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    ์ƒ์ฒด์ ํ•ฉ์„ฑ ๋‚˜๋…ธ๋ฌผ์งˆ์„ ํ™œ์šฉํ•œ ํ•ญ๋ฐ”์ด๋Ÿฌ์Šค ์˜์•ฝํ’ˆ ๋ฐœ๊ตด ๋ฐ ์„ธํฌ ๋ถ„ํ™” ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ž์—ฐ๊ณผํ•™๋Œ€ํ•™ ํ™”ํ•™๋ถ€, 2021. 2. ๋ฏผ๋‹ฌํฌ.Since the arousal of the massive development and production of chemical medicine in 1980s, explosive scientific achievements of the traditional pharmaceuticals based on chemical products were accomplished. Nevertheless, numerous infectious diseases and neurological incurable disorders has been yet to be conquered, due to the integrated issues involving the complexity of the disease mechanism studies, difficulty in the critical factor control and so on. Therapeutic research on the RNA virus-associated diseases, for example, had suffered the drastic challenges such as the high rate of genetic mutation and increase in chance of drug evasion. As a result, seldom success has been accomplished in the development of antiviral drugs or vaccines to cope with such. Recent outbreak of several epidemics has been aggressive and severe, which has evoked the urgent need for the antiviral drugs and led to the massive competition of research and development among numerous pharmaceuticals. In the meantime, it has not been long since the potential of nanotechnology has risen on debate for its interdisciplinary application. Nanotechnology includes all research area where various materials in nano (10-9) scale are involved. Nano-sized materials have drawn much attention for their specific features (such as electrical, optical properties) distinguished from those of the bulk sources. Despite its short history compared to other research area, nanotechnology is now drawing much attention for their unique properties advantageous for diverse biological applications. Such attempts include the development of biofunctional nanodevices such as biosensor, intracellular delivery carrier. Here, we introduce three representative multidisciplinary studies utilizing the nanotechnology: 1) rapid drug discovery incorporating a fluorescence-based nanobiosensor, 2) the efficient strategy for neural differentiation of the stem cell with porous particles, and 3) the non-viral direct reprogramming strategy to generate neural stem cell with carbon dot nanoreagent. In each chapter, we introduce the specific characteristics of the involved nanomaterials and describe how these features contributed to achieve the individual goals. In the first research, we propose our achievement on the development and utilization of the fluorescence nanobiosensor to the rapid discovery of the antiviral drug against the pathogenic RNA virus. We have developed a facile, and efficient viral enzyme activity analyzing platform incorporating modified RNA and graphene oxide, named as RANGO. We utilized it to the multi-well based, high-throughput chemical screening to identify novel direct-acting antiviral agents against a specific pathogenic RNA virus named as dengue virus from the FDA-approved small molecule library. Throughout the series of validation process carried out both in vitro and in vivo, we suggest the very compound as the potent direct-acting antiviral drug candidate. In the second research, we suggest the efficient method to mimic the neural differentiation process of mouse embryonic stem cell in vitro incorporating the porous silica nanoparticle as a drug delivery carrier. We selected the functionalized nanoparticle showing the maximum drug loading capacity and investigated its high capability of intracellular delivery by penetrating in the cell cluster. We confirm that the selected nanoaparticle could effectively support the stable, sustained delivery of the retinoic acid into the mouse embryonic stem cell, which led to the efficient induction of the retinoic acid-mediated neural differentiation. In the third research, we introduce the non-viral, direct reprogramming strategy to generate neural stem cell from somatic cell incorporating carbon dot nanocarrier. We observed that the carbon nanodot carrier with the optimized surface charge showed the higher biocompatibility and gene delivery efficiency against the human fibroblast. With sequential evaluation from the non-viral gene delivery to the induction of the neural differentiation, we suggest that the carbon nanodot could be utilized as the non-viral gene delivery carrier to facilitate the direct reprogramming of human fibroblast into neural stem cell-like cell. We suggest that our research accomplishments could provide the fundamental ideas to overcome the limitations of classical approaches in the field of drug discovery and cell engineering.1980๋…„๋Œ€ ํ™”ํ•™ ์˜์•ฝํ’ˆ์˜ ๋Œ€๋Ÿ‰ ์ƒ์‚ฐ ๋ฐ ๊ฐœ๋ฐœ์— ํž˜์ž…์–ด, ํ•ฉ์„ฑ ์˜์•ฝํ’ˆ์œผ๋กœ ๋Œ€ํ‘œ๋˜๋Š” ์ „ํ†ต์ ์ธ ์˜์•ฝํ’ˆ์€ ๋น„์•ฝ์ ์ธ ๋ฐœ์ „์„ ์ด๋ฃฐ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๊ทธ๋Ÿฌํ•œ ์„ฑ์žฅ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ๋ฐ”์ด๋Ÿฌ์Šค์— ๊ธฐ๋ฐ˜ํ•œ ๊ฐ์—ผ์„ฑ ์งˆํ™˜์ด๋‚˜ ์‹ ๊ฒฝ๊ณ„ํ†ต ๊ด€๋ จ ๋‚œ์น˜์„ฑ ์งˆํ™˜๋“ค์€ ๋ฐœ์ƒ ๊ธฐ์ „์˜ ๋ณต์žก์„ฑ ๋ฐ ๊ด€์—ฌ ์ธ์ž ์ œ์–ด์˜ ์–ด๋ ค์›€ ๋“ฑ ๋ณตํ•ฉ์ ์ธ ์ด์œ ๋กœ ์ •๋ณต๋˜์ง€ ๋ชปํ•˜๊ณ  ์žˆ๋Š” ์‹ค์ •์ด๋‹ค. ๊ฐ€๋ น RNA ๋ฐ”์ด๋Ÿฌ์Šค์„ฑ ์งˆํ™˜์˜ ๊ฒฝ์šฐ, RNA ๋ฐ”์ด๋Ÿฌ์Šค์˜ ๋†’์€ ์œ ์ „์  ๋ณ€์ด์œจ๊ณผ ์•ฝ๋ฌผ ํšŒํ”ผ ๊ฐ€๋Šฅ์„ฑ ๋“ฑ์œผ๋กœ ์ธํ•ด ์น˜๋ฃŒ๋ฒ• ๊ฐœ๋ฐœ ์—ฐ๊ตฌ์—์„œ ๋‚œํ•ญ์„ ๊ฒช๊ณ  ์žˆ์œผ๋ฉฐ, ์ด๋Š” ํ˜„์žฌ ํ•ญ๋ฐ”์ด๋Ÿฌ์Šค์ œ์žฌ๋‚˜ ๋ฐฑ์‹  ๊ฐœ๋ฐœ ๋ถ„์•ผ๊ฐ€ ํˆฌ์ž ๋Œ€๋น„ ํšจ์œจ์ด ๋†’์ง€ ์•Š์€ ์ฃผ๋œ ์ด์œ ๋กœ ๊ผฝํžŒ๋‹ค. ์ตœ๊ทผ ๋ช‡๋ช‡ ๋ฐ”์ด๋Ÿฌ์Šค์„ฑ ์ „์—ผ๋ณ‘๋“ค์˜ ์‹ฌ๊ฐํ•œ ์ฐฝ๊ถ๋กœ ์ธํ•˜์—ฌ ํ•ญ๋ฐ”์ด๋Ÿฌ์Šค ์ œ์žฌ์˜ ์ˆ˜์š”๊ฐ€ ๊ธ‰์ฆํ•˜์˜€๊ณ , ์ด์— ๋”ฐ๋ผ ์ˆ˜๋งŽ์€ ์ œ์•ฝ ํšŒ์‚ฌ๋“ค ์‚ฌ์ด์—์„œ ์น˜์—ดํ•œ ์—ฐ๊ตฌ ๊ฐœ๋ฐœ ๊ฒฝ์Ÿ์ด ์ด๋ฃจ์–ด์ง€๊ณ  ์žˆ๋‹ค. ํ•œํŽธ, ์–ด๋–ค ๋ฌผ์งˆ์ด ๋‚˜๋…ธ ์ˆ˜์ค€ (10-9)์˜ ํฌ๊ธฐ๊ฐ€ ๋˜์—ˆ์„ ๋•Œ ์›๋ฌผ์งˆ๊ณผ ๋‹ค๋ฅธ ๊ณ ์œ ์˜ ํŠน์„ฑ์„ ๋จ ์ˆ˜ ์žˆ๋‹ค๋Š” ์ ์ด ๋ฐœ๊ฒฌ๋˜๋ฉด์„œ ๋‚˜๋…ธ๋ฌผ์งˆ์˜ ํŠน์„ฑ์„ ์—ฐ๊ตฌํ•˜๋Š” ํ•™๋ฌธ์ธ ๋‚˜๋…ธ๊ธฐ์ˆ ์ด ๋งŽ์€ ๊ด€์‹ฌ์„ ๋ฐ›๊ธฐ ์‹œ์ž‘ํ–ˆ๋‹ค. ์ด ํ•™๋ฌธ๋ถ„์•ผ์˜ ๋‹คํ•™์ œ์  ์—ฐ๊ตฌ ํ™œ์šฉ ๊ฐ€๋Šฅ์„ฑ์ด ๋Œ€๋‘๋œ ๊ฒƒ์€ ๋น„๊ต์  ์ตœ๊ทผ์œผ๋กœ, ๋‹ค์–‘ํ•œ ๋‚˜๋…ธ๋ฌผ์งˆ์˜ ๊ณ ์œ ํ•œ ํŠน์„ฑ์„ ํ™œ์šฉํ•˜์—ฌ ์ „๊ธฐ์‹ ํ˜ธ ๋ฐ ๊ด‘ํ•™ ์‹ ํ˜ธ๋ฅผ ๋น„๋กฏํ•œ ๋‹ค์–‘ํ•œ ์ž‘๋™ ๋ฐฉ์‹์„ ๊ตฌํ˜„ํ•  ์ˆ˜ ์žˆ๋Š” ํƒ์ง€ ์žฅ๋น„ ๋ฐ ์ƒ์ฒด ์ ์šฉ ๊ฐ€๋Šฅํ•œ ๋‚˜๋…ธ์‹œ์•ฝ๋“ค์˜ ๊ฐœ๋ฐœ ์—ฐ๊ตฌ๊ฐ€ ํ™œ๋ฐœํ•˜๊ฒŒ ์ด๋ฃจ์–ด์ง€๊ณ  ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋‚˜๋…ธ๊ธฐ์ˆ ์˜ ๋‹ค์–‘ํ•œ ๋‹คํ•™์ œ์  ํ™œ์šฉ ๋ถ„์•ผ ์ค‘ ๋Œ€ํ‘œ์„ฑ์„ ๋ ๋Š” ์„ธ ๊ฐ€์ง€ ์ฃผ์ œ๋กœ 1) ํ˜•๊ด‘ ๊ธฐ๋ฐ˜ ๋‚˜๋…ธ์„ผ์„œ๋ฅผ ํ™œ์šฉํ•œ ๊ณ ํšจ์œจ ์˜์•ฝํ’ˆ ๋ฐœ๊ตด ๋ฐ 2) ๋‹ค๊ณต์„ฑ ์ž…์ž๋ฅผ ํ™œ์šฉํ•œ ์ค„๊ธฐ์„ธํฌ์˜ ์‹ ๊ฒฝ ๋ถ„ํ™” ์—ฐ๊ตฌ, ๊ทธ๋ฆฌ๊ณ  3) ์นด๋ณธ๋‹ท ๋‚˜๋…ธ์ „๋‹ฌ์ฒด๋ฅผ ํ™œ์šฉํ•œ ๋น„๋ฐ”์ด๋Ÿฌ์Šค์„ฑ ์ฒด์„ธํฌ ์ง๋ถ„ํ™” ์—ฐ๊ตฌ๋ฅผ ๋ณ‘๋ ฌ์ ์œผ๋กœ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ๊ฐ ์—ฐ๊ตฌ์— ํ™œ์šฉ๋œ ๋‚˜๋…ธ๋ฌผ์งˆ๋“ค์€ ์ €๋งˆ๋‹ค ๋‹ค๋ฅธ ํŠน์„ฑ์„ ๊ฐ–๊ณ ์„œ ์‹œ์Šคํ…œ ๊ตฌํ˜„์— ๊ธฐ์—ฌํ•˜์˜€๋‹ค. ํ•ด๋‹น ํŠน์„ฑ๋“ค์ด ์–ด๋–ค ๋ฐฉ์‹์œผ๋กœ ํ™œ์šฉ๋˜์—ˆ๋Š”์ง€, ์ด๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ์–ด๋–ป๊ฒŒ ๊ฐ ์‹œ์Šคํ…œ์„ ๋””์ž์ธํ•˜๊ณ  ๊ฐœ๋ฐœํ•˜์˜€๋Š”์ง€์— ๋Œ€ํ•˜์—ฌ ๊ฐ ์žฅ์—์„œ ์ž์„ธํžˆ ๋‹ค๋ฃจ์—ˆ๋‹ค. ์ฒซ๋ฒˆ์งธ ์—ฐ๊ตฌ์—์„œ๋Š” ์‚ฐํ™”๊ทธ๋ž˜ํ•€์˜ ํŠน์„ฑ์„ ํ™œ์šฉํ•˜์—ฌ ๊ฐœ๋ฐœํ•œ ํ˜•๊ด‘ ๋‚˜๋…ธ๋ฐ”์ด์˜ค์„ผ์„œ๋ฅผ ํ™œ์šฉํ•ด ์ง์ ‘ ์ž‘์šฉ ํ•ญ๋ฐ”์ด๋Ÿฌ์Šค ํ›„๋ณด๊ตฐ์„ ์„ ๋ณ„ํ•˜๋Š” ์ „์ฒด ๊ณผ์ •์„ ์†Œ๊ฐœํ•˜์˜€๋‹ค. ๊ตฌ์ฒด์ ์œผ๋กœ, ํ˜•๊ด‘ ํ‘œ์ง€ํ•œ RNA์™€ ์‚ฐํ™”๊ทธ๋ž˜ํ•€์„ ์‚ฌ์šฉํ•˜์—ฌ ์‹œํ—˜๊ด€ ์ˆ˜์ค€์—์„œ ์‹ ์†ํ•˜๊ฒŒ RNA ๋ฐ”์ด๋Ÿฌ์Šค ํŠน์ด์  ํšจ์†Œ์˜ ํ™œ์„ฑ์„ ์ •๋Ÿ‰ ๋ถ„์„ํ•  ์ˆ˜ ์žˆ๋Š” ํ”Œ๋žซํผ์„ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ๋‹ค์ค‘ ์›ฐํ”Œ๋ ˆ์ดํŠธ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ˜•๊ด‘ ์‹ ํ˜ธ์— ์ž…๊ฐํ•œ ๊ณ ํšจ์œจ ์Šคํฌ๋ฆฌ๋‹์ด ๊ฐ€๋Šฅํ•˜๋„๋ก ์ตœ์ ํ™”์‹œํ‚จ ์ด ํ”Œ๋žซํผ์„ ์ด์šฉํ•ด, FDA ์Šน์ธ๋œ ์˜์•ฝํ’ˆ ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ๋กœ๋ถ€ํ„ฐ ๋Œ€ํ‘œ์ ์ธ RNA ๋ฐ”์ด๋Ÿฌ์Šค ํŠน์ด์  ํšจ์†Œ์ธ RNA-์˜์กด์„ฑ RNA ์ค‘ํ•ฉํšจ์†Œ (RdRp) ํ™œ์„ฑ ์ €ํ•ด์ œ ํ›„๋ณด๊ตฐ์„ ์„ ๋ณ„ํ•˜๋Š” ๋ฐ ์„ฑ๊ณตํ–ˆ๋‹ค. ๋‹ค์Œ์œผ๋กœ ์„ธํฌ ๋ฐ ๋™๋ฌผ ๊ฐ์—ผ ๋ชจ๋ธ์— ๊ธฐ๋ฐ˜ํ•œ ์•ฝํšจ ๋ถ„์„ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ, ์„ ๋ณ„๋œ ์•ฝ๋ฌผ ํ›„๋ณด๊ตฐ ์ค‘ ๋ชฌํ…”๋ฃจ์นด์ŠคํŠธ๊ฐ€ ๋ฐ”์ด๋Ÿฌ์Šค ๊ฐ์†Œ ํšจ๊ณผ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์ƒ์กด์œจ ์ฆ๊ฐ€, ํ˜ˆ์•ก ๋‚ด ๋ฐ”์ด๋Ÿฌ์Šค ์ €๊ฐ ํšจ๊ณผ ๋ฐ ๊ฐ์—ผ์— ์˜ํ•œ ์ „์‹  ์ฆ์ƒ ์™„ํ™” ๋“ฑ ์‹ค์งˆ์ ์ธ ํšจ๋Šฅ์„ ๊ฐ–๋Š” ์ง์ ‘ ์ž‘์šฉ ํ•ญ๋ฐ”์ด๋Ÿฌ์Šค ์•ฝ๋ฌผ ํ›„๋ณด๊ตฐ์ž„์„ ์ž…์ฆํ•˜์˜€๋‹ค. ๋‘๋ฒˆ์งธ ์—ฐ๊ตฌ๋Š” ์ €๋ถ„์ž ํ™”ํ•ฉ๋ฌผ์˜ ์ ์žฌ ๋ฐ ์„ธํฌ ๋‚ด ๋„์ž…์ด ๊ฐ€๋Šฅํ•œ ๋‹ค๊ณต์„ฑ ์‹ค๋ฆฌ์นด ๋‚˜๋…ธ์ „๋‹ฌ์ฒด๋ฅผ ํ™œ์šฉํ•˜์—ฌ, ์‹คํ—˜์‹ค ์ˆ˜์ค€์—์„œ ๋ฐฐ์•„์ค„๊ธฐ์„ธํฌ๋กœ๋ถ€ํ„ฐ ์‹ ๊ฒฝ ๋ฐœ์ƒ๋‹จ๊ณ„๋ฅผ ์žฌํ˜„ํ•˜๋Š” ํšจ์œจ์„ ๋†’์ด๋Š” ์ „๋žต์— ๋Œ€ํ•œ ์—ฐ๊ตฌ์ด๋‹ค. ๋‹ค์–‘ํ•œ ํ‘œ๋ฉด ๊ณ„์งˆ์„ ํ†ตํ•ด ์ €๋ถ„์ž ํ™”ํ•ฉ๋ฌผ์˜ ์ ์žฌ ํšจ์œจ์„ ์ตœ๋Œ€ํ™”ํ•œ ๋‹ค๊ณต์„ฑ ๋‚˜๋…ธ์ „๋‹ฌ์ฒด๋ฅผ ์„ ๋ณ„ํ•˜๊ณ , ํ•ด๋‹น ๋‚˜๋…ธ์ „๋‹ฌ์ฒด๊ฐ€ ๊ตฐ์ง‘ ํ˜•ํƒœ๋กœ ์ž๋ผ๋Š” ์ฅ ๋ฐฐ์•„์ค„๊ธฐ์„ธํฌ ๋‚ด๋ถ€์— ํšจ๊ณผ์ ์œผ๋กœ ์ „๋‹ฌ๋จ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ด ์ „๋‹ฌ์ฒด๋ฅผ ํ™œ์šฉํ•ด ๋‹ค๋Ÿ‰์˜ ๋ ˆํ‹ฐ๋†€์‚ฐ์„ ๋ฐฐ์•„์ค„๊ธฐ์„ธํฌ ๊ตฐ์ง‘์— ์•ˆ์ •์ ์œผ๋กœ ๊ณต๊ธ‰ํ•˜์—ฌ, ๋ ˆํ‹ฐ๋†€์‚ฐ ๊ด€์—ฌ ๊ธฐ์ „์— ๋”ฐ๋ฅธ ์‹ ๊ฒฝ์„ธํฌ ๋ถ„ํ™” ๊ณผ์ •์„ ์ด‰์ง„ํ•  ์ˆ˜ ์žˆ์Œ์„ ์ž…์ฆํ•˜์˜€๋‹ค. ์„ธ ๋ฒˆ์งธ ์—ฐ๊ตฌ๋Š” ์žฌ์กฐํ•ฉ ์œ ์ „์ž์˜ ์ ์žฌ ๋ฐ ์„ธํฌ ๋‚ด ๋„์ž…์ด ๊ฐ€๋Šฅํ•œ ํƒ„์†Œ์  ๋‚˜๋…ธ์ „๋‹ฌ์ฒด๋ฅผ ํ™œ์šฉํ•˜์—ฌ, ๋น„๋ฐ”์ด๋Ÿฌ์Šค์„ฑ ์œ ์ „์ž ์ „๋‹ฌ ๋ฐฉ์‹์œผ๋กœ ๊ณ ํšจ์œจ์˜ ์ฒด์„ธํฌ ์ง๋ถ„ํ™”๋ฅผ ์‹คํ˜„ํ•˜๋Š” ์ „๋žต์— ๋Œ€ํ•œ ์—ฐ๊ตฌ์ด๋‹ค. ํ‘œ๋ฉด ์ „ํ•˜๋ฅผ ์ตœ์ ํ™”ํ•œ ํƒ„์†Œ์  ๋‚˜๋…ธ์ „๋‹ฌ์ฒด๊ฐ€ ํ†ต์ƒ์ ์œผ๋กœ ํ™œ์šฉ๋˜๋Š” ๊ณ ๋ถ„์ž์„ฑ ์„ธํฌ์ „๋‹ฌ์ฒด ๋Œ€๋น„ ์žฌ์กฐํ•ฉ ์œ ์ „์ž์˜ ์ ์žฌ์œจ์ด ๋†’๊ณ  ์ธ๊ฐ„ ํ”ผ๋ถ€์„ธํฌ์— ๋Œ€ํ•ด ์šฐ์ˆ˜ํ•œ ์ƒ์ฒด์ ํ•ฉ๋„๋ฅผ ๋ณด์ž„์„ ํ™•์ธํ•˜์˜€๋‹ค. ์„ธํฌ ์ „ํ™˜ ์ธ์ž์ธ SOX2๋ฅผ ๋Œ€๋Ÿ‰์œผ๋กœ ์ ์žฌํ•œ ํƒ„์†Œ์  ๋‚˜๋…ธ์ „๋‹ฌ์ฒด๋ฅผ ์ธ๊ฐ„ ํ”ผ๋ถ€์„ธํฌ์— ์ฒ˜๋ฆฌํ•˜์—ฌ ์‹ ๊ฒฝ์ค„๊ธฐ์„ธํฌ ์œ ์‚ฌ ์„ธํฌ๋กœ์˜ ์ง๋ถ„ํ™”์— ์„ฑ๊ณตํ•˜์˜€๊ณ , ์ง๋ถ„ํ™”๋œ ์„ธํฌ์˜ ๋ฐฐ์–‘ ์กฐ๊ฑด์„ ์กฐ์ ˆํ•˜์—ฌ ์‹ ๊ฒฝ ์œ ์‚ฌ ์„ธํฌ๋กœ์˜ ๋ถ„ํ™” ์œ ๋„๊ฐ€ ๊ฐ€๋Šฅํ•จ์„ ํ•จ๊ป˜ ์ž…์ฆํ•˜์˜€๋‹ค. ์ƒ์ˆ ํ•œ ์—ฐ๊ตฌ ์„ฑ๊ณผ๋“ค์€ ๊ธฐ์กด ์‹ ์•ฝ ๋ฐœ๊ตด ๋ฐ ์„ธํฌ ๊ณตํ•™ ๋ถ„์•ผ์—์„œ ์ „ํ†ต์ ์ธ ์ ‘๊ทผ ๋ฐฉ์‹์œผ๋กœ ํ•ด๊ฒฐํ•˜๊ธฐ ์–ด๋ ค์› ๋˜ ์—ฐ๊ตฌ์  ํ•œ๊ณ„์ ๋“ค์„ ๊ทน๋ณตํ•˜๋Š” ๊ธฐ์ดˆ ์—ฐ๊ตฌ์— ํ™œ์šฉ๋  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€ํ•œ๋‹ค.Abstract 1 Table of Contents 4 List of Figures 6 Chapter 1. Introduction 20 1.1 Nanotechnology for antiviral drug discovery 20 1.2 Nanotechnology for cell engineering 23 1.3 Description of Research 26 1.3.1 Discovery of direct-acting antiviral agents with a graphene-based fluorescent nanosensor 26 1.3.2 Highly efficient and rapid neural differentiation of mouse embryonic stem cells based on retinoic acid encapsulated porous nanoparticle 28 1.3.3 Non-viral, direct neuronal reprogramming from human fibroblast using a polymer-functionalized nanodot 29 1.4 Reference 31 Chapter 2. Discovery of direct-acting antiviral agents with a graphene-based fluorescent nanosensor 36 2.1 Introduction 36 2.2 Result 40 2.3 Discussion 59 2.4 Material and Methods 64 2.5 Reference 74 Chapter 3. Highly efficient and rapid neural differentiation of mouse embryonic stem cells based on retinoic acid encapsulated porous nanoparticle 78 3.1 Introduction 78 3.2 Result 82 3.3 Discussion 95 3.4 Materials and Methods 96 3.6 Reference 103 Chapter 4. Non-viral, direct neuronal reprogramming from human fibroblast using a polymer-functionalized nanodot 105 4.1 Introduction 105 4.2 Result 108 4.3 Discussion 129 4.4 Materials and Methods 131 4.5 Conclusion 138 4.6 Reference 139 Conclusion 142 Summary in Korean (๊ตญ๋ฌธ์š”์•ฝ) 143 Acknowledgments 146 [Curriculum vitae] 147Docto

    ์—ด์†์ƒ ๋ฐฉ์ง€ ๋ฐ ์ ˆ์ œ ํšจ๊ณผ ๊ทน๋Œ€ํ™”๋ฅผ ์œ„ํ•œ ๊ณ ์ฃผํŒŒ ์ ˆ์ œ์šฉ ๋‹ค๋ชฉ์  ์ „๊ทน ๊ฐœ๋ฐœ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์˜๊ณผ๋Œ€ํ•™ ์˜ํ•™๊ณผ, 2023. 8. ์ด์ •๋ฏผ.๋ชฉํ‘œ: ์ƒ์ฒด ๋‚ด ๋ผ์ง€ ๊ฐ„์—์„œ ์‹์—ผ์ˆ˜ ์ ์  ๋ฐ ์ง์ ‘ ์กฐ์ง ์˜จ๋„ ์ธก์ •์ด ๊ฐ€๋Šฅํ•œ Octopus ๋‹ค๋ชฉ์ (MP) ์ „๊ทน๊ณผ ๊ณ ์ฃผํŒŒ ์ ˆ์ œ(RFA)์šฉ ๊ธฐ์กด ์ „๊ทน์„ ๋น„๊ตํ•ฉ๋‹ˆ๋‹ค. ์žฌ๋ฃŒ ๋ฐ ๋ฐฉ๋ฒ•: ์ƒ์ฒด ์™ธ ์—ฐ๊ตฌ์—์„œ ์ด 4๊ฐœ์˜ ์‹คํ—˜์ด ์ˆ˜ํ–‰๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ์‹คํ—˜ A์™€ B๋Š” ๊ธฐ์กด ์ „๊ทน๊ณผ์˜ ์ ˆ์ œ ์„ฑ๋Šฅ์„ ๋น„๊ตํ•˜์˜€์œผ๋ฉฐ, ๋…ธ์ถœ ๊ธธ์ด ๋ณ€ํ™”(20mm, 25mm, 30mm)์— ๋”ฐ๋ฅธ ์„ฑ๋Šฅ์„ ๋น„๊ตํ•˜์˜€๋‹ค. ์‹คํ—˜ C์—์„œ๋Š” ์˜จ๋„๊ฐ์ง€์ „๊ทน์˜ ํšจ๊ณผ๋ฅผ ๊ฒ€์ฆํ•˜์˜€๋‹ค. ์ ˆ์ œ ์ค‘ ์˜จ๋„๊ฐ€ 60๋„์— ๋„๋‹ฌํ•˜๋ฉด ์ถœ๋ ฅ์„ ์ข…๋ฃŒํ•˜๊ณ , ๋Œ€์ƒ ์ „๊ทน ์ฃผ๋ณ€ 10mm ๊ฑฐ๋ฆฌ์— ์—ด์†์ƒ์„ ์ฃผ๋ฉด ์•ˆ ๋˜๋Š” ์žฅ๊ธฐ๊ฐ€ ์žˆ๋‹ค๊ณ  ๊ฐ€์ •ํ–ˆ๋‹ค. ์‹คํ—˜ D๋Š” ์‹์—ผ์ˆ˜ ์ฃผ์ž…์— ๋”ฐ๋ฅธ ์„ฑ๋Šฅ ์ฐจ์ด๋ฅผ ์‹คํ—˜ํ•˜์˜€๋‹ค. ๋‘ ๊ฐœ์˜ ์ „๊ทน ์ค‘์•™์— ๋‹ค๋ชฉ์  ์ „๊ทน์„ ์‚ฝ์ž…ํ•˜๊ณ  ์ ˆ์ œ ํ›„ 3๋ถ„๋ถ€ํ„ฐ 3๋ถ„๊ฐ„ ์‹์—ผ์ˆ˜๋ฅผ ์ฃผ์ž…ํ•˜์—ฌ ์„ฑ๋Šฅ์„ ๋น„๊ตํ•˜์˜€๋‹ค. ์ƒ์ฒด ๋‚ด ์—ฐ๊ตฌ์—์„œ๋Š” 16๋งˆ๋ฆฌ์˜ ๋ผ์ง€๋ฅผ ์‚ฌ์šฉํ•˜์˜€๋‹ค. ์ฒซ ๋ฒˆ์งธ ์‹คํ—˜์—์„œ๋Š” Octopus MP ์ „๊ทน(n = 15 ์ ˆ์ œ ์˜์—ญ)๊ณผ ๊ธฐ์กด ์ „๊ทน(n = 12 ์ ˆ์ œ ์˜์—ญ)์„ ์‚ฌ์šฉํ•˜์—ฌ ๊ฐ„์—์„œ 6๋ถ„ ๋™์•ˆ RFA๋ฅผ ์ˆ˜ํ–‰ํ•˜์—ฌ ์‹์—ผ์ˆ˜ ์ฃผ์ž…์˜ ํšจ๊ณผ๋ฅผ ์กฐ์‚ฌํ–ˆ์Šต๋‹ˆ๋‹ค. ๋‘ ์ „๊ทน์˜ ์ ˆ์ œ ์—๋„ˆ์ง€, ์ „๊ธฐ ์ž„ํ”ผ๋˜์Šค ๋ฐ ์ ˆ์ œ ๋ถ€ํ”ผ๋ฅผ ๋น„๊ตํ–ˆ์Šต๋‹ˆ๋‹ค. ๋‘ ๋ฒˆ์งธ ์‹คํ—˜์—์„œ๋Š” ์ง์ ‘ ์กฐ์ง ์˜จ๋„ ๋ชจ๋‹ˆํ„ฐ๋ง ๋ฐ ๊ธฐ์กด ์ „๊ทน(๊ฐ๊ฐ์— ๋Œ€ํ•ด n = 11๊ฐœ ์ ˆ์ œ ์˜์—ญ)์ด ์žˆ๋Š” Octopus MP ์ „๊ทน(๊ฐ๊ฐ์— ๋Œ€ํ•ด n = 12๊ฐœ ์ ˆ์ œ ์˜์—ญ)์„ ์‚ฌ์šฉํ•˜์—ฌ ๋‹ด๋‚ญ(GB) ๋ฐ ๊ฒฐ์žฅ ๊ทผ์ฒ˜์—์„œ RFA๋ฅผ ์ˆ˜ํ–‰ํ–ˆ์Šต๋‹ˆ๋‹ค. Octopus MP ์ „๊ทน๊ตฐ์—์„œ๋Š” ์˜จ๋„๊ฐ€ 60ยฐC ์ด์ƒ์œผ๋กœ ์ƒ์Šนํ•˜๋ฉด RFA๋ฅผ ์ค‘๋‹จํ•œ ๋ฐ˜๋ฉด, ๊ธฐ์กด ์ „๊ทน๊ตฐ์—์„œ๋Š” ์ด 6๋ถ„ ๋™์•ˆ RFA๋ฅผ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ์—ด ์†์ƒ์€ ๋ณ‘๋ฆฌํ•™์  ๊ฒ€์‚ฌ์— ์˜ํ•ด ๋‘ ๊ทธ๋ฃน ์‚ฌ์ด์—์„œ ํ‰๊ฐ€ ๋ฐ ๋น„๊ต๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ๊ฒฐ๊ณผ: ์ƒ์ฒด ์™ธ ์—ฐ๊ตฌ์—์„œ ๊ธฐ์กด ์ „๊ทน๊ณผ Octopus MP ์ „๊ทน์„ ๋น„๊ตํ–ˆ์„ ๋•Œ, ์‹คํ—˜ A์™€ B์—์„œ ๋…ธ์ถœ ๊ธธ์ด์— ๋”ฐ๋ฅธ ๋ณ€ํ™”์™€ ์„ฑ๋Šฅ ์ธก๋ฉด์—์„œ ๋‘ ์ „๊ทน ์‚ฌ์ด์— ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•œ ์ฐจ์ด๋Š” ์—†์—ˆ๋‹ค. ์˜จ๋„ ์ธก์ •์—์„œ ์ด ์—๋„ˆ์ง€์™€ ์ ˆ์ œ ๋ถ€ํ”ผ๋Š” ์˜จ๋„๋ฅผ ์ธก์ •ํ•˜์ง€ ์•Š์€ ๊ธฐ์กด ์ „๊ทน ๊ทธ๋ฃน๋ณด๋‹ค ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜๊ฒŒ ๋‚ฎ์•˜๋‹ค(๊ฐ๊ฐ P<0.001). ์‹์—ผ์ˆ˜๋ฅผ ์ฃผ์ž…ํ•œ ๊ทธ๋ฃน์€ ์ฃผ์ž…ํ•˜์ง€ ์•Š์€ ๊ทธ๋ฃน๋ณด๋‹ค ์ž„ํ”ผ๋˜์Šค๊ฐ€ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜๊ฒŒ ๋‚ฎ์•˜๊ณ  ์ด ์—๋„ˆ์ง€์™€ ์ ˆ์ œ ๋ถ€ํ”ผ๋Š” ์‹คํ—˜ D์—์„œ ๋” ๋†’์•˜๋‹ค(๊ฐ๊ฐ P<0.001). ์ƒ์ฒด ์™ธ ์‹คํ—˜์—์„œ ์ฒซ ๋ฒˆ์งธ ์‹คํ—˜์—์„œ Octopus MP ์ „๊ทน ๊ทธ๋ฃน์—์„œ ์ „๋‹ฌ๋œ ์ ˆ์ œ ๋ถ€ํ”ผ์™€ ์ด ์—๋„ˆ์ง€๋Š” ๊ธฐ์กด ์ „๊ทน ๊ทธ๋ฃน(15.7 ยฑ 4.26 cm3 vs. 12.5 ยฑ 2.14 cm3, p = 0.027; 5.48 ยฑ 0.49 Kcal vs. 5.04 ยฑ 0.49 Kcal, p = 0.029)๋ณด๋‹ค ํ›จ์”ฌ ์ปธ์Šต๋‹ˆ๋‹ค. ๋‘ ๋ฒˆ์งธ ์‹คํ—˜์—์„œ GB ๋ฐ ๊ฒฐ์žฅ์— ๋Œ€ํ•œ ์—ด ์†์ƒ์€ ๊ธฐ์กด ์ „๊ทน ๊ทธ๋ฃน๋ณด๋‹ค Octopus MP ์ „๊ทน ๊ทธ๋ฃน์—์„œ ๋œ ์ž์ฃผ ๋‚˜ํƒ€๋‚ฌ์Šต๋‹ˆ๋‹ค(16.7% [2/12] vs. 90.9% [10/11] GB ๋ฐ 8.3 ๊ฒฐ์žฅ์˜ ๊ฒฝ์šฐ % [1/12] ๋Œ€ 90.9% [10/11], ๋ชจ๋‘ p <0.001). GB(2.65 ยฑ 1.07 Kcal vs. 5.04 ยฑ 0.66 Kcal) ๋ฐ ๊ฒฐ์žฅ(2.58 ยฑ 0.57 Kcal vs. 5.17 ยฑ 0.90 Kcal) ์ฃผ๋ณ€์— ์ „๋‹ฌ๋œ ์ด ์—๋„ˆ์ง€๋Š” Octopus MP ์ „๊ทน ๊ทธ๋ฃน์—์„œ ๊ธฐ์กด ์ „๊ทน ๊ทธ๋ฃน๋ณด๋‹ค ํ˜„์ €ํžˆ ๋‚ฎ์•˜์Šต๋‹ˆ๋‹ค(๋ชจ๋‘์— ๋Œ€ํ•ด p <0.001). ๊ฒฐ๋ก : Octopus MP ์ „๊ทน์„ ์‚ฌ์šฉํ•˜๋Š” RFA๋Š” ๊ธฐ์กด ์ „๊ทน์— ๋น„ํ•ด ๋” ํฐ ์ ˆ์ œ ๋ถ€ํ”ผ๋ฅผ ์œ ๋„ํ•˜๊ณ  ์ธ์ ‘ ์žฅ๊ธฐ์— ๋Œ€ํ•œ ์—ด ์†์ƒ์ด ์ ์—ˆ์Šต๋‹ˆ๋‹ค.Objective: To evaluate the feasibility, ablative zone, and safety of radiofrequency ablation (RFA) using Octopus multipurpose (MP) electrodes in ex vivo and in vivo porcine liver. Materials and Methods: A total of 4 experiments were conducted in the ex vivo study. Experiments A and B compared the ablation performance with the conventional electrode and compared the performance according to the exposure length variation (20mm, 25mm, 30mm). In Experiment C, the effect of the temperature sensing electrode was verified. The output was terminated when the temperature reached 60 degrees during ablation, and it was assumed that there was an organ that should not be thermally damaged at a distance of 10 mm around the target electrode. Experiment D tested the difference in performance according to saline injection. A multipurpose electrode was inserted into the center of the two electrodes, and saline was injected for 3 minutes from 3 minutes after ablation, and the performance was compared. In in vivo study, total 16 pigs were used. RFA was performed in the liver for 6 min using the Octopus MP electrodes and the conventional electrodes to investigate the effect of saline instillation in the first experiment. Ablation energy, electrical impedance, and ablation volume were compared between the two groups. RFA was performed near the gallbladder (GB) and colon using the Octopus MP electrodes with direct tissue temperature monitoring and the conventional electrodes in the second experiment. RFA was discontinued when the temperature was increased to > 60ยฐC in the Octopus MP electrode group, while RFA was performed for a total of 6 min in the conventional electrode group. Thermal injury was assessed and compared between the two groups upon pathological examination. Results: When comparing the conventional electrode and the Octopus MP electrode in the ex vivo study, there was no statistically significant difference between the two electrodes in terms of change according to exposure length and performance in experiment A and B. In Experiment C, which compared performance according to temperature measurement, the total energy and ablation volume were statistically significantly lower than the conventional electrode group that did not measure temperature (P <0.001, respectively). The group injected with saline had a statistically significantly lower impedance than the non-injected group, and the total energy and ablation volume were higher (P<0.001, respectively) in experiment D. In the first experiment of in vivo study, the ablation volume and total energy delivered in the Octopus MP electrode group were significantly larger than that in the conventional electrode group (15.7ยฑ4.26 cm3 vs. 12.5ยฑ2.14 