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Plain language summaryMutant strains of SARS-CoV-2 called 'variants of concern' (VOCs) are linked to a good ability to infect, re-infect and spread among people. They are also linked to poor ability to fight the disease and reduced effectiveness of vaccines. Delta and Omicron are important VOCs because they are difficult to control and treat. Specific resistance to some drugs used to treat COVID-19 poses a further challenge. Therefore, discovering natural or plant-derived drugs with no known resistance would be valuable to the treatment of COVID-19. In this study, we screen and identify seven plant-derived compounds that may be useful to treating COVID-19 - we identify Quercetin-3-acetyl-glucoside, Rutin, Kaempferol, Catechin, Orientin, Obetrioside and Neridienone A as potential candidates. Orientin, Obetrioside, Catechin and Neridienone A are identified as candidates against Delta and Omicron for the first time. Aim: Structure-based identification of natural compounds against SARS-CoV-2, Delta and Omicron target proteins. Materials & methods: Several known antiviral natural compounds were subjected to molecular docking and MD simulation against SARS-CoV-2 Mpro, Helicase and Spike, including Delta and Omicron Spikes. Results: Of the docked ligands, 20 selected for each complex exhibited overall good binding affinities (-7.79 to -5.06 kcal/mol) with acceptable physiochemistry following Lipinski's rule. Finally, two best ligands from each complex upon simulation showed structural stability and compactness. Conclusion: Quercetin-3-acetyl-glucoside, Rutin, Kaempferol, Catechin, Orientin, Obetrioside and Neridienone A were identified as potential inhibitors of SARS-CoV-2 Mpro, Helicase and Spike, while Orientin and Obetrioside also showed good binding-affinities with Omicron Spike. Catechin and Neridienone A formed stable complexes with Delta Spike. Tweetable We report structure-based identification of natural compounds viz., Quercetin-3-acetyl-glucoside, Rutin, Kaempferol, Catechin, Orientin, Obetrioside and Neridienone A against SARS-CoV-2 Mpro, Helicase and Spike as well as Delta and Omicron Spike proteins.
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Background: During the eleven months of the novel SARS-CoV-2 disease (COVID-19) outbreak in China and its global spread, there is a remarkable understanding of its epidemiology, pathobiol-ogy, and clinical management strategies. While countering a heavy toll on health and the economy, world's regional authorities are enforcing safety guidelines and providing patient care. Currently, there is no globally approved treatment or intervention for COVID-19. Method(s): A structured online literature search for peer-reviewed articles was conducted on PubMed, Europe PMC, Google, WHO, CDC, FDA, and ClinicalTrials portals, using phrases such as COVID-19 treatment and intervention, COVID-19 drugs and COVID-19 vaccines. Result(s): Analysis of the retrieved data showed that as a part of 'Solidarity Clinical Trials', hundreds of treatment and intervention strategies, including antiviral drugs, cytokine antagonists, convalescent plasma therapy, and vaccine candidates, have been registered worldwide. While remdesivir, the anti-Ebola virus drug, has been approved as an 'emergency use' drug in the USA, favipiravir, the anti-flu drug, has been recently approved in Russia. Tocilizumab and sarilumab, the cytokine (IL-6) antagonists, have entered Phase-II/III clinical trials in hospitalized COVID-19 patients. Among the leading vaccine candidates, Phase-III clinical trial results of Moderna, Pfizer and Oxford vaccines seem to be game changers for COVID19. Conclusion(s): The world health authorities have strongly and quickly responded to the COVID-19 pan-demic. Nonetheless, world bodies must unite in combating this health crisis by developing cost-effective drugs and vaccines and making them accessible to resource-poor countries.Copyright © 2021 Bentham Science Publishers.
