• Applied Chemistry for Engineering
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• v.33 no.1
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• pp.83-89
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• 2022

Since the pandemic of COVID-19, active investigation to develop immunity to infectious disease by delivering nucleic acids has been proceeded. Particularly, many studies have been conducted on non-viral vector as several vital side-effects which were found on nucleic acid delivery system using viral vectors. In this study, we have developed plasmid DNA (pDNA) loaded-hyaluronic acid derivative (HA) coated-polyethyleneimine (PEI) based polyplex for enhanced nucleic acid delivery efficiency. We have optimized the ratio of pDNA : PEI : HA by measuring size and protein transcription efficiency. The final product, polyplex-HA, was characterized through measuring size, zeta-potential and TEM image. Intracellular uptake and protein transcription efficiency were compared to commercially available transfection reagent, lipofectamine, through fluorescence image and flow cytometry. In conclusion, polyplex-HA presents a novel gene delivery system for efficient and stable protein transcription since it is available for delivering various genetic materials and has less immunoreactivity.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.363-372
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• 2022

Since the recent COVID-19 Pandemic, the ransomware fandom has intensified along with the expansion of remote work. Currently, anti-virus vaccine companies are trying to respond to ransomware, but traditional file signature-based static analysis can be neutralized in the face of diversification, obfuscation, variants, or the emergence of new ransomware. Various studies are being conducted for such ransomware detection, and detection studies using signature-based static analysis and behavior-based dynamic analysis can be seen as the main research type at present. In this paper, the frequency of ".text Section" Opcode and the Native API used in practice was extracted, and the association between feature information selected using K-means Clustering algorithm, Cosine Similarity, and Pearson correlation coefficient was analyzed. In addition, Through experiments to classify and detect worms among other malware types and Cerber-type ransomware, it was verified that the selected feature information was specialized in detecting specific ransomware (Cerber). As a result of combining the finally selected feature information through the above verification and applying it to machine learning and performing hyper parameter optimization, the detection rate was up to 93.3%.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.127-147
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• 2020

The world is suffering from numerous human and economic losses due to the novel coronavirus infection (COVID-19). The Korean government established a strategy to overcome the national infectious disease crisis through research and development. It is difficult to find distinctive features and changes in a specific R&D field when using the existing technical classification or science and technology standard classification. Recently, a few studies have been conducted to establish a classification system to provide information about the investment research areas of infectious diseases in Korea through a comparative analysis of Korea government-funded research projects. However, these studies did not provide the necessary information for establishing cooperative research strategies among countries in the infectious diseases, which is required as an execution plan to achieve the goals of national health security and fostering new growth industries. Therefore, it is inevitable to study information services based on the classification system and classification model for establishing a national collaborative R&D strategy. Seven classification - Diagnosis_biomarker, Drug_discovery, Epidemiology, Evaluation_validation, Mechanism_signaling pathway, Prediction, and Vaccine_therapeutic antibody - systems were derived through reviewing infectious diseases-related national-funded research projects of South Korea. A classification system model was trained by combining Scopus data with a bidirectional RNN model. The classification performance of the final model secured robustness with an accuracy of over 90%. In order to conduct the empirical study, an infectious disease classification system was applied to the coronavirus-related research and development projects of major countries such as the STAR Metrics (National Institutes of Health) and NSF (National Science Foundation) of the United States(US), the CORDIS (Community Research & Development Information Service)of the European Union(EU), and the KAKEN (Database of Grants-in-Aid for Scientific Research) of Japan. It can be seen that the research and development trends of infectious diseases (coronavirus) in major countries are mostly concentrated in the prediction that deals with predicting success for clinical trials at the new drug development stage or predicting toxicity that causes side effects. The intriguing result is that for all of these nations, the portion of national investment in the vaccine_therapeutic antibody, which is recognized as an area of research and development aimed at the development of vaccines and treatments, was also very small (5.1%). It indirectly explained the reason of the poor development of vaccines and treatments. Based on the result of examining the investment status of coronavirus-related research projects through comparative analysis by country, it was found that the US and Japan are relatively evenly investing in all infectious diseases-related research areas, while Europe has relatively large investments in specific research areas such as diagnosis_biomarker. Moreover, the information on major coronavirus-related research organizations in major countries was provided by the classification system, thereby allowing establishing an international collaborative R&D projects.

• Pediatric Infection and Vaccine
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• v.31 no.1
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• pp.75-82
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• 2024

Purpose: As the coronavirus disease 2019 (COVID-19) pandemic ended, the number of patients with respiratory syncytial virus (RSV) pneumonia increased during the spring/summer of 2022. This study aimed to analyze the clinical features and antibiotic usage of children hospitalized for RSV pneumonia in a recently established general hospital in Sejong city. Methods: In this retrospective review, we included inpatients of the Pediatric Department of Chungnam National University Sejong Hospital diagnosed with RSV pneumonia between March 2022 and April 2023. Patients were divided into 2 groups: with and without antibiotic treatment. Demographic data, initial presentations, and clinical courses were reviewed. Results: A total of 116 patients with RSV pneumonia were hospitalized during this period, of which 102 were analyzed, excluding 14 with underlying diseases or who did not fall within the definition of pneumonia. The median age was 17 months. Diagnoses of bacterial infections (acute otitis media and sinusitis) were documented in 9.8% of cases. Intravenous (IV) antibiotics were administered in 46% of cases. The group receiving IV antibiotics showed higher inflammatory levels (C-reactive protein; CRP), more infiltration on initial chest X-rays, and longer fever duration. There was no difference in the length of hospitalization between the groups with and without IV antibiotics. Conclusions: This study showed a tendency for the attending physician to prescribe IV antibiotics to patients with longer fever duration, pulmonary infiltrations on the initial chest X-ray, and higher CRP levels. However, given the high rate of IV antibiotic usage compared to previous studies, care should be taken in antibiotic use.