cm3, P=0.027; 5.48ยฑ0.49 Kcal vs. 5.04ยฑ0.49 Kcal, P=0.029). In the second experiment, thermal injury to the GB and colon was less frequently noted in the Octopus MP electrode group than in the conventional electrode group (16.7% (2/12) vs. 90.9% (10/11); 8.3% (1/12) vs. 90.9% (10/11), P<0.001 for all). The total energy delivered around the GB (2.65ยฑ1.07 Kcal vs. 5.04ยฑ0.66 Kcal) and colon (2.58ยฑ0.57 Kcal vs. 5.17ยฑ0.90 Kcal) were significantly lower in the Octopus MP electrode group than in the conventional electrode group (P<0.001 for all). Conclusion: RFA using the Octopus MP electrodes is capable of saline instillation and direct tissue temperature measurement, and induces a larger ablation volume and results in lesser thermal injury to the adjacent organs compared with conventional electrodes.Chapter 1. Introduction 4 Chapter 2. Materials and Methods 6 Chapter 3. Results 12 Chapter 4. Discussion 15 Chapter 5. Conclusion 20 Bibliography 41 Abstract in Korean 44๋ฐ•

    Fault Diagnosis of an Industrial Plant Using Maintenance Record and Multivariate Analysis

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ํ™”ํ•™์ƒ๋ฌผ๊ณตํ•™๋ถ€, 2019. 2. ์ด์ข…๋ฏผ.์ด์ƒ ๊ฐ์ง€ ๋ฐ ์ง„๋‹จ ๋ถ„์•ผ๋Š” ํ™”ํ•™ ๊ณต์ • ์‚ฌ์—…์—์„œ ๋งค์šฐ ์ค‘์š”ํ•œ ์ด์Šˆ๋กœ ๋ถ€์ƒ๋˜๋ฉด์„œ ๊ด€๋ จ๋œ ์—ฌ๋Ÿฌ ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ๊ฐœ๋ฐœ๋˜์—ˆ๋‹ค. ์ตœ๊ทผ ์ปดํ“จํ„ฐ ๊ณ„์‚ฐ ๋Šฅ๋ ฅ ํ–ฅ์ƒ ๋ฐ ์ƒˆ๋กœ์šด ํ†ต๊ณ„ ๊ธฐ๋ฒ•๋“ค์˜ ๊ฐœ๋ฐœ๋กœ ์ธํ•ด ๋ฐ์ดํ„ฐ ๊ธฐ๋ฐ˜ ์ ‘๊ทผ๋ฒ•์ด ์ด์ƒ ๊ฐ์ง€ ๋ฐ ์ง„๋‹จ ๋ถ„์•ผ์— ๋งŽ์ด ์‚ฌ์šฉ๋˜๊ณ  ์žˆ๋‹ค. ์ด์ƒ ๊ฐ์ง€ ๋ฐ ์ง„๋‹จ์„ ์œ„ํ•ด ์‹ค์ œ ์šด์˜ ๊ณต์ • ๋ฐ์ดํ„ฐ๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ๊ฒƒ์ด ๊ฐ€์žฅ ์ด์ƒ์ ์ด์ง€๋งŒ, ์‹ค์ œ ์šด์˜ ๋ฐ์ดํ„ฐ์˜ ํ™•๋ณด๊ฐ€ ์–ด๋ ต๊ณ  ์ž์„ธํ•œ ๋ฐ์ดํ„ฐ ์„ ์ฒ˜๋ฆฌ ๋ฐฉ๋ฒ•์ด ์•Œ๋ ค์ง„ ๋ฐ”๊ฐ€ ์—†์–ด ๋Œ€๋ถ€๋ถ„์˜ ์ด์ƒ ๊ฐ์ง€ ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ ํ†ต์ œ ๊ฐ€๋Šฅํ•œ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๋ฐ์ดํ„ฐ๋กœ ๊ฒ€์ฆ์ด ์ˆ˜ํ–‰๋˜์–ด ์™”๋‹ค. ์ด๋กœ ์ธํ•ด ์ด์ƒ ๊ฐ์ง€ ๋ฐ ์ง„๋‹จ์— ๋งค์šฐ ์ค‘์š”ํ•œ ๋ถ€๋ถ„์ธ ์‹ค์ œ ์šด์˜ ๋ฐ์ดํ„ฐ์— ๋Œ€ํ•œ ์„ ์ฒ˜๋ฆฌ์— ๋Œ€ํ•ด ์ด๋ฒˆ ์—ฐ๊ตฌ์—์„œ ์ •๋ฆฝํ–ˆ๋‹ค. ์‹ค์ œ ์šด์˜ ๋ฐ์ดํ„ฐ์— ๋Œ€ํ•œ ์„ ์ฒ˜๋ฆฌ๋Š” ํฌ๊ฒŒ 2๋ถ€๋ถ„(์ •๋น„ ๊ธฐ๋ก๋ถ€, ์„ผ์„œ ๋ฐ์ดํ„ฐ)์œผ๋กœ ๊ตฌ๋ถ„๋œ๋‹ค. ์ •๋น„๊ธฐ๋ก๋ถ€์˜ ๋‚ด์šฉ์€ ์ •๋น„ ํ–‰์œ„ ํŠน์„ฑ์œผ๋กœ ์˜ˆ๋ฐฉ์ •๋น„, ๊ธฐ๊ฐ„๋ณ„ ์ •๋น„, ์‹œ์ • ์ •๋น„, ์˜ˆ์ธก ์ •๋น„ ๋“ฑ ์ด4๊ฐ€์ง€๋กœ ๋ถ„๋ฅ˜๋  ์ˆ˜ ์žˆ๋‹ค. ๊ฒฐํ•จ ํŠน์„ฑ์ด ๋“œ๋Ÿฌ๋‚˜๋Š” ๋ฐ์ดํ„ฐ์ธ ์‹œ์ • ์ •๋น„๋กœ ๋ถ„๋ฅ˜๋œ 6๊ฐœ์˜ ๊ธฐ๋ก์ด ์ด๋ฒˆ ์—ฐ๊ตฌ์—์„œ ์‚ฌ์šฉ๋˜์—ˆ๋‹ค. ์„ผ์„œ ๋ฐ์ดํ„ฐ์˜ 236๊ฐœ์˜ ๋ณ€์ˆ˜๋Š” ๊ฐœ๋žต๋„์™€ ๋ฐ์ดํ„ฐ์˜ ์„ฑํ–ฅ ๋ถ„์„์„ ํ†ตํ•ด 28๊ฐœ๋กœ ๊ฐ์†Œํ•  ์ˆ˜ ์žˆ๋‹ค. 56 ์‹ค์ œ ์šด์˜ ๋ฐ์ดํ„ฐ์˜ ์ด์ƒ ๊ฐ์ง€ ๋ฐ ์ง„๋‹จ์„ ์œ„ํ•ด Dynamic Principal Component Analysis(DPCA)์™€ 1-class Support Vector Machine(SVM) ๊ธฐ๋ฒ•์„ ์‚ฌ์šฉํ–ˆ๋‹ค. DPCA๋Š” ๋ฐ์ดํ„ฐ์˜ ์ฐจ์› ์ถ•์†Œ๋ฅผ ์œ„ํ•ด ์‚ฌ์šฉํ–ˆ๊ณ  1-class SVM์€ SVM ๊ตฌ์ถ•์„ ์œ„ํ•ด1 ์ข…๋ฅ˜์˜ ๋ฐ์ดํ„ฐ๋งŒ ํ•„์š”ํ•˜๊ธฐ ๋•Œ๋ฌธ์— ์šด์˜ ๊ณต์ • ๋ฐ์ดํ„ฐ ๋ถ„๋ฅ˜์— ์ ํ•ฉํ•˜์—ฌ ์‚ฌ์šฉํ–ˆ๋‹ค. ๊ธฐ์กด์˜ SVM score๋ถ„๋ฅ˜ ์ž„๊ณ„ ๊ฐ’์€ 0 ์ด๊ณ  score ๊ฐ’์ด ์Œ์ˆ˜์ผ ๊ฒฝ์šฐ ๊ฒฐํ•จ์œผ๋กœ ๋ถ„๋ฅ˜ํ–ˆ๋‹ค. ์ด ์—ฐ๊ตฌ์—์„œ๋Š” ์—ฐ์†์ ์ธ SVM score ๊ฐ’์˜ ์ฐจ์ด๊ฐ€ 130์ผ ๊ฒฝ์šฐ๋ฅผ ๊ฒฐํ•จ์œผ๋กœ ๋ถ„๋ฅ˜ํ•˜๋Š” ์ƒˆ๋กœ์šด ์ž„๊ณ„ ๊ฐ’์„ ์ œ์•ˆํ–ˆ๋‹ค. ์„ ์ฒ˜๋ฆฌํ•œ ๋ฐ์ดํ„ฐ๋ฅผ ํ™œ์šฉํ•˜์—ฌ6๊ฐœ์˜ ์‹œ์ • ์ •๋น„ ๊ธฐ๋ก๋ถ€ ๋‚ด์šฉ์— ๋Œ€ํ•ด ์ด์ƒ ๊ฐ์ง€ ๋ฐ ์ง„๋‹จ์„ ํ•œ ๊ฒฐ๊ณผ, 5๊ฐœ์˜ ์‹œ๋‚˜๋ฆฌ์˜ค์—์„œ ์ข‹์€ ๊ฐ์ง€ ๋ฐ ์ง„๋‹จ ๊ฒฐ๊ณผ๋ฅผ ๋ณด์˜€๋‹ค. ์ด ์—ฐ๊ตฌ์—์„œ ์ œ์•ˆํ•œ ์‹ค์ œ ์šด์˜ ํ”Œ๋žœํŠธ ๋ฐ์ดํ„ฐ์— ๋Œ€ํ•œ ์„ ์ฒ˜๋ฆฌ ์„ธ๋ถ€ ๊ณผ์ •๊ณผ ์ƒˆ๋กœ์šด SVM score ์ž„๊ณ„ ๊ฐ’์œผ๋กœ ์ธํ•ด ์ด์ƒ ๊ฐ์ง€ ๋ฐ ์ง„๋‹จ์„ ์ •ํ™•ํ•˜๊ณ  ์กฐ๊ธฐ์— ์ˆ˜ํ–‰ ๊ฐ€๋Šฅํ•˜๊ฒŒ ๋˜์—ˆ๋‹ค. ๋”ฐ๋ผ์„œ ์ œ์•ˆํ•œ ๋ฐฉ๋ฒ•๋“ค์€ ์กฐ๊ธฐ ๊ฒฐํ•จ ํƒ์ง€/์ง„๋‹จ์œผ๋กœ ์˜ˆ์ธก ์ •๋น„๋ฅผ ์ˆ˜ํ–‰์„ ๊ฐ€๋Šฅ์ผ€ ํ•ด์„œ ์ตœ์ ์˜ ํ”Œ๋žœํŠธ ์šด์˜์— ์ด๋ฐ”์ง€ํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋‹ค.Many algorithms have been introduced are for fault detection and diagnosis(FDD) over the years as FDD has been important in the chemical engineering industry. Recent improvements of computation power and advances in statistical techniques, data-driven method have been more popular and well-received approach for FDD. Actual operating process data sets are optimal for FDD algorithm validation but they are hard to acquire and most of FDD algorithm is tested on controlled simulation data for convenience. Preprocess is a crucial part to FDD result, but due to the scarcity of operating process data usage, there are no known specific steps to handle and preprocess actual