• Journal of Ginseng Research
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• v.46 no.2
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• pp.183-187
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• 2022

The current Covid-19 pandemic has changed the entire world and bought so many unprecedented challenges to the scientific community. More than 5 million people died due to the SARS-COV-2 outbreak. For many thousands of years, ginseng, the traditional herb has been used for various infectious diseases by traditional healers. Ginseng showed promising antiviral effects by modulating both natural and acquired immunity. Ginseng might be used as a potential therapeutic agent to prevent SARS-CoV-2 infection along with the vaccine. In this current review, we offer an alternative approach for SARS-COV-2 prevention during this unprecedented pandemic.

• Korean Journal of Radiology
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• v.21 no.4
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• pp.505-508
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• 2020

The epidemic of 2019 novel coronavirus, later named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is still gradually spreading worldwide. The nucleic acid test or genetic sequencing serves as the gold standard method for confirmation of infection, yet several recent studies have reported false-negative results of real-time reverse-transcriptase polymerase chain reaction (rRT-PCR). Here, we report two representative false-negative cases and discuss the supplementary role of clinical data with rRT-PCR, including laboratory examination results and computed tomography features. Coinfection with SARS-COV-2 and other viruses has been discussed as well.

• Clinics in Shoulder and Elbow
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• v.25 no.3
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• pp.236-239
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• 2022

The objective of this article is to describe intraoperative pulmonary embolism during shoulder arthroscopy in a patient with previous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Further, we describe how the pandemic has influenced the population by increasing the rate of embolisms. Awareness of such cases will help to increase knowledge regarding SARS-Cov-2 and to determine if such patients should receive routine antithrombotic prophylaxis.

• Journal of Microbiology and Biotechnology
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• v.32 no.9
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• pp.1098-1102
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• 2022

The placenta is a captivating multifunctional organ of fetal origin and plays an essential role during pregnancy by intimately connecting mother and baby. This study explicates placental pathology and information about 25 placentas collected from the mothers infected with novel coronavirus (SARS-COV-2). So far, congenital transmission of SARS-CoV-2 seems to be remarkably uncommon in spite of many cases of COVID-19 during pregnancy. Out of the 25 placental tissue samples collected, none has shown gene expression of SARS-CoV-2 when confirmed by RT-PCR. At the same time, nasal and throat swab samples collected from newborns of SARS-CoV-2-positive mothers correspondingly tested negative by RT-PCR. The shielding properties of placental barriers against viral infections from mothers to newborns remains a mystery. Major histopathological findings have been recorded as choriodecidual tissue with necrosis, intramural fibrin deposition, chorionic villi with fibrosis, and calcification. Moreover, although recent findings are insufficient to prove direct placental transmission of COVID-19, the abundance of angiotensin-converting enzymes-2 (ACE-2) on the placental surface could potentially contribute to unpleasant outcomes during pregnancy as SARS-CoV-2 gains access to human cells via ACE-2. Finally, the significance of these findings is vague and needs further study.

• Journal of applied mathematics & informatics
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• v.42 no.4
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• pp.945-968
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• 2024

This study focuses on SIR model for SARS-CoV-2. The SIR model classifies a population into three compartments: susceptible S(t), infected I(t), and recovered R(t) individuals. The SARS-CoV-2 model considers various factors, such as immigration, birth rate, death rate, contact rate, recovery rate, and interactions between infected and healthy individuals to explore their impact on population dynamics during the pandemic. To analyze this model, we employed two powerful semi-analytical methods: the Laplace Adomian decomposition method (LADM) and the differential transform method (DTM). Both techniques demonstrated their efficacy by providing highly accurate approximate solutions with minimal iterations. Furthermore, to gain a comprehensive understanding of the system behavior, we conducted a comparison with the numerical simulations. This comparative analysis enabled us to validate the results and to gain valuable understanding of the responses of SARS-CoV-2 model across different scenarios.

• IMMUNE NETWORK
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• v.24 no.4
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• pp.28.1-28.13
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• 2024

Vaccines are the most effective intervention currently available, offering protective immunity against targeted pathogens. The emergence of the coronavirus disease 2019 pandemic has prompted rapid development and deployment of lipid nanoparticle encapsulated, mRNA-based vaccines. While these vaccines have demonstrated remarkable immunogenicity, concerns persist regarding their ability to confer durable protective immunity to continuously evolving severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. This review focuses on human B cell responses induced by SARS-CoV-2 mRNA vaccination, with particular emphasis on the crucial role of germinal center reactions in shaping enduring protective immunity. Additionally, we explored observations of immunological imprinting and dynamics of recalled pre-existing immunity following variants of concern-based booster vaccination. Insights from this review contribute to comprehensive understanding B cell responses to mRNA vaccination in humans, thereby refining vaccination strategies for optimal and sustained protection against evolving coronavirus variants.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.3
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• pp.135-161
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• 2023

