25 research outputs found

    Does construct overload truly overload the performance? - An experimental study of experienced data modeler.

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› ๊ฒฝ์˜๋Œ€ํ•™ ๊ฒฝ์˜ํ•™๊ณผ, 2017. 8. ๋ฐ•์ง„์ˆ˜.A principal activity in information systems development involves building a conceptual model of domain that an information system is intended to support. Such models are created using a conceptual-modeling grammar fundamental means to specifying information systems requirement. However, the actual usage of grammar is poorly understood and some issues regarding conceptual grammar such as construct overload still remain unsolved. With regard to construct overload in conceptual modeling, past studies have had some deficiencies in research methods and even have presented contradicting results. In this paper, we experimented to test whether construct overload enables conceptual models users to understand a domain more efficiently. To acquire a more complete and accurate understanding of construct overload, our study focused on three major pointsthe evaluation of conceptual modeling grammar semantics, research participants and domain familiarity. This papers key contribution is that it is one of the first studies to investigate practitioners aspects of construct overload employing different degrees of domain familiarity by investigating the cognitive processes of practitioner. In addition, this research reconciles conflicting outcomes by examining practical directions for model variation. The result of study will broaden the perspective on usability in the context of the conceptual model and may serve as an ontological guidance to construct overload when modelers create a conceptual model.1. Introduction 2 2. Theory and Related Work 5 2.1. Theory 6 Theory of Ontological Clarity 7 Feynman-Tufte Principle 7 Mayers Cognitive Theory of Multimedia Learning 8 Information Processing Theory 8 Theory of Visual Attention 9 2.2. Related Work 9 Ontological Clarity 13 Domain Familiarity 13 3. Proposition Development 14 4. Research Method 18 4.1. Design and Measures 19 4.2. Materials 20 Personal Profile and Training Materials 20 Conceptual Models 21 Understanding Task Materials 27 4.3. Participants 31 4.4. Procedures 32 4.5. Results 33 Data Scoring 33 Quantitative Data Analysis 33 5. Cognitive Process Tracing Study 36 5.1. Design and Measures 36 5.2. Materials 37 5.3. Participants 38 5.4. Procedures 38 5.5. Coding Scheme 39 5.6. Analysis of Protocol Data 40 5.7. Analysis of Eye-tracking Data 45 Scan Path 48 Focus and Heat Map 52 Quantitative Data Analysis of Key Performance Indicators 56 6. Discussion 63 6.1. Conclusion 63 6.2. Implication 63 6.3. Limitations and Future Research Directions 65 Reference 66 Appendix A 73 Summary of Information Processing Coding Typology 73 Appendix B 75 Glossary of Eye Tracking Technique 75 Focus Map of Unfamiliar Domain (Waste Processing System) 75Docto

    Type I collagen inhibits degradation of Runx2 protein through down-regulation of Smurf1 in MC4 cells

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์น˜์˜ํ•™๊ณผ ๋‘๊ฐœ์•…์•ˆ๋ฉด์„ธํฌ๋ฐ๋ฐœ์ƒ์ƒ๋ฌผํ•™์ „๊ณต,2007.Maste

