195 research outputs found

    ์ด์ฃผ๊ฐ€ ์‹ ๋ขฐ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ : ๊ฐœ์ธ ๋ฐ ๋‚˜๋ผ ๋‹จ์œ„ ๋ถ„์„์„ ์ค‘์‹ฌ์œผ๋กœ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์‚ฌํšŒ๊ณผํ•™๋Œ€ํ•™ ๊ฒฝ์ œํ•™๋ถ€, 2018. 2. ๊น€๋ณ‘์—ฐ.Albeit its importance, the relationship between migration/immigration and trust is relatively an unexplored subject in the social capital literature. Using a natural experimental setting of the German reunification, this dissertation sets out to analyze the effects of migration on trust and to address how trust is formed or destroyed. Chapters 1 and 2 investigate the impact of a shockโ€”either positive or negativeโ€”on trust, triggered by the German reunification. In these chapters, Germanys individual-level panel data, known as the German Socio-Economic Panel (SOEP), are utilized to examine whether East Germans trust increases upon exposure to Western environment. The regression results demonstrate that spending time in the West raises East German migrants trust, which supports the view that trust is molded through contemporaneous shocks or experiences, even for East Germans whose initial stock is low. The self-selection problem of choosing migration to the West is dealt with by employing the instrumental variable approach, the finding of which suggests the robustness of the aforementioned result. The second chapter focuses on the West Germans who experienced the aftermath of the fall of the Berlin Wall, investigating the persistence of a historical shock. Whether this mass migration had an impact on West Germans trust is examined through the use of the net migration rate in the early 1990s as a proxy for the shock. Results using the random effects estimator show that West Germans trust is negatively affected by the labor supply shock, but the persistent effect is only confined to the labor force participants at the time. The subsequent analysis using various subgroups finds that perceiving migrants as labor market competitors is a possible channel through which trust is negatively affected. In the final chapter, the impact of migration or immigrants on trust is explored at the country-level with a combined dataset that includes the World Values Surveys and the European Values Surveys, the UN Migration Stock dataset, and the World Banks World Development Indicators. The impact of migration is proxied by the countrys immigrant inflow which is further distinguished by immigrants countries of origin. In addition, an age-cohort panel is constructed to test whether labor market competition is a channel through which trust is formed. It is found that the immigrant inflow of unskilled immigrants is negatively associated with trust while the effect of the inflow of skilled immigrants is insignificant. In addition, the immigration shock received at prime-age is negatively correlated with trust, which implies that natives negative perception from the labor market competition is a possible link that explains the relationship.Introduction 9 I. Motivation 9 II. Authors Note 14 Chapter 1. The Effect of East-West Migration on East Germans Trust in Germanys Post-Reunification Era 19 1.1 Introduction 19 1.2 Historical Background: Internal Migration in Germany after Reunification 24 1.3 Literature Review 27 A. Social Capital of East and West Germans after Reunification 27 B. Selection-Bias of Migrants 28 C. Social Capital of Immigrants 30 1.4 Data and Variable Descriptions 31 1.5 Empirical Strategy 36 1.6 Regression Results 47 A. The Effect of Migration to the West 47 B. Possible Channel: Labor Market Returns 52 C. Robustness Check: Relaxing Sample Restrictions 55 D. Robustness Check: Additional Controls 57 1.7 Conclusion 60 References 62 Appendices 66 Chapter 2. The Impact of Mass Migration on West Germans Trust in the Reunified Germany 69 2.1 Introduction 69 2.2 Literature Review 72 A. Literature on Migration and Social Capital 72 B. The Impact of Exogenous Shocks on Social Capital Outcomes 74 C. The German Reunification as a Natural Experiment 76 2.3 Data and Variable Descriptions 77 2.4 Empirical Strategy 83 2.5 Regression Results 84 A. Baseline Regressions 84 B. Subgroup Analyses 92 C. A Cross-Sectional Approach 99 D. Effects by Skill and by Gender 101 E. Distinguishing between the Influx of Germans and that of Foreigners 103 2.6 Conclusion 107 References 109 Appendices 111 Chapter 3. Immigrants and Trust: A Country-Panel Data Analysis 118 3.1 Introduction 118 3.2 Related Literature 122 3.3 Data and Variable Descriptions 127 3.4 Regression Results 137 3.5 Robustness Checks 147 A. Controlling for Immigrants Countries of Origin 147 B. Alternative Proxy for Immigrants Skills 152 3.6 Conclusion 156 References 158 Appendices 160 Conclusion and Discussions 172 ๊ตญ๋ฌธ์ดˆ๋ก 178Docto

    ์ฃผ๋ฏผ ์ฒด๊ฐ์•ˆ์ „๋„ ๊ฒฐ์ •์š”์ธ์— ๊ด€ํ•œ ์—ฐ๊ตฌ('์‚ฌํšŒ ๋ฌด์งˆ์„œ'์™€ '์ง€์—ญ์‚ฌํšŒ ๊ฒฝ์ฐฐํ™œ๋™'์„ ์ค‘์‹ฌ์œผ๋กœ)

