7 research outputs found

    ์™ธ๋ž€ ๊ด€์ธก๊ธฐ์˜ ์ด๋ก ์  ํ•ด์„ : ์•ˆ์ •์„ฑ ๋ฐ ์„ฑ๋Šฅ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2014. 8. ์‹ฌํ˜•๋ณด.This dissertation provides the stability and performance analysis of the disturbance observer and proposes several design methods for guaranteeing the robust stability and for enhancing the disturbance rejection performance. Compared to many success stories in industry, theoretic analysis on the disturbance observer itself has attracted relatively little attention. In order to enlarge the horizon of its applications, we provide some rigorous analysis both in the frequency and time domain. In the frequency domain, we focus on two main issues: disturbance rejection performance and robust stability. In spite of its powerful ability for disturbance rejection, the conventional disturbance observer rejects the disturbance approximately rather than asymptotically. To enhance the disturbance rejection performance, based on the well-known internal model principle, we propose a design method to embed an internal model into the disturbance observer structure for achieving the asymptotic disturbance rejection and derive a condition for robust stability. Thus, the proposed disturbance observer can reject not only approximately the unmodeled disturbances but also asymptotically the disturbances of sinusoidal or polynomial-in-time type. In addition, a constructive design procedure to satisfy the proposed stability condition is presented. The other issue is to design of the disturbance observer based control system for guaranteeing robust stability under plant uncertainties. We study the robust stability for the case that the relative degree of the plant is not exactly known and so it happens to be different from that of nominal model. Based on the above results, we propose a universal design method for the disturbance observer when the relative degree of the plant is less than or equal to 4. Moreover, from the observation about the role of each block, we generalize the design of disturbance observer and propose a reduced order type-k disturbance observer to improve the disturbance rejection performance and to reduce the design complexity simultaneously. As a counterpart of the frequency domain analysis, we analyze the disturbance observer in the state space for the purpose of extending the horizon of the disturbance observer applications and obtaining the deeper understanding of the role of each block. Based on the singular perturbation theory, it reveals not only well-known properties but also interesting facts such as the peaking in the transient response. Moreover, we investigate robust stability of the disturbance observer based control systems with and without unmodeled dynamics and derive an explicit relation between the nominal performance recovery and the time constant of Q-filter. Since the classical linear disturbance observer does not ensure the recovery of transient response, a nonlinear disturbance observer, in which all the benefits of the classical one are still preserved, is presented for guaranteeing the recovery of transient as well as steady-state response.Abstract List of Figures Symbols and Acronyms 1. Introduction 1.1 Motivation 1.2 Contributions and Outline of the Dissertation 2. Robust Stability for Closed-loop System with Disturbance Observer 2.1 Structure of Disturbance Observer 2.2 Robust Stability Condition for Closed-loop System with Disturbance Observer 2.3 Illustrative Example 3. Embedding Internal Model in Disturbance Observer with Robust Stability 3.1 Design Method for Embedding Internal Model of Disturbance 3.2 Design of Q-filter for Guranteeing Robust Stability 3.2.1 Robust Stability Condition of Closed-loop System 3.2.2 Selecting a_i's for Robust Stability 3.3 Illustrative Example 3.4 Discussions on Robustness 3.4.1 Pros and Cons of Proposed Design Procedure 3.4.2 Bode Diagram Approach 4. Disturbance Observer with Unknown Relative Degree of the Plant 4.1 Robust Stability 4.2 A Guideline for Selecting Q and P_n 4.2.1 A Universal Robust Controller 4.3 Technical Proofs 4.4 Illustrative Examples 5. Reduced Order Type-k Disturbance Observer under Generalized Q-filter 5.1 Concept of Disturbance Observer with Generalized Q-filter Structure 5.2 Robust Stability 5.3 Reduced Order Type-k Disturbance Observer 5.4 Illustrative Examples 6. State Space Analysis of Disturbance Observer 6.1 State Space Realization of Disturbance Observer 6.2 Analysis of Disturbance Observer based on Singular Perturbation Theory 6.3 Discussion on Disturbance Observer Approach 6.3.1 Relation of Robust Stability Condition