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The Covid-19 spun into a pandemic and has affected routine lives and global health. It is crucial to identify the infectious Covid-19 subjects as early as possible to avert its spread. The CXR images processed with deep learning (DL) processes have newly become an earnest method for early Covid-19 detection along with the regular RT-PCR test. This paper examines the deep learning (DL) models to detect Covid-19 from CXR images for early analysis of Covid-19. We conducted an empirical study to assess the efficacy of the proposed convolutional neural network DL model (CNN-DLM), pre-trained with some eminent networks such as MobileNet, InceptionNet-V3, ResNet50, Xception, and DenseNet121 for initial detection of Covid-19 for an openly accessible dataset. We also exhibited the accuracy and loss value curves for the selected number of epochs for all these models. The results indicate that with the proposed CNN model pre-trained with the DenseNet121 greater results were achieved compared to other pre-trained CNN-DLMs applied in a transfer learning approach. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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The impact of the pandemic is driving the recent upsurge in service automation and the adoption of service robots in the hospitality industry. As service paradigm and customer expectations shift from conventional customized and personalized services towards a digitalized service environment, such customer orientation may favor using service robots at scales that could render service employees redundant. This study aims to answer the above question by investigating service employees' perceptions of service robots. Data solicited from 405 service employees in the United States of America via Amazon's MTurk were analyzed using structural equation modeling. The result revealed that employees' awareness of adopting and using service robots significantly impacts their perception of robot-induced unemployment. Further, results indicated that the perception of robots' social skills significantly influences service employees' perception of robot-induced unemployment. Employee status was found to moderate the relationships mentioned above. Specifically, entry-level employees perceive the unemployment risk more than managers.
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Background: Assessing individuals’ knowledge and attitudes towards the Coronavirus Disease of 2019 (COVID-19) is essential for the related public health surveillance strategies. Although some of the studies were conducted in Bangladesh, none of these studies considered the social attitudes along with the awareness towards COVID-19. Because social attitudes may affect the mental health of COVID-19 patients. Therefore, the present cross-sectional study aims to assess the knowledge and social mindset toward COVID-19. Methods: A cross-sectional study was conducted via an online questionnaire, from 330 participants. Participants was purposefully selected who were Bangladeshi citizens age minimum 18 years of old, has internet connections and gave their consent to participate this survey. The measures included in this study were demographic data along with source of knowledge, measures taking for COVID-19 prevention, management, avoid affected person and places etc. All the data collected through survey were analyzed by SPSS-25.0. Mean, median, mode, percentages and 95% Confidence Interval with 5% margin of errors were calculated Results: Study indicating a high level of knowledge (95.5%) to COVID-19. Practically, Maximum respondents will avoid COVID-19 affected persons due to fear of infection 84% (95% CI: 80.0% to 87.1%) and fear of death 27.7% (22.9% to 32.5%) respectively. Another valuable point that about 71.8% (66.1– 76.7%) of them have the knowledge of the COVID-19 spreading process and around 56.4% (51.0–61.8%) of them know how to maintain necessary protection without avoiding COVID-19 affected person. This knowledge and attitude reflecting the belief that COVID-19 is controllable and containable. Conclusions: The finding suggests that health education interventions, public awareness-raising campaign should be directed by Government of Bangladesh (GoB) who may have knowledge gap or pessimism about COVID-19 infections and spread. © Journal of Xiangya Medicine. All rights reserved.
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Coronavirus 2019 (in short, Covid-19), was first found in the Wuhan province of China in December 2019 and has been declared a global pandemic by WHO in March 2020. Since its inception, its rapid spread among nations had initially collapsed the world economy and the increasing death-pool created a strong fear among people as the virus spread through human contact. Initially doctors struggled to diagnose the increasing number of patients as there was less availability of testing kits and failed to treat people efficiently which ultimately led to the collapse of the health sector of several countries. To help doctors primarily diagnose the virus, researchers around the world have come up with some radiology imaging techniques using the Convolutional Neural Network (CNN). While some of them worked on X-ray images and some others on CT scan images, very few of them worked on both the image types where their works are limited to detecting only covid and normal cases and none of them performed any comparative analysis between the performance of these two image types as far as our knowledge goes. This, therefore, has insisted us to perform a comparative analysis between X-ray and CT scan images. Thus we came up with a novel CNN model named CoroPy which works for both the image types and can detect normal, Covid-19 and viral pneumonia with great accuracy and shows that X-ray images have overall better performance. © 2021, Springer Nature Switzerland AG.
