notions and new contraction named as S-weakly contraction after that we obtained the p-common best proximity point theorems for different types of contractions in the setting of complete metric spaces by using weak P_p-property and proved the uniqueness of these points. Also we presented some examples to prove the validity of our results.

Metal oxide p-n heterojunction nanofibers (NFs) are among the most promising approaches to enhancing the efficiency of gas sensors. In this paper, we report the preparation of a series of p-NiO-loaded n-ZnO NFs, namely (1 − x) ZnO-xNiO (x = 0.03, 0.05, and 0.1 wt%), for hydrogen gas sensing experiments. Samples were prepared through the electrospinning technique followed by a calcination process. The sensing experiments showed that the sample with 0.05 wt% NiO loading resulted in the highest sensing performance at an optimal sensing temperature of 200 °C. The sensing mechanism is discussed in detail and contributions of the p-n heterojunctions, metallization of ZnO and catalytic effect of NiO on the sensing enhancements of an optimized gas sensor are analyzed. This study demonstrates the possibility of fabricating high-performance H₂ sensors through the optimization of p-type metal oxide loading on the surfaces of n-type metal oxides.

Kummerowia striata is a traditional medicine used for the therapy of inflammation-related diseases. Herein, we investigated the anti-melanogenic and antioxidant activities of an ethanolic extract of K. striata (EKS) using a number of in vitro and cell culture model systems. The anti-melanogenic effect was assessed in B16F10 melanoma cells based on melanin synthesis and in vitro tyrosinase inhibitory activity and the anti-oxidant activity assays were performed using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2ʹ-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS); EKS exhibited strong anti-oxidant activities in both the assays. The expression of tyrosinase, tyrosinase-related protein 1, tyrosinase-related protein 2, and microphthalmia-associated transcription factor was decreased in a dose-dependent manner at mRNA and protein levels upon treatment with EKS. Notably, EKS did not affect the cell viability at all the EKS concentrations used in this study, indicating that EKS-mediated inhibition of melanin synthesis is not accompanied with cytotoxicity. Collectively, our findings demonstrate, for the first time, that EKS possesses anti-melanogenic and anti-oxidant activities, and suggest that further evaluation and development of EKS as a functional supplement or cosmetic might be useful for skin whitening and for reduction wrinkles.

Graph coloring is a manifestation of graph partitioning, wherein, a graph is partitioned based on the adjacency of its elements. Partitioning serves potentially as a compartmentalization for any structural problem. Vertex coloring is the heart of the problem which is to find the chromatic number of a graph. The fact that there is no general efficient solution to this problem that may work unequivocally for all graphs opens up the realistic scope for combinatorial optimization algorithms to be invoked. The algorithmic complexity of graph coloring is non-deterministic in polynomial time (NP) and hard. To the best of our knowledge, there is no algorithm as yet that procures an exact solution of the chromatic number comprehensively for any and all graphs within the polynomial (P) time domain. However, several heuristics as well as some approximation algorithms have been attempted to obtain an approximate solution for the same. Here, we present a novel heuristic, namely, the 'trailing path', which returns an approximate solution of the chromatic number within polynomial time, and, with a better accuracy than most existing algorithms. The ‘trailing path’ algorithm is effectively a subtle combination of the search patterns of two existing heuristics (DSATUR and Largest First), and, operates along a trailing path of consecutively connected nodes (and thereby effectively maps to the problem of finding spanning tree(s) of the graph) during the entire course of coloring, where essentially lies both the novelty and the apt of the current approach. The study also suggests that the judicious implementation of randomness is one of the keys towards rendering an improved accuracy in such combinatorial optimization algorithms. Apart from the algorithmic attributes, essential properties of graph partitioning in random and different structured networks have also been surveyed, followed by a comparative study. The study reveals the remarkable stability and absorptive property of chromatic number across a wide array of graphs. Finally, a case study is presented to demonstrate the potential use of graph coloring in protein design – yet another hard problem in structural and evolutionary biology.

This paper includes some new investigations and results for post quantum calculus, denoted by (p,q)-calculus. A chain rule for (p,q)-derivative is developed. Also, a new (p,q)-analogue of the exponential function is introduced and some its properties including the addition property for (p,q)-exponential functions are investigated. Several useful results involving (p,q)-binomial coefficients and (p,q)-antiderivative are discovered. At the final part of this paper, (p,q)-analogue of some elementary functions including trigonometric functions and hyperbolic functions are considered and some properties and relations among them are analyzed extensively.

In this paper we establish several Hermite-Hadamard type integral inequalities for hyperbolic p-convex functions. Applications for special means are provided as well.

In this paper, we introduce a new generalization of the Hermite polynomials via (p, q)-exponential generating function and investigate several properties and relations for mentioned polynomials including derivative property, explicit formula, recurrence relation, integral representation. We also de…ne a (p, q)-analogue of the Bernstein polynomials and acquire their some formulas. We then provide some (p, q)-hyperbolic representations of the (p, q)-Bernstein polynomials. In addition, we obtain a correlation between (p, q)-Hermite polynomials and (p, q)-Bernstein polynomials.

In this study, a graphene-doped porous silicon (G-doped/p-Si) substrate for low ppm H₂ gas detection by an inexpensive synthesis route was proposed as a potential noble graphene-based gas sensor material and to understand the sensing mechanism. The G-doped/p-Si gas sensor was synthesized by a simple capillary force-assisted solution dropping method on p-Si substrates, whose porosity was generated through an electrochemical etching process. G-doped/p-Si was fabricated with various graphene concentrations and exploited as a H₂ sensor operated at room temperature. The sensing mechanism of the sensor with/without graphene decoration on p-Si was proposed to elucidate the synergetic gas sensing effect generated from the interface between the graphene and p-type silicon.

The current generation of nuclear reactors are evolutionary in design, mostly based on the technology originally designed to power submarines, and dominated by Light Water Reactors. The aims of the GenIV consortium are driven by sustainability, safety and reliability, economics, and proliferation resistance. The aims are extended here to encompass the ultimate and universal vision for strategic development of energy production, the ‘perpetuum mobile’ – at least as close as possible. We propose to rethink nuclear reactor design with the mission to develop a system which uses no fresh resources and produces no fresh waste during operation as well as generates power safe and reliably in economic way. The results of the innovative simulations presented here demonstrate that, from a theoretical perspective, it is feasible to fulfil the mission through the reuse of spent nuclear fuel from currently operating reactors as the fuel for a new reactor. The produced waste is less burdensome than current spent nuclear fuel which is used as feed to the system. However, safety, reliability and operational economics will need to be demonstrated to create the basis for the long term success of nuclear reactors as a major carbon free, sustainable, and applied highly reliable energy source.