22 research outputs found
An experimental study on fluid characteristics and heat transfer characteristics along a horizontal circular tube by baffle cut rate
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, 40โ, 30โ, cooling temperature 5โ. 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
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์ฌ์ฉ๊ธฐํธ โ
น
์ 1 ์ฅ ์ ๋ก 1
1.1 ์ฐ๊ตฌ์ ๋ฐฐ๊ฒฝ 1
1.2 ์ข
๋์ ์ฐ๊ตฌ์ ๋ชฉ์ 4
์ 2 ์ฅ ์คํ๋ฐฉ๋ฒ ๋ฐ ์คํ๋ฒ์ 7
2.1 ์คํ๋ฐฉ๋ฒ ๋ฐ ์คํ๋ฒ์ 7
2.2 PIV ์์คํ
์ ๊ตฌ์ฑ 12
2.2.1 ์กฐ๋ช
๋ฐ ์ถ์ ์
์ 12
2.2.2 ์์ ์
๋ ฅ ๋ฐ ์ ์ฅ ์ฅ์น 13
2.2.3 ์ํตํ ๋ ์ฆ 15
2.3 ๊ท ์ผ ์ ์
์๋ ํ์ธ 15
์ 3์ฅ ์๊ด ๋ด์์์ ์ด์ ๋ฌ ์์นํด์ 18
3.1 ์ด๋ก ํด์ 18
3.1.1 ์์นํด์ ๊ฐ์ 18
3.1.2 ์ง๋ฐฐ๋ฐฉ์ ์ 19
3.2 ๊ฒฝ๊ณ์กฐ๊ฑด 20
3.2.1 ์
๊ตฌ์กฐ๊ฑด 20
3.2.2 ์ถ๊ตฌ์กฐ๊ฑด 20
3.2.3 ์์นํด์ ๋ฐฉ๋ฒ 20
3.3 ๋ชจ๋ธ๋ง ํ์ 21
3.4 ํด์ ๊ฒฐ๊ณผ ๋ฐ ๊ณ ์ฐฐ 23
3.4.1 ์ด์ ๋ฌ ํน์ฑ 23
3.4.2 ์๋ ฅ๊ฐํ ํน์ฑ 30
3.6 ๊ฒฐ ๋ก 32
์ 4 ์ฅ ์๊ด ๋ด์์์ ์ ์ฒด์ ๋ ๋ฐ ์ด์ ๋ฌ ํน์ฑ 33
4.1 ์คํ์ฅ์น 33
4.2 Baffle์ ๋ฐ๋ฅธ ์ํฅ 45
4.2.1 ์๋ ํ๋กํ์ผ 45
4.2.2 ๋๋ฅ๊ฐ๋ 52
4.2.3 ์ด๋์๋์ง 59
4.2.4 ์ด์ ๋ฌ ํน์ฑ 66
4.3 ์ ์์ ๋ฐ๋ฅธ ์ํฅ 73
4.3.1 ์๋ ํ๋กํ์ผ 73
4.3.2 ๋๋ฅ๊ฐ๋ 77
4.3.3 ์ด๋์๋์ง 87
4.3.4 ์ด์ ๋ฌ ํน์ฑ 91
4.4 ์๋ ฅ๊ฐํ ํน์ฑ 95
์ 5 ์ฅ ์ด ๊ฒฐ ๋ก 97
์ฐธ ๊ณ ๋ฌธ ํ 9
