• Korean Journal of Radiology
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• v.24 no.4
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• pp.362-370
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• 2023

Objective: To report the clinical and radiological characteristics of patients with underlying B-cell lymphoma and coronavirus disease 2019 (COVID-19) showing migratory airspace opacities on serial chest computed tomography (CT) with persistent COVID-19 symptoms. Materials and Methods: From January 2020 to June 2022, of the 56 patients with underlying hematologic malignancy who had undergone chest CT more than once at our hospital after acquiring COVID-19, seven adult patients (5 female; age range, 37-71 years; median age, 45 years) who showed migratory airspace opacities on chest CT were selected for the analysis of clinical and CT features. Results: All patients had been diagnosed with B-cell lymphoma (three diffuse large B-cell lymphoma and four follicular lymphoma) and had received B-cell depleting chemotherapy, including rituximab, within three months prior to COVID-19 diagnosis. The patients underwent a median of 3 CT scans during the follow-up period (median 124 days). All patients showed multifocal patchy peripheral ground glass opacities (GGOs) with basal predominance in the baseline CTs. In all patients, follow-up CTs demonstrated clearing of previous airspace opacities with the development of new peripheral and peribronchial GGO and consolidation in different locations. Throughout the follow-up period, all patients demonstrated prolonged COVID-19 symptoms accompanied by positive polymerase chain reaction results from nasopharyngeal swabs, with cycle threshold values of less than 25. Conclusion: COVID-19 patients with B-cell lymphoma who had received B-cell depleting therapy and are experiencing prolonged SARS-CoV-2 infection and persistent symptoms may demonstrate migratory airspace opacities on serial CT, which could be interpreted as ongoing COVID-19 pneumonia.

• Clinical and Experimental Pediatrics
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• v.63 no.4
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• pp.119-124
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• 2020

A cluster of severe pneumonia of unknown etiology in Wuhan City, Hubei province in China emerged in December 2019. A novel coronavirus named severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) was isolated from lower respiratory tract sample as the causative agent. The current outbreak of infections with SARS-CoV-2 is termed Coronavirus Disease 2019 (COVID-19) by the World Health Organization (WHO). COVID-19 rapidly spread into at least 114 countries and killed more than 4,000 people by March 11 2020. WHO officially declared COVID-19 a pandemic on March 11, 2020. There have been 2 novel coronavirus outbreaks in the past 2 decades. The outbreak of severe acute respiratory syndrome (SARS) in 2002-2003 caused by SARS-CoV had a case fatality rate of around 10% (8,098 confirmed cases and 774 deaths), while Middle East respiratory syndrome (MERS) caused by MERS-CoV killed 861 people out of a total 2,502 confirmed cases between 2012 and 2019. The purpose of this review is to summarize known-to-date information about SARS-CoV-2, transmission of SARS-CoV-2, and clinical features.

• Genomics & Informatics
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• v.21 no.2
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• pp.16.1-16.14
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• 2023

Coronavirus disease 2019 (COVID-19) is a viral infection produced by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus epidemic, which was declared a global pandemic in March 2020. The World Health Organization has recorded around 43.3 billion cases and 59.4 million casualties to date, posing a severe threat to global health. Severe COVID-19 indicates viral pneumonia caused by the SARS-CoV-2 infections, which can induce fatal consequences, including acute respiratory distress syndrome (ARDS). The purpose of this research is to better understand the COVID-19 and ARDS pathways, as well as to find targeted single nucleotide polymorphism. To accomplish this, we retrieved over 100 patients' samples from the Sequence Read Archive, National Center for Biotechnology Information. These sequences were processed through the Galaxy server next generation sequencing pipeline for variant analysis and then visualized in the Integrative Genomics Viewer, and performed statistical analysis using t-tests and Bonferroni correction, where six major genes were identified as DNAH7, CLUAP1, PPA2, PAPSS1, TLR4, and IFITM3. Furthermore, a complete understanding of the genomes of COVID-19-related ARDS will aid in the early identification and treatment of target proteins. Finally, the discovery of novel therapeutics based on discovered proteins can assist to slow the progression of ARDS and lower fatality rates.

