14 research outputs found

    A Study on the Utilization Strategies of Rules of Origin in Korean FTA

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    Abstract This study tries to make a literature survey to understand the testing methods and some characteristics of rules of origin in terms of Korean FTA. Also we introduce theoretical and empirical backgrounds about rules of origin in Korean FTA. Then this study used the existing statistical data, related to Korean rules of origin such as FTA utilization rates, rigorness index, complexity index and tariff rates. Through the linear regression methods, we try to find the facts related to the spaghetti bowl effects in Korean FTA. We want to know whether the spaghetti bowl phenomena appear in Korean FTA or not. Our study shows that Korean FTAs have the spaghetti bowl effects during early FTA periods before 2008. Our empirical results and policy implications are summarized as follows. Firstly, the more complex rules of origin show the more serious spaghetti bowl effects. So the Korean government will make some efforts to unify the more complex rules of origin under the more FTAs. Also the government needs to analyze the complex rules of origin and introduce them with very easy contents. Small and medium- sized companies avoid the complex rules of origin and neglect them. They are not willing to utilize them because of heavy opportunity costs. So more incentives are given to these small and medium- sized companies Secondly, the higher tariff rates induce the more utilization of rules of origin. The bigger differences between privileged and non-privileged tariff rates give some incentives to utilize the complex rules of origin even if more FTAs make Korean rules of origin more complex. This means that non-privileged tariff rates have strong protective effects which can protect domestic industries. From this result, we have to analyze the FTA results to harm the domestic industries with comparative disadvantages. We have to minimize the harmful effects to influence the domestic industries. Thirdly, this study has some contributions in that we find out the spaghetti bowl phenomena in Korean FTAs. Many Asian countries have been exposed to more FTAs and rapidly experienced the more complex rules of origin. So these countries are expected to show more serious spaghetti bowl phenomena. This study has some limitations. In the future studies, we need to extend our data with longer time series. In particular, with recent rigorousness index, we should examine the recent spaghetti bowl effects. Also we need to analyze spaghetti bowl phenomena in terms of individual products instead of aggregate products. We need compare Korean results with foreign results.๋ชฉ ์ฐจ Abstract iii 1. ์„œ ๋ก  1 1.1 ์—ฐ๊ตฌ์˜ ๋ชฉ์  1 1.2 ์—ฐ๊ตฌ์˜ ๋ฒ”์œ„ ๋ฐ ๋ฐฉ๋ฒ• 3 1.2.1 ์—ฐ๊ตฌ์˜ ๋ฒ”์œ„ 3 1.2.2 ์—ฐ๊ตฌ๋ฐฉ๋ฒ• 3 2. ์›์‚ฐ์ง€ ๊ทœ์ •์˜ ์˜๋ฏธ ๋ฐ ์ค‘์š”์„ฑ 4 2.1 ์›์‚ฐ์ง€ ๊ทœ์ •์˜ ์˜๋ฏธ 4 2.2 ์›์‚ฐ์ง€ ๊ทœ์ •์˜ ์ค‘์š”์„ฑ 5 3. ์›์‚ฐ์ง€ ๊ทœ์ •๊ณผ ๊ด€๋ จํ•œ ๋ฌด์—ญํšจ๊ณผ 7 3.1 ์›์‚ฐ์ง€ ๊ทœ์ •๊ณผ ๊ฐ„์ ‘์  ๋ฌด์—ญํšจ๊ณผ 7 3.2 ์ž์œ ๋ฌด์—ญํ˜‘์ •์˜ ์›์‚ฐ์ง€๊ทœ์ •๊ณผ ๋ฌด์—ญํšจ๊ณผ 8 3.3 ์›์‚ฐ์ง€ ๊ทœ์ •๊ณผ ํˆฌ์ž๊ตฌ์กฐ 9 4. ์›์‚ฐ์ง€ ๊ทœ์ •์˜ ์œ ํ˜•๊ณผ ๊ฒ€์ฆ 11 4.1 FTA์˜ ์›์‚ฐ์ง€ ๊ฒฐ์ •๊ธฐ์ค€ 11 4.2 ์‹ค์งˆ๋ณ€๊ฒฝ๊ธฐ์ค€ ๋น„๊ต 12 4.3 FTA์˜ ์›์‚ฐ์ง€ ๊ทœ์ •์˜ ์œ ํ˜• 14 4.4 FTA์˜ ์›์‚ฐ์ง€ ์ฆ๋ช… 15 4.5 FTA์˜ ์›์‚ฐ์ง€ ๊ฒ€์ฆ 16 5. FTA ์›์‚ฐ์ง€์— ๊ด€ํ•œ ๊ธฐ์กด ์—ฐ๊ตฌ 17 5.1 ์ด๋ก ์  ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ 17 5.2 ์‹ค์ฆ์  ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ 20 6. ํ•œ๊ตญ์˜ ์›์‚ฐ์ง€ ๊ทœ์ •์— ๊ด€ํ•œ ์‹ค์ฆ ์—ฐ๊ตฌ 25 6.1 ์›์‚ฐ์ง€ ๊ทœ์ •์˜ ์—„๊ฒฉ์„ฑ ์ง€์ˆ˜ 25 6.2 FTA๋ณ„ ์›์‚ฐ์ง€ ๊ทœ์ •์˜ ์—„๊ฒฉ์„ฑ ์ง€์ˆ˜ 26 6.3 FTA ์›์‚ฐ์ง€ ๊ทœ์ •์— ๋”ฐ๋ฅธ ํ™œ์šฉ์œจ 29 6.4 FTA ์›์‚ฐ์ง€ ๊ทœ์ •์— ๊ด€ํ•œ ์‹ค์ฆ์—ฐ๊ตฌ 29 7. ๊ฒฐ๋ก  33 7.1 ์—ฐ๊ตฌ์˜ ๊ฒฐ๊ณผ 33 7.2 ์—ฐ๊ตฌ์˜ ์ •์ฑ…์  ํ•จ์˜ 33 ์ฐธ๊ณ ๋ฌธํ—Œ 3

