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    ํ˜•ํƒœ์ ์‘ํ˜• ์ด๋ ฅํ˜„์ƒ ๋ชจํ˜•์„ ์ด์šฉํ•œ ์œ ์—ฐ๊ตฌ๋™ ๋ฉ”์ปค๋‹ˆ์ฆ˜์˜ ๋ชจ๋ธ๋ง

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€, 2020. 8. ๊น€์ข…์›.Flexible surgical robots and instruments are slowly paving its way into the modern surgical arena. Compared to conventional laparoscopic surgical systems, flexible systems have some distinct advantages in that it can approach surgical targets that were unreachable before, leaves less scar and therefore reducing recovery time for patients. In order to drive the articulated surgical instruments joints, flexible instruments require a tendon-sheath mechanism (TSM). Utilization of TSM brings about a different attribute in a position control standpoint, compared to the rather simple cable-pulley system found in conventional robotic surgical instruments. In this research, a tendon-sheath mechanism was configured, taking into account the actual size constraint of a robotic surgical instrument and the material characteristics of the components. An experiment hardware was designed to measure the input signal and the corresponding output response while varying the shape configuration parameters of TSM. Twenty four distinct experiments with different shape configuration parameters were carried out to identify how the shape affects the performance and the hysteresis curve of the TSM. For modeling the hysteretic behavior of the TSM, a composite model consisting of elementary hysteresis operators is proposed. Such a composite models parameters are empirically identified with least-squares optimization, for every shape configurations defined. The model processes the input to produce an estimated output for a certain shape, and this was verified with various types of input signals. Lastly, for compensating TSMs hysteretic behavior, a recursive algorithm producing inverse control signal from the empirical model is proposed, with a guaranteed real-time performance. The inverse algorithms position control effectiveness was verified under various shape configurations and input signal types.๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์œ ์—ฐํ•œ ๋กœ๋ด‡ ์ˆ˜์ˆ ๋„๊ตฌ๋ฅผ ๊ตฌํ˜„ํ•˜๊ธฐ ์œ„ํ•ด ์‚ฌ์šฉ๋˜๋Š” Tendon-Sheath Mechanism (TSM)์ด ํ˜•์ƒ์— ๋”ฐ๋ฅธ ์ด๋ ฅํ˜„์ƒ์˜ ๋ณ€ํ™”๊ฐ€ ๋ฐœ์ƒํ•˜๋Š” ๊ฒƒ์„ ์‹คํ—˜์ ์œผ๋กœ ํ™•์ธํ•˜์˜€์œผ๋ฉฐ, ์ด๋Ÿฌํ•œ ์ด๋ ฅํ˜„์ƒ์„ ํ‘œํ˜„ํ•˜๊ธฐ ์œ„ํ•œ ๋ชจํ˜•์„ ์ œ์•ˆํ•˜๊ณ  ์ด๋ฅผ ์ด์šฉํ•˜์—ฌ ์ด๋ ฅํ˜„์ƒ์„ ๋ณด์ƒํ•  ์ˆ˜ ์žˆ๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์•ˆํ•˜์˜€๋‹ค. ์ฒซ ๋‹จ๊ณ„๋กœ TSM์„ ๊ตฌ์„ฑํ•˜๋Š” ๋ถ€ํ’ˆ์ธ Tendon๊ณผ Sheath๋ฅผ ์„ ์ •ํ•˜๋Š”๋ฐ ์žˆ์–ด, ์ด๋ ฅํ˜„์ƒ์— ์ผ์กฐ ํ•˜๋Š” ๋น„์„ ํ˜•์  ํŠน์„ฑ์„ ์ตœ์†Œํ™”ํ•˜๋Š” ์žฌ๋ฃŒ์™€ ๊ณต์ • ๋ฐ ํ›„์ฒ˜๋ฆฌ ๋ฐฉ๋ฒ•์„ ๊ณ ๋ คํ•˜์—ฌ ์ ์šฉํ•˜์˜€๋‹ค. ๋‹ค์Œ์œผ๋กœ TSM์˜ ํ˜•์ƒ ๋ณ€์ˆ˜๋ฅผ ์ •์˜ํ•˜๊ณ  ์ด๋ฅผ ๋‹ค์–‘ํ•œ ํ˜•์ƒํ•˜์—์„œ ์ด๋ ฅํ˜„์ƒ์˜ ๋ณ€ํ™”๋ฅผ ๊ด€์ฐฐํ•˜๋Š” ์‹คํ—˜์žฅ์น˜๋ฅผ ์„ค๊ณ„ํ•˜์—ฌ ์‹คํ—˜ ๋ฐ์ดํ„ฐ๋ฅผ ์ˆ˜์ง‘ํ•˜์˜€๋‹ค. ์ด๋ฅผ ํ† ๋Œ€๋กœ ์ž…๋ ฅ์— ๋Œ€ํ•œ ์ถœ๋ ฅ์˜ ๊ด€๊ณ„๋ฅผ Preisach