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    Multi-omics analysis based upon immune biomarker PD-L1

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์˜๊ณผ๋Œ€ํ•™ ํ˜‘๋™๊ณผ์ • ์ข…์–‘์ƒ๋ฌผํ•™์ „๊ณต, 2023. 8. ๊ตฌ์ž๋ก.์•” ์ง„๋‹จ ๋ฐ ์น˜๋ฃŒ ๊ธฐ๋ฒ•์ด ๋ฐœ๋‹ฌํ–ˆ์Œ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ํ์•”์€ ๊ตญ๋‚ด ๋ฐ ์ „ ์„ธ๊ณ„์ ์œผ๋กœ ๋†’์€ ๋ฐœ์ƒ๋ฅ ๊ณผ ์‚ฌ๋ง๋ฅ ์„ ๋‚˜ํƒ€๋‚ด๋Š” ์งˆํ™˜์ด๋‹ค. ์ตœ๊ทผ ๋„์ž…๋œ ๋ฉด์—ญํ•ญ์•”์ œ๋Š” ์ œํ•œ์ ์ธ ํšจ๊ณผ์™€ ๋ถ€์ž‘์šฉ, ์•ฝ์ œ ๋‚ด์„ฑ์„ ๋‚˜ํƒ€๋‚ด๊ณ  ์žˆ๋‹ค. ํ์•” ๋ฐœ์ƒ์˜ ์•” ํ™”์™€ ์•…์„ฑ ๊ธฐ์ž‘์˜ ์œ ์ „์  ๋ณ€์ด์™€ ์‹ ํ˜ธ์ „๋‹ฌ์˜ ๋ถ„์„์„ ํ†ตํ•ด ๋ฉด์—ญ ํ•ญ์•”์— ํ•„์š”ํ•œ ํ์•”์˜ ์ข…์–‘ ์œ ์ „์ž ํ‘œ์ ๊ณผ ๊ทธ์— ์•Œ๋งž์€ ์‹ ํ˜ธ์ „๋‹ฌ๊ฒฝ๋กœ์˜ ๊ทœ๋ช…์ด ํ•„์š”ํ•˜๋‹ค. ํ์•” ํ™˜์ž ํ‰์ˆ˜๋กœ๋ถ€ํ„ฐ ์œ ๋ž˜ํ•œ ์„ธํฌ์ฃผ ์ˆ˜๋ฆฝํ•œ ํ›„์— ํŠน์„ฑ์„ ๋ถ„์„ํ•จ์œผ๋กœ์„œ ์กฐ๊ธˆ ๋” ์ž„์ƒ ์น˜๋ฃŒ์— ๊ฐ€๊นŒ์šด ์น˜๋ฃŒ ์ „๋žต์„ ์ œ์‹œํ•  ์ˆ˜ ์žˆ๋‹ค. ๋ฉด์—ญ ํ•ญ์•” ์น˜๋ฃŒ์˜ PD-L1์€ ์ข…์–‘ ํ‘œ์ง€์ž๋กœ์„œ ๊ทธ๋ฅผ ๊ธฐ์ค€์œผ๋กœ ์œ ์ „์ž ๋ฐ”์ด์˜ค๋งˆ์ปค์™€ ์‹ ํ˜ธ์ „๋‹ฌ ๊ฒฝ๋กœ๋ฅผ ๋ถ„์„, ์—ฐ๊ตฌํ•ด ๋ณด์•˜๋‹ค. ์ˆ˜๋ฆฝํ•œ ์„ธํฌ์ฃผ๋“ค์€ ํ™˜์ž์˜ ํŠน์„ฑ์„ ์ž˜ ๋ฐ˜์˜ํ•˜๊ธฐ์— ํ–ฅํ›„ ๋ฉด์—ญ ํ•ญ์•” ์น˜๋ฃŒ์˜ ํ‘œ์ ์ด ๋  ์ˆ˜ ์žˆ๋Š” ๋ฐ”์ด์˜ค๋งˆ์ปค์™€ ์‹ ํ˜ธ์ „๋‹ฌ๊ฒฝ๋กœ๋ฅผ ์ž„์ƒ์—์„œ ์ฑ„ํƒํ•˜์—ฌ ์ ์šฉํ•˜๊ฒŒ ๋  ๊ฐ€๋Šฅ์„ฑ์„ ์ œ์‹œํ•˜๊ณ ์ž ํ•œ๋‹ค. ์•” ํ™˜์ž๋“ค์˜ ๊ฐœ์ธ๋งž์ถคํ™”์น˜๋ฃŒ๊ฐ€ ์ง„ํ–‰๋˜๋ฉด์„œ ์ข…์–‘์˜ ๋ถ„์ž์  ๋ฐœ์•” ๊ฒฝ๋กœ ๋ฐ ์ข…์–‘ ์œ ์ „์ž์˜ ๋ฐ”์ด์˜ค๋งˆ์ปค์™€ ์‹ ํ˜ธ์ „๋‹ฌ๊ฒฝ๋กœ์˜ ๋” ๊นŠ์€ ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•˜์—ฌ ๋ถ„์ž์  ๋ฐœ์•” ์‹ ํ˜ธ์ „๋‹ฌ ๊ฒฝ๋กœ, ์œ ์ „์ฒด ๋ถ„์„์„ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ํ์•” ํ™˜์ž์—์„œ ์œ ๋ž˜ํ•œ ์„ธํฌ์ฃผ 29๊ฐœ๋ฅผ ์ˆ˜๋ฆฝํ•œ ํ›„ ์ˆ˜๋ฆฝํ•œ ์„ธํฌ์ฃผ์˜ STR(Short Tandem Repeat) ๊ฒ€์‚ฌ๋ฅผ ํ†ตํ•ด ํ™˜์ž์™€ ๋™์ผํ•œ ์„ธํฌ์ฃผ์ธ ๊ฒƒ์„ ํ™•์ธํ•œ ํ›„ ํŠน์„ฑ๋ถ„์„์„ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ์ˆ˜๋ฆฝํ•œ ์„ธํฌ์ฃผ๋ฅผ ๊ฐ€์ง€๊ณ  ์œ ์ „์ž์˜ ๋Œ์—ฐ๋ณ€์ด์™€ ๊ฐ ์„ธํฌ ์ฃผ์— ๋Œ€ํ•œ ์œ ์ „์ •๋ณด์˜ ๋”ฐ๋ฅธ ํŠน์ง•์„ ๊ทœ๋ช…ํ•˜์—ฌ ์œ ์ „๋ณ€์ด์™€์˜ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๋ฐํžˆ๊ณ ์ž ํ•˜์˜€๋‹ค. ๋ฉด์—ญ ํ•ญ์•” ์น˜๋ฃŒ์˜ ์ง„ํ–‰ ์—ฌ๋ถ€์˜ ๊ฒ€์ง„๋ฐฉ๋ฒ•์œผ๋กœ PD-L1์˜ ๋ฐœํ˜„ ์ •๋„๋ฅผ ๋ณด๋“ฏ์ด ์šฐ๋ฆฌ๊ฐ€ ์ˆ˜๋ฆฝํ•œ ์„ธํฌ์ฃผ์—์„œ๋„ ์ฃผ์š” ๋ถ„์„ ๊ฒฐ์ • ๋ถ„๋ฅ˜๋กœ western analysis๋ฅผ ํ†ตํ•ด PD-L1 ๋ฐœํ˜„ ๊ธฐ์ค€์œผ๋กœ ์„ธํฌ์ฃผ๋ฅผ ๋‚˜๋ˆ„์–ด ๋ถ„์„ ์‹œํ–‰ ํ•˜์˜€๋‹ค. PD-L1์˜ ๋ฐœํ˜„ ์ •๋„์— ๋”ฐ๋ผ ๋‚˜๋ˆ„์–ด์ง„ ์„ธํฌ์ฃผ๋“ค์€ protein coding ์˜์—ญ์ธ exome ์˜์—ญ๋งŒ์„ ๋ณด๋Š” whole exome sequencing (WES), Transcriptome์ƒ์˜ RNA sequencing์„ ํ†ตํ•ด ์œ ์ „ ๋ณ€์ด์™€ ๋ฐœํ˜„๋œ ์œ ์ „์ž๋“ค์˜ ๋ฐœํ˜„๋Ÿ‰์˜ ์ฐจ์ด๋ฅผ ํ™•์ธํ•œ ํ›„ PD-L1์˜ ๋ฐœํ˜„ ์ƒ๊ด€๊ด€๊ณ„์™€ ์‹ ํ˜ธ์ „๋‹ฌ๊ฒฝ๋กœ์˜ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๋ฐํžˆ๊ณ ์ž ํ•˜์˜€๋‹ค. ์—ฌ๋Ÿฌ ์—ฐ๊ตฌ์—์„œ ๋ฐํ˜€์ง„ PD-L1์˜ ๋ฐœํ˜„๊ณผ EGFR์˜ ๋Œ์—ฐ๋ณ€์ด์˜ ์ƒ๊ด€๊ด€๊ณ„๊ฐ€ ์šฐ๋ฆฌ๊ฐ€ ์ˆ˜๋ฆฝํ•œ ์„ธํฌ์ฃผ์—์„œ ๊ฐ™์€ ๊ฒฝํ–ฅ์„ฑ์„ ๋ณด์—ฌ์ฃผ์—ˆ๊ณ , Protein level๊ณผ mRNA level์—์„œ์˜ PD-L1์˜ ์ƒ๊ด€๊ด€๊ณ„๊ฐ€ ์žˆ์Œ์„ ๊ทœ๋ช…ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋˜ ํ•œ, ํ์•” ํ™˜์ž ํ‰์ˆ˜ ์œ ๋ž˜๋กœ ์ˆ˜๋ฆฝํ•œ 29๊ฐœ์˜ ํ์•” ์„ธํฌ์ฃผ์˜ PD-L1์˜ ๋ฐœํ˜„์˜ ์ฐจ์ด์™€ ๋Œ์—ฐ๋ณ€์ด์˜ ์ƒ๊ด€๊ด€๊ณ„๊ฐ€ ํ•ญ์•”์ œ ๋‚ด์„ฑ์ด๋‚˜ ๋ฏผ๊ฐ์„ฑ์—์„œ ์–ด๋– ํ•œ ๋ฐ˜์‘์„ฑ์„ ๋ณด์ด๋Š”์ง€๋ฅผ ์—ฐ๊ตฌ ๋ถ„์„ํ•˜์—ฌ ๊ทธ์™€ ๊ด€๋ จํ•œ ๊ธฐ์ „๊ณผ target ํ•˜๋Š” ๋ฉ”์นด๋‹ˆ์ฆ˜์˜ ์•ฝ๋ฌผ ๋ฐ˜์‘์„ฑ ๋ฐ ์‹ ํ˜ธ์ „๋‹ฌ ๊ฒฝ๋กœ, ์œ ์ „์ž๋“ค์„ ๊ทœ๋ช…ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ํ•ญ์•” ์•ฝ์ œ์˜ ๋ฏผ๊ฐ์„ฑ๊ณผ ์œ ์ „์ •๋ณด์˜ ๋ถ„์„์„ ํ†ตํ•ด ์•ฝ๋ฌผ์˜ validation์„ ํ•  ์ˆ˜ ์žˆ์—ˆ์œผ๋ฉฐ, ์œ ์˜๋ฏธํ•œ ๊ฒฐ๊ณผ๋ฅผ ํ†ตํ•ด ํ์•” ์„ธํฌ์ฃผ์˜ ํŠน์„ฑ์„ ๋ถ„์„ํ•จ์œผ๋กœ ๋ฉด์—ญ-ํ™”ํ•™ ๋ณ‘์šฉ ์น˜๋ฃŒ์˜ ๋ฉด์—ญ ํ•ญ์•” ์š”๋ฒ•์˜ ์ „๋žต ์ค‘ ํ•˜๋‚˜๋กœ ์‚ฌ์šฉ๋  ๊ฒƒ์œผ๋กœ ์‚ฌ๋ฃŒ ๋œ๋‹ค. ํ์•” ํ™˜์ž ์œ ๋ž˜ ์„ธํฌ์ฃผ์˜ ์œ ์ „์ฒด ์ •๋ณด๋ฅผ ๊ฐ€์ง€๊ณ  ์„ธํฌ์ƒ๋ฌผํ•™์  ํŠน์„ฑ๊ณผ ๋ฉด์—ญ ์น˜๋ฃŒ์˜ ์ฃผ์š” ์ƒ๋ฌผ ์ง€ํ‘œ์ธ PD-L1์˜ ๋ฐœํ˜„ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ํŒŒ์•…ํ•จ์œผ๋กœ์„œ ๊ฐœ์ธ์˜ ํ•ญ์•” ์น˜๋ฃŒ ๋ฐ˜์‘์„ ์˜ˆ์ธกํ•  ์ˆ˜ ์žˆ๋„๋ก ๋„์šธ ์ˆ˜ ์žˆ๋‹ค. ์ƒ๋ฌผ ์ง€ํ‘œ์ธ PD-L1์— ๋”ฐ๋ฅธ ๋ถ„๋ฅ˜๋ฅผ ํ†ตํ•ด ์œ ์ „์ž ๋ณ€์ด์™€ ์•ฝ์ œ ๊ฐ์ˆ˜์„ฑ์˜ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๊ทœ๋ช…ํ•˜์—ฌ ์ž„์ƒ์  ์น˜๋ฃŒ ์ ‘๊ทผ์„ฑ์„ ๊ฐ€๊นŒ์ด ๊ฐˆ ์ˆ˜ ์žˆ์œผ๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด ์œ ์ „์ž ๋ณ€์ด์™€ ์‹ ํ˜ธ์ „๋‹ฌ ๊ฒฝ๋กœ๊ฐ€ ๋ฉด์—ญ-ํ™”ํ•™ ์น˜๋ฃŒ ์š”๋ฒ•์˜ ์œ ์˜๋ฏธํ•œ ๊ฒฐ๊ณผ๋ฅผ ๋„์ถœ ๊ฐ€๋Šฅํ•˜๋‹ค. ํ•ญ์•” ์น˜๋ฃŒ์˜ ์„ธ๋Œ€๊ฐ€ ์ •๋ฐ€ ์ข…์–‘ํ•™์— ๊ธฐ์ธํ•œ ๊ฐœ์ธ ๋งž์ถคํ™” ๋˜์–ด๊ฐ€๊ณ  ์žˆ๋“ฏ์ด ์ด ์—ฐ๊ตฌ๋Š” ํ•ญ์•” ์น˜๋ฃŒ์˜ ํ™œ์šฉ ๊ฐ€๋Šฅ์„ฑ๊ณผ ํ•„์š”์„ฑ์„ ๋ณด์—ฌ์ฃผ๋Š” ๊ฒฐ๊ณผ๋ฌผ์ด ๋  ๊ฒƒ์ด๋‹ค.Despite advances in cancer diagnosis and treatment techniques, lung cancer is a disease with high incidence and mortality both domestically and globally. Most of the recently introduced immuno-anticancer drugs show limited effects, side effects, and drug resistance. So, it is crucial to find advanced oncogenic and malignant mechanisms of lung cancer development through analysis of genetic mutations and signal transduction in immune oncology. After establishing 29 cell lines derived from the pleural fluid of lung cancer patients, we suggest clinical treatment strategy by analyzing the characteristics of the patient characteristics. As personalized treatment for cancer patients has progressed, further research on the molecular carcinogenic pathway of tumors and biomarkers and signal transduction pathways of tumor genes was needed. A short tandem repeat (STR) test was confirmed to be the same cell line as the patient, and then characterization study was performed. With the established cell lines, the characteristics of gene mutations and genetic information for each cell line were identified to reveal the correlation with genetic mutations. As expression of PD-L1 is examined as a screening method for the progress of immunotherapy, the established cell lines were analyzed by dividing the cell lines based on PD-L1 expression through western analysis as a major analysis decision classification. The classified cell lines according to the level of expression of PD-L1 were identified to confirm the genetic mutations and the difference in expression level through whole exome sequencing (WES), and RNA sequencing on the transcriptome. This study reveals the correlation between the expression of PD-L1 and the signal transduction pathway. Several previous studies showed the same trend in terms of the correlation between PD-L1 expression and EGFR mutation. This study further supports the correlation between PD-L1 at protein level and mRNA level in established lung cancer cell lines. In addition, it identifies the correlation between PD-L1 expression and genetic mutation, drug sensitivity. `Individual anticancer treatment responses are predicted by identifying the correlation between cell biological characteristics and the expression of PD-L1, which is a key biomarker for immunotherapy. The classification according to the biomarker PD-L1 identifies the relations of genetic variation with drug sensitivity thereby contributing to expanding clinical treatment access and through this, significant results are achieved for immuno-chemotherapy, also contributing to the future cancer therapy. Based upon precision oncology, the generation of anticancer treatment is becoming personalized. This study shows the necessity and potential applications of anticancer treatment in the immunotherapy.Table of Contents Abstract โ…ฐ Table of Contents โ…ณ List of Tables โ…ด List of Figures โ…ต Introduction 1 Materials and Methods 4 Results 13 Discussion 86 References 92 Abstract in Korean 98๋ฐ•

