ABSTRACT
Cytokine storm has been reported in a number of patients with severe acute respiratory syndrome - corona virus-2 (SARS-CoV-2) due to elevated level of pro-inflammatory cytokine such as interleukin-6 and interleukin-17. The aim of this study was to evaluate the level of interleukin-6 and interleukin-17 among patients with coronavirus disease 2019 (COVID-19). This case control study included 78 confirmed cases with COVID-19 (58 males and 30 females;their age ranged between 15-83 years old) and compared with 10 apparently healthy individuals (8 males and 2 females), were admitted to Epidemiological Monitoring Unit, Emergency Department in Baqubah Teaching Hospital during the period from 1st of October to the 1st of December 2020. Nasopharyngeal swabs were collected from all patients who were included in this study and directly placed in tube contain 2ml of viral transport medium then stored at -20 °C until the time of RNA extraction and real time polymerase chain reaction processing as well as blood sample were collected from patients then the sera were separated, labelled and sored until the time of test for quantitative detection of interleukin-6 and interleukin-17. There is significant difference in level of interleukin-6 and interleukin-17 between patients and control using ELISA assay, 0.0398 and 0,0046 respectively, and the mean serum level of IL-6 were 136.25±12.55 µg and 72.93±15.02 µg respectively and IL-17 was 37.87±4.83 µg and 13.48±2.23 µg respectively. Most infections were noticed among males and age group 15-35 years old. © 2023 Author(s).
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In recent decades, epidemic and pandemic illnesses have grown prevalent and are a regular source of concern throughout the world. The extent to which the globe has been affected by the COVID-19 epidemic is well documented. Smart technology is now widely used in medical applications, with the automated detection of status and feelings becoming a significant study area. As a result, a variety of studies have begun to focus on the automated detection of symptoms in individuals infected with a pandemic or epidemic disease by studying their body language. The recognition and interpretation of arm and leg motions, facial recognition, and body postures is still a developing field, and there is a dearth of comprehensive studies that might aid in illness diagnosis utilizing artificial intelligence techniques and technologies. This literature review is a meta review of past papers that utilized AI for body language classification through full-body tracking or facial expressions detection for various tasks such as fall detection and COVID-19 detection, it looks at different methods proposed by each paper, their significance and their results.
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PURPOSE: This paper reviews the changes in the relationships between Small and Medium Size Enterprises (SMEs) in the tourism industry and sustainability dimensions (social, economic and environmental) following the COVID-19 crisis. It offers some reflections on changes in the relationships between SMEs’ sustainable development in the tourism industry and sustainability. DESIGN/METHODOLOGY/APPROACH: The paper describes how COVID-19 impacted several sectors in tourism (hotels, tour operators, restaurants) and reviews how the COVID-19 crisis is likely to negatively impact sustainable development efforts for SMEs in this sector. FINDINGS: This exploratory review of SMEs’ sustainability challenges reveals that it might be harder to maintain or adopt any sustainable practices, whether social, economic or environmental, under the financial stress and sharp decline of revenue resulting from the COVID-19 crisis. ORIGINAL/VALUE OF THE PAPER: The paper is the first to investigate how the COVID-19 crisis might impact SMEs’ sustainable development in various tourism sectors. RESEARCH LIMITATIONS/IMPLICATIONS: This review paper presents a theoretical outline of the crisis and opens up promising research opportunities for enhancing our understanding of the changing relationships between sustainability and SMEs in the tourism industry. PRACTICAL IMPLICATIONS: The paper fills the current gap in the literature in sustainable tourism challenges arising from the COVID-19 crisis, and demonstrates the importance of governments and policy-makers supporting SME survival and the Sustainable Development Goals (SDGs). We hope that this paper will become inspirational for academic researchers, entrepreneurs, and policy-makers who are involved in the sustainable development discourse. © 2022 by all the authors of the article above and 2022 World Association for Sustainable Development (WASD).
