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    An experimental study on fluid characteristics and heat transfer characteristics along a horizontal circular tube by baffle cut rate

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    Saving energy and efficient use are required when consider environmental problem of the earth become serious gradually with limited energy resources. Specially, energy frugality style, high efficiency heat exchanger development is urgently required over industry whole by increase trend of energy consumption recently. Interest for this heat exchanger became efficiency elevation, efficiency elevation to importance subject according as making of energy frugality style device spreads since the first Oil Shock in 1973. Elevation of the heat transfer efficiency is specially important in this high efficiency heat exchanger. To elevation of the heat transfer efficiency, in the past, used process surface channel for improve heat transfer areas and fluid characteristics but it is condition that development of shell and tube type heat exchanger is required urgently that is more high efficiency heat exchanger according to use ship and purpose. Heat exchanger according to purpose of the use kind of fluid, number of fluid, phase of fluid , direction of flow, speed range, heat exchanger form, shape of extension surface(fin), direction, use the quality of the material, size, capacity etc. the form very many . In many case of heat exchangers two working fluids between put solid wall and heat exchange . Heat is passed in low temperature fluid passing wall surface from high temperature fluid and accompanies phase change sometimes this time. By method for heat exchange performance elevations of heat exchanger, at first, can think increase of heat transfer area but don't satisfaction about problem of efficient space management, increase of pumping work by pressure drop etc. Need for development of high efficiency heat exchanger that prove heat passage rates of heat exchanger for solution of this problem. In the channel flow studied purpose of engineering by many peoples for a long time. Channel that baffle plate exists is blocked fluid flow and can be detour. So fluid is stay within channel lengthen by doing blocked time. This is desirable phenomenon in place that do by purpose that heat exchange between two bodies. Also, flow that flow baffle in channel together is shape such as shell and tube heat exchanger. This does by purpose that heat exchange between flow of tube interior and external flow. Segmental baffle is lots of stagnant field of heat areas and increase of pressure