ํ์์ ๋ ์ด์ข ์ด์ ๋ชจ๋ธ์ ์ด์ฉํ ์์์์ ์ด๋ฏธ์ง ๋ฐ์ด์ค๋ง์ปค๋ก์จ FDG ์นํ๋ ฅ ์์ธก ๋ชจ๋ธ
ํ์๋
ผ๋ฌธ (๋ฐ์ฌ) -- ์์ธ๋ํ๊ต ๋ํ์ : ์๊ณผ๋ํ ํ๋๊ณผ์ ์ข
์์๋ฌผํ์ ๊ณต, 2020. 8. ์ํ๊ด.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 ๋ค์ํ ์์ ๋ณ๊ธฐ, ์ฝ๋ฌผ๋ฐ์ ๊ทธ๋ฆฌ๊ณ ์ฌ๋ฐ ํ๊ฐ์ ๋๋ฆฌ ์ฐ์ด๋, ์์์ ๊ฒฝ์ฐ FDG์ ์ญ์ทจ๊ฐ ์ผ์ ์น ์์ ๊ทธ ์ญํ ์ด ์ ํ์ ์ด๋ค. ํ์์ ๋์ด์ข
์ด์ ๋ชจ๋ธ(PDX)์ ์ ์์ ์ฐ๊ตฌ์์ ์ ๋งํ in-vivo ๋ชจ๋ธ์ด๋ค. ๋ณธ ์ฐ๊ตฌ๋ ํ์๋ง์ถค PET ๊ณํ ๋ฐ ๋ถ์์ ํน์ฑ ์กฐ์ฌ๋ฅผ ์ํด ์์ PDX ๋ง์ฐ์ค ๋ชจ๋ธ์ ์ด์ฉํ FDG ์ญ์ทจ ์์ธก ์ ์ ์ ์งํ๋ฅผ ๊ฐ๋ฐํ๋ ๊ฒ์ด๋ค.
๋ฐฉ๋ฒ: ์์ปท BALB/c ๋๋๋ง์ฐ์ค์ ์์ PDX ์กฐ์ง์ ์ ์ ๋ฐ ํผํ์ ์ด์ํ๋ค. [18F]FDG-PET ์ดฌ์ ํ๋กํ ์ฝ์ ๋ค์ํ ์ข
์ ํฌ๊ธฐ ๋ฐ FDG ์ ๋, ์ดฌ์ ๊ฐ๊ฒฉ ๊ทธ๋ฆฌ๊ณ ์ฅ๊ธฐ ํน์ด์ FDG ์ญ์ทจ์ ๋ํด ํ๊ฐํ๋ค. ๋์ผ PDX๋ฅผ ์ด์ฉํ ์ ์ ๋ฐ ํผํ ์ด์ ๋ชจ๋ธ ๊ฐ FDG ์นํ๋ ฅ์ ๋น๊ตํ๋ค. ์ข
์ ์ฑ์ฅ ํ์ธ ๋ฐ ํฌ๋๋น ์์ก์ฒด 1(GLUT1) ๊ทธ๋ฆฌ๊ณ ํฅ์ํค๋์์ 2(HK2)์ FDG ์ญ์ทจ ๊ฐ ์๊ด๊ด๊ณ๋ฅผ ํ๋ฏธ๊ฒฝ์ ๊ด์ฐฐ๊ณผ ๋ฉด์ญ์ผ์ ํ์ฉํ์ฌ ์กฐ์ฌํ๋ค.
FDG-PET ๊ฒฐ๊ณผ๊ฐ ์๋ 30๋ก์ PDX์ RNA ์ํ์ฑ ๋ฐ์ดํฐ๋ฅผ ์ด์ฉํ์ฌ ์ต๋ ํ์ค์ญ์ทจ๊ณ์(SUVmax)์ ์ฐ๊ด๋ ์ ์ ์ ์งํ๋ฅผ ์๋ณํ๋ค. 5๊ฐ์ง ์ ์ ์ ์งํ(PLS1, PYY, HBQ1, SLC6A5, NAT16)๋ฅผ ์ด์ฉํ์ฌ ๋์ FDG ์ญ์ทจ๋ฅผ ๋ณด์ด๋ ์์์ ์์ธกํ๋ ๋ชจ๋ธ(PETscore)๋ฅผ ๊ตฌ์ถํ๊ณ , ํ์์์ RNA-seq ๊ณผ qRT-PCR ๊ธฐ๋ฒ์ ํตํด ํ๊ฐํ๋ค. ๋์ฑ์ด, ์์ ์ ์ฒด์ง๋(TCGA) ๋ฐ ์์์ ์ ์ฐ๊ตฌ ๊ทธ๋ฃน(ACRG) ์์ ๊ณต๊ณต๋ฐ์ดํฐ์์ ๋ชจ๋ธ์ ํน์ฑ์ ์กฐ์ฌํ๋ค.