ABSTRACT
Given the current COVID-19 pandemic, medical research today focuses on epidemic diseases. Innovative technology is incorporated in most medical applications, emphasizing the automatic recognition of physical and emotional states. Most research is concerned with the automatic identification of symptoms displayed by patients through analyzing their body language. The development of technologies for recognizing and interpreting arm and leg gestures, facial features, and body postures is still in its early stage. More extensive research is needed using artificial intelligence (AI) techniques in disease detection. This paper presents a comprehensive survey of the research performed on body language processing. Upon defining and explaining the different types of body language, we justify the use of automatic recognition and its application in healthcare. We briefly describe the automatic recognition framework using AI to recognize various body language elements and discuss automatic gesture recognition approaches that help better identify the external symptoms of epidemic and pandemic diseases. From this study, we found that since there are studies that have proven that the body has a language called body language, it has proven that language can be analyzed and understood by machine learning (ML). Since diseases also show clear and different symptoms in the body, the body language here will be affected and have special features related to a particular disease. From this examination, we discovered that it is possible to specialize the features and language changes of each disease in the body. Hence, ML can understand and detect diseases such as pandemic and epidemic diseases and others.
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Antibodies play a crucial role in the immune response, in fighting off pathogens as well as helping create strong immunological memory. Antibody-dependent enhancement (ADE) occurs when non-neutralising antibodies recognise and bind to a pathogen, but are unable to prevent infection, and is widely known and is reported as occurring in infection caused by several viruses. This narrative review explores the ADE phenomenon, its occurrence in viral infections and evaluates its role in infection by SARS-CoV-2 virus, which causes coronavirus disease 2019 (COVID-19). As of yet, there is no clear evidence of ADE in SARS-CoV-2, though this area is still subject to further study.
Subject(s)
COVID-19 , SARS-CoV-2 , Antibodies, Neutralizing , Antibodies, Viral/therapeutic use , Antibody-Dependent Enhancement , HumansABSTRACT
The coronavirus disease 2019 outbreak has brought the world to a standstill, especially the education sector. Globally, it has claimed over two million lives, with over 100 million people infected, forcing schools to close down. This has reignited the importance of online teaching and learning for preservice teachers who comprise the next frontiers in providing online education to their future students. However, studies on online learning [OL] success among preservice teachers in developing countries, such as Ghana, remain scarce. Accordingly, this study mainly aimed to assess the predictors of OL success among preservice teachers in Ghana. Bandura’s social cognitive theory guided the study;in total, 526 preservice teachers were recruited from four colleges of education. Although the teachers were ambivalent regarding the success of OL, significant differences were found between the following demographics: gender, specialization, marital status, the preferred mode of learning, and the place of residence. Moreover, the study discussed the need for intensive information and communications technology education among preservice teachers, particularly women, developing their confidence in computer skills, and other recommendations. © Copyright © 2021 Nketsia, Opoku, Mohammed, Kumi, Twum and Kyere.
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Coronavirus pandemic, is a progressing worldwide pandemic of coronavirus disease 2019 (COVID-19), brought about by sever acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The episode was first distinguished in Wuhan, China, in December 2019. The World Health Organization announced a Public Health Emergency of International Concern on 30 January 2020, and a pandemic on 11 March. Scientists around the world are working to establish an effective treatment against SARS-CoV-2 to control the spread of this pandemic. In this review, we summarized the potential therapeutic strategies for treatment of COVID-19 and dividing the treatments to several categories including antiviral drugs which act on decreasing the viral load inside the body of patients, immunotherapy and immunomodulatory which relive the inflammatory process of viral infection.
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The whole planet today is having to fight COVID-19 with big obstacles. The COVID-19 influenced several countries around the world between December 2019 and the present day. Many organisations and scientists seek to find a vaccine and to minimize the spread of COVID-19. Artificial Intelligence is one technology that can successfully address this virus (AI). In the case of other pathogens, artificial intelligence performed very well and could help us cope with the virus COVID-19, too. It is the imagination and the information of the people who use it which will help to overcome this dilemma. In some previous instances AI played a major role in virus prevention and identification. We have an ability to detect certain aspects of the AI because of the COVID-19 crisis. Machine learning that an AI subclass is used to identify patterns and to plan valuable knowledge based on recorded data sets. At the point where used entirely, AI can exceed human efforts by speed and differentiate designs from knowledge previously ignored. However many correct and appropriate data are needed for effective implementation of AI systems. This paper discusses the AI's role in COVID-19 prevention and detection and examines numerous technological aspects of AI. This paper would also clarify where AI will contribute with likely solutions to stop the spread of COVID-19. © 2021 IEEE.
