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Ghena A Kasasbeh

Bio: Ghena A Kasasbeh is an academic researcher from Yarmouk University. The author has contributed to research in topics: Coronavirus & Middle East respiratory syndrome. The author has an hindex of 1, co-authored 2 publications receiving 380 citations.

Papers
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TL;DR: The scientific community raced to uncover the origin of the virus, understand the pathogenesis of the disease, develop treatment options, define the risk factors, and work on vaccine development.
Abstract: In December 2019, a cluster of fatal pneumonia cases presented in Wuhan, China. They were caused by a previously unknown coronavirus. All patients had been associated with the Wuhan Wholefood market, where seafood and live animals are sold. The virus spread rapidly and public health authorities in China initiated a containment effort. However, by that time, travelers had carried the virus to many countries, sparking memories of the previous coronavirus epidemics, severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), and causing widespread media attention and panic. Based on clinical criteria and available serological and molecular information, the new disease was called coronavirus disease of 2019 (COVID-19), and the novel coronavirus was called SARS Coronavirus-2 (SARS-CoV-2), emphasizing its close relationship to the 2002 SARS virus (SARS-CoV). The scientific community raced to uncover the origin of the virus, understand the pathogenesis of the disease, develop treatment options, define the risk factors, and work on vaccine development. Here we present a summary of current knowledge regarding the novel coronavirus and the disease it causes.

528 citations

Journal ArticleDOI
TL;DR: Factors that could affect the susceptibility of children to the novel coronavirus and the reasons behind the relative protection of children and infants are reviewed.
Abstract: AIM: The 2019 coronavirus disease (COVID-19) has spread worldwide and the number of cases continues to rise exponentially. Epidemiologic reports indicate that severity of illness increases with age. However, the reasons behind the relative protection of children and infants are unclear. Whether the rationale is host-related or virus-dependent is important to determine since the latter could change with viral mutations. We review factors that could affect the susceptibility of children to the novel coronavirus. METHODS: We search publications indexed on PUBMED. RESULTS: Descriptions of the pathophysiology of current and previous coronavirus infections suggest several viral targets and immunomodulatory pathways affecting the severity of illness. There is limited evidence to suggest age-variability of viral cell receptors and transmembrane co-factors required for coronavirus entry and replication. However, the ensuing cytokine storm and the effect of higher melatonin in children are age-dependent and could explain decreased disease variability in children. CONCLUSION: We believe that current evidence suggests host factors can play a role in disease severity in children and thus may remain protective despite potential virus mutation in the future. However, we recognize and discuss avenues of future research that can further illuminate the reasons children are protected from severe COVID-19 illness.

4 citations


Cited by
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Journal ArticleDOI
TL;DR: The current knowledge about this disease is reviewed and the potential explanation of the different symptomatology between children and adults is considered.

1,390 citations

Journal ArticleDOI
TL;DR: This review provides a complete review related to structure, origin, and how the body responds to this virus infection and explains the possibility of an immune system over-reaction or cytokine storm.
Abstract: Background and aim As a result of its rapid spread in various countries around the world, on March 11, 2020, WHO issued an announcement of the change in coronavirus disease 2019 status from epidemic to pandemic disease. The virus that causes this disease is indicated originating from animals traded in a live animal market in Wuhan, China. Severe Acute Respiratory Syndrome Coronavirus 2 can attack lung cells because there are many conserved receptor entries, namely Angiotensin Converting Enzyme-2. The presence of this virus in host cells will initiate various protective responses leading to pneumonia and Acute Respiratory Distress Syndrome. This review aimed to provide an overview related to this virus and examine the body’s responses and possible therapies. Method We searched PubMed databases for Severe Acute Respiratory Syndrome Coronavirus-2, Middle East respiratory syndrome-related coronavirus and Severe Acute Respiratory Syndrome Coronavirus. Full texts were retrieved, analyzed and developed into an easy-to-understand review. Results We provide a complete review related to structure, origin, and how the body responds to this virus infection and explain the possibility of an immune system over-reaction or cytokine storm. We also include an explanation of how this virus creates modes of avoidance to evade immune system attacks. We further explain the therapeutic approaches that can be taken in the treatment and prevention of this viral infection. Conclusion In summary, based on the structural and immune-evasion system of coronavirus, we suggest several approaches to treat the disease.