drop. Also, be apt to corrosion or pierced a hole by fouling in stagnant field. To investigate the characteristics of fluid flow and heat transfer performance in a channel in terms of the various effects of baffle cut rate. The results show that the decrease of a baffle cut rate gives a good heat transfer enhancement. However, it also increase pressure drop. The object of the experimental is comparing that changing Baffle cut rate, fluid velocity in the channel and changing flow temperatures, behaved experimental study to investigate fluid characteristics of interior, pressure drop characteristics and heat transfer characteristics by PIV system, numerical prediction and heat transfer experimental. In this experimental, baffle cut rate is 30%, 40%, 50%, velocity is 0.5m/s, 1.0m/s, 1.5m/s and heat temperature is 50โ„ƒ, 40โ„ƒ, 30โ„ƒ, cooling temperature 5โ„ƒ. PIV system determine velocity characteristics, turbulent intensity, kinetic energy and pressure drop. Also, through the numerical prediction and experimental comparing and examination for heat transfer characteristics understanding.Abstract โ…ต ์‚ฌ์šฉ๊ธฐํ˜ธ โ…น ์ œ 1 ์žฅ ์„œ ๋ก  1 1.1 ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ 1 1.2 ์ข…๋ž˜์˜ ์—ฐ๊ตฌ์™€ ๋ชฉ์  4 ์ œ 2 ์žฅ ์‹คํ—˜๋ฐฉ๋ฒ• ๋ฐ ์‹คํ—˜๋ฒ”์œ„ 7 2.1 ์‹คํ—˜๋ฐฉ๋ฒ• ๋ฐ ์‹คํ—˜๋ฒ”์œ„ 7 2.2 PIV ์‹œ์Šคํ…œ์˜ ๊ตฌ์„ฑ 12 2.2.1 ์กฐ๋ช… ๋ฐ ์ถ”์  ์ž…์ž 12 2.2.2 ์˜์ƒ ์ž…๋ ฅ ๋ฐ ์ €์žฅ ์žฅ์น˜ 13 2.2.3 ์›ํ†ตํ˜• ๋ Œ์ฆˆ 15 2.3 ๊ท ์ผ ์œ ์ž… ์†๋„ ํ™•์ธ 15 ์ œ 3์žฅ ์›๊ด€ ๋‚ด์—์„œ์˜ ์—ด์ „๋‹ฌ ์ˆ˜์น˜ํ•ด์„ 18 3.1 ์ด๋ก  ํ•ด์„ 18 3.1.1 ์ˆ˜์น˜ํ•ด์„ ๊ฐ€์ • 18 3.1.2 ์ง€๋ฐฐ๋ฐฉ์ •์‹ 19 3.2 ๊ฒฝ๊ณ„์กฐ๊ฑด 20 3.2.1 ์ž…๊ตฌ์กฐ๊ฑด 20 3.2.2 ์ถœ๊ตฌ์กฐ๊ฑด 20 3.2.3 ์ˆ˜์น˜ํ•ด์„ ๋ฐฉ๋ฒ• 20 3.3 ๋ชจ๋ธ๋ง ํ˜•์ƒ 21 3.4 ํ•ด์„ ๊ฒฐ๊ณผ ๋ฐ ๊ณ ์ฐฐ 23 3.4.1 ์—ด์ „๋‹ฌ ํŠน์„ฑ 23 3.4.2 ์••๋ ฅ๊ฐ•ํ•˜ ํŠน์„ฑ 30 3.6 ๊ฒฐ ๋ก  32 ์ œ 4 ์žฅ ์›๊ด€ ๋‚ด์—์„œ์˜ ์œ ์ฒด์œ ๋™ ๋ฐ ์—ด์ „๋‹ฌ ํŠน์„ฑ 33 4.1 ์‹คํ—˜์žฅ์น˜ 33 4.2 Baffle์— ๋”ฐ๋ฅธ ์˜ํ–ฅ 45 4.2.1 ์†๋„ ํ”„๋กœํŒŒ์ผ 45 4.2.2 ๋‚œ๋ฅ˜๊ฐ•๋„ 52 4.2.3 ์šด๋™์—๋„ˆ์ง€ 59 4.2.4 ์—ด์ „๋‹ฌ ํŠน์„ฑ 66 4.3 ์œ ์†์— ๋”ฐ๋ฅธ ์˜ํ–ฅ 73 4.3.1 ์†๋„ ํ”„๋กœํŒŒ์ผ 73 4.3.2 ๋‚œ๋ฅ˜๊ฐ•๋„ 77 4.3.3 ์šด๋™์—๋„ˆ์ง€ 87 4.3.4 ์—ด์ „๋‹ฌ ํŠน์„ฑ 91 4.4 ์••๋ ฅ๊ฐ•ํ•˜ ํŠน์„ฑ 95 ์ œ 5 ์žฅ ์ด ๊ฒฐ ๋ก  97 ์ฐธ ๊ณ  ๋ฌธ ํ—Œ 9

    ํ™˜์ž์œ ๋ž˜ ์ด์ข…์ด์‹ ๋ชจ๋ธ์„ ์ด์šฉํ•œ ์œ„์•”์—์„œ ์ด๋ฏธ์ง• ๋ฐ”์ด์˜ค๋งˆ์ปค๋กœ์จ FDG ์นœํ™”๋ ฅ ์˜ˆ์ธก ๋ชจ๋ธ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์˜๊ณผ๋Œ€ํ•™ ํ˜‘๋™๊ณผ์ • ์ข…์–‘์ƒ๋ฌผํ•™์ „๊ณต, 2020. 