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ํ–‰์ •ํ•™๊ณผ, 2017. 2. ์ด์ˆ˜์˜.์ด ์—ฐ๊ตฌ๋Š” ๊ตญ๋‚ด์™ธ ์ฃผ์š”์—ฐ๊ตฌ์—์„œ ๋ฒ”์ฃ„์— ๋Œ€ํ•œ ๋‘๋ ค์›€ ๋“ฑ์œผ๋กœ ํ‘œํ˜„๋˜๋Š” ์ฒด๊ฐ์•ˆ์ „ ๋„์˜ ๊ฒฐ์ •์š”์ธ์— ๊ด€ํ•œ ์—ฐ๊ตฌ์ด๋‹ค. ์ฒด๊ฐ์•ˆ์ „๋„๋ฅผ ๊ฒฐ์ •ํ•˜๋Š” ์š”์ธ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋ฅผ ์œ„ํ•œ ์„ ํ–‰์—ฐ๊ตฌ ์ค‘ ๋ฒ”์ฃ„์˜ˆ๋ฐฉ ๋ฐ ํ†ต์ œ์— ๊ด€๋ จ๋œ ๋ฒ”์ฃ„ํ•™ ์ด๋ก ์„ ๋จผ์ € ์‚ดํŽด๋ณด์•˜๋‹ค. ์†Œ๊ทน์ โ€ค ์ ๊ทน์  ์ผ๋ฐ˜์˜ˆ๋ฐฉ์ด๋ก , ํŠน๋ณ„์˜ˆ๋ฐฉ์ด๋ก , ๊ตฌ์กฐ๋ชจ๋ธ๋ก , ๋ฒ”์ฃ„ํ”ผํ•ดํ™” ์ด๋ก ์„ ์‘์šฉํ•œ ๋ฒ”์ฃ„์˜ˆ ๋ฐฉ, ํ•ฉ๋ฆฌ์  ์„ ํƒ์ด๋ก ์— ๊ทผ๊ฑฐํ•œ ๋ฒ”์ฃ„ํ†ต์ œ์ „๋žต, ์ƒํ™ฉ์  ๋ฒ”์ฃ„์˜ˆ๋ฐฉ ๋“ฑ ๋‹ค์–‘ํ•œ ์ด๋ก ๋“ค์ด ํ˜„์žฌ๊นŒ์ง€ ์—ฐ๊ตฌ๋˜์–ด ์™”๋‹ค. ํŠนํžˆ, ์ด ์—ฐ๊ตฌ์—์„œ๋Š” 1982๋…„ ๋ฏธ๊ตญ์˜ ์‚ฌํšŒํ•™์ž James Q. Wilson๊ณผ ๋ฒ”์ฃ„ํ•™์ž George L. Kelling์ด Atlantic Monthly์— ๊ฒŒ์žฌํ•œ ๋…ผ๋ฌธ ใ€ŒBroken windowใ€์— ์˜ํ•˜์—ฌ ์ œ์ฐฝ๋œ ๊นจ์ง„ ์œ ๋ฆฌ์ฐฝ ์ด๋ก ์— ์ฃผ๋ชฉํ•˜์˜€๋‹ค. ํ•ด๋‹น ์ด๋ก ์€ ๊ณต๋™์ฒด ๋‚ด์˜ ์‚ฌ์†Œํ•œ ๋ฌด์งˆ์„œ๋ฅผ ๋ฐฉ์น˜ํ•˜๋Š” ๊ฒƒ์ด ๊ฒฐ๊ตญ ์‚ฌํšŒ์ „์ฒด์˜ ๋ฌด์งˆ์„œ๋กœ ํ™•๋Œ€๋˜์–ด ๋ฒ”์ฃ„๊ฐ€ ๋ฐœ์ƒํ•˜๊ฒŒ ๋˜๋ฏ€๋กœ ์ž‘์€ ๋ถˆ๋ฒ•โ€ค๋ฌด์งˆ์„œ๋ผ๋„ ๋‹จ์†ํ•˜๋Š” ๋“ฑ ์ ์ ˆํ•œ ์กฐ์น˜๋ฅผ ์ทจํ•ด์•ผ ํ•œ๋‹ค๊ณ  ์ฃผ์žฅํ–ˆ๋‹ค. ์•„์šธ๋Ÿฌ, ์ด ์—ฐ๊ตฌ์—์„œ ๋˜ํ•˜๋‚˜์˜ ์ด๋ก ์  ์ถ•์€ ์ง€์—ญ์‚ฌํšŒ ๊ฒฝ์ฐฐํ™œ๋™ ์ด๋ก ์ด ๋‹ค. ์˜ค๋Š˜ ๋‚ ์—๋Š” ๋ฒ”์ฃ„๋ฌธ์ œ ํ•ด๊ฒฐ์ด๋‚˜ ๋ฒ”์ฃ„์— ๋Œ€ํ•œ ๋‘๋ ค์›€ ํ•ด์†Œ๋ฅผ ์œ„ํ•ด ์ง€์—ญ์‚ฌํšŒ์™€ ๊ฒฝ์ฐฐ ๊ฐ„์˜ ๊ณต๋™ ๋…ธ๋ ฅ์ด ๊ฐ•์กฐ๋˜๋Š”๋ฐ, ์ด๋Ÿฌํ•œ ๋…ธ๋ ฅ์„ ์ผ๋ฐ˜์ ์œผ๋กœ ์นญํ•˜์—ฌ ์ง€์—ญ์‚ฌํšŒ ๊ฒฝ ์ฐฐํ™œ๋™(Community Policing)์ด๋ผ๊ณ  ๋ถ€๋ฅธ๋‹ค. ์ข€ ๋” ๋ถ€์—ฐํ•œ๋‹ค๋ฉด, ์ด๋Š” ๊ฒฝ์ฐฐ๊ณผ ์ง€์—ญ์‚ฌ ํšŒ ์ฃผ๋ฏผ ๊ฐ„์˜ ์นœ๋ฐ€ํ•œ ์†Œํ†ต์„ ํ† ๋Œ€๋กœ ๊ธด๋ฐ€ํ•œ ํ˜‘๋ ฅํ™œ๋™์„ ์‹ค์‹œํ•˜์—ฌ, ๋ฒ”์ฃ„, ๋ฌผ๋ฆฌ์ โ€ค์‚ฌ ํšŒ์  ๋ฌด์งˆ์„œ์— ๊ด€๋ จ๋œ ๋ฌธ์ œ ํ•ด๊ฒฐ์„ ํ–ฅํ•œ ์ƒˆ๋กœ์šด ๋ฐฉ๋ฒ•์„ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•˜๋Š” ๋ฒ”์ฃ„์˜ˆ๋ฐฉ ์ „ ๋žต์ด๋‹ค. ์ด ์—ฐ๊ตฌ์—์„œ๋Š” ์•ž์—์„œ ์–ธ๊ธ‰ํ•œ ๋‘ ๊ฐ€์ง€ ์ค‘์‹ฌ์ด๋ก ์„ ๋ฐ”ํƒ•์œผ๋กœ ํ•˜์—ฌ, ๋ฒ”์ฃ„๋‘๋ ค ์›€์— ๊ด€ํ•œ ์—ฐ๊ตฌ, ๋ฌด์งˆ์„œ์— ๊ด€ํ•œ ์—ฐ๊ตฌ, ์ฒด๊ฐ์•ˆ์ „๋„ ๊ฒฐ์ •์š”์ธ์— ๊ด€ํ•œ ๊ตญ๋‚ด์™ธ ์—ฌ๋Ÿฌ ์„  ํ–‰์—ฐ๊ตฌ๋ฅผ ํƒ๊ตฌํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ์ด๋ก ๊ณผ ์„ ํ–‰์—ฐ๊ตฌ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ํ•ด์„œ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ง€์—ญ์‚ฌํšŒ์˜ ๋ฌด์งˆ์„œ์™€ ์ง€์—ญ์‚ฌํšŒ ๊ฒฝ์ฐฐํ™œ๋™์— ๋Œ€ํ•œ ์ธ์‹์ด ์ฃผ๋ฏผ ์ฒด๊ฐ์•ˆ์ „๋„์— ์–ด๋– ํ•œ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š”๊ฐ€?๋ผ ๋Š” ์—ฐ๊ตฌ๋ฌธ์ œ๋ฅผ ์„ค์ •ํ•˜์˜€๋‹ค. ์ด ์—ฐ๊ตฌ๋ฌธ์ œ๋ฅผ ํƒ๊ตฌํ•˜๊ธฐ ์œ„ํ•ด์„œ ๋‹ค์Œ๊ณผ ๊ฐ™์ด ๋‘๊ฐ€์ง€์˜ ์ฃผ๋œ ๊ฐ€์„ค์„ ์„ค์ •ํ•˜๊ณ , ๊ฐ๊ฐ ์†Œ์ˆ˜์˜ ํ•˜์œ„๊ฐ€์„ค์„ ์ถ”๊ฐ€๋กœ ์„ค์ •ํ•˜์˜€๋‹ค. ๋จผ์ €, ๊ฐ€์„ค 1๋กœ ์„œ ๊ฑฐ์ฃผ ์ง€์—ญ์˜ ์งˆ์„œ ์ˆ˜์ค€์ด ๋†’๋‹ค๊ณ  ๋Š๋ผ๋Š” ์ฃผ๋ฏผ์ผ์ˆ˜๋ก ์ฒด๊ฐ์•ˆ์ „๋„๊ฐ€ ๋†’์„ ๊ฒƒ์ด ๋‹ค. ๋ผ๋Š” ๊ฐ€์„ค์„ ์„ค์ •ํ•˜์˜€๋‹ค. ์ง€์—ญ์‚ฌํšŒ์˜ ๋ฌด์งˆ์„œ ์ˆ˜์ค€์€ ์ง€์—ญ์‚ฌํšŒ์˜ ์งˆ์„œ ์ค€์ˆ˜ ์ˆ˜ ์ค€๊ณผ ์ƒ๋ฐ˜๋œ ๊ฐœ๋…์œผ๋กœ ์ง€์—ญ ์‚ฌํšŒ์˜ ์งˆ์„œ ์ค€์ˆ˜ ์ˆ˜์ค€์ด ๋†’์„์ˆ˜๋ก ์‚ฌํšŒ ๋ฌด์งˆ์„œ์˜ ์ •๋„ ๊ฐ€ ๋‚ฎ์Œ์„, ์ง€์—ญ์‚ฌํšŒ์˜ ์งˆ์„œ ์ค€์ˆ˜ ์ˆ˜์ค€์ด ๋‚ฎ์„์ˆ˜๋ก ์‚ฌํšŒ ๋ฌด์งˆ์„œ ์ •๋„๊ฐ€ ๋†’์Œ์„ ์˜ ๋ฏธํ•  ๊ฒƒ์œผ๋กœ ๊ฐ€์ •ํ•˜์˜€๋‹ค. ๋‘ ๋ฒˆ์งธ, ๊ฐ€์„ค 2๋กœ์„œ ๊ฑฐ์ฃผ ์ง€์—ญ์— ์ง€์—ญ์‚ฌํšŒ ๊ฒฝ์ฐฐํ™œ๋™์ด ์ ๊ทน์ ์œผ๋กœ ์ด๋ฃจ์–ด์ง€๊ณ  ์žˆ๋‹ค๊ณ  ๋Š๋ผ๋Š” ์ฃผ๋ฏผ์ผ์ˆ˜๋ก ์ฒด๊ฐ์•ˆ์ „๋„๊ฐ€ ๋†’์„ ๊ฒƒ์ด๋‹ค.๋ผ๋Š” ๊ฐ€์„ค์„ ์„ค์ •ํ•˜์˜€๋‹ค. ๋ฏธ๊ตญ์€ ์ง€์—ญ์‚ฌํšŒ ๊ฒฝ์ฐฐํ™œ๋™(Community-Oriented Policing)์ด ํšจ ๊ณผ์ ์ด์—ˆ๋Š”์ง€ ๊ธฐ์กด ์—ฐ๊ตฌ์ €๋„๋“ค์— ๋Œ€ํ•œ ๋ฉ”ํƒ€๋ถ„์„์„ ํ†ตํ•ด ํ™•์ธํ•˜๊ณ  ์žˆ์œผ๋‚˜, ์šฐ๋ฆฌ๋‚˜๋ผ ์—์„œ๋Š” ์ง€์—ญ์‚ฌํšŒ ๊ฒฝ์ฐฐํ™œ๋™์— ๋Œ€ํ•œ ํšจ๊ณผ์„ฑ ๋ถ„์„์€ ํ˜„์žฌ๊นŒ์ง€ ์ œ๋Œ€๋กœ ์ด๋ฃจ์–ด์ง€์ง€ ์•Š๊ณ  ์žˆ๋‹ค๊ณ  ๋ณด์—ฌ์ง€๋ฏ€๋กœ, ๋ณธ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ์ง€์—ญ์‚ฌํšŒ ๊ฒฝ์ฐฐํ™œ๋™ ์ˆ˜์ค€์— ๋”ฐ๋ฅธ ์ฒด๊ฐ์•ˆ์ „๋„ ๋ณ€ ํ™”๋ฅผ ์ธก์ •ํ•จ์œผ๋กœ์จ ๊ฐ„์ ‘์ ์œผ๋กœ ์ง€์—ญ์‚ฌํšŒ ๊ฒฝ์ฐฐํ™œ๋™์˜ ํšจ๊ณผ์„ฑ ๋ถ„์„๋„ ์‹œ๋„ํ•˜๊ณ ์ž ํ•˜ ์˜€๋‹ค. ๊ฐ€์„ค์„ ๊ฒ€์ •ํ•˜๊ธฐ ์œ„ํ•ด์„œ ์ฃผ๋ฏผ๋“ค์˜ ์ฒด๊ฐ์•ˆ์ „๋„๋ฅผ ์ข…์†๋ณ€์ˆ˜๋กœ ํ™œ์šฉํ•˜๊ณ ์ž ํ•œ๋‹ค. ์ฒด๊ฐ์•ˆ์ „๋„ ์ ์ˆ˜๋Š” ๊ฒฝ์ฐฐ์ฒญ ์ฃผ๊ด€์œผ๋กœ 2016๋…„ 7์›”๋ถ€ํ„ฐ 9์›”๊นŒ์ง€ ์‹œํ–‰๋œ 2016๋…„๋„ ํ•˜๋ฐ˜ ๊ธฐ ์ฒด๊ฐ์•ˆ์ „๋„ ์กฐ์‚ฌ ์ ์ˆ˜๋ฅผ ํ™œ์šฉํ•˜์—ฌ ์ธก์ •ํ•œ๋‹ค. ๋…๋ฆฝ๋ณ€์ˆ˜๋Š” ๋‘ ๊ฐ€์ง€ ์นดํ…Œ๊ณ ๋ฆฌ๋กœ ๋‚˜ ๋ˆ„์—ˆ๋‹ค. ๋จผ์ € ์‚ฌํšŒ ์งˆ์„œ ์ˆ˜์ค€์œผ๋กœ๋Š” โ‘  ๊ธฐ์ดˆโ€ค์ง‘ํšŒ์‹œ์œ„ ์งˆ์„œ, โ‘ก ์œ„ํ—˜์ธ๋ฌผ๋กœ๋ถ€ํ„ฐ์˜ ์•ˆ์ „๋„, โ‘ข ๊ตํ†ต๋ฒ•๊ทœ ์ค€์ˆ˜ ์ˆ˜์ค€์„ ํ™œ์šฉํ•˜์˜€๋‹ค. ๋˜๋‹ค๋ฅธ ๋ณ€์ˆ˜๋กœ๋Š” ์ง€์—ญ์‚ฌํšŒ ๊ฒฝ์ฐฐํ™œ๋™ ์„ ํ™œ์šฉํ•˜์˜€๋‹ค. ์ด๋Š”, โ‘  ๊ฒฝ์ฐฐ๊ณผ ์ฃผ๋ฏผ๊ณผ์˜ ์†Œํ†ต ์ˆ˜์ค€, โ‘ก ๋„๋ณด์ˆœ์ฐฐ ์ •๋„๋กœ ์ธก์ •ํ•˜์˜€ ๋‹ค. ์•„์šธ๋Ÿฌ, ์—ฐ๊ตฌ์˜ ์ธ๊ณผ๊ด€๊ณ„์— ์˜ํ–ฅ์„ ์ค„ ์ˆ˜ ์žˆ๋Š” ๋‹ค์–‘ํ•œ ๋ณ€์ˆ˜๋“ค์„ ํ†ต์ œํ•˜์˜€๋‹ค. ์ฃผ ์š”ํ•œ ํ†ต์ œ๋ณ€์ˆ˜๋กœ๋Š” ์„ฑ๋ณ„, ์—ฐ๋ น, ๊ฒฝ์ฐฐ๊ด€ 1์ธ๋‹น ๋‹ด๋‹น ์ธ๊ตฌ ์ˆ˜, 5๋Œ€ ๋ฒ”์ฃ„ ๋ฐœ์ƒ๊ฑด์ˆ˜, ๊ต ํ†ต์‚ฌ๊ณ  ์ธํ”ผ๊ฑด์ˆ˜, 112์‹ ๊ณ ๊ฑด์ˆ˜, ๊ฒฝ์ฐฐ์„œ ๊ธ‰์ง€, ๋ฒ”์ฃ„ ๊ฒ€๊ฑฐ์œจ์ด๋‹ค. ์œ„๊ณ„์  ์„ ํ˜•๋ชจํ˜•(HLM: Hierarchical Linear Models)์„ ํ™œ์šฉํ•˜์—ฌ ๊ฐœ์ธ์ˆ˜์ค€์˜ ๋ณ€ ์ˆ˜๋“ค์„ 1์ˆ˜์ค€(level-1)์œผ๋กœ, ๊ฐœ์ธ์„ ํฌํ•จํ•˜๋Š” ์ง€์—ญ๋‹จ์œ„ ์ˆ˜์ค€์˜ ๋ณ€์ˆ˜๋“ค์„ 2์ˆ˜์ค€ (level-2)์œผ๋กœ ๊ตฌ๋ถ„ํ•œ ํ›„ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋ถ„์„๊ฒฐ๊ณผ, ์ฒซ์งธ, ๊ฑฐ์ฃผ ์ง€์—ญ์˜ ์‚ฌํšŒ์งˆ์„œ ์ˆ˜์ค€์ด ๋†’๋‹ค๊ณ  ๋Š๋ผ๋Š” ์ฃผ๋ฏผ์ผ์ˆ˜๋ก ์ฒด๊ฐ์•ˆ์ „๋„๊ฐ€ ๋†’์€ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ตฌ์ฒด์ ์œผ๋กœ ๊ฑฐ์ฃผ ์ง€์—ญ์˜ ๊ธฐ์ดˆ์งˆ์„œยท์ง‘ํšŒ์‹œ์œ„ ์งˆ์„œ ์ค€์ˆ˜ ์ˆ˜์ค€์ด ๋†’์„์ˆ˜๋ก ์ฃผ๋ฏผ๋“ค์˜ ์ฒด๊ฐ์•ˆ์ „๋„๊ฐ€ ๋†’์€ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ, ๊ฑฐ์ฃผ์ง€์—ญ์˜ ๋ถˆ๋Ÿ‰์ฒญ์†Œ๋…„ ๋˜๋Š” ๋…ธ์ˆ™์ž ๋“ฑ ์œ„ํ—˜์ธ๋ฌผ๋กœ๋ถ€ํ„ฐ ์•ˆ์ „ํ•˜ ๋‹ค๊ณ  ๋Š๋‚„์ˆ˜๋ก ์ฒด๊ฐ์•ˆ์ „๋„๊ฐ€ ๋†’์€ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋˜ํ•œ ๊ตํ†ต๋ฒ•๊ทœ์™€ ๊ด€๋ จํ•˜์—ฌ ๊ฑฐ ์ฃผ์ง€์—ญ์˜ ๊ตํ†ต๋ฒ•๊ทœ ์ˆ˜์ค€์ด ๋†’์„์ˆ˜๋ก ์ฃผ๋ฏผ๋“ค์˜ ์ฒด๊ฐ์•ˆ์ „๋„๊ฐ€ ๋†’๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋‘˜์งธ, ๊ฑฐ์ฃผ ์ง€์—ญ์˜ ์ง€์—ญ์‚ฌํšŒ ๊ฒฝ์ฐฐํ™œ๋™์ด ์ ๊ทน์ ์œผ๋กœ ์ด๋ฃจ์–ด์ง€๊ณ  ์žˆ๋‹ค๊ณ  ๋Š๋ผ๋Š” ์ฃผ๋ฏผ์ผ์ˆ˜ ๋ก ์ฒด๊ฐ์•ˆ์ „๋„๊ฐ€ ๋†’๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ตฌ์ฒด์ ์œผ๋กœ ๊ฑฐ์ฃผ ์ง€์—ญ์˜ ๊ฒฝ์ฐฐ๊ณผ ์ฃผ๋ฏผ๊ฐ„์˜ ์†Œํ†ต์ด ์ž˜ ์ด๋ฃจ์–ด์ง„๋‹ค๊ณ  ๋Š๋‚„์ˆ˜๋ก ๊ทธ๋ฆฌ๊ณ  ๊ฑฐ์ฃผ ์ง€์—ญ์˜ ๊ฒฝ์ฐฐ๊ด€๋“ค์ด ๋„๋ณด์ˆœ์ฐฐ์„ ๋งŽ์ด ํ•˜๊ณ  ์žˆ๋‹ค๊ณ  ๋Š๋‚„์ˆ˜๋ก ์ฃผ๋ฏผ๋“ค์˜ ์ฒด๊ฐ์•ˆ์ „๋„๊ฐ€ ๋†’์€ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋ถ„์„๊ฒฐ๊ณผ ๋‘ ๊ฐ€์ง€ ๊ฐ€์„ค์„ ๋ชจ๋‘ ์ง€์ง€ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ์—ฌ๋Ÿฌ ๊ฐ€์ง€ ์‹œ์‚ฌ์ ์„ ๊ฐ€์ง„๋‹ค. ์ง€์—ญ์‚ฌํšŒ ๊ฒฝ์ฐฐํ™œ๋™๊ณผ ๊ด€๋ จํ•˜์—ฌ ์ฒด๊ฐ์•ˆ์ „ ๋„๋ฅผ ๋†’์ด๋Š” ๋Œ€์ฑ…์€ ์ง€์—ญ๊ฒฝ์ฐฐ์˜ ๊ฐ€์‹œ์  ์น˜์•ˆํ™œ๋™์„ ํ™œ์„ฑํ™”ํ•˜๋Š” ๊ฒƒ์„ ๊ธฐ๋ณธ์ „์ œ๋กœ ์ฃผ ๋ฏผ๊ณผ์˜ ์†Œํ†ต ๋ฐ ์ฐธ์—ฌ๋ฅผ ์œ ๋„ํ•  ์ˆ˜ ์žˆ๋Š” ๋‹ค์–‘ํ•œ ๋ฐฉ์•ˆ์„ ์ •์ฑ…์ ์œผ๋กœ ๋„์ž…ํ•  ํ•„์š”์„ฑ์ด ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ํŒ๋‹จ๋œ๋‹ค. ์•„์šธ๋Ÿฌ, ์ฒด๊ฐ์•ˆ์ „๋„๋Š” ์ง€์—ญ์‚ฌํšŒ ๊ฒฝ์ฐฐํ™œ๋™๊ณผ ๋”๋ถˆ์–ด ์ง€์—ญ ๋‚ด ๋ฌด์งˆ์„œ๋ฅผ ์ œ๊ฑฐํ•˜๋Š” ๊ฒƒ์ด ์ค‘์š”ํ•˜๋ฉฐ, ์ด๋Š” ๊ฒฝ์ฐฐ์˜ ์—ญํ• ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์ง€์—ญ์‚ฌํšŒ์™€ ํ˜‘๋ ฅ ํ•˜์—ฌ ์ด๋ฃจ์–ด์งˆ ๋•Œ ๋”์šฑ ํšจ๊ณผ์ ์ด๋ผ๋Š” ๊ฒƒ์„ ์•Œ ์ˆ˜ ์žˆ์œผ๋ฏ€๋กœ, ํ–ฅํ›„ ์น˜์•ˆ์ •์ฑ…์€ ์ง€๊ธˆ ๋ณด๋‹ค ๋” ์ง€์ž์ฒด, ์ฃผ๋ฏผ๋“ค๊ณผ ์†Œํ†ตํ•˜๋ฉฐ ํ˜‘๋ ฅ์„ ํ†ตํ•œ ๊ณต๋™์ฒด ์น˜์•ˆ์„ ์‹ค์ฒœํ•ด๋‚˜๊ฐ€๋Š” ๊ฒƒ์ด ์ค‘์š”ํ•  ๊ฒƒ์ด๋ผ๊ณ  ์ƒ๊ฐ๋œ๋‹ค.โ… . ์—ฐ๊ตฌ์˜ ๋ชฉ์  1 1. ์—ฐ๊ตฌ์˜ ๋ชฉ์ ๊ณผ ํ•„์š”์„ฑ 1 2. ์—ฐ๊ตฌ์˜ ๋Œ€์ƒ๊ณผ ๋ฒ”์œ„ 8 โ…ก. ์ด๋ก ์  ๋…ผ์˜์™€ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  9 1. ์ด๋ก ์  ๋…ผ์˜ 9 2. ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  12 โ…ข. ์น˜์•ˆํ™˜๊ฒฝ ๋ถ„์„ 18 1. ์น˜์•ˆํ™œ๋™์˜ ๊ฐœ๋… 18 2. ์น˜์•ˆํ™˜๊ฒฝ ๋ถ„์„ 20 3. ์ฒด๊ฐ์•ˆ์ „๋„์™€ ๊ตญ๋ฏผํ–‰๋ณต 30 โ…ฃ. ์—ฐ๊ตฌ์„ค๊ณ„ ๋ฐ ๋ถ„์„๋ฐฉ๋ฒ• 31 1. ์—ฐ๊ตฌ ๊ฐ€์„ค ๋ฐ ์—ฐ๊ตฌ์˜ ๋ถ„์„ํ‹€ 31 2. ์ธก์ • ๋ณ€์ˆ˜ 35 3. ๋ถ„์„ ์ž๋ฃŒ์™€ ๋ถ„์„ ๋ชจํ˜• 41 โ…ค. ๋ถ„์„๊ฒฐ๊ณผ 44 1. ํ‘œ๋ณธ ํ˜„ํ™ฉ 44 2. ๊ธฐ์ˆ  ํ†ต๊ณ„ ๋ถ„์„ 45 3. ํƒ€๋‹น์„ฑ ๋ฐ ์‹ ๋ขฐ์„ฑ ๋ถ„์„ 50 4. ์ƒ๊ด€๊ด€๊ณ„ ๋ถ„์„ 53 5. ์œ„๊ณ„์  ์„ ํ˜• ๋ชจํ˜• ๋ถ„์„ ๊ฒฐ๊ณผ 55 6. ๊ฐ€์„ค ๊ฒ€์ฆ ๊ฒฐ๊ณผ์™€ ํ•ด์„ 62 โ…ฅ. ๊ฒฐ๋ก  64 1. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ์˜ ์š”์•ฝ 64 2. ์ด๋ก ์  ์˜์˜ ๋ฐ ์ •์ฑ…์  ์‹œ์‚ฌ์  65 3. ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„ ๋ฐ ํ–ฅํ›„ ์—ฐ๊ตฌ๊ณผ์ œ 72 ์„ค๋ฌธ๋ฌธํ•ญ 74 ์ฐธ๊ณ ๋ฌธํ—Œ 78 Abstract 81Maste

