• Food Science and Industry
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• v.51 no.4
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• pp.278-301
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• 2018

Although more than 80% of living organisms are found in marine ecosystems, only less than 10% of marine resources have been utilized for human food consumptions and other usages. It is well known that marine resources (fish, shellfish and algae) have exceptional nutritional properties; however, their functional characteristic has not been completely discovered. It is believed that metabolites (organic compounds, proteins, peptides, lipids, minerals, etc.) play an important role to show its biological properties. Marine proteins and peptides are considered to be future drugs due to their excellent biological activities with a fewer adverse side effect. Marine peptides show several biological activities, including antimicrobial, antioxidant, anti-inflammatory, anti-cancer, anti-viral, anti-tumor, anti-diabetic, anti-hypertensive, anti-coagulant, immunomodulatory, appetite suppressing and neuroprotective effects. Therefore, the pharmaceutical, nutraceutical, and cosmeceutical companies have been paid attention to the marine peptides to commercialize into products. This current review mainly focused on the above mentioned biological activities of marine peptides and protein hydrolysates as a functional food and pharmaceutical applications. To commercialize these materials in industrial level required large quantity in high-purity level, and it is complicated to produce huge quantity from the marine resources due to insufficient raw materials, unavailability of raw materials through a year, hinder the growth with geographical variations, and availability of compounds in extreme small quantities. The best solution for these issues is to introduce new modern technologies such as artificial intelligence robots, drones, submersibles and automated raw material harvesting vessels in farming industries instead of man power, which will lead to 4th industrial revolution.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.47-64
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• 2021

The global spread of COVID-19 around the world has not only affected many parts of our daily life but also has a huge impact on many areas, including the economy and society. As the number of confirmed cases and deaths increases, medical staff and the public are said to be experiencing psychological problems such as anxiety, depression, and stress. The collective tragedy that accompanies the epidemic raises fear and anxiety, which is known to cause enormous disruptions to the behavior and psychological well-being of many. Long-term negative emotions can reduce people's immunity and destroy their physical balance, so it is essential to understand the psychological state of COVID-19. This study suggests a method of monitoring medial news reflecting current days which requires striving not only for physical but also for psychological quarantine in the prolonged COVID-19 situation. Moreover, it is presented how an easier method of analyzing social media networks applies to those cases. The aim of this study is to assist health policymakers in fast and complex decision-making processes. News plays a major role in setting the policy agenda. Among various major media, news headlines are considered important in the field of communication science as a summary of the core content that the media wants to convey to the audiences who read it. News data used in this study was easily collected using "Bigkinds" that is created by integrating big data technology. With the collected news data, keywords were classified through text mining, and the relationship between words was visualized through semantic network analysis between keywords. Using the KrKwic program, a Korean semantic network analysis tool, text mining was performed and the frequency of words was calculated to easily identify keywords. The frequency of words appearing in keywords of articles related to COVID-19 emotions was checked and visualized in word cloud 'China', 'anxiety', 'situation', 'mind', 'social', and 'health' appeared high in relation to the emotions of COVID-19. In addition, UCINET, a specialized social network analysis program, was used to analyze connection centrality and cluster analysis, and a method of visualizing a graph using Net Draw was performed. As a result of analyzing the connection centrality between each data, it was found that the most central keywords in the keyword-centric network were 'psychology', 'COVID-19', 'blue', and 'anxiety'. The network of frequency of co-occurrence among the keywords appearing in the headlines of the news was visualized as a graph. The thickness of the line on the graph is proportional to the frequency of co-occurrence, and if the frequency of two words appearing at the same time is high, it is indicated by a thick line. It can be seen that the 'COVID-blue' pair is displayed in the boldest, and the 'COVID-emotion' and 'COVID-anxiety' pairs are displayed with a relatively thick line. 'Blue' related to COVID-19 is a word that means depression, and it was confirmed that COVID-19 and depression are keywords that should be of interest now. The research methodology used in this study has the convenience of being able to quickly measure social phenomena and changes while reducing costs. In this study, by analyzing news headlines, we were able to identify people's feelings and perceptions on issues related to COVID-19 depression, and identify the main agendas to be analyzed by deriving important keywords. By presenting and visualizing the subject and important keywords related to the COVID-19 emotion at a time, medical policy managers will be able to be provided a variety of perspectives when identifying and researching the regarding phenomenon. It is expected that it can help to use it as basic data for support, treatment and service development for psychological quarantine issues related to COVID-19.

• Childhood Kidney Diseases
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• v.9 no.2
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• pp.175-182
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• 2005

Purpose : Interleukin 1 receptor antagonist(IL-1ra) is an endogenous antiinflammatory agent that binds to IL-1 receptor and thus competitively inhibits the binding of IL-1$\alpha$ and IL-1$\beta$. Allele 2 in association with various autoimmune diseases has been reported. In order to evaluate the influence of IL-1ra gene VNTR polymorphism on the susceptibility to HSP and its possible association with disease severity, manifested by severe renal involvement and renal sequelae, we studied the incidence of carriage rate and allele frequency of the 2 repeats of IL-1ra allele 2($IL1RN^{*}2$) of the IL-1ra gene in children with HSP with and without renal involvement. Methods : The IL-1ra gene polymorphisms were determined in children with HSP with(n=40) or without nephritis(n=34) who had been diagnosed at Busan Paik Hospital and the control groups(n=163). Gene polymorphism was identified by PCR amplification of the genomic DNA. Results : The allelic frequency and carriage rate of $IL1RN^{*}1$ were found most frequently in patients with HSP and in controls. The allelic frequency of $IL1RN^{*}2$ was higher in patients with HSP compared to that of controls($4.7\%\;vs.\;2.5\%$, P=0.794). The carriage rate of $IL1RN^{*}2$ was higher In patients with HSP compared to that of controls($8.1\%\;vs.\;6.8\%$, P=0.916). The allelic frequency of $IL1RN^{*}2$ was higher in patients with HSP nephritis compared to that of HSP($5.3\%\;vs.\;2.9\%$, P=0.356). The carriage rate of $IL1RN^{*}2$ was higher in Patients with HSP nephritis compared to that of HSP($10.0\%\;vs.\;5.9\%$, P=0.523). Among 13 patients with heavy proteinuria(>1.0 g), 11 had $IL1RN^{*}1$, 1 had $IL1RN^{*}2$ and the others had $IL1RN^{*}4$. At the time of last follow up 4 patients had sustained proteinuria and their genotype was $IL1RN^{*}1$. Conclusion : The allelic frequency and carriage rate of $IL1RN^{*}1$ were found most frequently in patients with HSP and in controls. Our study suggests that the carriage rate and allele frequency of the 2-repeats of IL-1lra allele 2($IL1RN^{*}2$) of the IL-1ra gene may not be associated with susceptibility and severity of renal involvement in children with HSP (J Korean Soc Pediatr Nephrol 2005;9:175-182)