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Objective: This study aims to determine the prevalence of stress and depression among pharmacy students, evaluate their health related quality of life (HRQoL) in Malaysia. Methods: A cross-sectional study design was conducted among pharmacy students at eight universities from March to May 2020 across Malaysia. Instruments adopted in the survey included perceived stress scale 4 (PSS-4) for stress, patient health questionnaire-9 (PHQ-9) for depression and WHOQOL-BREF for health related quality of life. Results: A total of 441 students participated in the study. The overall PSS-4 score mean was 7.30 and the differences in PHQ-9 scores mean between public and private universities were not significant. A positive correlation was observed between total PSS-4 scores and PHQ-9 scores. Only 24.5% of pharmacy students reported a good quality of life, with a median score of 96.00. A Significant negative correlation was found between stress and depression against the quality of life. Conclusions: Stress and depression play a significant role in deteriorating the quality of life of pharmacy students. This highlighted the importance of future research in developing useful interventions to improve the quality of life of university students, especially students from the medical and health science fields.
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Nanoparticles are small particles sized 1-100 nm, which have a large surface-to-volume ratio, allowing efficient adsorption of drugs, proteins, and other chemical compounds. Consequently, functionalized nanoparticles have potential diagnostic and therapeutic applications. A variety of nanoparticles have been studied, including those constructed from inorganic materials, biopolymers, and lipids. In this review, we focus on recent work targeting the severe acute respiratory syndrome coronavirus 2 virus that causes coronavirus disease (COVID-19). Understanding the interactions between coronavirus-specific proteins (such as the spike protein and its host cell receptor angiotensin-converting enzyme 2) with different nanoparticles paves the way to the development of new therapeutics and diagnostics that are urgently needed for the fight against COVID-19, and indeed for related future viral threats that may emerge.
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In this study, density functional theory (DFT) and docking calculations were systematically performed to study the non-competitive interaction between Hydroxychloroquine (HCQ) and azithromycin (AZTH). The calculated changes in Gibbs free energy and enthalpy (at 310 K) were positive, indicating the non-spontaneous formation of HCQ-AZTH specifically in water media. Docking calculation confirmed the obtained DFT result as evident from the different binding sites of both drugs to the SARS-CoV-2 main protease and human angiotensin-converting enzyme 2 (ACE2) proteins. The HCQ-AZTH structure revealed enhanced electrochemical properties, suggesting the synergy between HCQ and AZTH without affecting their therapeutic efficacy against SARS-CoV-2.
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Summary: Due to the threat of COVID-19, universities across Malaysia are facing decisions about how to continue teaching and learning whilst keeping their faculty, staff, and students safe from a public health emergency that is fast moving and not well understood. Monash University Malaysia is no exception and have opted to cancel all face-to-face classes, including laboratory and other learning experiences, and have mandated that faculty move their units online to help prevent the spread of the virus that causes COVID-19. Approaches as well as the remedial measures undertaken by the School of Pharmacy, Monash University Malaysia, with regards to teaching and learning (T&L) activities during and beyond the execution of the Movement Control Order (MCO) in Malaysia are discussed below.
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The elevated inflammatory cytokines suggest that a cytokine storm, also known as cytokine release syndrome (CRS), may play a major role in the pathology of pandemic Coronavirus Disease (COVID-19) leading to cause Acute respiratory distress syndrome (ARDS) and multiple organ dysfunction then death. However, there was a controversial efficacy of corticosteroids in the treatment of COVID-19 induced cytokine release syndrome (CRS). Novel therapies to treat COVID-19-induced CRS become urgent needed. One of the most common cytokine that showed to be critical in the COVID-19 is the IL-6 and this article discuss the pathogenesis of this cytokine in severe acute respiratory syndrome (SARS). Also, this article proposes to utilize interleukin-6 (IL-6) blockade and potential therapeutic effect of IFN-P to manage COVID-19-induced CRS and discuss several factors that should be taken into consideration for its clinical application.
ABSTRACT
Due to the threat of COVID-19, universities across Malaysia are facing decisions about how to continue teaching and learning whilst keeping their faculty, staff, and students safe from a public health emergency that is fast moving and not well understood. Monash University Malaysia is no exception and have opted to cancel all face-to-face classes, including laboratory and other learning experiences, and have mandated that faculty move their units online to help prevent the spread of the virus that causes COVID-19. Approaches as well as the remedial measures undertaken by the School of Pharmacy, Monash University Malaysia, with regards to teaching and learning (T&L) activities during and beyond the execution of the Movement Control Order (MCO) in Malaysia are discussed below.