29 research outputs found

    Industrial Policy, Rent-Seeking, and Economic Development under Syngman Rhee's Government

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    1950๋…„๋Œ€์— ๋ ŒํŠธ์™€ ๋ถ€ํŒจ๊ฐ€ ๋งŒ๋“ค์–ด์ง€๋Š” ๊ตฌ์ฒด์  ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ์•Œ์•„๋ณด๊ณ , ๊ทธ๊ฒƒ์ด ๋‹น์‹œ์˜ ์‚ฐ์—…์ •์ฑ…๊ณผ ์–ด๋–ค ๊ด€๋ จ์ด ์žˆ๋Š”์ง€๋ฅผ ์‚ดํŽด๋ณด๋Š” ๊ฒƒ์ด ์ด ๊ธ€์˜ ๋ชฉ์ ์ด๋‹ค. ์ด์Šน๋งŒ ์ •๋ถ€๊ฐ€ ์†Œ๋น„์žฌ ์œ„์ฃผ์˜ ์ˆ˜์ž…๋Œ€์ฒด์‚ฐ์—…ํ™”๋ฅผ ์ถ”์ง„ ํ•  ์ˆ˜๋ฐ–์— ์—†์—ˆ๋˜ ์ฃผ๋œ ์ด์œ ๋Š” ๋ฏธ๊ตญ์ด ์ œ๊ณตํ•˜๋Š” ์›์กฐ ๋ฌผ์ž๊ฐ€ ์†Œ๋น„์žฌ ์ค‘์‹ฌ์ด์—ˆ๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ๋ฏธ๊ตญ์€ ํ•œ๊ตญ์€ ์ •์น˜์‚ฌํšŒ์ ์œผ๋กœ ์•ˆ์ •์‹œ์ผœ ๊ตญ๋ฐฉ์„ ๋‹ด๋‹น์ผ€ ํ•˜๊ณ  ์ผ๋ณธ์€ ๊ฒฝ์ œ๋ฐœ์ „์„ ํ†ตํ•ด ๋™์•„์‹œ์•„์˜ ์ค‘์‹ฌ์ด ๋˜๋„๋ก ํ•˜๊ธฐ ์œ„ํ•ด ํ•œ๊ตญ์—๋Š” ์ฃผ๋กœ ์†Œ๋น„์žฌ ์œ„์ฃผ๋กœ ์›์กฐ๋ฅผ ์ œ๊ณตํ–ˆ๋‹ค. ์†Œ๋น„์žฌ ์ค‘์‹ฌ์˜ ์ˆ˜์ž…๋Œ€์ฒด ์‚ฐ์—…ํ™”๋Š” ๊ธˆ์œตํ†ต์ œ, ์™ธํ™˜ํ†ต์ œ(์ €ํ™˜์œจ์ •์ฑ…), ๋ณดํ˜ธ๋ฌด์—ญ ์ •์ฑ…์„ ์ˆ˜๋ฐ˜ํ–ˆ๊ณ , ๋ฐ”๋กœ ์ด๋Ÿฐ ์ •์ฑ…์ˆ˜๋‹จ์ด ๋ ŒํŠธ์ถ”๊ตฌ์™€ ๋ถ€ํŒจ๊ฐ€ ์ƒ๊ฒจ๋‚  ์ˆ˜ ์žˆ๋Š” ์—ฌ์ง€๋ฅผ ์ œ๊ณตํ–ˆ๋‹ค. ์•„์šธ๋Ÿฌ ๋‹น์‹œ ์ •๋ถ€๊ฐ€ ์‹œํ–‰ํ•˜๋˜ ๊ท€์†๊ธฐ์—…์ฒด ๋ถˆํ•˜์กฐ์น˜๋„ ๋ ŒํŠธ์ถ”๊ตฌ์™€ ๋ถ€ํŒจ๊ฐ€ ์ƒ๊ฒจ๋‚  ์ˆ˜ ์žˆ๋Š” ์ฃผ์š”ํ•œ ํ†ต๋กœ์˜€๋‹ค. ์ด๋Ÿฐ ํ†ต๋กœ๋ฅผ ํ†ตํ•ด 1950๋…„๋Œ€์— ์ผ์–ด๋‚œ ๋Œ€ํ‘œ์ ์ธ ๋ถ€ํŒจ์Šค์บ”๋“ค์ด ์ค‘์„๋ถˆ ์‚ฌ๊ฑด, ๊ตญ๋ฐฉ๋ถ€ ์›๋ฉด(ๅŽŸ็ถฟ) ๋ถ€์ •์‚ฌ๊ฑด, ์‚ฐ์—…์€ํ–‰ ์—ฐ๊ณ„์ž๊ธˆ ์‚ฌ๊ฑด, ๊ธˆ์œต์˜ค์ง ์‚ฌ๊ฑด ๋“ฑ์ด๋‹ค. 1960๋…„๋Œ€ ์ดํ›„ ๊ตญ๊ฐ€์ฃผ๋„์ ์ธ ์ˆ˜์ถœ์ง€ํ–ฅ์‚ฐ์—…ํ™” ์ •์ฑ… ์•„๋ž˜์„œ๋„ ๋ ŒํŠธ์ถ”๊ตฌ์™€ ๋ถ€ํŒจ๋Š” ์žˆ์—ˆ๋‹ค. ํ•˜์ง€๋งŒ 1950๋…„๋Œ€์— ๋น„ํ•ด 1960๋…„๋Œ€ ์ดํ›„๋Š” ๊ฒฝ์ œ์  ์„ฑ๊ณผ ๋ฉด์—์„œ ํฐ ์ฐจ์ด๋ฅผ ๋ณด์˜€๋‹ค. 1950๋…„๋Œ€์— ์†Œ์ˆ˜์˜ ๋Œ€๊ธฐ์—…์—๊ฒŒ ํŠนํ˜œ์ ์œผ๋กœ ์ œ๊ณต๋œ ์œต์ž์™€ ์™ธํ™˜์€ ์ฃผ๋กœ ์ˆ˜์ž…์ˆ˜์š”๋ฅผ ์ถฉ๋‹นํ•˜๋Š”๋ฐ ์“ฐ์˜€๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๋ฐ•์ •ํฌ ์ •๋ถ€ ํ•˜์—์„œ์˜ ์ €๋ฆฌ์˜ ์œต์ž์™€ ์™ธ์ž๋Š” ์ฃผ๋กœ ์ˆ˜์ถœ์„ ํ†ตํ•ด ์„ฑ๊ณผ๋ฅผ ๋‚ด๋Š” ๊ธฐ์—…์—๊ฒŒ ์ฃผ์–ด์ง€๊ฑฐ๋‚˜ ๊ตญ๊ฐ€๊ฐ€ ํ•„์š”๋กœ ํ•˜๋Š” ์‚ฌํšŒ๊ธฐ๋ฐ˜์‹œ์„ค์ด๋‚˜ ๊ธฐ๊ฐ„(ๅŸบๅนน)์‚ฐ์—… ๋ถ„์•ผ์— ํˆฌ์ž…๋˜์—ˆ๋‹ค. ๋”ฐ๋ผ์„œ ๋˜‘๊ฐ™์ด ์œต์ž๋ฅผ ๋‘˜๋Ÿฌ์‹ผ ํŠนํ˜œ์˜ ์ถ”๊ตฌ๋ผ ํ• ์ง€๋ผ๋„ 1950๋…„๋Œ€์˜ ๊ทธ๊ฒƒ์€ ์†Œ๋น„์ ์ด์—ˆ๋‹ค๋ฉด, 1960๋…„๋Œ€์˜ ๊ทธ๊ฒƒ์€ ์„ฑ๊ณผ์— ๋”ฐ๋ฅธ ๋ณด์ƒ์˜ ์„ฑ๊ฒฉ์„ ์ง€๋…”๋‹ค๋Š” ์ ์—์„œ ๋ณด๋‹ค ์ƒ์‚ฐ์ ์ด์—ˆ๋‹ค๊ณ  ํ•  ์ˆ˜ ์žˆ๋‹ค.The purpose of this paper is to analyze how rent and corruption were made under the import substitution industrialization(ISI) policy of Syngman Rhee's government. The important policy instruments of ISI were financial repression, foreign exchange control, protective trade policy, under which room for rent-seeking and corruption could be created. Another route for rent-seeking and corruption was the privatization policy of the vested properties. Under these circumstances there were the four well-known corruption scandals in 1950s: tungsten dollar scandal, cotton scandal, the Industrial Bank scandal, the Saving Bank scandal. Even though there were also rent-seeking and corruption under the export oriented industrialization(EOI) policy of Park Chung Hee's government, 1960s showed much better economic performance than 1950s. Loans and dollar which had been preferentially distributed to a few big capitalists in 1950s were mainly used to import materials for producing consumption goods. But Park's government gave preferential loans(domestic and foreign) to the companies which showed their economic performance through export. In this sense, preferential loans in 1960s could be used more productively, whereas those of 1950s were wastefully consumed

    (The) effect of nicotine & NNK on growth & attachment of gingival fibroblast from smoker and non-smoker