745 citations

Journal ArticleDOI
01 Apr 2020-Symmetry
TL;DR: The main idea is to collect all the possible images for COVID-19 that exists until the writing of this research and use the GAN network to generate more images to help in the detection of this virus from the available X-rays images with the highest accuracy possible.
Abstract: The coronavirus (COVID-19) pandemic is putting healthcare systems across the world under unprecedented and increasing pressure according to the World Health Organization (WHO). With the advances in computer algorithms and especially Artificial Intelligence, the detection of this type of virus in the early stages will help in fast recovery and help in releasing the pressure off healthcare systems. In this paper, a GAN with deep transfer learning for coronavirus detection in chest X-ray images is presented. The lack of datasets for COVID-19 especially in chest X-rays images is the main motivation of this scientific study. The main idea is to collect all the possible images for COVID-19 that exists until the writing of this research and use the GAN network to generate more images to help in the detection of this virus from the available X-rays images with the highest accuracy possible. The dataset used in this research was collected from different sources and it is available for researchers to download and use it. The number of images in the collected dataset is 307 images for four different types of classes. The classes are the COVID-19, normal, pneumonia bacterial, and pneumonia virus. Three deep transfer models are selected in this research for investigation. The models are the Alexnet, Googlenet, and Restnet18. Those models are selected for investigation through this research as it contains a small number of layers on their architectures, this will result in reducing the complexity, the consumed memory and the execution time for the proposed model. Three case scenarios are tested through the paper, the first scenario includes four classes from the dataset, while the second scenario includes 3 classes and the third scenario includes two classes. All the scenarios include the COVID-19 class as it is the main target of this research to be detected. In the first scenario, the Googlenet is selected to be the main deep transfer model as it achieves 80.6% in testing accuracy. In the second scenario, the Alexnet is selected to be the main deep transfer model as it achieves 85.2% in testing accuracy, while in the third scenario which includes two classes (COVID-19, and normal), Googlenet is selected to be the main deep transfer model as it achieves 100% in testing accuracy and 99.9% in the validation accuracy. All the performance measurement strengthens the obtained results through the research.

391 citations

Journal ArticleDOI
TL;DR: The current knowledge of COVID-19 in pregnancy and signpost areas for further research are explored to minimise its impact for women and their children.
Abstract: There are many unknowns for pregnant women during the coronavirus disease 2019 (COVID-19) pandemic. Clinical experience of pregnancies complicated with infection by other coronaviruses e.g., Severe Acute Respiratory Syndrome (SARS) and Middle Eastern Respiratory Syndrome, has led to pregnant woman being considered potentially vulnerable to severe SARS-CoV-2 infection. Physiological changes during pregnancy have a significant impact on the immune system, respiratory system, cardiovascular function, and coagulation. These may have positive or negative effects on COVID-19 disease progression. The impact of SARS-CoV-2 in pregnancy remains to be determined, and a concerted, global effort is required to determine the effects on implantation, fetal growth and development, labor, and neonatal health. Asymptomatic infection presents a further challenge regarding service provision, prevention, and management. Besides the direct impacts of the disease, a plethora of indirect consequences of the pandemic adversely affect maternal health, including reduced access to reproductive health services, increased mental health strain, and increased socioeconomic deprivation. In this review, we explore the current knowledge of COVID-19 in pregnancy and highlight areas for further research to minimize its impact for women and their children.

376 citations

Journal ArticleDOI
TL;DR: Obesity, family members at home, watching TV during mealtime, country of residence, and maternal education were diversely correlated with adequate nutrition during COVID-19 confinement, suggesting that public health authorities reshape future policies on their nutritional recommendations, in preparation for future pandemics.
Abstract: Confinement due to the COVID-19 pandemic can influence dietary profiles, especially those of adolescents, who are highly susceptible to acquiring bad eating habits Adolescents’ poor dietary habits increase their subsequent risk of degenerative diseases such as obesity, diabetes, cardiovascular pathologies, etc Our aim was to study nutritional modifications during COVID-19 confinement in adolescents aged 10 to 19 years, compare them with their usual diet and dietary guidelines, and identify variables that may have influenced changes Data were collected by an anonymous online questionnaire on food intake among 820 adolescents from Spain, Italy, Brazil, Colombia, and Chile The results show that COVID-19 confinement did influence their dietary habits In particular, we recorded modified consumption of fried food, sweet food, legumes, vegetables, and fruits Moreover, gender, family members at home, watching TV during mealtime, country of residence, and maternal education were diversely correlated with adequate nutrition during COVID-19 confinement Understanding the adolescents’ nutrition behavior during COVID-19 lockdown will help public health authorities reshape future policies on their nutritional recommendations, in preparation for future pandemics

305 citations