    ๊ธฐํƒ€ํฌ๊ด„์†์ต์ด ์žฌ๋ฌด๋ณด๊ณ ์˜ ๋ถˆํˆฌ๋ช…์„ฑ๊ณผ ์ฃผ๊ฐ€๊ธ‰๋ฝ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š”๊ฐ€

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ฒฝ์˜ํ•™๊ณผ ํšŒ๊ณ„ํ•™ ์ „๊ณต, 2016. 2. ํ™ฉ์ด์„.๋ณธ ์—ฐ๊ตฌ๋Š” ๊ธฐํƒ€ํฌ๊ด„์†์ต๊ณผ ๊ทธ ๊ตฌ์„ฑ์š”์†Œ์™€ ๊ด€๋ จํ•˜์—ฌ ์žฌ๋ฌด๋ณด๊ณ ์˜ ๋ถˆํˆฌ๋ช…์„ฑ ๋ฐ ์ฃผ๊ฐ€๊ธ‰๋ฝ ๊ฐ„์˜ ๊ด€๊ณ„๋ฅผ ์‚ดํŽด๋ณธ๋‹ค. ์žฌ๋ฌด๋ณด๊ณ ์˜ ๋ถˆํˆฌ๋ช…์„ฑ์„ ์ธก์ •ํ•˜๋Š” ์ง€ํ‘œ๋กœ์„œ ์žฌ๋Ÿ‰์  ๋ฐœ์ƒ์•ก์˜ 3๋…„๊ฐ„ ์ด๋™ ํ‰๊ท ์„ ์‚ฌ์šฉํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ ๋‹น๊ธฐ์— ๋ณด๊ณ ๋œ ๊ธฐํƒ€ํฌ๊ด„์†์ต ์ด์•ก์ด ์Œ์ด๊ณ  ๊ทธ ๊ธˆ์•ก์ด ๋งŽ์œผ๋ฉด ์žฌ๋ฌด๋ณด๊ณ ์˜ ๋ถˆํˆฌ๋ช…์„ฑ์ด ์ฆ๊ฐ€ํ•˜์˜€๋‹ค. ์ด ํšจ๊ณผ๋Š” ๊ธฐํƒ€ํฌ๊ด„์†์ต ๊ตฌ์„ฑ์š”์†Œ ์ค‘ ์™ธํ™”ํ™˜์‚ฐ์†์ต ๊ณ„์ •์— ์˜ํ•˜์—ฌ ์ฃผ๋„๋˜๊ณ  ์žˆ์—ˆ๋‹ค. ๋‹น๊ธฐ์— ๋ณด๊ณ ๋œ ๊ธฐํƒ€ํฌ๊ด„์†์ต ์ด์•ก์ด ์–‘์ด๊ณ  ๊ทธ ๊ธˆ์•ก์ด ํฐ ๊ฒฝ์šฐ์—๋„ ์žฌ๋ฌด๋ณด๊ณ ์˜ ๋ถˆํˆฌ๋ช…์„ฑ์ด ์ฆ๊ฐ€ํ•˜์˜€์œผ๋‚˜ ๊ทธ ํšจ๊ณผ๋Š” ๊ธฐํƒ€ํฌ๊ด„์†์ต ์ด์•ก์ด ์Œ์ธ ๊ฒฝ์šฐ๋ณด๋‹ค ์ž‘์•˜๋‹ค. ์ด ํšจ๊ณผ๋Š” ๊ธฐํƒ€ํฌ๊ด„์†์ต ๊ตฌ์„ฑ์š”์†Œ ์ค‘ ํ‡ด์ง์—ฐ๊ธˆ๊ณผ ๊ด€๋ จ๋œ ๊ณ„์ •์— ์˜ํ•˜์—ฌ ์ฃผ๋„๋˜๊ณ  ์žˆ์—ˆ๋‹ค. ๋‹น๊ธฐ์— ๋ณด๊ณ ๋œ ๊ธฐํƒ€ํฌ๊ด„์†์ต์˜ ๋ถ€ํ˜ธ์— ์ƒ๊ด€์—†์ด ๋‹น๊ธฐ์— ๋ณด๊ณ ๋œ ๊ธฐํƒ€ํฌ๊ด„์†์ต ์ด์•ก์ด ํด์ˆ˜๋ก ์ฃผ๊ฐ€๊ธ‰๋ฝ์œ„ํ—˜์€ ๊ฐ์†Œํ•˜์˜€๋‹ค. ์ด ํšจ๊ณผ๋Š” ํˆฌ์ž์ž๋“ค์ด ๋‹น๊ธฐ์— ๋ณด๊ณ ๋œ ๊ธฐํƒ€ํฌ๊ด„์†์ต์˜ ๋ถ€ํ˜ธ๊ฐ€ ์–‘์ˆ˜์ธ ๊ฒฝ์šฐ์— ๋” ๋ฏผ๊ฐํ•˜๊ฒŒ ๋ฐ˜์‘ํ•˜๊ฑฐ๋‚˜ ๊ธฐํƒ€ํฌ๊ด„์†์ต์˜ ์ˆ˜์น˜๊ฐ€ ์–‘์ˆ˜์ธ ๊ฒƒ์„ ํ˜ธ์žฌ๋กœ์„œ ํ•ด์„ํ•˜์—ฌ ์–‘์˜ ์ˆ˜์น˜์— ๊ณ ์ฐฉ๋˜์–ด์žˆ๊ธฐ ๋•Œ๋ฌธ์œผ๋กœ ๋ณด์ธ๋‹ค. ๋˜ํ•œ, ๊ธฐํƒ€ํฌ๊ด„์†์ต์ด ์žฌ๋ฌด๋ณด๊ณ ์˜ ๋ถˆํˆฌ๋ช…์„ฑ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์ด ์ฃผ์‹์‹œ์žฅ์— ์ง์ ‘ ์˜ํ–ฅ์„ ๋ฏธ์น˜์ง€ ์•Š๊ณ  ๋‹ค๋ฅธ ์š”์†Œ๋ฅผ ํ†ตํ•˜์—ฌ ์ฃผ์‹์‹œ์žฅ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๊ธฐ ๋•Œ๋ฌธ์œผ๋กœ ๋ณด์ธ๋‹ค.This study examines the financial reporting opacity and the crash risk of a stock price that is relating to Other Comprehensive Income (OCI) and its components. Using the three-year moving sum of absolute value of discretionary accruals as a measure of financial reporting opacity, I find out that negatively high amount of total OCI reported at the current period increases the financial reporting opacity, driven by the account of adjustment of foreign currency translation. The positively high amount of OCI also increases financial reporting opacity, but the degree of the effect is smaller than the subsample of the negative amount of total OCI. The effect of the positive amount of total OCI is driven by adjustment of pension related issues. A considerable value of total OCI decreases the crash risk of stock return, regardless of the sign of the total amount of OCI. This phenomenon is because investors seem to react to the positive amount of OCI more sensitive, or the investors might partially fixate on the positive number so that they interpret the positive number of OCI as good news and the effect of OCI on opacity does not go directly to stock market, rather go through another factor.1. INTRODUCTION 1 2. BACKGROUND AND HYPOTHESIS DEVELOPMENT 12 3. SAMPLE SELECTION AND VARIABLES 19 3.1 Sample Selection 19 3.2 Variables 20 4. RESEARCH DESIGN 27 4.1 Other Comprehensive Income and Financial Reporting Opacity 27 4.2 Other Comprehensive Income and Crash Risk 28 5. RESULTS 30 5.1 Descriptive Statistics 30 5.2 Other Comprehensive Income and Financial Reporting Opacity 32 5.3 Other Comprehensive Income and Crash Risk 35 6. ADDITIONAL TESTS 37 6.1 Partitioning Sample Based on Firm Size 37 6.2 Alternative Measure of Crash Risk 38 6.3 Non-zero Samples of TOCI, AFS, HDG, PEN, and FCT 39 7. CONCLUSION 40 APPENDIX 42 REFERENCES 45 ๊ตญ๋ฌธ์ดˆ๋ก 65Maste