operating process data. ii Preprocess of actual operating data includes 2 parts: maintenance record and sensor raw data. Maintenance record entries are classified into 4 categories by analyzing the content of the entry and trait of maintenance.: corrective, preventive, predictive, periodic maintenance. Only 6 corrective maintenance record is used for FDD as they are the only type that will show fault attributes. Variables of sensor raw data have been reduced from 236 to 28 by analyzing the schematics and analyzing the data tendencies. Dynamic principal component analysis (DPCA) and 1 class support vector machine (SVM) is used as a FDD algorithm for actual operating plant data. DPCA is used to reduce dimension of data and 1-class SVM is a useful tool to classify actual operating plant data as it only needs a single type of data class to construct a SVM structure. The conventional threshold of SVM classification score is zero, and a negative value is considered as a fault. Proposed new threshold in this study is a difference of consecutive score that exceeds 130. If a difference score and following score is more than 130 than it can be classified as a fault. The result of proposed FDD with a new proposed threshold of 6 corrective maintenance record showed great detection accuracy by early detecting 5 fault scenarios. With the proposed specific steps to preprocess operating process plant data sets and new SVM classification score threshold, accurate and early process detection/diagnosis is possible. Therefore, the proposed methods can help iii optimal plant management by detecting a fault early to perform a predictive maintenance.CHAPTER 1. Introduction . 1 1.1. Research motivation . 1 1.2. Research objectives 3 1.3. Description of the equipment used in this thesis 4 1.4. Outline of the thesis 7 1.5. Outline of the thesis 9 CHAPTER 2. Methodology . 10 2.1. Multivariate analysis methods 10 2.1.1. Principal component analysis . 10 2.1.2. Hotellings T-squared and squared prediction error . 12 2.1.3. DPCA . 15 2.2. Support Vector Machine . 17 2.2.1. SVM . 17 2.2.2. 1-class support vector machine 21 CHAPTER 3. Simulation . 23 3.1. Process of pattern recognition 23 3.2. Preprocessing . 25 3.2.1. Maintenance record 26 3.2.2. Raw data . 28 3.3. Selecting optimal data set for validation 29 3.4. Algorithm Validation 31 3.4.1. Tennessee Eastman Process 31 CHAPTER 4. Result 36 4.1. Fault detection and diagnosis . 36 4.1.1. Fault detection and diagnosis result . 37 CHAPTER 5. Conclusion 53 ์ดˆ๋ก 55 References 58Maste

    A Study on Activating Factor Analysis Viewed from Process of Creating Community-based Eco-tourism village

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ํ™˜๊ฒฝ๋Œ€ํ•™์› : ํ™˜๊ฒฝ์กฐ๊ฒฝํ•™๊ณผ, 2016. 8. ์†์šฉํ›ˆ.์ตœ๊ทผ ์ง€๋ฐฉ์ž์น˜๋‹จ์ฒด์™€ ์†Œ๋‹จ์œ„ ๋งˆ์„์—์„œ๋Š” ํ™˜๊ฒฝ์„ ๋ณด์ „ํ•˜๋ฉด์„œ ์ง€์—ญ์†Œ๋“์„ ์˜ฌ๋ฆด ์ˆ˜ ์žˆ๋Š” ์ƒˆ๋กœ์šด ์ง€์—ญ์‚ฌ์—…์œผ๋กœ ์ƒํƒœ๊ด€๊ด‘๋งˆ์„์‚ฌ์—…์„ ๊ฒฝ์Ÿ์ ์œผ๋กœ ์ถ”์ง„ํ•˜๊ณ  ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๋Œ€๋ถ€๋ถ„์˜ ์‚ฌ์—…์€ ์ง€์—ญ์˜ ํ™˜๊ฒฝ์  ํŠน์„ฑ์„ ๊ณ ๋ คํ•˜์ง€ ์•Š์€ ์ฑ„ ์ •๋ถ€์˜ ์ฃผ๋„๋กœ ์ด๋ฃจ์–ด์ง€๊ณ  ์žˆ๊ณ , ์ง€์—ญ์ฃผ๋ฏผ ๋ฐ ๋‹จ์ฒด์˜ ์—ญ๋Ÿ‰๋ถ€์กฑ๊ณผ ์ฐธ์—ฌ์ €์กฐ๋กœ ์ธํ•ด ์‚ฌ์—…๊ณผ์ •์—์„œ ๋งŽ์€ ๋ฌธ์ œ๊ฐ€ ์•ผ๊ธฐ๋˜์–ด์ง€๊ณ  ์žˆ๋‹ค. ์ด์— ์ง€์—ญ ๊ณต๋™์ฒด๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ ์ฃผ๋ฏผ์ฐธ์—ฌํ˜• ์ƒํƒœ๊ด€๊ด‘๋งˆ์„์„ ๋งŒ๋“ค๊ณ , ์ง€์†๊ฐ€๋Šฅํ•˜๊ฒŒ ์šด์˜ํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ์–ด๋– ํ•œ ์š”์ธ๋“ค์ด ํ•„์š”ํ•˜๊ณ , ๊ทธ ์š”์ธ๋“ค์ด ์–ด๋– ํ•œ ๋ฐฉํ–ฅ์œผ๋กœ ๋งˆ์„์— ์ž‘์šฉํ•˜๋Š”์ง€์— ํŒŒ์•…ํ•˜์—ฌ์•ผ ํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์„ ํ˜1๋ฆฌ ๋žŒ์‚ฌ๋ฅด์‹œ๋ฒ”๋งˆ์„์˜ ํ™œ์„ฑํ™” ์‚ฌ๋ก€ ๋ถ„์„์„ ํ† ๋Œ€๋กœ ์ง€์—ญ์ฃผ๋ฏผ์˜ ์ฐธ์—ฌ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ํ•œ ์ฃผ๋ฏผ์ฃผ๋„ํ˜• ๋งˆ์„๋งŒ๋“ค๊ธฐ ์‚ฌ์—…์„ ์ง„ํ–‰ํ•˜๊ณ  ์žˆ๋Š” ์‚ฌ๋ก€์ง€์—ญ์˜ ์‚ฌ์—…๊ณผ์ •์„ ๋ถ„์„ํ•˜์—ฌ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ์˜ ๋Œ€์ƒ์ง€์ธ ์„ ํ˜๋ฆฌ ๋™๋ฐฑ๋™์‚ฐ ๋žŒ์‚ฌ๋ฅด์‹œ๋ฒ”๋งˆ์„์€ ์„ ํ˜๊ณถ์ž์™ˆ ์„œ์ชฝ์— ์œ„์น˜ํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ์„ ํ˜๊ณถ์˜ ์ผ๋ถ€์ธ ๋™๋ฐฑ๋™์‚ฐ์˜ ์ƒํƒœ์  ๊ฐ€์น˜๊ฐ€ ๋„๋ฆฌ ์•Œ๋ ค์ง€๋ฉด์„œ ๋ณดํ˜ธ์ง€์—ญ์œผ๋กœ ์ง€์ •๋˜์—ˆ๋‹ค. ๋˜ํ•œ, ๋žŒ์‚ฌ๋ฅด๋งˆ์„ ์‹œ๋ฒ”์‚ฌ์—…์ง€๋กœ ์„ ์ •๋˜์–ด, ์ด๋ฅผ ํ† ๋Œ€๋กœ ์ฃผ๋ฏผ์ฃผ๋„ํ˜• ๋งˆ์„์‚ฌ์—…์ด ์ง€์†์ ์œผ๋กœ ์ด๋ฃจ์–ด์ง€๋ฉด์„œ ๋งˆ์„์˜ ์ž์›์ธ ๋™๋ฐฑ๋™์‚ฐ์„ ์ค‘์‹ฌ์œผ๋กœ ์ƒํƒœ๊ด€๊ด‘์ด ํ™œ๋ฐœํžˆ ์ด๋ฃจ์–ด์ง€๊ณ  ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๊ณต๋™์ฒด๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ ์ฃผ๋ฏผ์ฃผ๋„ํ˜• ๋งˆ์„๋งŒ๋“ค๊ธฐ ์‚ฌ์—…์„ ์ง„ํ–‰ํ•˜๊ณ  ์žˆ๋Š” ๋žŒ์‚ฌ๋ฅด์‹œ๋ฒ”๋งˆ์„์˜ ์‚ฌ์—…๊ณผ์ •์„ ๋ถ„์„ํ•˜๊ณ , ๋งˆ์„์˜ ์ž์›๊ณผ ์‚ฌ์—…์šด์˜์— ๋Œ€ํ•œ ์ดํ•ด๋‹น์‚ฌ์ž์˜ ์˜์‹๊ตฌ์กฐ๋ฅผ ํŒŒ์•…ํ•˜์—ฌ ์ง€์—ญ๊ฒฝ์ œ์™€ ๋งˆ์„ ํ™œ์„ฑํ™”๋ฅผ ์ด๋Œ์–ด๋‚ด๊ณ  ์žˆ๋Š” ๋งˆ์„๋งŒ๋“ค๊ธฐ์˜ ๊ฐ€์น˜์™€ ํ™œ์„ฑํ™” ์š”์ธ์„ ๋„์ถœํ•ด ๋‚ด๊ณ ์ž ํ•˜์˜€๋‹ค. ๋ถ„์„์„ ํ†ตํ•ด ๋„์ถœ ๋œ ๋žŒ์‚ฌ๋ฅด์‹œ๋ฒ”๋งˆ์„ ํ™œ์„ฑํ™”์— ์ง์ ‘์ ์œผ๋กœ ์˜ํ–ฅ์„ ๋ฏธ์นœ ์š”์†Œ๋“ค์€ ๋ฆฌ๋”์™€ ์ฃผ๋ฏผํ˜‘์˜์ฒด์˜ ์—ญํ• , ์ฃผ๋ฏผ์กฐ์ง์˜ ๊ณต๋™์ฒด๊ธฐ๋ฐ˜ ํ™œ๋™, ์ž์›์˜ ๊ด€๋ฆฌ์™€ ๋ณด์ „, ๋žŒ์‚ฌ๋ฅด๋งˆ์„ ์ƒํƒœ๊ด€๊ด‘ํ”„๋กœ๊ทธ๋žจ, ๋ถ„๋ฐฐ์˜ ํ˜•ํ‰์„ฑ ์ด๋‹ค. ์ด๋ฅผ ํ† ๋Œ€๋กœ ๋‚˜ํƒ€๋‚œ ๋žŒ์‚ฌ๋ฅด์‹œ๋ฒ”๋งˆ์„์˜ ์ƒํƒœ๊ด€๊ด‘๋งˆ์„๋งŒ๋“ค๊ธฐ ์‚ฌ์—…๊ณผ์ •์˜ ํŠน์ง• ๋ฐ ๊ฒฐ๊ณผ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์ฒซ์งธ, ๋งˆ์„๋งŒ๋“ค๊ธฐ ์‚ฌ์—… ์ถ”์ง„ ์‹œ ๋งˆ์„์˜ ๋ฆฌ๋”์™€ ๋งˆ์„ ์‚ฌ์—…์˜ ํ˜„์•ˆ์— ๋Œ€ํ•ด ์กฐ์–ธ์„ ๋ฐ›๊ธฐ์œ„ํ•ด ๋‹ค์–‘ํ•œ ์ธ์ ๊ตฌ์„ฑ์œผ๋กœ ์ด๋ฃจ์–ด์ง„ ์šด์˜์กฐ์ง์ด ํ•„์š”ํ•˜๋ฉฐ, ์ดํ•ด๋‹น์‚ฌ์ž๋“ค ๊ฐ„์˜ ์˜๊ฒฌํ•ฉ์˜๊ฐ€ ์ด๋ฃจ์–ด ์ ธ์•ผ ํ•œ๋‹ค. ๋‘˜์งธ, ๋งˆ์„์ด ํ™œ์„ฑํ™”๋˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ์ฃผ๋ฏผ์˜ ์ ๊ทน์ ์ธ ์ฐธ์—ฌ๋ฅผ ์ด๋Œ์–ด ๋‚ด๊ธฐ์œ„ํ•œ ๋…ธ๋ ฅ๊ณผ ์ฃผ๋ฏผ์—ญ๋Ÿ‰์„ ๋†’์ผ ์ˆ˜ ์žˆ๋Š” ๊ต์œก์ด ํ•„์š”ํ•˜๋‹ค. ๋˜ํ•œ, ๋Œ€ํ™”๋ฅผ ํ†ตํ•ด ๊ณต๋™์˜ ๋ชฉํ‘œ๋ฅผ ๋งŒ๋“ค์–ด ๋‚˜๊ฐˆ ์ˆ˜ ์žˆ๋Š” ๋ฏผ์ฃผ์ ์ธ ์˜์‚ฌ๊ฒฐ์ • ๊ตฌ์กฐ๊ฐ€ ํ•„์š”ํ•˜๋‹ค. ์…‹์งธ, ๋งˆ์„์ด ์ง€์†๊ฐ€๋Šฅํ•œ ๋ฐœ์ „์„ ์ด๋ฃจ๊ธฐ ์œ„ํ•ด์„œ๋Š” ์ง€์—ญ์ฃผ๋ฏผ ์Šค์Šค๋กœ ์ง€์—ญ์˜ ๊ฐ€์น˜๋ฅผ ๊นจ๋‹ซ๊ณ  ์ด๋ฅผ ๊ณต์œ ํ•˜๋ฉฐ, ๋ณด์กดํ•˜๊ณ  ๊ด€๋ฆฌ ํ•  ์ˆ˜ ์žˆ๋Š” ๋ฐฉ์•ˆ์„ ์ˆ˜๋ฆฝํ•˜๋Š” ๊ฒƒ์ด ์ค‘์š”ํ•˜๋‹ค. ๋„ท์งธ, ์ง€์—ญ์ฃผ๋ฏผ ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์™ธ๋ถ€์—์„œ ๋งˆ์„์˜ ๊ฐ€์น˜๋ฅผ ์•Œ์•„๋ณด๊ณ  ์ฐพ์•„์˜ค๊ฒŒ ๋งŒ๋“œ๋Š” ๊ฒƒ ๋˜ํ•œ ์ค‘์š”ํ•˜๋‹ค. ๊ทธ ์ง€์—ญ๋งŒ์ด ๊ฐ€์ง€๋Š” ํŠน์ˆ˜์„ฑ์„ ํ™œ์šฉํ•˜์—ฌ ํ”„๋กœ๊ทธ๋žจ์„ ๊ณ„ํšํ•˜๊ณ  ์šด์˜ํ•˜๋Š” ๊ฒƒ์€ ๋งˆ์„ํ™œ์„ฑํ™”์— ์˜ํ–ฅ์„ ๋ฏธ์นœ๋‹ค. ๋‹ค์„ฏ์งธ, ๋งˆ์„์„ ์ง€์†๊ฐ€๋Šฅํ•˜๊ฒŒ ์šด์˜ํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ์ง€์—ญ์ฃผ๋ฏผ์˜ ์ผ์ž๋ฆฌ๊ฐ€ ์ฐฝ์ถœ๋˜๋ฉฐ, ์ง€์—ญ ๋‚ด๋กœ ํ™˜์›๋˜๋Š” ์ˆ˜์ต์ด ์กด์žฌํ•ด์•ผ ํ•œ๋‹ค. ๋˜ํ•œ, ํ˜•ํ‰์„ฑ ์žˆ๊ฒŒ ์ด์ต์„ ๋ถ„๋ฐฐํ•˜๊ณ  ๋งˆ์„์— ํ™˜์›ํ•˜๋Š” ๊ฒฝ์ œ๊ตฌ์กฐ๊ฐ€ ์„ฑ๋ฆฝ๋˜์–ด์•ผ ํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ƒํƒœ๊ด€๊ด‘๋งˆ์„๋งŒ๋“ค๊ธฐ ๊ณผ์ •์—์„œ ๋‚˜ํƒ€๋‚˜๋Š” ์„ฑ๊ณต์ ์ธ ์ƒํƒœ๊ด€๊ด‘๋งˆ์„ ํ™œ์„ฑํ™” ์š”์ธ๋“ค์„ ๋„์ถœํ•˜์—ฌ ๋ถ„์„ํ•˜์˜€์œผ๋ฉฐ, ์ด๋Š” ์‚ฌํšŒ์ ์œผ๋กœ๋„ ๋‹ค๋ฅธ ์ง€์—ญ์˜ ์ƒํƒœ๊ด€๊ด‘๋งˆ์„๋งŒ๋“ค๊ธฐ์— ๊ธ์ •์  ์˜ํ–ฅ์„ ๋ฏธ์น  ์ˆ˜ ์žˆ๋‹ค๋Š” ์ ์—์„œ ์˜์˜๊ฐ€ ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๋žŒ์‚ฌ๋ฅด์‹œ๋ฒ”๋งˆ์„์—์„œ ์ง„ํ–‰ํ•˜์—ฌ ๋„์ถœํ•œ ํ™œ์„ฑํ™” ์š”์†Œ๋“ค ์ค‘ ์ƒํƒœ๊ด€๊ด‘ํ”„๋กœ๊ทธ๋žจ์˜ ๋‹ค์–‘์„ฑ ๋ฐ ์ง€์†๊ฐ€๋Šฅํ•œ ๊ฒฝ์ œ์  ๊ธฐ๋ฐ˜์˜ ๋งˆ๋ จ ๋“ฑ์€ ์„ฑ๊ณต ์š”์ธ์œผ๋กœ ํŒ๋‹จํ•˜๊ธฐ์—๋Š” ์ง€์—ญ์„ ์—ฐ๊ตฌํ•˜๋Š” ๊ธฐ๊ฐ„์˜ ๋ถ€์กฑํ•˜๋‹ค๋Š”๋ฐ ๋ณธ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„์ ์ด ์žˆ๋‹ค.์ œ1์žฅ ์„œ๋ก  8 1์ ˆ. ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  8 1. ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ 8 2. ์—ฐ๊ตฌ์˜ ๋ชฉ์  10 2์ ˆ. ์—ฐ๊ตฌ์˜ ๋‚ด์šฉ ๋ฐ ๋ฐฉ๋ฒ• 11 1. ์—ฐ๊ตฌ์˜ ๋ฒ”์œ„ 11 2. ์—ฐ๊ตฌ์˜ ๋ฐฉ๋ฒ• 12 3์ ˆ. ๋Œ€์ƒ์ง€ ์„ ์ • ์ด์œ  16 ์ œ2์žฅ ์ด๋ก ์  ๊ณ ์ฐฐ 18 1์ ˆ. ์ƒํƒœ๊ด€๊ด‘๊ณผ ์ƒํƒœ๊ด€๊ด‘๋งˆ์„ 18 1. ์ƒํƒœ๊ด€๊ด‘์˜ ๋™ํ–ฅ๊ณผ ํ•œ๊ณ„ 18 2. ์ƒํƒœ๊ด€๊ด‘๋งˆ์„ 19 2์ ˆ. ์ƒํƒœ๊ด€๊ด‘๋งˆ์„์— ๋Œ€ํ•œ ์‚ฌ๋ก€ ์—ฐ๊ตฌ 22 1. ๊ตญ์™ธ ์ƒํƒœ๊ด€๊ด‘๋งˆ์„ ์‚ฌ๋ก€์—ฐ๊ตฌ 22 2. ๊ตญ๋‚ด ์ƒํƒœ๊ด€๊ด‘๋งˆ์„ ์‚ฌ๋ก€์—ฐ๊ตฌ 26 3. ์ƒํƒœ๊ด€๊ด‘๋งˆ์„ ๋งŒ๋“ค๊ธฐ์˜ ๋ฌธ์ œ ๋ฐ ํ•œ๊ณ„์ ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ 30 3์ ˆ. ์ƒํƒœ๊ด€๊ด‘๋งˆ์„ ํ™œ์„ฑํ™” ์š”์ธ์— ๋Œ€ํ•œ ์ด๋ก ์—ฐ๊ตฌ 31 1. ์ƒํƒœ๊ด€๊ด‘์˜ ํ™œ์„ฑํ™” ์š”์ธ 31 2. ๊ณต๋™์ฒด ๊ธฐ๋ฐ˜๊ด€๊ด‘์˜ ํ™œ์„ฑํ™” ์š”์ธ 32 ์ œ3์žฅ ๋Œ€์ƒ์ง€์˜ ์ดํ•ด์™€ ๋ถ„์„์˜ ํ‹€ 36 1์ ˆ. ์„ ํ˜1๋ฆฌ ๋žŒ์‚ฌ๋ฅด์‹œ๋ฒ”๋งˆ์„์˜ ์ดํ•ด 36 1. ์„ ํ˜1๋ฆฌ ๋žŒ์‚ฌ๋ฅด์‹œ๋ฒ”๋งˆ์„์˜ ํ˜„ํ™ฉ 36 2. ์„ ํ˜1๋ฆฌ ๋žŒ์‚ฌ๋ฅด์‹œ๋ฒ”๋งˆ์„์˜ ์ž์› 36 2์ ˆ. ์„ ํ˜1๋ฆฌ ๋žŒ์‚ฌ๋ฅด์‹œ๋ฒ”๋งˆ์„๋งŒ๋“ค๊ธฐ ๊ณผ์ • 39 1. ์„ ํ˜1๋ฆฌ ๋žŒ์‚ฌ๋ฅด์‹œ๋ฒ”๋งˆ์„ ๋งŒ๋“ค๊ธฐ ํ™œ๋™ 39 2. ์„ ํ˜1๋ฆฌ ๋žŒ์‚ฌ๋ฅด์‹œ๋ฒ”๋งˆ์„์˜ ํ™œ์„ฑํ™” 43 3์ ˆ. ๋ถ„์„์˜ ํ‹€ 44 1. ๋ถ„์„๋ฐฉํ–ฅ์˜ ์„ค์ • 44 2. ๋ถ„์„์˜ ํ‹€ 45 ์ œ4์žฅ ์„ ํ˜1๋ฆฌ ๋žŒ์‚ฌ๋ฅด์‹œ๋ฒ”๋งˆ์„ ๊ณต๋™์ฒด๊ธฐ๋ฐ˜ ๋งˆ์„๋งŒ๋“ค๊ธฐ์˜ ํ™œ์„ฑํ™” ์š”์ธ ๋ถ„์„ 48 1์ ˆ. ๋žŒ์‚ฌ๋ฅด์‹œ๋ฒ”๋งˆ์„ ๋ฆฌ๋”์™€ ์ฃผ๋ฏผํ˜‘์˜์ฒด์˜ ์—ญํ•  48 1. ๋งˆ์„๋งŒ๋“ค๊ธฐ ์‚ฌ์—…์˜ ์‹œ์ž‘ 48 2. ์ถ”์ง„ํ˜‘์˜์ฒด ๊ตฌ์„ฑ ๋ฐ ์—ญํ•  51 3. ์ดํ•ด๋‹น์‚ฌ์ž ์˜๊ฒฌํ•ฉ์˜ ๊ณผ์ • 53 2์ ˆ. ๋žŒ์‚ฌ๋ฅด์‹œ๋ฒ”๋งˆ์„ ์ฃผ๋ฏผ์กฐ์ง์˜ ๊ณต๋™์ฒด๊ธฐ๋ฐ˜ ํ™œ๋™ 55 1. ์ฃผ๋ฏผ์กฐ์ง ํ˜„ํ™ฉ๊ณผ ์ฐธ์—ฌ ๊ณผ์ • 55 2. ์›ํƒํšŒ์˜์™€ ์ฃผ๋ฏผ์ฐธ์—ฌ ํ”„๋กœ๊ทธ๋žจ์˜ ์šด์˜ 60 3. ์ง€์—ญ๊ณต๋™์ฒด ํ™œ๋™์— ์˜ํ•œ ์ฃผ๋ฏผ์ธ์‹๋ณ€ํ™” 64 3์ ˆ. ๋žŒ์‚ฌ๋ฅด์‹œ๋ฒ”๋งˆ์„ ์ž์›์˜ ๊ด€๋ฆฌ์™€ ๋ณด์ „ 67 1. ์ž์›์˜ ๊ฐ€์น˜๊ณต์œ ์™€ ๊ด€๋ฆฌ ๋ฐฉ์•ˆ 67 2. ๋žŒ์‚ฌ๋ฅด์‹œ๋ฒ”๋งˆ์„์˜ ์ž์› ๋ณด์ „์„ ์œ„ํ•œ ํ™œ๋™ 72 4์ ˆ. ๋žŒ์‚ฌ๋ฅด์‹œ๋ฒ”๋งˆ์„ ์ƒํƒœ๊ด€๊ด‘ํ”„๋กœ๊ทธ๋žจ 74 1. ๊ณถ์ž์™ˆ๊ณผ ๋žŒ์‚ฌ๋ฅด์Šต์ง€๋ฅผ ํ™œ์šฉํ•œ ์ƒํƒœ๊ด€๊ด‘ ํ”„๋กœ๊ทธ๋žจ 74 2. ์ƒํƒœ๊ด€๊ด‘ํ”„๋กœ๊ทธ๋žจ์˜ ํ™œ์„ฑํ™” 76 5์ ˆ. ๋žŒ์‚ฌ๋ฅด์‹œ๋ฒ”๋งˆ์„ ์ด์ต๋ถ„๋ฐฐ์˜ ํ˜•ํ‰์„ฑ 79 1. ์ƒํƒœ๊ด€๊ด‘ํ™œ๋™์„ ํ†ตํ•œ ๋งˆ์„์˜ ์ˆ˜ํ˜œ 79 2. ํ˜•ํ‰์„ฑ ์žˆ๋Š” ์ด์ต๋ถ„๋ฐฐ๋ฅผ ์œ„ํ•œ ๊ณผ์ • 82 ์ œ5์žฅ ๊ฒฐ๋ก  86 ์ฐธ๊ณ  ๋ฌธํ—Œ 89 ๋ถ€๋ก 94 Abstract 100Maste