๊ฒฐ๊ณผ: PET ์ดฌ์ ํ๋กํ ์ฝ 150 ฮผCi ์ ์ฉ๋์ ์ฃผ์
ํ๊ณ , 1์๊ฐ ๋ค ์ดฌ์ํ๋ ๊ฒ์ผ๋ก ๊ฒฐ์ ํ๋ค. ๋์ผ PDX ์กฐ์ง์ ์ด์ฉํ ์ ์์ด์ ๋ฐ ํผํ์ด์ ๋ง์ฐ์ค ๋ชจ๋ธ ๊ฐ ๋น๊ต์์ ์ ์์ด์ ๋ชจ๋ธ์ด FDG์ญ์ทจ๊ฐ ๋์๊ณ , ์ข
์ ์ฑ์ฅ์ด ๋๋ ธ๋ค. ์ข
์ ์ธํฌ ๋ด GLUT1๊ณผ HK2 ๋ฐํ์ H-score๋ SUVmax์ ์๊ด๊ด๊ณ๋ฅผ ๋ณด์๋ค.
ํ์์์ PETscore๋ ์ค์ SUVmax๊ฐ๊ณผ ๋น๊ตํ์ฌ ์ ์ํ ์์ธก ๊ฐ์ ์ ๊ณตํ๋ค. TCGA ๋ฐ ACRG ๋ฐ์ดํฐ๋ฅผ ์ด์ฉํ ์กฐ์ฌ์์ PETscore๊ฐ ํด๋น๊ณผ์ , ํ๋ฏธ๋ถ์์ฒด ๋ถ์์ ์ฑ(MSI) ์ํ, ๊ทธ๋ฆฌ๊ณ ์ํผ๊ฐ์ฝ์ดํ(EMT) ๊ด๋ จ ์ํ์ ์ฐ๊ด์ฑ์ ๋ณด์๋ค.
๊ฒฐ๋ก : ์ ์์์ ์์ PDX ๊ธฐ๋ฐ [18F]FDG-PET ํ๋กํ ์ฝ์ ์ข
์ ํน์ด์ FDG ์ญ์ทจ๋ฅผ ๋ํ๋ด๊ณ , ๋น๋์ฌ ๋จ๋ฐฑ๊ณผ ์๊ด๊ด๊ณ๋ฅผ ๋ณด์ธ๋ค. PDX ์ด์ ๋ง์ฐ์ค๋ชจ๋ธ์ ์์์์ PET ํ์ฑ ํ๊ฐ์ ์ ์ฉํ ์ ์๋ค. FDG ์ญ์ทจ ์์ธก ๋ชจ๋ธ(PETscore)์ ๋ค์ํ ๋์ฌ ํ๋กํ์ผ ๊ธฐ๋ฐ ์์์ ๋ถ์์ ํน์ง์ ์ ์ํ๋ค. ๋์ฑ์ด, PETscore๋ FDG ์ญ์ทจ๋ฅผ ์์ธกํ์ฌ ๋ณ๊ธฐ ๋ฐ ๊ด์ฐฐ์ ์ํ ๊ฐ์ธ๋ง์ถค FDG-PET์ ์ ์ํ ์ ์์ ๊ฒ์ด๋ค.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
ํ์๋