    Deguelin, an Akt inhibitor, down-regulates NF-kB signaling, induces apoptosis in colon cancer cells, and inhibits tumor growth in mice

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) --์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์˜ํ•™๊ณผ(๋‚ด๊ณผํ•™์ „๊ณต),2010.2.Docto

    ๋Œ€๋•์ „ํŒŒ์ฒœ๋ฌธ๋Œ€ ๋‹ค์ค‘๋น” ์ˆ˜์‹ ๊ธฐ์šฉ ์ œ์–ด์‹œ์Šคํ…œ ๊ตฌ์ถ•๊ณผ ๊ณ ์งˆ๋Ÿ‰์„ฑ ์ƒ์„ฑ ์˜์—ญ์— ๋Œ€ํ•œ ๋ฌผ๊ณผ ๋ฉ”ํƒ„์˜ฌ๋ฉ”์ด์ € ๊ด€์ธก์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์ž์—ฐ๊ณผํ•™๋Œ€ํ•™ ๋ฌผ๋ฆฌยท์ฒœ๋ฌธํ•™๋ถ€,2014. 8. ๋ฐ•์šฉ์„ .Multi-beam receiver can greatly increase the observation efficiency by allowing observations of wide-field of sky in a short time. World-wide observatories have made efforts to develop such multi-feed receivers. The TRAO imported a multi-beam receiver called QUARRY from the FCRAO, USA, instead of developing it by himself, to swiftly follow the trend. We developed control system for the multi-beam receiver to be compatible with the remaining system. We made a new program and an interface to control spectrometers that acquire data from the receiver, improved a front-end system that manages the receiver, and installed a new data acquisition storage that saves data from Modcomp. In software part, we applied an asynchronous timer and a non-blocking method to the back-end system, used several communication methods to carry command and data directly, and edited the front-end system program with the non-blocking method to minimize a time of tuning process. In hardware part, we revised a DIO board, connected new DIO lines and serial lines, and adopted DMA method to transfer data quickly. By using the radio telescope equipped with the multi-feed receiver and the KVN telescope, we carried out survey observations toward star forming regions in H2O, CH3OH masers and in HCO+, H13CO+, and 13CO thermal lines to understand their association with star formation activities. The targets are taken from Arecibo methanol maser Galactic plane survey and from Methanol Multibeam catalog identified with 6.7 GHz CH3OH class II methanol maser. The detection rates of 22 GHz, 44 GHz, and 95 GHz toward 271 6.7 GHz class II methanol maser sources are 49 %, 51%, and 44%, respectively. Water maser is detected mostly with other masers, but does not show any correlation with them in terms of the flux density and the velocity. 12 sources out of the 66 sources in which water maser are detected have high-velocity (> 30kmsโˆ’1) features, and the 7 sources out of the 12 sources may be related with pole-on jets. 95GHz class I methanol maser always comes with 44 GHz class I methanol maser. They are related with each other in the flux density and the velocity. Almost 44 GHz sources (87 %) come with 95 GHz maser. The distribution of velocity offset from the systemic velocity of 6.7GHz peak flux density appears as a double peak shape and differs from others.Abstract i 1 Introduction 1 Reference .................................... 5 2 Development of the TRAO control system for the multi-beam receiver 7 2.1 Introduction................................ 8 2.2 Hardware structure............................ 10 2.2.1 Modcomp............................. 10 2.2.2 Platform PC (PPC) ....................... 12 2.2.3 Backend management PC (BPC)................ 14 2.2.4 correlator PC (CPC)....................... 16 2.2.5 Data Acquisition Server (DAS)................. 18 2.2.6 Correlator............................. 19 2.2.7 Time generator (TG) ...................... 20 2.2.8 digital input / output (DIO) divider . . . . . . . . . . . . . . 21 2.3 Details on the control system ...................... 23 2.3.1 Concepts of system programming................ 23 2.3.2 Communication between the control programs . . . . . . . . 35 2.3.3 Realization of the DMA method ................ 42 2.4 Conclusion ................................ 44 Reference .................................... 49 3 Simultaneous observation of water and class I methanol masers toward class II methanol maser sources 51 3.1 Introduction................................ 52 3.2 Source Selection and Observations ................... 55 3.2.1 Source Selection ......................... 55 3.2.2 Observations ........................... 55 3.3 Results................................... 57 3.3.1 Detection Rates ......................... 57 3.3.2 New Maser Sources........................ 58 3.3.3 Notes on Selected Sources.................... 60 3.4 Analyses.................................. 63 3.4.1 Velocity Characteristics ..................... 63 3.4.2 Flux Densities and Luminosities ................ 67 3.4.3 Associated BGPS Clumps.................... 71 3.4.4 Methanol Column Densities and Abundances . . . . . . . . . 72 3.5 Conclusions................................ 76 Reference .................................... 79 4 Observational study of water and class I methanol masers toward class II methanol maser sources 107 4.1 Introduction................................ 108 4.2 Source Selection and Observations ................... 111 4.2.1 Source Selection ......................... 111 4.2.2 Observations ........................... 111 4.3 Results................................... 113 4.3.1 Detection Rates ......................... 113 4.3.2 Notes on Selected Sources.................... 114 4.3.3 High velocity Features of Water Maser . . . . . . . . . . . . . 117 4.4 Analyses.................................. 117 4.4.1 Velocity Characteristics ..................... 117 4.4.2 Analysis of detection rates.................... 128 4.4.3 Flux Densities .......................... 131 4.4.4 BGPS counterparts ........................ 134 4.5 Conclusions................................ 134 Reference .................................... 137 5 Conclusions 169Docto

    ์„œ์šธ์ „ํŒŒ์ฒœ๋ฌธ๋Œ€(SRAO) 6M ๋ง์›๊ฒฝ์˜ On The Fly Mapping ์‹œ์Šคํ…œ๊ตฌ์ถ•

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์ง€๊ตฌํ™˜๊ฒฝ๊ณผํ•™๋ถ€ ์ฒœ๋ฌธํ•™์ „๊ณต,2004.Maste

    ๋ฐ”๋žŒ ๋ฐ ์กฐ์„์„ ๊ณ ๋ คํ•œ ํ™ฉํ•ด ๋ฐ ๋™์ค‘๊ตญํ•ด ํ•ด์ˆ˜ ์ˆœํ™˜์— ๊ด€ํ•œ ์ˆ˜์น˜ ์‹คํ—˜ ์—ฐ๊ตฌ

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    Thesis (doctoral)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :ํ•ด์–‘ํ•™๊ณผ,2001.Docto