    Effects of interleukin-13 and montelukast on the expression of zonula occludens-1 in human podocytes

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    PURPOSE: The aim of this study was to investigate whether pathologic changes in zonula occludens-1 (ZO-1) are induced by interleukin-13 (IL-13) in the experimental minimal-change nephrotic syndrome (MCNS) model and to determine whether montelukast, a leukotriene receptor antagonist, has an effect on ZO-1 restoration in cultured human podocytes. MATERIALS AND METHODS: Human podocytes cultured on bovine serum albumin-coated plates were treated with different doses of IL-13 and montelukast and then examined for distribution using confocal microscopy and for ZO-1 protein levels using Western blotting. RESULTS: ZO-1 was internalized and shown to accumulate in the cytoplasm of human podocytes in an IL-13 dose-dependent manner. High doses (50 and 100 ng/mL) of IL-13 decreased the levels of ZO-1 protein at 12 and 24 h (both p<0.01; n=3), which were significantly reversed by a high dose (0.5 ฮผM) montelukast treatment (p<0.01; n=3). CONCLUSION: Our results suggest that IL-13 alters the expression of ZO-1, and such alterations in the content and distribution of ZO-1 may be relevant in the pathogenesis of proteinuria in the MCNS model.ope

    Ultrasonographic Findings in Children with Vesicoureteral Reflux.

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    PURPOSE: The aim of this study is to investigate the renal ultrasonographic findings in children with vesicoureteral reflux (VUR). METHODS: We retrospectively reviewed the medical records of 83 patients who were diagnosed with VUR and underwent ultrasonography at Ilsan hospital between January 2000 and December 2010. RESULTS: Among 166 renal units, 108 (65.0%) were found to have vesicoureteral reflux (VUR). Fifty-one (73.9%) had VUR in renal units with abnormal ultrasonography (USG), whereas 57 (58.7%) had VUR in renal units with normal USG. Abnormal USG findings were independent risk factors for VUR (Odds ratio, 1.98; 95% CI, 1.01-3.89; P=0.045). In renal units with VUR, the number of normal USG finding was 52.8%, and the abnormal findings were as follows; increased cortical echogenicity 16.7%, hydronephrosis 17.6%, megaureter or ureter dilatation 8.3%, hydronephrosis and ureter dilatation 1.9%, duplication of ureter 1.9%, and atrophic kidney 0.9%. The prevalence of VUR was relatively higher in renal units with hydronephrosis (23/19, 82.6%), ureter dilatation (9/9, 100%), duplication of ureter (2/3, 66.6%), and atrophic kidney (1/1, 100%). CONCLUSION: Our study indicates that VUR was associated with abnormal USG findings. When there are abnormal USG findings such as hydronephrosis, ureter dilatation, duplication of ureter, and atrophic kidney in children with UTI, VCUG is recommended to detect VUR after controlling UTI.ope

    The first case of familial Mediterranean fever associated with renal amyloidosis in Korea

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    Familial Mediterranean fever (FMF) is an auto-inflammatory disease characterized by periodic episodes of fever and recurrent polyserositis. It is caused by a dysfunction of pyrin (or marenostrin) as a result of a mutation within the MEFV gene. It occurs mostly in individuals of Mediterranean origin; however, it has also been reported in non-Mediterranean populations. In this report, we describe the first case of FMF in a Korean child. As eight-year-old boy presented recurrent febrile attacks from an unknown cause, an acute scrotum and renal amyloidosis. He also showed splenomegaly, lymphadenopathy, pleural effusion, ascites and elevated acute phase reactants. After MEFV gene analysis, he was diagnosed as FMF combined with amyloidosis.ope
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