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    ์น˜์˜ํ•™๊ณผ/์„์‚ฌ[ํ•œ๊ธ€] ์น˜์ฃผ์งˆํ™˜์˜ ์›์ธ์˜ ํ•˜๋‚˜๋กœ ์ธ์‹๋˜๋Š” ํก์—ฐ์ด ์น˜์ฃผ์กฐ์ง์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ์—ฐ๊ตฌํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ํก์—ฐ์ž์™€ ๋น„ํก์—ฐ์ž์˜ ์น˜์€์„ฌ์œ ์•„์„ธํฌ๋ฅผ ๊ฐ๊ธฐ ๋ฐฐ์–‘ํ•˜์—ฌ, ์ด๋“ค ์„ธํฌ๊ตฐ์— ๋‹ˆ์ฝ”ํ‹ด๊ณผ nicotine-derived nitfosaminoketone(NNK)๋ฅผ ๊ฐ๊ฐ 50, 100ng/m1์„ ์ฒ˜๋ฆฌํ•œ ํ›„ ๊ฐ 30๋ถ„, 60๋ถ„, 90๋ถ„, 120๋ถ„, 240๋ถ„์— ๋ถ€์ฐฉ๋„๋ฅผ ๊ฒ€์‚ฌํ•˜์˜€๋‹ค. ๊ฐ™์€ ๋ฐฉ๋ฒ•์œผ๋กœ ๋ถ€์ฐฉ ํ›„ 24์‹œ๊ฐ„, 48์‹œ๊ฐ„, 72์‹œ๊ฐ„, 96์‹œ๊ฐ„, 144์‹œ๊ฐ„์—์„œ ๋‹ˆ์ฝ”ํ‹ด๊ณผ NNK๋ฅผ 1ํšŒ ๋ฐ 3ํšŒ ์ฒ˜๋ฆฌํ•œ ์„ธํฌ๊ตฐ์˜ ์„ฑ์žฅ๋„๋ฅผ ๊ฒ€์‚ฌํ•˜์—ฌ ๊ฐ ์‹œ๊ฐ„์— ๋”ฐ๋ฅธ ๋ถ€์ฐฉ๋„์™€ ์„ฑ์žฅ๋„๋ฅผ ๋น„๊ตํ•˜์—ฌ ๋‹ค์Œ๊ณผ ๊ฐ™์€ ๊ฒฐ๋ก ์„ ์–ป์—ˆ๋‹ค. 1. ํก์—ฐ์ž์™€ ๋น„ํก์—ฐ์ž์˜ ์น˜์€์„ฌ์œ ์•„์„ธํฌ์˜ ๋ถ€์ฐฉ๋„์™€ ์„ฑ์žฅ๋„๋Š” ๋น„ํก์—ฐ์ž์˜ ๊ตฐ์—์„œ ๋ชจ๋“  ์‹œ๊ฐ„๋Œ€์— ๊ฑธ์ณ ์œ ์˜์„ฑ ์žˆ๊ฒŒ ๋†’๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค(P<0.05). 2. ๋น„ํก์—ฐ์ž์˜ ์น˜์€์„ฌ์œ ์•„์„ธํฌ์— ๋‹ˆ์ฝ”ํ‹ด๊ณผ NNK์ฒ˜๋ฆฌํ•˜์—ฌ ๋ถ€์ฐฉ๋„์™€ ์„ฑ์žฅ๋„๋ฅผ ๋น„๊ตํ•˜์˜€์„ ๋•Œ ์ฒ˜๋ฆฌ๊ตฐ์ด ๋Œ€๋ถ€๋ถ„์˜ ๊ตฌ๊ฐ„์—์„œ ์œ ์˜์„ฑ ์žˆ๊ฒŒ ๋‚ฎ๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค(P<0.05). 3. ํก์—ฐ์ž์˜ ์น˜์€์„ฌ์œ ์•„์„ธํฌ์— ๋‹ˆ์ฝ”ํ‹ด๊ณผ NNK์ฒ˜๋ฆฌํ•˜์—ฌ ๋ถ€์ฐฉ๋„์™€ ์„ฑ์žฅ๋„๋ฅผ ๋น„๊ตํ•˜์˜€์„ ๋•Œ ๊ทธ ์˜ํ–ฅ์€ ๋ถˆ๊ทœ์น™ํ•˜๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ด์ƒ์˜ ๊ฒฐ๊ณผ์—์„œ ๋น„ํก์—ฐ์ž์˜ ์น˜์€์„ฌ์œ ์•„์„ธํฌ๊ฐ€ ํก์—ฐ์ž์˜ ์น˜์€์„ฌ์œ ์•„์„ธํฌ๋ณด๋‹ค ๋ถ€์ฐฉ๋„์™€ ์„ฑ์žฅ๋„๊ฐ€ ๋†’์•˜๊ณ  ๋น„ํก์—ฐ์ž์˜ ์น˜์€์„ฌ์œ ์•„์„ธํฌ๊ฐ€ ํก์—ฐ์ž์˜ ์น˜์€์„ฌ์œ ์•„์„ธํฌ๋ณด๋‹ค ๋‹ˆ์ฝ”ํ‹ด๊ณผ NNK์— ๋Œ€ํ•œ ๊ฐ์ˆ˜์„ฑ์ด ๋†’์€ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ด๋กœ ๋ฏธ๋ฃจ์–ด ๋‹ˆ์ฝ”ํ‹ด๊ณผ NNK๋Š” ์น˜์€์กฐ์ง์˜ ๋ถ€์ฐฉ๊ณผ ์„ฑ์žฅ์— ํ•ด๋กœ์šด ์˜ํ–ฅ์„ ์ค€๋‹ค๊ณ  ์‚ฌ๋ฃŒ๋œ๋‹ค. [์˜๋ฌธ] In order to study the effects of cigarette smoking on periodontal tissues, gingival flbroblasts from the smoking and non-smnking groups were cultured and each group were treated with nicotine(50ng/m1, 100ng/m1) and NNK(50ng/m1, 100ng/m1)to test their attachment ability at time intervals of 30minutes, 60minutes, 90minutes, 120minutes, and 240ninutes. Using the same method the growth each group treated with nicotine and NNK to compare their attachment ability and growth rate. The Results are as follows. 1. In comparing the attachnent ability and growth rate between the smnking and non-smoking group were significantly higher in all time intervals. 2. When the attachment ability was compared among these two groups after treatment with nicotine and NNK, the non-smoking group showed decrease in attachment ability while the smoking group was not affected. 3. The growth rate of these two groups were compared after treating with nicotine and NNK The growth rate of fibroblast from the non-smoking group decreased while fiboblast from the smoking group was not affected. These results suggest that fibroblast from the non-smoking group showed higher attarhment ability, growth rate, and sensitivity to nicotine and NNK. This implies that fibroblast from the non-smoking group is a more reliable source in testing the cytotoxicity of nicotine and NNK. Also it could be reasonable to think that nicotine and NNK is a probable cause for problems in attachment and repair mechanismrestrictio

    ์„ฑ๊ฒฌ์˜ 1๋ฉด ๊ณจ๋‚ด๋‚ญ์—์„œ ํ…ŒํŠธ๋ผ์‚ฌ์ดํด๋ฆฐ๊ณผ ํ•ฉ์„ฑ๋œ ์ฐจ๋‹จ๋ง‰์ด ์น˜์ฃผ์กฐ์ง

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    Dept. of Dental Science/๋ฐ•์‚ฌ[ํ•œ๊ธ€] ์น˜์ฃผ ์น˜๋ฃŒ์˜ ์ตœ์ข… ๋ชฉ์ ์€ ์ง„ํ–‰๋˜๋Š” ์น˜์ฃผ ์งˆํ™˜์˜ ์ฆ์ƒ์„ ์ œ๊ฑฐํ•˜๋Š” ๊ฒƒ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์ด๋ฏธ ํŒŒ๊ดด๋œ ์ง€์ง€์กฐ์ง์„ ๊ธฐ๋Šฅ์ ์œผ๋กœ ์žฌ์ƒ์‹œํ‚ค๋Š”๋ฐ ์žˆ๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ์กฐ์ง์œ ๋„ ์žฌ์ƒ์ˆ , ๊ณจ ์ด์‹์ˆ ๊ณผ ์„ฑ์žฅ ์ธ์ž์˜ ์ ์šฉ ๋“ฑ ๋‹ค์–‘ํ•œ ์น˜์ฃผ ์žฌ์ƒ์„ ์œ„ํ•œ ์ˆ ์‹์ด ์‹œํ–‰๋˜์–ด์ ธ ์™”์œผ๋‚˜, ๊ทธ ๊ฐ๊ฐ์ด ๋ชจ๋‘ ํ•œ๊ณ„๋ฅผ ๋‚˜ํƒ€๋‚ด๊ณ  ์žˆ๋‹ค. ํŠนํžˆ ์ฐจ๋‹จ๋ง‰์„ ์ด์šฉํ•œ ์น˜์ฃผ์กฐ์ง์žฌ์ƒ์ˆ ์€ ์˜ค๋žœ๊ธฐ๊ฐ„์— ๊ฑธ์ณ ์‹คํ—˜๋˜๊ณ  ์ž„์ƒ์— ์ ์šฉ๋˜๊ณ  ์žˆ์œผ๋‚˜ ๊ทธ ์žฌ๋ฃŒ๊ฐ€ ๊ฐ€์ง„ ํŠน์„ฑ๊ณผ ์ž„์ƒ์  ์ ์šฉ์˜ ์–ด๋ ค์›€์œผ๋กœ ์ธํ•ด ์ˆ ํ›„ ๊ฐ์—ผ๊ณผ ์น˜์€ ํ‡ด์ถ• ๋“ฑ์œผ๋กœ ์ธํ•œ ์น˜์ฃผ์žฌ์ƒ์กฐ์ง์˜ ํ•œ๊ณ„์„ฑ์„ ๋‚˜ํƒ€๋ƒˆ๋‹ค. ์ด์— ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์„ฑ๊ฒฌ์˜ 1๋ฉด ๊ณจ๋‚ด๋‚ญ์— TC-PLGA์™€ PLGA membrane์„ ์ ์šฉํ•˜์˜€์„ ๋•Œ ์น˜์ฃผ์กฐ์ง ์žฌ์ƒ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ํ‰๊ฐ€ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ๋น„๊ธ€๊ฒฌ์˜ ์–‘์ธก ํ•˜์•… ์ œ 1 ์†Œ๊ตฌ์น˜ ๊ทผ ์›์‹ฌ๋ฉด๊ณผ ์ œ 3 ์†Œ๊ตฌ์น˜ ๊ทผ์‹ฌ๋ฉด์— ๊ทผ์›์‹ฌํญ 4 ใŽœ, ์น˜์กฐ์ •์—์„œ ๊นŠ์ด 4 ใŽœ์˜ 1๋ฉด ๊ณจ๊ฒฐ์†๋ถ€๋ฅผ ํ˜•์„ฑํ•˜์—ฌ ์น˜์€๋ฐ•๋ฆฌ ์†ŒํŒŒ์ˆ ๋งŒ ์‹œํ–‰ํ•œ ๋ถ€์œ„๋ฅผ ๋Œ€์กฐ๊ตฐ์œผ๋กœ, ์น˜์€๋ฐ•๋ฆฌ ์†ŒํŒŒ์ˆ  ํ›„ PLGA membrane๋ฅผ ์ ์šฉํ•œ ๊ตฐ์„ ์‹คํ—˜ 1๊ตฐ์œผ๋กœ, ์น˜์€๋ฐ•๋ฆฌ ์†ŒํŒŒ์ˆ  ํ›„ TC-PLGA membrane๋ฅผ ์ ์šฉํ•œ ๊ตฐ์„ ์‹คํ—˜ 2๊ตฐ์œผ๋กœ ์„ค์ •ํ•˜์—ฌ ์‹คํ—˜ํ•˜๊ณ  ์ˆ  ํ›„ 8์ฃผ์— ์น˜์œ  ๊ฒฐ๊ณผ๋ฅผ ์กฐ์งํ•™์ ์œผ๋กœ ๋น„๊ต ๊ด€์ฐฐํ•˜์—ฌ ๋‹ค์Œ๊ณผ ๊ฐ™์€ ๊ฒฐ๋ก ์„ ์–ป์—ˆ๋‹ค. 1. ์ ‘ํ•ฉ์ƒํ”ผ์˜ ์น˜๊ทผ๋‹จ ์ด๋™๋Ÿ‰์€ ๋Œ€์กฐ๊ตฐ, ์‹คํ—˜ 1๊ตฐ, ์‹คํ—˜ 2๊ตฐ์—์„œ ๊ฐ๊ฐ 1.20 ยฑ 0.27 ใŽœ, 1.21 ยฑ 0.26 ใŽœ, 0.66 ยฑ 0.17 ใŽœ๋กœ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ, ๋Œ€์กฐ๊ตฐ๊ณผ ์‹คํ—˜ 2๊ตฐ๊ฐ„์—๋Š” ์œ ์˜์„ฑ ์žˆ๋Š” ์ฐจ์ด๊ฐ€ ์žˆ์—ˆ๊ณ  (P<0.05), ๋Œ€์กฐ๊ตฐ๊ณผ ์‹คํ—˜ 1๊ตฐ๊ณผ๋„ ์œ ์˜์„ฑ ์žˆ๋Š” ์ฐจ์ด๊ฐ€ ์—†์—ˆ์œผ๋ฉฐ, ์‹คํ—˜ 1๊ตฐ๊ณผ ์‹คํ—˜ 2๊ตฐ๊ฐ„์—๋„ ์œ ์˜์„ฑ์žˆ๋Š” ์ฐจ์ด๊ฐ€ ์žˆ์—ˆ๋‹ค. (P<0.05) 2. ๊ฒฐํ•ฉ์กฐ์ง ์œ ์ฐฉ์˜ ๊ธธ์ด๋Š” ๋Œ€์กฐ๊ตฐ, ์‹คํ—˜ 1๊ตฐ, ์‹คํ—˜ 2๊ตฐ์—์„œ ๊ฐ๊ฐ 0.85 ยฑ 0.43 ใŽœ, 0.69 ยฑ 0.17 ใŽœ, 0.64 ยฑ 0.10 ใŽœ๋กœ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ, ๋Œ€์กฐ๊ตฐ๊ณผ ์‹คํ—˜ 1, 2๊ตฐ๊ฐ„์— ์œ ์˜์„ฑ ์žˆ๋Š” ์ฐจ์ด๋Š” ์—†์—ˆ๋‹ค. 3. ์‹ ์ƒ๋ฐฑ์•…์งˆ ํ˜•์„ฑ์€ ๋Œ€์กฐ๊ตฐ์—์„œ 2.00 ยฑ 0.70 ใŽœ, ์‹คํ—˜ 1๊ตฐ์—์„œ 3.16 ยฑ 0.37 ใŽœ, ์‹คํ—˜ 2๊ตฐ์—์„œ 3.72 ยฑ 0.53 ใŽœ๋กœ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ, ๋Œ€์กฐ๊ตฐ๊ณผ ์‹คํ—˜ 1๊ตฐ ๋ฐ ๋Œ€์กฐ๊ตฐ๊ณผ ์‹คํ—˜ 2๊ตฐ ์‚ฌ์ด์— ์œ ์˜์„ฑ์žˆ๋Š” ์ฐจ์ด๋ฅผ ๋ณด์˜€๋‹ค(P<0.05).์‹คํ—˜ 1๊ตฐ๊ณผ ์‹คํ—˜ 2๊ตฐ ์‚ฌ์ด์—๋Š” ์œ ์˜์„ฑ์žˆ๋Š” ์ฐจ์ด๊ฐ€ ์—†์—ˆ๋‹ค. 4. ์‹ ์ƒ๊ณจ ํ˜•์„ฑ์€ ๋Œ€์กฐ๊ตฐ, ์‹คํ—˜ 1๊ตฐ, ์‹คํ—˜ 2๊ตฐ์—์„œ ๊ฐ๊ฐ 1.46 ยฑ 0.68 ใŽœ, 2.39 ยฑ 0.52 ใŽœ, 2.88 ยฑ 0.66 ใŽœ๋กœ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ, ๋Œ€์กฐ๊ตฐ๊ณผ ์‹คํ—˜ 1๊ตฐ ๋ฐ ๋Œ€์กฐ๊ตฐ๊ณผ ์‹คํ—˜ 2๊ตฐ ์‚ฌ์ด์— ์œ ์˜์„ฑ์žˆ๋Š” ์ฐจ์ด๋ฅผ ๋ณด์˜€๋‹ค(P<0.05). ์‹คํ—˜ 1๊ตฐ๊ณผ ์‹คํ—˜ 2๊ตฐ ์‚ฌ์ด์—๋Š” ์œ ์˜์„ฑ์žˆ๋Š” ์ฐจ์ด๊ฐ€ ์—†์—ˆ๋‹ค. ์ด์ƒ์˜ ๊ฒฐ๊ณผ์—์„œ ๋ณผ ๋•Œ, ์„ฑ๊ฒฌ์˜ 1๋ฉด ๊ณจ๊ฒฐ์†๋ถ€์— TC-PLGA membrane์„ ์‚ฌ์šฉํ•œ ๊ฒฝ์šฐ ์ƒํ”ผ ์ด์ฃผ ์–ต์ œ ํšจ๊ณผ๊ฐ€ ์žˆ์—ˆ์œผ๋ฉฐ, ์‹ ์ƒ๋ฐฑ์•…์งˆ๊ณผ ์‹ ์ƒ๊ณจ ํ˜•์„ฑ๋„ ์ฆ๊ฐ€์‹œํ‚ฌ ์ˆ˜ ์žˆ์Œ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๊ณ , ๋”ฐ๋ผ์„œ TC-PLGA membrane์€ ์น˜์ฃผ์กฐ์ง ์žฌ์ƒ์— ํšจ๊ณผ์ ์ธ ์žฌ๋ฃŒ๋ผ๊ณ  ์‚ฌ๋ฃŒ๋œ๋‹ค. [์˜๋ฌธ] Guided tissue regeneration (GTR) is an accepted therapeutic modality for the treatment of periodontal destructive lesions. However, incomplete regeneration or infection of surgery site is often noted after GTR therapy. The purpose of this study was to evaluate the regenerative effects of TC-PLGA and PLGA barrier membrane implanted to the preclinical one wall intrabony defects surgically created in beagle dogs. 4ยกยฟ4 ยง(r) defects were created in bilateral mandibular second and fourth premolars. The surgical control group received flap operation only. The subjects were sacrificed at eight weeks after operation, and the comparative histological examination of their healing results yielded the following conclusion. 1. In comparison of extension of junctional epithelium migration, a significant difference showed between the surgical control and TC-PLGA membrane group (P<0.05), and also between membrane and TC-PLGA membrane group (P<0.05) 2. In comparison of connective tissue adhesion, no significant difference was apparent between the groups. 3. Cementum regeneration amounted to 2.00ยก3/40.70 ยง(r) (49.5% of the depth of defects), 3.16 ยก3/4 0.37 ยง(r) (62.5 %), and 3.72 ยก3/4 0.53 ยง(r) (73.8%) respectively in the surgical control, membrane, and TC membrane group. Both the TC membrane group and the membrane group showed a significant difference from the control group (P<0.05). No significant difference was seen between PLGA membrane group and TC-PLGA membrane group. 