    Trust and Labor Market Participation

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ฒฝ์ œํ•™๋ถ€, 2013. 2. ๊น€๋ณ‘์—ฐ.This paper investigates the relationship between trust and individuals labor market participation by using the United States General Social Survey. This study utilizes instrumental variable and pseudo-panel estimation methods in addition to simple Probit models, which enhance the reliability of results. The findings suggest that trust as an individuals attitude is significantly associated with the probability of the individuals labor market participation, and that the inherited component of trust affects individuals decision to participate in the labor market. The results from the pseudo-panel, constructed by taking the average values of the agegroup cohort within the same region, imply that trust at the regional level, but not at the cohort level, is significantly associated with the proportion of people involved in the labor market in the United States.1. Introduction 2. Literature Review 2.1 Trust as a measure of social capital 2.2 Social capital and labor market 3. Data 4. Empirical Strategy 5. Estimation Results 6. Conclusion AppendixMaste

    Orally Administered 6:2 Chlorinated Polyfluorinated Ether Sulfonate (F-53B) Causes Thyroid Dysfunction in Rats

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    The compound 6:2 chlorinated polyfluorinated ether sulfonate (F-53B), a replacement for perfluorooctanesulfonate (PFOS) in the electroplating industry, has been widely detected in numerous environmental matrices, human sera, and organisms. Due to regulations that limit PFOS use, F-53B use is expected to increase. Therefore, in this study, we performed a subchronic oral toxicity study of F-53B in Sprague Dawley (SD) rats. F-53B was administered orally once daily to male and female rats for 28 days at doses of 5, 20, and 100 mg/kg/day. There were no toxicologically significant changes in F-53B-treated rats, except in the thyroid gland. However, F-53B slightly reduced the serum concentrations of thyroid hormones, including triiodothyronine and thyroxine, compared with their concentrations in the vehicle group. F-53B also induced follicular hyperplasia and was associated with increased thyroid hormone biosynthesis-associated protein expression. These results demonstrate that F-53B is a strong regulator of thyroid hormones in SD rats as it disrupts thyroid function. Thus, caution should be exercised in the industrial application of F-53B as an alternative for PFOS.ope

    HMGB1 orchestrates STING-mediated senescence via TRIM30ฮฑ modulation in cancer cells