• Korean Journal of Radiology
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• v.25 no.5
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• pp.473-480
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• 2024

We systematically reviewed radiological abnormalities in patients with prolonged SARS-CoV-2 infection, defined as persistently positive polymerase chain reaction (PCR) results for SARS-CoV-2 for > 21 days, with either persistent or relapsed symptoms. We extracted data from 24 patients (median age, 54.5 [interquartile range, 44-64 years]) reported in the literature and analyzed their representative CT images based on the timing of the CT scan relative to the initial PCR positivity. Our analysis focused on the patterns and distribution of CT findings, severity scores of lung involvement on a scale of 0-4, and the presence of migration. All patients were immunocompromised, including 62.5% (15/24) with underlying lymphoma and 83.3% (20/24) who had received anti-CD20 therapy within one year. Median duration of infection was 90 days. Most patients exhibited typical CT appearance of coronavirus disease 19 (COVID-19), including ground-glass opacities with or without consolidation, throughout the follow-up period. Notably, CT severity scores were significantly lower during ≤ 21 days than during > 21 days (P < 0.001). Migration was observed on CT in 22.7% (5/22) of patients at ≤ 21 days and in 68.2% (15/22) to 87.5% (14/16) of patients at > 21 days, with rare instances of parenchymal bands in previously affected areas. Prolonged SARS-CoV-2 infection usually presents as migrating typical COVID-19 pneumonia in immunocompromised patients, especially those with impaired B-cell immunity.

• Korean Journal of Radiology
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• v.21 no.5
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• pp.627-628
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• 2020

• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.170-176
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• 2024

Since the World Health Organization (WHO) has declared COVID-19 as pandemic, many researchers have started working on developing vaccine and developing AI systems to detect COVID-19 patient using Chest X-ray images. The purpose of this work is to improve the performance of pre-trained Deep convolution neural nets (DCNNs) on Chest X-ray images dataset specially COVID-19 which is developed by collecting from different sources such as GitHub, Kaggle. To improve the performance of Deep CNNs, data augmentation is used in this study. The COVID-19 dataset collected from GitHub was containing 257 images while the other two classes normal and pneumonia were having more than 500 images each class. There were two issues whike training DCNN model on this dataset, one is unbalanced and second is the data is very less. In order to handle these both issues, we performed data augmentation such as rotation, flipping to increase and balance the dataset. After data augmentation each class contains 510 images. Results show that augmentation on Chest X-ray images helps in improving accuracy. The accuracy before and after augmentation produced by our proposed architecture is 96.8% and 98.4% respectively.

• The Journal of Korean Medicine
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• v.44 no.4
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• pp.193-207
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• 2023

Objectives: The purpose of this study was to evaluate the effectiveness and safety of traditional herbal medicine as a stand-alone treatment group through major English databases due to the lack of RCTs in Korea, and to provide a review of the herbal interventions used. Methods: Using four databases (Pubmed, EMBASE, OASIS, RISS), combination of words such as "Coronavirus" "RCT" "Herb" "Decoction" "TCM" were used. RCTs using herbal medicines to treat coronavirus were searched. Final 4 studies were selected by two authors according to inclusion and exclusion criteria. Results: A total of 1,435 patients were studied. The Chinese herbs used in the treatment group were Shengmai Yin, JingYinGuBiao granules, Jinhua Qinggan granules, and Bufei Huoxue capsules. The intervention group showed greater attenuation of pneumonia lesions on CT. Also, improvement in 6-min walk distance (6MWD), and negative conversion rate in treatment group were reported. Furthermore, scores on the Fatigue Assessment Inventory (FAI) were lower in the herbal group than in the placebo group. The median time to recovery of COVID-19 related symptoms was shorter in TCM group compared to the control group. Reported adverse effects were diarrhea, liver dysfunction, and excessive menstruation, and two papers did not mention side effects in detail. Conclusion: Herbal medicine alone can increase the conversion rate of viral negativity and relieve COVID-19 related symptoms without significant adverse effects.

