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Background: Rapid antigen detection tests for SARS-CoV-2 infection could promote the clinical and public health policies to handle the COVID-19 pandemic. Rapid antigen detection and molecular approaches could expand entry to checking and initial evidence of issues and playing an essential role in public health managing choices that may decrease the transmission. Objectives: We evaluated the diagnostic accurateness of couple of rapid antigen recognition tests equated with the molecular-based assays for verdict of SARS-CoV-2 infection. Methods: The 100 nasopharyngeal swabs were verified by the SARS-CoV-2 RT-PCR kit as a gold standard for COVID-19 recognition. SARS‐CoV‐2 antigen (Ag) was evaluated in the nasopharyngeal swabs using iFlash and UNICELL-2019-nCoV antigen methods. The iFlash-2019-nCoV antigen assay, which is a chemiluminescent immunoassay (CLIA), was used to qualitatively determine the nucleocapsid protein antigen, where the other one was used to identify the nucleocapsid protein antigen by lateral flow immunofluorescent test. Results: Out of the 100 samples, 62% were positive by RT-PCR. Amongst 62 confirmed COVID-19 cases, 43 (69.4%) were positive by iFlash and 40 samples (64.5%) were positive by the UNICELL-2019-nCoV antigen assay. The specificity of both I Flash-2019-nCoV antigen assay & UNICELL-2019-nCoV antigen assay with RT-PCR were 100% and sensitivity were 69.35 and 64.52%, respectively. This sensitivity was augmented to 100% compared with the PCR with Ct-value of ≤25 and specificity of 80.28 and 84.51%, respectively. Conclusion: Antigen detection rapid diagnostic tests may be motivating in the initial stage of the infection when the viral load is elevated, and the risk of SARS‐CoV‐2 transmission be high. © 2020 The author (s).
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This research aims to provide perspicuous insights and solid overviews on research trends and themes within the context of tourism, leisure, and hospitality before and during the COVID-19 era. In doing so, a blend of bibliometric (evaluative and relational) measures was employed to systematically analyze and visually map a total of 22787 publications in the top fifteen academic journals based on Scopus CiteScore under the category of 'Tourism, Leisure, and Hospitality Management' from 2000 to May 2021. The results of evaluative methods indicate that there is a substantial growth in the number of publications in the selected journals over the given period, especially during the COVID-19 era. Several reputed institutions and nations significantly contributed to the targeted journals. Moreover, key tourism research themes and clusters were specified and an integrated overview on international research collaboration is confirmed. Theoretical and practical contributions are provided. Limitations and future research directions are outlined.
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Artificial intelligence (AI) has recently become the focus of academia and practitioners, reflecting the substantial evolution of scientific production in this area, particularly during the COVID-19 era. However, there is no known academic work exploring the major trends and the extant and emerging themes of scientific research production of AI leading journals. To this end, this study is to specify the research progress on AI among the top-tier journals by highlighting the development of its trends, topics, and key themes. This article employs an integrated bibliometric analysis using evaluative and relational metrics to analyze, map, and outline the key trends and themes of articles published in the leading AI academic journals, based on the latest CiteScore of Scopus-indexed journals between 2020 and 2021. The findings depict the major trends, conceptual and social structures, and key themes of AI leading journals' publications during the given period. This paper represents valuable implications for concerned scholars, research centers, higher education institutions, and various organizations within different domains. Limitations and directions for further research are outlined. © 2023 by the authors.
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Background: Remdesivir is a novel broad spectrum antiviral drug previously used to treat Ebola. It is a pro-drug nucleoside with antiviral activity that is opposed to SARS-CoV-2 and coronavirus. Aim: Current research was planned to evaluate and compare the potential ameliorative impact of the hematopoietic-stem-cell mobilized by the granulocyte colony-stimulating factor (G-CSF) versus BM-MSC on the effect of novel antiviral remdesivir on the kidney. Materials and Methods: Rats divided into four groups: control group, Remdesivir treated group (20 mg/kg/day IV on the first day followed by 10 mg/kg/day for 6 days), Remdesivir + BM-MSCs group (3x106 cells/ml of PKH26 labelled MSC) and Remedesivir+ Filgrastim group (70 μg/kg/day/5 days). At the end of the experiment, animals were anaesthetized and sacrificed. Both animal kidneys were excised for histological, immunohistochemistry, and electron microscopy studies. Biochemical and morphometric assessments had been performed. Results: Remdesivir caused distortion and degeneration of both the glomeruli and the renal tubules associated with Bowman's space widening. It greatly increased the deposition of collagen and enhanced the expression of caspase 3, IL-6, and TGF-β1. Ultrastructure changes were observed in the form of thickening of glomerular basement membrane, dilated basal plasma membrane infoldings of tubular epithelium and mitochondrial degeneration. Biochemically, decreased antioxidant enzymes, reduced glutathione (GSH), superoxide dismutase (SOD), and catalase (CAT) with increased serum urea and creatinine were also recorded. Both BM-MSCs and G-CSF improved histological structure and function of the kidney. Conclusion: Prescribing drugs such as remdesivir should be carried out with severe care. BM-MSCs and G-CSF are an efficient and ideal option to protect patients from irreversible kidney damage. © 2022. All rights served.
