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    ๊ธˆ์œต ๊ฒฝ์ œ์— ๊ด€ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์‚ฌํšŒ๊ณผํ•™๋Œ€ํ•™ ๊ฒฝ์ œํ•™๋ถ€, 2021.8. ๊น€ํ˜„์„.๊ธˆ์œต ๊ฒฝ์ œ๋Š” ์—ฌ๋Ÿฌ ๊ธฐ์ˆ ์˜ ๋ฐœ์ „๊ณผ ํ•จ๊ป˜ ๋น ๋ฅด๊ฒŒ ์„ฑ์žฅํ•˜๊ณ  ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ๊ธฐ์ˆ ์˜ ๋ฐœ์ „์€ ๋งŽ์€ ์‚ฌ๋žŒ๋“ค์ด ๊ธˆ์œต์ž์‚ฐ์— ์ ‘๊ทผํ•˜๊ธฐ ์‰ฝ๊ฒŒ ๋งŒ๋“ค์—ˆ๊ณ  ์ด๋Š” ๊ธˆ์œต ๊ฒฝ์ œ๊ฐ€ ์‹ค๋ฌผ ๊ฒฝ์ œ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ์ฆ๊ฐ€์‹œํ‚ค๊ณ  ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋ฏ€๋กœ ๊ธˆ์œต ๊ฒฝ์ œ์˜ ๋ณด๋‹ค ์ •ํ™•ํ•œ ์˜ํ–ฅ์„ ๋ถ„์„ํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ๋งŽ์€ ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•œ ์ƒํ™ฉ์ด๋‹ค. ๋ณธ ํ•™์œ„ ๋…ผ๋ฌธ์€ ๊ธˆ์œต ๊ฒฝ์ œ์— ๊ด€ํ•œ ์„ธ ๊ฐœ์˜ ๋‹ค๋ฅธ ์ฃผ์ œ๋กœ ๊ธˆ์œต ๊ฒฝ์ œ๋ฅผ ๋ถ„์„ํ•˜๋Š” ๊ฒƒ์„ ๋ชฉ์ ์œผ๋กœ ํ•œ๋‹ค. ์ฒซ ๋ฒˆ์งธ ์ฃผ์ œ๋Š” ์ฑ„๊ถŒ์‹œ์žฅ์˜ ๊ฐœ๋ฐœ์ด ํ†ตํ™” ์ •์ฑ…์˜ pass-through์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ๋ถ„์„ํ•œ ์—ฐ๊ตฌ์ด๋‹ค. ์ฑ„๊ถŒ ์‹œ์žฅ์˜ ๋ฐœ์ „ ์ง€ํ‘œ๋กœ ์ฑ„๊ถŒ์˜ ๋ฐœํ–‰์–‘์„ GDP๋กœ ๋‚˜๋ˆ„์–ด ์‚ฌ์šฉํ•˜์˜€์œผ๋ฉฐ ์—ฐ๊ตฌ์˜ ๊ฒฐ๊ณผ์—์„œ ๋Œ€์ถœ ๊ธˆ๋ฆฌ์— ๋Œ€ํ•œ ํ†ตํ™” ๊ธˆ๋ฆฌ์˜ pass-through๊ฐ€ ์ฑ„๊ถŒ ์‹œ์žฅ์˜ ๋ฐœ์ „ ์ •๋„์— ๋”ฐ๋ผ ํฌ๊ฒŒ ์˜ํ–ฅ์„ ๋ฐ›์Œ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋‘ ๋ฒˆ์งธ ์ฃผ์ œ๋Š” ๋ถˆํ™•์‹ค์„ฑ ์ถฉ๊ฒฉ์— ๋Œ€ํ•œ ์ฃผ์š” ๊ฑฐ์‹œ ๋ณ€์ˆ˜๋“ค์˜ ๋น„๋Œ€์นญ ๋ฐ˜์‘์„ ์—ฐ๊ตฌํ•œ ๋‚ด์šฉ์œผ๋กœ์„œ Smooth local project (SLP) ๋ฐฉ๋ฒ•์„ ์ด์šฉํ•˜์—ฌ ์ฃผ์š” ๊ฑฐ์‹œ๋ณ€์ˆ˜๋“ค์˜ ๋น„๋Œ€์นญ ๋ฐ˜์‘์„ ์‹ค์ฆ ๋ถ„์„ํ•˜๊ณ  ์‹ค์ฆ ๋ถ„์„์˜ ๊ฒฐ๊ณผ๋ฅผ ํ† ๋Œ€๋กœ DSGE ๋ชจํ˜•์— ๋ถˆํ™•์‹ค์„ฑ ์ถฉ๊ฒฉ์˜ ๋น„๋Œ€์นญ์„ฑ์„ calibrationํ•˜์˜€๋‹ค. ๋ชจ๋ธ ์ถ”์ • ๊ฒฐ๊ณผ ์–‘์˜ ๋ถˆํ™•์‹ค์„ฑ ์ถฉ๊ฒฉ์ด ์Œ์˜ ๋ถˆํ™•์‹ค์„ฑ ์ถฉ๊ฒฉ๋ณด๋‹ค ์ง€์†์„ฑ์ด ๋‚ฎ๊ณ  ๋ณ€๋™์„ฑ์ด ๋†’๋‹ค๋Š” ์‚ฌ์‹ค์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋˜ํ•œ ๊ฐ€๊ฒฉ ๊ฒฝ์ง์„ฑ๊ณผ ์œ„ํ—˜ ํšŒํ”ผ์„ฑ์€ ์ด๋Ÿฌํ•œ ๋ถˆํ™•์‹คํ•œ ์ถฉ๊ฒฝ์˜ ๋น„๋Œ€์นญ์„ฑ์— ์˜ํ–ฅ์„ ์ฃผ๋Š” ๊ฒƒ์œผ๋กœ ํ™•์ธ๋˜์—ˆ๋‹ค. ์„ธ ๋ฒˆ์งธ ์ฃผ์ œ๋Š” ๊ธˆ์œต์‹œ์žฅ์˜ ์œ ์ถœ ํšจ๊ณผ๋ฅผ ๊ณ ๋ คํ•œ ๊ฒฝ์šฐ ์ฃผ์‹๊ณผ ๊ตญ๊ณ ์ฑ„ ๊ฐ„์˜ ๋™์  ๊ด€๊ณ„๋ฅผ ๋ถ„์„ํ•œ ์—ฐ๊ตฌ์ด๋‹ค. ๊ธˆ์œต ์‹œ์žฅ์˜ ์œ ์ถœ ํšจ๊ณผ๋กœ์„œ ์œ„ํ—˜ ์œ ์ถœ ํšจ๊ณผ์™€ ๊ธˆ์œต ์ •๋ณด ์œ ์ถœ ํšจ๊ณผ๋ฅผ ์ •์˜ํ•˜๊ณ  ์ด๋Ÿฌํ•œ ์œ ์ถœ ํšจ๊ณผ๊ฐ€ ์žˆ๋Š” ๊ฒฝ์šฐ ๋ฏธ๊ตญ์˜ ์ฃผ์‹๊ณผ ๊ตญ๊ณ ์ฑ„ ๊ฐ„์˜ ๊ด€๊ณ„๋ฅผ ์‹ค์ฆ ๋ถ„์„ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ์˜ ๊ฒฐ๊ณผ๋ฅผ ํ†ตํ•ด ์ด๋Ÿฌํ•œ ์œ ์ถœ ํšจ๊ณผ๊ฐ€ ๋‘ ์‹œ์žฅ์˜ ๊ด€๊ณ„์— ์œ ์˜๋ฏธํ•œ ํšจ๊ณผ๋ฅผ ์ฃผ๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๊ณ  ์กฐ๊ฑด๋ถ€ ๋ณ€๋™์„ฑ๊ณผ ์ƒ๊ด€ ๊ณ„์ˆ˜์— ์˜ํ–ฅ์„ ์ฃผ๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ๋ฐœ๊ฒฌ์€ ๊ธˆ์œต ํ”„ํ† ํด๋ฆฌ์˜ค ํˆฌ์ž์ž์™€ ์ •๋ถ€ ์ •์ฑ… ์ž…์•ˆ์ž์—๊ฒŒ ์ค‘์š”ํ•œ ์˜๋ฏธ๋ฅผ ์ œ๊ณตํ•œ๋‹ค๊ณ  ๋ณผ ์ˆ˜ ์žˆ๋‹ค.The financial economy has grown rapidly with technology development. Financial assets are becoming more accessible to people, and this is increasing the impact of the financial economy on the real economy. Thus, many studies are needed to analyze the more accurate impact of the financial economy. This dissertation aims to analyze the financial economy with three separate essays. The first chapter analyzes how bond market development affects the pass-through of monetary policy to bank lending rates by using panel data of 36 countries. As the measure of bond market development, we use the ratio of outstanding bonds to GDP. Results show that the degree of monetary policy pass-through to lending rates are significantly changed by bond market development. The effect of bond market development is robust under various specifications of the empirical model. The second chapter studies asymmetric responses of economic agents to the uncertainty shock. Using a smooth local projection (SLP) method, study shows that macro variables have asymmetric responses to the increasing and decreasing VXO shocks and calibrate the asymmetric uncertainty shock process in a DSGE model using the empirical result. Model estimation results show that a positive uncertainty shock have lower persistence and higher volatile than a negative uncertainty shock. Furthermore, price stickiness and risk aversion affect asymmetry of responses to uncertainty shocks. The third chapter analyzes the dynamic relationship between the US stock and treasury bonds while considering spillover effects. Moving average terms and stock volume changes are used to measure the risk spillover and financial information spillover, respectively. Empirical results show three important implications in US financial markets. First, the stock market return and volatility decrease the bond market return, whereas the bond market return and volatility have no effects on the stock return. Second, spillover effects are observed in US financial markets and spillover effects vary depending on market conditions. Third, spillover effects affect the conditional second moments relations between the stock and bond returns. The findings provide an important implication for financial portfolio investors and policy makers.CHAPTER 1. Bond Market Development and Monetary Policy Pass-Through to Bank Lending Rates ๏ผ‘ 1.1. INTRODUCTION ๏ผ‘ 1.2. DATA AND METHODOLOGY ๏ผ• 1.2.1. Empirical Methodology ๏ผ• 1.2.2. Data ๏ผ– 1.3. BASELINE MODEL RESULTS ๏ผ™ 1.4. EXTENDED ANALYSIS ๏ผ‘๏ผ‘ 1.5. CONCLUSION ๏ผ’๏ผ CHAPTER 2. Asymmetric uncertainty shocks in a DSGE model ๏ผ’๏ผ” 2.1. INTRODUCTION ๏ผ’๏ผ” 2.2. EMPIRICAL WORKS ๏ผ’๏ผ— 2.3. DSGE MODEL ๏ผ“๏ผ’ 2.4. RESULT ๏ผ”๏ผ’ 2.5. FURTHER ANALYSIS ๏ผ”๏ผ“ 2.6. CONCLUSION ๏ผ”๏ผ• CHAPTER 3. Dynamic relationships between stocks and treasury bonds with spillover effects: Evidence from US financial markets ๏ผ”๏ผ˜ 3.1. INTRODUCTION ๏ผ”๏ผ˜ 3.2. LITERATURE REVIEW ๏ผ•๏ผ 3.3. DATA ๏ผ•๏ผ“ 3.4. METHODOLOGY AND RESULTS ๏ผ•๏ผ” 3.4.1. Univariate EGARCH (1,1)-M models ๏ผ•๏ผ” 3.4.2. Multivariate EGARCH (1,1)-M models ๏ผ•๏ผ– 3.5. CONCLUSIONS ๏ผ–๏ผ™ REFERENCES ๏ผ—๏ผ’ TABLES ๏ผ—9 FIGURES ๏ผ‘๏ผ‘๏ผ APPENDIX ๏ผ‘๏ผ“๏ผ• ABSTRACT IN KOREAN ๏ผ‘๏ผ”๏ผ’๋ฐ•

