• Title/Summary/Keyword: AI control

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Loss of EMP2 Inhibits Melanogenesis of MNT1 Melanoma Cells via Regulation of TRP-2

  • Enkhtaivan, Enkhmend;Kim, Hyun Ji;Kim, Boram;Byun, Hyung Jung;Yu, Lu;Nguyen, Tuan Minh;Nguyen, Thi Ha;Do, Phuong Anh;Kim, Eun Ji;Kim, Kyung Sung;Huy, Hieu Phung;Rahman, Mostafizur;Jang, Ji Yun;Rho, Seung Bae;Lee, Ho;Kang, Gyeoung Jin;Park, Mi Kyung;Kim, Nan-Hyung;Choi, Chang Ick;Lee, Kyeong;Han, Hyo Kyung;Cho, Jungsook;Lee, Ai Young;Lee, Chang Hoon
    • Biomolecules & Therapeutics
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    • v.30 no.2
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    • pp.203-211
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    • 2022
  • Melanogenesis is the production of melanin from tyrosine by a series of enzyme-catalyzed reactions, in which tyrosinase and DOPA oxidase play key roles. The melanin content in the skin determines skin pigmentation. Abnormalities in skin pigmentation lead to various skin pigmentation disorders. Recent research has shown that the expression of EMP2 is much lower in melanoma than in normal melanocytes, but its role in melanogenesis has not yet been elucidated. Therefore, we investigated the role of EMP2 in the melanogenesis of MNT1 human melanoma cells. We examined TRP-1, TRP-2, and TYR expression levels during melanogenesis in MNT1 melanoma cells by gene silencing of EMP2. Western blot and RT-PCR results confirmed that the expression levels of TYR and TRP-2 were decreased when EMP2 expression was knocked down by EMP2 siRNA in MNT1 cells, and these changes were reversed when EMP2 was overexpressed. We verified the EMP2 gene was knocked out of the cell line (EMP2 CRISPR/Cas9) by using a CRISPR/Cas9 system and found that the expression levels of TRP-2 and TYR were significantly lower in the EMP2 CRISPR/Cas9 cell lines. Loss of EMP2 also reduced migration and invasion of MNT1 melanoma cells. In addition, the melanosome transfer from the melanocytes to keratinocytes in the EMP2 KO cells cocultured with keratinocytes was reduced compared to the cells in the control coculture group. In conclusion, these results suggest that EMP2 is involved in melanogenesis via the regulation of TRP-2 expression.

Implementation of integrated monitoring system for trace and path prediction of infectious disease (전염병의 경로 추적 및 예측을 위한 통합 정보 시스템 구현)

  • Kim, Eungyeong;Lee, Seok;Byun, Young Tae;Lee, Hyuk-Jae;Lee, Taikjin
    • Journal of Internet Computing and Services
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    • v.14 no.5
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    • pp.69-76
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    • 2013
  • The incidence of globally infectious and pathogenic diseases such as H1N1 (swine flu) and Avian Influenza (AI) has recently increased. An infectious disease is a pathogen-caused disease, which can be passed from the infected person to the susceptible host. Pathogens of infectious diseases, which are bacillus, spirochaeta, rickettsia, virus, fungus, and parasite, etc., cause various symptoms such as respiratory disease, gastrointestinal disease, liver disease, and acute febrile illness. They can be spread through various means such as food, water, insect, breathing and contact with other persons. Recently, most countries around the world use a mathematical model to predict and prepare for the spread of infectious diseases. In a modern society, however, infectious diseases are spread in a fast and complicated manner because of rapid development of transportation (both ground and underground). Therefore, we do not have enough time to predict the fast spreading and complicated infectious diseases. Therefore, new system, which can prevent the spread of infectious diseases by predicting its pathway, needs to be developed. In this study, to solve this kind of problem, an integrated monitoring system, which can track and predict the pathway of infectious diseases for its realtime monitoring and control, is developed. This system is implemented based on the conventional mathematical model called by 'Susceptible-Infectious-Recovered (SIR) Model.' The proposed model has characteristics that both inter- and intra-city modes of transportation to express interpersonal contact (i.e., migration flow) are considered. They include the means of transportation such as bus, train, car and airplane. Also, modified real data according to the geographical characteristics of Korea are employed to reflect realistic circumstances of possible disease spreading in Korea. We can predict where and when vaccination needs to be performed by parameters control in this model. The simulation includes several assumptions and scenarios. Using the data of Statistics Korea, five major cities, which are assumed to have the most population migration have been chosen; Seoul, Incheon (Incheon International Airport), Gangneung, Pyeongchang and Wonju. It was assumed that the cities were connected in one network, and infectious disease was spread through denoted transportation methods only. In terms of traffic volume, daily traffic volume was obtained from Korean Statistical Information Service (KOSIS). In addition, the population of each city was acquired from Statistics Korea. Moreover, data on H1N1 (swine flu) were provided by Korea Centers for Disease Control and Prevention, and air transport statistics were obtained from Aeronautical Information Portal System. As mentioned above, daily traffic volume, population statistics, H1N1 (swine flu) and air transport statistics data have been adjusted in consideration of the current conditions in Korea and several realistic assumptions and scenarios. Three scenarios (occurrence of H1N1 in Incheon International Airport, not-vaccinated in all cities and vaccinated in Seoul and Pyeongchang respectively) were simulated, and the number of days taken for the number of the infected to reach its peak and proportion of Infectious (I) were compared. According to the simulation, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days when vaccination was not considered. In terms of the proportion of I, Seoul was the highest while Pyeongchang was the lowest. When they were vaccinated in Seoul, the number of days taken for the number of the infected to reach at its peak was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. When they were vaccinated in Pyeongchang, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. Based on the results above, it has been confirmed that H1N1, upon the first occurrence, is proportionally spread by the traffic volume in each city. Because the infection pathway is different by the traffic volume in each city, therefore, it is possible to come up with a preventive measurement against infectious disease by tracking and predicting its pathway through the analysis of traffic volume.