ผ๋ฌธ (์์ฌ)-- ์์ธ๋ํ๊ต ๋ํ์ : ๊ฒฝ์ํ๊ณผ ์ฌ๋ฌด๊ธ์ต ์ ๊ณต, 2013. 2. ์ตํ.๋ณธ ์ฐ๊ตฌ์์๋ ๊ทน๋จ์ ์์ ์์ต๋ฅ ๊ณผ ์ฃผ์์์ต๋ฅ ์ ๊ด๊ณ๋ฅผ ํ๊ตญ ์ฃผ์์์ฅ์ ์๋ฃ๋ฅผ ์ด์ฉํด ํฌํธํด๋ฆฌ์ค ์์ค์ ๋ถ์์ ํตํด ๊ด์ฐฐํ๋ค. ์ต๋์ผ๋ณ์์ต๋ฅ ์ ๊ธฐ์ค์ผ๋ก ๋๋ ํฌํธํด๋ฆฌ์ค ๋ถ์์ ํ ๊ฒฐ๊ณผ, ๋์ผ๊ฐ์ค ์ํ๊ท ์์ต๋ฅ ๋ก ๋ดค์ ๋ KOSPI์์ฅ๊ณผ KOSDAQ์์ฅ ๋ชจ๋ ๊ทน๋จ์ ์์ ์์ต๋ฅ ๊ณผ ์ฃผ์์์ต๋ฅ ๊ฐ์ ํต๊ณ์ ์ผ๋ก ์ ์ํ ์์ ๊ด๊ณ๊ฐ ์๋ ๊ฒ์ผ๋ก ๋ํ๋ฌ๋ค. ์ด๋ฌํ ๊ด๊ณ๋ ๋ ๊ฐ์ง ๊ธฐ์ค์ผ๋ก ํฌํธํด๋ฆฌ์ค๋ฅผ ๋๋๋ ๋ถ์์ ํตํด ์๊ฐ์ด์ก, ๋ฒ ํ, ๋จ๊ธฐ ๋ฆฌ๋ฒ์ค, ๋น์ ๋์ฑ, ์๋์ ๋ํด ๊ฐ๊ฑด์ฑ์ ๊ฐ์ง์ ํ์ธํ๋ค. ํ์ง๋ง, ๊ธฐ์
๊ณ ์ ๋ณ๋์ฑ์ ๊ณ ๋ คํ์ ๋๋ ๊ทน๋จ์ ์์ ์์ต๋ฅ ๊ณผ ์ฃผ์์์ต๋ฅ ์ฌ์ด์ ์ ์ํ ์์ ๊ด๊ณ๊ฐ ๋ํ๋์ง ์์๊ณ , ์์ 5๊ฐ์ ์ผ๋ณ์์ต๋ฅ ์ ํ๊ท ๊ฐ์ ์ต๋์ผ๋ณ์์ต๋ฅ ๋ก ๊ฐ์ฃผํ ๊ฒฝ์ฐ KOSDAQ ์์ฅ์์๋ง ๊ทน๋จ์ ์์ ์์ต๋ฅ ๊ณผ ์ฃผ์์์ต๋ฅ ์ฌ์ด์ ์ ์ํ ์์ ๊ด๊ณ๊ฐ ์๋ ๊ฒ์ผ๋ก ๋ํ๋ฌ๋ค. ์ถ๊ฐ์ ์ผ๋ก ๊ทน๋จ์ ์์ ์์ต๋ฅ ๊ณผ ์ฃผ์์์ต๋ฅ ์ ๊ด๊ณ์ ๋ํด์๋ ์ดํด๋ณธ ๊ฒฐ๊ณผ, ๊ทน๋จ์ ์์ ์์ต๋ฅ ๊ณผ ๋ง์ฐฌ๊ฐ์ง๋ก ๋์ผ๊ฐ์ค ์ํ๊ท ์์ต๋ฅ ๋ก ๋ดค์ ๋ ๊ทน๋จ์ ์์ ์์ต๋ฅ ๋ํ ์ฃผ์์์ต๋ฅ ๊ณผ ์์ ๊ด๊ณ์ ์๋ ๊ฒ์ผ๋ก ๋ํ๋ฌ๋ค.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.์ 1 ์ฅ ์ ๋ก
์ 1 ์ ์ฐ๊ตฌ ๋ชฉ์ ๋ฐ ๋ฌธํ์ฐ๊ตฌ
์ 2 ์ ๋
ผ๋ฌธ์ ๊ตฌ์ฑ