type ์—ฐ์‚ฐ์ž๋ฅผ ์ด์šฉํ•˜์—ฌ ํ‘œํ˜„ํ•˜์˜€๊ณ  ์‹คํ—˜ ๋ฐ์ดํ„ฐ์— ๊ธฐ๋ฐ˜ํ•œ ์—ฐ์‚ฐ์ž์˜ ๋ณ€์ˆ˜๋“ค์„ ์ตœ์†Œ์ž์Šน ์ตœ์ ํ™”๋ฅผ ํ†ตํ•ด ํƒ์ƒ‰ํ•˜์˜€์œผ๋ฉฐ, ๋ชจ๋ธ์˜ ์ ํ•ฉ์„ฑ์„ ๋‹ค์–‘ํ•œ ํ˜•์ƒํ•˜์—์„œ, ๊ฐ๊ธฐ ๋‹ค๋ฅธ ์ข…๋ฅ˜์˜ ์ž…๋ ฅ ์‹ ํ˜ธ์— ๋Œ€ํ•œ ์ถœ๋ ฅ์„ ๋ชจ๋ธ์„ ํ†ตํ•ด ์ƒ์„ฑ๋˜๋Š” ์ถœ๋ ฅ ์ถ”์ •์น˜์™€์˜ ์˜ค์ฐจ ๋ถ„์„์œผ๋กœ ๊ฒ€์ฆํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ๋ชจ๋ธ๋กœ ์ด๋ ฅํ˜„์ƒ์„ ๋ณด์ƒํ•˜๊ธฐ ์œ„ํ•ด์„œ Set-Point ์ถœ๋ ฅ์— ๋Œ€ํ•œ Inverse Control ์‹ ํ˜ธ๋ฅผ ์ƒ์„ฑํ•˜๋Š” ์žฌ๊ท€์  ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์•ˆํ•˜์˜€์œผ๋ฉฐ, ์ด๋Ÿฌํ•œ ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ๋‹ค์–‘ํ•œ Set-point ์ถœ๋ ฅ์˜ ํ˜•ํƒœ์— ๋Œ€ํ•ด์„œ ์‹ค์‹œ๊ฐ„์„ฑ์ด ๋ณด์žฅ๋˜๋Š” ๋น ๋ฅธ ์—ฐ์‚ฐ์ด ๊ฐ€๋Šฅํ•˜๋‹ค๋Š” ์ ์„ ๋ณด์˜€๋‹ค. ์ด๋ ฅํ˜„์ƒ์ด ๋ณด์ƒ๋œ ์‹คํ—˜๋ฐ์ดํ„ฐ์™€ ๊ธฐ์กด์˜ ๋ณด์ƒ์ „ ์‹คํ—˜๋ฐ์ดํ„ฐ์˜ ๋น„๊ต๋ฅผ ํ†ตํ•ด ๋ณด์ƒ์ „๋žต์ด ํšจ๊ณผ์ ์ด๋ผ๋Š” ๊ฒƒ์„ ๋ณด์˜€์œผ๋ฉฐ, ๋‹ค์–‘ํ•œ ํ˜•ํƒœ์—์„œ๋„ ์ ์šฉ์ด ๊ฐ€๋Šฅํ•จ์„ ๊ฒ€์ฆํ•˜์˜€๋‹ค.Table of Contents Chapter 1. Introduction 1 1.1 Background 1 1.1.1 Evolution of surgical robots 1 1.1.2 Flexible robotic systems 3 1.2 Tendon-sheath mechanism 6 1.2.1 Application of TSM in flexible surgical instruments 6 1.2.2 Effects on motion transfer characteristics 8 1.3 Previous studies 10 1.4 Research objectives 12 Chapter 2. Configuration and fabrication of TSM 14 2.1 Sheath 17 2.2 Tendon 19 2.2.1 Cable 19 2.2.2 Fitting 23 Chapter 3. Hysteretic behavior of TSM 25 3.1 Experiment setup 26 3.1.1 Experiment design 26 3.1.2 Hardware design 28 3.2 Experiment results 34 3.2.1 Effect of curve angle variation 34 3.2.2 Effect of radius of curvature variation 39 3.2.3 Summary of results of hysteretic behavior 46 Chapter 4. Modeling Hysteresis of TSM 49 4.1 Preisach model and Hysterons 50 4.2 Mechanical play operator 53 4.3 Complex hysteresis operator: 56 4.4 Parameter identification for complex hysteresis operator 59 4.5 Result of experimental verification of complex hysteresis operator 60 4.5.1 Result of reference input profile sinusoidal excitation 63 4.5.2 Result of validation input profile triangular excitation 65 4.5.3 Result of reference input profile trapezoidal excitation 67 4.5.4 Obtained weights for all shape configurations and summary 69 4.6 Inverse operator formulation 60 4.7 Experimental verification of hysteresis compensation with the inverse operator: 77 4.7.1 Experiment setup 77 4.7.2 Result of hysteresis compensation for shape =90,r=30mm 79 4.7.3 Result of hysteresis compensation for shape =60,r=60mm 82 4.7.4 Error statistic and result analysis 85 Chapter 6. Conclusion 87 Bibliography 88 Abstract in Korean 92Docto

    ๊ฒฐํ•ต์˜ ๋ณ‘์ธ์— ๊ด€์—ฌํ•˜๋Š” ์ˆ˜์ง€์ƒ ์„ธํฌ์˜ ํŠน์„ฑ๊ณผ ์—ญํ•  ๊ทœ๋ช…์„ ํ†ตํ•œ ์ƒˆ๋กœ์šด ๊ฒฐํ•ต์ œ์–ด ๊ธฐ๋ฒ•๊ณผ ์ „๋žต์ œ์‹œ