    ์ด์ค‘ ์ž…์ž ์˜์ƒํ™”์™€ ์‹œ์•ผ๊ฐ ํ™•๋Œ€๋ฅผ ํ†ตํ•œ ํšŒ์ „ ๋ณ€์กฐ ์ง‘์†๊ธฐ ์˜์ƒํ™” ๊ธฐ๋ฒ• ๊ฐœ์„ 

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์œตํ•ฉ๊ณผํ•™๊ธฐ์ˆ ๋Œ€ํ•™์› ์œตํ•ฉ๊ณผํ•™๋ถ€,2019. 8. ์˜ˆ์„ฑ์ค€.Rotational modulation collimator (RMC) is one of the radiation imaging techniques that make use of mechanical collimation, and it comprises a single detector placed behind two rotating collimator masks. This technique has the advantage of eliminating the need for position-sensitive radiation detectors, offering the possibility of reducing the system complexity and cost. However, the limitations of the existing RMC technique are that it 1) only has single-particle imaging and its 2) narrow field of view (FOV) is determined by the aspect ratio of the cylinder. The objective of this dissertation is to further investigate an RMC technique for localization of the radioactive materials, and it has mainly been improved along the following two viewpoints. First, dual-particle localization system was developed based on RMC coupled with a pulse shape discrimination (PSD) capable scintillator. The design parameters for RMC system were optimized using Monte Carlo (MC) simulations. To remove the 180ยฐ source ambiguity imposed by the conventional bilateral symmetric mask, a new slit and slat design of the mask was proposed. The method for estimating the location of radioactive materials was established using the maximum likelihood expectation maximization (MLEM) algorithm, and the imaging capability of the developed system was verified via measurement experiments. It offered an angular resolution 0.95ยฐ and FOV of 18ยฐ in the cross-sectional plane. Second, to overcome the limited FOV, a hemispherical collimator was developed to extend the FOV to approximately 2ฯ€. The design parameters were optimized using MC simulations, and MLEM algorithm was applied to estimate the radiation distribution. Experiments were conducted to evaluate the imaging capability of the system. The proposed hemispherical collimator was shown to be valid as designed and simulated, and it offered an FOV of 160ยฐ in the cross-sectional plane and an angular resolution of 10ยฐ. In conclusion, the RMC technique was improved from single particle localization to a dual-particle system, and method to extend the FOV approximately 2ฯ€ was proposed. If these functional improvements are applied to the RMC technique, it could realize more practical and useful applications in the field of radiation safety and nuclear security.ํšŒ์ „ ๋ณ€์กฐ ์ง‘์†๊ธฐ ๊ธฐ๋ฐ˜ ์˜์ƒํ™” ๊ธฐ์ˆ ์€ ๊ธฐ๊ณ„์  ์ง‘์†์„ ์ด์šฉํ•˜๋Š” ๊ธฐ๋ฒ• ์ค‘ ํ•˜๋‚˜๋กœ ๋‹จ์ผ ๊ฒ€์ถœ๊ธฐ ์•ž์—์„œ ๋™์‹œ์— ํšŒ์ „ํ•˜๋Š” ๋‘ ๊ฐœ์˜ ์ง‘์†๊ธฐ๋กœ ๊ตฌ์„ฑ๋œ๋‹ค. ์ด ๊ธฐ์ˆ ์€ ์œ„์น˜ ๋ฏผ๊ฐํ˜• ๊ฒ€์ถœ๊ธฐ๊ฐ€ ํ•„์š” ์—†๊ธฐ ๋•Œ๋ฌธ์— ์‹œ์Šคํ…œ์˜ ๋ณต์žก์„ฑ๊ณผ ๋น„์šฉ์„ ์ค„์ผ ์ˆ˜ ์žˆ๋Š” ์žฅ์ ์ด ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๊ธฐ์กด์˜ ํšŒ์ „ ๋ณ€์กฐ ์ง‘์†๊ธฐ ๊ธฐ๋ฒ•์€ ๋‹จ์ผ ์ž…์ž ์˜์ƒํ™”๋งŒ ๊ฐ€๋Šฅํ•˜์˜€๊ณ , ์›๊ธฐ๋‘ฅ ํ˜•ํƒœ์˜ ๊ตฌ์กฐ๋กœ ์ธํ•ด ์‹œ์•ผ๊ฐ์ด ์ข์€ ํ•œ๊ณ„์ ์ด ์žˆ์—ˆ๋‹ค. ๋ณธ ํ•™์œ„๋…ผ๋ฌธ์€ ํšŒ์ „ ๋ณ€์กฐ ์ง‘์†๊ธฐ ๊ธฐ๋ฒ•์— ๋Œ€ํ•œ ์ถ”๊ฐ€์ ์ธ ํƒ๊ตฌ๋ฅผ ๋ชฉํ‘œ๋กœ ํ•˜์—ฌ, ํฌ๊ฒŒ ๋‘ ๊ฐ€์ง€ ์ธก๋ฉด์—์„œ ํšŒ์ „ ๋ณ€์กฐ ์ง‘์†๊ธฐ ์˜์ƒํ™” ๊ธฐ๋ฒ•์„ ๊ฐœ์„ ํ•˜์˜€๋‹ค. ๊ทธ ์ฒซ ๋ฒˆ์งธ ์—ฐ๊ตฌ ๋‚ด์šฉ์œผ๋กœ์„œ, ํšŒ์ „ ๋ณ€์กฐ ์ง‘์†๊ธฐ ๊ธฐ๋ฒ•์— ์‹ ํ˜ธ ํŒŒํ˜• ๊ตฌ๋ถ„๋ฒ•์ด ์ ์šฉ ๊ฐ€๋Šฅํ•œ ์„ฌ๊ด‘ ๊ณ„์ธก๊ธฐ๋ฅผ ์ ‘๋ชฉํ•˜์—ฌ ์ค‘์„ฑ์ž์™€ ๊ฐ๋งˆ์„ ์„ ๋™์‹œ์— ํƒ์ง€ํ•  ์ˆ˜ ์žˆ๋Š” ์ด์ค‘์ž…์ž ์œ„์น˜ ์ถ”์ • ์‹œ์Šคํ…œ์„ ๊ณ„๋ฐœํ•˜์˜€๋‹ค. ๋ชฌํ…Œ ์นด๋ฅผ๋กœ ์ „์‚ฐ ๋ชจ์‚ฌ๋ฅผ ์ด์šฉํ•˜์—ฌ ์„ค๊ณ„ ํŒŒ๋ผ๋ฏธํ„ฐ๋ฅผ ์ตœ์ ํ™”ํ•˜์˜€๊ณ , ๊ธฐ์กด์˜ ์ขŒ์šฐ ๋Œ€์นญํ˜•ํƒœ์˜ ์ง‘์†๊ธฐ ๊ตฌ์กฐ๊ฐ€ ๊ฐ€์ง€๋Š” 180ยฐ ๋Œ€์นญ ์œ„์น˜์˜ ์„ ์› ์ถ”์ • ๋ชจํ˜ธ์„ฑ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด์„œ ์ƒˆ๋กœ์šด ๋น„๋Œ€์นญํ˜• ์ง‘์†๊ธฐ๋ฅผ ์ œ์•ˆํ•˜์˜€๋‹ค. ๋ฐฉ์‚ฌ์„ฑ ๋ฌผ์งˆ์˜ ์œ„์น˜ ์ถ”์ •์„ ์œ„ํ•ด์„œ ์ตœ๋Œ€ ์šฐ๋„ ์ถ”์ • ๊ธฐ๋Œ“๊ฐ’ ๊ทน๋Œ€ํ™” ๊ธฐ๋ฒ•์— ๊ธฐ๋ฐ˜ํ•œ ์˜์ƒ ์žฌ๊ตฌ์„ฑ ๋ฐฉ๋ฒ•๋ก ์„ ํ™•๋ฆฝํ•˜์˜€๊ณ , ๊ฐœ๋ฐœ๋œ ์žฅ๋น„์˜ ์˜์ƒํ™” ๋Šฅ๋ ฅ์€ ์ธก์ • ์‹คํ—˜์„ ํ†ตํ•ด ๊ฒ€์ฆ๋˜์—ˆ๋‹ค. ๊ฐœ๋ฐœ๋œ ์ด์ค‘์ž…์ž ์œ„์น˜ ์ถ”์ • ์‹œ์Šคํ…œ์˜ ๊ฐ ๋ถ„ํ•ด๋Šฅ์€ 0.95ยฐ ์ด๊ณ , ์‹œ์•ผ๊ฐ์€ ์‹œ์Šคํ…œ์˜ ํšก๋‹จ๋ฉด์„ ๊ธฐ์ค€์œผ๋กœ 18ยฐ ์ด๋‹ค. ๋‘ ๋ฒˆ์งธ ์—ฐ๊ตฌ ๋‚ด์šฉ์œผ๋กœ์„œ, ์ผ๋ฐ˜์ ์ธ ํšŒ์ „ ๋ณ€์กฐ ์ง‘์†๊ธฐ ๋””์ž์ธ์˜ ์ข์€ ์‹œ์•ผ๊ฐ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ๋ฐ˜๊ตฌ ํ˜•ํƒœ์˜ ์ง‘์†๊ธฐ ๋””์ž์ธ์„ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ๋ชฌํ…Œ ์นด๋ฅผ๋กœ ์ „์‚ฐ ๋ชจ์‚ฌ๋ฅผ ์ด์šฉํ•˜์—ฌ ์„ค๊ณ„ ํŒŒ๋ผ๋ฏธํ„ฐ๋ฅผ ์ตœ์ ํ™”ํ•˜์˜€๊ณ , ์ตœ๋Œ€ ์šฐ๋„ ์ถ”์ • ๊ธฐ๋Œ“๊ฐ’ ๊ทน๋Œ€ํ™” ๊ธฐ๋ฒ•์— ๊ธฐ๋ฐ˜ํ•œ ์˜์ƒ ์žฌ๊ตฌ์„ฑ ๋ฐฉ๋ฒ•๋ก ์„ ์ ์šฉํ•˜์—ฌ ๋ฐฉ์‚ฌ์„ฑ ๋ฌผ์งˆ์˜ ๋ถ„ํฌ๋ฅผ ์ถ”์ •ํ•˜์˜€๋‹ค. ์‹œ์Šคํ…œ์˜ ์˜์ƒํ™” ๋Šฅ๋ ฅ์„ ํ‰๊ฐ€ํ•˜๊ธฐ ์œ„ํ•ด ์ธก์ • ์‹คํ—˜์„ ์ˆ˜ํ–‰ํ•˜์˜€์œผ๋ฉฐ, ๊ฐœ๋ฐœ๋œ ๋ฐ˜๊ตฌํ˜• ํšŒ์ „ ๋ณ€์กฐ ์ง‘์†๊ธฐ๋Š” ์„ค๊ณ„๋˜๊ณ  ์‹œ๋ฎฌ๋ ˆ์ด์…˜๋œ ๊ฒƒ์ฒ˜๋Ÿผ ์œ ํšจํ•œ ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์‹œ์Šคํ…œ์˜ ์‹œ์•ผ๊ฐ์€ ํšก๋‹จ๋ฉด์„ ๊ธฐ์ค€์œผ๋กœ 160ยฐ ์ด๊ณ  ๊ฐ ๋ถ„ํ•ด๋Šฅ์€ 10ยฐ ์ด๋‹ค. ๊ฒฐ๋ก ์ ์œผ๋กœ, ๋ณธ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ํšŒ์ „ ๋ณ€์กฐ ์ง‘์†๊ธฐ ๊ธฐ๋ฒ•์€ ์ด์ค‘์ž…์ž ์œ„์น˜ ์ถ”์ • ์‹œ์Šคํ…œ์œผ๋กœ ๊ฐœ์„ ๋˜์—ˆ์œผ๋ฉฐ, ์‹œ์•ผ๊ฐ์„ ์•ฝ 2ฯ€ ์˜์—ญ๊นŒ์ง€ ํ™•์žฅ์‹œํ‚ฌ ์ˆ˜ ์žˆ๋Š” ๋ฐฉ๋ฒ•์ด ์ œ์•ˆ๋˜์—ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๊ฐœ์„ ์ ์ด ํšŒ์ „ ๋ณ€์กฐ ์ง‘์†๊ธฐ ๊ธฐ๋ฒ•์— ์ ์šฉ๋œ๋‹ค๋ฉด ํšŒ์ „ ๋ณ€์กฐ ์ง‘์†๊ธฐ ๊ธฐ๋ฐ˜ ์˜์ƒํ™” ์‹œ์Šคํ…œ์ด ๋ฐฉ์‚ฌ์„  ์•ˆ์ „ ๋ฐ ํ•ต์•ˆ๋ณด ๋ถ„์•ผ์—์„œ ๋ณด๋‹ค ์‹ค์šฉ์ ์ด๊ณ  ์œ ์šฉํ•˜๊ฒŒ ํ™œ์šฉ๋  ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋ผ ๊ธฐ๋Œ€ํ•œ๋‹ค.Chapter 1. Introduction 1 1.1. Image-based Radioactive Material Detection Technique 2 1.1.1. Mechanical Collimation Method 3 1.1.2. Electrical Collimation Method 6 1.2. RMC Imaging System 9 1.2.1. Basic Principle of the RMC Imager 11 1.2.2. Previous Studies of the RMC Technique 15 1.2.3. Limitation of Previous Studies and Motivation 18 1.3. Purpose of this Work and Contributions 20 Chapter 2. Dual-particle Localization System based on RMC Technique 21 2.1. Characterization of the CLYC Detector 22 2.1.1. Description of the CLYC Detector System 22 2.1.2. Simulation and Experiments on the Gamma-ray Detection 25 2.1.3. Simulation and Experiments on Neutron Detection 38 2.2. RMC System Design 48 2.2.1. Structural Design of RMC System 48 2.2.2. Optimization of Collimator Mask Design 50 2.2.3. Fabrication of RMC Components 67 2.3. Image Reconstruction 74 2.3.1. MLEM based Reconstruction Algorithm 74 2.3.2. Analytical Model of RMC System 77 2.4. Evaluation of the Imaging Capability 82 2.4.1. Data Acquisition and Image Reconstruction 82 2.4.2. Localization of Gamma-ray Sources 84 2.4.3. Localization of Neutron/Gamma-ray Sources 94 2.5. Additional Considerations for Practical Applications 98 Chapter 3. Extension of the Field of View for RMC System 107 3.1. Hemispherical RMC System Design 108 3.1.1. Optimization of Collimator Mask Design 108 3.1.2. Spectroscopic and Mechanical Performance 115 3.2. Evaluation of the Imaging Capability 119 3.2.1. Data Acquisition and Image Reconstruction 119 3.2.2. Localization of Single Gamma-ray Source 121 3.2.3. Localization of Double Gamma-ray Sources 126 3.2.4. Localization of Complex Gamma-ray Environment 132 3.2.5. Imaging Dynamic Range 136 3.3. Additional Considerations for Practical Applications 140 Chapter 4. Conclusion 148 REFERENCES 150Docto