์ 2 ์ฅ ์ฐ๊ตฌ ์๋ฃ ๋ฐ ์ค๋ช
๋ณ์
์ 1 ์ ์ฐ๊ตฌ ์๋ฃ
์ 2 ์ ์ค๋ช
๋ณ์
์ 3 ์ฅ ๊ทน๋จ์ ์์ ์์ต๋ฅ ๊ณผ ์ฃผ์์์ต๋ฅ
์ 1 ์ ํ ๊ฐ์ง ๊ธฐ์ค์ ๋ฐ๋ฅธ ํฌํธํด๋ฆฌ์ค ๋ถ์
์ 2 ์ ๋ ๊ฐ์ง ๊ธฐ์ค์ ๋ฐ๋ฅธ ํฌํธํด๋ฆฌ์ค ๋ถ์
์ 4 ์ฅ ๊ธฐ์
๊ณ ์ ๋ณ๋์ฑ๊ณผ ๊ทน๋จ์ ์์ต๋ฅ
์ 5 ์ฅ ๊ทน๋จ์ ์์ ์์ต๋ฅ ๊ณผ ์๋์ ๊ด๊ณ
์ 6 ์ฅ ๊ทน๋จ์ ์์ ์์ต๋ฅ ๊ณผ ์ฃผ์์์ต๋ฅ
์ 7 ์ฅ ๊ฒฐ ๋ก
์ฐธ๊ณ ๋ฌธํMaste
๋ฐฐํ ํ๋ ์ดํธ ํฌ๊ธฐ์ ๋ฐ๋ฅธ ๊ด๋ด ์ ์ฒด ์ ๋ ํน์ฑ ๋ฐ ์ด์ ๋ฌ ํน์ฑ์ ๊ดํ ์คํ์ ์ฐ๊ตฌ
์ ๋ฆฌ ๋ฐฉ์ฌ์ ์กฐ์ฌ ํ ํ๊ด ์ด๋ฏธ์ง์ผ๋ก ๊ด์ฐฐํ HeLa-FUCCI์ S/G2/M ๋์กฐํ
ํ์๋
ผ๋ฌธ (์์ฌ)-- ์์ธ๋ํ๊ต ๋ํ์ : ์๊ณผ๋ํ ์ข
์์๋ฌผํ์ ๊ณต, 2016. 2. ์ ์ค๊ธฐ.๋ชฉ์ : ์๊ถ๊ฒฝ๋ถ์์ ์ธ๊ณ์์ ์ฌ์ฑ ์ ์ค ์ธ ๋ฒ์งธ๋ก ๋น๋ฒํ ์์ด๊ณ ๋ฐฉ์ฌ์ ์น๋ฃ๊ฐ ์ฃผ์ ์น๋ฃ๋ฒ์ด๋ค. ์์ธํฌ์ ๋ฐฉ์ฌ์ ์ ํญ์ฑ์ ๋ฐฉ์ฌ์ ์น๋ฃ์์ ํฐ ์ฅ์ ๋ฌผ์ด๋ค. ์ธํฌ ์ฆ์๊ณผ ์น๋ฃ ํจ๊ณผ๋ ์ธํฌ์ฃผ๊ธฐ์ ๊ด๋ จ์ด ์์ผ๋ฏ๋ก ์ธํฌ์ฃผ๊ธฐ์ ๋ฐฉ์ฌ์ ํจ๊ณผ๋ฅผ ์ดํดํ๋ ๊ฒ์ ์ค์ํ๋ค. ์ต๊ทผ์ ๊ฐ๋ฐ๋ ์ธํฌ์ฃผ๊ธฐ ํ๊ด ํ๋ก๋ธ (FUCCI)๋ G0/G1๊ธฐ์ S/G2/M๊ธฐ๋ฅผ ๊ตฌ๋ถ๋๋ ์๊น๋ก ๋ณผ ์ ์๋ ์์คํ
์ด๋ค. ์ด ๋
ผ๋ฌธ์์๋ FUCCI ์์คํ
์ ์ด์ฉํ์ฌ ๋ฐฉ์ฌ์ ์ด ์ธํฌ๋ถ์ด์ ๋ฏธ์น๋ ์ํฅ์ ํ๊ฐํ์๋ค.