    A study on the effect of technology transfer support on SME business performance

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ํ–‰์ •๋Œ€ํ•™์› ๊ณต๊ธฐ์—…์ •์ฑ…ํ•™๊ณผ, 2021.8. ๊ธˆํ˜„์„ญ.This study sought to examine whether supporting SMEs to quickly acquire the necessary technologies through technology transfer is actually more effective in improving the business performance of SMEs than supporting them to develop their own technologies. In addition, it was intended to examine whether there was a difference in the business performance of SMEs depending on the area of technology transfered. To this end, whether technology was transferrer, and whether it was transfered in the strategic technology sector of the 4th Industrial Revolution were set as independent variables and financial indicators on growth, profitability and stability were set as dependent variables. Research was conducted on SMEs that received IP-Acquisition guarantees or R&D guarantees from the Korea Technology Finance Corporation from 2011 to 2017. The study found that supporting technology transfer through IP acquisition guarantees has a negative impact on the growth rate of total assets by SMEs rather than supporting their own development through R&D guarantees, but a positive impact on the return on total assets and return on equity by SMEs. Because technology development costs are credited as assets if they meet intangible asset recognition requirements, the effect of asset growth is not significant for technology transactions that require less cost. But, If SMEs receive technology transfer, they are considered more advantageous in generating profits because they have a low risk of failure and can respond quickly to market demand. This study confirmed empirically that creating a technology ecosystem where open innovation such as technology transfer actively occurs is effective in enhancing the financial performance of SMEs Because the effectiveness of technology greatly affects the financial performance of SMEs rather than the type of technology transfered, it has been confirmed that it is important to accurately identify the demand for technology from SMEs and support technology transfer.๋ณธ ์—ฐ๊ตฌ๋Š” ์ค‘์†Œ๊ธฐ์—…์ด ๊ธฐ์ˆ ๊ฑฐ๋ž˜๋ฅผ ํ†ตํ•ด ๋‚ฎ์€ ๋น„์šฉ์œผ๋กœ ์‹ ์†ํ•˜๊ฒŒ ํ•„์š”ํ•œ ๊ธฐ์ˆ ์„ ํš๋“ํ•˜๋„๋ก ์ง€์›ํ•˜๋Š” ๊ฒƒ์ด ์ž์ฒด์ ์œผ๋กœ ๊ธฐ์ˆ ์„ ๊ฐœ๋ฐœํ•˜๋„๋ก ์ง€์›ํ•˜๋Š” ๊ฒƒ๋ณด๋‹ค ์ค‘์†Œ๊ธฐ์—…์˜ ์žฌ๋ฌด ์„ฑ๊ณผ ์ œ๊ณ ์— ์‹ค์ œ๋กœ ๋” ํšจ๊ณผ์ ์ธ์ง€ ์‚ดํŽด๋ณด๊ณ ์ž ํ•˜์˜€๋‹ค. ๋˜ํ•œ, ๊ธฐ์ˆ ๊ฑฐ๋ž˜๋ฅผ ์ง€์›ํ•˜๋Š” ๊ฒฝ์šฐ ์ค‘์†Œ๊ธฐ์—…์ด ์ด์ „๋ฐ›์€ ๊ธฐ์ˆ ์˜ ๋ถ„์•ผ์— ๋”ฐ๋ผ ์ค‘์†Œ๊ธฐ์—…์˜ ์žฌ๋ฌด์  ์„ฑ๊ณผ์— ์ฐจ์ด๊ฐ€ ์žˆ๋Š”์ง€ ์‚ดํŽด๋ณด๊ณ ์ž ํ•˜์˜€๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ๊ธฐ์ˆ ๊ฑฐ๋ž˜๋ฅผ ํ†ตํ•ด ๊ธฐ์ˆ ์„ ์ด์ „๋ฐ›์•˜๋Š”์ง€ ์—ฌ๋ถ€ ๋ฐ ์ด์ „๋ฐ›์€ ๊ธฐ์ˆ ์˜ 4์ฐจ ์‚ฐ์—…ํ˜๋ช… ์ „๋žต๊ธฐ์ˆ ๋ถ„์•ผ ํ•ด๋‹น์—ฌ๋ถ€๋ฅผ ๋…๋ฆฝ๋ณ€์ˆ˜๋กœ ์„ค์ •ํ•˜๊ณ  ์„ฑ์žฅ์„ฑ, ์ˆ˜์ต์„ฑ ๋ฐ ์•ˆ์ •์„ฑ์— ๊ด€ํ•œ ์žฌ๋ฌด์ง€ํ‘œ๋ฅผ ์ข…์†๋ณ€์ˆ˜๋กœ ์„ค์ •ํ•˜์˜€์œผ๋ฉฐ, 2011๋…„ ๋ถ€ํ„ฐ 2017๋…„ ๊นŒ์ง€ ๊ธฐ์ˆ ๋ณด์ฆ๊ธฐ๊ธˆ์œผ๋กœ๋ถ€ํ„ฐ ๊ธฐ์ˆ ๊ฑฐ๋ž˜์ž๊ธˆ ๋˜๋Š” ์ž์ฒด๊ฐœ๋ฐœ์ž๊ธˆ์„ ์ง€์›๋ฐ›์€ ์ค‘์†Œ๊ธฐ์—…์„ ๋Œ€์ƒ์œผ๋กœ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ, IP์ธ์ˆ˜๋ณด์ฆ์„ ํ†ตํ•ด ๊ธฐ์ˆ ๊ฑฐ๋ž˜๋ฅผ ์ง€์›ํ•˜๋Š” ๊ฒƒ์ด R&D๋ณด์ฆ์„ ํ†ตํ•ด ์ž์ฒด๊ฐœ๋ฐœ์„ ์ง€์›ํ•˜๋Š” ๊ฒƒ๋ณด๋‹ค ์„ฑ์žฅ์„ฑ ์ธก๋ฉด์—์„œ๋Š” ์ค‘์†Œ๊ธฐ์—…์˜ ์ด์ž์‚ฐ์ฆ๊ฐ€์œจ ์ œ๊ณ ์— ์œ ์˜๋ฏธํ•œ ๋ถ€(-)์˜ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋‚˜, ์ˆ˜์ต์„ฑ ์ธก๋ฉด์—์„œ๋Š” ์ค‘์†Œ๊ธฐ์—…์˜ ์ด์ž์‚ฐ์ˆœ์ด์ต๋ฅ  ๋ฐ ์ž๊ธฐ์ž๋ณธ ์ˆœ์ด์ต๋ฅ  ์ œ๊ณ ์— ์œ ์˜๋ฏธํ•œ ์ •(+)์˜ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ฑฐ๋ž˜๊ธฐ์ˆ ์ด 4์ฐจ ์‚ฐ์—…ํ˜๋ช… ์ „๋žต๊ธฐ์ˆ ๋ถ„์•ผ์— ํ•ด๋‹นํ•˜๋Š”์ง€ ์—ฌ๋ถ€๋Š” ๊ธฐ์ˆ ์„ ์ด์ „๋ฐ›์€ ์ค‘์†Œ๊ธฐ์—…์˜ ์‚ฌ์—…์„ฑ๊ณผ ์ฐจ์ด์— ์œ ์˜๋ฏธํ•œ ์˜ํ–ฅ์„ ๋ฏธ์น˜์ง€ ์•Š๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ธฐ์ˆ ๊ฐœ๋ฐœ๋น„๋Š” ๋ฌดํ˜•์ž์‚ฐ ์ธ์‹์š”๊ฑด์„ ์ถฉ์กฑํ•  ๊ฒฝ์šฐ ์ž์‚ฐ์œผ๋กœ ๊ณ„์ƒ๋˜๊ธฐ ๋•Œ๋ฌธ์— ์ƒ๋Œ€์ ์œผ๋กœ ๋น„์šฉ์ด ์ ๊ฒŒ ์†Œ์š”๋˜๋Š” ๊ธฐ์ˆ ๊ฑฐ๋ž˜์˜ ๊ฒฝ์šฐ ์ž์‚ฐ์ฆ๊ฐ€ ํšจ๊ณผ๋Š” ์ž‘์ง€๋งŒ, ์‹คํŒจ์œ„ํ—˜์„ฑ์ด ๋‚ฎ๊ณ  ์‹œ์žฅ์ˆ˜์š”์— ์‹ ์†ํ•œ ๋Œ€์‘์ด ๊ฐ€๋Šฅํ•˜๊ธฐ ๋•Œ๋ฌธ์— ์ˆ˜์ต ์ฐฝ์ถœ์—๋Š” ๋” ์œ ๋ฆฌํ•œ ๊ฒƒ์œผ๋กœ ํŒ๋‹จ๋œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ๊ธฐ์ˆ ๊ฑฐ๋ž˜ ๋“ฑ ๊ฐœ๋ฐฉํ˜• ํ˜์‹ ์ด ํ™œ๋ฐœํ•˜๊ฒŒ ์ผ์–ด๋‚˜๋Š” ๊ธฐ์ˆ ์ƒํƒœ๊ณ„๋ฅผ ์กฐ์„ฑํ•˜๋Š” ๊ฒƒ์ด ์ค‘์†Œ๊ธฐ์—…์˜ ์žฌ๋ฌด์„ฑ๊ณผ ์ œ๊ณ ์— ํšจ๊ณผ์ ์ž„์„ ์‹ค์ฆ์ ์œผ๋กœ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ์œผ๋ฉฐ, ๊ธฐ์ˆ ๊ฑฐ๋ž˜์˜ ์„ฑ๊ณผ๋Š” ๊ฑฐ๋ž˜๋˜๋Š” ๊ธฐ์ˆ ์˜ ์ข…๋ฅ˜๋ณด๋‹ค๋Š” ๊ฑฐ๋ž˜๋˜๋Š” ๊ธฐ์ˆ ์˜ ์‹คํšจ์„ฑ ์œ ๋ฌด๊ฐ€ ๋” ์ค‘์š”ํ•˜๊ธฐ ๋•Œ๋ฌธ์— ์ค‘์†Œ๊ธฐ์—…์˜ ๊ธฐ์ˆ ์ˆ˜์š”๋ฅผ ์ •ํ™•ํ•˜๊ฒŒ ํŒŒ์•…ํ•˜๊ณ  ์‹คํšจ์„ฑ ์žˆ๋Š” ๊ณต๊ธ‰๊ธฐ์ˆ ๊ณผ ๋งค์นญํ•˜์—ฌ ๊ธฐ์ˆ ๊ฑฐ๋ž˜๋ฅผ ์ง€์›ํ•˜๋Š” ๊ฒƒ์ด ์ค‘์š”ํ•จ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค.์ œ 1 ์žฅ ์„œ ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ๊ณผ ๋ชฉ์  1 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ๋Œ€์ƒ ๋ฐ ๋ฐฉ๋ฒ• 4 ์ œ 2 ์žฅ ์ œ๋„ ๊ฐœ์š” ๋ฐ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  6 ์ œ 1 ์ ˆ IP์ธ์ˆ˜ ๋ฐ R&D๋ณด์ฆ ์ œ๋„์™€ ๊ตญ์ œํŠนํ—ˆ๋ถ„๋ฅ˜ 6 1. IP์ธ์ˆ˜๋ณด์ฆ ์ œ๋„ 6 2. R&D๋ณด์ฆ ์ œ๋„ 7 3. ๊ตญ์ œํŠนํ—ˆ๋ถ„๋ฅ˜(IPC) 9 ์ œ 2 ์ ˆ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  11 1. ๊ธฐ์ˆ ์‹œ์žฅ ํ˜„ํ™ฉ 11 2. ๊ธฐ์ˆ ๊ฑฐ๋ž˜ ํ™œ์„ฑํ™” ๋ฐฉ์•ˆ์— ๊ด€ํ•œ ์—ฐ๊ตฌ 13 3. ๊ธฐ์ˆ ์ด์ „ ์„ฑ๊ณผ์— ๊ด€ํ•œ ์—ฐ๊ตฌ 15 4. R&D ์ง€์›์„ฑ๊ณผ์— ๊ด€ํ•œ ์—ฐ๊ตฌ 18 ์ œ 3 ์žฅ ์—ฐ๊ตฌ์„ค๊ณ„ 20 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ๋ชจํ˜• 20 1. ์—ฐ๊ตฌ๊ฐ€์„ค๊ณผ ๋ถ„์„ํ‹€ 20 2. ๋ณ€์ˆ˜์˜ ์ •์˜ 22 ๊ฐ€. ๋…๋ฆฝ๋ณ€์ˆ˜ 22 ๋‚˜. ์ข…์†๋ณ€์ˆ˜ 27 ๋‹ค. ํ†ต์ œ๋ณ€์ˆ˜ 30 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ๋ฐฉ๋ฒ• 30 1. ๋ถ„์„๋Œ€์ƒ 30 2. ๋ถ„์„๋ฐฉ๋ฒ• 31 ๊ฐ€. ํ™•๋ฅ ํšจ๊ณผ ๋ชจํ˜• 32 ๋‚˜. ์„ฑํ–ฅ์ ์ˆ˜ ๋งค์นญ 33 ์ œ 4 ์žฅ ๋ถ„์„๊ฒฐ๊ณผ 36 ์ œ 1 ์ ˆ ๊ธฐ์ˆ ๊ฑฐ๋ž˜ ์ง€์›์˜ ์„ฑ๊ณผ 36 1. ๊ธฐ์ˆ ํ†ต๊ณ„๋Ÿ‰ 36 2. ์„ฑ์žฅ์„ฑ ์ง€ํ‘œ ๋ถ„์„๊ฒฐ๊ณผ 40 3. ์ˆ˜์ต์„ฑ ์ง€ํ‘œ ๋ถ„์„๊ฒฐ๊ณผ 44 4. ์•ˆ์ •์„ฑ ์ง€ํ‘œ ๋ถ„์„๊ฒฐ๊ณผ 48 ์ œ 2 ์ ˆ ๊ฑฐ๋ž˜๊ธฐ์ˆ ์˜ ๋ถ„์•ผ๋ณ„ ์„ฑ๊ณผ 50 1. ๊ธฐ์ˆ ํ†ต๊ณ„๋Ÿ‰ 50 2. ์„ฑ์žฅ์„ฑ ์ง€ํ‘œ ๋ถ„์„๊ฒฐ๊ณผ 51 3. ์ˆ˜์ต์„ฑ ์ง€ํ‘œ ๋ถ„์„๊ฒฐ๊ณผ 55 3. ์•ˆ์ •์„ฑ ์ง€ํ‘œ ๋ถ„์„๊ฒฐ๊ณผ 59 ์ œ 5 ์žฅ ๊ฒฐ๋ก  62 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ๊ฒฐ๊ณผ์˜ ์š”์•ฝ 62 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ์‹œ์‚ฌ์  63 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„ ๋ฐ ํ–ฅํ›„๊ณผ์ œ 67 ์ฐธ๊ณ ๋ฌธํ—Œ 69 Abstract 72์„