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    ๊ฒฐํ•ต๊ท (Mycobacterium tuberculosis, Mtb)์€ ์‚ฌ๋žŒ์„ ์œ ์ผํ•œ ์ˆ™์ฃผ๋กœ ํ•˜๋Š” ๋ณ‘์›์ฒด๋กœ ๊ฒฐํ•ต(tuberculosis)์„ ์œ ๋ฐœ์‹œํ‚ค๋ฉฐ, ๊ฒฐํ•ต์€ 2018 ๋…„๋„ ํ•œ ํ•ด์—๋งŒ ํ•ด๋„ 150 ๋งŒ์—ฌ ๋ช…์„ ์‚ฌ๋ง์— ์ด๋ฅด๊ฒŒ ํ•˜๋Š” ๊ฐ€์žฅ ์‹ฌ๊ฐํ•œ ๊ฐ์—ผ ๋ณ‘์ด๋‹ค. ๊ฒฐํ•ต๊ท ์ด ๋ฐœ๊ฒฌ๋œ ์ดํ›„, 100 ๋…„์ด ๋„˜๋Š” ๋™์•ˆ ๊ฒฐํ•ต์„ ์ œ์–ดํ•˜๊ธฐ ์œ„ํ•ด ๋งŽ์€ ์—ฐ๊ตฌ๊ฐ€ ์ง„ํ–‰๋˜์–ด ์™”์ง€๋งŒ ๊ฒฐํ•ต์˜ ๋ณ‘์ธ๊ธฐ์ „์— ๋Œ€ํ•œ ์ดํ•ด๋Š” ์•„์ง๋„ ๋ฏธํกํ•œ ์ƒํƒœ์ด๋‹ค. ์ˆ˜์ง€์ƒ ์„ธํฌ๋Š” ์ „๋ฌธ์ ์ธ ํ•ญ์›์ œ์‹œ์„ธํฌ(antigen presenting cell) ์ค‘ ํ•˜๋‚˜๋กœ์„œ, ์™ธ๋ถ€ ํ•ญ์›์— ์˜ํ•ด์„œ ์„ฑ์ˆ™ํ™” ๊ณผ์ •์„ ๊ฑฐ์นœ ํ›„ ๋ฐฐ์ˆ˜ ๋ฆผํ”„์ ˆ(draining lymph node)๋กœ ์ด๋™ํ•˜์—ฌ T ์„ธํฌ์— ์˜ํ•œ ํ•ญ์› ์ธ์‹์„ ์ด‰์ง„ํ•˜๊ณ  ๊ฐ์—ผ ๋ฏธ์„ธํ™˜๊ฒฝ์— ๋”ฐ๋ผ ํŠน์ • T ์„ธํฌ์˜ ํŽธํ–ฅํ™”(polarization)๋ฅผ ์œ ๋„ํ•œ๋‹ค. ๊ฒฐํ•ต ์ œ์–ด๋ฅผ ์œ„ํ•ด ์ œ 1 ํ˜• ๋ณด์กฐ T ์„ธํฌ(type 1 helper T cell, Th1) ๋ฉด์—ญ์˜ ํ˜•์„ฑ์ด ์ค‘์š”ํ•˜๊ธฐ ๋•Œ๋ฌธ์—, T ์„ธํฌ์˜ ๋ฉด์—ญํŽธํ–ฅํ™”๋ฅผ ์กฐ์ ˆํ•˜๋Š” ์ˆ˜์ง€์ƒ ์„ธํฌ๋Š” ๊ฒฐํ•ต ๋ณ‘์ธ์—์„œ ์ค‘์š”ํ•œ ์—ญํ• ์„ ์ˆ˜ํ–‰ํ•œ๋‹ค. ํ•˜์ง€๋งŒ, ๊ฒฐํ•ต๊ท ์€ ์ˆ˜์ง€์ƒ ์„ธํฌ์— ์˜ํ•œ ํšจ๊ณผ์ ์ธ ๋ฉด์—ญ๋ฐ˜์‘์„ ์–ต์ œ, ํšŒํ”ผํ•˜๋Š” ๊ธฐ์ „์ด ์กด์žฌ ํ•œ๋‹ค๋Š” ์—ฐ๊ตฌ๋“ค์ด ์ง€์†์ ์œผ๋กœ ๋ณด๊ณ ๋˜๊ณ  ์žˆ๊ธฐ ๋•Œ๋ฌธ์—, ๊ฒฐํ•ต์˜ ๋ฐœ๋ณ‘๊ณผ ๋ฐฉ์–ด์— ๊ด€์—ฌํ•˜๋Š” ์ˆ˜์ง€์ƒ ์„ธํฌ์˜ ํŠน์ง• ๋ฐ ์—ญํ• ์„ ์ดํ•ดํ•˜๊ณ , ์ด๋ฅผ ์ด์šฉํ•œ๋‹ค๋ฉด ํšจ๊ณผ์ ์ธ ๊ฒฐํ•ต์ œ์–ด๊ธฐ๋ฒ•์„ ์ œ์‹œํ•  ์ˆ˜ ์žˆ๋‹ค. ์ด์— ๋ณธ ํ•™์œ„ ๋…ผ๋ฌธ์—์„œ๋Š” ๋‹ค์–‘ํ•œ ๊ฒฐํ•ต ๊ฐ์—ผ๋ชจ๋ธ์—์„œ ํ˜•์„ฑ๋˜๋Š” ์ˆ˜์ง€์ƒ ์„ธํฌ์˜ ๋ฉด์—ญํ•™์  ํ‘œํ˜„ํ˜•๊ณผ ์—ญํ• ์„ ๊ทœ๋ช…ํ•˜๊ณ , ์ด๋ฅผ ์ด์šฉํ•˜์—ฌ ํ–ฅ์ƒ๋œ ๊ฒฐํ•ต์˜ˆ๋ฐฉ ๋ฐ ์น˜๋ฃŒ์˜ ๊ฐ€๋Šฅ์„ฑ์„ ์—ฐ๊ตฌํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ์ œ 1 ์žฅ์—์„œ๋Š” ๊ฒฐํ•ต ๋ฐœ๋ณ‘๊ณผ ๋ฐฉ์–ด ๊ธฐ์ „์— ๊ด€์—ฌํ•˜๋Š” ์ˆ˜์ง€์ƒ ์„ธํฌ์˜ ์—ญํ• ๊ณผ T ์„ธํฌ์™€์˜ ๊ด€๊ณ„, ์ž„์ƒ ์‹œํ—˜ ์ค‘์ธ ๊ฒฐํ•ต๋ฐฑ์‹ ์„ ํ† ๋Œ€๋กœ ํ–ฅํ›„ ํšจ๊ณผ์ ์ธ ๊ฒฐํ•ต๋ฐฑ์‹ ๊ณผ ์ œ์–ด๊ธฐ๋ฒ• ๊ฐœ๋ฐœ์„ ์œ„ํ•œ ์ˆ˜์ง€์ƒ ์„ธํฌ์˜ ํ™œ์šฉ ๋ฐ ๊ทธ ํŠน์„ฑ์— ๋Œ€ํ•œ ๋ฌธํ—Œ๊ณ ์ฐฐ๊ณผ ์ตœ์‹  ์—ฐ๊ตฌ๋™ํ–ฅ์— ๋Œ€ํ•œ ๋‚ด์šฉ์œผ๋กœ ๊ตฌ์„ฑ๋˜์–ด์žˆ๋‹ค. ์ œ 2 ์žฅ์—์„œ๋Š” ๋™๋ฌผ์‹คํ—˜ ๋ชจ๋ธ๋ง ๋ฐ in vitro ์‹คํ—˜์„ ํ†ตํ•˜์—ฌ ์ˆ˜์ง€์ƒ ์„ธํฌ์™€ ๊ฒฐํ•ต ๊ฐ์ˆ˜์„ฑ์— ๊ด€ํ•œ ์ƒ๊ด€๊ด€๊ณ„์™€ ์ˆ˜์ง€์ƒ ์„ธํฌ์˜ ๊ธฐ๋Šฅ์„ ๋ฐํžˆ๊ณ ์ž ํ•˜์˜€๋‹ค. ์ผ๋ฐ˜์ ์œผ๋กœ ๊ฒฐํ•ต๊ท  ๊ฐ์—ผ๋ชจ๋ธ์— ์‚ฌ์šฉ๋˜๋Š” C57BL/6 ๋งˆ์šฐ์Šค์— ๋น„ํ•ด ๊ฒฐํ•ต๊ท  ๊ฐ์—ผ์— ๋Œ€ํ•ด ๋†’์€ ๊ฐ์ˆ˜์„ฑ(susceptibility)์„ ์ง€๋‹Œ A/J ๋งˆ์šฐ์Šค์˜ ๊ฒฝ์šฐ, C57BL/6 ๋งˆ์šฐ์Šค์— ๋น„ํ•ด ๋‚ฎ์€ ๋นˆ๋„์ˆ˜์˜ ์ˆ˜์ง€์ƒ ์„ธํฌ ๋ฐ T ์„ธํฌ์™€, ์•ฝํ™”๋œ Th1 ๋ฐ˜์‘ ํ˜•์„ฑ์ด ๊ด€์ฐฐ๋˜์—ˆ๋‹ค. ๋˜ํ•œ, ๋ณ‘์›์„ฑ์ด ์„œ๋กœ ๋‹ค๋ฅธ ๊ฒฐํ•ต ๊ท ์ฃผ๋“ค(Mtb K, H37Rv ๋ฐ H37Ra)์˜ ๊ฐ์—ผ์„ ํ†ตํ•˜์—ฌ ๋งˆ์šฐ์Šค ๋ชจ๋ธ์—์„œ ๋ณ‘์›์„ฑ๊ณผ ๋ฐ˜๋น„๋ก€ ํ•˜๋Š” Th1 ๋ฐ˜์‘์˜ ํ˜•์„ฑ๊ณผ, ์ˆ˜์ง€์ƒ ์„ธํฌ์ƒ์˜ major histocompatibility complex (MHC) class II ๋ถ„์ž์˜ ์–ต์ œ๋ฅผ ํ™•์ธํ•˜์—ฌ, ๊ฒฐํ•ต๊ท  ๊ฐ์—ผ์˜ ์ค‘์ฆ๋„์™€ T ์„ธํฌ ๋ฉด์—ญ ๊ทธ๋ฆฌ๊ณ  ์ˆ˜์ง€์ƒ ์„ธํฌ์— ๋Œ€ํ•œ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ์ œ์‹œํ•˜์˜€๋‹ค. ๋˜ํ•œ, ๋ณ‘์›์„ฑ ๊ฒฐํ•ต๊ท ์ฃผ H37Rv ๋˜๋Š” ์•ฝ๋…ํ™” ๊ฒฐํ•ต๊ท ์ฃผ H37Ra ๊ฐ์—ผ์„ ํ†ตํ•ด ๋ณ‘์›์„ฑ์ด ์„œ๋กœ ๋‹ค๋ฅธ ๊ฒฐํ•ต๊ท ์˜ ๊ฐ์—ผ์— ๋”ฐ๋ฅธ ์ˆ˜์ง€์ƒ ์„ธํฌ์˜ ํ‘œํ˜„ํ˜• ๋ฐ ๊ธฐ๋Šฅ์  ๋ณ€ํ™”์™€ T ์„ธํฌ์™€์˜ ์ƒํ˜ธ์ž‘์šฉ์„ ์กฐ์‚ฌ ํ•˜์˜€๋‹ค. H37Rv ๊ฐ์—ผ-์ˆ˜์ง€์ƒ ์„ธํฌ์—์„œ๋Š” H37Ra ๊ฐ์—ผ์— ๋น„ํ•ด ๋”์šฑ ๋†’์€ ์ˆ˜์ค€์˜ Th1 ๋ฐ˜์‘์˜ ์–ต์ œ๊ฐ€ ๊ด€์ฐฐ๋˜์—ˆ๊ณ , ์ด๋Š” H37Rv ๊ฐ์—ผ์„ ํ†ตํ•ด ๋ฉด์—ญ ์–ต์ œ์„ฑ ์‚ฌ์ดํ† ์นด์ธ ์ค‘ ํ•˜๋‚˜์ธ Interleukin 10 (IL-10)์˜ ๋ถ„๋น„์— ์˜ํ•œ ์˜ํ–ฅ์ž„์„ ํ™•์ธํ•˜์˜€๋‹ค. ๊ฐ์—ผ ์ดˆ๊ธฐ๋ถ€ํ„ฐ ๋‹ค๋Ÿ‰์˜ IL 10 ์˜ ๋ถ„๋น„๊ฐ€ ์œ ๋„๋œ H37Rv ๊ฐ์—ผ-์ˆ˜์ง€์ƒ ์„ธํฌ๋Š” T ์„ธํฌ์™€์˜ ์ƒํ˜ธ์ž‘์šฉ์„ ์œ„ํ•œ CD80, CD86 ๋ฐ MHC class II ๋ถ„์ž ๋ฐœํ˜„์˜ ์ €ํ•˜์™€ programmed deathligand 1 (PD-L1), CD103, Tim-3 ๋ฐ indoleamin 2, 3-dioxygenase ๋ถ„์ž ๋ฐœํ˜„์˜ ์ฆ๊ฐ€๋ฅผ ํ†ตํ•ด ๋ฉด์—ญ ๊ด€์šฉ์„ฑ ์ˆ˜์ง€์ƒ ์„ธํฌ๋กœ ์œ ๋„๋จ์„ ํ™•์ธํ•˜์˜€๋‹ค. H37Rv ๊ฐ์—ผ-์ˆ˜์ง€์ƒ ์„ธํฌ์—์„œ ๊ด€์ฐฐ๋œ ๋ฉด์—ญ ๊ด€์šฉ์„ฑ ํ‘œํ˜„ํ˜•์€ IL-10 ๊ฒฐํ• ๋งˆ์šฐ์Šค๋กœ๋ถ€ํ„ฐ ์ƒ์„ฑ๋œ ์ˆ˜์ง€์ƒ ์„ธํฌ ๋˜๋Š” IL-10 ์ค‘ํ™” ๋‹จ์ผํด๋ก  ํ•ญ์ฒด๋กœ ์ฒ˜๋ฆฌ ๋œ ์ˆ˜์ง€์ƒ ์„ธํฌ์—์„œ ์ •์ƒ์ ์ธ ์„ฑ์ˆ™ ์ˆ˜์ง€์ƒ ์„ธํฌ ํ‘œํ˜„ํ˜•์œผ๋กœ ํšŒ๋ณต ๋จ์„ ํ™•์ธํ•˜์˜€์œผ๋ฉฐ, T ์„ธํฌ์™€์˜ ๊ณต๋™ ๋ฐฐ์–‘์—์„œ๋„ T ์„ธํฌ์˜ ์ฆ์‹ ๋ฐ Th1 ์„ธํฌ๋กœ์˜ ๋ถ„ํ™”๊ฐ€ ํšŒ๋ณต ๋จ์„ ํ™•์ธ ํ•จ์œผ๋กœ์จ, H37Rv ๊ฐ์—ผ์— ์˜ํ•ด ์œ ๋„๋˜๋Š” ๋ฉด์—ญ๊ด€์šฉ์„ฑ ์ˆ˜์ง€์ƒ ์„ธํฌ์— IL-10 ์ด ํ•ต์‹ฌ์ ์ธ ์—ญํ• ์„ ํ•˜๊ณ  ์žˆ์Œ์„ ์ฆ๋ช…ํ•˜์˜€๋‹ค. ์ถ”๊ฐ€์ ์œผ๋กœ, H37Rv ๊ฐ์—ผ์— ์˜ํ•œ IL-10 ์˜ ๋ถ„๋น„๋Š” p38 mitogenactivated protein kinases (MAPK) ํ™œ์„ฑํ™”์— ์˜ํ•ด ๋งค๊ฒŒ ๋œ๋‹ค๋Š” ๊ฒƒ์„ ํ™•์ธ ํ•จ์œผ๋กœ์จ, p38 MAPKโˆ’IL-10 ์œผ๋กœ ์ด์–ด์ง€๋Š” ์‹ ํ˜ธ์ „๋‹ฌ์ด ๋ฉด์—ญ ๊ด€์šฉ์„ฑ ์ˆ˜์ง€์ƒ ์„ธํฌ์˜ ํ˜•์„ฑ์— ์ค‘์š”ํ•จ์„ ์ฆ๋ช…ํ•˜์˜€๋‹ค. ๊ฒฐ๋ก ์ ์œผ๋กœ, ๊ฒฐํ•ต์˜ ์ค‘์ฆ๋„ ๋ฐ ๊ฒฐํ•ต๊ท ์˜ ๋ณ‘์›์„ฑ์— ๋”ฐ๋ฅธ ์ˆ˜์ง€์ƒ ์„ธํฌ์˜ ํ‘œํ˜„ํ˜• ๋ฐ ๊ธฐ๋Šฅ์˜ ํŠน์ง•์„ ๊ทœ๋ช…ํ•˜์˜€๊ณ , ์ˆ˜์ง€์ƒ ์„ธํฌ์˜ ์กฐ์ ˆ์„ ํ†ตํ•ด ํšจ๊ณผ์ ์ธ T ์„ธํฌ ๋ฉด์—ญ์„ ์œ ๋„ํ•จ์œผ๋กœ์จ ๊ฒฐํ•ต๊ท ์„ ์–ต์ œํ•˜๋Š” ์ „๋žต์— ๋Œ€ํ•œ ๊ฐ€๋Šฅ์„ฑ์„ ์ œ์‹œํ•˜์˜€๋‹ค. ํ•ญ์›์˜ ๋‹นํ™”(glycosylation)๋Š” ํ•ญ์›์ œ์‹œ์„ธํฌ์˜ ํ•ญ์›์ธ์‹ ๋ฐ ํ•ญ์›์ธ์‹ ์ดํ›„์— ์œ ๋„๋˜๋Š” T ์„ธํฌ ๋ฉด์—ญ๋ฐ˜์‘์— ์˜ํ–ฅ์„ ์ค„ ์ˆ˜ ์žˆ๋‹ค๊ณ  ๋ณด๊ณ ๋˜์—ˆ๋‹ค. ํŠน์ดํ•˜๊ฒŒ๋„ ๊ฒฐํ•ต๊ท ์€ ๋‹ค๋ฅธ ์„ธ๊ท ์— ๋น„ํ•ด, ํ•ญ์›๋“ค์˜ ๋‹นํ™”๊ฐ€ ์ „์ฒด ๋‹จ๋ฐฑ์ฒด ์ค‘์—์„œ ๋งค์šฐ ๋†’์€ ๋น„์ค‘์„ ์ฐจ์ง€ํ•œ๋‹ค๊ณ  ์•Œ๋ ค์กŒ๋‹ค. ๋”ฐ๋ผ์„œ, ์ œ 3 ์žฅ์—์„œ๋Š” ํ–ฅ์ƒ๋œ ์•„๋‹จ์œ„ ๋ฐฑ์‹ (subunit vaccine) ๊ฐœ๋ฐœ์„ ์œ„ํ•ด ๋‹จ๋ฐฑ์งˆ ๋ฐœํ˜„ ํ›„ ๋‹นํ™”๊ณผ์ •์„ ๊ฐ€์ง€๋Š” ๋‹จ๋ฐฑ์งˆ-์‹๋ฌผ๋ฐœํ˜„์‹œ์Šคํ…œ์„ ์ด์šฉํ•˜์—ฌ ํ•ญ์›์„ ํ™•๋ณดํ•˜์˜€๊ณ , ๊ฒฐํ•ต๋ฐฑ์‹ ์œผ๋กœ์„œ์˜ ๋ฐฉ์–ดํšจ๊ณผ๋ฅผ ์ œ์‹œํ•˜์˜€๋‹ค. ๊ฐ๊ด€์  ๋น„๊ต๋ฅผ ์œ„ํ•ด ๋‹จ๋ฐฑ์งˆ- ๋ฐ•ํ…Œ๋ฆฌ์•„ ๋ฐœํ˜„ ์‹œ์Šคํ…œ์œผ๋กœ์„œ ๋Œ€์žฅ๊ท (Escherichia coli)์—์„œ ๋ฐœํ˜„ ๋œ ๋น„ ๋‹นํ™” Ag85A (NG-Ag85A)์™€ ๋‹จ๋ฐฑ์งˆ-์‹๋ฌผ ๋ฐœํ˜„ ์‹œ์Šคํ…œ์œผ๋กœ์„œ ๋‹ˆ์ฝ”ํ‹ฐ์•„๋‚˜ ๋ฒคํƒ€๋ฏธ์•„๋‚˜(Nicotiana benthamiana)์—์„œ ๋ฐœํ˜„ ๋œ ๋‹นํ™” Ag-85A (G-Ag85A)์˜ ๋ฐฑ์‹  ํšจ๋Šฅ์„ ๊ฒฐํ•ต๊ท  ๊ฐ์—ผ ๋งˆ์šฐ์Šค ๋ชจ๋ธ์—์„œ ๋น„๊ต ํ•˜์˜€๋‹ค. ๊ฒฐํ•ต๊ท  ๊ฐ์—ผ ๋งˆ์šฐ์Šค์—์„œ ๋ถ„๋ฆฌํ•œ T ์„ธํฌ์— ๊ฐ๊ฐ์˜ ํ•ญ์›์„ ์ž๊ทนํ•œ ๊ฒฐ๊ณผ G-Ag85A ๋Š” NGAg85A ์— ๋น„ํ•ด ๋”์šฑ ๋†’์€ ํ•ญ์›์„ฑ(antigenicity)์„ ๋ณด์œ ํ•จ์„ ํ™•์ธํ•˜์˜€๊ณ , ๊ฐ๊ฐ์˜ ํ•ญ์›์œผ๋กœ ์ž๊ทน์‹œํ‚จ ์ˆ˜์ง€์ƒ ์„ธํฌ์™€ ๊ฒฐํ•ต๊ท  ๊ฐ์—ผ ๋งˆ์šฐ์Šค ๋ถ„๋ฆฌ T ์„ธํฌ์˜ ๊ณต๋™ ๋ฐฐ์–‘ ๊ฒฐ๊ณผ์—์„œ G-Ag85A ๋กœ ์ž๊ทนํ•œ ์ˆ˜์ง€์ƒ ์„ธํฌ์—์„œ ๋”์šฑ ๋†’์€ ํ•ญ์› ํŠน์ด์  IFN- ์™€ T ์„ธํฌ ์ฆ์‹์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๋Š”, GAg85A ๊ฐ€ ํ•ญ์›์„ ํƒ์‹ํ•˜๊ณ  ์ œ์‹œํ•˜๋Š” ์ˆ˜์ง€์ƒ ์„ธํฌ๋ฅผ ํ†ตํ•ด Th1 ๋ฐ˜์‘์„ ์ฆ๊ฐ€์‹œํ‚ฌ ์ˆ˜ ์žˆ๋Š” ๊ฒฐํ•ต ๋ฐฑ์‹  ํ›„๋ณด๋กœ์„œ์˜ ๊ฐ€๋Šฅ์„ฑ์„ ๋ณด์—ฌ์ค€๋‹ค. ๊ฒฐํ•ต๊ท  ๊ฐ์—ผ ํ›„ 4 ์ฃผ ๋ฐ 9 ์ฃผ์— ํ ์กฐ์ง ๋‚ด ๋ฐ•ํ…Œ๋ฆฌ์•„ ์„ฑ์žฅ ๋ฐ ํ ์กฐ์ง ๋ณ‘๋ณ€ ๋ถ„์„ ๊ฒฐ๊ณผ, G-Ag85A ๋กœ ๋ฉด์—ญํ™” ๋œ ๋งˆ์šฐ์Šค ๊ทธ๋ฃน์€ NG-Ag85A ๋ฉด์—ญํ™”์— ๋น„ํ•ด ๋”์šฑ ๋†’์€ ๋ฐฑ์‹  ํšจ๋Šฅ์„ ๋‚˜ํƒ€๋ƒ„์„ ํ™•์ธํ•˜์˜€๊ณ , ๋ฐฑ์‹ ์— ์˜ํ•ด ์œ ๋„๋œ ๊ฒฐํ•ต๊ท  ๋ฐฉ์–ด๊ฐ€ ํšจ๊ณผ๋Š” IFN-, TNF- ๋ฐ IL-2 ๋ฅผ ๊ณต๋™ ์ƒ์„ฑํ•˜๋Š” ํ•ญ์›ํŠน์ด์  ๋‹ค๊ธฐ๋Šฅ CD4+ T ์„ธํฌ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์ด๋ฃจ์–ด์ง์„ ํ™•์ธ ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๊ฒฐ๋ก ์ ์œผ๋กœ, ์‹๋ฌผ ๋‹จ๋ฐฑ์งˆ ๋ฐœํ˜„ ์‹œ์Šคํ…œ์„ ์ด์šฉํ•œ ๋‹นํ™”๋œ ๋ฐฑ์‹  ํ•ญ์›์˜ ํŠน์ง•๊ณผ ํšจ๋Šฅ์„ ์ˆ˜์ง€์ƒ ์„ธํฌ๋กœ๋ถ€ํ„ฐ ๊ฒฐํ•ต๊ท  ๋™๋ฌผ๋ชจ๋ธ์„ ํ†ตํ•˜์—ฌ ๋ณด์—ฌ์คŒ์œผ๋กœ์จ ๊ฒฐํ•ต์˜ ํšจ๊ณผ์ ์ธ ์˜ˆ๋ฐฉ์„ ์œ„ํ•œ ๋ฐฑ์‹ ํ•ญ์› ๊ฐœ๋ฐœ์— ์ƒˆ๋กœ์šด ์ „๋žต์„ ์ œ๊ณตํ•˜์˜€๋‹ค. ๊ฒฐํ•ต์˜ ์ œ์–ด๋ฅผ ์œ„ํ•ด์„œ ํšจ๊ณผ์ ์ธ ์˜ˆ๋ฐฉ๊ณผ ๊ฒฐํ•ต ํ™˜์ž์— ๋Œ€ํ•œ ํšจ์œจ์ ์ธ ์น˜๋ฃŒ๊ฐ€ ์ค‘์š”ํ•˜๋‹ค. ์ด๋ฅผ ์œ„ํ•ด์„œ ์ƒˆ๋กœ์šด ๋ฐฑ์‹  ๊ฐœ๋ฐœ์„ ํ†ตํ•œ ๊ฒฐํ•ต๊ท  ๊ฐ์—ผ ์–ต์ œ ๋ฐ ๊ฒฐํ•ต ๋ฐœ๋ณ‘ ์–ต์ œ์™€, ์ƒˆ๋กœ์šด ์น˜๋ฃŒ๋ฒ•์„ ํ†ตํ•œ ์น˜๋ฃŒ ๊ธฐ๊ฐ„ ๋‹จ์ถ•์ด ์‹œ๊ธ‰ํ•œ ์‹ค์ •์ด๋‹ค. ์ตœ๊ทผ ์ˆ˜์ง€์ƒ ์„ธํฌ๋ฅผ ํ‘œ์ ์œผ๋กœ ํ•˜๊ฑฐ๋‚˜ ์ˆ˜์ง€์ƒ ์„ธํฌ์˜ ์ง์ ‘์ ์ธ ์ด์šฉ์„ ํ†ตํ•œ ๊ฒฐํ•ต๋ฐฑ์‹  ๋ชจ๋ธ์—์„œ ๋†’์€ ์ˆ˜์ค€์˜ ๋ฐฑ์‹  ํšจ๋Šฅ์ด ๋ณด๊ณ ๋˜๊ณ  ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ, ์ œ 4 ์žฅ์—์„œ๋Š” ๊ฒฐํ•ต๊ท ์˜ ๋ฐฐ์–‘์•ก์„ ๋†์ถ•ํ•œ ๋ถ„๋น„ํ•ญ์›(culture Filtrate antigens, CFA)์œผ๋กœ ์„ฑ์ˆ™์‹œํ‚จ ์ˆ˜์ง€์ƒ ์„ธํฌ(CFA-์ˆ˜์ง€์ƒ ์„ธํฌ)๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ (i) BCG ํ”„๋ผ์ž„-๋ถ€์Šคํ„ฐ ๋ฐฑ์‹ ์œผ๋กœ์˜ ๊ฐ€๋Šฅ์„ฑ๊ณผ, (ii) ์•ฝ์ œ ๊ฐ์ˆ˜์„ฑ ๊ฒฐํ•ต(drug susceptible TB) ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์•ฝ์ œ ์ €ํ•ญ์„ฑ ๊ฒฐํ•ต(multidrug resistant TB) ์˜ ์น˜๋ฃŒํšจ๋Šฅ์„ ์ฆ๊ฐ€์‹œํ‚ค๊ธฐ ์œ„ํ•œ ๋ณด์กฐ ๋ฉด์—ญ ์š”๋ฒ•์œผ๋กœ์„œ์˜ ๊ฐ€๋Šฅ์„ฑ์„ ๋‹ค์–‘ํ•œ ๋งˆ์šฐ์Šค ๋ชจ๋ธ์„ ์‚ฌ์šฉํ•˜์—ฌ ํ‰๊ฐ€ ํ•˜์˜€๋‹ค. ๋งˆ์šฐ์Šค์— BCG ๋ฐฑ์‹  ํ›„, CFA- ์ˆ˜์ง€์ƒ ์„ธํฌ๋ฅผ ํ†ตํ•œ BCG ํ”„๋ผ์ž„-๋ถ€์Šคํ„ฐ ๋ฐฑ์‹ ์€, BCG ๋‹จ๋… ๋ฐฑ์‹ ์— ๋น„ํ•ด ์ข…๊ฒฉ๋™ ๋ฆผํ”„์ ˆ (mediastinal lymph node) ๋ฐ ํ ์กฐ์ง ๋‚ด์˜ ์ˆ˜์ง€์ƒ ์„ธํฌ ์™€ T ์„ธํฌ์˜ ์นจ์œค์„ ์ด‰์ง„ํ•˜์˜€๊ณ , ํ•ญ์› ์ œ๊ฑฐ ํŠนํ™”๋œ ์ดํŽ™ํ„ฐ ๋ฉ”๋ชจ๋ฆฌ T ์„ธํฌ(effector memory T cell) ๋ฐ ํ•ญ์›์— ๋Œ€ํ•œ ๋ฉ”๋ชจ๋ฆฌ ๋ฐ˜์‘์„ ์žฅ๊ธฐ์ ์œผ๋กœ ์ง€์†ํ•˜๋Š” ์„ผํŠธ๋Ÿด ๋ฉ”๋ชจ๋ฆฌ T ์„ธํฌ(central memory T cell)์˜ ํ˜•์„ฑ์„ ์ด‰์ง„ํ•จ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋˜ํ•œ, TNF-, IFN- ๋ฐ IL-๋ฅผ ๋™์‹œ์— ์ƒ์„ฑํ•˜๋Š” ํ•ญ์›ํŠน์ด์  ๋‹ค๊ธฐ๋Šฅ CD4+ T ์„ธํฌ์˜ ํ˜„์ €ํ•œ ์ฆ๊ฐ€์™€ ํ•จ๊ป˜ ์ดˆ๊ธฐ ๊ฐ์—ผ ๋‹จ๊ณ„๋ถ€ํ„ฐ ์ƒ๋‹นํ•œ ๋ฐ•ํ…Œ๋ฆฌ์•„ ๊ฐ์†Œ๋ฅผ ์œ ๋„ํ•จ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ด ๊ฒฐ๊ณผ๋Š” ๋‹ค์–‘ํ•œ ๊ท  ์ฃผ์˜ ๊ฒฐํ•ต๊ท  ๊ฐ์—ผ ๋ชจ๋ธ์—์„œ๋„ ๋™์ผํ•œ ๋ณดํ˜ธ ํšจ๋Šฅ์„ ๊ฐ€์กŒ์œผ๋ฉฐ, ๋ถ€์ŠคํŒ… ๋ฐฑ์‹ ์œผ๋กœ๋ถ€ํ„ฐ 26 ์ฃผ ํ›„์—๋„ ๋ณดํ˜ธ ํšจ๋Šฅ์ด ์ง€์†๋จ์„ ํ™•์ธํ•˜์˜€๋‹ค. ํ•ญ๊ฒฐํ•ต ํ™”ํ•™ ์š”๋ฒ•์— ๋Œ€ํ•œ ๋ณด์กฐ ๋ฉด์—ญ ์š”๋ฒ• ์‹คํ—˜์˜ ๊ฒฝ์šฐ, ํ•ญ์ƒ์ œ ์น˜๋ฃŒ์™€ ํ•จ๊ป˜ ํˆฌ์—ฌ๋œ CFA-์ˆ˜์ง€์ƒ ์„ธํฌ๋Š” ํ•ญ์›ํŠน์ด์  ๋‹ค๊ธฐ๋Šฅ CD4+ T ์„ธํฌ์˜ ์ฆ๊ฐ€ ๋ฐ ์œ ์ง€์™€ ํ•จ๊ป˜ ๋™์ผ ์น˜๋ฃŒ๊ธฐ๊ฐ„ ๋‚ด์— ์›”๋“ฑํ•œ ํ ์กฐ์ง ๋‚ด ๋ฐ•ํ…Œ๋ฆฌ์•„ ์ˆ˜์˜ ๊ฐ์†Œ์™€ ํ ์—ผ์ฆ์˜ ํ˜„์ €ํ•œ ๊ฐ์†Œ๋ฅผ ์œ ๋ฐœํ•จ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋˜ํ•œ, ์žฌํ™œ์„ฑํ™” ๊ฒฐํ•ต ๋ชจ๋ธ์—์„œ, ํ•ญ์ƒ์ œ์™€ ํ•จ๊ป˜ CFA-์ˆ˜์ง€์ƒ ์„ธํฌ์˜ ํˆฌ์—ฌ ํ•œ ๊ทธ๋ฃน์˜ ๊ฒฝ์šฐ, ํ•ญ์ƒ์ œ ๋‹จ๋… ํˆฌ์—ฌ ๊ทธ๋ฃน์— ๋น„ํ•ด ๋†’์€ ์ˆ˜์ค€์˜ ์„ผํŠธ๋Ÿด ๋ฉ”๋ชจ๋ฆฌ T ์„ธํฌ์˜ ํ˜•์„ฑ์„ ํ™•์ธํ•˜์˜€์œผ๋ฉฐ, ๊ฐ์—ผ ํ›„ 35 ์ฃผ๊นŒ์ง€ ๊ฒฐํ•ต์˜ ์žฌ ํ™œ์„ฑํ™”๋กœ๋ถ€ํ„ฐ ๋†’์€ ๋ณดํ˜ธํšจ๊ณผ๊ฐ€ ๊ด€์ฐฐ๋˜์—ˆ๋‹ค. ๋‹ค์ œ๋‚ด์„ฑ ๊ฒฐํ•ต๊ท  ๊ฐ์—ผ ๋งˆ์šฐ์Šค ๋ชจ๋ธ์—์„œ๋„ CFA-์ˆ˜์ง€์ƒ ์„ธํฌ์— ์˜ํ•œ ์น˜๋ฃŒ ํšจ์œจ ์ฆ๊ฐ€๊ฐ€ ์œ ์ง€๋จ์„ ํ™•์ธํ•˜์—ฌ ๊ฒฐํ•ต ์–ต์ œ์˜ ์ฃผ์š” ๋ฌธ์ œ์  ์ค‘ ํ•˜๋‚˜์ธ ๋‹ค์ œ๋‚ด์„ฑ ๊ฒฐํ•ต๊ท ์˜ ์น˜๋ฃŒ ์ „๋žต์— ๋Œ€ํ•œ ์ ์šฉ ๊ฐ€๋Šฅ์„ฑ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๊ฒฐ๋ก ์ ์œผ๋กœ, CFA- ์ˆ˜์ง€์ƒ ์„ธํฌ๋ฅผ ํ†ตํ•œ BCG ํ”„๋ผ์ž„-๋ถ€์Šคํ„ฐ ๋ฐฑ์‹  ๋ฐ ํ•ญ์ƒ์ œ ์น˜๋ฃŒ์— ๋Œ€ํ•œ ๋ณด์กฐ ๋ฉด์—ญ์š”๋ฒ•์€ ๊ธฐ๊ฐ„ ๋‹จ์ถ• ๋ฐ ๊ฒฐํ•ต๊ท  ์žฌ ํ™œ์„ฑํ™” ์˜ˆ๋ฐฉ์— ๋Œ€ํ•œ ์ˆ˜์ง€์ƒ ์„ธํฌ ๊ธฐ๋ฐ˜ ๋ฉด์—ญ ์š”๋ฒ•์— ๋Œ€ํ•œ ์ƒˆ๋กœ์šด ๊ฐ€๋Šฅ์„ฑ์„ ์ œ์‹œํ•˜์˜€๋‹ค. ์ข…ํ•ฉ์ ์œผ๋กœ, ๋ณธ ํ•™์œ„ ๋…ผ๋ฌธ์—์„œ๋Š” (1) ๊ฒฐํ•ต์˜ ๋ฐœ๋ณ‘๊ณผ ์ง„ํ–‰, ์ค‘์ฆ๋„์— ๊ด€์—ฌํ•˜๋Š” ์ˆ˜์ง€์ƒ ์„ธํฌ์˜ ํŠน์ง•์„ ๊ทœ๋ช…ํ•จ์€ ๋ฌผ๋ก , ๋ณ‘์›์„ฑ์— ๋”ฐ๋ผ ํ˜•์„ฑ๋˜๋Š” ์ˆ˜์ง€์ƒ ์„ธํฌ์˜ ํ‘œํ˜„ํ˜•์ , ๊ธฐ๋Šฅ์  ํŠน์„ฑ์„ ๊ทœ๋ช…ํ•˜์˜€๋‹ค. (2) ํ–ฅ์ƒ๋œ ๋ฐฑ์‹  ๊ฐœ๋ฐœ์„ ์œ„ํ•ด ๋‹จ๋ฐฑ์งˆ ํ•ญ์›์˜ ๋‹นํ™”๋ฅผ ์œ ๋„ํ•˜์—ฌ ๋น„๋‹นํ™” ํ•ญ์› ๋Œ€๋น„ ํ–ฅ์ƒ๋œ ๋ฐฑ์‹ ํšจ๊ณผ๋ฅผ ํ™•์ธํ•จ์€ ๋ฌผ๋ก , ์ด๋ฅผ ์‹๋ฌผ ๊ธฐ๋ฐ˜์˜ ๋‹จ๋ฐฑ์งˆ ๋ฐœํ˜„ ์‹œ์Šคํ…œ์„ ํ†ตํ•˜์—ฌ ์‚ฌ์šฉํ•จ์œผ๋กœ์จ ์ถ”ํ›„ ๋น„์šฉ์  ๊ด€๋ฆฌ์  ์ธก๋ฉด์—์„œ ํšจ์œจ์ ์ธ ๋ฐฑ์‹ ์ƒ์‚ฐ์˜ ํ”Œ๋žซํผ์— ๋Œ€ํ•œ ๊ฐ€๋Šฅ์„ฑ์„ ์ œ์‹œํ•˜์˜€๋‹ค. (3) ์ˆ˜์ง€์ƒ ์„ธํฌ์˜ ์ง์ ‘์ ์ธ ์ด์šฉ์„ ํ†ตํ•˜์—ฌ ๊ธฐ์กด์˜ BCG ๋ฐฑ์‹ ์˜ ํšจ์œจ์„ฑ ์ฆ๋Œ€๋ฅผ ์œ„ํ•ด BCG ํ”„๋ผ์ž„-๋ถ€์Šคํ„ฐ ๋ฐฑ์‹  ์ „๋žต์„ ์ œ์‹œํ•˜์˜€๊ณ , ์ˆ˜์ง€์ƒ ์„ธํฌ ๊ธฐ๋ฐ˜์˜ ๋ณด์กฐ ๋ฉด์—ญ์น˜๋ฃŒ(adjunctive immunotherapy)๋ฅผ ๊ฐœ๋ฐœํ•˜์—ฌ ์ƒˆ๋กœ์šด ๊ฒฐํ•ต ์น˜๋ฃŒ์š”๋ฒ•์˜ ์ „๋žต์„ ์ œ์‹œํ•˜์˜€์œผ๋ฉฐ, ๊ฒฐํ•ต์— ๋Œ€ํ•œ ์˜ˆ๋ฐฉ ๋ฐ ์น˜๋ฃŒ์˜ ํšจ์œจ์„ฑ ์ฆ๋Œ€์™€ ๊ฒฐํ•ต์˜ ์žฌ๋ฐœ์— ๋Œ€ํ•œ ์–ต์ œํšจ๊ณผ๋ฅผ ํ™•์ธํ•˜์˜€๋‹ค. ๋ณธ ํ•™์œ„๋…ผ๋ฌธ์—์„œ ๋„์ถœ๋œ ๊ฒฐ๊ณผ๋Š” ์ธ๋ฅ˜๋ฅผ ๊ฐ€์žฅ ๊ดด๋กญํ˜€ ์˜จ ๊ฒฐํ•ต์„ ํšจ์œจ์ ์œผ๋กœ ์ œ์–ดํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ๊ธฐ์ดˆ์  ์ง€์‹ ๋ฐœ์ „๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๋‹ค์–‘ํ•œ ๋ชจ๋ธ์—์„œ ์‹ค์ œ๋กœ ์ ์šฉ๊ฐ€๋Šฅ์„ฑ์„ ๋ณด์—ฌ์คŒ์œผ๋กœ์จ ํ–ฅํ›„ ๊ฐœ์„  ๋œ ๊ฒฐํ•ต๋ฐฑ์‹  ๋ฐ ์น˜๋ฃŒ์ œ ๊ฐœ๋ฐœ์— ์ผ์กฐํ•  ๊ฒƒ์ด๋‹ค. Mycobacterium tuberculosis (Mtb) is a harmful human pathogen causing 180 million annual deaths. To control this detrimental pathogen, a large amount of time and effort has been consumed but the mechanism of Mtb pathogenesis is still unclear. Dendritic cells (DCs) are professional antigen presenting cells mediating innate and acquired immunity. Acquired immunity, especially T cell immunity, is a crucial factor in controlling Mtb infection and disease, and DCs are an integral mediator of this process. Therefore, understanding the role of DCs in the pathogenesis of TB and their application in the development of treatments could provide a rational approach towards