๋ฐฉ๋ฒ: FUCCI๋ฅผ ๋ฐํํ๋ HeLa์ ์ธํฌ๋ถ์ด์ ํ๊ด ํ๋ฏธ๊ฒฝ (Olympus IX81)์ ์ฌ์ฉํ์ฌ ์ค์๊ฐ์ผ๋ก ๊ด์ฐฐํ์๋ค. G0/G1๊ธฐ์ S/G2/M๊ธฐ๋ฅผ ์ธํฌ ์ฃผ๊ธฐ์ ํน์ด์ ์ธ ์ ์ฌ์ธ์์ ์ํด ํ์ฑํ๋ ๋ ํ๊ด ๋จ๋ฐฑ์ง์ธ Cdt1๊ณผ Geminin์ ์ด์ฉํ์ฌ ๊ฒฐ์ ํ์๋ค. HeLa-FUCCI ์ธํฌ์ 0.2 mM ํ์ด๋๋ก์์ ๋ฆฌ์๋ฅผ 24์๊ฐ๋์ ์ฒ๋ฆฌํ์ฌ ์ธํฌ์ฃผ๊ธฐ๋ฅผ ๋์กฐํํ์๊ณ , 137Cs ์กฐ์ฌ๊ธฐ (IBL437C)๋ก 6 Gy ๋ฐฉ์ฌ์ ์ ์กฐ์ฌํ์๋ค. ๋ฐฉ์ฌ์ ์ด ์กฐ์ฌ๋ ์ธํฌ์ ์กฐ์ฌ๋์ง ์์ ๋์กฐ๊ตฐ์ ์๊ฐ์ ๋ณํ๋ฅผ ํ๊ด ํ๋ฏธ๊ฒฝ์ผ๋ก ์ดฌ์ํ์๋ค. ๋์ผ์กฐ๊ฑด ํ์ FACS ๋ถ์์ ํ์๋ค. ๋๋ ๋ง์ฐ์ค์ ์ด์ข
์ด์ HeLa-FUCCI ์ข
์์ ๊ตฌ์ถํ์๋ค. ๊ฐ๊ฐ์ ๋ง์ฐ์ค ๋ด ๋ ์ข
์ ์ค ์ ํ ๊ฐ์๊ธฐ (Clinac 6EX)์ ๋ค์ฝ์ฝ๋ฆฌ๋ฉ์ดํฐ (MLC)์ ์ํด ์กฐ์ ๋ ์์ญ์ ์๋ ํ ์ชฝ์๋ง 6 Gy ๋ฐฉ์ฌ์ ์ ์กฐ์ฌํ์๋ค. ๋ชจ๋ ์ข
์์ ์ ์ถํ์ฌ ์ ํธํ์๋ค. ํ๋ณธ์ ํฐ์ํฉ์ค ์์คํ
์ด ๊ฒฐํฉ๋ ํ๊ด ํ๋ฏธ๊ฒฝ (Zeiss Axioimager Z1)์ผ๋ก ์ดฌ์ํ์๋ค. ๋ฉํ๋ชจํ ์ํํธ์จ์ด๋ฅผ ์ด์ฉํ์ฌ ๊ฐ๊ฐ์ ์ธํฌ์ฃผ๊ธฐ์ ํด๋นํ๋ ์์ธํฌ์ ๋ถํฌ๋ฅผ ๊ณ์ฐํ์๋ค.