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BACKGROUND: The AABB Clinical Transfusion Medicine Committee (CTMC) compiles an annual synopsis of the published literature covering important developments in the field of transfusion medicine (TM), which has been made available as a manuscript published in Transfusion since 2018. METHODS: CTMC committee members reviewed original manuscripts including TM-related topics published electronically (ahead) or in print from December 2019 to December 2020. The selection of topics and manuscripts was discussed at committee meetings and chosen based on relevance and originality. Next, committee members worked in pairs to create a synopsis of each topic, which was then reviewed by two additional committee members. The first and senior authors of this manuscript assembled the final manuscript. Although this synopsis is extensive, it is not exhaustive, and some papers may have been excluded or missed. RESULTS: The following topics are included: COVID-19 effects on the blood supply and regulatory landscape, COVID convalescent plasma, adult transfusion practices, whole blood, molecular immunohematology, pediatric TM, cellular therapy, and apheresis medicine. CONCLUSIONS: This synopsis provides easy access to relevant topics and may be useful as an educational tool.
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Transfusion Medicine/trends , HumansABSTRACT
Social Stigma and COVID-19: The Experiences of Bangladeshi Returnees from Italy The outbreak of the COVID-19 pandemic has escalated social discrimination against migrants around the world. However, research on the forms of social stigma faced by the returned migrants in their home countries is absent. Based on in-depth inter-views with Bangladeshi migrants who returned from Italy during the COVID-19 pan-demic, this article explores their experiences of discrimination and social harassment in Bangladesh. Drawing on Link’s and Phelan’s (2001) conceptual framework of social stigma, this study finds that returned migrants experienced different forms of social harassment and stigmatization, including labeling, stereotyping, social separation, status loss, and discrimination. © 2021, ZRC SAZU, Založba ZRC. All rights reserved.
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The ongoing pandemic due to the novel SARS-CoV-2 disease (COVID-19) has exerted a great toll on human health. The SARS-CoV-2 is the third most pathogenic human CoV after SARS-CoV-1 and MERS-CoV, which is classified within the genus Betacoronavirus. Though the actual source of its origin and transmission is still unclear, genetic analysis has shown its very close similarity (~96%) with bat SARS-like CoV. SARS-CoV-2 is a spherically-icosahedral virus with a plus-sense single-strand RNA (~30 kb) genome defined into thirteen open reading frames, which encode 2 non-structural polyproteins, 4 structural proteins and 6 accessory proteins. Of its structural proteins the 'S1' subunit of spike (S) contains the cellular ACE-2 receptor binding domain (RBD) whereas the 'S2' subunit is required for cell membrane fusion. The membrane (M) protein participates in cell-fusion whereas envelope (E) is necessary for virion assembly and morphogenesis. The non-structural polyproteins (pp1a and pp1b) undergo proteolytic processing to produce a total of 16 small proteins, which are involved in mRNA synthesis and replication. Of the accessory proteins (3a, 6, 7a, 7b, 8 and 9b), few are known to modulate host-innate immunity. Interestingly, '3b' is absent in SARS-CoV-2 that significantly differentiates it from other human CoV. Detection of several novel mutations in '3a', '3b' and 'ORF8' proteins, notably in the 'S' RBD strongly suggest SARS-CoV-2 enhanced cell attachment and facilitated entry, its high infectivity and disease severity in humans. The recent emergence of highly contagious SARS-CoV-2 RBD variants in the United Kingdom (B.1.1.7 strain), South Africa (B.1.351 strain) and Brazil (P.1 strain), and their subsequent spread to other counties have raised serious concerns.
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Enteric or diarrheal viruses are primarily transmitted through contaminated water, and cause self-limiting gastroenteritis, diarrhea or jaundice. The human coronaviruses (CoV), including the severe acute respiratory syndrome CoV (SARS-CoV-1) and Middle-East respiratory syndrome CoV (MERS-CoV) which are inherently respiratory viruses, also manifest in gastrointestinal tract. Similarly, the novel SARS-CoV-2 also causes diarrhea and liver disorder as well as shed in stool in a proportion of SARS-CoV-2 diseases (COVID-19) patients. This is well supported by detections of SARS-CoV-2 RNA in gut specimen, rectal swabs and stool samples. Recent data on its occurrence in wastewater provides a warning on further spread of COVID-19 in resource-poor countries. Therefore, laboratory test of COVID-19 patients stool along with nasopharyngeal specimen as well as implementation of water surveillances could be very useful in protecting community health. well as implementation of water surveillances could be very useful in protecting community health.