4. Alveolar bone regeneration amounted to 1.46 ยก3/4 0.68 ยง(r) (24.8% of the depth of defects), 2.39ยก3/40.52ยง(r) (47.2%), and 2.88ยก3/40.66ยง(r) (57.1%) respectively in the surgical control, PLGA membrane, and TC-PLGA membrane group. Both the TC-PLGA membrane group and the PLGA membrane group showed a significant difference from the control group (P<0.05). No significant difference was seen between PLGA membrane group and TC-PLGA membrane group (P<0.05). The above results demonstrate the beneficial effect of TC-PLGA membranes to the preclinical one wall intrabony defects of beagle dogs. The inhibited apical migration of epithelium and the increase in new bone and new cementum suggest the potency of TC-PLGA membrnae in inducing periodontal tissue regeneration.ope

    Effects of Diet Composition on Glucose Metabolism in Liver and Muscle of Rat

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    ์˜ํ•™๊ณผ/๋ฐ•์‚ฌ[ํ•œ๊ธ€] ์„ธํฌ๋‚ด ์ค‘๊ฐ„์‹ ์ง„๋Œ€์‚ฌ(intermediary metabolism)๋Š” ์‹์ด์กฐ์„ฑ์ฐจ์ด ๋ฐ ๊ทธ ํˆฌ์—ฌ๋ฐฉ๋ฒ•์— ์˜ํ•ด ์˜ํ–ฅ์„ ๋ฐ›๋Š”๋‹ค๋Š” ์‚ฌ์‹ค์€ ์ค‘์‹ฌ์œผ๋กœ ๋ณด๊ณ ๋˜์–ด ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์‹์ด์กฐ์„ฑ์„ ๋‹ฌ๋ฆฌํ•˜์—ฌ ์‚ฌ์œกํ•œ ๋ฐฑ์„œ์— ์—๋„ˆ์ง€์›์œผ๋กœ glucose๋ฅผ ์žฌํˆฌ์—ฌํ•  ๋•Œ glycogen ํ•ฉ์„ฑ, ๋‹จ๋ฐฑ์งˆ ๋ฐ ์ง€๋ฐฉํ•ฉ์„ฑ๊ณผ glucose ๋Œ€์ƒ๊ณผ์ •์— ์–ด๋–ป๊ฒŒ ์˜ํ–ฅํ•˜์—ฌ ๋Œ€์‚ฌ๋˜๋Š”์ง€์— ๋Œ€ํ•ด์„œ๋Š” ์•„์ง ์—ฐ๊ตฌ๋ณด๊ณ ๊ฐ€ ์—†๋‹ค. ์ด์— ๋ณธ์ธ์€ 130g ๋‚ด์™ธ์˜ ์ •์ƒ์ ์ธ ์›…์„ฑ ๋ฐฑ์„œ๋ฅผ ์ •์ƒ, ๊ณ ํ•จ์ˆ˜ํƒ„์†Œ, ์ €ํ•จ์ˆ˜ํƒ„์†Œ, ๊ณ ์ง€๋ฐฉ ์‹์ด๊ตฐ์œผ๋กœ ๋‚˜๋ˆ„์–ด ํ•ด๋‹น์‹์ด๋กœ 2์ฃผ๊ฐ„ ์‚ฌ์œกํ•˜์—ฌ ๋™๋ฌผ์„ ๊ฐ ์‹์ด์— ์ ์‘์‹œํ‚จ ๋‹ค์Œ cold D-glucose๋ฅผ ์ฒด์ค‘ 100g๋‹น 250mg์”ฉ stomach tube๋กœ ์ฃผ์ž…ํ•œ ์งํ›„ D-glucose (14)**C(U) (55 ร—10**5 dpm)์„ ๋ณต๊ฐ•๋‚ด ์ฃผ์‚ฌํ•˜๊ณ  2,4,6์‹œ๊ฐ„๋งˆ๋‹ค ๊ฐ ์‹์ด๊ตฐ์˜ ๋ฐฑ์„œ๋ฅผ ํฌ์ƒ์‹œ์ผœ D-glucose (14)**C(U)์ด ์–ด๋–ป๊ฒŒ ๋Œ€์‚ฌ๋˜์–ด (14)**CO^^2, ์ง€๋ฐฉ, ๋‹น์งˆ๋กœ ์œ ์ž…๋˜๋Š”์ง€ ๊ด€์ฐฐํ•˜๊ณ  ๋„์‹œ์— ๋ฐฑ์„œ ๊ฐ„์žฅ์—์„œ ์„ธํฌ์งˆ(cytosol), mitochondria, microsome์„ ์†Œ์ •์˜ ๋ฐฉ๋ฒ•์œผ๋กœ ๋ถ„๋ฆฌํ•˜์—ฌ ์ด ๊ฐ ์†Œ๊ธฐ๊ด€๋‚ด ๋‹จ๋ฐฑ์งˆ, ์ง€๋ฐฉ์— D-glucose (14)**C(U)์—์„œ ์œ ์ž…๋œ radioactivity๋ฅผ ๊ด€์ฐฐ (14)**CO^^2ํ•˜์—ฌ D-glucose (14)**C(U)์˜ ๋Œ€์‚ฌ๊ฐ€ ์ด๋“ค ์†Œ๊ธฐ๊ด€์—์„œ๋Š” ์–ด๋–ค ์˜ํ–ฅํ•˜์— ๋Œ€์‚ฌ๋˜๋Š”์ง€๋ฅผ ๋ฐํžˆ๊ณ ์ž ๋ณธ ์‹คํ—˜์— ์ฐฉ์ˆ˜ํ•˜์—ฌ ๋‹ค์Œ๊ณผ ๊ฐ™์€ ๊ฒฐ๊ณผ๋ฅผ ์–ป์—ˆ๋‹ค. 1. ์‹์ด์กฐ์„ฑ์„ ๋‹ฌ๋ฆฌํ•˜์—ฌ 2์ฃผ๊ฐ„ ๋ฐฑ์„œ๋ฅผ ์‚ฌ์œกํ•œ ์ •์ƒ ์‹์ด๊ตฐ, ์ €ํ•จ์ˆ˜ํƒ„์†Œ ์‹์ด๊ตฐ, ๊ณ ์ง€๋ฐฉ ์‹์ด๊ตฐ์—์„œ ์ฒด์ค‘์ด ๊ฐ๊ฐ 70,60,80g์ด ์ฆ๊ฐ€ํ•˜์˜€๊ณ  ๊ณ ํ•จ์ˆ˜ํƒ„์†Œ ์‹์ด๊ตฐ์€ ๋ณ€ํ™”๊ฐ€ ์—†์—ˆ๋‹ค. ์ฒด์ค‘์— ๋Œ€ํ•œ ๊ฐ„์žฅ๋ฌด๊ฒŒ ๋น„๋Š” ๊ณ ํ•จ์ˆ˜ํƒ„์†Œ ์‹์ด๊ตฐ์ด ํƒ€๊ตฐ์— ๋น„ํ•ด 18% ์ฆ๊ฐ€ํ•˜์˜€๋‹ค. 2. ๊ฐ ์‹์ด๊ตฐ์— D-glucose (14)**C(U)์„ ํˆฌ์—ฌ์‹œ (14)**CO^^2์˜ ๋ฐฐ์„ค์€ 2์‹œ๊ฐ„ํ›„์— ๊ฐ ์‹์ด๊ตฐ์—์„œ ๋ชจ๋‘ ์ตœ๊ณ ์น˜์— ๋„๋‹ฌํ•˜๊ณ  ๊ณ ํ•จ์ˆ˜ํƒ„์†Œ ์‹์ด๊ตฐ์€ ์ •์ƒ ์‹์ด๊ตฐ์˜ 2.6๋ฐฐ, ์ €ํ•จ์ˆ˜ํƒ„์†Œ ์‹์ด๊ตฐ์€ 1.5๋ฐฐ ์ฆ๊ฐ€๋˜์—ˆ์œผ๋ฉฐ ๊ณ ์ง€๋ฐฉ ์‹์ด๊ตฐ์€ 20% ๊ฐ์†Œ๋˜์—ˆ๋‹ค. 6์‹œ๊ฐ„ ํ›„ (14)**CO^^2 ๋ฐฐ์„ค๋Ÿ‰์€ ๊ณ ํ•จ์ˆ˜ํƒ„์†Œ ์‹์ด๊ตฐ๊ณผ ๊ณ ์ง€๋ฐฉ ์‹์ด๊ตฐ์ด ์ •์ƒ ์‹์ด๊ตฐ ๋ณด๋‹ค ์˜์˜์žˆ๊ฒŒ ๋‚ฎ์•˜๋‹ค(p<0.05). 3. ๊ฐ„์žฅ์—์„œ glycogen ํ•จ๋Ÿ‰์€ D-glucose ํˆฌ์—ฌ ํ›„ 4์‹œ๊ฐ„์— ๊ฐ๊ตฐ์—์„œ ์ตœ๊ณ ์น˜์— ๋‹ฌํ•˜์˜€๊ณ  ๊ทธ ํ›„ ๊ฐ™์€ ๋น„์œจ๋กœ ์•ฝ๊ฐ„ ๊ฐ์†Œํ•˜์˜€๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ •์ƒ ์‹์ด๊ตฐ์€ 2์‹œ๊ฐ„์— ์ตœ๊ณ ์น˜์— ๋‹ฌํ•˜๊ณ  ๊ทธํ›„ ๊ฐ์†Œํ•˜์˜€์œผ๋ฉฐ ๊ฐ์†Œ์œจ์ด ๊ฐ€์žฅ ๋นจ๋ž๋‹ค. 6์‹œ๊ฐ„ ํ›„ ๊ฐ๊ตฐ์˜ glycogen ํ•จ๋Ÿ‰์€ ๊ณ ํ•จ์ˆ˜ํƒ„์†Œ ์‹์ด๊ตฐ์—์„œ ๊ฐ€์žฅ ๋†’์•˜๊ณ  ์ •์ƒ ์‹์ด๊ตฐ์—์„œ ๊ฐ€์žฅ ๋‚ฎ์•˜๋‹ค. ๊ทผ์œก glycogen ์–‘์€ ๊ฐ„์žฅ glycogen์–‘์˜ ์•ฝ 20%์ด์—ˆ์œผ๋ฉฐ ์‹์ด ํˆฌ์—ฌํ›„ 2์‹œ๊ฐ„์— ์ตœ๊ณ ์น˜์— ๋‹ฌํ•˜๊ณ  ๊ทธํ›„ ๋ณ€๋™์ด ์—†์—ˆ๋‹ค. D-glucose(14)**CO(U)์œผ๋กœ๋ถ€ํ„ฐ ์œ ๋ž˜๋œ glycogen ํ•จ๋Ÿ‰์€ 6์‹œ๊ฐ„๊นŒ์ง€ ๊ณ„์† ์ฆ๊ฐ€ํ•˜์˜€์œผ๋ฉฐ ๊ณ ํ•จ์ˆ˜ํƒ„์†Œ ์‹์ด๊ตฐ์—์„œ ํ•ฉ์„ฑ์†๋„๊ฐ€ ๊ฐ€์žฅ ๋น ๋ฅด๊ณ  ๊ณ ์ง€๋ฐฉ ์‹์ด๊ตฐ์ด ๊ฐ€์žฅ ๋Š๋ ธ๋‹ค. 4. ๊ฐ„์žฅ ์ด ์ง€๋ฐฉ๋Ÿ‰์€ ๊ณ ์ง€๋ฐฉ ์‹์ด๊ตฐ์ด ๊ฐ€์žฅ ๋†’์•˜๊ณ  ์ €ํ•จ์ˆ˜ํƒ„์†Œ ์‹์ด๊ตฐ์ด ๊ฐ€์žฅ ๋‚ฎ์•˜์œผ๋ฉฐ ์ •์ƒ ์‹์ด๊ตฐ๊ณผ ๊ณ ํ•จ์ˆ˜ํƒ„์†Œ ์‹์ด๊ตฐ์€ ์„œ๋กœ ์ฐจ์ด๊ฐ€ ์—†์—ˆ๋‹ค. ์ง€๋ฐฉ ํ•ฉ์„ฑ ์†๋„๋Š” ๊ณ ํ•จ์ˆ˜ํƒ„์†Œ ์‹์ด๊ตฐ์ด ๊ฐ€์žฅ ๋น ๋ฅด๊ณ  ๋‹ค๋ฅธ ์‹์ด๊ตฐ๊ฐ„์—๋Š” ๋ณ„ ์ฐจ์ด๊ฐ€ ์—†์—ˆ๋‹ค. 5. 