8. ์–‘ํ•œ๊ด‘.Background: Although fluorodeoxyglucose positron emission tomography (FDG-PET) is widely used in staging, response monitoring and evaluating recurrence for various cancers, its role in gastric cancer (GC) is still limited due to variable FDG avidity of malignant lesions. Patient derived-xenograft (PDX) models, as patient surrogates, are considered promising in-vivo models in preclinical research. The purpose of this study is to develop a gene signature to predict FDG avidity in GC based on established PET imaging PDX murine models to plan individualized PET and investigate the molecular characteristic landscape. Methods: Female BALB/c nu/nu mice were implanted orthotopically and subcutaneously with GC PDX tissues. [18F]FDG-PET scanning protocol evaluation included different tumor sizes, FDG doses, scanning intervals and organ specific uptake. FDG avidity of similar PDX cases were compared between orthotopic and heterotopic tumor implantation models. Microscopic and immunohistochemical investigations were performed to confirm tumor growths and correlate protein expressions of glucose transporter 1 (GLUT1) and hexokinase 2 (HK2) with FDG uptake. Using RNA sequencing data of thirty PDX cases paired with FDG-PET results, we identified a five-gene signature (PLS1, PYY, HBQ1, SLC6A5, NAT16) associated with the maximum standardized uptake value (SUVmax). We established a model (PETscore) for predicting high FDG-avid GC using the signature, which was validated in human by RNA-seq and qRT-PCR. Furthermore, we also characterized the model using public data of GC profiled in The Cancer Genome Atlas (TCGA) and Asian Cancer Research Group (ACRG). Results: PET scanning protocol was determined to include 150 ฮผCi FDG injection dose and scanning after one hour. Comparison of heterotopic and orthotopic implanted mouse models revealed longer growths interval for orthotopic models with higher uptake in similar PDX tissues. H-scores of GLUT1 and HK2 expressions in tumor cells were correlated with measured SUVmax values. Validation of PETscore provided significant predictive values compared with actual SUVmax in human. Investigation with TCGA and ACRG data showed that the PETscore was significantly associated with glycolysis, microsatellite instability (MSI) status and epithelial mesenchymal transition (EMT)-related prognosis. Conclusion: This preclinical GC PDX based [18F]FDG-PET protocol reveals tumor specific FDG uptake and shows correlation to glucose metabolic proteins. PDX transplanted mouse model can be useful to access PET activity in gastric cancer. Our findings in study for FDG avidity prediction model suggest the molecular characteristics of GC underlying the diverse metabolic profiles. Furthermore, our PETscore could be proposed for an individualized FDG-PET for staging and disease monitoring by predicting FDG avidity.