    XPO1-dependent nuclear export is a druggable vulnerability in KRAS-mutant lung cancer

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    The common participation of oncogenic KRAS proteins in many of the most lethal human cancers, together with the ease of detecting somatic KRAS mutant alleles in patient samples, has spurred persistent and intensive efforts to develop drugs that inhibit KRAS activity. However, advances have been hindered by the pervasive inter- and intra-lineage diversity in the targetable mechanisms that underlie KRAS-driven cancers, limited pharmacological accessibility of many candidate synthetic-lethal interactions and the swift emergence of unanticipated resistance mechanisms to otherwise effective targeted therapies. Here we demonstrate the acute and specific cell-autonomous addiction of KRAS-mutant non-small-cell lung cancer cells to receptor-dependent nuclear export. A multi-genomic, data-driven approach, utilizing 106 human non-small-cell lung cancer cell lines, was used to interrogate 4,725 biological processes with 39,760 short interfering RNA pools for those selectively required for the survival of KRAS-mutant cells that harbour a broad spectrum of phenotypic variation. Nuclear transport machinery was the sole process-level discriminator of statistical significance. Chemical perturbation of the nuclear export receptor XPO1 (also known as CRM1), with a clinically available drug, revealed a robust synthetic-lethal interaction with native or engineered oncogenic KRAS both in vitro and in vivo. The primary mechanism underpinning XPO1 inhibitor sensitivity was intolerance to the accumulation of nuclear IฮบBฮฑ (also known as NFKBIA), with consequent inhibition of NFฮบB transcription factor activity. Intrinsic resistance associated with concurrent FSTL5 mutations was detected and determined to be a consequence of YAP1 activation via a previously unappreciated FSTL5-Hippo pathway regulatory axis. This occurs in approximately 17% of KRAS-mutant lung cancers, and can be overcome with the co-administration of a YAP1-TEAD inhibitor. These findings indicate that clinically available XPO1 inhibitors are a promising therapeutic strategy for a considerable cohort of patients with lung cancer when coupled to genomics-guided patient selection and observation.ope

    Mode of action and pharmacogenomic biomarkers for exceptional responders to didemnin B

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    Modern cancer treatment employs many effective chemotherapeutic agents originally discovered from natural sources. The cyclic depsipeptide didemnin B has demonstrated impressive anticancer activity in preclinical models. Clinical use has been approved but is limited by sparse patient responses combined with toxicity risk and an unclear mechanism of action. From a broad-scale effort to match antineoplastic natural products to their cellular activities, we found that didemnin B selectively induces rapid and wholesale apoptosis through dual inhibition of PPT1 and EEF1A1. Furthermore, empirical discovery of a small panel of exceptional responders to didemnin B allowed the generation of a regularized regression model to extract a sparse-feature genetic biomarker capable of predicting sensitivity to didemnin B. This may facilitate patient selection in a fashion that could enhance and expand the therapeutic application of didemnin B against neoplastic disease.ope

    High-throughput identification of protein functional similarities using a gene-expression-based siRNA screen

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    A gene expression-based siRNA screen was used to evaluate functional similarity between genetic perturbations to identify functionally similar proteins. A siRNA library (siGenome library, Dharmacon) consisting of multiple siRNAs per gene that have been pooled in to one well per gene was arrayed in a 384-well format and used to individually target 14,335 proteins for depletion in HCT116 colon cancer cells. For each protein depletion, the gene expression of eight genes was quantified using the multiplexed Affymetrix Quantigene 2.0 assay in technical triplicate. As a proof of concept, six genes (BNIP3, NDRG1, ALDOC, LOXL2, ACSL5, BNIP3L) whose expression pattern reliably reflect the disruption of the molecular scaffold KSR1 were measured upon each protein depletion. The remaining two genes (PPIB and HPRT) are housekeeping genes used for normalization. The gene expression signatures from this screen can be used to estimate the functional similarity between any two proteins and successfully identified functional relationships for specific proteins such as KSR1 and more generalized processes, such as autophagy.ope

    Systematic Identification of Molecular Subtype-Selective Vulnerabilities in Non-Small-Cell Lung Cancer

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    Context-specific molecular vulnerabilities that arise during tumor evolution represent an attractive intervention target class. However, the frequency and diversity of somatic lesions detected among lung tumors can confound efforts to identify these targets. To confront this challenge, we have applied parallel screening of chemical and genetic perturbations within a panel of molecularly annotated NSCLC lines to identify intervention opportunities tightly linked to molecular response indicators predictive of target sensitivity. Anchoring this analysis on a matched tumor/normal cell model from a lung adenocarcinoma patient identified three distinct target/response-indicator pairings that are represented with significant frequencies (6โ€“16%) in the patient population. These include NLRP3 mutation/inflammasome activation-dependent FLIP addiction, co-occuring KRAS and LKB1 mutation-driven COPI addiction, and selective sensitivity to a synthetic indolotriazine that is specified by a 7-gene expression signature. Target efficacies were validated in vivo, and mechanism of action studies uncovered new cancer cell biology.ope

    A noncomplementation screen for quantitative trait alleles in saccharomyces cerevisiae

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    Both linkage and linkage disequilibrium mapping provide well-defined approaches to mapping quantitative trait alleles. However, alleles of small effect are particularly difficult to refine to individual genes and causative mutations. Quantitative noncomplementation provides a means of directly testing individual genes for quantitative trait alleles in a fixed genetic background. Here, we implement a genome-wide noncomplementation screen for quantitative trait alleles that affect colony color or size by using the yeast deletion collection. As proof of principle, we find a previously known allele of CYS4 that affects colony color and a novel allele of CTT1 that affects resistance to hydrogen peroxide. To screen nearly 4700 genes in nine diverse yeast strains, we developed a high-throughput robotic plating assay to quantify colony color and size. Although we found hundreds of candidate alleles, reciprocal hemizygosity analysis of a select subset revealed that many of the candidates were false positives, in part the result of background-dependent haploinsufficiency or second-site mutations within the yeast deletion collection. Our results highlight the difficulty of identifying small-effect alleles but support the use of noncomplementation as a rapid means of identifying quantitative trait alleles of large effect.ope

    Computational detection and suppression of sequence-specific off-target phenotypes from whole genome RNAi screens

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    A challenge for large-scale siRNA loss-of-function studies is the biological pleiotropy resulting from multiple modes of action of siRNA reagents. A major confounding feature of these reagents is the microRNA-like translational quelling resulting from short regions of oligonucleotide complementarity to many different messenger RNAs. We developed a computational approach, deconvolution analysis of RNAi screening data, for automated quantitation of off-target effects in RNAi screening data sets. Substantial reduction of off-target rates was experimentally validated in five distinct biological screens across different genome-wide siRNA libraries. A public-access graphical-user-interface has been constructed to facilitate application of this algorithm.ope

    A Study on the Marine Scientific Research of International Cooperation in Northeast Asian Seas