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SESSION TITLE: Uncommon Presentations and Complications of Chest Infections SESSION TYPE: Rapid Fire Case Reports PRESENTED ON: 10/18/2022 10:15 am - 11:10 am INTRODUCTION: The correlation between long-haul Coronavirus 2019 (COVID-19) and sleep disorders remains poorly understood. In this report, we present a case of newly diagnosed central sleep apnea (CSA) and symptoms starting after a COVID-19 infection as part of a long-haul COVID-19 presentation. CASE PRESENTATION: A 69-year-old male presented to a sleep medicine clinic for evaluation of hypersomnia. He had a history of hypertension and pulmonary embolism. He contracted COVID-19 eight months prior to his presentation. He was not hospitalized, but received Remdesivir and prednisone. He complained of long-haul COVID-19 symptoms since his infection which included headaches, fatigue, cough, dyspnea, anosmia, poor appetite, dysgeusia, and memory impairment. He also started noticing nocturnal apneic episodes that frightened him and woke him up from sleep. His symptoms started after his infection and were not present prior. He went to the emergency department for evaluation and no etiology was identified. He was then referred to sleep medicine for further evaluation. A home sleep apnea test was done and showed severe sleep apnea with an Apnea-Hypopnea Index of 35.7 events per hour. His sleep apnea was predominantly central with a central apnea index of 15.3 events per hour. Cardiac testing showed no evidence of ischemia or cardiomyopathy with an ejection fraction of 52%. A CT angiogram showed no evidence of PE. Brain MRI showed no acute abnormalities. He was started on positive airway pressure therapy but could not tolerate it so he was sent for a phrenic nerve stimulator implantation. DISCUSSION: Long-term sequelae of COVID-19 infection have been increasingly recognized. However, the etiology and pathophysiology is poorly understood (1). Symptoms of long-haul COVID-19 include fatigue, dyspnea, cognitive manifestations, thrombosis and sleep disturbances (1). Sleep apnea was found in some studies to be a risk factor for severe COVID-19 illness and worse outcomes (2). The relationship between COVID-19 and sleep apnea in the post-viral syndrome remains unknown. Only few case reports have found obstructive sleep apnea as a new diagnosis and a possible cause of fatigue in post COVID-19 infection (3). There is no report of a relationship between CSA and COVID-19 in the literature. It is hypothesized that long-COVID can lead to brainstem dysfunction and dysautonomia, which can affect the ventilatory control mechanisms and lead to an unstable respiration (4–6). Our patient's nocturnal symptoms started after his infection as part of long-haul COVID-19. While we cannot determine if CSA was a result of COVID-19 infection or not, it is important to evaluate for sleep disordered breathing (SDB) in patients presenting with long-COVID symptoms to better understand the association. CONCLUSIONS: More research is need to better understand the correlation between SDB and long-haul COVID-19. Reference #1: 1. Mehandru S, Merad M. Pathological sequelae of long-haul COVID. Nat Immunol. 2022 Feb;23(2):194–202. 2. Miller MA, Cappuccio FP. A systematic review of COVID-19 and obstructive sleep apnoea. Sleep Medicine Reviews. 2021 Feb;55:101382. Reference #2: 3. Koczulla AR, Stegemann A, Gloeckl R, Winterkamp S, Sczepanski B, Boeselt T, et al. Newly detected rapid eye movement associated sleep apnea after coronavirus disease 2019 as a possible cause for chronic fatigue: two case reports. J Med Case Reports. 2021 Dec;15(1):211. 4. Barizien N, Le Guen M, Russel S, Touche P, Huang F, Vallée A. Clinical characterization of dysautonomia in long COVID-19 patients. Sci Rep. 2021 Dec;11(1):14042. Reference #3: 5. Yong SJ. Persistent Brainstem Dysfunction in Long-COVID: A Hypothesis. ACS Chem Neurosci. 2021 Feb 17;12(4):573–80. 6. White DP. Pathogenesis of Obstructive and Central Sleep Apnea. Am J Respir Crit Care Med. 2005 Dec;172(11):1363–70. DISCLOSURES: No relevant relationships by Amer Als ekh Mousa No relevant relationships by University of Arizona at Banne Institute No relevant relationships by Joyce Lee-Iannotti No relevant relationships by Anas Rihawi No relevant relationships by Amr Salem No relevant relationships by Mohanad Soliman No relevant relationships by Kristen Trimble