๋ฐฐ๊ฒฝ: FDG-PET์€ ๋‹ค์–‘ํ•œ ์•”์˜ ๋ณ‘๊ธฐ, ์•ฝ๋ฌผ๋ฐ˜์‘ ๊ทธ๋ฆฌ๊ณ  ์žฌ๋ฐœ ํ‰๊ฐ€์— ๋„๋ฆฌ ์“ฐ์ด๋‚˜, ์œ„์•”์˜ ๊ฒฝ์šฐ FDG์˜ ์„ญ์ทจ๊ฐ€ ์ผ์ •์น˜ ์•Š์•„ ๊ทธ ์—ญํ• ์ด ์ œํ•œ์ ์ด๋‹ค. ํ™˜์ž์œ ๋ž˜์ด์ข…์ด์‹ ๋ชจ๋ธ(PDX)์€ ์ „์ž„์ƒ ์—ฐ๊ตฌ์—์„œ ์œ ๋งํ•œ in-vivo ๋ชจ๋ธ์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ํ™˜์ž๋งž์ถค PET ๊ณ„ํš ๋ฐ ๋ถ„์ž์  ํŠน์„ฑ ์กฐ์‚ฌ๋ฅผ ์œ„ํ•ด ์œ„์•” PDX ๋งˆ์šฐ์Šค ๋ชจ๋ธ์„ ์ด์šฉํ•œ FDG ์„ญ์ทจ ์˜ˆ์ธก ์œ ์ „์ž ์ง€ํ‘œ๋ฅผ ๊ฐœ๋ฐœํ•˜๋Š” ๊ฒƒ์ด๋‹ค. ๋ฐฉ๋ฒ•: ์•”์ปท BALB/c ๋ˆ„๋“œ๋งˆ์šฐ์Šค์— ์œ„์•” PDX ์กฐ์ง์„ ์ •์œ„ ๋ฐ ํ”ผํ•˜์— ์ด์‹ํ–ˆ๋‹ค. [18F]FDG-PET ์ดฌ์˜ ํ”„๋กœํ† ์ฝœ์„ ๋‹ค์–‘ํ•œ ์ข…์–‘ ํฌ๊ธฐ ๋ฐ FDG ์„ ๋Ÿ‰, ์ดฌ์˜ ๊ฐ„๊ฒฉ ๊ทธ๋ฆฌ๊ณ  ์žฅ๊ธฐ ํŠน์ด์  FDG ์„ญ์ทจ์— ๋Œ€ํ•ด ํ‰๊ฐ€ํ–ˆ๋‹ค. ๋™์ผ PDX๋ฅผ ์ด์šฉํ•œ ์ •์œ„ ๋ฐ ํ”ผํ•˜ ์ด์‹ ๋ชจ๋ธ ๊ฐ„ FDG ์นœํ™”๋ ฅ์„ ๋น„๊ตํ–ˆ๋‹ค. ์ข…์–‘ ์„ฑ์žฅ ํ™•์ธ ๋ฐ ํฌ๋„๋‹น ์ˆ˜์†ก์ฒด 1(GLUT1) ๊ทธ๋ฆฌ๊ณ  ํ—ฅ์†Œํ‚ค๋‚˜์•„์ œ 2(HK2)์™€ FDG ์„ญ์ทจ ๊ฐ„ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ํ˜„๋ฏธ๊ฒฝ์  ๊ด€์ฐฐ๊ณผ ๋ฉด์—ญ์—ผ์ƒ‰ ํ™œ์šฉํ•˜์—ฌ ์กฐ์‚ฌํ–ˆ๋‹ค. FDG-PET ๊ฒฐ๊ณผ๊ฐ€ ์žˆ๋Š” 30๋ก€์˜ PDX์˜ RNA ์‹œํ€€์‹ฑ ๋ฐ์ดํ„ฐ๋ฅผ ์ด์šฉํ•˜์—ฌ ์ตœ๋Œ€ ํ‘œ์ค€์„ญ์ทจ๊ณ„์ˆ˜(SUVmax)์™€ ์—ฐ๊ด€๋œ ์œ ์ „์ž ์ง€ํ‘œ๋ฅผ ์‹๋ณ„ํ–ˆ๋‹ค. 5๊ฐ€์ง€ ์œ ์ „์ž ์ง€ํ‘œ(PLS1, PYY, HBQ1, SLC6A5, NAT16)๋ฅผ ์ด์šฉํ•˜์—ฌ ๋†’์€ FDG ์„ญ์ทจ๋ฅผ ๋ณด์ด๋Š” ์œ„์•”์„ ์˜ˆ์ธกํ•˜๋Š” ๋ชจ๋ธ(PETscore)๋ฅผ ๊ตฌ์ถ•ํ–ˆ๊ณ , ํ™˜์ž์—์„œ RNA-seq ๊ณผ qRT-PCR ๊ธฐ๋ฒ•์„ ํ†ตํ•ด ํ‰๊ฐ€ํ–ˆ๋‹ค. ๋”์šฑ์ด, ์•”์œ ์ „์ฒด์ง€๋„(TCGA) ๋ฐ ์•„์‹œ์•„ ์•” ์—ฐ๊ตฌ ๊ทธ๋ฃน(ACRG) ์œ„์•” ๊ณต๊ณต๋ฐ์ดํ„ฐ์—์„œ ๋ชจ๋ธ์˜ ํŠน์„ฑ์„ ์กฐ์‚ฌํ–ˆ๋‹ค. ๊ฒฐ๊ณผ: PET ์ดฌ์˜ ํ”„๋กœํ† ์ฝœ 150 ฮผCi ์˜ ์šฉ๋Ÿ‰์„ ์ฃผ์ž…ํ•˜๊ณ , 1์‹œ๊ฐ„ ๋’ค ์ดฌ์˜ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๊ฒฐ์ •ํ–ˆ๋‹ค. ๋™์ผ PDX ์กฐ์ง์„ ์ด์šฉํ•œ ์ •์œ„์ด์‹ ๋ฐ ํ”ผํ•˜์ด์‹ ๋งˆ์šฐ์Šค ๋ชจ๋ธ ๊ฐ„ ๋น„๊ต์—์„œ ์ •์œ„์ด์‹ ๋ชจ๋ธ์ด FDG์„ญ์ทจ๊ฐ€ ๋†’์•˜๊ณ , ์ข…์–‘ ์„ฑ์žฅ์ด ๋Š๋ ธ๋‹ค. ์ข…์–‘ ์„ธํฌ ๋‚ด GLUT1๊ณผ HK2 ๋ฐœํ˜„์˜ H-score๋Š” SUVmax์™€ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๋ณด์˜€๋‹ค. ํ™˜์ž์—์„œ PETscore๋Š” ์‹ค์ œ SUVmax๊ฐ’๊ณผ ๋น„๊ตํ•˜์—ฌ ์œ ์˜ํ•œ ์˜ˆ์ธก ๊ฐ’์„ ์ œ๊ณตํ–ˆ๋‹ค. TCGA ๋ฐ ACRG ๋ฐ์ดํ„ฐ๋ฅผ ์ด์šฉํ•œ ์กฐ์‚ฌ์—์„œ PETscore๊ฐ€ ํ•ด๋‹น๊ณผ์ •, ํ˜„๋ฏธ๋ถ€์ˆ˜์ฒด ๋ถˆ์•ˆ์ •์„ฑ(MSI) ์ƒํƒœ, ๊ทธ๋ฆฌ๊ณ  ์ƒํ”ผ๊ฐ„์—ฝ์ดํ–‰(EMT) ๊ด€๋ จ ์˜ˆํ›„์— ์—ฐ๊ด€์„ฑ์„ ๋ณด์˜€๋‹ค. ๊ฒฐ๋ก : ์ „์ž„์ƒ์  ์œ„์•” PDX ๊ธฐ๋ฐ˜ [18F]FDG-PET ํ”„๋กœํ† ์ฝœ์€ ์ข…์–‘ ํŠน์ด์  FDG ์„ญ์ทจ๋ฅผ ๋‚˜ํƒ€๋‚ด๊ณ , ๋‹น๋Œ€์‚ฌ ๋‹จ๋ฐฑ๊ณผ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๋ณด์ธ๋‹ค. PDX ์ด์‹ ๋งˆ์šฐ์Šค๋ชจ๋ธ์€ ์œ„์•”์—์„œ PET ํ™œ์„ฑ ํ‰๊ฐ€์— ์œ ์šฉํ•  ์ˆ˜ ์žˆ๋‹ค. FDG ์„ญ์ทจ ์˜ˆ์ธก ๋ชจ๋ธ(PETscore)์€ ๋‹ค์–‘ํ•œ ๋Œ€์‚ฌ ํ”„๋กœํŒŒ์ผ ๊ธฐ๋ฐ˜ ์œ„์•”์˜ ๋ถ„์ž์  ํŠน์ง•์„ ์ œ์•ˆํ•œ๋‹ค. ๋”์šฑ์ด, PETscore๋Š” FDG ์„ญ์ทจ๋ฅผ ์˜ˆ์ธกํ•˜์—ฌ ๋ณ‘๊ธฐ ๋ฐ ๊ด€์ฐฐ์„ ์œ„ํ•œ ๊ฐœ์ธ๋งž์ถค FDG-PET์„ ์ œ์•ˆํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋‹ค.INTRODUCTION 1 PART I. Establishment of protocol for preclinical PET imaging of human gastric cancer PDX models 4 MATERIAL AND METHODS 5 RESULTS 13 PART II. Development of prediction model with a gene signature for FDG avidity in gastric cancer 25 MATERIAL AND METHODS 26 RESULTS 39 DISCUSSION 70 REFERENCES 81 ABSTRACT IN KOREAN 91Docto

    A study on extreme positive returns and expected returns

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ฒฝ์˜ํ•™๊ณผ ์žฌ๋ฌด๊ธˆ์œต ์ „๊ณต, 2013. 2. ์ตœํ˜.๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๊ทน๋‹จ์  ์–‘์˜ ์ˆ˜์ต๋ฅ ๊ณผ ์ฃผ์‹์ˆ˜์ต๋ฅ ์˜ ๊ด€๊ณ„๋ฅผ ํ•œ๊ตญ ์ฃผ์‹์‹œ์žฅ์˜ ์ž๋ฃŒ๋ฅผ ์ด์šฉํ•ด ํฌํŠธํด๋ฆฌ์˜ค ์ˆ˜์ค€์˜ ๋ถ„์„์„ ํ†ตํ•ด ๊ด€์ฐฐํ–ˆ๋‹ค. ์ตœ๋Œ€์ผ๋ณ„์ˆ˜์ต๋ฅ ์„ ๊ธฐ์ค€์œผ๋กœ ๋‚˜๋ˆˆ ํฌํŠธํด๋ฆฌ์˜ค ๋ถ„์„์„ ํ•œ ๊ฒฐ๊ณผ, ๋™์ผ๊ฐ€์ค‘ ์›”ํ‰๊ท  ์ˆ˜์ต๋ฅ ๋กœ ๋ดค์„ ๋•Œ KOSPI์‹œ์žฅ๊ณผ KOSDAQ์‹œ์žฅ ๋ชจ๋‘ ๊ทน๋‹จ์  ์–‘์˜ ์ˆ˜์ต๋ฅ ๊ณผ ์ฃผ์‹์ˆ˜์ต๋ฅ  ๊ฐ„์— ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•œ ์Œ์˜ ๊ด€๊ณ„๊ฐ€ ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ด๋Ÿฌํ•œ ๊ด€๊ณ„๋Š” ๋‘ ๊ฐ€์ง€ ๊ธฐ์ค€์œผ๋กœ ํฌํŠธํด๋ฆฌ์˜ค๋ฅผ ๋‚˜๋ˆ„๋Š” ๋ถ„์„์„ ํ†ตํ•ด ์‹œ๊ฐ€์ด์•ก, ๋ฒ ํƒ€, ๋‹จ๊ธฐ ๋ฆฌ๋ฒ„์„ค, ๋น„์œ ๋™์„ฑ, ์™œ๋„์— ๋Œ€ํ•ด ๊ฐ•๊ฑด์„ฑ์„ ๊ฐ€์ง์„ ํ™•์ธํ–ˆ๋‹ค. ํ•˜์ง€๋งŒ, ๊ธฐ์—…๊ณ ์œ  ๋ณ€๋™์„ฑ์„ ๊ณ ๋ คํ–ˆ์„ ๋•Œ๋Š” ๊ทน๋‹จ์  ์–‘์˜ ์ˆ˜์ต๋ฅ ๊ณผ ์ฃผ์‹์ˆ˜์ต๋ฅ  ์‚ฌ์ด์— ์œ ์˜ํ•œ ์Œ์˜ ๊ด€๊ณ„๊ฐ€ ๋‚˜ํƒ€๋‚˜์ง€ ์•Š์•˜๊ณ , ์ƒ์œ„ 5๊ฐœ์˜ ์ผ๋ณ„์ˆ˜์ต๋ฅ ์˜ ํ‰๊ท ๊ฐ’์„ ์ตœ๋Œ€์ผ๋ณ„์ˆ˜์ต๋ฅ ๋กœ ๊ฐ„์ฃผํ•œ ๊ฒฝ์šฐ KOSDAQ ์‹œ์žฅ์—์„œ๋งŒ ๊ทน๋‹จ์  ์–‘์˜ ์ˆ˜์ต๋ฅ ๊ณผ ์ฃผ์‹์ˆ˜์ต๋ฅ  ์‚ฌ์ด์— ์œ ์˜ํ•œ ์Œ์˜ ๊ด€๊ณ„๊ฐ€ ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ถ”๊ฐ€์ ์œผ๋กœ ๊ทน๋‹จ์  ์Œ์˜ ์ˆ˜์ต๋ฅ ๊ณผ ์ฃผ์‹์ˆ˜์ต๋ฅ ์˜ ๊ด€๊ณ„์— ๋Œ€ํ•ด์„œ๋„ ์‚ดํŽด๋ณธ ๊ฒฐ๊ณผ, ๊ทน๋‹จ์  ์–‘์˜ ์ˆ˜์ต๋ฅ ๊ณผ ๋งˆ์ฐฌ๊ฐ€์ง€๋กœ ๋™์ผ๊ฐ€์ค‘ ์›”ํ‰๊ท  ์ˆ˜์ต๋ฅ ๋กœ ๋ดค์„ ๋•Œ ๊ทน๋‹จ์  ์Œ์˜ ์ˆ˜์ต๋ฅ  ๋˜ํ•œ ์ฃผ์‹์ˆ˜์ต๋ฅ ๊ณผ ์Œ์˜ ๊ด€๊ณ„์— ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค.This study examines the relation between extreme positive returns and expected returns in the Korean stock market using portfoilo-level analyses. The results of portfolio-level analyses with maximum daily returns indicate a statistically significant negative relation between extreme positive returns and expected returns in KOSPI and KOSDAQ market in terms of equally weighted average monthly returns. By bivariate portfolio-analysis, I verified that this relation is robust to size, beta, short-term reversal, skewness. However, when idiosyncratic is considered, there is no statistically significant negative relation between extreme positive returns and expected