controlling TB. Chapter I contains a literature review regarding the role of dendritic cells in tuberculosis pathogenesis, the current status of TB vaccines used in clinical trials, and the application of DCs and their properties for development of TB vaccines. In Chapter II we demonstrate that Mtb infection inhibits optimal Th1 responses by altering the function of DCs. We infected DCs with either the virulent Mtb strain H37Rv or the attenuated strain H37Ra to investigate the phenotypic and functional alterations in DCs and the resultant T cell responses. H37Rv-infected DCs suppressed Th1 responses more strongly than H37Ra-infected DCs. Interestingly, H37Rv, but not H37Ra, impaired the expression of DC surface molecules (CD80, CD86, and MHC class II), due to prominent IL-10 production, while augmenting the expression of tolerogenic molecules, including PD-L1, CD103, Tim-3, and indoleamine 2,3-dioxygenase (IDO). These results indicate that virulent Mtb drives immature DCs toward a tolerogenic phenotype. Notably, the tolerogenic phenotype of H37Rv-infected DCs was blocked in DCs generated from IL-10-/- mice and in DCs treated with an IL-10-neutralizing monoclonal antibody (mAb), leading to restoration of Th1 polarization. These findings suggest that IL-10 induces a tolerogenic DC phenotype. Interestingly, p38 MAPK activation predominantly mediates IL-10 production; thus, H37Rv tends to induce a tolerogenic DC phenotype via expression of tolerogenic molecules in the p38 MAPK-IL-10 axis. Therefore, suppressing the tolerogenic cascade in DCs is a novel strategy for stimulating optimal protective T cell responses against Mtb infection. In Chapter III, we compared vaccine efficacy of non-glycosylated Ag85A (NG-Ag85A) expressed in Escherichia coli and glycosylated Ag85A (G-Ag85A) expressed in Nicotiana benthamiana. As a result, G-Ag85A induced a stronger IFN- response than NG-Ag85A in antigen-immunized mice, and the G-Ag85A-immunized group showed a greater protective efficacy on bacterial growth and histopathology at four and nine weeks post-infection. Importantly, the protective efficacy of G-AG85A immunization correlated with a remarkable generation of Ag-specific CD4+ T cells co-producing IFN-, TNF-, and IL-2. Taken together, these studies will provide new insights for the prevention and treatment of tuberculosis immunologically and may help develop new vaccines. In Chapter IV, we evaluated whether culture filtrate antigens (CFA)-pulsed-mature dendritic cells (DCs) vaccination could potentiate the efficacy of BCG vaccination as a booster vaccine and in therapy with anti-TB drugs in a murine model. We used various mouse models for aerosol infection with Mtb and transfer CFA-pulsed-matured DCs (CFA-DC) in order to evaluate the efficacy of CFA-DC as a BCG-booster vaccine or an immunotherapy with anti-TB drug treatment. Mice which received a BCG-prime/CFA-DC-boost vaccination promoted early recruitment of DCs and T cells in the mediastinal lymph