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A major challenge in the online delivery of engineering courses is the implementation of the lab component. With most campuses being closed due to COVID-19 pandemic, many of the engineering courses’ labs are either cancelled, converted to a totally virtual, or remote lab setting. The paper proposes a novel hybrid virtual-physical laboratories for a control theory course that is delivered online. The virtual labs are implemented using a 3D animated digital twin of a motor. The physical labs are implemented using a low-cost take-home lab kit that was sent to students. The use of the proposed hybrid approach achieves the benefits of both virtual labs and physical labs. Specifically, the virtual labs form a sandbox where the student can safely experiment and try new designs without worrying about damaging equipment. This will also form a gentle introduction to the utilization of the physical labs. The physical labs allow the student to see the actual control system components, and hardware troubleshooting. Both the proposed virtual and physical labs can be performed by the student from home at any convenient time;and the lab is always available to the student through the whole semester. The hybrid virtual-physical labs were utilized in the fall of 2020 within an introductory control theory course offered to a third-year undergraduate students at McMaster University. Based on the students’ feedback, the designed labs were effective within the online course delivery and they provided deep insights and understanding of the concepts that were taught in the class. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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INTRODUCTION: Although primarily a respiratory disorder, the coronavirus pandemic has paralyzed almost all aspects of healthcare delivery. Neurosurgeons provide critical care and their role in this pandemic is necessary and yet evolving. METHODS: Through professional registries and internet resources, we surveyed neurosurgeons from around the world. We looked at the national burden of illness, perception of preparedness, cancellation of clinics, surgeries and cessation of research and educational activities. Chisquare, Fisher's exact tests, and multivariate logistic regression model were used to analyze variables. RESULTS:Our survey was completed on April 3, 2020, and was wellreceived (661 completed, 60.7% response rate, 96 nations). Neurosurgeons in affluent nations still lacked adequate resources to combat this pandemic primarily due to lack of preparedness and insufficient medical equipment. The challenges to lower-income nations were similar but also included knowledge dissemination and inadequate resources. Hospital preparedness was central to effective healthcare delivery but also influenced the cancellation of surgeries and clinics. The impact on education, conferences and research was also significant. CONCLUSION: Neurosurgical disorders are significant casualties of the COVID-19 pandemic. Reduction of services, lack of preparedness, inadequate education, insufficient supplies and resources are important contributors. Improved preparedness requires careful planning, real-time surveillance and allocation of resources. This is more critical in poorer nations.
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This paper proposes a deep neural networks model to predict COVID-19 patients automatically based on chest X-ray images. The model is trained using imbalance dataset with a new hybrid balancing technique proposed to solve this problem. The Deep Convolutional Neural VGG-16 is trained and utilized to extract features from a given chest X-ray image after some preprocessing steps. To overcome the data imbalance issue, a new hybrid Class Weights-SMOTE is applied to the extracted feature vector and compared with traditional balancing techniques. The feature vector is then classified utilizing a Fine-tuning VGG-16. The model provides a multi-classification for the input x-ray images into COVID-19, Normal, and Pneumonia. Comparison with existing methods shows that the proposed model achieves a superior classification accuracy and outperforms all other models, providing 98% accurate prediction and improving the model's performance on minority-class samples to achieve high accuracy 100%. The findings of this study could be useful for diagnosing COVID-19 from chest X-ray images. © 2022 Little Lion Scientific. All rights reserved.
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One of the unique comedic expressions that evolved during the first wave of the Covid-19 pandemic in Egypt is a Facebook page called "Coronavirus". What is exceptional about the memes published on this page is that the author adopts the persona of the coronavirus to explore issues of the pandemic in the Egyptian context. Moreover, followers of the page fully participate in this make-believe scenario that the author has established. In addition, most of the posts mock the illogical actions undertaken by both the public and the state. Memes have been created, and shared, by Facebook users, not only as comic relief but also as a means of documenting events during the pandemic. This article aims to analyse different memes created by the "Coronavirus" Facebook page in the Egyptian context. The discussion is based on content and visual analysis. Memes were contextualised in relation to real incidents or decisions criticised by the author of the page, or the meme creator. The discussion also examines the different styles and types of humour employed by the author of the page to deliver his/her message in a comic way.