between State Space and Frequency Domain Approach 6.3.2 Effect of Zero Dynamics 6.3.3 Stability of Nominal Closed-loop System 6.3.4 Infinite Gain Property with p-dynamics 6.3.5 Peaking in Fast Transient 6.4 Nominal Performance Recovery with respect to Time Constant of Q-filter 7. Nominal Performance Recovery and Stability Analysis of Disturbance Observer under Unmodeled Dynamics 7.1 Problem Formulation 7.2 Stability and Performance Analysis based on Singular Perturbation Theory 7.2.1 Nominal Performance Recovery 7.2.2 Multi-time-scale Singular Perturbation Analysis 7.3 Nominal Performance Recovery by Disturbance Observer under Unmodeled Dynamics 8. Extensions of Disturbance Observer for Guaranteeing Robust Transient Performance 8.1 Extensions to MIMO Nonlinear Systems 8.1.1 SISO Nonlinear Disturbance Observer with Nonlinear Nominal Model 8.1.2 MIMO Nonlinear Disturbance Observer with Linear Nominal Model 9. Conclusions Appendix Bibliography ๊ตญ๋ฌธ์ดˆ๋กDocto

    Suicide Related Indicators and Trends in Korea in 2017

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    Suicide is a major public health issue that causes over 800,000 deaths each year globally. Korea ranks high in suicide rates, in which around 24.3 per 100,000 individuals are reported to have died by intentional self-harm in 2017 according to Statistics Korea. The aim of this study was to examine the current status and trend of suicide ideation and attempt using data from the following five sources: Korean National Health and Nutrition Examination (KNHANES, โ€˜07โ€“13, โ€˜15โ€“17), Korean Community Health Survey (KCHS, โ€˜08โ€“09, โ€™13, โ€™17), Korean Wealth Panel Study (KOWEPS, โ€˜12โ€“17), Korea Health Panel Survey (KHP, โ€˜10โ€“13), and Statistics Korea (1983โ€“2017). Suicide ideation and attempts were also further examined based on equalized household income levels. Data published by Statistics Korea were used to show the updated suicide rate and number of deaths by intentional self-harm. The rate of suicide ideation at the recent year was 4.73% (KNHANES, โ€˜17), 6.96% (KCHS, โ€˜17), 1.63% (KOWEPS, โ€˜17), and 5.39% (KHP, โ€˜13). That of suicide attempts as recent year was 0.71% (KNHANES, โ€˜17), 0.32% (KCHS, โ€˜17), and 0.09% (KOWEPS, โ€˜17). Annual percentage change of suicidal ideation was -15.4% (KNHANES, โ€˜07โ€“17), -2.5% (KCHS, โ€˜08โ€“17), -8.6% (KOWEPS, โ€˜12โ€“17), and -10.9% (KHP, โ€˜10โ€“13). Annual percentage change of suicide attempts was -4.0% (KNHANES, โ€˜07โ€“17), -4.4% (KCHS, โ€˜08โ€“17), and -14.9% (KOWEPS, โ€˜12โ€“17). Individuals with lower income levels were more likely to experience suicide ideation and attempts. Considering that Korea still shows a high suicide rate despite the continuously decreasing trend of suicide ideation and attempt, continuous observation and appropriate policy implementation regarding suicide related problems are necessary.open22Nkc

    College Alcohol Study for Alcohol-Related Behaviors and Problems

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    Background: In this study, we aimed to investigate the drinking behaviors and drinking-related problems of college students in South Korea to produce national alcohol statistics. Methods: We carefully examined the questionnaires and previous research developed in the previous research project and selected questions that reflect the special environment and culture of college students. In order to stratify a nationally representative sample of college students, the distribution of students around the country were found through the educational statistics database of the Korea Educational Development Institute. Based on this information, we conducted a survey in collaboration with Gallup (Korea) to survey and analyze the drinking behaviors of 5,024 Korean students. Results: A nationwide cross-sectional survey was conducted in 2017, for Korean college students. A total of 5,024 students were recruited and analyzed. The monthly drinking rate was 78.0% for male students and 72.9% for female students. The high-risk drinking rate was 23.3% for male students and 17.2% for female students. The most popular category for number of drinks per drinking session was โ€˜more than 10 glassesโ€™ per drinking session for both male (44.1%) and female (32.8%). On the alcohol use disorders identification test, the greatest proportion of male students were in the high-risk drinking category (score 8 to 15) 43.8%, followed by the โ€˜low-risk drinkingโ€™ (score 0 to 7) in 43.6%, โ€˜alcohol abuseโ€™ (score 16 to 19) 7.2%, and โ€˜alcohol dependenceโ€™ (greater than 20) 5.4% categories, respectively. For female students, the greatest proportion of female students were in the โ€˜low-risk drinkingโ€™ in 49.6%, followed by โ€˜high-risk drinkingโ€™ 37.1%, โ€˜alcohol abuseโ€™ 8.4%, and โ€˜alcohol dependenceโ€™ 4.9% categories, respectively. Conclusion: The results of the study showed that the drinking behavior of Korean college students was excessive. Overall, it was found that the college population has a greater high-risk drinking behaviors than general adult population. Furthermore, these problem drinking behaviors were prominent among female college students. Results from the present study suggest that it is necessary to monitor the drinking behavior of college students with constant interest and to prepare policies and strategies suitable for these circumstances.restriction22Nkc

    ๋ฏธ๊ตญ, ์œ ๋Ÿฝ์—ฐํ•ฉ, ์ค‘๊ตญ, ํ•œ๊ตญ์„ ์ค‘์‹ฌ์œผ๋กœ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :ํ–‰์ •๋Œ€ํ•™์› ํ–‰์ •ํ•™๊ณผ(์ •์ฑ…ํ•™์ „๊ณต),2020. 2. ๊ตฌ๋ฏผ๊ต.๋ณธ ์—ฐ๊ตฌ๋Š” ๋ฏธ๊ตญ, ์œ ๋Ÿฝ์—ฐํ•ฉ, ์ค‘๊ตญ, ํ•œ๊ตญ ๋“ฑ ์ฃผ์š”๊ตญ์˜ ํ•ด์™ธ์ง๊ตฌ ๊ด€๋ จ ๊ทœ์ œ์ •์ฑ…์„ ์‚ดํŽด๋ณด๊ณ  ๊ทœ์ œ ํŽธ์ฐจ๋ฅผ ๊ฐ€์ง€๊ณ  ์˜ค๋Š” ์›์ธ์ด ๋ฌด์—‡์ธ์ง€ ๋ถ„์„ํ•˜๋Š” ๊ฒƒ์ด ๋ชฉ์ ์ด๋‹ค. ํ•ด์™ธ์ง๊ตฌ์— ๋Œ€ํ•œ ๊ทœ์ œ์ •์ฑ…์ด ๊ตญ๊ฐ€๋ณ„๋กœ ๋‹ค์–‘ํ•œ ์–‘์ƒ์„ ๋ ๋Š” ์›์ธ์„ ํ•˜๋‚˜์˜ ์ผ๊ด€๋œ ๋ถ„์„์ฒด๊ณ„๋กœ ๋ถ„์„ํ•˜๊ธฐ ์œ„ํ•ด, ์ด์ต์ง‘๋‹จ์˜ ์ •์น˜ยท๊ฒฝ์ œ์  ์ƒํ™ฉ๊ณผ ๊ทœ์ œ๊ธฐ๊ด€์˜ ๊ทœ์ œ ๋ชฉ์ ์„ ๋™์ผํ•œ ์ฐจ์›์—์„œ ๋ถ„์„ํ•  ์ˆ˜ ์žˆ๋Š” Wilson์˜ ๊ทœ์ œ์ •์น˜ ๋ชจํ˜•์„ ๋ถ„์„ํ‹€๋กœ ์‚ฌ์šฉํ•˜์˜€๋‹ค. ์˜จ๋ผ์ธ ์‡ผํ•‘๋ชฐ ์‚ฌ์—…์ž์™€ ๊ธฐ์กด์˜ ์†Œ๋งค์—…์ž๋ฅผ ํ•ด์™ธ์ง๊ตฌ ๊ด€๋ จ ๊ทœ์ œ์™„ํ™”๋ฅผ ๋‘˜๋Ÿฌ์‹ผ ์ฃผ์š” ์ด์ต์ง‘๋‹จ์œผ๋กœ ์„ ์ •ํ•˜๊ณ , ์ด๋“ค์ด ์ธ์ง€ํ•˜๋Š” ํŽธ์ต๊ณผ ๋น„์šฉ์˜ ๋ถ„ํฌ๋ฅผ ํ†ตํ•ด ๊ฐ ๊ตญ์˜ ๊ทœ์ œ์˜ ๋ฐฉํ–ฅ์„ ์˜ˆ์ธกํ•˜์˜€๋‹ค. ์˜จ๋ผ์ธ ์†Œ๋งค์‹œ์žฅ์˜ ์‹œ์žฅ์ง‘์ค‘๋„๊ฐ€ ๋†’์€ ๋ฏธ๊ตญ๊ณผ ์ค‘๊ตญ์˜ ๊ฒฝ์šฐ ํ•ด์™ธ์ง๊ตฌ ๊ด€๋ จ ๊ทœ์ œ๋ฅผ ์™„ํ™”ํ•  ๋•Œ ๋ชจ๋‘ ๊ณ ๊ฐ ์ •์น˜์  ์ƒํ™ฉ์ด ๋ฐœ์ƒํ•  ๊ฒƒ์ด๋ผ๊ณ  ์˜ˆ์ธกํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์˜จ๋ผ์ธ ์†Œ๋งค์‹œ์žฅ์˜ ์‹œ์žฅ์ง‘์ค‘๋„๊ฐ€ ๋‚ฎ์€ ์œ ๋Ÿฝ์—ฐํ•ฉ๊ณผ ํ•œ๊ตญ์˜ ๊ฒฝ์šฐ ๊ทœ์ œ๋ฅผ ์™„ํ™”ํ•  ๋•Œ ๊ฐ๊ฐ ๊ธฐ์—…๊ฐ€ ์ •์น˜, ๋Œ€์ค‘ ์ •์น˜์  ์ƒํ™ฉ์ด ๋ฐœ์ƒํ•  ๊ฒƒ์ด๋ผ๊ณ  ์˜ˆ์ธกํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๊ฐ ๊ตญ์˜ ๊ทœ์ œํ˜„์‹ค์„ ๋ถ„์„ํ•œ ๊ฒฐ๊ณผ ํ•ด์™ธ์ง๊ตฌ ๊ด€๋ จ ๊ทœ์ œ์ •์ฑ…์˜ ํŽธ์ฐจ๋ฅผ ํŒŒ์•…ํ•˜๋Š” ๋ฐ ์žˆ์–ด Wilson์˜ ๊ทœ์ œ์ •์น˜ ๋ชจํ˜•์€ ๋Œ€์ฒด๋กœ ํ˜„์‹ค ์„ค๋ช…๋ ฅ์ด ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋“œ๋Ÿฌ๋‚ฌ๋‹ค. ๋ฏธ๊ตญ์€ ์˜จ๋ผ์ธ ์‡ผํ•‘๋ชฐ ์‚ฌ์—…์ž๊ฐ€ ๋†’์€ ์ˆ˜์ต์„ฑ์„ ๋ณด์žฅ๋ฐ›๊ณ  ์žˆ์—ˆ๊ณ  ์ด๋“ค์ด ๊ทœ์ œ๊ธฐ๊ด€์„ ํฌํšํ•  ๊ฐ€๋Šฅ์„ฑ์ด ๋†’์€ ๊ฒƒ์œผ๋กœ ๋“œ๋Ÿฌ๋‚ฌ์œผ๋ฉฐ ๊ทœ์ œ๊ธฐ๊ด€์˜ ์ •์ฑ…๋ชฉํ‘œ์™€ ํšจ๊ณผ๊ฐ€ ๋ถˆ์ผ์น˜ํ•˜๋Š” ๋“ฑ ์ „ํ˜•์ ์ธ ๊ณ ๊ฐ ์ •์น˜ ์œ ํ˜•์˜ ๊ทœ์ œํ˜„์‹ค์ด ์šฐ์„ธํ•˜์˜€๋‹ค. ํ•œ๊ตญ์€ ์–ธ๋ก  ๋“ฑ ๊ณต์ต์ง‘๋‹จ์œผ๋กœ๋ถ€ํ„ฐ ๊ทœ์ œ์™„ํ™”์˜ ํ•„์š”์„ฑ์ด ์ œ๊ธฐ๋˜์—ˆ๊ณ  ์ด๋ฅผ ํ†ตํ•ด ๊พธ์ค€ํžˆ ๊ทœ์ œ์™„ํ™”์— ๋Œ€ํ•œ ์—ฌ๋ก ์ด ํ˜•์„ฑ๋˜์–ด ์™”์œผ๋ฉฐ ์ด๋ฅผ ์ •์ฑ…์œผ๋กœ ์‹คํ˜„ํ•ด ๋‚ผ ์ˆ˜ ์žˆ๋Š” ๊ธฐ์—…๊ฐ€์  ์ •์น˜์ธ์ด ์กด์žฌํ•˜๋Š” ๋“ฑ ๋Œ€์ค‘ ์ •์น˜ ์œ ํ˜•์˜ ๊ทœ์ œํ˜„์‹ค์ด ๋ฐœ์ƒํ•˜์˜€๋‹ค. ์œ ๋Ÿฝ์—ฐํ•ฉ์€ ๊ธฐ์—…๊ฐ€ ์ •์น˜ ์œ ํ˜•์—์„œ ๊ฐ€์žฅ ์ค‘์š”ํ•œ ์กฐ๊ฑด์ธ ๊ธฐ์—…๊ฐ€์  ์ •์น˜์ธ์˜ ๋ถ€์žฌ๋กœ ์ธํ•ด ํ˜„์‹ค์—์„œ ํ•ด๋‹น ์ •์น˜ ์œ ํ˜•์˜ ํŠน์ง•์„ ์ฐพ์•„๋ณผ ์ˆ˜ ์—†์—ˆ๋‹ค. ์˜คํžˆ๋ ค ๊ธฐ์กด์˜ ์†Œ๋งค์—…์ž์—๊ฒŒ ํŽธ์ต์ด ์ง‘์ค‘๋˜์–ด ์ด๋“ค์˜ ๋†’์€ ์ˆ˜์ต์ด ๋ณด์žฅ๋˜๊ณ  ์ด๋“ค์ด ๊ทœ์ œ๊ธฐ๊ด€์— ๊ฐ•๋ ฅํ•œ ์˜ํ–ฅ๋ ฅ์„ ํ–‰์‚ฌํ•˜๋Š” ๊ณ ๊ฐ ์ •์น˜ ์œ ํ˜•์˜ ๊ทœ์ œ์ •์น˜๊ฐ€ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ค‘๊ตญ๊ณผ ๊ฐ™์ด ํŠน์ˆ˜ํ•œ ์ •์น˜์ฒด์ œ์˜ ๊ฒฝ์šฐ ์ด์ต์ง‘๋‹จ ๊ฐ„์˜ ๊ฐˆ๋“ฑ์„ ๋ฏผ์ฃผ์  ์˜์‚ฌ๊ฒฐ์ • ๊ณผ์ •์„ ๊ฑฐ์ณ ํ•ด๊ฒฐํ•˜๋Š” ๊ฒƒ์„ ์ƒ์ •ํ•œ ๊ทœ์ œ์ •์น˜ ๋ชจํ˜•์€ ํ˜„์‹ค ์„ค๋ช…๋ ฅ์ด ๋ถ€์กฑํ•œ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์˜ ๊ฒฐ๊ณผ๋Š” ์ถ”ํ›„ ์šฐ๋ฆฌ๋‚˜๋ผ์˜ ์—ญ์ง๊ตฌ ํ™œ์„ฑํ™” ๋ฐฉ์•ˆ๊ณผ ๊ตญ๋‚ด ๊ทœ์ œ์˜ ์ง€ํ–ฅ์ ์— ๋Œ€ํ•ด ์ •์ฑ…์  ์‹œ์‚ฌ์ ์„ ์ œ๊ณตํ•œ๋‹ค. ์ˆ˜์ž…๊ตญ์˜ ์˜จ๋ผ์ธ ์‡ผํ•‘๋ชฐ ์‚ฌ์—…์ž์™€ ๊ธฐ์กด์˜ ์†Œ๋งค์—…์ž์˜ ํ•ด์™ธ์ง๊ตฌ ๊ด€๋ จ ๊ทœ์ œ์™„ํ™”์— ๋”ฐ๋ฅธ ํŽธ์ต๊ณผ ๋น„์šฉ์˜ ์ง‘์ค‘๋„๋ฅผ ์•Œ ์ˆ˜ ์žˆ๋‹ค๋ฉด ์ด๋ฅผ ํ†ตํ•ด ํ•ด๋‹น๊ตญ ๊ทœ์ œ์ •์ฑ…์˜ ์œ ํ˜•์„ ์˜ˆ์ธกํ•˜๊ณ  ๊ฐ ์œ ํ˜•์˜ ์ด๋ก ์  ํŠน์ง•์— ์ž…๊ฐํ•œ ๋งž์ถค ์—ญ์ง๊ตฌ ์ „๋žต์„ ์ˆ˜๋ฆฝํ•  ์ˆ˜ ์žˆ๋‹ค. ๊ตญ๋‚ด์ ์œผ๋กœ๋Š” ํ•ด์™ธ์ง๊ตฌ ๊ด€๋ จ ๊ทœ์ œ์™„ํ™”์— ๋”ฐ๋ฅธ ์ธ์ง€๋œ ํŽธ์ต๊ณผ ๋น„์šฉ์˜ ๋ณ€ํ™” ์ถ”์ด๋ฅผ ํ†ตํ•ด ๋ฐ”๋žŒ์งํ•œ ๊ทœ์ œ์˜ ๋ฐฉํ–ฅ์„ ์„ค์ •ํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋‹ค.The purpose of this study is to examine the regulatory policies related to overseas direct purchase in major countries such as the United States, the European Union, China and South Korea, and to analyze the causes of regulatory divergence. J.Q. Wilsons Regulatory Politics Model was used as an analysis framework in order to explore the causes of regulatory divergence of countries on overseas direct purchase. The