    ํ•™๋ น์ „๊ธฐ ๋ณด์œก์‹œ์„ค ์•„๋™์„ ์œ„ํ•œ ํ•œ์˜์‚ฌ ์ฃผ์น˜์˜ ํ”„๋กœ๊ทธ๋žจ ๊ฐœ๋ฐœ ๋ฐ ํ‰๊ฐ€

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋ณด๊ฑด๋Œ€ํ•™์› : ๋ณด๊ฑดํ•™๊ณผ(๋ณด๊ฑด์ •์ฑ…๊ด€๋ฆฌํ•™์ „๊ณต), 2013. 2. ์กฐ๋ณ‘ํฌ.์šฐ๋ฆฌ ์‚ฌํšŒ์˜ ์—ฌ์„ฑ ๊ฒฝ์ œํ™œ๋™ ์ฐธ์—ฌ ์ฆ๊ฐ€์™€ ์ •๋ถ€์˜ ๋ณด์œก์‹œ์„ค ํ™•์ถฉ์œผ๋กœ ์ด๋ฅธ ๋‚˜์ด์— ์žฅ์‹œ๊ฐ„ ๋ณด์œก์‹œ์„ค์„ ์ด์šฉํ•˜๋Š” ์•„๋™์ด ๋Š˜์–ด๋‚˜๊ณ  ์žˆ๋‹ค. ๋ณด์œก์‹œ์„ค์€ ๋งŽ์€ ์•„๋™์ด ๋ฐ€์ง‘ํ•ด ์žˆ์–ด ์žฆ์€ ์ ‘์ด‰์œผ๋กœ ์ธํ•œ ๊ฐ์—ผ์„ฑ ์งˆํ™˜์˜ ๋ฐœ์ƒ์ด ์šฉ์ดํ•˜๋ฉฐ, ๋ฉด์—ญ๋ ฅ์ด ๋‚ฎ์€ ์˜์œ ์•„์˜ ๊ฒฝ์šฐ ์ง‘๋‹จ ์ƒํ™œ์ด ์ฒด๋ ฅ์ , ์‹ฌ๋ฆฌ์  ์ŠคํŠธ๋ ˆ์Šค๋กœ ์ž‘์šฉํ•ด ๊ฐ์—ผ์„ฑ ์งˆํ™˜์ด ์ง€์†, ์ค‘์ฒฉ๋˜๋Š” ๊ฒฝ์šฐ๊ฐ€ ๋นˆ๋ฒˆํ•˜๋‹ค. ์•„๋™๊ธฐ์˜ ๊ฑด๊ฐ•์ด ์ผ์ƒ์˜ ๊ฑด๊ฐ•์„ ์ขŒ์šฐํ•จ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ์ด๋“ค ๋ณด์œก์‹œ์„ค ์•„๋™์— ๋Œ€ํ•œ ๊ฑด๊ฐ•๊ด€๋ฆฌ ๋ฐ ์ค‘์žฌ ํ”„๋กœ๊ทธ๋žจ์€ ๋ฏธํกํ•œ ์‹ค์ •์ด๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋ณด์œก์‹œ์„ค ์•„๋™๋“ค์ด ํ”ํžˆ ๊ฒช๋Š” ๊ฐ์ข… ๊ฐ์—ผ์„ฑ ์งˆํ™˜์„ ์˜ˆ๋ฐฉํ•˜๊ณ  ๊ฑด๊ฐ•์ฆ์ง„์„ ๋„๋ชจํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์ „๋ฌธ ์˜๋ฃŒ ์ธ๋ ฅ์ธ ํ•œ์˜์‚ฌ๋ฅผ ๋ณด์œก์‹œ์„ค์— ์ฃผ์น˜์˜๋กœ ์—ฐ๊ณ„ํ•˜๊ณ , ํ•œ์˜ํ•™์˜ ์˜ˆ๋ฐฉ์  ๊ฐœ๋…์ธ ้คŠ็”Ÿ๊ณผ ๆฒปๆœช็—…์„ ๋ฐ”ํƒ•์œผ๋กœ ๊ด€๋ฆฌ, ๊ต์œก, ๊ฒ€์ง„์œผ๋กœ ๊ตฌ์„ฑ๋œ ๋ณด์œก์‹œ์„ค ํ•œ์˜์‚ฌ ์ฃผ์น˜์˜ ํ”„๋กœ๊ทธ๋žจ์„ ๊ฐœ๋ฐœ, ์‹œํ–‰ํ•˜์—ฌ ๊ทธ ํšจ๊ณผ๋ฅผ ํ‰๊ฐ€ํ•˜์˜€๋‹ค. ๋น„๋™๋“ฑ์„ฑ ๋Œ€์กฐ๊ตฐ ์œ ์‚ฌ์‹คํ—˜์—ฐ๊ตฌ๋กœ ์„œ์šธ๊ณผ ๊ฒฝ๊ธฐ๋„ 12๊ณณ์˜ ๋ณด์œก์‹œ์„ค ์•„๋™ ์ด 568๋ช…, ๋ณด์œก๊ต์‚ฌ ์ด 85๋ช…์„ ๋Œ€์ƒ์œผ๋กœ ํ•˜์˜€์œผ๋ฉฐ, ์‚ฌ์ „์„ค๋ฌธ์กฐ์‚ฌ, ํ”„๋กœ๊ทธ๋žจ ์‹œํ–‰, ์‚ฌํ›„์„ค๋ฌธ์กฐ์‚ฌ์˜ ์ˆœ์œผ๋กœ 12์ฃผ๊ฐ„ ์ง„ํ–‰๋˜์—ˆ๋‹ค. ์•„๋™์— ๋Œ€ํ•œ ํ”„๋กœ๊ทธ๋žจ ์ž์ฒด์˜ ํšจ๊ณผ๋ฅผ ๋ณด๊ธฐ ์œ„ํ•ด ์ด์ค‘์ฐจ์ด(Difference in defference, DID)๋ถ„์„ ๋ฐฉ๋ฒ•์„ ์ ์šฉํ•˜์—ฌ ์ค‘์žฌ ์ „ํ›„์˜ ๊ฐ์—ผ์„ฑ ์งˆํ™˜์œผ๋กœ ์ธํ•œ ์ด ์˜๋ฃŒ์ด์šฉ ์ผ์ˆ˜์™€ ๊ธฐ๋Šฅ์  ์ƒํƒœ์ธ ์ด ๊ฒฐ์„ ๋ฐ ์กฐํ‡ดโ€ข์ง€๊ฐ์ผ์ˆ˜์˜ ๋ณ€ํ™”๋ฅผ ๋ถ„์„ํ•˜์˜€์œผ๋ฉฐ, ๊ฒฐ๊ณผ๋ณ€์ˆ˜์— ์˜ํ–ฅ์„ ์ค„ ์ˆ˜ ์žˆ๋Š” ๋‹ค๋ฅธ ์„ค๋ช…๋ณ€์ˆ˜๋“ค์€ ์˜๊ณผ์ž‰-์Œ์ดํ•ญ-ํšŒ๊ท€๋ชจํ˜•์„ ํ†ตํ•ด ๋ณด์ •ํ•˜์˜€๋‹ค. ๋ณด์œก๊ต์‚ฌ์— ๋Œ€ํ•ด์„œ๋Š” ์ค‘์žฌ ์ „ํ›„ ๊ฐ์—ผ์— ๋Œ€ํ•œ ํƒœ๋„ ๋ณ€ํ™”๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ ์˜๋ฃŒ์ด์šฉ ์ผ์ˆ˜๋Š” ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•œ ์ฐจ์ด๋ฅผ ๋ณด์ด์ง€ ์•Š์•˜์œผ๋‚˜ ๊ฐ์†Œํ•œ ๋ฐฉํ–ฅ์˜ ๊ฒฐ๊ณผ๋ฅผ ๋‚˜ํƒ€๋‚ด์—ˆ๊ณ (IRR=0.97), ๊ฒฐ์„ ๋ฐ ์กฐํ‡ดโ€ข์ง€๊ฐ์ผ์ˆ˜๋Š” ์œ ์˜ํ•˜๊ฒŒ ๊ฐ์†Œํ•˜์˜€๋‹ค(IRR=0.37, p<.05). ๋‘ ๊ฒฐ๊ณผ๋ณ€์ˆ˜์—๋Š” ๊ณตํ†ต์ ์œผ๋กœ ์•„๋™์˜ ๊ณผ๊ฑฐ์งˆํ™˜ ์—ฌ๋ถ€์™€ ๋ณด์œก์‹œ์„ค ์ด์šฉ๊ธฐ๊ฐ„์ด ์œ ์˜ํ•œ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ธฐ๋Šฅ์  ์ƒํƒœ์— ์žˆ์–ด์„œ๋Š” ์—ฐ๋ น ๋ณ€์ˆ˜๋„ ์œ ์˜ํ•˜์˜€์œผ๋ฉฐ, ๋ณด์œก์‹œ์„ค์˜ ์œ ํ˜•๊ณผ ๊ทœ๋ชจ์— ๋”ฐ๋ผ์„œ๋„ ์œ ์˜ํ•œ ์ฐจ์ด๋ฅผ ๋ณด์˜€๋‹ค. ํ•œํŽธ, ๋ณด์œก๊ต์‚ฌ์˜ ๊ฐ์—ผ์— ๋Œ€ํ•œ ํƒœ๋„๋Š” ๋‘ ๊ตฐ๊ฐ„์— ์ดˆ๊ธฐ ๋™์งˆ์„ฑ ๊ฒ€์ •์—์„œ ์ฐจ์ด๊ฐ€ ์—†์—ˆ์œผ๋‚˜, ์ค‘์žฌ ํ›„์—๋„ ์œ ์˜ํ•œ ์ฐจ์ด๋ฅผ ๋ณด์ด์ง€ ์•Š์•˜๋‹ค. ์ฐธ์—ฌ ์•„๋™์˜ ํ•™๋ถ€๋ชจ๋“ค์€ ํ”„๋กœ๊ทธ๋žจ ๊ณผ์ • ํ‰๊ฐ€์˜ ์ผํ™˜์œผ๋กœ ์‹ค์‹œํ•œ ํ”„๋กœ๊ทธ๋žจ์˜ ์œ ์šฉ์„ฑ๊ณผ ๋‚ด์šฉ์— ๋Œ€ํ•œ ๋งŒ์กฑ๋„ ํ‰๊ฐ€์—์„œ ํ”„๋กœ๊ทธ๋žจ ๊ธฐ๊ฐ„์ด ์งง์•˜๋‹ค๋Š” ์‘๋‹ต ์™ธ์— ๋ชจ๋“  ๋ฌธํ•ญ์—์„œ ๊ธ์ •์ ์ธ ๋ฐ˜์‘์„ ๋ณด์˜€๋‹ค. DID ๋ฐฉ๋ฒ•์„ ์ด์šฉํ•˜์—ฌ ๋‘ ์ง‘๋‹จ์— ๊ณตํ†ต์ ์ธ ์ถ”์„ธํšจ๊ณผ์™€ ์‹œ๋ถˆ๋ณ€๋ณ€์ˆ˜๋ฅผ ํšจ๊ณผ์ ์œผ๋กœ ํ†ต์ œํ•œ ๋ณธ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ์—์„œ ๋ณด์œก์‹œ์„ค ํ•œ์˜์‚ฌ ์ฃผ์น˜์˜ ํ”„๋กœ๊ทธ๋žจ์€ ๋น„๊ต์  ์งง์€ ์ค‘์žฌ ๊ธฐ๊ฐ„์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ๊ฐ์—ผ์„ฑ ์งˆํ™˜์˜ ์˜ˆ๋ฐฉ๊ณผ ๊ด€๋ฆฌ์— ์žˆ์–ด ์ผ๋ถ€ ํšจ๊ณผ์ ์ž„์„ ์‹œ์‚ฌํ•˜์˜€๋‹ค. ๋”ฐ๋ผ์„œ ์ถ”ํ›„ ํ”„๋กœ๊ทธ๋žจ์„ ๋ณด์™„ํ•˜์—ฌ ์ผ์ฐจ์˜๋ฃŒ ๋ฐ ๊ณต๊ณต๋ณด๊ฑด ์˜์—ญ์—์„œ ํ•œ์˜์‚ฌ ์ฃผ์น˜์˜์™€ ๋ณด์œก์‹œ์„ค ์—ฐ๊ณ„๋ฅผ ์ถ”์ง„ํ•˜๋ฉด ๋ณด์œก์‹œ์„ค ์•„๋™์˜ ๊ฑด๊ฐ•์ฆ์ง„์— ๊ธฐ์—ฌํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋‹ค.์ œ 1 ์žฅ ์„œ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ ๋ฐ ํ•„์š”์„ฑ 1 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ๋ชฉ์  3 ์ œ 3 ์ ˆ ์—ฐ๊ตฌ๊ฐ€์„ค 3 ์ œ 4 ์ ˆ ๊ฐœ๋… ์ •์˜ 3 ์ œ 5 ์ ˆ ๋ฌธํ—Œ ๊ณ ์ฐฐ 5 ์ œ 2 ์žฅ ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 12 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ์„ค๊ณ„ 12 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ๋Œ€์ƒ ๋ฐ ๊ธฐ๊ฐ„ 19 ์ œ 3 ์ ˆ ์—ฐ๊ตฌ๋„๊ตฌ 20 ์ œ 4 ์ ˆ ์ž๋ฃŒ์ˆ˜์ง‘ ๋ฐ ๋ถ„์„๋ฐฉ๋ฒ• 22 ์ œ 5 ์ ˆ ์—ฐ๊ตฌ ์œค๋ฆฌ 26 ์ œ 3 ์žฅ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ 27 ์ œ 1 ์ ˆ ์ผ๋ฐ˜์  ํŠน์„ฑ ๋ฐ ์‚ฌ์ „ ๋™์งˆ์„ฑ ๊ฒ€์ • 27 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ๊ฐ€์„ค ๊ฒ€์ • 35 ์ œ 3 ์ ˆ ํ”„๋กœ๊ทธ๋žจ ๋งŒ์กฑ๋„ ํ‰๊ฐ€ 39 ์ œ 4 ์žฅ ๊ณ ์ฐฐ 41 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ ๋ฐฉ๋ฒ•์— ๋Œ€ํ•œ ๊ณ ์ฐฐ 41 ์ œ 2 ์ ˆ ํ”„๋กœ๊ทธ๋žจ์˜ ํšจ๊ณผ ํ‰๊ฐ€ 46 ์ œ 3 ์ ˆ ์—ฐ๊ตฌ์˜ ์ œํ•œ์  50 ์ œ 4 ์ ˆ ์—ฐ๊ตฌ์˜ ์˜์˜ 51 ์ œ 5 ์žฅ ๊ฒฐ๋ก  ๋ฐ ์ œ์–ธ 52 ์ œ 1 ์ ˆ ๊ฒฐ๋ก  52 ์ œ 2 ์ ˆ ์ œ์–ธ 52 ์ฐธ๊ณ ๋ฌธํ—Œ 54 Abstract 74Maste

    ๅœ‹ๅฎถ็ซถ็ˆญๅ„ชไฝๅ‘ไธŠ์„ ์œ„ํ•œ ็ตฑๅˆ์  ๆŽฅ่ฟ‘ๆณ•: ๆฑไบž็ดฐไบž ็ถ“ๆฟŸ์˜ ๆˆๅŠŸ่ฆๅ› ์— ๋Œ€ํ•œ ๅˆ†ๆž - ้Ÿ“ๅœ‹์˜ ็™ผๅฑ•์„ ไธญๅฟƒ์œผ๋กœ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๊ตญ์ œ๋Œ€ํ•™์› : ๊ตญ์ œํ•™๊ณผ, 2014. 8. ๋ฌธํœ˜์ฐฝ.The classical economic theories focus on inherited advantages and their effective utilization when explaining economic development. However, countries that possess advantage show wide discrepancies in their levels of developmentsome have grown rich but others have stayed poor. In order to promote economic and social advancement of less developed countries (LDCs), developed countries and international organizations launched various development activities and programs. Despite these aids, however, their performances vary. This research is dedicated to find the critical factors that caused such different outcomes by mainly focusing on the case of Korea. This dissertation consists of three main parts. In Part I, important economic and business literature on the elements of economic development and success are reviewed, followed by the limitations of the earlier studies. This naturally leads to the need of a new approach for explaining economic development. In Part II, a new approach called the ABCD framework by Hwy-Chang Moon (2012), is presented and a rigorous theoretical support is provided. Later, the validity of this new approach is tested statistically. In Part III, the economic developments of Koreas