1) Cytosol์— ์žˆ๋Š” ์ด (14)**C์€ ํˆฌ์—ฌํ›„ 2์‹œ๊ฐ„์— ๊ฐ๊ตฐ์—์„œ ์ตœ๊ณ ์น˜์— ๋‹ฌํ•˜๊ณ  ๊ทธํ›„6์‹œ๊ฐ„๊นŒ์ง€ ๊ธ‰๊ฒฉํžˆ ๋–จ์–ด์กŒ์œผ๋ฉฐ ๊ณ ํ•จ์ˆ˜ํƒ„์†Œ ์‹์ด๊ตฐ์—์„œ ๊ฐ€์žฅ ์‹ฌํ•˜๊ณ  ๋‹ค๋ฅธ ์‹์ด๊ตฐ์—์„œ๋„ ๊ฐ™์€ ๊ฒฝํ–ฅ์œผ๋กœ ๊ฐ์†Œ๋˜์—ˆ๋‹ค. D-glucose(14)**C(U)์œผ๋กœ๋ถ€ํ„ฐ ์œ ๋ž˜๋œ cytosol๋‚ด ๋‹จ๋ฐฑ์งˆ ์–‘์€ ๋ชจ๋“  ๊ตฐ์—์„œ 2์‹œ๊ฐ„์— ๊ฐ€์žฅ ๋†’์•˜์œผ๋ฉฐ ๊ณ ์ง€๋ฐฉ ์‹์ด๊ตฐ์ด ๋‹ค์†Œ ๋‚ฎ๊ณ  ๋‹ค๋ฅธ ์‹์ด๊ตฐ๊ฐ„์—๋Š” ๋ณ„ ์ฐจ์ด๊ฐ€ ์—†์—ˆ๋‹ค. 2) Mitochondrial fraction์— ๋ถ„ํฌ๋œ ์ด (14)**C์€ 4์‹œ๊ฐ„ ํ›„์— ์ตœ๊ณ ์น˜์— ๋‹ฌํ•˜์˜€๊ณ  ๊ทธ ํ›„ ๊ฐ๊ตฐ์—์„œ ๋น„์Šทํ•œ ๊ฒฝํ–ฅ์œผ๋กœ ๊ฐ์†Œ๋˜์—ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๋‹จ๋ฐฑ์งˆ ํ•ฉ์„ฑ๋Ÿ‰๊ณผ ์ง€๋ฐฉ ํ•ฉ์„ฑ๋Ÿ‰์€ 2์‹œ๊ฐ„์— ์ตœ๊ณ ์น˜์— ๋„๋‹ฌํ•˜์˜€์œผ๋ฉฐ ๊ทธ ํ›„ ๋ณ„ ๋ณ€๋™์ด ์—†์œผ๋‚˜ ๊ณ ํ•จ์ˆ˜ํƒ„์†Œ ์‹์ด๊ตฐ์—์„œ๋Š” ๋‹ค๋ฅธ ์‹์ด๊ตฐ์— ๋น„ํ•ด ์ง€๋ฐฉ ํ•ฉ์„ฑ๋Ÿ‰์ด ๋งŽ์€ ์ƒํƒœ๋กœ 6์‹œ๊ฐ„๊นŒ์ง€ ์œ ์ง€๋˜์—ˆ๋‹ค. 3) Mitochondrial fraction์— ๋ถ„ํฌ๋œ ์ด(14)**C์€ 4์‹œ๊ฐ„ ํ›„์— ์ตœ๊ณ ์น˜์— ๋„๋‹ฌํ•˜์˜€๊ณ  ๊ฐ ๊ตฐ์—์„œ ๋น„์Šทํ•œ ๊ฒฝํ–ฅ์œผ๋กœ ๊ฐ์†Œ๋˜์—ˆ๋‹ค. ๋‹จ๋ฐฑ์งˆ ํ•ฉ์„ฑ๋Ÿ‰์€ 2์‹œ๊ฐ„ ํ›„์— ์ตœ๊ณ ์น˜์— ๋„๋‹ฌํ•˜๊ณ  ๊ทธ ์ดํ›„์—๋Š” ๊ฐ์†Œํ•˜๋Š” ๊ฒฝํ–ฅ์„ ๋ณด์˜€์œผ๋ฉฐ ๊ณ ํ•จ์ˆ˜ํƒ„์†Œ ์‹์ด๊ตฐ์—์„œ ๋‹จ๋ฐฑ์งˆ ํ•ฉ์„ฑ๋Ÿ‰์€ ์ •์ƒ ์‹์ด๊ตฐ์— ๋น„ํ•ด ์˜์˜์žˆ๊ฒŒ ์ฆ๊ฐ€ํ•˜์˜€๋‹ค. ์ง€๋ฐฉ ํ•ฉ์„ฑ๋Ÿ‰์€ 2์‹œ๊ฐ„ ํ›„์— ์ตœ๊ณ ์น˜์— ๋„๋‹ฌํ•˜์˜€์œผ๋ฉฐ ๊ทธ ์ดํ›„ 6์‹œ๊ฐ„๊นŒ์ง€๋Š” ๋ณ„ ๋ณ€๋™์ด ์—†๊ณ  ๊ณ ํ•จ์ˆ˜ํƒ„์†Œ ์‹์ด๊ตฐ์ด ์ •์ƒ ์‹์ด๊ตฐ์— ๋น„ํ•ด 2,4,6์‹œ๊ฐ„์— ๋ชจ๋‘ ๋†’์•˜๋‹ค. ๊ฐ ๊ตฐ์˜ ์‹์ด๋กœ ์‚ฌ์œกํ•œ ๋ฐฑ์„œ์— D-glucose(14)**C(U) (55 ร— 10**5 dpm)์„ ๋ณต๊ฐ•๋‚ด ํˆฌ์—ฌํ•œ ๋‹ค์Œ 6์‹œ๊ฐ„ํ›„์˜ ๋ฐฑ์„œ ์ฒด์ค‘ gm๋‹น (14)**CO^^2์ƒ์‚ฐ๋Ÿ‰์€ ๊ณ ํ•จ์ˆ˜ํƒ„์†Œ ์‹์ด๊ตฐ์€ ์ด ํˆฌ์—ฌ๋Ÿ‰์˜ 0.18%, ์ €ํ•จ์ˆ˜ํƒ„์†Œ ์‹์ด๊ตฐ์€ 0.13%, ์ •์ƒ ์‹์ด๊ตฐ์€ 0.10%์ด์—ˆ์œผ๋ฉฐ ๊ณ ์ง€๋ฐฉ ์‹์ด๊ตฐ์€ 0.08%์ด์—ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ D-glucose (14)**C(U)์œผ๋กœ๋ถ€ํ„ฐ 6์‹œ๊ฐ„ ๋„์•ˆ ๊ฐ„์žฅ๊ณผ ๊ทผ์œก ๊ฐ gm๋‹น glycogen์œผ๋กœ ํ•ฉ์„ฑ๋œ ์–‘์€ ๊ฐ๊ฐ ์ด ํˆฌ์—ฌ๋Ÿ‰์˜ 3%์™€ 0.3%์ด์—ˆ์œผ๋ฉฐ ๊ฐ„์žฅ๋‚ด ์ง€๋ฐฉ์œผ๋กœ ํ•ฉ์„ฑ๋œ ์–‘์€ 0.1%์ด์—ˆ๋‹ค. ๋˜ํ•œ D-glucose(14)**C(U)์œผ๋กœ๋ถ€ํ„ฐ 6์‹œ๊ฐ„ ๋™์•ˆ ์œ ๋ž˜๋œ ๊ฐ„์žฅ gm๋‹น ์„ธํฌ์งˆ, mitochondria ์™€ microsomal fraction ๋‚ด ์ด dpm์€ ๊ฐ๊ฐ ์ด ํˆฌ์—ฌ๋Ÿ‰์˜ 6%, 0.4%์™€ 0.4%์ด์—ˆ๋‹ค. D-glucose(14)**C(U)์œผ๋กœ๋ถ€ํ„ฐ 6์‹œ๊ฐ„ ๋™์•ˆ ๊ฐ„์žฅ ์„ธํฌ์งˆ, mitochondria์™€ microsomal fraction๋‚ด ๋‹จ๋ฐฑ์งˆ๋กœ ํ•ฉ์„ฑ๋œ ์–‘์€ ๊ฐ๊ฐ ์ด ํˆฌ์—ฌ๋Ÿ‰์˜ 0.5%, 0.2%์™€ 0.3์ด์—ˆ์œผ๋ฉฐ mitochondria์™€ microsomal fraction์—์„œ ์ง€๋ฐฉ์œผ๋กœ ํ•ฉ์„ฑ๋œ ์–‘์€ 0.1%์ด์—ˆ๋‹ค. ์ด๋Ÿฐํ•œ ๊ฒฐ๊ณผ๋กœ ๋ฏธ๋ฃจ์–ด D-glucose (14)**C(U)์—์„œ (14)**CO^^2 ์ƒ์‚ฐ์€ ๊ณ ํ•จ์ˆ˜ํƒ„์†Œ ์‹์ด๊ตฐ(0.18%)์—์„œ ๊ฐ€์žฅ ๋งŽ์•˜์œผ๋ฉฐ ๊ณ ์ง€๋ฐฉ ์‹์ด๊ตฐ(0.05%)์—์„œ ๊ฐ€์žฅ ๋‚ฎ์•˜๋‹ค. ๋ฐฑ์„œ ๊ฐ„์žฅ๊ณผ ๊ทผ์œก ์กฐ์ง ๋ฐ ๊ฐ ์†Œ๊ธฐ๊ด€์—์„œ D-glucose (14)**C(U)๋Œ€์‚ฌ๋Š” ๊ฐ„์žฅ์„ธํฌ์งˆ์—์„œ ๊ฐ€์žฅ ๋งŽ๊ณ  mitochondria์™€ microsome๋‚ด ์ง€๋ฐฉ์œผ๋กœ turnover๋˜๋Š” ์–‘์ด ์ ์œผ๋ฉฐ ๋‹จ๋ฐฑ์งˆ๋กœ turnover๋˜๋Š” ์–‘์€ ์„ธํฌ์งˆ(0.5%), microsome(0.3%), mitochondria(0.2%)์ˆœ์œผ๋กœ ์ ์—ˆ๋‹ค. [์˜๋ฌธ] In the present study, we have investigated whether the glucose turnover into glycogen, lipid, protein and CO^^2 in the cellular organelles is influenced when D-glucose (14)**C(U) was administered to rats adapted to different diets(normal, high carbohydrate, low carbohydrate, high fat) for 2 weeks. The (14)CO^^2 production from high carbohydrate(high CHO) and low carbohydrate(low CHO) diet groups was 2.6 folds and 1.5 folds higher as compared to that of normal diet group, however, the amount of (14)**CO^^2 produced in hiํ˜ธ fat diet group was 20% lower than that of normal diet group. The radioactivity found in muscle glycogen was increased up to 6 hours and the rate of glycogen synthesis was the most raped in high CHO diet group and the slowest in high for diet group. The total lipid content was the highest in high fat diet group and the lowest in low CHO diet group. However, lipid synthesis from D-glucose (14)**C(U) was the most active in high CHO diet group. In high CHO diet group, lipogenesis from glucose in mitochondrial fraction was the highest during 6 hours as compared to that of other diet groups. The protein synthesis from glucose in microsomal fraction was higher in high CHO diet group as compared