    ๊ฐ„ํก์ถฉ์—์„œ์˜ ํ”ผ๋‚ญ์œ ์ถฉ ์žฅ๊ธฐ ๋ณด์กด์— ๋Œ€ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์˜ํ•™๊ณผ ๊ธฐ์ƒ์ถฉํ•™์ „๊ณต,2004.Maste

    Tauroursodeoxycholic Acid Inhibits Nuclear Factor Kappa B Signaling in Gastric Epithelial Cells and Ameliorates Gastric Mucosal Damage in Mice

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    Background/Aims: Previous studies have reported the protective effects of tauroursodeoxycholic acid (TUDCA) on gastric epithelial cells in some animal models, but the precise mechanisms are unclear. This study examined the effects of TUDCA on NF-kappa B signaling in gastric epithelial cells. Moreover, the protective effects of TUDCA in experimental gastritis models induced by ethanol and NSAID were evaluated and compared with ursodeoxycholic acid (UDCA). Methods: After a pretreatment with TUDCA or UDCA, human gastric epithelial MKN-45 cells were stimulated with tumor necrosis factor (TNF)-alpha to activate NF-kappa B signaling. A real-time PCR (RT-PCR) for human interleukin (IL)-1 mRNA was performed. An electrophoretic mobility shift assay (EMSA) and immunoblot analyses were carried out. In murine models, after a pretreatment with TUDCA or UDCA, ethanol and indomethacin were administered via oral gavage. Macroscopic and microscopic assessments were performed to evaluate the preventive effects of TUDCA and UDCA on murine gastritis. Results: A pretreatment with TUDCA downregulated the IL-1 alpha mRNA levels in MKN-45 cells stimulated with TNF-alpha, as assessed by RT-PCR. As determined using EMSA, a pretreatment with TUDCA reduced the TNF-alpha-induced NF-kappa B DNA binding activity. A pretreatment with TUDCA inhibited I kappa B alpha phosphorylation induced by TNF-alpha, as assessed by immunoblot analysis. TUDCA attenuated the ethanol-induced and NSAID-induced gastritis in murine models, as determined macroscopically and microscopically. Conclusions: TUDCA inhibited NF-kappa B signaling in gastric epithelial cells and ameliorated ethanol-and NSAID-induced gastritis in murine models. These results support the potential of TUDCA for the prevention of gastritis in humans.N
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