automobile and film industries are analyzed by using the newly proposed approach, with a special attention to government intervention and industrial policies. Lastly, a summary of the new approach, discussion on the results, and important implications derived from this research are presented. International trade theories, which have the foundations from the work by Adam Smith, assume that a nation has an advantage and should focus on an intensive use of advantageous factors. However, these theories cannot explain two problemsfirst, the different level of economic development of countries with similar natural endowments and second, the development initiatives of a country that does not possess any advantage in factors of production. Productivity theorists emphasized the importance of upgraded labor through education, training, capital investment, and technology progress derived from the best-practice. However, productivity theories cannot fully explain the economic development of LDCs, since good universities, research institutes, or accumulated capitals for upgrading labor, or best-practices are not usually found in LDCs. As commonly known, during the 1960s and 1970s when the newly industrialized countries in Asia, such as Korea, took-off, they did not have these conditions. Another popular approach is on culture. Scholars such as Hofstede (1997), Schein (1998), and Trompenaars (1998) treated culture as a national characteristic which does not easily change. This means the cultural approach cannot explain the difference between ex-ante and ex-post of economic development. Porterian scholars such as Porter (1990) and Moon, Rugman, and Verbeke (1995, 1998) cleverly integrated the important variables determining a nations competitiveness into one model and most other theories represent subsets of Porters comprehensive model. While Porterian approach based on the diamond model brilliantly and systematically classified significant factors of economic development, it cannot explain the underlying force that strengthens or weakens each determinant of the diamond. Based on the empirical studies, Moon (2012) proposed a new framework which explains the fundamental factors that enhance the determinants of economic development. This is called the ABCD framework and consists of four factors: Agility, Benchmarking, Convergence, and Dedication. Agility refers to how fast and accurately a process of business is done and has two sub-factors which are speed and precision. Benchmarking is defined as the search for an industrys best practices that will lead to superior performance. Under this perspective, benchmarking is categorized into two componentsโ€”imitation and global standard. Convergence is a good mixture of resources and capabilities, and is classified into mixing and synergy-creation. Lastly, dedication means that people work hard and have extra commitment and loyalty for the work. This can is divided into diligence and goal-orientation. In order to prove statistically, this dissertation chooses relevant proxies that can represent each sub-factor and conducts an empirical test with statistical data. Each sub-factor of the ABCD is measured by two criteria, and the values of Cronbachs Alpha for the eight sub-factors are mostly larger than 0.7 except for diligence. This implies that the criteria measure well for each sub-factor, and the consistency is high among other criteria. This study employs two statistical methods: ANOVA and regression. First, ANOVA is utilized to compare the difference between developed and developing countries in terms of four factors of ABCD. Then by using regression, the influences of these factors to economic development are analyzed. All of the four factors show significant difference between developing and developed countries. The dependent variable is GDP per capita, and the independent variables are the ABCD and control variables. The result of the test implies that each ABCD variable explains the difference in GDP per capita among countries. The ABCD frameworks applicability is also demonstrated to explain the development and evolution of two Korean industries: The automobile industry, one of the most important manufacturing industries, and the film industries, a resurging industry as part of the Korean Wave which has been attracting much attention from all over the world to Korea. In 1955, Koreas automobile industry started with a car called Sibal, built on the basis of an abandoned Willys Jeep and other spare parts from the U.S. military. A short time later, Korea started to assemble cars with imported CKD (completely knock-down) kit and to form partnerships with foreign companies. As time passed by, the whole industry changed its function from a simple assembler to automobile developer and the first Korean-developed automobile, Hyundai Pony was produced in 1976. Although Koreas automobile industry faced turmoil during the Asian financial crisis in 1997, Koreas automobile companies were recovered quickly, increased production and exports. According to the International Organization of Motor Vehicle Manufacturers, Korea is the fifth-largest in the world measured by automobile unit production and Hyundai, with its affiliate Kia Motors, is the worlds fifth-biggest auto maker by sales in 2013. Unlike other developing countries, Korean government encouraged to have its own national model car within relatively short time from the beginning of industrialization, despite the nations lack of skills and technology. Under this government effort, partnerships with foreign companies were promoted, although the government prohibited direct investment by foreign companies into Korea. Through CKD kits and partnerships with foreign companies, Korea could learn manufacturing skills and accumulate important technologies. Government aimed to have horizontal integration among manufacturers and auto-parts producers, and these companies formed vertical integration which accelerated car producing capability more effectively. Since Korea did not have enough capital needed for economic development to start with, Korea was motivated with a strong desire for developing its own cars and exporting them to earn foreign hard currency. Unlike the automobile industry that has prospered until today, the Korean film industry enjoyed a golden age between the late 1950s and mid-1960s. In the following two decades, there was a dark age due to interventions by the governments market-distorting policy. As a result, the market share of Korean films decreased unprecedentedly. Especially, their market share in 1993 recorded 15.9%, the lowest ever in the history, after Hollywood production companies began to distribute their films directly into Korea. From the late 1990s, Korea opened