online retailers and offline retailers were selected as the main interest groups of deregulation on overseas direct purchase. The direction of regulation in each country was predicted through the distribution of their perceived benefits and costs. In the US and China, where the online retail market is highly concentrated, it was hypothesized that client-political situations will occur when the regulations alleviated. In the EU and South Korea, where the online retail market is not concentrated, it was hypothesized that mitigation would result in entrepreneurial-political and majoritarian-political situations, respectively. Wilsons model of regulatory politics has generally been able to explain divergent reality of regulatory policies related to overseas direct purchase. Client-political situations prevailed in the US and majoritarian-political situations in South Korea, as predicted by the model. In the US, online retailers were found to be highly profitable and likely to capture regulators, while regulators policy objectives were inconsistent with reality. In South Korea, it was found that public interest groups such as the media advocated deregulation, public opinion on deregulation has been steadily formed and entrepreneurial politicians carried out the policy. In the EU, entrepreneurial-political situations were not found because of the absence of entrepreneurial politicians. Instead, this absence led to client politics, such as highly profitable offline retailers and their strong influences on regulators. In the case of a non-democratic regime such as China, the model, which assumes that conflicts are resolved through democratic decision-making process, was found to lack reality. This study provides policy suggestions on regulating overseas direct purchase and overseas direct sale. If you know the distribution of perceived benefits and costs of online and offline retailers in importing countries, you can develop a tailored strategy based on the theoretical characteristics of each regulatory politics predicted by the model. Domestically, studying the changes of perceived benefits and costs of interest groups will help set the direction of regulations in the most desirable way.์ œ 1 ์žฅ ์„œ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  1 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ฐฉ๋ฒ• ๋ฐ ๊ตฌ์„ฑ 4 ์ œ 2 ์žฅ ์ด๋ก ์  ๋ฐฐ๊ฒฝ ๋ฐ ๋ถ„์„ํ‹€ 7 ์ œ 1 ์ ˆ ์ด๋ก ์  ๋ฐฐ๊ฒฝ 7 1. ํ•ด์™ธ์ง๊ตฌ์˜ ๋ฒ•์  ์ง€์œ„ 7 2. ํ•ด์™ธ์ง๊ตฌ์˜ ๊ทœ์ œ ๋ฐฉ๋ฒ• 11 ์ œ 2 ์ ˆ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  14 ์ œ 3 ์ ˆ ๋ถ„์„ํ‹€ 19 1. ๊ทœ์ œ์ •์น˜ ๋ชจํ˜• 19 2. ๊ทœ์ œ์™„ํ™”์ •์น˜ ๋ชจํ˜• 22 3. ๊ฐ€์„ค ์„ค์ • 26 ์ œ 3 ์žฅ ๋†’์€ ์‹œ์žฅ์ง‘์ค‘๋„ ๊ตญ๊ฐ€ ๋ถ„์„ 31 ์ œ 1 ์ ˆ ๋ฏธ๊ตญ 31 1. ์ธ์ง€๋œ ํŽธ์ต๊ณผ ๋น„์šฉ์˜ ๋ถ„ํฌ 31 2. ํ•ด์™ธ์ง๊ตฌ ๊ด€๋ จ ๊ทœ์ œ์ •์ฑ… 34 ์ œ 2 ์ ˆ ์ค‘๊ตญ 41 1. ์ธ์ง€๋œ ํŽธ์ต๊ณผ ๋น„์šฉ์˜ ๋ถ„ํฌ 41 2. ํ•ด์™ธ์ง๊ตฌ ๊ด€๋ จ ๊ทœ์ œ์ •์ฑ… 43 ์ œ 3 ์ ˆ ์†Œ๊ฒฐ 47 ์ œ 4 ์žฅ ๋‚ฎ์€ ์‹œ์žฅ์ง‘์ค‘๋„ ๊ตญ๊ฐ€ ๋ถ„์„ 51 ์ œ 1 ์ ˆ ์œ ๋Ÿฝ์—ฐํ•ฉ 51 1. ์ธ์ง€๋œ ํŽธ์ต๊ณผ ๋น„์šฉ์˜ ๋ถ„ํฌ 51 2. ํ•ด์™ธ์ง๊ตฌ ๊ด€๋ จ ๊ทœ์ œ์ •์ฑ… 55 ์ œ 2 ์ ˆ ํ•œ๊ตญ 61 1. ์ธ์ง€๋œ ํŽธ์ต๊ณผ ๋น„์šฉ์˜ ๋ถ„ํฌ 61 2. ํ•ด์™ธ์ง๊ตฌ ๊ด€๋ จ ๊ทœ์ œ์ •์ฑ… 63 ์ œ 3 ์ ˆ ์†Œ๊ฒฐ 70 ์ œ 5 ์žฅ ๊ฒฐ๋ก  74 ์ฐธ๊ณ ๋ฌธํ—Œ 81 Abstract 91Maste

    ๋…ธ์ธ์žฅ๊ธฐ์š”์–‘๋ณดํ—˜ ์น˜๋งคํŠน๋ณ„๋“ฑ๊ธ‰ ๋„์ž…์— ๋”ฐ๋ฅธ ๊ฒฝ์ฆ ์น˜๋งค๋…ธ์ธ์˜ ์ธ์ง€๊ธฐ๋Šฅ, ์‹ ์ฒด๊ธฐ๋Šฅ์˜ ๋ณ€ํ™”

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    ๋ณด๊ฑดํ•™๊ณผBackground: Non-pharmacological approaches, including cognitive function training, are available to help elderly people with early stage dementia, rendering a promising approach to delaying deterioration in function. Korea introduced the special dementia rating (grade 5) in July 2014, to provide cognitive training services to elderly people with dementia who require a minor need for long-term care. This study investigated changes in cognitive and physical functions among the elderly with mild dementia associated with the introduction of special dementia rating. Materials and Methods: The data evaluated in this study were derived from the Korean National Health Insurance Service-Elderly Cohort (NHIS-EC) database between 2008 and 2015. A total of 2304 subjects were selected for the study, including 352 in the intervention group and 1952 in control groups (control 1 [extra-grade dementia]: 337 subjects, control 2 [grade 4 dementia]: 1615 subjects). The subjects in the intervention group were beneficiaries who received the special dementia rating after its introduction in July 2014 and who maintained the same rating until 2015. The control 1 group was composed of extra grade elderly dementia patients identified as