to that of normal diet group and lipogenesis from glucose in microsomal fraction occurred more actively in 2,4,6 hours than that of other diet groups. (14)**CO**2 production per gram of body weight for 6 hours in each diet group after administration of D-glucose (14)**C(U) (55 ร— 10**5 dpm) was 0.18% in high CHO, 0.12% in low CHO, 0.11% in normal and 0.08% in high fat diet groups. However, after 6 hours, turnover of administrated D-glucose(14)**C(U) in liver and muscle into glycogen in all diet groups was 3% and 0.3%, respectively. The incorporation of administrated D-glucose (14)**C(U) into liver lipid was 0.1% for 6 hours. Distribution of radioactive intermediates from D-glucose (14)**C(U) in liver cytosol, mitochondrial, and microsomal fractions for six hours were 6%, 0.4% and 0.4%, respectively. Radioactivities of proteins dirived from D-glucose (14)**C(U) for six hours were 0.5%, 0.2% and 0.3% in cytosol, mitochondrial and microsomal fractions, respectively. In mitochondrial and microsomal fractions, the incorporation of D-glucose (14)**C(U) into lipid was 0.1% for 6 hours. These results suggest that glucose turnover rate into macromolecules in each organelle of liver and muscle cells was the most rapid in liver cytosol and the slowest in mitochondrial and microsomal lipids.restrictio

    Studies of Phenobarbital on Ethanol Oxidation of Rat Liver

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    ์˜ํ•™๊ณผ/์„์‚ฌ[ํ•œ๊ธ€] ์ €์ž๋Š” ์ฒด์ค‘ 200gm ๋‚ด์™ธ์˜ ์›…์„ฑ๋ฐฑ์„œ์— phenobarbital์„ ์ฒด์ค‘ kg๋‹น 100mg๋ฅผ stomack tube๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ๋งค์ผ 1ํšŒ์”ฉ 1์ฃผ์ผ๊ฐ„ ํˆฌ์—ฌํ•œ ํ›„ ์ฒด์ค‘๋ณ€ํ™” ๋ฐ ๊ฐ„์žฅ๋‚ด ์—ํƒ€๋†€๋Œ€์‚ฌ์— ๊ด€์—ฌํ•˜๋Š” ํšจ์†Œ๋“ค์˜ ๋ณ€ํ™”๋ฅผ ์ธก์ • ๊ด€์ฐฐํ•˜์˜€๋“  ๋ฐ” ๋‹ค์Œ๊ณผ ๊ฐ™์€ ์˜์˜์žˆ๋Š” ์‹คํ—˜๊ฒฐ๊ณผ๋ฅผ ์–ป์—ˆ๋‹ค. Phenobarbital ํˆฌ์—ฌ๊ฐ€ ์ฒด์ค‘์—๋Š” ๋ณ€ํ™”๋ฅผ ๊ฐ€์ ธ์˜ค์ง€ ์•Š์•˜์œผ๋‚˜ ๋Œ€์กฐ๊ตฐ์— ๋น„ํ•˜์—ฌ ๊ฐ„์žฅ๋ฌด๊ฒŒ๋Š” 53.9%, microsomal proteinํ•จ๋Ÿ‰์€ 55% ์ฆ๊ฐ€ํ•˜์˜€๋‹ค. ๊ฐ„์žฅ์„ธํฌ๋‚ด cytosol์˜ alcohol dehydrogenase(ADH) ํ™œ์„ฑ์น˜๋Š” ๋‹จ๋ฐฑ์งˆ mg๋‹น ๋ฐ ๊ฐ„์žฅ์กฐ์ง gm๋‹น ํ‘œ์‹œํ•˜๋ฉด ๋Œ€์กฐ๊ตฐ๊ณผ ํ•˜๋“ฑ์˜ ์ฐจ์ด๋ฅผ ๋ณด์ด์ง€ ์•Š์•˜์œผ๋‚˜ ์ด๊ฐ„์žฅ๋‚ด ADHํ™œ์„ฑ์น˜๋Š” phenobarbitalํˆฌ์—ฌ๋กœ ๋Œ€์กฐ๊ตฐ์— ๋น„ํ•˜์—ฌ 48%๊ฐ€ ์ฆ๊ฐ€ํ•˜์˜€๋‹ค. ์ด๋Š” ADHํ™œ์„ฑ ๋˜๋Š” ํ•จ๋Ÿ‰ ์ฆ๊ฐ€์— ์˜ํ•œ ๊ฒƒ์ด ์•„๋‹ˆ๋ผ ์ „์ฒด ๊ฐ„์žฅ์กฐ์ง์˜ ์ฆ๋Œ€์— ๋”ฐ๋ฅธ ๊ฒฐ๊ณผ๋กœ ์‚ฌ๋ฃŒ๋œ๋‹ค. ์ด์™€๋Š” ๋‹ฌ๋ฆฌ ๊ฐ„์žฅ microsome๋‚ด์™ธ MEOSํ™œ์„ฑ์€ ๋‹จ๋ฐฑ์งˆ mg๋‹น์—์„œ๋Š” ๋Œ€์กฐ๊ตฐ์— ๋น„ํ•˜์—ฌ 119%๊ฐ€ ์ฆ๊ฐ€ํ•˜๊ณ  ๊ฐ„์žฅ์กฐ์ง gm๋‹น์—์„œ๋Š” 171.5%๋กœ ์˜์˜์žˆ๊ฒŒ ์ฆ๊ฐ€ํ•˜์˜€์œผ๋ฉฐ, ์ด๊ฐ„์žฅ๋‚ด MEOSํ™œ์„ฑ์น˜๋Š” 319%๋‚˜ ์ฆ๊ฐ€ํ•˜์˜€๋‹ค. Microsomal NADPH ??idaseํ™œ์„ฑ์น˜๋Š” mg๋‹น 46.8%, gm๋‹น 128.8% ์ฆ๊ฐ€ํ•˜์˜€๊ณ  ์ด๊ฐ„์žฅ๋‚ด NADPH oxidase๋Š” 252% ์ฆ๊ฐ€ํ•˜์˜€๋‹ค. ์ด์ƒ๊ณผ ๊ฐ™์ด phenobarbital ํˆฌ์—ฌ๋Š” ๊ฐ„์žฅ์กฐ์ง ๋น„๋Œ€ ๋ฐ microsomal protein ํ•จ๋Ÿ‰์„ ์ฆ๊ฐ€์‹œํ‚ค๋ฉฐ ์—ํƒ€๋†€๋Œ€์‚ฌ์— ๊ด€์—ฌํ•˜๋Š” ํšจ์†Œ๋“ค์˜ ํ•จ๋Ÿ‰์ฆ๊ฐ€๋กœ ์—ํƒ€๋†€๋Œ€์‚ฌ๊ฐ€ ์ฆ๊ฐ€๋˜๋ฉฐ, ํŠนํžˆ phenobarbital ํˆฌ์—ฌ๋กœ ์—ํƒ€๋†€์‚ฐํ™” ์ฆ๊ฐ€๋Š” MEOSํ™œ์„ฑ ๋ฐ MADPH oxidase ํ™œ์„ฑ์ฆ๊ฐ€๋ณด๋‹ค๋Š” ๊ฐ„์žฅ์กฐ์ง ๋น„๋Œ€์— ์˜ํ•œ ADH์˜ ์–‘์ ์ฆ๊ฐ€๊ฐ€ ๋”์šฑ ์ค‘์š”ํ•œ ์š”์ธ์œผ๋กœ ์‚ฌ๋ฃŒ๋œ๋‹ค. [์˜๋ฌธ] The administration of phenobarbital (100mg/kg) ti rats bt stomach tube daily for one week resulted in significant increases in liver weight and microsomal protein concentration by 53.9 and 55 per cent respectively over that of the control group. No significant increase in cytomplasmic alcohol dehydrogenase activity was observed, when it was expressed per mg of protein and gm of fresh liver; however, the total activity of cytoplasmic alcobol dehydrogenase in the whole liver increased signifficantly by 48 per cent. This was due to the fact the total weight of liver was imm?????in phenobarbital treamed rats. The activity of the hepatic an??????? ??????? ?????? system (MEOS) increased by 119 per cent over that of the controls when it was expreased per mg of protein and increased by 171.5 per cent when it was expressed per gm of fresh liver weight. The activity