its market and changed its view on the film industry from cultural to commercial sector. In competition against foreign films, Korean films resurged and started to be recognized internationally. Particularly, along with dramas, the film industry was one of the strong drivers for Hallyu, the Korean wave, which implies the popular trend of Koreas entertainment industry. There are two booms in the history of Koreas film industry: One, from the late 1950s to the mid-1960s and the other, after late 1990s until now. The agility, benchmarking, convergence, and dedication are useful to explain the success of this industry during these resurgent periods. A number of Korea filmmakers quickly learned American technology in the early phase. This allowed them to accumulate producing technology. With this technology, Korean film producers added Korean features to attract domestic audience. To achieve success from the early stage, the government employed various measures, aiming to make the industry self-sustainable by reinvesting profits gained from exportation. From the late 1990s until now, the ABCD framework can explain the success of Korean film industry more evidently. Around this time, private companies and government worked together for the success of industry within fairly short time span by investing huge amount of money in the infrastructure and production. Having been influenced immensely by American films and Hollywood companies, Koreas film industry imitated the storyline of American films and their distribution channel. However, Korean films and companies did not just imitate Hollywood films and business strategies, but also added more Korean-ness. Behind all the measures, there is a high dedication to foster the industry and to achieve success. It is noteworthy that the industrial policy of Korea was always export-oriented to overcome and improve beyond the industrys current status. Possessing abundant population, natural resources, and technology does not guarantee economic success. These concepts are included in the diamond model of Porter who emphasized the importance of competitive advantage of nations. However, this approach is limited to explain the initial development of East Asian countries as well as that of other advanced countries. The ABCD framework explains more comprehensively the economic achievement of these countries. Through rigorous theoretical review, statistical analysis, and case studies, these strategic variables are proven to be useful in enhancing industrial, corporate and national competitiveness. These findings can also give important implications for the economic planning of other countries.Abstract Introduction: The Need for a New Approach PART I. FOUNDATIONS 1. Rationales for Economic Prosperity 1: Classical Approaches 1.1 International trade theories 1.2 Productivity theories 2. Rationales for Economic Prosperity 2: Modern Approaches 2.1 Dynamic approaches 2.2 Sociological and other approaches 3. Rationales for Economic Prosperity 3: Porterian Approaches 3.1 The diamond model 3.2 The generalized double diamond model 4. The Need for a New Approach to Competitive Advantage 4.1 Problems of existing theories and need for a new approach PART II. NEW APPROACH 5. The ABCD Framework 5.1 The dynamics of the economic forces 5.1.1 Agility: Speed and precision 5.1.2 Benchmarking: Imitation and global standard 5.1.3 Convergence: Mixing and synergy-creation 5.1.4 Dedication: Diligence and goal-orientation 5.2 Theoretical back-ups 5.2.1 Agility: Speed and precision 5.2.2 Benchmarking: Imitation and global standard 5.2.3 Convergence: Mix and synergy-creation 5.2.4 Dedication: Diligence and goal-orientation 5.2.5 Comprehensiveness of the ABCD framework 6. Empirical Evidences 6.1 Operationalization of ABCD 6.1.1 Agility 6.1.2 Benchmarking 6.1.3 Convergence 6.1.4 Dedication 6.1.5 Reliability analysis 6.2 Variables 6.2.1 Dependent variable 6.2.2 Explanatory and control variables 6.3 Data and samples 6.4 Analysis methodology 6.5 Results 6.5.1 Results for cluster analysis 6.5.2 Results for ANOVA 6.5.3 Results for regression analysis 6.6 Discussion PART III. DEVELOPMENT OF KOREAN INDUSTRIES 7. Koreas Automobile Industry 7.1 Introduction to Koreas automobile industry 7.2 From liberation to Rhee Syngman regime (1945-1960) 7.2.1 Domestic and international circumstances 7.2.2 Evolutions of policies and business/corporate strategies 7.3 Park Chung-hee regime 1 (1962-1972) 7.3.1 Domestic and international circumstances 7.3.2 Evolutions of policies and business/corporate strategies 7.4 Park Chung-hee regime 2 (1973-1979) 7.4.1 Domestic and international circumstances 7.4.2 Evolutions of policies and business/corporate strategies 7.5 From Chun Doo-hwan to Roh Tae-woo regimes (1980-1992) 7.5.1 Domestic and international circumstances 7.5.2 Evolutions of policies and business/corporate strategies 7.6 From Kim Young-sam to Kim Dae-jung regimes (1993-2002) 7.6.1 Domestic and international circumstances 7.6.2 Evolutions of policies and business/corporate strategies 7.7 From Roh Moo-hyun to Lee Myung-bak regimes (2003-2013) 7.7.1 Domestic and international circumstances 7.7.2 Evolutions of policies and business/corporate strategies 7.8 The Dynamics of the forces 8. Koreas Film Industry 8.1 Introduction to Koreas film industry 8.2 From liberation to Rhee Syngman regime (1945-1960) 8.2.1 Domestic and international circumstances 8.2.2 Evolutions of policies and business/corporate strategies 8.3 Park Chung-hee regime 1 (1962-1972) 8.3.1 Domestic and international circumstances 8.3.2 Evolutions of policies and business/corporate strategies 8.4 Park Chung-hee regime 2 (1973-1979) 8.4.1 Domestic and international circumstances 8.4.2 Evolutions of policies and business/corporate strategies 8.5 From Chun Doo-hwan to Roh Tae-woo regimes (1980-1992) 8.5.1 Domestic and international circumstances 8.5.2 Evolutions of policies and business/corporate strategies 8.6 From Kim Young-sam to Kim Dae-jung regimes (1993-2002) 8.6.1 Domestic and international circumstances 8.6.2 Evolutions of policies and business/corporate strategies 8.7 From Roh Moo-hyun to Lee Myung-bak regimes (2003-2013) 8.7.1 Domestic and international circumstances 8.7.2 Evolutions of policies and business/corporate strategies 8.8 The dynamics of the forces Conclusion Bibliography Appendices 1. Data sets for ABCD 2. Dependent (GDP per capita, ppp) and control variables 3. Evolution of Koreas automobile companies 4. Motor vehicle production of Korea (1955-2012) 5. Motor vehicle export of Korea (1975-2012) 6. Korean film industry trends (1960-2013) 7. Korean film export trends (1970-2002) Chronology 1. Koreas automobile industry 2. Koreas film industryDocto