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Background: The coronavirus disease of 2019 (COVID-19) has challenged and disrupted medical education worldwide. Objective structured clinical examination (OSCE) is one of the types of assessment for undergraduate medical students that has been conducted for first-year medical students in the College of Medicine. Peer student training on participating in OSCE has been conducted prior to the pandemic. The aim of this study was to assess medical students’ perception of online virtual peer student video training on participating in the OSCE. Methods: Medical student’s council team prepared a video demonstration on the steps of participating in OSCE. In October 2020, the video was provided online for first-year medical students (n = 302) prior to their OSCE. After the completion of the OSCE exam, a 10 – item questionnaire was distributed on the students’ perception on the impact of the peer student video demonstration on students’ orientation about the OSCE. The questionnaire was sent by Google Forms. The results were expressed as a percentage on a Likert scale. Results: About 74.17% (n = 224) of students responded to the online questionnaire. More than half of the students (n = 126, 56%) found the steps of conduction of the OSCE well explained, provided the sufficient orientation (n = 121, 54%), and found the video stimulating (n = 122, 54%). In addition, the majority of students (n = 160, 71%) learned and understood the steps of the OSCE and 152 students (68%) found that the video helped introducing them to the concept of OSCE. Almost half the students found that the video helped lowering the stress level before the OSCE (n = 91, 41%), eased the steps of the OSCE (n = 113, 50%), and found that the materials were well prepared and explained (n = 126, 56%). Conclusions: The virtual video demonstration of the OSCE during the COVID-19 pandemic had an overall positive perception from first-year medical students. However, peer student’s orientation on the OSCE will continue after the pandemic. Further supports for first-year medical students are needed during the pandemic. © 2021 Journal of Nature and Science of Medicine.
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Background: The COVID-19 pandemic has challenged medical education and resulted in a rapid and unexpected global shift toward online education. The study presents the experience of the College of Medicine of King Saud University in delivering a comprehensive internal medicine course for final-year medical students, which includes the implementation of novel methods of assessment. Methods: A 2-week revision of the internal medicine course was conducted for 70 pregraduation medical students. Lectures and focused case-based tutorials were conducted online. Novel assessment methods included brief written essays summarizing the tutorials, open-book short-answer question (SAQ) examination, and a virtual standardized oral examination (vSOE). A questionnaire was sent to the students (n = 70) on the contents of the course, clarity of objectives, duration, and online platform. Results: The response rate was 99.3%. Students scored higher in the SAQs compared with traditional multiple-choice tests (mean score: 92.3% vs. 69.8%). The vSOE was efficient, and grades were comparable to traditional objective structured clinical examination. The majority of students (93%) reported the scientific content as good or excellent, whereas approximately 30% found the course goals lacked a clear description. The majority (76%) found the course length appropriate, and 94% reported the online platform installation and operation easy or very easy. Conclusions: The comprehensive online internal medicine course was successfully delivered to pregraduation students. Innovative online examination methods can be a reasonable alternative in the case of lockdown. This modality of teaching and assessment was considered useful and met the expectations of students. © 2021 Journal of Nature and Science of Medicine.
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The COVID-19 pandemic has a massive influence upon the working environments of scholars globally. In this paper, we investigate how the changing conditions under which individuals work because of various restrictions have influenced the productivity of scholars based on a global sample of 1073 scholars from 83 countries. The findings show that tourism and non-tourism scholars react in similar ways to the changes in the social and physical environment of the pandemic with one exception: teleworking stressors positively affected all scholars' perceived safety and did not impact tourism scholarly productivity. Tourism and non-tourism researchers' productivity had also a positive relationship with social isolation and perceived safety. Additionally, perceived safety mediated the relationship between the psychological factors and scientific production. Moreover, perceived risk moderated the link between perceived safety and scholarly productivity. This paper contributes to tourism studies by looking at the psychological factors that influence tourism researchers' productivity during COVID-19 and comparing their responses to non-tourism scholars.
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Coronavirus disease 2019 (COVID-19) was declared a pandemic by the World Health Organization on March 11, 2020. In response to the pandemic, the Kingdom of Saudi Arabia’s Ministry of Education announced the suspension of educational activities. The pandemic has challenged universities worldwide to provide education virtually as an immediate response to prolonged lockdown periods. This article highlights the College of Medicine’s experience at King Saud University, Saudi Arabia, in managing undergraduate medical education in response to the pandemic situation. We describe the process of implementing the curriculum’s delivery online during the lockdown and the decisions regarding the final assessment for all years. Furthermore, we highlight the steps taken to prepare for the new academic year 2020-2021 as a blended learning approach in light of the COVID-19 situation. © 2021 Journal of Nature and Science of Medicine.
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Although the COVID-19 pandemic continues to expand, researchers around the world are working to understand, diminish, and curtail its spread. The primary fields of research include investigating transmission of COVID-19, promoting its identification, designing potential vaccines and therapies, and recognizing the pandemic’s socio-economic impacts. Deep Learning (DL), which uses either deep learning architectures or hierarchical approaches to learning, is developed a machine learning class since 2006. The exponential growth and availability of data and groundbreaking developments in hardware technology have led to the rise of new distributed and learning studies. Throughout this chapter, we discuss how deep learning can contribute to these goals by stepping up ongoing research activities, improving the efficiency and speed of existing methods, and proposing original lines of research. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.