of hepatic microsomal NADPH oxidase also increased by 46 per cent over that of the control group when it was expressed in mg of protein and increased by 128.8 per cent when it was expressed in gm of fresh liver weight, indicating that the amount of these two enzymes was increased per gm of fresh liver when treated by phenobarbital. The per cent of total ethanol oxidation by cytoplasmic alcohol dehydrogenase and microsomal oxidation system was 88 and 12 per cent respect tively in the control group; however, it was 72.5 and 27.5 per cent respecively in the phenobarbital treated group. In spite of microsomal ethanol oxidation and microsomal proteins were increased significanty but cytoplasmic alcohol dehydrogenase activity in liver was not altered as such by phenobarbital treatment, accordingto our experimental results. These results suggest that ethanol oxidation by cytoplasmic alcobol dehydrogenase in cytosol plays the main part and the microsomal ethanol oxidation system plays the minor part in the metaboliam of ethanol.restrictio

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์‚ฌํšŒ๊ณผํ•™๋Œ€ํ•™ ์‹ฌ๋ฆฌํ•™๊ณผ, 2018. 8. ์ตœ์ง„์˜.์ตœ๊ทผ ์—ฐ๊ตฌ๊ฒฐ๊ณผ๋“ค์€ ๊ณผ์ œ์ˆ˜ํ–‰ ๋™์•ˆ์˜ ์—ฐ์Šตํšจ๊ณผ, ์ฆ‰ ํšŒ๊ธฐ ๋‚ด ์—ฐ์Šตํšจ๊ณผ(within-session practice effect)๊ฐ€ ํ•™์Šต ์ž ์žฌ๋ ฅ ๋˜๋Š” ์œ ์—ฐํ•œ ์ ์‘ ๋Šฅ๋ ฅ์— ๋Œ€ํ•œ ํ–‰๋™์  ์ง€ํ‘œ๊ฐ€ ๋  ์ˆ˜ ์žˆ๋‹ค๋Š” ์ ์„ ์‹œ์‚ฌํ•œ๋‹ค (Duff et al., 2012). ๊ทธ๋Ÿฌ๋‚˜ ์ฃผ์–ด์ง„ ๊ณผ์ œ๋ฅผ ์—ฐ์Šตํ•˜๋Š” ๋™์•ˆ์˜ ๊ธ‰๊ฒฉํ•œ ์ˆ˜ํ–‰ ๋ณ€ํ™”๊ฐ€ ์–ด๋– ํ•œ ์ธ์ง€๊ธฐ๋Šฅ์„ ๋ฐ˜์˜ํ•˜๊ณ  ์•ˆ์ •์ ์œผ๋กœ ์˜ˆ์ธกํ•˜๋Š”์ง€, ์‹ ๊ฒฝํ•™์  ๋ฐฉ๋ฒ•์„ ํ†ตํ•ด ์—ฐ๊ตฌ๋œ ๋ฐ”๋Š” ๋“œ๋ฌผ๋‹ค. ํ–‰๋™์ ์œผ๋กœ ์œ ์—ฐํ•˜๊ฒŒ ๋ณ€ํ™”ํ•˜๋Š” ๋Šฅ๋ ฅ์€ ์ง‘ํ–‰๊ธฐ๋Šฅ์˜ ๊ตฌ์„ฑ์š”์†Œ ์ค‘ ์ตœ์‹ ํ™” ๋ฐ ์ „ํ™˜ ๋“ฑ์˜ ์š”์†Œ์— ์˜ํ•ด ๋’ท๋ฐ›์นจ๋˜๋Š” ๊ฒƒ์œผ๋กœ ๋ณด์ธ๋‹ค (Miyake & Friedman, 2012). ์ด๋Ÿฌํ•œ ์ ์—์„œ ํšŒ๊ธฐ ๋‚ด ์—ฐ์Šตํšจ๊ณผ๊ฐ€ ์ตœ์‹ ํ™” ๋ฐ ์ „ํ™˜๊ณผ ๊ฐ™์€ ์ง‘ํ–‰๊ธฐ๋Šฅ์˜ ์š”์†Œ์™€ ์‹ ๊ฒฝ ๊ธฐ์ „์„ ๊ณต์œ ํ•  ๊ฐ€๋Šฅ์„ฑ์ด ์ œ๊ธฐ๋œ๋‹ค. ์ „๋‘๋‘์ •๋„คํŠธ์›Œํฌ๊ฐ€ ์œ ์—ฐํ•œ ํ†ต์ œ์ฒ˜๋ฆฌ๊ณผ์ • (flexible control process)์„ ๋‹ด๋‹นํ•œ๋‹ค๋Š” ๊ธฐ์กด ๊ฒฐ๊ณผ๋“ค์„ ํ† ๋Œ€๋กœ, ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ํšŒ๊ธฐ ๋‚ด ์—ฐ์Šตํšจ๊ณผ์˜ ์‹ ๊ฒฝํ•™์  ์ƒ๊ด€๊ณผ ์ „๋‘๋‘์ •๋„คํŠธ์›Œํฌ์˜ ์—ฐ๊ด€์„ฑ์„ ๊ธฐ๋Šฅ์  ์ž๊ธฐ๊ณต๋ช…์˜์ƒ์„ ํ†ตํ•ด ํƒ๊ตฌํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ง‘ํ–‰๊ธฐ๋Šฅ๊ณผ์ œ ์ค‘ ํ•˜๋‚˜์ธ ๋‹ค์ค‘๊ฐ„์„ญ๊ณผ์ œ(multi-source interference task)๋ฅผ ์ˆ˜ํ–‰ํ•˜๋Š” ๋™์•ˆ, ๊ณผ์ œ ์ดˆ๊ธฐ์™€ ํ›„๊ธฐ ์‚ฌ์ด์˜ ์‹œํ–‰ ๋ฐ˜์‘์‹œ๊ฐ„ ์ฐจ์ด์™€ ๋‡Œ์˜์—ญ ํ™œ์„ฑํ™” ๋ฐ ๋Œ€๋‡Œ๋„คํŠธ์›Œํฌ์˜ ๊ธฐ๋Šฅ์  ์—ฐ๊ฒฐ์„ฑ ๊ฐ•๋„์˜ ์ฐจ์ด๋ฅผ ์ธก์ •ํ•˜์˜€๋‹ค. ์šฐ์„ , ๊ณผ์ œ์ˆ˜ํ–‰๋™์•ˆ ๋‡Œ๊ธฐ๋Šฅ ๋ณ€ํ™”๊ฐ€ ์œ ์˜ํ•œ ์ง€ ๊ณต๊ฐ„ํŒจํ„ด ํ•ด์„(spatial decoding)๊ณผ ๋Œ€์‘ํ‘œ๋ณธ t๊ฒ€์ •์„ ์‹ค์‹œํ•˜์˜€๋‹ค. ์ด ์ค‘์—์„œ ์—ฐ์Šตํšจ๊ณผ ํฌ๊ธฐ์™€ ์œ ์˜ํ•œ ์ƒ๊ด€์„ ๋ณด์ด๋Š” ๋‡Œ๊ธฐ๋Šฅ ๋ณ€ํ™”๋ฅผ ์—ฐ์Šตํšจ๊ณผ์˜ ์‹ ๊ฒฝ์ƒ๊ด€์ž๋กœ ์ •์˜ํ•˜์˜€๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ๊ฒฐ๊ณผ๊ฐ€ ํŠน์ • ๊ณผ์ œ์ƒํ™ฉ์— ๊ตญํ•œ๋˜์ง€ ์•Š๋Š”์ง€ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•ด, ์—ฐ์Šตํšจ๊ณผ์˜ ์‹ ๊ฒฝ์ƒ๊ด€์ž์™€ ์ง‘ํ–‰๊ธฐ๋Šฅ์„ ์ธก์ •ํ•˜๋Š” ์‹ ๊ฒฝ์‹ฌ๋ฆฌ๊ฒ€์‚ฌ ์ ์ˆ˜๋“ค ๊ฐ„ ์ƒ๊ด€์ด ๋ถ„์„๋˜์—ˆ๋‹ค. ๊ทธ ๊ฒฐ๊ณผ, ํšŒ๊ธฐ ๋‚ด ์—ฐ์Šตํšจ๊ณผ์˜ ์ƒ๊ด€์ž๋Š” ์ „๋‘๋‘์ •๋„คํŠธ์›Œํฌ์™€ ๊ด€๋ จ๋œ ์˜์—ญ ๋ฐ ๊ธฐ๋Šฅ์  ์—ฐ๊ฒฐ์„ฑ์ด์—ˆ๋‹ค. ํ•ด๋‹น ๋„คํŠธ์›Œํฌ์— ์†ํ•œ ์–‘์ธก ์ƒ๋‘์ •์—ฝ, ์ขŒ์ธก ์ƒ์ „๋‘ํšŒ ๋ฐ ํ•˜์ „๋‘ํšŒ์˜ ํ™œ์„ฑํ™”๊ฐ€ ๊ณผ์ œ ํ›„๊ธฐ์— ๋” ๋งŽ์ด ๊ฐ์†Œํ• ์ˆ˜๋ก ๋” ํฐ ์—ฐ์Šตํšจ๊ณผ๊ฐ€ ์žˆ์—ˆ๋‹ค. ๋˜ํ•œ, ์ „๋‘๋‘์ •๋„คํŠธ์›Œํฌ ๋‚ด๋ถ€์˜ ์—ฐ๊ฒฐ์„ฑ, ์ „๋‘๋‘์ • ๋„คํŠธ์›Œํฌ์™€ ์†Œ๋‡Œ๋„คํŠธ์›Œํฌ ๊ฐ„ ์—ฐ๊ฒฐ์„ฑ์ด ๊ฐ์†Œํ• ์ˆ˜๋ก ์—ฐ์Šตํšจ๊ณผ๊ฐ€ ์ปธ๋‹ค. ๊ณต๊ฐ„ํŒจํ„ดํ•ด์„ ๊ฒฐ๊ณผ ์—ญ์‹œ ์ผ๊ด€๋˜๊ฒŒ ์ „๋‘๋‘์ •๋„คํŠธ์›Œํฌ ์ค‘์‹ฌ์˜ ๋ณ€ํ™”๋ฅผ ์ง€์ง€ํ–ˆ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ์ด๋Ÿฌํ•œ ์‹ ๊ฒฝ์ƒ๊ด€์ž๋Š” ์ž‘์—…๊ธฐ์–ต์„ ์ธก์ •ํ•˜๋Š” ๊ฑฐ๊พธ๋กœ ์ˆซ์ž ์™ธ์šฐ๊ธฐ ์ ์ˆ˜์™€ ์ผ๊ด€๋œ ์ƒ๊ด€์„ ๋ณด์˜€๋‹ค. ์ข…ํ•ฉ์ ์œผ๋กœ, ๋ณธ ์—ฐ๊ตฌ๊ฒฐ๊ณผ๋Š” ํšŒ๊ธฐ ๋‚ด ์—ฐ์Šตํšจ๊ณผ์™€ ์œ ์—ฐํ•œ ํ†ต์ œ์ฒ˜๋ฆฌ๊ณผ์ •์˜ ๊ณตํ†ต๋œ ์‹ ๊ฒฝ์ƒ๊ด€์ž๊ฐ€ ์ „๋‘๋‘์ •๋„คํŠธ์›Œํฌ์ด๋ฉฐ, ๊ณผ์ œ๋ฅผ ์Šต๋“ํ•˜๋Š” ์ดˆ๊ธฐ ๊ณผ์ •์—์„œ ํ•ด๋‹น ๋„คํŠธ์›Œํฌ์˜ ํšจ์œจ์  ์‚ฌ์šฉ์ด ์ ์‘์ ์œผ๋กœ ํ–‰๋™ ๋ณ€ํ™”๋ฅผ ๋„๋ชจํ•˜๋Š” ๋Šฅ๋ ฅ์˜ ๊ธฐ๋ฐ˜์ž„์„ ์‹œ์‚ฌํ•œ๋‹ค.There is a growing interest that practice effect may role as a behavioral marker of learning potential and flexible adaptability. However, the relationship between performance change during a brief task (i.e., within-session practice effect) and other cognitive abilities is still unclear. Assuming behavioral flexibility is associated with flexible components of executive function, it was hypothesized that there would be common neural correlates between within-session practice effect and flexible components of executive function. Based on previous reports that frontoparietal network engages in flexible control process, we investigated the association between the brain marker of within-session practice effect and frontoparietal network using task fMRI. In this study, task performance and brain changes between early and late phase of multi-source interference task were tracked with task fMRI. We first tested the significance of brain changes by paired t-test. To test specificity of their association with frontoparietal network, spatial decoding was done for activation results and eight different large-scale networks were compared for connectivity results. To define brain markers of within-session practice effect, correlation analyses examined predictive power of such brain markers on the amount of within-session practice effect. Lastly, correlation between obtained brain markers and neuropsychological measures of flexible executive function was tested to decide whether the role of brain marker can be generalized to other task settings. As a result, brain regions and functional connectivities which significantly predicted practice effect were primarily associated with frontoparietal network. Specifically, activation decline in bilateral superior parietal lobule, left superior and inferior frontal gyrus and decline in frontoparietal network intra-network connectivity and frontoparietal-cerebellum inter-network connectivity significantly predicted greater practice-related gain. Spatial decoding advocated the dominant engagement of frontoparietal network in the short-term learning process. Lastly, the brain markers of practice effect were consistently correlated with digit span backward score. These suggest that frontoparietal network serves as the common neural correlates between practice effect and flexible executive function.Introduction 1 1. Practice effect 2 1.1 Cognitive accounts on practice effect 3 2. Executive function and practice effect 6 2.1 Executive function 7 2.2 Executive function and learning 9 3. Objective and Hypotheses 10 Methods 13 1. Participants 13 2. Materials 13 2.1 Experimental task 13 2.2 Neuropsychological tests 17 2.3 Functional magnetic resonance imaging 18 3. Data analysis 19 3.1 Behavioral data analysis 19 3.2 Functional activation analysis 20 3.3 Functional connectivity analysis 22 3.4 Brain-behavior relationship analysis 24 Results 25 1. Practice effect on task performance 25 2. Practice effect on brain function 28 2.1 Activation change 28 2.2 Spatial decoding of activation change 31 2.3 Functional connectivity change 33 3. The neural correlates of within-session practice effect 37 3.1 Practice effect-related activation change 37 3.2 Practice effect-related functional connectivity change 38 3.3 Correlation with neuropsychological measures 40 Discussion 43 1. Frontoparietal network change accounts for practice effect 44 1.1 Pure time effect and practice effect 44 1.2 The direction of brain change 47 2. The link between within-session practice effect and working memory 49 2.1 Shared neural correlates 49 2.2 Specificity of the relationship 50 2.3 Connectivity change reliably measures working memory capacity 51 3. Limitations and future considerations 52 References 54 ๊ตญ๋ฌธ์ดˆ๋ก 66 Appendix I. 68Maste
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