    ๋ง๊ฐ„์˜ ๊ตฌ์กฐ์™€ ์‚ฐํ™”์ˆ˜๊ฐ€ ์‚ฐ์†Œ ๋ฐœ์ƒ ์ด‰๋งค ์ž‘์šฉ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์žฌ๋ฃŒ๊ณตํ•™๋ถ€, 2014. 2. ๋‚จ๊ธฐํƒœ.The development of a water oxidation catalyst has been a demanding challenge for the realization of overall water-splitting systems. The asymmetric geometry and flexible ligation of the biological Mn4CaO5 cluster are important properties for the function of photosystem II, and these properties can be applied to the design of a new inorganic water oxidation catalyst. In part I, we identified a new crystal structure, Mn3(PO4)2-3H2O, that precipitates spontaneously in aqueous solution at room temperature and demonstrated its superior catalytic performance at neutral pH. Computational analysis indicated that phosphate ligations in our crystal make Mn-O bonding longer and more distorted than in other Mn-based oxides. Such structural flexibility can stabilize Jahn-Teller distorted Mn(III) and thus facilitate Mn(II) oxidation, as monitored by electron paramagnetic resonance spectroscopy. Moreover, although intensive studies have explored the role of Mn element in water oxidation catalysis, it has been difficult to understand whether the catalytic capability originates mainly from either the Mn arrangement or the Mn valency. In part II, to decouple these two factors and to investigate the role of Mn valency on catalysis, we selected a new pyrophosphate-based Mn compound (Li2MnP2O7), which has not been utilized for water oxidation catalysis to date, as a model system. Due to the monophasic behavior of Li2MnP2O7 with the delithiation, the Mn valency of Li2-xMnP2O7 (x = 0.3, 0.5, 1) can be controlled with negligible change in crystal framework (e.g. volume change ~ 1 %). Interestingly, we observed that as the averaged oxidation state of Mn in Li2-xMnP2O7 increases from 2 to 3, the catalytic performance is enhanced in the series Li2MnP2O7 < Li1.7MnP2O7 < Li1.5MnP2O7 < LiMnP2O7. Moreover, Li2MnP2O7 itself exhibits superior catalytic performance compared with MnO or MnO2 because of the highly distorted Mn geometry in Li2MnP2O7. In summary, we selected Mn3(PO4)2-3H2O and Li2-xMnP2O7 compounds as artificial platforms for understanding the effect of Mn structure and valency on water oxidation catalysis, respectively. We think that this study presents valuable guidelines for developing an efficient Mn-based catalyst which can be comparable with the biological Mn4CaO5 cluster in photosystem II under neutral conditions with controlled Mn valency and atomic arrangement.List of Tables 10 List of Figures 11 Chapter 1 Introduction 17 1.1 Energy Crisis and Demand for renewable energy 17 1.2 Water splitting 19 1.3 Oxygen Evolution reaction(OER) 21 1.3.1 Noble metal based OER electrocatalysts 24 1.3.2 Transition metal (Co,Ni,Cu,Fe) based OER electrocatalysts 26 1.4 Manganese based OER electrocatalysts 30 1.4.1 Photosystem II in biological system 30 1.4.2 Bio-inspired Mn based OER electrocatalysts 31 1.4.3 Bottleneck in Mn based electrocatalysts in OER 36 1.4.4 Importance for understanding the effect of Mn valency And Structure on water oxidation catalysis 37 Chapter 2 Mn3(PO4)2-3H2O : Effect on Mn structure 41 2.1 Experimental and Procedure 41 2.1.1 Synthesis and Materials 41 2.1.2 Characterization 42 2.1.2.1 Powder X-ray diffraction 42 2.1.2.1 ICP/MS 42 2.1.2.2 Rietveld analysis 43 2.1.2.3 Scanning electron microscopy(SEM) analysis 43 2.1.2.4 Transmission electron microscopy (TEM) analysis 44 2.1.2.5 BrunauerEmmettTeller (BET) method 44 2.1.3 Electrochemical analysis 46 2.1.3.1 Cyclic Voltammetry (CV) 46 2.1.3.2 Gas Chromatography (GC) 47 2.1.3 Electron paramagnetic resonance (EPR) spectroscopy 49 2.1.4 DFT calculation 51 2.2 Results and Discussions 52 2.2.1 Structural Characterization of Mn3(PO4)2-3H2O 52 2.2.2 Electrochemical analysis of Mn3(PO4)2-3H2O 64 2.2.3 Mechanistic studies of Mn3(PO4)2-3H2O 75 Chapter 3 Li2-xMnP2O7 (x= 0~1): Effect on Mn Valency 81 3.1 Experimental and Procedure 81 3.1.1 Synthesis and Material 81 3.1.2 Characterization 81 3.1.2.1 ICP/MS 82 3.1.2.2 Powder X-ray diffraction, Full-pattern matching 82 3.1.2.3 X-ray photon spectroscopy (XPS) 82 3.1.2.4 Transmission electron microscopy (TEM) analysis 83 3.1.2.5 BrunauerEmmettTeller (BET) method 83 3.1.3 Electrochemical analysis 84 3.1.4 DFT calculation 86 3.2 Results and Discussion 87 3.2.1 Structural Characterization of Li2-xMnP2O7 (x=0~1) 87 3.2.2 Electrochemical analysis of Li2-xMnP2O7 (x=0~1) 93 3.2.3 Mechanistic studies of Li2-xMnP2O7 (x=0~1) 112 Chapter 4 Conclusion 128 References 130 ๊ตญ๋ฌธ์ดˆ๋ก 138 ๊ฐ์‚ฌ์˜ ๊ธ€ (Acknowledgement) 140Maste

    Clonal Fertility Variation and Genetic Characteristics at the Seed Orchards of Chamaecyparis obtusa in Gochang and Seogwipo, Korea

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๋†์—…์ƒ๋ช…๊ณผํ•™๋Œ€ํ•™ ๋†๋ฆผ์ƒ๋ฌผ์ž์›ํ•™๋ถ€, 2023. 2. ๊ฐ•๊ทœ์„.Chamaecyparis obtusa is a major tree species for wood production in Korea. It is straight and light and is used for interior and ship materials. It also has a scent and gloss, so widely used as a park or garden tree. In addition, it has various functional substances such as oil extracted from wood and fragrances extracted from cones. Therefore, it has recently been spotlighted as a preferred tree for afforestation, and planting is being attempted in various parts the country. C. obtusa is the most well-known species that can live in warm temperate zones, but the survival rate of planted trees tends to decrease significantly with climate. Therefore, it is urgent to supply excellent seeds and seedlings that can adapt to various climates. Seed orchards, the basis of forest tree breeding, are established to produce stably and supply genetically improved seeds. Genetic improvement refers to maximizing the characteristics and genetic structures of plus trees to be improved by transferring it on to the next generation (seed). By estimating the production capacity and contribution among clones and analyzing the genetic characteristics involved in the seed production process, the quality of seed orchard seeds can be proved and effective seed management methods can be suggested. This study was conducted to quantify some reproductive traits of C. obtusa. Over the past three years (2020~2022), the reproductive characteristics of 61 and 23 clones were surveyed in the seed orchards at Gochang and Seogwipo, Korea. The seed orchards were established in 2015 and 1969, respectively. In this study, the clonal contributions of male and female strobilus, and cone productions were estimated. It has been clearly shown that female and male parents contributed unequally to the gamete gene pool. Among the 61 clones at the seed orchard of Gochang, 12 to 15 clones (20 to 25% of the total) and 6 to 9 clones (10 to 15% of the total) produced 50% female and male