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    ํ•ด์–‘๋ฒ•ํ˜‘์•ฝ์€ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ(Marine Scientific Research)์— ๊ด€ํ•œ ์ •์˜ ๊ทœ์ •์„ ๋‘๊ณ  ์žˆ์ง€ ์•Š๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ๋Š” ๋‹ค์–‘ํ•œ ๋ชฉ์ ์œผ๋กœ ์ˆ˜ํ–‰๋˜๋ฉฐ ํ•ด์–‘์ž์›์˜ ํ•ฉ๋ฆฌ์ ์ธ ๊ฐœ๋ฐœ์„ ์œ„ํ•œ ๊ธฐ๋ณธ์ ์ธ ์กฐ๊ฑด์ด๋‹ค. ์ด๋Ÿฌํ•œ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ๋Š” ํ•ด์–‘๋ฌผ๋ฆฌํ•™, ํ•ด์–‘ํ™”ํ•™, ํ•ด์–‘์ƒ๋ฌผํ•™, ํ•ด์–‘์ง€์งˆํ•™ ๋ฐ ์ง€๊ตฌ๋ฌผ๋ฆฌํ•™ ๋“ฑ ํ•ด์–‘ํ™˜๊ฒฝ์˜ ์ž์—ฐ ํ˜„์ƒ์— ๊ด€ํ•œ ๊ณผํ•™์  ์ง€์‹์˜ ์ฆ์ง„์„ ๋ชฉ์ ์œผ๋กœ ํ•ด์–‘ ๋ฐ ์—ฐ์•ˆ ์ˆ˜์—ญ์—์„œ ๊ธฐ์ดˆ์ž๋ฃŒ๋ฅผ ์ˆ˜์ง‘ํ•˜๊ณ  ๊ทธ๊ฒƒ์„ ๋ถ„์„ํ•˜๋Š” ์‹คํ—˜์ ์ธ ์ž‘์—…์ด๋ผ๊ณ  ํ•  ์ˆ˜ ์žˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์šฐ๋ฆฌ๋‚˜๋ผ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ๋ฒ• ์ œ2์กฐ ์ œ1ํ•ญ์—์„œ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ๋ผ ํ•จ์€ โ€œํ•ด์–‘์˜ ์ž์—ฐํ˜„์ƒ์„ ๊ตฌ๋ช…ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ํ•ด์ €๋ฉด ยท ํ•˜์ธตํ†  ยท ์ƒ๋ถ€์ˆ˜์—ญ ๋ฐ ์ธ์ ‘ ๋Œ€๊ธฐ๋ฅผ ๋Œ€์ƒ์œผ๋กœ ํ•˜๋Š” ์กฐ์‚ฌ ๋˜๋Š” ํƒ์‚ฌ ๋“ฑ์˜ ํ–‰์œ„โ€๋ผ๊ณ  ๊ทœ์ •ํ•˜๊ณ  ์žˆ๋‹ค. ๊ฒฐ๊ตญ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ๋Š” ๊ณผํ•™์  ์ง€์‹์˜ ์ฆ์ง„์„ ํ†ตํ•ด ์ธ๋ฅ˜์˜ ์‚ถ์„ ๋”์šฑ ํ’์š”๋กญ๊ฒŒ ๋งŒ๋“ค๊ธฐ ์œ„ํ•œ ๊ฒƒ์ด๋‹ค. ํ•˜์ง€๋งŒ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ์—์„œ ๋‚˜์˜ค๋Š” ์—ฌ๋Ÿฌ ๊ฐ€์ง€ ์ž๋ฃŒ๋“ค์€ ์ƒ์—… ๋ฐ ๊ตฐ์‚ฌ์  ์ด์šฉ ๊ฐ€์น˜๊ฐ€ ๋†’๊ณ  ๋˜ํ•œ ์ˆœ์ˆ˜ํ•œ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ๋กœ ํ–‰ํ•ด์ง„๋‹ค ํ•˜๋”๋ผ๋„ ๊ทธ ์ž๋ฃŒ๋“ค์ด ์ƒ์—…์ ์ด๊ณ  ํ˜น์€ ๊ตฐ์‚ฌ์ ์ธ ์ž๋ฃŒ๋กœ์จ ์ด์šฉ๋  ๊ฐ€๋Šฅ์„ฑ์ด ์กด์žฌํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ์ด์œ ๋กœ ์ธํ•˜์—ฌ ๋งŽ์€ ๋‚˜๋ผ๋“ค์ด ์ž๊ตญ์˜ ๊ด€ํ• ๊ถŒ์ด ๋ฏธ์น˜๋Š” ํ•ด์—ญ์— ๋Œ€ํ•œ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ๋ฅผ ๊บผ๋ คํ•˜๊ณ  ์žˆ์œผ๋ฉฐ ํŠนํžˆ ํ•ด์–‘๊ฒฝ๊ณ„๊ฐ€ ํš์ •๋˜์ง€ ์•Š๋Š” ์ˆ˜์—ญ์—์„œ์˜ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ๋Š” ๊ตฐ์‚ฌ์  ์กฐ์น˜๋ฅผ ๋ฐœ์ƒ์‹œํ‚ค๊ธฐ๋„ ํ•œ๋‹ค. ์œ ์—”ํ•ด์–‘๋ฒ•ํ˜‘์•ฝ์—์„œ๋Š” ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ์˜ ์ˆ˜ํ–‰, ์ฆ์ง„ ๋ฐ ์ดํ–‰์›์น™์— ๋Œ€ํ•ด์„œ ๋ฐํ˜€๋†“์•˜์œผ๋‚˜ ์ด๊ฒƒ์€ ์ผ๋ฐ˜์›์น™๋“ค์ด๊ณ , ํŠนํžˆ ๋Œ€๋ฅ™๋ถ• ๋ฐ ๋ฐฐํƒ€์ ๊ฒฝ์ œ์ˆ˜์—ญ์—์„œ์˜ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ๋Š” ๋Œ€๋ถ€๋ถ„ ์—ฐ์•ˆ๊ตญ์˜ ์žฌ๋Ÿ‰๊ถŒ์— ์˜ํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ์‹ค์ •์—์„œ ๋Œ€๋ฅ™๋ถ•์—์„œ์˜ ์ž์› ํƒ์‚ฌ๋“ฑ ๊ฐ์ข… ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ๋ฅผ ์ด์šฉํ•˜๋Š” ์‚ฌ๋ก€๋“ค์ด ์ฆ๊ฐ€ํ•˜์ž ์—ฐ์•ˆ๊ตญ๋“ค์˜ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ๋ฅผ ๊บผ๋ คํ•˜๋Š” ๋ถ„์œ„๊ธฐ๋Š” ํ™•์‚ฐ๋˜๊ณ  ์žˆ๋‹ค. ํŠนํžˆ ์šฐ๋ฆฌ๋‚˜๋ผ๊ฐ€ ์œ„์น˜ํ•œ ๋™๋ถ์•„ ์ง€์—ญ์€ ์ค‘๊ตญ๊ณผ ์ผ๋ณธ๊ณผ์˜ ๊ฑฐ๋ฆฌ๊ฐ€ 400ํ•ด๋ฆฌ๊ฐ€ ๋˜์ง€ ์•Š์€ ์ƒํƒœ์—์„œ ํ•ด์–‘๊ฒฝ๊ณ„๊ฐ€ ํš์ •๋˜์ง€ ์•Š์€ ์ƒํ™ฉ์ด๋‹ค. ํ•œ๊ตญ, ์ค‘๊ตญ, ์ผ๋ณธ์ด ๊ฐ๊ฐ ์ฃผ์žฅํ•˜๋Š” ํ•ด์–‘๊ฒฝ๊ณ„ํš์ •์˜ ๊ธฐ์ค€์ด ์ƒ์ดํ•˜์—ฌ ์‚ผ๊ตญ์ด ์ฃผ์žฅํ•˜๋Š” ๊ฒฝ๊ณ„์„ ์—์„œ ์ค‘์ฒฉ ์ˆ˜์—ญ์ด ์ƒ๊ฒจ๋‚ฌ์œผ๋ฉฐ ํ•ด๋‹น ์ค‘์ฒฉ์ˆ˜์—ญ์— ๋Œ€ํ•œ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ๋Š” ์‚ผ๊ตญ์˜ ์ •์น˜์ ์ด๊ณ  ์™ธ๊ต์ ์ธ ๋ถ„์Ÿ์œผ๋กœ๊นŒ์ง€ ๋น„ํ™”๋˜๊ณ  ์žˆ๋‹ค. ์ด๋Š” ๋ฐฉ๋ฒ•์˜ ๋ฌธ์ œ๋กœ์„œ ์œ ์—”ํ•ด์–‘๋ฒ•ํ˜‘์•ฝ์˜ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ์— ๊ด€ํ•œ ๊ทœ์ •๊ณผ ๊ฐ๊ตญ์˜ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ๋ฒ• ๋“ฑ์— ๋”ฐ๋ผ์„œ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ๋ฅผ ์‹œํ–‰ํ•œ๋‹ค๊ณ  ํ•˜์ง€๋งŒ ํ•œ์ค‘์ผ ์‚ผ๊ตญ์€ ์ค‘์ฒฉ ์ˆ˜์—ญ ์ฆ‰ ๋ฏธํš์ •๊ฒฝ๊ณ„์ˆ˜์—ญ์ด๋ผ ์ผ์ปฌ์–ด์ง€๋Š” ์ˆ˜์—ญ์—์„œ์˜ ์ •์น˜์ , ์™ธ๊ต์  ๋ฌธ์ œ๋กœ ๋ง๋ฏธ์•”์•„ ์ œ๋Œ€๋กœ ์ด๋ฃจ์–ด์ง€์ง€ ๋ชปํ•˜๊ณ  ์žˆ๋Š” ๊ฒƒ์ด๋‹ค. ์ธ๋ฅ˜์˜ ํ•ด์–‘์— ๋Œ€ํ•œ ๊ณผํ•™์  ์ง€์‹์˜ ์ฆ๋Œ€๋ผ๋Š” ๋ชฉ์ ๊ณผ ์ˆœ์ˆ˜ํ•˜๊ณ  ํ‰ํ™”์ ์ธ ๋ฐฉ๋ฒ•์œผ๋กœ ์‹ค์‹œ๋˜์–ด์•ผ ํ•˜๋Š” ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ์ž„์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ์ด๊ฒƒ์ด ์ •์น˜, ์™ธ๊ต์ ์ธ ๋ฐฉ๋ฒ•์œผ๋กœ ํ™œ์šฉ๋˜๊ณ  ์žˆ๋Š” ๊ฒƒ์ด ํ˜„์‹ค์ด๋ฏ€๋กœ ์‰ฝ๊ฒŒ ํ•ด๊ฒฐ๋  ์ˆ˜ ์žˆ๋Š” ๋ฌธ์ œ๋Š” ์•„๋‹๊ฒƒ์ด๋‹ค. ํ•˜์ง€๋งŒ ๊ฐˆ์ˆ˜๋ก ๋ณ€ํ™”ํ•˜๋Š” ์ง€๊ตฌํ™˜๊ฒฝ์†์—์„œ ํŠนํžˆ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ๋Š” ๋ฐ˜๋“œ์‹œ ์ˆ˜ํ–‰๋˜์–ด์•ผ ํ•˜๋Š” ๊ฒƒ์ด๋ฉฐ ๋™๋ถ์•„ ์‚ผ๊ตญ์€ ์„œ๋กœ ์ž๊ธฐ๋งŒ์˜ ์š•์‹ฌ์ด ์•„๋‹Œ ์ƒ์ƒ์˜ ๋ชฉ์ ์„ ์œ„ํ•˜์—ฌ ์ด๋Ÿฌํ•œ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ๋ฅผ ๋…๋ คํ•˜์—ฌ์•ผ ํ•  ๊ฒƒ์ด๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ๋ฌธ์ œ๊ฐ€ ๋˜๊ณ  ์žˆ๋Š” ๋™๋ถ์•„ ํ•ด์—ญ์—์„œ์˜ ์›ํ™œํ•œ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ๋ฅผ ์œ„ํ•˜์—ฌ ๋ฌธ์ œ์ ์„ ์งš๊ณ  ํ•ด๊ฒฐ ๋ฐฉ์•ˆ์„ ๋ชจ์ƒ‰ํ•ด๋ณด๊ณ ์ž ํ•œ๋‹ค.Abstract ็ฌฌไธ€็ซ  ๅบ ่ซ– 1 ์ œ1์ ˆ ์—ฐ๊ตฌ์˜ ๋ชฉ์  1 ์ œ2์ ˆ ์—ฐ๊ตฌ์˜ ๋ฒ”์œ„ ๋ฐ ๋ฐฉ๋ฒ• 3 ็ฌฌไบŒ็ซ  ๆตทๆด‹็ง‘ๅญธ่ชฟๆŸป์˜ ๆงชๅฟต 6 ์ œ1์ ˆ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ์ œ๋„์˜ ๋ฐœ๋‹ฌ ๊ณผ์ • 6 ์ œ2์ ˆ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ์˜ ์˜์˜ 10 1. ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ์˜ ์ •์˜ 10 2. ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ์ œ๋„์™€ ์œ ์‚ฌ๊ฐœ๋…์˜ ๋น„๊ต 13 ็ฌฌไธ‰็ซ  ๆตทๆด‹็ง‘ๅญธ่ชฟๆŸป์˜ ไธ€่ˆฌๅŽŸๅ‰‡๊ณผ ๅœ‹้š›ๅ”ๅŠ› 16 ์ œ1์ ˆ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ์˜ ์ดํ–‰, ์ฆ์ง„ ๋ฐ ์ผ๋ฐ˜์›์น™ 16 1. ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ์˜ ์ดํ–‰ 16 2. ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ์˜ ์ฆ์ง„ 17 3. ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ์˜ ์ดํ–‰์„ ์œ„ํ•œ ์ผ๋ฐ˜์›์น™ 17 ์ œ2์ ˆ ๋Œ€๋ฅ™๋ถ• ๋ฐ ๋ฐฐํƒ€์ ๊ฒฝ์ œ์ˆ˜์—ญ์—์„œ์˜ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ 21 1. ์—ฐ์•ˆ๊ตญ์˜ ๋™์˜๊ถŒ๊ณผ ์žฌ๋Ÿ‰๊ถŒ 21 2. ์กฐ์‚ฌ๊ตญ์˜ ์˜๋ฌด 33 3. 200ํ•ด๋ฆฌ ์ด์›์˜ ๋Œ€๋ฅ™๋ถ•์—์„œ์˜ ์กฐ์‚ฌํ™œ๋™ 38 4. ์กฐ์‚ฌํ™œ๋™์˜ ์ •์ง€ ๋ฐ ์ค‘์ง€ 39 ์ œ3์ ˆ ๊ธฐํƒ€ ์ˆ˜์—ญ์—์„œ์˜ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ 42 1. ๋‚ด์ˆ˜ ๋ฐ ์˜ํ•ด์—์„œ์˜ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ 42 2. ๊ณตํ•ด์—์„œ์˜ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ 43 3. ์‹ฌํ•ด์ €์—์„œ์˜ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ 44 ์ œ4์ ˆ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ๋ฅผ ์œ„ํ•œ ๊ตญ์ œํ˜‘๋ ฅ 45 1. ๊ตญ์ œํ˜‘๋ ฅ์˜ ์ฆ์ง„ 45 2. ์œ ๋ฆฌํ•œ ์กฐ๊ฑด ์กฐ์„ฑ 47 3. ์ •๋ณดยท์ง€์‹์˜ ๊ณต์œ ์™€ ๋ฐฐํฌ 48 ็ฌฌๅ››็ซ  ๆฑๅŒ—ไบž ไธป่ฆๅœ‹ๅฎถ์˜ ๆตทๆด‹็ง‘ๅญธ่ชฟๆŸปๆณ• 50 ์ œ1์ ˆ ์šฐ๋ฆฌ๋‚˜๋ผ ๋ฐ ์ธ์ ‘๊ตญ๊ฐ€์˜ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ๊ด€๋ จ ๋ฒ•๋ น 50 1. ํ•œ๊ตญ์˜ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ๋ฒ• 50 2. ์ผ๋ณธ์˜ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ๋ฒ• 53 3. ์ค‘๊ตญ์˜ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ๋ฒ• 55 ์ œ2์ ˆ ์ฃผ์š” ์ฐจ์ด์ ๊ณผ ์‹œ์‚ฌ์  58 ็ฌฌไบ”็ซ  ๅœ‹้š›็š„ ๅ”ๅŠ›้ซ”ๅˆถ์— ๊ด€ํ•œ ๆ”นๅ–„ๆ–นๆกˆ 61 ์ œ1์ ˆ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ์˜ ํ˜‘๋ ฅ์ฒด์ œ์˜ ๊ทผ๊ฑฐ 63 1. ์œ ์—”ํ•ด์–‘๋ฒ•ํ˜‘์•ฝ์ƒ ๊ตญ์ œํ˜‘๋ ฅ 64 2. ์œ ์—”ํ•ด์–‘๋ฒ•ํ˜‘์•ฝ์ƒ ํ˜‘๋ ฅ์˜๋ฌด 65 3. ๋ฐฐํƒ€์  ๊ฒฝ์ œ์ˆ˜์—ญ์—์„œ์˜ ์ƒ๋ฌผ์ž์›๋ณด์กด๊ณผ ๊ด€๋ จํ•œ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ์˜ ํ˜‘๋ ฅ์ฒด์ œ 66 4. ๋Œ€๋ฅ™๋ถ•์—์„œ ์žˆ์–ด์„œ์˜ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ์™€ ๊ด€๋ จํ•œ ํ˜‘๋ ฅ์ฒด์ œ 67 ์ œ2์ ˆ ํ˜„ํ–‰ ๋™๋ถ์•„ํ•ด์—ญ ๊ตญ์ œํ˜‘๋ ฅ์ฒด์ œ์™€ ํ•ด์™ธ์œ ์‚ฌ์ œ๋„ 69 1. ์–‘์ž๊ฐ„ ์–ด์—…ํ˜‘์ •์ƒ์˜ ๊ด€ํ–‰ 69 2. ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ์™€ ๊ด€๋ จํ•œ ์–‘์žํ˜‘์ •์ƒ์˜ ๊ด€ํ–‰ 74 3. ํ•œ ยท ์ค‘ ยท ์ผ์˜ ํ•ด์–‘๊ณผํ•™์กฐ์‚ฌ ๊ด€๋ จ๋ฒ•๊ทœ์ƒ์˜ ๊ด€ํ–‰ 75 4. ๋ฒ”์„ธ๊ณ„์  ๊ตญ์ œ๊ธฐ๊ตฌ์˜ ๋ฐœ์ „ 78 5. ์ง€์—ญ์  ๊ตญ์ œ๊ธฐ๊ตฌ์˜ ๋ฐœ์ „ 81 ์ œ3์ ˆ ๋™๋ถ์•„ํ•ด์—ญ์—์„œ์˜ ํ•ฉ๋ฆฌ์  ํ˜‘๋ ฅ์ฒด์ œ ๋ฐฉ์•ˆ 85 1. ํ•œ ยท ์ค‘ ยท ์ผ์˜ ๊ด€ํ–‰๋ถ„์„์„ ํ†ตํ•œ ํ˜‘๋ ฅ์ฒด์ œ 85 2. ๊ตญ์ œ๊ธฐ๊ตฌ์˜ ํ™œ์šฉ์„ ํ†ตํ•œ ํ˜‘๋ ฅ์ฒด์ œ 87 ็ฌฌ๏ง‘็ซ  ็ต ่ซ– 89 ๅƒ่€ƒๆ–‡็ป 9