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    Although cellular senescence has emerged as a novel therapeutic concept in cancer, its underlying mechanisms remain unclear. High mobility group box 1 (HMGB1) and stimulator of interferon genes (STING) are involved in senescence. However, their interactions in senescence have not been reported. Therefore, in this study, we investigated the relationships between HMGB1 and STING in senescence in cancer and other cells. In mouse melanoma cells and several other cell lines, doxorubicin treatment induced senescence in an HMGB1-dependent manner. These responses were mediated by STING, and this function of STING was negatively regulated by the E3 ligase tripartite motif protein 30ฮฑ (TRIM30ฮฑ). We also found that HMGB1 bound to the TRIM30ฮฑ promoter and then suppressed its expression by inhibiting its transcription, which enhanced STING-induced senescence. This mechanism was further mediated by signal transducer and activator of transcription 6 (STAT6) and p21. Overall, our findings demonstrated that HMGB1 orchestrated STING-STAT6-p21-mediated senescence by regulating TRIM30ฮฑ as an alternative anticancer mechanism.ope

    Role of Nox4 in Mitigating Inflammation and Fibrosis in Dextran Sulfate Sodium-Induced Colitis

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    Background & aims: Fibrosis development in ulcerative colitis is associated directly with the severity of mucosal inflammation, which increases the risk of colorectal cancer. The transforming growth factor-ฮฒ (TGF-ฮฒ) signaling pathway is an important source of tissue fibrogenesis, which is stimulated directly by reactive oxygen species produced from nicotinamide adenine dinucleotide phosphate oxidases (NOX). Among members of the NOX family, NOX4 expression is up-regulated in patients with fibrostenotic Crohn's disease (CD) and in dextran sulfate sodium (DSS)-induced murine colitis. The aim of this study was to determine whether NOX4 plays a role in fibrogenesis during inflammation in the colon using a mouse model. Methods: Acute and recovery models of colonic inflammation were performed by DSS administration to newly generated Nox4-/- mice. Pathologic analysis of colon tissues was performed, including detection of immune cells, proliferation, and fibrotic and inflammatory markers. RNA sequencing was performed to detect differentially expressed genes between Nox4-/- and wild-type mice in both the untreated and DSS-treated conditions, followed by functional enrichment analysis to explore the molecular mechanisms contributing to pathologic differences during DSS-induced colitis and after recovery. Results: Nox4-/- mice showed increased endogenous TGF-ฮฒ signaling in the colon, increased reactive oxygen species levels, intensive inflammation, and an increased fibrotic region after DSS treatment compared with wild-type mice. Bulk RNA sequencing confirmed involvement of canonical TGF-ฮฒ signaling in fibrogenesis of the DSS-induced colitis model. Up-regulation of TGF-ฮฒ signaling affects collagen activation and T-cell lineage commitment, increasing the susceptibility for inflammation. Conclusions: Nox4 protects against injury and plays a crucial role in fibrogenesis in DSS-induced colitis through canonical TGF-ฮฒ signaling regulation, highlighting a new treatment target.ope

    Mean platelet volume is elevated in patients with psoriasis vulgaris

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    PURPOSE: This retrospective study was done to investigate the mean platelet volume (MPV) level in patients with psoriasis vulgaris and its relationship with disease severity. MATERIALS AND METHODS: We undertook a cross-sectional study on 176 patients and 101 healthy controls to examine the association between MPV and psoriasis. Various clinical and laboratory parameters were analyzed and compared. RESULTS: Platelet distribution width and MPV were significantly higher in patients with psoriasis than controls. In addition, there was positive correlation between Psoriasis Area Severity Index (PASI) and MPV. When psoriasis patients were grouped into mild psoriasis (PASI<10) and moderate to severe psoriasis (PASIโ‰ฅ10), the MPV of the latter group was significantly elevated. Nevertheless, patients with higher MPV level (MPVโ‰ฅ10.4 fL) did not show higher PASI than lower MPV level (MPV<10.4 fL). MPV levels significantly decreased after improvements of psoriasis with various treatments. The variations of MPV and PASI also showed significant correlation. CONCLUSION: We have shown that MPV is increased in psoriasis patients and correlates with disease severity. Therefore, MPV levels may be considered as a marker of disease severity of psoriasis.ope

    Laboratory information management system for COVID-19 non-clinical efficacy trial data

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    Background: As the number of large-scale studies involving multiple organizations producing data has steadily increased, an integrated system for a common interoperable format is needed. In response to the coronavirus disease 2019 (COVID-19) pandemic, a number of global efforts are underway to develop vaccines and therapeutics. We are therefore observing an explosion in the proliferation of COVID-19 data, and interoperability is highly requested in multiple institutions participating simultaneously in COVID-19 pandemic research. Results: In this study, a laboratory information management system (LIMS) approach has been adopted to systemically manage various COVID-19 non-clinical trial data, including mortality, clinical signs, body weight, body temperature, organ weights, viral titer (viral replication and viral RNA), and multiorgan histopathology, from multiple institutions based on a web interface. The main aim of the implemented system is to integrate, standardize, and organize data collected from laboratories in multiple institutes for COVID-19 non-clinical efficacy testings. Six animal biosafety level 3 institutions proved the feasibility of our system. Substantial benefits were shown by maximizing collaborative high-quality non-clinical research. Conclusions: This LIMS platform can be used for future outbreaks, leading to accelerated medical product development through the systematic management of extensive data from non-clinical animal studies.ope

    Comparison of the pathogenesis of SARS-CoV-2 infection in K18-hACE2 mouse and Syrian golden hamster models

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    Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of COVID-19, causes life-threatening disease. This novel coronavirus enters host cells via the respiratory tract, promoting the formation of severe pulmonary lesions and systemic disease. Few animal models can simulate the clinical signs and pathology of COVID-19 patients. Diverse preclinical studies using K18-hACE2 mice and Syrian golden hamsters, which are highly permissive to SARS-CoV-2 in the respiratory tract, are emerging; however, the systemic pathogenesis and cellular tropism of these models remain obscure. We intranasally infected K18-hACE2 mice and Syrian golden hamsters with SARS-CoV-2, and compared the clinical features, pathogenesis, cellular tropism and infiltrated immune-cell subsets. In K18-hACE2 mice, SARS-CoV-2 persistently replicated in alveolar cells and caused pulmonary and extrapulmonary disease, resulting in fatal outcomes. Conversely, in Syrian golden hamsters, transient SARS-CoV-2 infection in bronchial cells caused reversible pulmonary disease, without mortality. Our findings provide comprehensive insights into the pathogenic spectrum of COVID-19 using preclinical models.ope
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