having similar long-term care needs as the intervention group, with better cognitive function than subjects in the intervention group but without use of long-term care services due to being assessed as requiring little need for long-term care services in both 2014 and 2015. The control 2 group was composed of dementia patients who were identified as grade 4 patients in both 2014 and 2015 and who had similar baseline cognitive function scores to those in the intervention group. The dependent variables were cognitive function, problem behavior, instrumental activities of daily living, and activities of daily living scores. Each score was calculated as the sum of each item, with higher scores suggesting more severe status. Using a difference-in-differences analysis, we compared changes in each score in intervention vs control groups from pre- (2014) and post- (2015) introduction of the special dementia rating. We estimated an interaction term between post-introduction and intervention group, and then we applied generalized estimating equations (GEE) to the data. Results: The introduction of special dementia rating had a positive impact on changes in cognitive function and instrumental activities of daily living. The mean cognitive function scores pre- and post-introduction were 43.34 and 45.60, respectively, in the intervention group and 31.61 and 37.82, respectively, in the control 1 group. The mean instrumental activities of daily living score pre- and post-introduction were 19.93 and 20.58, respectively, in the intervention group and 16.76 and 18.17, respectively, in the control 1 group. The introduction of special dementia rating was associated with significantly less cognitive and physical function decline in the intervention group than in the control groups which was not related to the provision of the cognitive training service by the introduction of special dementia rating (cognitive function: ฮฒ = โ€“3.39, SE = 1.14, P = 0.0029; instrumental activities of daily living: ฮฒ = โ€“0.75, SE = 0.23, P = 0.0010). This positive effect increased if subjects were in the youngest group, in the low income bracket, had a caregiver, were helped in multiple ways by the caregiver, or were not living alone. For the control 2 group, the mean cognitive function score of pre- and post-introduction was 43.34 and 45.60 among intervention group and 42.81 and 46.16 among control 2 group. Neither cognitive nor physical functions were associated with positive effects of the introduction of special dementia rating. (cognitive function: ฮฒ = โ€“1.40, SE = 0.82, P = 0.0881). Positive results were observed in the subgroups including female, subjects in the low-income bracket, or elderly people living with others. Conclusions: The introduction of special dementia rating was associated with positive effects for changes in cognitive and physical function. Based on results of this study, we suggest that special dementia rating currently being offered to long-term care insurance beneficiaries should provide a comprehensive approach to help maintain not only cognitive function but also various other functions. In addition, the findings should increase interest in non-pharmacological approaches to the prevention of cognitive decline among elderly people with dementia and help to improve the management of dementia in Korea. ์„œ๋ก : ์ธ์ง€๊ธฐ๋Šฅํ›ˆ๋ จ๊ณผ ๊ฐ™์€ ์น˜๋งค์— ๋Œ€ํ•œ ๋น„์•ฝ๋ฌผ์  ์ ‘๊ทผ์€ ์ดˆ๊ธฐ๋‹จ๊ณ„ ์น˜๋งค๋…ธ์ธ์˜ ์ธ์ง€๊ธฐ๋Šฅ ์•…ํ™”๋ฅผ ์ง€์—ฐ์‹œํ‚ค๋Š” ๋“ฑ ๊ธ์ •์ ์ธ ํšจ๊ณผ๋ฅผ ์ค„ ์ˆ˜ ์žˆ๊ธฐ ๋•Œ๋ฌธ์— ์ตœ๊ทผ ๊ทธ ๊ด€์‹ฌ์ด ์ง‘์ค‘๋˜๊ณ  ์žˆ๋‹ค. ํ•œ๊ตญ์—์„œ๋Š” 2014๋…„ 7์›” ์žฅ๊ธฐ์š”์–‘๋ณดํ—˜ ๋‚ด์— ์น˜๋งคํŠน๋ณ„๋“ฑ๊ธ‰ (์žฅ๊ธฐ์š”์–‘ 5๋“ฑ๊ธ‰)์„ ์‹ ์„คํ•˜์—ฌ ์น˜๋งค๋ฅผ ์•“๊ณ  ์žˆ์ง€๋งŒ ์žฅ๊ธฐ์š”์–‘ ์š”๊ตฌ๋„๊ฐ€ ๊ฒฝ๋ฏธํ•˜์—ฌ ์žฅ๊ธฐ์š”์–‘์„œ๋น„์Šค๋ฅผ ์ด์šฉํ•  ์ˆ˜ ์—†๋˜ ๊ฒฝ์ฆ์น˜๋งค ๋…ธ์ธ๋“ค์„ ๋Œ€์ƒ์œผ๋กœ ์žฅ๊ธฐ์š”์–‘์„œ๋น„์Šค๋ฅผ ์ œ๊ณตํ•˜์˜€๋‹ค. ์„œ๋น„์Šค์˜ ์ฃผ๋œ ๋‚ด์šฉ์€ ์ธ์ง€๊ธฐ๋Šฅ ํ›ˆ๋ จ์ด๋ฉฐ ์˜๋ฌด์ ์œผ๋กœ ์„œ๋น„์Šค๋ฅผ ์ด์šฉํ•˜๋„๋ก ํ•˜์˜€๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ์น˜๋งคํŠน๋ณ„๋“ฑ๊ธ‰(๋…ธ์ธ์žฅ๊ธฐ์š”์–‘ 5๋“ฑ๊ธ‰) ๋„์ž…์— ๋”ฐ๋ฅธ ๊ฒฝ์ฆ ์น˜๋งค๋…ธ์ธ์˜ ์ธ์ง€๊ธฐ๋Šฅ, ์‹ ์ฒด๊ธฐ๋Šฅ์˜ ๋ณ€ํ™”๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ๋ฐฉ๋ฒ•: ์ด ์—ฐ๊ตฌ๋Š” ๊ตญ๋ฏผ๊ฑด๊ฐ•๋ณดํ—˜๊ณต๋‹จ์˜ ๋…ธ์ธ ์ฝ”ํ˜ธํŠธ ๋ฐ์ดํ„ฐ๋ฒ ์ด์Šค 2008-2015๋…„ ์ž๋ฃŒ๋ฅผ ์ด์šฉํ•˜์˜€๋‹ค. ์ค‘์žฌ์ง‘๋‹จ 352๋ช…, ํ†ต์ œ์ง‘๋‹จ 1,952๋ช… (ํ†ต์ œ์ง‘๋‹จ 1 = 337; ํ†ต์ œ์ง‘๋‹จ 2 = 1,615)์„ ํฌํ•จํ•˜์—ฌ ์ด 2,304๋ช…์„ ์—ฐ๊ตฌ๋Œ€์ƒ์ž๋กœ ์„ ์ •ํ•˜์˜€๋‹ค. ์ค‘์žฌ์ง‘๋‹จ์€ ์น˜๋งคํŠน๋ณ„๋“ฑ๊ธ‰์ œ ๋„์ž… ํ›„ ์ƒˆ๋กญ๊ฒŒ ์น˜๋งคํŠน๋ณ„๋“ฑ๊ธ‰ (5๋“ฑ๊ธ‰)์„ ๋ฐ›์€ ์žฅ๊ธฐ์š”์–‘๋ณดํ—˜ ์ˆ˜ํ˜œ์ž์ด๋ฉฐ 2015๋…„๊นŒ์ง€ ์น˜๋งคํŠน๋ณ„๋“ฑ๊ธ‰์„ ์œ ์ง€ํ•˜๊ณ  ์žˆ๋Š” ๋Œ€์ƒ์ž์ด๋‹ค. ํ†ต์ œ์ง‘๋‹จ์€ ๋‘ ์ง‘๋‹จ์„ ์„ ์ •ํ•˜์˜€๋Š”๋ฐ ํ†ต์ œ์ง‘๋‹จ 1์€ 2014๋…„๊ณผ 2015๋…„ ๋ชจ๋‘ ๋“ฑ๊ธ‰ ์™ธ ํŒ์ •์„ ๋ฐ›์•„ ์žฅ๊ธฐ์š”์–‘์„œ๋น„์Šค๋ฅผ ์ด์šฉํ•  ์ˆ˜ ์—†๋Š” ๋Œ€์ƒ์ž๋“ค ์ค‘ ์น˜๋งค๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ๋Š” ๋…ธ์ธ์ด๋‹ค. ํ†ต์ œ์ง‘๋‹จ 1์€ ์ค‘์žฌ์ง‘๋‹จ๊ณผ ๋น„์Šทํ•œ ์žฅ๊ธฐ์š”์–‘ ํ•„์š”๋„๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ์ง€๋งŒ ์ธ์ง€๊ธฐ๋Šฅ ์ ์ˆ˜๋Š” ์ค‘์žฌ์ง‘๋‹จ์— ๋น„ํ•ด ์–‘ํ˜ธํ•˜๋‹ค. ํ†ต์ œ์ง‘๋‹จ 2๋Š” 2014๋…„๊ณผ 2015๋…„ ๋ชจ๋‘ 4๋“ฑ๊ธ‰ ํŒ์ •์„ ๋ฐ›์€ ์žฅ๊ธฐ์š”์–‘๋ณดํ—˜ ์ˆ˜ํ˜œ์ž๋“ค ์ค‘ ์น˜๋งค๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ๋Š” ๋…ธ์ธ์ด๋ฉฐ ์ด๋“ค ์ค‘ ์ค‘์žฌ์ง‘๋‹จ์˜ 2014๋…„ ์ธ์ง€๊ธฐ๋Šฅ ์ ์ˆ˜ (baseline), ์„ฑ๋ณ„, ๋‚˜์ด๊ฐ€ ์œ ์‚ฌํ•œ ๋Œ€์ƒ์ž๋“ค๋กœ ๋งค์นญํ•˜์—ฌ ๋Œ€์ƒ์ž๋ฅผ ์„ ์ •ํ•˜์˜€๋‹ค. ๋‘๋ฒˆ์งธ ํ†ต์ œ ์ง‘๋‹จ์€ ์ค‘์žฌ์ง‘๋‹จ๊ณผ ์œ ์‚ฌํ•œ ์ธ์ง€๊ธฐ๋Šฅ ์ ์ˆ˜๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ์ง€๋งŒ ์ค‘์žฌ์ง‘๋‹จ์— ๋น„ํ•ด ์žฅ๊ธฐ์š”์–‘ ํ•„์š”๊ฐ€ ๋” ์š”๊ตฌ๋˜๋Š” ์ง‘๋‹จ์ด๋‹ค. ๊ฐ ๋Œ€์ƒ์ž๋“ค์€ 2014๋…„ (์น˜๋งคํŠน๋ณ„๋“ฑ๊ธ‰ ๋„์ž… ์ „ ๋“ฑ๊ธ‰ํŒ์ •์„ ๋ฐ›๊ธฐ ์œ„ํ•œ ์ธก์ • = ๋„์ž… ์ „ ์ ์ˆ˜)๊ณผ 2015๋…„ (๋„์ž… ํ›„ ์ ์ˆ˜) ๋ชจ๋‘ ๊ฐ ๋…„๋„์˜ ๋“ฑ๊ธ‰ ํ‰๊ฐ€๋ฅผ ๋ฐ›์œผ๋ฉด์„œ ์ธ์ง€๊ธฐ๋Šฅ๊ณผ ์‹ ์ฒด๊ธฐ๋Šฅ์ด ์ธก์ •๋˜์—ˆ๋‹ค. ๊ฐ ๊ธฐ๋Šฅ๋ณ„ ์ ์ˆ˜๋“ค์€ ๊ธฐ๋Šฅ ์ธก์ •์„ ์œ„ํ•œ ํ•ญ๋ชฉ๋“ค์˜ ์ ์ˆ˜์˜ ์ดํ•ฉ์œผ๋กœ ํ‰๊ฐ€ํ•˜์˜€์œผ๋ฉฐ, ์ ์ˆ˜๊ฐ€ ๋†’์„ ์ˆ˜๋ก ์ƒํƒœ๊ฐ€ ์‹ฌ๊ฐํ•จ์„ ์˜๋ฏธํ•œ๋‹ค. ์ด ์—ฐ๊ตฌ์˜ ์ข…์†๋ณ€์ˆ˜๋Š” ์ธ์ง€๊ธฐ๋Šฅ ์ ์ˆ˜, ๋ฌธ์ œํ–‰๋™ ์ ์ˆ˜, ๋„๊ตฌ์  ์ผ์ƒ์ƒํ™œ์ˆ˜ํ–‰๋Šฅ๋ ฅ ์ ์ˆ˜, ์ผ์ƒ์ƒํ™œ์ˆ˜ํ–‰๋Šฅ๋ ฅ ์ ์ˆ˜ ์ด๋‹ค. ์ด์ค‘์ฐจ์ด๋ถ„์„(difference-in-differences)์„ ์‚ฌ์šฉํ•˜์—ฌ ์ค‘์žฌ์ง‘๋‹จ๊ณผ ํ†ต์ œ์ง‘๋‹จ์—์„œ์˜ ์น˜๋งคํŠน๋ณ„๋“ฑ๊ธ‰ ๋„์ž… ์ „, ํ›„์˜ ๊ฐ ๊ธฐ๋Šฅ ์ ์ˆ˜๋“ค์˜ ๋ณ€ํ™”์˜ ์ฐจ์ด๋ฅผ ๋ถ„์„ํ•˜์˜€๊ณ , ์ด๋ฅผ ํ† ๋Œ€๋กœ ๋…ธ์ธ์žฅ๊ธฐ์š”์–‘๋ณดํ—˜ ์น˜๋งคํŠน๋ณ„๋“ฑ๊ธ‰ ๋„์ž…์ด ๊ฒฝ์ฆ์น˜๋งค ๋…ธ์ธ์˜ ์ธ์ง€๊ธฐ๋Šฅ๊ณผ ์‹ ์ฒด๊ธฐ๋Šฅ ๋ณ€ํ™”์— ๊ธ์ •์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์ณค๋Š”์ง€ ํ‰๊ฐ€ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ๊ฒฐ๊ณผ: ์น˜๋งคํŠน๋ณ„๋“ฑ๊ธ‰ ๋„์ž…์— ๋”ฐ๋ฅธ ์ธ์ง€๊ธฐ๋Šฅ ํ›ˆ๋ จ ์„œ๋น„์Šค ์ œ๊ณต์€ ์น˜๋งค๋…ธ์ธ์˜ ์ธ์ง€๊ธฐ๋Šฅ๊ณผ ๋„๊ตฌ์  ์ผ์ƒ์ƒํ™œ์ˆ˜ํ–‰๋Šฅ๋ ฅ์— ๊ธ์ •์ ์ธ ์˜ํ–ฅ์„ ์ค€ ๊ฒƒ์œผ๋กœ ๊ด€์ฐฐ๋˜์—ˆ๋‹ค. ์น˜๋งคํŠน๋ณ„๋“ฑ๊ธ‰ ๋„์ž… ์ „, ํ›„ ์ค‘์žฌ์ง‘๋‹จ์˜ ์ธ์ง€๊ธฐ๋Šฅ ํ‰๊ท ์ ์ˆ˜๋Š” 43.34์ ๊ณผ 45.60์  ์ด์—ˆ์œผ๋ฉฐ ํ†ต์ œ์ง‘๋‹จ 1์˜ ๋„์ž… ์ „, ํ›„ ํ‰๊ท ์ ์ˆ˜๋Š” 31.61์ ๊ณผ 37.82์  ์ด์—ˆ๋‹ค. ๋˜ํ•œ ์น˜๋งคํŠน๋ณ„๋“ฑ๊ธ‰ ๋„์ž… ์ „, ํ›„ ์ค‘์žฌ์ง‘๋‹จ์˜ ๋„๊ตฌ์  ์ผ์ƒ์ƒํ™œ ์ˆ˜ํ–‰๋Šฅ๋ ฅ ํ‰๊ท  ์ ์ˆ˜๋Š” 19.93์ ๊ณผ 20.58์  ์ด์—ˆ์œผ๋ฉฐ ํ†ต์ œ์ง‘๋‹จ 1์˜ ๋„์ž… ์ „, ํ›„ ํ‰๊ท  ์ ์ˆ˜๋Š” 16.76์ ๊ณผ 18.17์  ์ด์—ˆ๋‹ค. ์น˜๋งคํŠน๋ณ„๋“ฑ๊ธ‰ ๋„์ž…์— ๋”ฐ๋ฅธ ์ธ์ง€๊ธฐ๋Šฅ ํ›ˆ๋ จ ์„œ๋น„์Šค ์ œ๊ณต๊ณผ ๊ด€๋ จ์ด ์—†๋Š” ํ†ต์ œ ์ง‘๋‹จ 1์— ๋น„ํ•ด ์ค‘์žฌ ์ง‘๋‹จ์—์„œ ์ธ์ง€๊ธฐ๋Šฅ๊ณผ ๋„๊ตฌ์  ์ผ์ƒ์ƒํ™œ์ˆ˜ํ–‰๋Šฅ๋ ฅ์˜ ์•…ํ™”๊ฐ€ ๋œ ์ง„ํ–‰๋˜๋Š” ๊ฒƒ์œผ๋กœ ๊ด€์ฐฐ๋˜์—ˆ๋‹ค (์ธ์ง€๊ธฐ๋Šฅ: interaction effect = โ€“3.39, SE = 1.14, P = 0.0029; ๋„๊ตฌ์  ์ผ์ƒ์ƒํ™œ์ˆ˜ํ–‰๋Šฅ๋ ฅ: interaction effect = โ€“0.75, SE = 0.23, P = 0.0010). ํŠนํžˆ, ๋Œ€์ƒ์ž๊ฐ€ ์—ฐ๋ น์ด ์–ด๋ฆด์ˆ˜๋ก, ์ €์†Œ๋“ ๊ณ„์ธต์ผ์ˆ˜๋ก, ์ˆ˜๋ฐœ์ž๊ฐ€ ์žˆ๋Š” ๊ฒฝ์šฐ, ์ฃผ ์ˆ˜๋ฐœ์ž๋กœ๋ถ€ํ„ฐ ์ง€์›์„ ๋งŽ์ด ๋ฐ›์„์ˆ˜๋ก ๊ธ์ •์ ์ธ ํšจ๊ณผ๊ฐ€ ์ฆ๋Œ€๋˜์—ˆ๋‹ค. ํ†ต์ œ์ง‘๋‹จ 2์˜ ๊ฒฝ์šฐ, ์น˜๋งคํŠน๋ณ„๋“ฑ๊ธ‰ ๋„์ž… ์ „๊ณผ ๋„์ž… ํ›„ ์ค‘์žฌ์ง‘๋‹จ์˜ ์ธ์ง€๊ธฐ๋Šฅ ํ‰๊ท ์ ์ˆ˜๋Š” 42.81์ ๊ณผ 46.16์  ์ด์—ˆ๋‹ค. ์น˜๋งคํŠน๋ณ„๋“ฑ๊ธ‰ ๋„์ž…์— ๋”ฐ๋ฅธ ๊ฒฝ์ฆ ์น˜๋งค ๋…ธ์ธ์˜ ์ธ์ง€๊ธฐ๋Šฅ๊ณผ ์‹ ์ฒด๊ธฐ๋Šฅ ๋ณ€ํ™”์˜ ๊ธ์ •์ ์ธ ํšจ๊ณผ๋Š” ๊ด€์ฐฐ๋˜์ง€ ์•Š์•˜๋‹ค (์ธ์ง€๊ธฐ๋Šฅ: interaction effect = โ€“1.40, SE = 0.82, P = 0.0881). ํ•˜์ง€๋งŒ ํŠน์ • ํ•˜์œ„ ๊ทธ๋ฃน์—์„œ ํ†ต์ œ์ง‘๋‹จ 2์— ๋น„ํ•ด ์ค‘์žฌ ์ง‘๋‹จ์—์„œ ์ธ์ง€๊ธฐ๋Šฅ์˜ ์•…ํ™”๊ฐ€ ๋œ ์ง„ํ–‰๋˜์—ˆ์œผ๋ฉฐ, ์ด๋Ÿฌํ•œ ๊ธ์ •์ ์ธ ํšจ๊ณผ๋Š” ์—ฌ์„ฑ, ์ €์†Œ๋“ ๊ณ„์ธต, ๋น„๋…๊ฑฐ ๋…ธ์ธ ๊ทธ๋ฃน์—์„œ ๊ด€์ฐฐ๋˜์—ˆ๋‹ค. ๊ฒฐ๋ก : ์น˜๋งคํŠน๋ณ„๋“ฑ๊ธ‰ ๋„์ž…์„ ํ†ตํ•œ ์ธ์ง€๊ธฐ๋Šฅ ํ›ˆ๋ จ ์„œ๋น„์Šค ์ œ๊ณต์ด ๊ฒฝ์ฆ ์น˜๋งค๋…ธ์ธ์˜ ์ธ์ง€๊ธฐ๋Šฅ๊ณผ ๋„๊ตฌ์  ์ผ์ƒ์ƒํ™œ ์ˆ˜ํ–‰๋Šฅ๋ ฅ์˜ ์•…ํ™”๋ฅผ ์ง€์—ฐ์‹œํ‚ค๋Š” ๊ธ์ •์ ์ธ ํšจ๊ณผ๊ฐ€ ์žˆ์Œ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ด ์—ฐ๊ตฌ๊ฒฐ๊ณผ๋ฅผ ํ†ตํ•ด ๊ด€์ฐฐ๋œ ๊ธ์ •์ ์ธ ํšจ๊ณผ๊ฐ€ ์ปค์ง€๋Š” ์ง‘๋‹จ๋“ค์˜ ํŠน์„ฑ์„ ํ”„๋กœ๊ทธ๋žจ ์ œ๊ณต ์‹œ ๊ณ ๋ คํ•  ๊ฒƒ์„ ์ œ์•ˆํ•œ๋‹ค. ๋˜ํ•œ, ํ˜„์žฌ ์น˜๋งคํŠน๋ณ„๋“ฑ๊ธ‰ ์ˆ˜ํ˜œ์ž์—๊ฒŒ ์ œ๊ณต๋˜๊ณ  ์žˆ๋Š” ์ธ์ง€๊ธฐ๋Šฅ ํ›ˆ๋ จ ํ”„๋กœ๊ทธ๋žจ์ด ์ธ์ง€๊ธฐ๋Šฅ ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๋‹ค์–‘ํ•œ ์ธก๋ฉด์˜ ๊ธฐ๋Šฅ๋“ค์„ ํšจ์œจ์ ์œผ๋กœ ์œ ์ง€ํ•  ์ˆ˜ ์žˆ๋„๋ก ํ†ตํ•ฉ์ ์ธ ๊ด€์ ์—์„œ ์ œ๊ณต ๋˜์–ด์•ผ ํ•จ์„ ์ œ์•ˆํ•œ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ์ด ๊ฒฐ๊ณผ๋“ค์„ ํ†ตํ•ด ์น˜๋งค๋…ธ์ธ๋“ค์˜ ์ธ์ง€๊ธฐ๋Šฅ ๋ฐ ๋‹ค์–‘ํ•œ ๊ธฐ๋Šฅ ํ–ฅ์ƒ์„ ์œ„ํ•œ ๋น„์•ฝ๋ฌผ์  ์ ‘๊ทผ๊ณผ ๊ด€๋ จ๋œ ์—ฐ๊ตฌ๋“ค์ด ๋งŽ์ด ์ง„ํ–‰๋˜์–ด, ๊ตญ๊ฐ€ ์น˜๋งค๊ด€๋ฆฌ๋ฅผ ์œ„ํ•œ ๋‹ค์–‘ํ•˜๊ณ  ๋ฐœ์ „์ ์ธ ๊ทผ๊ฑฐ๋“ค์ด ์ œ์‹œ๋  ์ˆ˜ ์žˆ๊ธฐ๋ฅผ ๊ธฐ๋Œ€ ํ•œ๋‹ค.open๋ฐ•