This study analyzed the research trends of COVID-19 research papers published in medical journals of Korea. Data were collected from 25 MEDLINE journals in 'Medicine and Pharmacy' studies and a total of 800 were selected. As a result of the study, authors from domestic affiliations made up 76.96% of the total, and the proportion of authors from foreign institutions decreased without significant change. The authors' majors were 'Internal Medicine' (32.85%), 'Preventive Medicine/Occupational and Environmental Medicine' (16.23%), 'Radiology' (5.74%), and 'Pediatrics' (5.50%), and 435 (54.38%) papers were collaborative research. As for author keywords, 'COVID19' (674), 'SARSCoV2' (245), 'Coronavirus' (81), and 'Vaccine' (80) were derived as top keywords. There were six words that appeared throughout the entire period: 'COVID19,' 'SARSCoV2,' 'Coronavirus,' 'Korea,' 'Pandemic,' and 'Mortality.' Co-occurrence network analysis was conducted on MeSH terms and author keywords, and common keywords such as 'covid-19,' 'sars-cov-2,' and 'public health' were derived. In topic modeling, five topics were identified, including 'Vaccination,' 'COVID-19 outbreak status,' 'Omicron variant,' 'Mental health, control measures,' and 'Transmission and control in Korea.' Through this study, it was possible to identify the research areas and major keywords by year of COVID-19 research papers published during the 'Public Health Emergency of International Concern (PHEIC).'

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.27-33
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• 2021

The whole world now is dealing with Coronavirus, and it has turned to be one of the most widespread and long-lived pandemics of our times. Reports reveal that the infectious disease has taken toll of the almost 80% of the world's population. Amidst a lot of research going on with regards to the prediction on growth and transmission through Symptomatic carriers of the virus, it can't be ignored that pre-symptomatic and asymptomatic carriers also play a crucial role in spreading the reach of the virus. Classification Algorithm has been widely used to classify different types of COVID-19 carriers ranging from simple feature-based classification to Convolutional Neural Networks (CNNs). This research paper aims to present a novel technique using a Random Forest Machine learning algorithm with hyper-parameter tuning to classify different types COVID-19-carriers such that these carriers can be accurately characterized and hence dealt timely to contain the spread of the virus. The main idea for selecting Random Forest is that it works on the powerful concept of "the wisdom of crowd" which produces ensemble prediction. The results are quite convincing and the model records an accuracy score of 99.72 %. The results have been compared with the same dataset being subjected to K-Nearest Neighbour, logistic regression, support vector machine (SVM), and Decision Tree algorithms where the accuracy score has been recorded as 78.58%, 70.11%, 70.385,99% respectively, thus establishing the concreteness and suitability of our approach.

• Journal of the FoodService Safety
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• v.1 no.1
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• pp.37-44
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• 2020

The virus isolated from patients with severe pneumonia of unknown etiology in Wuhan City, Hubei province in China was termed SARS-CoV-2 and the World Health Organization (WHO) named the disease caused by this virus as coronavirus disease 2019 (COVID-19). The COVID-19 infection has spread rapidly and become a pandemic. In July 2020, there were 13.25 million infected patients and over 570,000 deaths worldwide, and 13,711 infected patients and 294 deaths were reported in South Korea. Since the primary mode of transmission of COVID-19 is through respiratory droplets, the importance of preventive measures, including social distancing, has become important in daily life. In response to the continuous spread of COVID-19, this study developed three guidelines for preventing COVID-19 for the food service industry including childcare centers, institutional foodservices and restaurants by the integration of the manual of controlling foodborne illness. These are included the COVID-19 prevention action methods for food deliverers, for food service administrator, for foodservice works and for customers. All guidelines were designed for easy understanding using illustrations and have been systematically explained subject wise. Thus, these COVID-19 prevention guidelines can be appropriately applied depending on the specific situation and workplace. In addition, they are worthy as educational materials that contribute to the food safety.

• Genomics & Informatics
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• v.20 no.2
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• pp.22.1-22.9
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• 2022

The rise of newer coronavirus disease 2019 (COVID-19) variants has brought a challenge to ending the spread of COVID-19. The variants have a different fatality, morbidity, and transmission rates and affect vaccine efficacy differently. Therefore, the impact of each new variant on the spread of COVID-19 is of interest to governments and scientists. Here, we proposed mathematical SEIQRDVP and SEIQRDV3P models to predict the impact of the Omicron variant on the spread of the COVID-19 situation in South Korea. SEIQEDVP considers one vaccine level at a time while SEIQRDV3P considers three vaccination levels (only one dose received, full doses received, and full doses + booster shots received) simultaneously. The omicron variant's effect was contemplated as a weighted sum of the delta and omicron variants' transmission rate and tuned using a hyperparameter k. Our models' performances were compared with common models like SEIR, SEIQR, and SEIQRDVUP using the root mean square error (RMSE). SEIQRDV3P performed better than the SEIQRDVP model. Without consideration of the variant effect, we don't see a rapid rise in COVID-19 cases and high RMSE values. But, with consideration of the omicron variant, we predicted a continuous rapid rise in COVID-19 cases until maybe herd immunity is developed in the population. Also, the RMSE value for the SEIQRDV3P model decreased by 27.4%. Therefore, modeling the impact of any new risen variant is crucial in determining the trajectory of the spread of COVID-19 and determining policies to be implemented.