node and lung. The CFA-DC-booster elicited a significant bacterial reduction from the early phase of infection along with remarkable generation of Ag-specific multifunctional CD4+ T cells co-producing TNF-, IFN- and IL-2. This regimen had protective efficacy against various clinical strains of Mtb, and had long-lasting protective efficacy until 26 weeks from boosting. In the case of chemotherapy experiments, CFA-DC transfer with antibiotics resulted in significant reduction in bacterial burden and lung inflammation accompanied by prominent maintenance of Ag-specific multifunctional CD4+ T cells. In addition, mice administrated antibiotics with CFA-DC transfer in a latent TB model were protected from Mtb-reactivation for up to 35 weeks post-infection. Finally, we confirmed the effect of CFA-DC on the treatment course of MDR-Mtb infection. Our results provide new insights into the BCG-booster vaccine, and into DC-based immunotherapy with respect to shortening antibiotic treatment duration and prevention of Mtb-reactivation. Taken together, these results provide evidence for mechanisms related to disease progression by identifying the immune response of Mtb infected dendritic cells and also pave the way for designing improved vaccines and therapy by using the properties of DCs against Mtb infection.open๋ฐ•

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€, 2015. 2. ๊น€์ข…์›.Based on a previous research that verified the effects of lateral undulation of a bipedal running lizard, Callisaurus Draconoides, a novel robotic system was proposed. For this novel robotic system, the leg mechanism that resembles the running characteristics of the real lizard is the most important component in successfully developing the robot. This study focused on the synthesis of a leg propulsion mechanism of a lizard inspired robot. As a first step, data from a running lizard was acquired by a motion captured video. The four bar mechanism was utilized in mimicking the trajectory of the feet of the lizard, and optimization scheme was applied to determine the optimal lengths of the links of the proposed mechanism. Finally, running experiment was carried out with the designed leg mechanism on a treadmill, concluded with a performance analysisContents Abstract 2 Contents 3 1 Introduction 7 1.1 Research background 7 1.2 Previous study on the lizards running 8 1.3 Research goals and contributions 10 2 Analysis on the biomimetic target 12 2.1 Running characteristics 14 2.2 Mechanism type for the leg 18 2.3 Leg motion extraction and function approximation 21 3 Mechanism synthesis 25 3.1 Design variables and constraints of four bar linkage 25 3.2 Four bar linkage optimization 28 3.3 CAD design of the overall structure 31 4 Prototype production and experiment 34 4.1 Prototype production 34 4.2 Test bench setup 36 4.3 Leg mechanism drive experiment 37 5 Conclusion 39 Bibliography 40 Abstract in Korean 41Maste
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