strobili, respectively. The effective population numbers of female and male strobilus ranged from 23.64 (2021) to 37.38 (2022) and from 15.52 (2021) to 19.84 (2022) at gamete level, respectively. The effective population numbers at zygote (cone) level ranged from 20.15 (2022) to 35.94 (2021). Among the 23 clones at the seed orchard of Seogwipo, 1 to 5 clones (5 to 21% of the total) and 1 to 3 clones (5 to 15% of the total) produced 50% female and male strobili, respectively. Compared with the previous reports of other species, fewer clones contributed to the reproductive process in the seed orchards of C. obtusa. The effective population numbers of female and male strobilus ranged from 6.4 (2021) to 15.45 (2022) and from 4.32 (2021) to 9.58 (2022) at gamete level, respectively. The effective population numbers at zygote (cone) level ranged from 7.3 (2020) to 10.71 (2021), compared with the gamete level, more clones had contributed to reproductive process in the Seogwipo seed orchards. The individual heritabilities of female and male strobilus, and cone production ranged from 0.150 (2022) to 0.306 (2021), from 0.161 (2020) to 0.326 (2021), from 0.013 (2022) to 0.133 (2020), respectively in the seed orchard of Gochang. At the seed orchard of Seogwipo, the individual heritabilities of female and male strobilus, and cone production were estimated from 0.086 (2022) to 0.297 (2021), from 0.077 (2021) to 0.489 (2020), from 0.156 (2022) to 0.408 (2021), respectively. In both seed orchards, the clonal heritabilities were estimated to be higher than the individual heritabilities. The strobilus and cone production were positively correlated and statistically significant, except for the male strobilus and cone production at the seed orchard of Seogwipo in 2020. A total of 10 cones were collected per each individual tree for cone analysis over two consecutive years (2020โˆผ2021). At the seed orchard of Gochang, the cones were analyzed to have 72.69% full-filled seeds, and 27.30% empty seeds, and 11.57% aborted ovules, so the seed efficiency was estimated to be 57.96% in 2020. In 2021, the cone had 56.43% full-filled seeds, and the 43.57% empty seeds, showing similar proportions of the full-filled seeds and empty seeds. The seed efficiency was estimated to be 46.98% that was slightly lower than in 2020. The germination rate per cone was very low with an average of 5.09%. The cones had 9.46% full-filled seeds, 90.54% empty seeds, and 33.06% aborted ovules. The seed efficiency was estimated to be 7.51% in 2020. In 2021, the cones had 25.77% full-filled seeds, 73.23% empty seeds, and 3.33% aborted ovules. Seed efficiency was higher than that in 2020, but the amount of full-filled seeds was lower. The average germination rate per clone was very low at 3.13%, which was similar to that of the seed orchard of Gochang. Parameters of the mating system and pollen flow were estimated using eleven nuclear microsatellite markers. At the seed orchard of Gochang, the expected heterozygosity (He) and the observed heterozygosity (Ho) were 0.740 and 0.796, respectively, in mother trees. The He and Ho were 0.702 and 0.765, respectively in seeds. Fixation indices (F) were -0.062 and -0.087 in mother trees and seeds, respectively. At the seed orchard of Seogwipo, the He and Ho were 0.683 and 0.667 in mother trees, and those were 0.704 and 0.826 in seeds, respectively. Fixation indices (F) were 0.037 in mother trees and -0.084 in seeds. From the analysis using MLTR, the outcrossing rate (tm), the biparental inbreeding (tm-ts), and the correlation of paternity (rp) were estimated to be 0.982, 0.028, and 0.172, respectively, at the seed orchard of Gochang. These values were similar to those analyzed using microsatellite markers in other Pinus species. At the seed orchard of Seogwipo, the tm, the (tm-ts), and the rp were 1.000, 0.059, and 0.064, respectively. From the analysis using CERVUS, the averages of outcrossing rate, pollen contamination rate, and selfing rate were estimated to be 94.21, 1.1, and 4.69%, respectively. The average number of pollen donors was 11.1 at the seed orchard of Gochang. The averages of outcrossing rate and selfing rate were 95.14 and 4.86%, respectively, at the seed orchard of Seogwipo. The average number of pollen donors was 10.8. Using TwoGener model for optimal pollen dispersal with the effective density of 130 trees per ha, the genetic differentiation level in pollen pool structure was estimated to be 0.134 at the seed orchard of Gochang. The average radial distance of pollen flow was calculated as 5.58 m. At the seed orchard of Seogwipo, the genetic differentiation level in pollen pool structure was estimated to be 0.330 with the effective density of 125 trees per ha. The average radial distance of pollen flow was calculated as 3.89 m. As the effective pollen dispersal in the population might be restricted, the amount of genetic variation could be maintained in each generation without loss of genetic diversity caused by selfing or inbreeding in seedlings at the seed orchard of Gochang and Seogwipo. The genetic diversity of pollen pool might be high at the seed orchard of Seogwipo, but the number of pollen donors at the seed orchard of Gochang were similar in the natural populations. Therefore, pollen donors should be managed to increase genetic diversity under completely random mating conditions at the seed orchard of Gochang.ํŽธ๋ฐฑ์€ ์šฐ๋ฆฌ๋‚˜๋ผ์˜ ๋ชฉ์žฌ ์ƒ์‚ฐ์„ ์œ„ํ•œ ์ฃผ์š” ์ˆ˜์ข…์œผ๋กœ, ํ†ต์งํ•˜๊ณ  ๊ฐ€๋ฒผ์šฐ๋ฉฐ ํ–ฅ๊ธฐ์™€ ๊ด‘ํƒ์ด ์žˆ์–ด ๋‚ด์žฅ์žฌ, ์„ ๋ฐ•์žฌ ๋“ฑ์œผ๋กœ ์‚ฌ์šฉ๋˜๊ณ  ๊ณต์›์ˆ˜๋‚˜ ์ •์›์ˆ˜๋กœ๋„ ๋„๋ฆฌ ์ด์šฉ๋œ๋‹ค. ๋˜ํ•œ ์ •์œ ์™€ ํ–ฅ๋ฃŒ ๋“ฑ ๋‹ค์–‘ํ•œ ๊ธฐ๋Šฅ์„ฑ ๋ฌผ์งˆ์ด ๋งŽ์•„ ์ตœ๊ทผ ์กฐ๋ฆผ ์„ ํ˜ธ ์ˆ˜์ข…์œผ๋กœ ์ฃผ๋ชฉ๋ฐ›๊ณ  ์žˆ์œผ๋ฉฐ ๋‹ค์–‘ํ•œ ์ง€์—ญ์—์„œ ์‹์žฌ๋ฅผ ์‹œ๋„ํ•˜๊ณ  ์žˆ๋‹ค. ํ•˜์ง€๋งŒ ๋‚œ๋Œ€ ์ˆ˜์ข…์œผ๋กœ ๊ธฐํ›„์— ๋”ฐ๋ผ ์กฐ๋ฆผ๋ชฉ์˜ ์ƒ์กด์œจ์ด ๋งค์šฐ ๊ฐ์†Œํ•˜๋Š” ๊ฒฝํ–ฅ์„ ๋‚˜ํƒ€๋‚ด๊ธฐ ๋•Œ๋ฌธ์— ๋‹ค์–‘ํ•œ ๊ธฐํ›„์— ์ ์‘์ด ๊ฐ€๋Šฅํ•œ ์šฐ์ˆ˜ ์ข…์ž ๋ฐ ์ข…๋ฌ˜์˜ ๋ณด๊ธ‰์ด ์‹œ๊ธ‰ํ•˜๋‹ค. ์ž„๋ชฉ ์œก์ข…์˜ ๋ฐ”ํƒ•์„ ์ด๋ฃจ๋Š” ์ฑ„์ข…์›์˜ ์กฐ์„ฑ ๋ชฉ์ ์€ ์œ ์ „์ ์œผ๋กœ ๊ฐœ๋Ÿ‰๋œ ์ข…์ž๋ฅผ ์•ˆ์ •์ ์œผ๋กœ ์ƒ์‚ฐํ•˜๊ณ  ๋ณด๊ธ‰ํ•˜๋Š” ๋ฐ ์žˆ๋‹ค. ์œ ์ „์  ๊ฐœ๋Ÿ‰์€ ์ˆ˜ํ˜•๋ชฉ์œผ๋กœ ์ฆ์‹๋œ ์ฑ„์ข…๋ชฉ ๊ฐ„ ์ž์—ฐ ๊ต๋ฐฐ๋ฅผ ํ†ตํ•ด ์ƒ์‚ฐ๋œ ์ฐจ๋Œ€(์ข…์ž)๋กœ ๊ฐœ๋Ÿ‰ํ•˜๊ณ ์ž ํ•˜๋Š” ๋ชจ์ˆ˜์˜ ํŠน์„ฑ๊ณผ ์œ ์ „ ๊ตฌ์กฐ๊ฐ€ ์ „์ด๋˜์–ด ๊ทน๋Œ€ํ™”๋˜๋Š” ๊ฒƒ์„ ์˜๋ฏธํ•œ๋‹ค. ์ด์™€ ๊ด€๋ จํ•˜์—ฌ ํด๋ก  ๊ฐ„ ๋ฐฐ์šฐ์ž ์ƒ์‚ฐ ๋Šฅ๋ ฅ๊ณผ ๊ธฐ์—ฌ๋„๋ฅผ ์ถ”์ •ํ•˜๊ณ , ์ด๋“ค์˜ ์ข…์ž ์ƒ์‚ฐ ๊ณผ์ •์— ๊ด€์—ฌํ•˜๋Š” ์œ ์ „ ํŠน์„ฑ์„ ๋ถ„์„ํ•จ์œผ๋กœ์จ ์ฑ„์ข…์›์‚ฐ ์ข…์ž์˜ ํ’ˆ์งˆ์„ ์ฆ๋ช…ํ•˜๊ณ  ํšจ๊ณผ์ ์ธ ์ฑ„์ข…์› ๊ด€๋ฆฌ ๋ฐฉ์•ˆ์„ ์ œ์‹œํ•  ์ˆ˜ ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” 1969๋…„์— ์กฐ์„ฑ๋œ ์„œ๊ท€ํฌ ํŽธ๋ฐฑ ์ฑ„์ข…์›๊ณผ 2015๋…„์— ์กฐ์„ฑ๋œ ๊ณ ์ฐฝ ํŽธ๋ฐฑ ์ฑ„์ข…์›์—์„œ 3๋…„๊ฐ„(2020~2022๋…„) ๊ฐœํ™”๋Ÿ‰ ๋ฐ ๊ตฌ๊ณผ ์ƒ์‚ฐ๋Ÿ‰์„ ์กฐ์‚ฌํ•˜์—ฌ ์–ป์€ ์ž๋ฃŒ๋ฅผ ํ† ๋Œ€๋กœ ์ƒ์‹ ๊ณผ์ •์— ๊ด€๊ณ„๋œ ๋ช‡ ๊ฐ€์ง€ ํŠน์„ฑ์„ ๊ณ„๋Ÿ‰ํ™”ํ•˜์˜€๋‹ค. ๊ณ ์ฐฝ ์ฑ„์ข…์›์—์„œ์˜ ๊ฒฝ์šฐ 61๊ฐœ ํด๋ก  ์ค‘ ์ „์ฒด ๊ฐœํ™”๋Ÿ‰์˜ 50%์— ๊ธฐ์—ฌํ•˜๋Š” ์•”๊ตฌํ™”์˜ ์ƒ๋Œ€์ ์ธ ๋น„์œจ์€ 20~25%์ด์—ˆ์œผ๋ฉฐ, ์ˆ˜๊ตฌํ™”์˜ ์ƒ๋Œ€์ ์ธ ๋น„์œจ์€ 10~15%๋กœ ๋‚˜ํƒ€๋‚˜ ์•”๊ตฌํ™”๊ฐ€ ์ˆ˜๊ตฌํ™”๋ณด๋‹ค ๋‹ค์†Œ ๋†’๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋ฐฐ์šฐ์ฒด ์ˆ˜์ค€์—์„œ ์œ ํšจ ์ง‘๋‹จ ํฌ๊ธฐ๋Š” ์•”๊ตฌํ™”์˜ ๊ฒฝ์šฐ 23.64(2021)~37.38(2022๋…„) ์ด์—ˆ์œผ๋ฉฐ, ์ˆ˜๊ตฌํ™”๋Š” 15.52(2021)~19.84(2022๋…„)๋กœ ์•”๊ตฌํ™”๋ณด๋‹ค ๋‹ค์†Œ ๋‚ฎ๊ฒŒ ์ถ”์ •๋˜์—ˆ๊ณ , ๊ตฌ๊ณผ ์ˆ˜์ค€์—์„œ๋Š” 20.15(2022)~35.94(2021๋…„)๋กœ ์ถ”์ •๋˜์—ˆ๋‹ค. ์„œ๊ท€ํฌ ์ฑ„์ข…์›์—์„œ๋Š” 23๊ฐœ ํด๋ก  ์ค‘ ์ „์ฒด ๊ฐœํ™”๋Ÿ‰์˜ 50%์— ๊ธฐ์—ฌํ•˜๋Š” ์•”๊ตฌํ™”์˜ ์ƒ๋Œ€์ ์ธ ๋น„์œจ์ด 5~21%์ด์—ˆ์œผ๋ฉฐ, ์ˆ˜๊ตฌํ™”์˜ ์ƒ๋Œ€์ ์ธ ๋น„์œจ์€ 5~15%๋กœ ๋‚˜ํƒ€๋‚˜ ๊ณ ์ฐฝ ์ฑ„์ข…์›์—์„œ์™€ ๋งˆ์ฐฌ๊ฐ€์ง€๋กœ ์•”๊ตฌํ™”๊ฐ€ ์ˆ˜๊ตฌํ™”๋ณด๋‹ค ๋‹ค์†Œ ๋†’๊ฒŒ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ ์†Œ์ˆ˜ ํด๋ก ์— ์˜ํ•ด ํŽธ์ค‘๋˜๋Š” ํ˜„์ƒ์ด ๋‹ค๋ฅธ ์ˆ˜์ข…์— ๋น„ํ•˜์—ฌ ๋†’๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋ฐฐ์šฐ์ฒด ์ˆ˜์ค€์—์„œ ์œ ํšจ ์ง‘๋‹จ ํฌ๊ธฐ๋Š” ์•”๊ตฌํ™”์˜ ๊ฒฝ์šฐ 6.40(2021)~15.45(2022๋…„), ์ˆ˜๊ตฌํ™”์˜ ๊ฒฝ์šฐ 4.32(2021) ~9.58(2022๋…„)๋กœ ์•”๊ตฌํ™”์— ๋น„ํ•ด ๋‹ค์†Œ ๋‚ฎ๊ฒŒ ์ถ”์ •๋˜์—ˆ์œผ๋ฉฐ, ๊ตฌ๊ณผ์˜ ๊ฒฝ์šฐ 7.30(2020)~10.71(2021๋…„)๋กœ ์ถ”์ •๋˜์–ด ๋ฐฐ์šฐ์ฒด ์ˆ˜์ค€๋ณด๋‹ค ๋†’๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ณ ์ฐฝ ์ฑ„์ข…์›์—์„œ์˜ ํด๋ก  ๊ฐ„ ๊ฐœํ™”๋Ÿ‰์— ๋Œ€ํ•œ ๊ฐœ์ฒด ์œ ์ „๋ ฅ์€ ์•”๊ตฌํ™”์˜ ๊ฒฝ์šฐ 0.150(2022)~0.309(2021๋…„), ์ˆ˜๊ตฌํ™”๋Š” 0.161(2020)~0.326 (2021๋…„), ๊ตฌ๊ณผ๋Š” 0.013(2022)~0.133(2020๋…„)์œผ๋กœ ์ ‘ํ•ฉ์ž ์ˆ˜์ค€์—์„œ์˜ ์œ ์ „๋ ฅ์ด ๋‚ฎ๊ฒŒ ์ถ”์ •๋˜์—ˆ๋‹ค. ์„œ๊ท€ํฌ ์ฑ„์ข…์›์—์„œ์˜ ํด๋ก  ๊ฐ„ ๊ฐœํ™”๋Ÿ‰์— ๋Œ€ํ•œ ๊ฐœ์ฒด ์œ ์ „๋ ฅ์€ ์•”๊ตฌํ™”์˜ ๊ฒฝ์šฐ 0.086(2022)~0.297(2021๋…„), ์ˆ˜๊ตฌํ™”์˜ ๊ฒฝ์šฐ 0.077(2021)~0.489(2020๋…„)๋กœ ์ถ”์ •๋˜์—ˆ์œผ๋ฉฐ, ๊ตฌ๊ณผ๋Š” 0.156(2022)~ 0.408(2021๋…„)๋กœ ์ถ”์ •๋˜์—ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ๋‘ ์ฑ„์ข…์› ๋ชจ๋‘์—์„œ ๊ฐœ์ฒด ์œ ์ „๋ ฅ๋ณด๋‹ค ํด๋ก  ์œ ์ „๋ ฅ์ด ๋งค์šฐ ๋†’์•˜๋‹ค. ์•”, ์ˆ˜๊ตฌํ™” ๊ฐœํ™”๋Ÿ‰๊ณผ ๊ตฌ๊ณผ ์ƒ์‚ฐ๋Ÿ‰ ๊ฐ„ ์ƒ๊ด€๋ถ„์„ ๊ฒฐ๊ณผ, 2020๋…„๋„ ์„œ๊ท€ํฌ ์ฑ„์ข…์›์—์„œ์˜ ์ˆ˜๊ตฌํ™”์™€ ๊ตฌ๊ณผ ์ƒ์‚ฐ๋Ÿ‰์€ ์œ ์˜ํ•œ ์ƒ๊ด€์„ ๋ณด์ด์ง€ ์•Š์•˜์œผ๋ฉฐ, ์ด๋ฅผ ์ œ์™ธํ•œ ๋‚˜๋จธ์ง€๋Š” ๋ชจ๋‘ ์œ ์˜ํ•œ ์ •์˜ ์ƒ๊ด€์„ ๋ณด์˜€๋‹ค. 2020๋…„๋ถ€ํ„ฐ 2021๋…„๊นŒ์ง€ 2๋…„๊ฐ„ ๊ณ ์ฐฝ๊ณผ ์„œ๊ท€ํฌ ์ฑ„์ข…์›์—์„œ ์ „์ˆ˜๋กœ๋ถ€ํ„ฐ ๊ฐœ์ฒด๋ชฉ๋‹น 10๊ฐœ ๊ตฌ๊ณผ๋ฅผ ์ฑ„์ทจํ•˜์—ฌ, ํด๋ก  ๊ฐ„ ๊ตฌ๊ณผ์™€ ์ข…์ž์˜ ํŠน์„ฑ์„ ๋ถ„์„ํ•˜์˜€๋‹ค. ๊ณ ์ฐฝ ์ฑ„์ข…์›์—์„œ์˜ ๊ฒฝ์šฐ 2020๋…„์˜ ์ถฉ์‹ค ์ข…์ž์œจ์€ 72.69%, ๋น„๋ฆฝ ์ข…์ž์œจ์€ 27.31%, ๊ณ ์‚ฌ ๋ฐฐ์ฃผ์œจ์€ 11.57%, ์ข…์ž ํšจ์œจ์€ 57.96%๋กœ ์ถ”์ •๋˜์—ˆ๋‹ค. 2021๋…„์˜ ์ถฉ์‹ค ์ข…์ž์œจ์€ 56.43%, ๋น„๋ฆฝ ์ข…์ž์œจ์€ 43.57%๋กœ ์ถฉ์‹ค ์ข…์ž์œจ๊ณผ ๋น„๋ฆฝ ์ข…์ž์œจ์˜ ๋น„์œจ์ด ์œ ์‚ฌํ•˜์˜€๋‹ค. ์ข…์ž ํšจ์œจ์€ 46.98%๋กœ ์ถ”์ •๋˜์–ด 2020๋…„์— ๋น„ํ•ด ๋‹ค์†Œ ๋‚ฎ๊ฒŒ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ, ๋ฐœ์•„์œจ์€ ํด๋ก ๋‹น ํ‰๊ท  5.09%๋กœ ๋งค์šฐ ์ €์กฐํ•˜์˜€๋‹ค. ์„œ๊ท€ํฌ ์ฑ„์ข…์›์—์„œ์˜ ๊ฒฝ์šฐ 2020๋…„์˜ ์ถฉ์‹ค ์ข…์ž์œจ์€ 9.46%, ๋น„๋ฆฝ ์ข…์ž์œจ์€ 90.54%, ๊ณ ์‚ฌ ๋ฐฐ์ฃผ์œจ์€ 33.06%๋กœ ํ™•์ธ๋˜์–ด ์ถฉ์‹ค ์ข…์ž ๊ฒฐ์‹ค์ด ๋งค์šฐ ์ €์กฐํ•˜์˜€์œผ๋ฉฐ, ์ข…์ž ํšจ์œจ์ด 7.51%๋กœ ๋‚ฎ๊ฒŒ ์ถ”์ •๋˜์—ˆ๋‹ค. 2021๋…„์˜ ์ถฉ์‹ค ์ข…์ž์œจ์€ 25.77%, ๋น„๋ฆฝ ์ข…์ž์œจ์€ 74.23%, ๊ณ ์‚ฌ ๋ฐฐ์ฃผ์œจ์€ 3.33%๋กœ ์ถ”์ •๋˜์—ˆ๋‹ค. ์ข…์ž ํšจ์œจ์€ 24.36%๋กœ 2020๋…„์— ๋น„ํ•ด ์ข…์ž ํšจ์œจ์€ ์ฆ๊ฐ€ํ•˜์˜€์ง€๋งŒ ์ถฉ์‹ค ์ข…์ž ๊ฒฐ์‹ค์ด ์ €์กฐํ•˜์˜€๋‹ค. ํด๋ก ๋‹น ํ‰๊ท  ๋ฐœ์•„์œจ์€ 3.13%๋กœ ๊ณ ์ฐฝ ์ฑ„์ข…์›์—์„œ์™€ ๋งˆ์ฐฌ๊ฐ€์ง€๋กœ ๋งค์šฐ ์ €์กฐํ•˜์˜€๋‹ค. ๊ณ ์ฐฝ๊ณผ ์„œ๊ท€ํฌ ์ฑ„์ข…์›์˜ ์œ ์ „ ๋ชจ์ˆ˜๋ฅผ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•˜์—ฌ microsatellite ํ‘œ์ง€๋ฅผ ์ด์šฉํ•˜์—ฌ 2021๋…„์— ์ƒ์‚ฐ๋œ ์„ฑ์ˆ™ ์ข…์ž๋ฅผ ๋Œ€์ƒ์œผ๋กœ ํƒ€๊ฐ€ ๊ต๋ฐฐ์œจ๊ณผ ํ™”๋ถ„ ์˜ค์—ผ๋ฅ , ๊ทผ์นœ ๊ต๋ฐฐ์œจ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๊ณ ์ฐฝ ์ฑ„์ข…์›์˜ ๋ชจ์ˆ˜์—์„œ ํ™•์ธ๋œ ์ดํ˜• ์ ‘ํ•ฉ๋„ ๊ธฐ๋Œ€์น˜๋Š” 0.740์ด์—ˆ์œผ๋ฉฐ, ๊ด€์ธก์น˜๋Š” 0.796์œผ๋กœ ์ถ”์ •๋˜์—ˆ๋‹ค. ์ข…์ž์—์„œ ํ™•์ธ๋œ ์ดํ˜• ์ ‘ํ•ฉ๋„ ๊ธฐ๋Œ€์น˜๋Š” 0.702์ด์—ˆ์œผ๋ฉฐ, ๊ด€์ธก์น˜๋Š” 0.756์ด์—ˆ๋‹ค. ๋ชจ์ˆ˜์™€ ์ข…์ž์˜ ๊ณ ์ •์ง€์ˆ˜๋Š” ๊ฐ๊ฐ -0.062์™€ -0.074๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์„œ๊ท€ํฌ ์ฑ„์ข…์›์˜ ๋ชจ์ˆ˜์—์„œ ์ดํ˜• ์ ‘ํ•ฉ๋„ ๊ธฐ๋Œ€์น˜๋Š” 0.683์ด์—ˆ์œผ๋ฉฐ, ๊ด€์ธก์น˜๋Š” 0.667๋กœ ํ™•์ธ๋˜์—ˆ๋‹ค. ์ข…์ž์—์„œ ํ™•์ธ๋œ ์ดํ˜• ์ ‘ํ•ฉ๋„ ๊ธฐ๋Œ€์น˜๋Š” 0.704์ด์—ˆ์œผ๋ฉฐ, ๊ด€์ธก์น˜๋Š” 0.740์œผ๋กœ ์ถ”์ •๋˜์—ˆ๋‹ค. ๋ชจ์ˆ˜์™€ ์ข…์ž์˜ ๊ณ ์ •์ง€์ˆ˜๋Š” ๊ฐ๊ฐ 0.037๊ณผ -0.206์œผ๋กœ ๋„์ถœ๋˜์—ˆ๋‹ค. MLTR ํ”„๋กœ๊ทธ๋žจ์„ ์ด์šฉํ•˜์—ฌ ๋ถ„์„ํ•œ ํƒ€๊ฐ€ ๊ต๋ฐฐ์œจ์€ ๊ณ ์ฐฝ์˜ ๊ฒฝ์šฐ 0.982์ด์—ˆ์œผ๋ฉฐ, ๊ทผ์นœ ๊ต๋ฐฐ์œจ์€ 0.028์ด์—ˆ๋‹ค. ๋ถ€๊ณ„ ์ƒ๊ด€์€ 0.172๋กœ ์ถ”์ •๋˜์—ˆ๋‹ค. ์„œ๊ท€ํฌ ์ฑ„์ข…์›์—์„œ์˜ ๊ฒฝ์šฐ ํƒ€๊ฐ€ ๊ต๋ฐฐ์œจ์€ 0.100์œผ๋กœ ๋งค์šฐ ๋†’๊ฒŒ ์ถ”์ •๋˜์—ˆ์œผ๋ฉฐ, ๊ทผ์นœ ๊ต๋ฐฐ์œจ์€ 0.059๋กœ ์‚ฐ์ถœ๋˜์—ˆ๋‹ค. ๋ถ€๊ณ„ ์ƒ๊ด€์€ 0.064๋กœ ์ถ”์ •๋˜์—ˆ๋‹ค. CERVUS ํ”„๋กœ๊ทธ๋žจ์„ ์ด์šฉํ•˜์—ฌ ๋ถ„์„ํ•œ ๊ณ ์ฐฝ ์ฑ„์ข…์›์—์„œ์˜ ํƒ€๊ฐ€ ๊ต๋ฐฐ์œจ์€ ํด๋ก  ๊ฐ„ ํ‰๊ท  94.21%์˜€์œผ๋ฉฐ, MLTR ํ”„๋กœ๊ทธ๋žจ์œผ๋กœ ๋ถ„์„ํ•œ ๊ฒฐ๊ณผ์™€ ์œ ์‚ฌํ•˜์˜€๋‹ค. ํ™”๋ถ„ ์˜ค์—ผ๋ฅ ์€ 1.1%, ์ž๊ฐ€ ๊ต๋ฐฐ์œจ์€ 4.69%๋กœ ์ถ”์ •๋˜์—ˆ์œผ๋ฉฐ ๊ธฐ์—ฌ ํ™”๋ถ„์นœ ์ˆ˜๋Š” ํ‰๊ท  11.1๊ฐœ์ด์—ˆ๋‹ค. ์„œ๊ท€ํฌ ์ฑ„์ข…์›์—์„œ์˜ ๊ฒฝ์šฐ ํƒ€๊ฐ€ ๊ต๋ฐฐ์œจ์€ 95.14%, ์ž๊ฐ€ ๊ต๋ฐฐ์œจ์€ 4.86%๋กœ ํ™•์ธ๋˜์—ˆ์œผ๋ฉฐ ๊ธฐ์—ฌ ํ™”๋ถ„์นœ ์ˆ˜๋Š” ํ‰๊ท  10.8๊ฐœ๋กœ ํ™•์ธ๋˜์—ˆ๋‹ค. TwoGener ๋ฐฉ๋ฒ•์œผ๋กœ ํ™”๋ถ„์›์˜ ๋ถ„์‚ฐ์„ ํ™•์ธํ•œ ๊ฒฐ๊ณผ, ๊ณ ์ฐฝ ์ฑ„์ข…์›์—์„œ์˜ ๊ฒฝ์šฐ ์ž„๋ถ„ ๋ฐ€๋„๋ฅผ ha๋‹น 130๋ณธ์œผ๋กœ ํ•˜์˜€์„ ๋•Œ ํ™”๋ถ„์›์˜ ์œ ์ „์  ๋ถ„ํ™”๋Š” 0.134์˜€์œผ๋ฉฐ, ํ‰๊ท  ์œ ํšจ ํ™”๋ถ„ ์ด๋™ ๊ฑฐ๋ฆฌ๋Š” 5.990m๋กœ ์ถ”์ •๋˜์—ˆ๋‹ค. ์„œ๊ท€ํฌ ์ฑ„์ข…์›์—์„œ์˜ ๊ฒฝ์šฐ ์ž„๋ถ„ ๋ฐ€๋„๋ฅผ ha๋‹น 125๋ณธ์œผ๋กœ ์ถ”์ •ํ•˜์˜€์œผ๋ฉฐ, ํ™”๋ถ„์›์˜ ์œ ์ „์  ๋ถ„ํ™”๋Š” 0.330์ด์—ˆ๊ณ , ํ‰๊ท  ํ™”๋ถ„ ์ด๋™๊ฑฐ๋ฆฌ๋Š” 3.892m๋กœ ์ถ”์ •๋˜์—ˆ๋‹ค. ์ด์™€ ๊ฐ™์ด ๊ณ ์ฐฝ๊ณผ ์„œ๊ท€ํฌ ํŽธ๋ฐฑ ์ฑ„์ข…์› ๋ชจ๋‘ ํƒ€๊ฐ€ ๊ต๋ฐฐ์œจ์ด ๋†’๊ฒŒ ์ถ”์ •๋˜์—ˆ์œผ๋ฏ€๋กœ, ์ฑ„์ข…์›์‚ฐ ์ข…์ž๋กœ ์ƒ์‚ฐ๋œ ํŽธ๋ฐฑ ๋ฌ˜๋ชฉ์˜ ๊ฒฝ์šฐ ์ž๊ฐ€ ๊ต๋ฐฐ๋กœ ์ธํ•œ ๊ทผ๊ต์•ฝ์„ธ๊ฐ€ ์›์ธ์ด ๋˜๋Š” ๋ถˆ๋Ÿ‰ ํ˜•์งˆ์€ ๋ฐœ์ƒํ•  ๊ฐ€๋Šฅ์„ฑ์ด ๋‚ฎ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋˜์—ˆ๋‹ค. ํ•˜์ง€๋งŒ ๊ธฐ์—ฌ ํ™”๋ถ„์นœ ์ˆ˜์˜ ๋น„์œจ์ด ๊ณ ์ฐฝ ํŽธ๋ฐฑ ์ฑ„์ข…์›์˜ ๊ฒฝ์šฐ ์ž์—ฐ ์ง‘๋‹จ์—์„œ ๊ธฐ์—ฌํ•˜๋Š” ํ™”๋ถ„์นœ ์ˆ˜์™€ ์œ ์‚ฌํ•˜๊ฒŒ ๋‚˜ํƒ€๋‚˜ ์œ ์ „ ๋‹ค์–‘์„ฑ์„ ๋†’์ด๊ธฐ ์œ„ํ•œ ํ™”๋ถ„์›์˜ ๊ด€๋ฆฌ๊ฐ€ ํ•„์š”ํ•  ๊ฒƒ์œผ๋กœ ํŒ๋‹จ๋˜์—ˆ๋‹ค.์ œ1์žฅ ์„œ๋ก  ๏ผ‘ ์ œ1์ ˆ ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ ๋ฐ ํ•„์š”์„ฑ ๏ผ‘ ์ œ2์ ˆ ์—ฐ๊ตฌ ๋ชฉ์  ๏ผ” ์ œ2์žฅ ์—ฐ๊ตฌ์‚ฌ ๏ผ– ์ œ1์ ˆ ํŽธ๋ฐฑ(C. obtusa)์˜ ์œ ์ „ ๋ฐ ์ƒํƒœ ๏ผ– ์ œ2์ ˆ ์ฑ„์ข…์› ๋‚ด ๊ฐœํ™”๊ฒฐ์‹ค๋Ÿ‰ ๋ณ€์ด ์—ฐ๊ตฌ 12 ์ œ3์ ˆ ์ฑ„์ข…์›์‚ฐ ์ข…์ž์˜ ๊ตฌ๊ณผ ๋ถ„์„ 20 ์ œ4์ ˆ DNA ํ‘œ์ง€๋ฅผ ์ด์šฉํ•œ ๊ต๋ฐฐ ์–‘์‹ ์—ฐ๊ตฌ 23 ์ œ3์žฅ ์žฌ๋ฃŒ ๋ฐ ๋ฐฉ๋ฒ• 30 ์ œ1์ ˆ ์—ฐ๊ตฌ ๋Œ€์ƒ์ง€ ํ˜„ํ™ฉ 30 ์ œ2์ ˆ ๊ฐœํ™” ๋ฐ ๊ตฌ๊ณผ ์ƒ์‚ฐ๋Ÿ‰ 32 ์ œ3์ ˆ ๊ตฌ๊ณผ ๋ฐ ์ข…์ž ํŠน์„ฑ ๋ถ„์„ 33 ์ œ4์ ˆ ํ†ต๊ณ„ ๋ถ„์„ ๋ฐ ์œ ์ „๋ ฅ ์ถ”์ • 37 ์ œ5์ ˆ ๋ˆ„์  ๊ธฐ์—ฌ๋„ ๊ณก์„  37 ์ œ6์ ˆ ์œ ํšจ ์ง‘๋‹จ ํฌ๊ธฐ ๋ฐ ์œ ์ „ ๋‹ค์–‘์„ฑ ์ถ”์ • 39 ์ œ7์ ˆ Microsatellite ํ‘œ์ง€ ๋ถ„์„ 40 ์ œ8์ ˆ ์œ ์ „ ๊ตฌ์กฐ ๋ฐ ๊ต๋ฐฐ ์–‘์‹ ๋ถ„์„ 44 ์ œ4์žฅ ๊ฒฐ๊ณผ 48 ์ œ1์ ˆ ๊ฐœํ™”๊ฒฐ์‹ค๋Ÿ‰ 48 1.1 ํด๋ก  ๊ฐ„ ๊ฐœํ™”๋Ÿ‰ ๋ฐ ๊ตฌ๊ณผ ์ƒ์‚ฐ๋Ÿ‰ ๋ณ€์ด 48 1.2 ๋ˆ„์  ๊ธฐ์—ฌ๋„ ๊ณก์„  50 1.3 ์œ ํšจ ์ง‘๋‹จ ํฌ๊ธฐ ๋ฐ ์œ ์ „ ๋‹ค์–‘์„ฑ ์ถ”์ • 53 1.4 ์œ ์ „๋ ฅ ์ถ”์ • 55 1.5 ๊ฐœํ™” ๋ฐ ๊ตฌ๊ณผ ์ƒ์‚ฐ๋Ÿ‰ ๊ฐ„ ์ƒ๊ด€๊ด€๊ณ„ ๋ถ„์„ 61 ์ œ2์ ˆ ๊ตฌ๊ณผ ๋ฐ ์ข…์ž์˜ ์œ ์ „ ๋‹ค์–‘์„ฑ 64 2.1 ๊ตฌ๊ณผ์˜ ํ˜•ํƒœ์  ํŠน์„ฑ 64 2.2 ์ข…์ž ํŠน์„ฑ ๋ถ„์„ 66 2.3 ๊ตฌ๊ณผ ๋ฐ ์ข…์ž ํŠน์„ฑ์˜ ์œ ์ „๋ ฅ ์ถ”์ • 69 2.4 ๊ตฌ๊ณผ ๋ฐ ์ข…์ž ํŠน์„ฑ ๊ฐ„ ์ƒ๊ด€๊ด€๊ณ„ ๋ถ„์„ 71 2.5 ๋ฐœ์•„๋ ฅ ๊ฒ€์ • 75 ์ œ3์ ˆ ๊ต๋ฐฐ ์–‘์‹ ๋ถ„์„ 75 3.1 ์œ ์ „ ๋‹ค์–‘์„ฑ ๋ถ„์„ 75 3.2 ๊ต๋ฐฐ ์–‘์‹ 84 3.3 ํ™”๋ถ„์›์˜ ์œ ์ „์  ๋ถ„ํ™” 86 3.4 ๋ถ€๊ณ„ ์œ ์ „์žํ˜• ๋ฐ ํ™”๋ถ„ ์˜ค์—ผ๋ฅ  ์ถ”์ • 86 ์ œ5์žฅ ๊ณ ์ฐฐ 94 ์ œ1์ ˆ ๊ฐœํ™”๋Ÿ‰ ๋ฐ ๊ตฌ๊ณผ ๊ฒฐ์‹ค๋Ÿ‰ ๋ณ€์ด์™€ ์œ ์ „ ๋‹ค์–‘์„ฑ 94 ์ œ2์ ˆ ๊ตฌ๊ณผ ๋ถ„์„ ๋ฐ ์ข…์ž ํŠน์„ฑ ๋ถ„์„ 99 ์ œ3์ ˆ ๊ต๋ฐฐ ์–‘์‹ ๋ถ„์„ 105 ์ œ6์žฅ ๊ฒฐ๋ก  114 ์ฐธ๊ณ  ๋ฌธํ—Œ 117 Appendix 141 Abstract 240๋ฐ•