• Pediatric Infection and Vaccine
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• v.27 no.1
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• pp.1-10
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• 2020

A cluster of severe pneumonia of unknown etiology in Wuhan City, Hubei province in China emerged in December 2019. A novel coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was isolated from lower respiratory tract sample as the causative agent. The current outbreak of infections with SARS-CoV-2 is termed coronavirus disease 2019 (COVID-19) by the World Health Organization (WHO). COVID-19 rapidly spread into at least 114 countries and killed more than 4,000 people by March 11, 2020. WHO officially declared COVID-19 a pandemic on March 11, 2020. There have been 2 novel coronavirus outbreaks in the past 2 decades. The outbreak of severe acute respiratory syndrome (SARS) in 2002-2003 caused by SARS-CoV had a case fatality rate of around 10% (8,098 confirmed cases and 774 deaths), while Middle East respiratory syndrome (MERS) caused by MERS-CoV killed 858 people out of a total 2,499 confirmed cases between 2012 and 2019. The purpose of this review is to summarize known-to-date information about SARS-CoV-2, transmission of SARS-CoV-2, and clinical features of COVID-19.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.131-138
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• 2022

Novel Coronavirus (COVID-19) is viewed as one of the main general wellbeing theaters on the worldwide level all over the planet. Because of the abrupt idea of the flare-up and the irresistible force of the infection, it causes individuals tension, melancholy, and other pressure responses. The avoidance and control of the novel Covid pneumonia have moved into an imperative stage. It is fundamental to early foresee and figure of infection episode during this troublesome opportunity to control of its grimness and mortality. The entire world is investing unimaginable amounts of energy to fight against the spread of this lethal infection. In this paper, we utilized machine learning and deep learning techniques for analyzing what is going on utilizing countries shared information and for detecting the climate factors that effect on spreading Covid-19, such as humidity, sunny hours, temperature and wind speed for understanding its regular dramatic way of behaving alongside the forecast of future reachability of the COVID-2019 around the world. We utilized data collected and produced by Kaggle and the Johns Hopkins Center for Systems Science. The dataset has 25 attributes and 9566 objects. Our Experiment consists of two phases. In phase one, we preprocessed dataset for DL model and features were decreased to four features humidity, sunny hours, temperature and wind speed by utilized the Pearson Correlation Coefficient technique (correlation attributes feature selection). In phase two, we utilized the traditional famous six machine learning techniques for numerical datasets, and Dense Net deep learning model to predict and detect the climatic factor that aide to disease outbreak. We validated the model by using confusion matrix (CM) and measured the performance by four different metrics: accuracy, f-measure, recall, and precision.

• Journal of Life Science
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• v.31 no.6
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• pp.603-608
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• 2021

The purpose of this perspective research is to discuss the potential role of exercise-interventions in COVID-19, terms of prevention and prognosis in the periods of the COVID-19 vaccine. SARCO-CoV-2. COVID-19 was detected as a new virus causing severe cardiovascular and respiratory complications. It emerged as a global public health emergency and national pandemic. It caused more than 1 million deaths in the first 6 months of the pandemic and resulted in huge social and economic fluctuations internationally. Unprecedented stressful situations, such as COVID-19 blue and COVID-19 red impact on many health problems. In healthy individuals, COVID-19 infection may induced no symptoms (i.e., asymptomatic), whereas others may experience flu-like symptoms, such as ARDS, pneumonia, and death. Poor health status, such as obesity and cardiovascular and respiratory complications, are high risk factors for COVID-19 prevention, occurrence, and prognosis. Several COVID-19 vaccines are currently in human trials. However, the efficacy and safety of COVID-19 vaccines, including potential side effects, such as anaphylaxis (a life-threatening allergic reaction) and rare blood clots, still need to be investigated. On the basis of direct and indirect evidence, it seems that regular and moderate physical exercise can be recommended as a nonpharmacological, efficient, and safe way to cope with COVID-19. Physical inactivity and metabolic abnormalities are directly associated with reduced immune responses, including reduced innate, CMI, and AMI responses. Due to prolonged viral shedding, quarantine in inactive, obese and disease people should likely be longer than physical active people. Multicomponent and systemic exercise should be considered for the obese, disease, and elderly people. More mechanism research is needed in this area.