    ์ž๊ฐ€๋ฐ˜์‘์„ฑ์— ๊ธฐ๋ฐ˜ํ•œ ํ•ญ์กด์  ์ œ 1 ์œ ํ˜• ์ธํ„ฐํŽ˜๋ก ์˜ naรฏve CD8+ T ์„ธํฌ ํ‘œํ˜„ํ˜• ๋ฐ ๊ธฐ๋Šฅ์˜ ๋‹ค์–‘์„ฑ ์กฐ์ ˆ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๋†์—…์ƒ๋ช…๊ณผํ•™๋Œ€ํ•™ ๋†์ƒ๋ช…๊ณตํ•™๋ถ€,2020. 2. ์œค์ฒ ํฌ.In a steady-state, naรฏve CD8+ T cells have been defined as a homogeneous population through low and high expression of CD44 and CD62L, respectively. However, recent studies have demonstrated that CD5hi naรฏve CD8+ T cells with a number of surface molecules being differently expressed consisted of heterogenic population. In the present study focused on Ly6C that is specifically expressed only on CD5hi naรฏve CD8+ T cells at steady-state mice. The Ly6C induction in CD8+ T cells is known to be increased by type I interferon (IFN). However, it needs to be further revealed how precisely generation of Ly6C+ naรฏve CD8+ T cells are regulated at molecular level in the extra-thymic environment at steady-state, and whether or not self-reactivity is involved in the generation of Ly6C+ naรฏve CD8+ T cells. Furthermore, it also remained to be uncovered whether the type I IFN induces not only the generation of Ly6C+ naรฏve CD8+ T cells but also functional features, such as clonal expansion and differentiation capacity, in acute viral infection. The results showed that constitutive type I IFN induced generation of Ly6C+ naรฏve CD8+ T cells in steady-state mice, in which the generation was enhanced by self-T cell receptor (TCR) engagement. The effect of constitutive type I IFN was most prominent for the naรฏve CD8+ T cell with higher intrinsic self-reactivity than lower counterpart, which is positively correlated to the expression level of CD5. Hence the greater heterogeneity has seen in CD5hi cells in the present study hinges on their particular attribute, namely heightened responsiveness to cytokines, especially type I IFN, and to high affinity of TCR contact with self-peptides. The results further suggested that the constitutive type I IFN signal influences not only the induction of Ly6C+ naรฏve CD8+ T cells but also their effector function-related genetic landscape (T-bet, Eomes, IL-18Rap, and CCL5) and pro-inflammatory cytokine production, especial to IFN-. Furthermore, Ly6C+ naรฏve CD8+ T cells favored to be differentiated into short-lived effector cell (SLEC) while CD5lo naรฏve CD8+ T cells favor memory precursor effector cell (MPEC) in lymphocytic choriomeningitis virus (LCMV) infection model. Same with the effector precursor differentiation, CD5lo naรฏve CD8+ T cells have generated more memory CD8+ T cells than Ly6C- or Ly6C+ naรฏve CD8+ T cells. Furthermore, by temporally blocking of interferon alpha receptor 1 (IFNAR1) in the steady-state mice, Ly6C+ naรฏve CD8+ T cells were increasingly differentiated into MPEC while reducing SLEC differentiation. It suggested that constitutive type I IFN exposed during steady-state can affect the fate decision of naรฏve CD8+ T cells between MPEC and SLEC in LCMV infection models. Collectively, this study demonstrated that the effect of constitutive type I IFN on naรฏve CD8+ T cells is closely related to its self-reactivity and directly affects their phenotype and effector function. Also type I IFN affected differentiation fate of naรฏve CD8+ T cells between SLEC and MPEC upon LCMV infection model. At the best of my knowledge, this is the first to demonstrate that the differentiation fate in infection had been pre-determined within naรฏve T cell phase dependent on type I IFN together with self-reactivity.๊ฐ์—ผ์ด๋‚˜ ์งˆ๋ณ‘์ด ์—†๋Š” ์ •์ƒ ์ƒํƒœ(steady-state condition)์—์„œ ์™ธ๋ถ€ ํ•ญ์›์„ ํ•œ๋ฒˆ๋„ ๊ฒฝํ—˜ํ•œ ์ ์ด ์—†๋Š” naรฏve CD8+ T ์„ธํฌ๋Š” ๊ฐ๊ฐ CD44 ๋ฐ CD62L์˜ ๋ฐœํ˜„ ์ •๋„๋ฅผ ํ†ตํ•ด CD44loCD62hi์˜ ํ‘œํ˜„ํ˜•์„ ๊ฐ€์ง€๋Š” ๊ท ์ผํ•œ ์ง‘๋‹จ์œผ๋กœ ์ •์˜๋  ์ˆ˜ ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ตœ๊ทผ์˜ ์—ฐ๊ตฌ๋“ค์—์„œ๋Š” naรฏve CD8+ T์„ธํฌ๋“ค์ด ์˜ˆ์ „ ์—ฐ๊ตฌ๋“ค์—์„œ ๋ณด๋„๋œ ๊ฒƒ๋ณด๋‹ค ๋” ๋‹ค์–‘ํ•œ ์„ธํฌ๋ง‰ ๋‹จ๋ฐฑ์งˆ๋“ค์„ ๋ฐœํ˜„ํ•˜๋Š” ๋ณต์žกํ•œ ์ง‘๋‹จ์œผ๋กœ ๊ตฌ์„ฑ๋˜์–ด ์žˆ๊ณ  CD5์˜ ๋ฐœํ˜„ ์ •๋„๋ฅผ ํ™œ์šฉํ•˜์—ฌ naรฏve CD8+ T ์„ธํฌ๋ฅผ ์„ฑ๊ฒฉ์ด ๋‹ค๋ฅธ CD5lo ์„ธํฌ ๋ฐ CD5hi ์„ธํฌ๋กœ ๊ตฌ๋ถ„ํ•  ์ˆ˜ ์žˆ๋‹ค๊ณ  ๋ณด๊ณ ํ•˜์˜€๋‹ค. ๋˜ํ•œ CD5hi ์„ธํฌ๊ฐ€ CD5lo ์„ธํฌ๋ณด๋‹ค ๋†’์€ ๋‹ค์–‘์„ฑ(heterogeneity)์„ ์ง€๋‹ˆ๋Š” ๋™์‹œ์— ๋ฐ•ํ…Œ๋ฆฌ์•„๋‚˜ ๋ฐ”์ด๋Ÿฌ์Šค ๊ฐ์—ผ์ƒํ™ฉ์—์„œ ๋” ๋†’์€ ๋ถ„์—ด ๋Šฅ๋ ฅ์„ ๋ณด์ธ๋‹ค๋Š” ๊ฒƒ๋„ ๋ณด๊ณ ๋˜์–ด ์™”๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ ์•ž์„œ ์–ธ๊ธ‰ํ•œ ๋‹ค์–‘ํ•œ ์„ธํฌ๋ง‰ ๋‹จ๋ฐฑ์งˆ ์ค‘ Ly6C ๋ถ„์ž์˜ ๋ฐœํ˜„์ด ๋‘๋“œ๋Ÿฌ์ง์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๊ณ  ํŠนํžˆ, ์ƒ์ฒด ๋‚ด(in vivo)์—์„œ๋Š” ๋†’์€ ๋‹ค์–‘์„ฑ์„ ๋ณด์ด๋Š” CD5hi ์„ธํฌ์—์„œ๋งŒ Ly6C์˜ ๋ถ„์ž๊ฐ€ ๋†’๊ฒŒ ๋ฐœํ˜„๋˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์‹ค์ œ๋กœ T ์„ธํฌ์—์„œ์˜ Ly6C ๋ฐœํ˜„์€ ์ œ 1 ์œ ํ˜• ์ธํ„ฐํŽ˜๋ก (type I IFN)์— ์˜ํ•ด ์ฆ๊ฐ€ํ•œ๋‹ค๊ณ  ์•Œ๋ ค์ ธ ์™”๊ณ  ์ •์ƒ์ƒํƒœ์˜ ์ƒ์ฅ์—์„œ ๋‚ฎ์€ ๋†๋„์˜ ์ œ 1 ์œ ํ˜• ์ธํ„ฐํŽ˜๋ก ์ด ํ•ญ์กด์  ์‚ฌ์ดํ† ์นด์ธ(constitutive cytokine)์œผ๋กœ์„œ ์ง€์†์ ์œผ๋กœ ์กด์žฌํ•œ๋‹ค๋Š” ๊ฒƒ์ด ์•Œ๋ ค์ ธ ์™”๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด๊ฒƒ์ด ํ‰์„  ๋‚ด๋ถ€ ๋ฐ ์™ธ๋ถ€์˜ ํ™˜๊ฒฝ์—์„œ ์–ด๋–ป๊ฒŒ ์กฐ์ ˆ๋˜๋Š” ์ง€ ๊ทธ๋ฆฌ๊ณ  ์–ด๋–ค ๋‹ค๋ฅธ ํ•ญ์ƒ์„ฑ ์š”์ธ(homeostatic factor)๋“ค๊ณผ ๊ด€๋ จ์ด ์žˆ๋Š”์ง€๋Š” ๋ช…ํ™•ํžˆ ๋ฐํ˜€์ง€์ง€ ์•Š์•˜์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ œ 1 ์œ ํ˜• ์ธํ„ฐํŽ˜๋ก  ์•ŒํŒŒ ์ˆ˜์šฉ์ฒด 1 ๊ฒฐํ• ์ƒ์ฅ(Ifnar1-/-)์˜ ํ‰์„ ๊ณผ ๋ง์ดˆ ๋ฉด์—ญ ๊ธฐ๊ด€์„ ๋ถ„์„ํ•ด๋ณธ ๊ฒฐ๊ณผ Ly6C๋ฅผ ๋ฐœํ˜„ํ•˜๋Š” naรฏveCD8+ ์„ธํฌ๋“ค์ด ์‚ฌ๋ผ์ง„ ๊ฒƒ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋˜ํ•œ ์ •์ƒ ์ƒ์ฅ์™€ ์ œ 1 ์œ ํ˜• ์ธํ„ฐํŽ˜๋ก  ์•ŒํŒŒ ์ˆ˜์šฉ์ฒด 1 ๊ฒฐํ• ์ƒ์ฅ์˜ Ly6C- ์„ธํฌ๋“ค ๋ถ„๋ฆฌํ•˜์—ฌ ์ •์ƒ์ ์ธ ์ˆ™์ฃผ ์ƒ์ฅ์—๊ฒŒ ์ด์‹ํ•ด์ฃผ์—ˆ์„ ๋•Œ ์ •์ƒ ์ƒ์ฅ์—์„œ ์œ ๋ž˜ํ•œ Ly6C- ์„ธํฌ๋Š” ํ•ญ์กด์  ์ œ 1 ์œ ํ˜• ์ธํ„ฐํŽ˜๋ก ์— ์˜ํ•ด Ly6C๋ฅผ ํš๋“ํ•œ ๋ฐ˜๋ฉด์— ์ œ 1 ์œ ํ˜• ์ธํ„ฐํŽ˜๋ก  ์•ŒํŒŒ ์ˆ˜์šฉ์ฒด 1 ๊ฒฐํ• ์ƒ์ฅ์—์„œ ์œ ๋ž˜ํ•œ Ly6C- ์„ธํฌ๋Š” ๊ทธ๋ ‡์ง€ ๋ชปํ–ˆ๋‹ค. ์ด๋ฅผ ํ†ตํ•ด ๋‚ฎ์€ ๋†๋„์˜ ํ•ญ์กด์  ์ œ 1 ์œ ํ˜• ์ธํ„ฐํŽ˜๋ก ์ด ํ‰์„ ๊ณผ ๋ง์ดˆ์˜ naรฏve CD8+ T ์„ธํฌ ๊ตฐ์ง‘ ๋‚ด์—์„œ Ly6C+ ์„ธํฌ์˜ ์ƒ์„ฑ์„ ์œ ๋„ํ•˜๋Š” ์ค‘์š”ํ•œ ์š”์ธ์ž„์„ ๋ณด์—ฌ์ฃผ์—ˆ๋‹ค. ๋˜ํ•œ CD5์˜ ๋ฐœํ˜„์ด T ์„ธํฌ์˜ ์ž๊ฐ€ ๋ฐ˜์‘์„ฑ(self-reactivity)์„ ๋Œ€๋ณ€ํ•  ์ˆ˜ ์žˆ๋Š” ๋‹จ๋ฐฑ์งˆ์ž„์„ ๊ณ ๋ คํ•ด๋ณด์•˜์„ ๋•Œ, CD5hi ์„ธํฌ์—์„œ ๋ณด์—ฌ์ง€๋Š” ๋†’์€ ๋‹ค์–‘์„ฑ์€ ์•„๋งˆ๋„ ์ž๊ฐ€ ํ•ญ์›(self-ligands)๊ณผ์˜ ๋†’์€ ๊ฒฐํ•ฉ๋ ฅ๊ณผ ์‚ฌ์ดํ† ์นด์ธ์— ๋Œ€ํ•œ ๋ฐ˜์‘์„ฑ, ํŠนํžˆ ์ œ 1 ์œ ํ˜• ์ธํ„ฐํŽ˜๋ก ์— ๋Œ€ํ•œ ๋†’์€ ๋ฐ˜์‘์„ฑ์„ ํ†ตํ•ด ํš๋“๋˜์—ˆ์„ ๊ฐ€๋Šฅ์„ฑ์ด ์žˆ์Œ์„ ์‹œ์‚ฌํ•˜์˜€๋‹ค. ๋˜ํ•œ ๋ณธ ์—ฐ๊ตฌ๋Š” ์ •์ƒ ์ƒํƒœ์˜ ํ•ญ์กด์  ์ œ 1 ์œ ํ˜• ์ธํ„ฐํŽ˜๋ก  ์‹ ํ˜ธ๋Š” Ly6C+ ์„ธํฌ์˜ ์ƒ์„ฑ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ T-bet, eomes, IL-18Rap, CCL5์˜ ๋ฐœํ˜„์„ ์ฆ๊ฐ€์‹œ์ผœ์„œ ๋…ํŠนํ•œ ์œ ์ „์  ํŠน์ง•์„ ํ˜•์„ฑ์‹œํ‚ค๋ฉฐ, Ly6C+ ์„ธํฌ ํŠน์ด์ ์œผ๋กœ ์ธํ„ฐํŽ˜๋ก -๊ฐ๋งˆ(IFN-ฮณ) ์ƒ์‚ฐ ๋Šฅ๋ ฅ์„ ์ฆ๊ฐ€์‹œํ‚ฌ ์ˆ˜ ์žˆ์Œ์„ ๋ณด์—ฌ์ฃผ์—ˆ๋‹ค. ๋” ๋‚˜์•„๊ฐ€ ๋ฆผํ”„๊ตฌ์„ฑ ๋งฅ๋ฝ์ˆ˜๋ง‰์—ผ(Lymphocytic choriomeningitis;LCMV) ๊ฐ์—ผ ๋ชจ๋ธ์—์„œ๋Š” ํ•ญ์กด์  ์ œ 1 ์œ ํ˜• ์ธํ„ฐํŽ˜๋ก  ์‹ ํ˜ธ๊ฐ€ Ly6C+์„ธํฌ์˜ ์žฅ๊ธฐ ๊ธฐ์–ต ์„ธํฌ(long-term memory cell)๋กœ์˜ ๋ถ„ํ™”์—๋„ ์˜ํ–ฅ์„ ์ค„ ์ˆ˜ ์žˆ์Œ์„ ์ œ์•ˆํ•˜์˜€๋‹ค. RNA ์—ผ๊ธฐ์„œ์—ด๋ถ„์„(RNA sequencing)์„ ํ™œ์šฉํ•œ ์œ ์ „์ž์„ธํŠธ์ฆํญ๋ถ„์„(gene set enrichment assay; GSEA)์„ ํ†ตํ•ด ํ•ญ์กด์  ์ œ 1 ์œ ํ˜• ์ธํ„ฐํŽ˜๋ก ์— ๊ฐ€์žฅ ๋ฏผ๊ฐํ•œ ๋ฐ˜์‘์„ฑ ๊ฐ–๋Š”๋‹ค๋Š” ๊ฒƒ์ด ํ™•์ธ๋œ Ly6C+ ์„ธํฌ๋Š” LCMV ๊ฐ์—ผ ์ƒํ™ฉ์—์„œ Ly6C๋ฅผ ๋ฐœํ˜„ํ•˜์ง€ ์•Š๋Š” ์ง‘๋‹จ์˜ ์„ธํฌ๋“ค๋ณด๋‹ค ๋‹จ๊ธฐ์ƒ์กดํ˜• effector ์„ธํฌ(short-lived effector cell; SLEC)๋กœ ๋” ๋งŽ์ด ๋ถ„ํ™”ํ•˜์˜€์œผ๋ฉฐ, ๋” ์ ์€ ์žฅ๊ธฐ๊ธฐ์–ต์„ธํฌ๋ฅผ ํ˜•์„ฑํ–ˆ๋‹ค. ๋ฐ˜๋ฉด ์— Ly6C+ ์„ธํฌ์™€ ์œ ์ „์  ๋ฐ ๊ธฐ๋Šฅ์ ์œผ๋กœ ๊ฐ€์žฅ ๋†’์€ ์ด์งˆ์„ฑ์„ ๋ณด์˜€๋˜ CD5lo ์„ธํฌ๋Š” ๊ธฐ์–ต์„ธํฌ ์ „๊ตฌ์ฒด effector ์„ธํฌ(memory precursor effector cell; MPEC)๋กœ ๋” ๋งŽ์ด ๋ถ„ํ™”ํ•˜์˜€์œผ๋ฉฐ, ๋” ๋งŽ์€ ์žฅ๊ธฐ๊ธฐ์–ต์„ธํฌ๋ฅผ ํ˜•์„ฑํ•จ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ํฅ๋ฏธ๋กญ๊ฒŒ๋„ ์ •์ƒ์ƒํƒœ์—์„œ ์ผ์‹œ์ ์œผ๋กœ ์ œ 1 ์œ ํ˜• ์ธํ…ŒํŽ˜๋ก  ์•ŒํŒŒ ์ˆ˜์šฉ์ฒด 1 ์ฐจ๋‹จ ํ•ญ์ฒด(blocking antibody)๋ฅผ ํˆฌ์—ฌํ•œ ์ƒ์ฅ์—์„œ ๋ถ„๋ฆฌํ•œ Ly6C+ ์„ธํฌ๋Š” ๋ฆผํ”„๊ตฌ์„ฑ ๋งฅ๋ฝ์ˆ˜๋ง‰์—ผ ๊ฐ์—ผ์ƒํ™ฉ์—์„œ ๊ธฐ์–ต์„ธํฌ ์ „๊ตฌ์ฒด effector ์„ธํฌ๋กœ์˜ ๋ถ„ํ™”๊ฐ€ ์ฆ๊ฐ€๋˜๊ณ , ๋‹จ๊ธฐ์ƒ์กดํ˜• effector ์„ธํฌ๋กœ์˜ ๋ถ„ํ™”๋Š” ์–ต์ œ๋˜๋Š” ๊ฒƒ์„ ๋ณด์˜€๋‹ค. ์ด ์‹คํ—˜์„ ํ†ตํ•ด ํ•ญ์กด์  ์ œ 1 ์œ ํ˜• ์ธํ„ฐํŽ˜๋ก ์ด naรฏve CD8+ T ์„ธํฌ๋“ค์˜ ์žฅ๊ธฐ๊ธฐ์–ต์„ธํฌ๋กœ์˜ ๋ถ„ํ™” ์ž ์žฌ๋ ฅ์„ ์กฐ์ ˆํ•  ์ˆ˜ ์žˆ๋Š” ์š”์ธ์ž„์„ ์‹œ์‚ฌํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๊ฒฐ๋ก ์ ์œผ๋กœ, ๋ณธ ์—ฐ๊ตฌ๋Š” ํ•ญ์กด์  ์ œ 1 ์œ ํ˜• ์ธํ„ฐํŽ˜๋ก ์ด naรฏve CD8+ T์„ธํฌ์˜ ์ž๊ฐ€ ๋ฐ˜์‘์„ฑ๊ณผ ๋ฐ€์ ‘ํ•œ ์—ฐ๊ด€์„ฑ์„ ๊ฐ€์ง€๊ณ  ์žˆ์œผ๋ฉฐ ๊ทธ๋“ค์˜ ํ‘œํ˜„ํ˜•๊ณผ ๊ธฐ๋Šฅ์„ฑ์— ์˜ํ–ฅ์„ ์ค„ ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฒƒ์„ ๋ณด์—ฌ์ฃผ๊ณ  ์žˆ๋‹ค. ๋˜ํ•œ ๋” ๋‚˜์•„๊ฐ€ naรฏve CD8+ T ์„ธํฌ๋“ค์˜ ์žฅ๊ธฐ๊ธฐ์–ต์„ธํฌ๋กœ์˜ ๋ถ„ํ™” ๊ฐ€๋Šฅ์„ฑ์€ ๊ฐ์—ผ ์ƒํ™ฉ์—์„œ ๋ฌด์ž‘์œ„๋กœ ๋ถ€์—ฌ๋˜๋Š” ๊ฒƒ์ด ์•„๋‹ˆ๋ผ, naรฏve CD8+ T ์„ธํฌ์˜ ํ•ญ์กด์  ์ œ 1 ์œ ํ˜• ์ธํ„ฐํŽ˜๋ก ์— ๋Œ€ํ•œ ๋ฏผ๊ฐ๋„์— ๋”ฐ๋ผ ์ •์ƒ ์ƒํƒœ์—์„œ ๋ฏธ๋ฆฌ ๊ฒฐ์ •๋˜๋Š” ํŠน์„ฑ์ด๋ผ๋Š” ๊ทผ๊ฑฐ๋ฅผ ์ฒ˜์Œ์œผ๋กœ ์ œ์‹œํ•œ ์—ฐ๊ตฌ์ผ ๊ฒƒ์ด๋‹ค.I. Literature review 1 II. Introduction 22 III. Materials and Method 27 IV. Results 34 V. Discussion 81 VI. Literature Cited 92 VII. Summary in Korean 114Docto

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) --์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์ „๊ธฐ. ์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€,2007.Maste
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