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    ํ•œ ์‚ฌ๋žŒ์ด ์žˆ์—ˆ๋‹ค. ๊ทธ ์‚ฌ๋žŒ์€ ์ข…์ข… ๋‚ด๊ฒŒ ํŽธ์ง€๋ฅผ ์จ์„œ ์ฃผ๊ณค ํ–ˆ๋‹ค. ๊ทธ ํŽธ์ง€์—๋Š” ๋•Œ๋กœ๋Š” ๊ฒฉ๋ ค์™€ ์ง€์ง€์˜ ๋”ฐ์Šคํ•œ ๋ง๋“ค์ด, ๋•Œ๋กœ๋Š” ๋‚จ๋“ค์ด ์‰ฝ๊ฒŒ ํ•˜์ง€ ๋ชปํ•  ๋‚ ์นด๋กœ์šด ์ถฉ๊ณ ๊ฐ€ ๋‹ด๊ฒจ ์žˆ์—ˆ๋‹ค. ๋‚˜๋Š” ๊ผญ ๊ทธ ์‚ฌ๋žŒ์˜ ํŽธ์ง€๋“ค์„ ๋‘์–ด ๋ฒˆ์”ฉ ๋˜๋‡Œ์–ด ์ฝ๊ณค ํ–ˆ์—ˆ๋Š”๋ฐ, ๊ทธ ์ด์œ ๋Š” ๊ทธ ์‚ฌ๋žŒ์˜ ํŽธ์ง€๊ฐ€ ํ™”๋ คํ•œ ๋ฏธ์‚ฌ์—ฌ๊ตฌ๋กœ ์“ฐ์—ฌ ์žˆ์—ˆ๋‹ค๊ฑฐ๋‚˜ ๊ธฐ๊ต์ ์œผ๋กœ ์ž˜ ์“ด ๊ธ€์ด์—ˆ๊ธฐ ๋•Œ๋ฌธ์ด๋ผ๊ธฐ๋ณด๋‹ค๋Š”, ๊ฐ„๊ฒฐํ–ˆ์ง€๋งŒ ๋Š˜ ๋‹ค์‹œ ์ฝ์–ด๋ณด๊ณ  ์‹ถ์„ ๋งŒํผ ๋งˆ์Œ์— ์™€ ๋‹ฟ์•˜๊ธฐ ๋•Œ๋ฌธ์ด์—ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์–ธ์ œ๋‚˜ ๋‚˜๋ฅผ ๋ฐฐ๋ คํ•˜๊ณ  ์กด์ค‘ํ•˜๋Š” ๋งˆ์Œ์ด ๋Š๊ปด์ง€๋Š” ๊ฒƒ์ด์—ˆ๊ธฐ์— ๊ทธ ์‚ฌ๋žŒ์˜ ํŽธ์ง€๋Š” ๋‚˜๋ฅผ ์›ƒ๊ฒŒ๋„ ํ•˜๊ณ  ์šธ๊ฒŒ๋„ ํ•˜๋Š” ๋งˆ๋ฒ•๊ฐ™์€ ๊ฒƒ์ด์—ˆ๋‹ค. ๊ทธ ์‚ฌ๋žŒ์˜ ํŽธ์ง€๊ฐ€ ๋‚ด๊ฒŒ ์ฃผ์—ˆ๋˜ ๊ฐ๋™์„ ๊ธฐ์–ตํ•˜๋ฉฐ, ๊ธ€์“ฐ๊ธฐ์— ๋Œ€ํ•œ ๋ช‡ ๊ฐ€์ง€๋ฅผ ์ด์•ผ๊ธฐํ•˜๊ณ ์ž ํ•œ๋‹ค. ๋ฌด์—‡๋ณด๋‹ค๋„ ๊ธ€์“ฐ๊ธฐ๋Š” ์• ์ •์˜ ํ‘œํ˜„์ด๋ผ๋Š” ์ƒ๊ฐ์ด ๋“ ๋‹ค. ๊ธ€์„ ์“ฐ๋Š” ๋Œ€์ƒ์— ๋Œ€ํ•œ, ๊ธ€์„ ์ฝ๋Š” ์‚ฌ๋žŒ์— ๋Œ€ํ•œ, ๋ฉ€๊ฒŒ๋Š” ๊ณต๋™์ฒด์— ๋Œ€ํ•œ ์• ์ •๋ถ€ํ„ฐ ๊ฐ€๊น๊ฒŒ๋Š” ๋‚˜ ์ž์‹ ์— ๋Œ€ํ•œ ์• ์ •๊นŒ์ง€ ๊ทธ ์–ด๋–ค ๊ฒƒ์— ๋Œ€ํ•œ ๊ฒƒ์ด๋“  ์• ์ • ์—†์ด๋Š” ๊ธ€์„ ์“ฐ๊ธฐ ์–ด๋ ต๋‹ค. ๋‚˜์— ๋Œ€ํ•œ ์• ์ •์ด ์žˆ์—ˆ๊ธฐ ๋•Œ๋ฌธ์— ๊ทธ ์‚ฌ๋žŒ์€ ๋‚ด๊ฒŒ ํŽธ์ง€๋ฅผ ์ผ์„ ๊ฒƒ์ด๋‹ค. ๋น„๋‹จ ๊ทธ ์‚ฌ๋žŒ์˜ ํŽธ์ง€๋งŒ์ด ์•„๋‹ˆ๋‹ค. ๋ˆˆ ๋‚ด๋ฆฐ ๋‹ค์Œ ๋‚  ์ด๋ฆ„ ๋ชจ๋ฅผ ๋ˆ„๊ตฐ๊ฐ€๊ฐ€ ๋ถ™์—ฌ ๋†“์•˜์„, ๋ฏธ๋„๋Ÿฌ์ง€์ง€ ์•Š๋„๋ก ์กฐ์‹ฌํ•˜๋ผ๋Š” ์ข…์ด ํ•œ ์žฅ์—์„œ๋ถ€ํ„ฐ ํ•˜๋ฃจํ•˜๋ฃจ ๋ณ€ํ™”ํ•˜๋Š” ์ •์„ธ ์†์—์„œ ๋งค์ผ๊ฐ™์ด ๋‚˜๋ผ๋ฅผ ๊ฑฑ์ •ํ•˜๋Š” ์กฐ๊ฐ„์‹ ๋ฌธ์˜ ์–ด๋Š ๊ธฐ์‚ฌ๊ธ€, ๊ทธ๋™์•ˆ ๋ณด๊ณ  ๋ฐฐ์šฐ๊ณ  ์•Œ๊ฒŒ ๋œ ๊ฒƒ๋“ค์„ ๊ธฐ๋กํ•œ ๋…ผ๋ฌธ์— ์ด๋ฅด๊ธฐ๊นŒ์ง€ ๊ทธ ๋ชจ๋“  ๊ฒƒ์ด ์• ์ •, ํŠนํžˆ ์†Œํ†ตํ•˜๊ณ ์ž ํ•˜๋Š” ์• ์ •์ด ์—†์—ˆ๋‹ค๋ฉด ์šฐ๋ฆฌ์˜ ๊ณ์— ๋‚จ์„ ์ˆ˜ ์—†์—ˆ์„ ๊ฒƒ์ด๋‹ค

    Elevated levels of preoperative CA 15-3 and CEA serum levels have independently poor prognostic significance in breast cancer

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    BACKGROUND: To evaluate the prognostic value of preoperative tumor markers, cancer antigen 15-3 (CA 15-3) and carcinoembryonic antigen (CEA), in breast cancers. PATIENTS AND METHODS: Preoperative CA 15-3 and CEA levels of 1681 patients were measured. The association of both tumor markers levels with clinicopathological parameters and outcomes was investigated by univariate and multivariate analyses. RESULTS: Among 1681 patients, elevated preoperative CA15-3 and CEA levels were identified in 176 and 131 patients, respectively. Higher preoperative CA 15-3 and CEA levels were significantly associated with a larger tumor size, axillary node metastases, and advanced stage. Patients with elevated CA 15-3 and CEA levels showed worse survival, even in stage-matched analysis. Patients with normal levels of both CA15-3 and CEA showed better survival than those with one or both markers levels elevated. In multivariate analysis, elevated preoperative CA 15-3 and CEA levels were independent prognostic factors. The statistical significance of elevated preoperative tumor markers levels on survival was solidified with longer follow-up and larger study population. CONCLUSIONS: Elevated preoperative CA 15-3 and CEA levels are associated with tumor burden and showed independent prognostic significance. Therefore, new treatment strategies are necessary for patients with elevated preoperative CA 15-3 and CEA levels in clinical practice.ope

    Homeodomain-interacting protein kinase 1 (HIPK1) expression in breast cancer tissues

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    OBJECTIVE: This study investigated the incidence and clinical significance of homeodomain-interacting protein kinase 1 expression in breast cancer patients. METHODS: We investigated immunohistochemical homeodomain-interacting protein kinase 1 expression from tissue microarrays of 1032 patients. The association of homeodomain-interacting protein kinase 1 expression pattern, clinicopathologic factors and survival outcome was evaluated. Tumors with โ‰ฅ10% stained cells were considered positive for homeodomain-interacting protein kinase 1. RESULTS: Non-cancerous breast tissue, pTis and pT1mic lesions did not show homeodomain-interacting protein kinase 1 expression at any sites. Of the 859 invasive tumors, 124 (14.4%) showed homeodomain-interacting protein kinase 1 expression with three different expression patterns: cytoplasmic (2.4%), nuclear (6.3%), and both cytoplasmic and nuclear (5.7%). Cytoplasmic homeodomain-interacting protein kinase 1-positive tumors showed distinctive features such as fewer nodal metastases, but were frequently Grade III, estrogen receptor-negative, progesterone receptor-negative, HER2-positive, highly proliferative and molecular apocrine tumors. No significant difference in clinicopathologic features was identified between negative and nuclear homeodomain-interacting protein kinase 1-positive tumors. Both cytoplasmic and nuclear HIPK1-positive tumors represent frequent small size, node negativity and moderately differentiated features. Survival was not significantly different by homeodomain-interacting protein kinase 1 expression patterns. CONCLUSIONS: Homeodomain-interacting protein kinase 1 expression was identified only in invasive breast cancer cells with three different patterns: cytoplasmic, nuclear, and both cytoplasmic and nuclear. Although the mechanism is not certain, the subcellular localization of HIPK1 expression is associated with tumor histopathologic characteristics and different functions.ope

    Comparing competitiveness of India and China : Are they competing or cooperating?

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    Thesis(masters) --์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ตญ์ œํ•™๊ณผ(๊ตญ์ œํ†ต์ƒ์ „๊ณต),2008. 8.Maste
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