returns. In only KOSDAQ market, when five highest maximum daily returns are considered as maximum daily returns, extreme positive returns and expected returns show a statistically significant negative relation. In addition, similarly to extreme positive returns, there is a negative relation between extreme negative returns and expected returns in terms of equally weighted average monthly returns.์ œ 1 ์žฅ ์„œ ๋ก  ์ œ 1 ์ ˆ ์—ฐ๊ตฌ ๋ชฉ์  ๋ฐ ๋ฌธํ—Œ์—ฐ๊ตฌ ์ œ 2 ์ ˆ ๋…ผ๋ฌธ์˜ ๊ตฌ์„ฑ ์ œ 2 ์žฅ ์—ฐ๊ตฌ ์ž๋ฃŒ ๋ฐ ์„ค๋ช… ๋ณ€์ˆ˜ ์ œ 1 ์ ˆ ์—ฐ๊ตฌ ์ž๋ฃŒ ์ œ 2 ์ ˆ ์„ค๋ช… ๋ณ€์ˆ˜ ์ œ 3 ์žฅ ๊ทน๋‹จ์  ์–‘์˜ ์ˆ˜์ต๋ฅ ๊ณผ ์ฃผ์‹์ˆ˜์ต๋ฅ  ์ œ 1 ์ ˆ ํ•œ ๊ฐ€์ง€ ๊ธฐ์ค€์— ๋”ฐ๋ฅธ ํฌํŠธํด๋ฆฌ์˜ค ๋ถ„์„ ์ œ 2 ์ ˆ ๋‘ ๊ฐ€์ง€ ๊ธฐ์ค€์— ๋”ฐ๋ฅธ ํฌํŠธํด๋ฆฌ์˜ค ๋ถ„์„ ์ œ 4 ์žฅ ๊ธฐ์—…๊ณ ์œ  ๋ณ€๋™์„ฑ๊ณผ ๊ทน๋‹จ์  ์ˆ˜์ต๋ฅ  ์ œ 5 ์žฅ ๊ทน๋‹จ์  ์–‘์˜ ์ˆ˜์ต๋ฅ ๊ณผ ์™œ๋„์˜ ๊ด€๊ณ„ ์ œ 6 ์žฅ ๊ทน๋‹จ์  ์Œ์˜ ์ˆ˜์ต๋ฅ ๊ณผ ์ฃผ์‹์ˆ˜์ต๋ฅ  ์ œ 7 ์žฅ ๊ฒฐ ๋ก  ์ฐธ๊ณ  ๋ฌธํ—ŒMaste

    ์ „๋ฆฌ ๋ฐฉ์‚ฌ์„  ์กฐ์‚ฌ ํ›„ ํ˜•๊ด‘ ์ด๋ฏธ์ง•์œผ๋กœ ๊ด€์ฐฐํ•œ HeLa-FUCCI์˜ S/G2/M ๋™์กฐํ™”

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์˜๊ณผ๋Œ€ํ•™ ์ข…์–‘์ƒ๋ฌผํ•™์ „๊ณต, 2016. 2. ์ •์ค€๊ธฐ.๋ชฉ์ : ์ž๊ถ๊ฒฝ๋ถ€์•”์€ ์„ธ๊ณ„์—์„œ ์—ฌ์„ฑ ์•” ์ค‘ ์„ธ ๋ฒˆ์งธ๋กœ ๋นˆ๋ฒˆํ•œ ์•”์ด๊ณ  ๋ฐฉ์‚ฌ์„ ์น˜๋ฃŒ๊ฐ€ ์ฃผ์š” ์น˜๋ฃŒ๋ฒ•์ด๋‹ค. ์•”์„ธํฌ์˜ ๋ฐฉ์‚ฌ์„  ์ €ํ•ญ์„ฑ์€ ๋ฐฉ์‚ฌ์„ ์น˜๋ฃŒ์—์„œ ํฐ ์žฅ์• ๋ฌผ์ด๋‹ค. ์„ธํฌ ์ฆ์‹๊ณผ ์น˜๋ฃŒ ํšจ๊ณผ๋Š” ์„ธํฌ์ฃผ๊ธฐ์™€ ๊ด€๋ จ์ด ์žˆ์œผ๋ฏ€๋กœ ์„ธํฌ์ฃผ๊ธฐ์˜ ๋ฐฉ์‚ฌ์„  ํšจ๊ณผ๋ฅผ ์ดํ•ดํ•˜๋Š” ๊ฒƒ์€ ์ค‘์š”ํ•˜๋‹ค. ์ตœ๊ทผ์— ๊ฐœ๋ฐœ๋œ ์„ธํฌ์ฃผ๊ธฐ ํ˜•๊ด‘ ํ”„๋กœ๋ธŒ (FUCCI)๋Š” G0/G1๊ธฐ์™€ S/G2/M๊ธฐ๋ฅผ ๊ตฌ๋ถ„๋˜๋Š” ์ƒ‰๊น”๋กœ ๋ณผ ์ˆ˜ ์žˆ๋Š” ์‹œ์Šคํ…œ์ด๋‹ค. ์ด ๋…ผ๋ฌธ์—์„œ๋Š” FUCCI ์‹œ์Šคํ…œ์„ ์ด์šฉํ•˜์—ฌ ๋ฐฉ์‚ฌ์„ ์ด ์„ธํฌ๋ถ„์—ด์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ํ‰๊ฐ€ํ•˜์˜€๋‹ค. ๋ฐฉ๋ฒ•: FUCCI๋ฅผ ๋ฐœํ˜„ํ•˜๋Š” HeLa์˜ ์„ธํฌ๋ถ„์—ด์„ ํ˜•๊ด‘ ํ˜„๋ฏธ๊ฒฝ (Olympus IX81)์„ ์‚ฌ์šฉํ•˜์—ฌ ์‹ค์‹œ๊ฐ„์œผ๋กœ ๊ด€์ฐฐํ•˜์˜€๋‹ค. G0/G1๊ธฐ์™€ S/G2/M๊ธฐ๋ฅผ ์„ธํฌ ์ฃผ๊ธฐ์— ํŠน์ด์ ์ธ ์ „์‚ฌ์ธ์ž์— ์˜ํ•ด ํ™œ์„ฑํ™”๋œ ๋‘ ํ˜•๊ด‘ ๋‹จ๋ฐฑ์งˆ์ธ Cdt1๊ณผ Geminin์„ ์ด์šฉํ•˜์—ฌ ๊ฒฐ์ •ํ•˜์˜€๋‹ค. HeLa-FUCCI ์„ธํฌ์— 0.2 mM ํ•˜์ด๋“œ๋ก์‹œ์œ ๋ฆฌ์•„๋ฅผ 24์‹œ๊ฐ„๋™์•ˆ ์ฒ˜๋ฆฌํ•˜์—ฌ ์„ธํฌ์ฃผ๊ธฐ๋ฅผ ๋™์กฐํ™”ํ•˜์˜€๊ณ , 137Cs ์กฐ์‚ฌ๊ธฐ (IBL437C)๋กœ 6 Gy ๋ฐฉ์‚ฌ์„ ์„ ์กฐ์‚ฌํ•˜์˜€๋‹ค. ๋ฐฉ์‚ฌ์„ ์ด ์กฐ์‚ฌ๋œ ์„ธํฌ์™€ ์กฐ์‚ฌ๋˜์ง€ ์•Š์€ ๋Œ€์กฐ๊ตฐ์˜ ์‹œ๊ฐ„์  ๋ณ€ํ™”๋ฅผ ํ˜•๊ด‘ ํ˜„๋ฏธ๊ฒฝ์œผ๋กœ ์ดฌ์˜ํ•˜์˜€๋‹ค. ๋™์ผ์กฐ๊ฑด ํ•˜์— FACS ๋ถ„์„์„ ํ•˜์˜€๋‹ค. ๋ˆ„๋“œ ๋งˆ์šฐ์Šค์— ์ด์ข… ์ด์‹ HeLa-FUCCI ์ข…์–‘์„ ๊ตฌ์ถ•ํ•˜์˜€๋‹ค. ๊ฐ๊ฐ์˜ ๋งˆ์šฐ์Šค ๋‚ด ๋‘ ์ข…์–‘ ์ค‘ ์„ ํ˜• ๊ฐ€์†๊ธฐ (Clinac 6EX)์˜ ๋‹ค์—ฝ์ฝœ๋ฆฌ๋ฉ”์ดํ„ฐ (MLC)์— ์˜ํ•ด ์กฐ์ ˆ๋œ ์˜์—ญ์— ์žˆ๋Š” ํ•œ ์ชฝ์—๋งŒ 6 Gy ๋ฐฉ์‚ฌ์„ ์„ ์กฐ์‚ฌํ•˜์˜€๋‹ค. ๋ชจ๋“  ์ข…์–‘์„ ์ ์ถœํ•˜์—ฌ ์ ˆํŽธํ•˜์˜€๋‹ค. ํ‘œ๋ณธ์€ ํ‹ฐ์ŠˆํŒฉ์Šค ์‹œ์Šคํ…œ์ด ๊ฒฐํ•ฉ๋œ ํ˜•๊ด‘ ํ˜„๋ฏธ๊ฒฝ (Zeiss Axioimager Z1)์œผ๋กœ ์ดฌ์˜ํ•˜์˜€๋‹ค. ๋ฉ”ํƒ€๋ชจํ”„ ์†Œํ”„ํŠธ์›จ์–ด๋ฅผ ์ด์šฉํ•˜์—ฌ ๊ฐ๊ฐ์˜ ์„ธํฌ์ฃผ๊ธฐ์— ํ•ด๋‹นํ•˜๋Š” ์•”์„ธํฌ์˜ ๋ถ„ํฌ๋ฅผ ๊ณ„์‚ฐํ•˜์˜€๋‹ค. ๊ฒฐ๊ณผ: ํ•˜์ด๋“œ๋ก์‹œ์œ ๋ฆฌ์•„๋ฅผ ์ฒ˜๋ฆฌ ํ›„ S/G2/M๊ธฐ ์„ธํฌ๋Š” FACS์—์„œ 62.11ยฑ3.57% ๊ทธ๋ฆฌ๊ณ  ํ˜•๊ด‘ ํ˜„๋ฏธ๊ฒฝ ๊ด€์ฐฐ์—์„œ 95.91ยฑ2.00%์˜€๋‹ค. S/G2/M๊ธฐ ๋™์กฐํ™”๋Š” ๋ฐฉ์‚ฌ์„ ์ด ์กฐ์‚ฌ๋œ ์„ธํฌ์—์„œ ๋Œ€์กฐ๊ตฐ์˜ ์„ธํฌ๋ณด๋‹ค ์˜ค๋ž˜ ์ง€์†๋˜์—ˆ๊ณ , ๊ทธ ์‹œ๊ฐ„ ์ฐจ๋Š” FACS์—์„œ 4์‹œ๊ฐ„, ๊ทธ๋ฆฌ๊ณ  ํ˜•๊ด‘ ํ˜„๋ฏธ๊ฒฝ์—์„œ 8์‹œ๊ฐ„์ด์—ˆ๋‹ค. FACS ๋ฐ์ดํ„ฐ์˜ ๊ฒฝ์šฐ, S/G2/M๊ธฐ ์„ธํฌ๊ฐ€ ๊ฐ€์žฅ ๋‚ฎ์•˜์„ ๋•Œ๋Š” ๋Œ€์กฐ๊ตฐ์—์„œ 12์‹œ๊ฐ„์ผ ๋•Œ (18.23ยฑ3.17%)์˜€๊ณ , ๋ฐฉ์‚ฌ์„ ์ด ์กฐ์‚ฌ๋œ ๊ตฐ ์—์„œ 16์‹œ๊ฐ„์ผ ๋•Œ (32.77ยฑ1.68%)์˜€๋‹ค. ํ˜•๊ด‘ ์ด๋ฏธ์ง• ๋ฐ์ดํ„ฐ์˜ ๊ฒฝ์šฐ, S/G2/M๊ธฐ ์„ธํฌ๊ฐ€ ๊ฐ€์žฅ ๋‚ฎ์•˜์„ ๋•Œ๋Š” ๋Œ€์กฐ๊ตฐ์—์„œ 8์‹œ๊ฐ„์ผ ๋•Œ (13.05ยฑ6.84%)์˜€๊ณ , ๋ฐฉ์‚ฌ์„ ์ด ์กฐ์‚ฌ๋œ ๊ตฐ ์—์„œ 16์‹œ๊ฐ„์ผ ๋•Œ (26.39ยฑ0.12%)์˜€๋‹ค. ์ด์ข… ์ด์‹ ๋ชจ๋ธ์˜ ๊ฒฝ์šฐ, 6 Gy๋ฅผ ์กฐ์‚ฌ ํ›„ 16์‹œ๊ฐ„ ์งธ ์ข…์–‘์—์„œ S/G2/M๊ธฐ ๋Œ€ G0/G1๊ธฐ์˜ ๋น„์œจ์ด ๊ฐ€์žฅ ๋†’์•˜๋‹ค (mAG/mKO2 = 2.00ยฑ0.84). ๊ฒฐ๋ก : ๋ฐฉ์‚ฌ์„ ์˜ ์˜ํ–ฅ์œผ๋กœ ์„ธํฌ ์ˆ˜์ค€์—์„œ S/G2/M ๋™์กฐํ™”๊ฐ€ ๋Š˜์–ด๋‚ฌ๊ณ , ๋งˆ์šฐ์Šค ๋ชจ๋ธ์—์„œ S/G2/M๊ธฐ ์„ธํฌ์˜ ๋ถ„ํฌ๊ฐ€ ์ฆ๊ฐ€ํ–ˆ๋‹ค. FUCCI ์‹œ์Šคํ…œ์€ ๋ฐฉ์‚ฌ์„ ์ด ์„ธํฌ์ฃผ๊ธฐ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ๋ฐ˜์˜ํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ, ์•”์—์„œ ๋ฐฉ์‚ฌ์„ ์ €ํ•ญ์„ฑ ๊ธฐ์ „์„ ์—ฐ๊ตฌํ•˜๋Š”๋ฐ ์œ ์šฉ ํ•  ์ˆ˜ ์žˆ๋‹ค.Objective: Cervical cancer is the third most common cancer in women worldwide and radiotherapy is one of the major treatment methods. Radioresistance of cancer cells is a big obstacle in radiotherapy. Since the cell proliferation and therapeutic efficacy might be related to cell cycle, it is necessary to understand the radiation effects on the cell cycle. Recently, fluorescent, ubiquitination-based cell cycle indicator (FUCCI) system was developed to visualize G1/G0 and/or S/G2/M phases of the cell cycle with distinct colors. In this study, I assessed the radiation effects on cell cycle using the FUCCI system. Methods: Cell division of FUCCI expressing HeLa cells was observed in real time using a fluorescence microscope (Olympus IX81). G0/G1 and S/G2/M phases were determined using two different fluorescent proteins, Cdt1 and Geminin, which were activated by cell cycle specific transcription factors. In-vitro cell studies were performed using HeLa-FUCCI cells. The cells were synchronized using 0.2 mM hydroxyurea for 24 hours, and then cells were irradiated with 6 Gy radiation using 137Cs irradiator (IBL437C). The time-lapse cellular change of irradiated or non-irradiated control cells