    Meta-Analysis of Large-Scale Toxicogenomic Data Finds Neuronal Regeneration Related Protein and Cathepsin D to Be Novel Biomarkers of Drug-Induced Toxicity

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    Undesirable toxicity is one of the main reasons for withdrawing drugs from the market or eliminating them as candidates in clinical trials. Although numerous studies have attempted to identify biomarkers capable of predicting pharmacotoxicity, few have attempted to discover robust biomarkers that are coherent across various species and experimental settings. To identify such biomarkers, we conducted meta-analyses of massive gene expression profiles for 6,567 in vivo rat samples and 453 compounds. After applying rigorous feature reduction procedures, our analyses identified 18 genes to be related with toxicity upon comparisons of untreated versus treated and innocuous versus toxic specimens of kidney, liver and heart tissue. We then independently validated these genes in human cell lines. In doing so, we found several of these genes to be coherently regulated in both in vivo rat specimens and in human cell lines. Specifically, mRNA expression of neuronal regeneration-related protein was robustly down-regulated in both liver and kidney cells, while mRNA expression of cathepsin D was commonly up-regulated in liver cells after exposure to toxic concentrations of chemical compounds. Use of these novel toxicity biomarkers may enhance the efficiency of screening for safe lead compounds in early-phase drug development prior to animal testing.ope
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