๊ฒฐ๊ณผ: ํ์ด๋๋ก์์ ๋ฆฌ์๋ฅผ ์ฒ๋ฆฌ ํ S/G2/M๊ธฐ ์ธํฌ๋ FACS์์ 62.11ยฑ3.57% ๊ทธ๋ฆฌ๊ณ ํ๊ด ํ๋ฏธ๊ฒฝ ๊ด์ฐฐ์์ 95.91ยฑ2.00%์๋ค. S/G2/M๊ธฐ ๋์กฐํ๋ ๋ฐฉ์ฌ์ ์ด ์กฐ์ฌ๋ ์ธํฌ์์ ๋์กฐ๊ตฐ์ ์ธํฌ๋ณด๋ค ์ค๋ ์ง์๋์๊ณ , ๊ทธ ์๊ฐ ์ฐจ๋ FACS์์ 4์๊ฐ, ๊ทธ๋ฆฌ๊ณ ํ๊ด ํ๋ฏธ๊ฒฝ์์ 8์๊ฐ์ด์๋ค. FACS ๋ฐ์ดํฐ์ ๊ฒฝ์ฐ, S/G2/M๊ธฐ ์ธํฌ๊ฐ ๊ฐ์ฅ ๋ฎ์์ ๋๋ ๋์กฐ๊ตฐ์์ 12์๊ฐ์ผ ๋ (18.23ยฑ3.17%)์๊ณ , ๋ฐฉ์ฌ์ ์ด ์กฐ์ฌ๋ ๊ตฐ ์์ 16์๊ฐ์ผ ๋ (32.77ยฑ1.68%)์๋ค. ํ๊ด ์ด๋ฏธ์ง ๋ฐ์ดํฐ์ ๊ฒฝ์ฐ, S/G2/M๊ธฐ ์ธํฌ๊ฐ ๊ฐ์ฅ ๋ฎ์์ ๋๋ ๋์กฐ๊ตฐ์์ 8์๊ฐ์ผ ๋ (13.05ยฑ6.84%)์๊ณ , ๋ฐฉ์ฌ์ ์ด ์กฐ์ฌ๋ ๊ตฐ ์์ 16์๊ฐ์ผ ๋ (26.39ยฑ0.12%)์๋ค. ์ด์ข
์ด์ ๋ชจ๋ธ์ ๊ฒฝ์ฐ, 6 Gy๋ฅผ ์กฐ์ฌ ํ 16์๊ฐ ์งธ ์ข
์์์ S/G2/M๊ธฐ ๋ G0/G1๊ธฐ์ ๋น์จ์ด ๊ฐ์ฅ ๋์๋ค (mAG/mKO2 = 2.00ยฑ0.84).
๊ฒฐ๋ก : ๋ฐฉ์ฌ์ ์ ์ํฅ์ผ๋ก ์ธํฌ ์์ค์์ S/G2/M ๋์กฐํ๊ฐ ๋์ด๋ฌ๊ณ , ๋ง์ฐ์ค ๋ชจ๋ธ์์ S/G2/M๊ธฐ ์ธํฌ์ ๋ถํฌ๊ฐ ์ฆ๊ฐํ๋ค. FUCCI ์์คํ
์ ๋ฐฉ์ฌ์ ์ด ์ธํฌ์ฃผ๊ธฐ์ ๋ฏธ์น๋ ์ํฅ์ ๋ฐ์ํ ์ ์์ผ๋ฉฐ, ์์์ ๋ฐฉ์ฌ์ ์ ํญ์ฑ ๊ธฐ์ ์ ์ฐ๊ตฌํ๋๋ฐ ์ ์ฉ ํ ์ ์๋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