was visualized using the fluorescence microscope. FACS analysis was also performed under the same condition. Xenografted HeLa-FUCCI tumors were established in nude mice. One side of two tumors on each mouse in the area adjusted using multi-leaf colimators (MLC) of a linear accelerator (Clinac 6EX) was irradiated with 6 Gy. All tumors were isolated and sliced. The specimens were imaged using a fluorescence microscope combined with a TissueFAXS Plusโ“‡ system. The portions of cancer cells in each cell cycle phase were calculated by the Metamorph software. Results: After hydroxyurea treatment, S/G2/M phase cells measured by FACS method and fluorescence microscopy were 62.11ยฑ3.57% and 95.91ยฑ2.00%, respectively. The S/G2/M synchronization in irradiated cells more long lasted than that in non-irradiated cells and the time difference in the FACS and fluorescence microscopy was 4 hours and 8 hours, respectively. In the FACS data, the lowest portion of S/G2/M phase cells in non-irradiated group and irradiated group and was 18.23ยฑ3.17% at 12 hours and 32.77ยฑ1.68% at 16 hours, respectively. In the fluorescence imaging data, the lowest portion of S/G2/M phase cells in non-irradiated group and irradiated group and was 13.05ยฑ6.84% at 8 hours and 26.39ยฑ0.12% at 16 hours, respectively. In xenograft models, the tumor at 16 hours after 6 Gy irradiation showed that the ratio of S/G2/M phase to G0/G1 phase was the highest (mAG/mKO2 = 2.00ยฑ0.84). Conclusion: Radiation induced prolongation of S/G2/M synchronization in vitro cells and increase of the portion of S/G2/M phase cells in vivo mouse model. The FUCCI system can reflect radiation effects on cell cycle and might be useful for studying the mechanism of radioresistance.Introduction 1 I. The necessity of studying the radiation effects on cell cycle 1 II. FUCCI as a system to visualize cell cycle 3 III. Purpose of this study 5 Material and Methods 6 Cell culture 6 Cytotoxicity test of hydroxyurea 6 Ionizing irradiation 7 Clonogenic assay 8 Flow Cytometry Analysis 8 Fluorescence imaging of HeLa-FUCCI cells 9 Xenograft modeling 10 Fluorescence imaging of tumor sections 10 Statistical analysis 11 Results 12 Classification of cell cycle phases in cells expressing the FUCCI probes 12 Optimal condition of hydroxyurea and ionizing radiation to induce cytotoxicity of cancer cells 13 Analysis of hydroxyurea-induced cell cycle synchronization 13 Radiation effects on cell cycle synchronization 14 Visualizing the fluorescence distributions in HeLa-FUCCI tumors 15 Discussion 30 References 33 Abstract in Korean 40Maste
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