    H. pylori์— ๊ฐ์—ผ๋œ ์œ„ ์ƒํ”ผ์„ธํฌ์—์„œ cyclooxygenase-2์™€ integrin ๋ฐœํ˜„์— protease-activated receptor-2์˜ ์—ญํ• 

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    Dept. of Medical Science/๋ฐ•์‚ฌ[ํ•œ๊ธ€]Protease-activated receptor-2(PAR-2)๋Š” G๋‹จ๋ฐฑ ๊ฒฐํ•ฉ ์ˆ˜์šฉ์ฒด ์ค‘ ํ•˜๋‚˜์ด๋ฉฐ COX-2 ๋‚˜ ์ธํ‹ฐ๊ทธ๋ฆฐ ๋ฐœํ˜„์— ๊นŠ์€ ๊ด€๋ จ์ด ์žˆ๋‹ค. H. pylori (H. pylori)์— ๊ฐ์—ผ๋œ ์ธ๊ฐ„์˜ ์œ„ ์ƒํ”ผ ์„ธํฌ์ฃผ์ธ AGS ์„ธํฌ์ฃผ์—์„œ COX-2์™€ ์„ธํฌ์œ ์ฐฉ๋ถ„์ž์ธ integrin ๋ฐœํ˜„์ด ์ฆ๊ฐ€ํ•จ์ด ๋ณด๊ณ ๋˜์—ˆ๋‹ค. ์ด๋ฒˆ ์—ฐ๊ตฌ์—์„œ๋Š” H. pylori์— ์˜ํ•ด PAR-2 ๋ฐœํ˜„์ด ์œ ๋„ ๋˜๋Š”์ง€ ๋˜ํ•œ H. pylori ๊ฐ์—ผ์— ์˜ํ•œ COX-2์™€ integrin์˜ ์ฆ๊ฐ€๊ฐ€ PAR-2์™€ ๊ด€๋ จ์ด ์žˆ๋Š”์ง€ ์•Œ์•„๋ณด๊ณ ์ž ํ•œ๋‹ค. H. pylori๋ฅผ AGS ์„ธํฌ์ฃผ์— 100:1์˜ ๋น„์œจ๋กœ ์ฒ˜์น˜ํ•˜๊ณ  PAR-2์™€ integrin์˜ mRNA์™€ ๋‹จ๋ฐฑ ๋ฐœํ˜„์„ ์—ญ์ „์‚ฌ์ค‘ํ•ฉ์—ฐ์‡„๋ฐ˜์‘๊ณผ immunoblotting์„ ํ†ตํ•ด์„œ ํ™•์ธํ•˜์˜€๋‹ค. ๋˜ํ•œ integrin์˜ ์–ด๋–ค ์†Œ๋‹จ์œ„๊ฐ€ H. pylori์— ์˜ํ•ด ์ฆ๊ฐ€ํ•œ ์„ธํฌ ์œ ์ฐฉ์— ๊ด€์—ฌํ•˜๋Š”์ง€ adhesion assay๋กœ ํ™•์ธํ•˜์˜€๋‹ค.์—ฐ๊ตฌ ๊ฒฐ๊ณผ H. pylori๋กœ ์ž๊ทนํ•œ AGS ์„ธํฌ์ฃผ์—์„œ PAR-2๊ฐ€ ํ™œ์„ฑํ™”๋˜๊ณ  integrin ฮฑ5ฮฒ1์ด ์œ ๋„๋˜์—ˆ๋‹ค. H. pylori๋Š” AGS ์„ธํฌ์ฃผ์˜ ์„ธํฌ์œ ์ฐฉ์„ integrin ฮฑ5ฮฒ1์„ ํ†ตํ•ด ์ฆ๊ฐ€์‹œ์ผฐ๋‹ค. H. pylori์— ์˜ํ•ด ์ฆ๊ฐ€ํ•œ COX-2์™€ integrin ฮฑ5ฮฒ1 ๋ฐœํ˜„์€ PAR-2 antisense oligodeoxynucleotide(AS ODN)์— ์˜ํ•ด ์–ต์ œ๋˜์—ˆ๋‹ค. ์ด๋Š” H. pylori์— ๊ฐ์—ผ๋œ ์„ธํฌ์ฃผ์˜ COX-2์™€ integrin ฮฑ5ฮฒ1 ๋ฐœํ˜„ ์ฆ๊ฐ€๋Š” PAR-2์— ์˜ํ•ด ๋งค๊ฐœ๋จ์„ ์‹œ์‚ฌํ•œ๋‹ค.H. pylori๋Š” ์„ธํฌ์™ธ๊ธฐ์งˆ ๋‹จ๋ฐฑ๋“ค(poly-L-lysine, fibronectin, collagen, laminin)๊ณผ integrin ฮฑ5ฮฒ1 ๊ณผ ๋ถ™์–ด ์„ธํฌ์œ ์ฐฉ์„ ์ฆ๊ฐ€์‹œํ‚ค๋‚˜ G-๋‹จ๋ฐฑ ์–ต์ œ์ œ์ธ pertussis toxin๊ณผ Src ์ธ์‚ฐํ™” ์–ต์ œ์ œ์ธ herbimycin A์— ์˜ํ•ด ์„ธํฌ์œ ์ฐฉ์ด ์œ ์˜ํ•˜๊ฒŒ ๊ฐ์†Œ๋˜์—ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๋กœ H. pylori๋Š” PAR-2/G-๋‹จ๋ฐฑ ์‹ ํ˜ธ์ฒด๊ณ„๋ฅผ ์ž๊ทนํ•˜์—ฌ ์„ธํฌ์œ ์ฐฉ์„ ์กฐ์ ˆํ•œ๋‹ค๊ณ  ์ƒ๊ฐํ•œ๋‹ค.์ด์ƒ์˜ ๊ฒฐ๊ณผ๋“ค๋กœ ์ข…ํ•ฉํ•˜์—ฌ ๋ณผ๋•Œ H. pylori๋Š” ์ธ๊ฐ„์˜ ์œ„์ƒํ”ผ ์„ธํฌ์ฃผ์˜ COX-2์™€ integrin ฮฑ5ฮฒ1์„ ์ฆ๊ฐ€์‹œ์ผœ ์„ธํฌ์œ ์ฐฉ์„ ์œ ๋„ํ•˜๋Š”๋ฐ ์ด๋Š” PAR-2 ํ™œ์„ฑํ™”์— ์˜ํ•ด ๋งค๊ฐœ๋œ๋‹ค๊ณ  ์ƒ๊ฐํ•œ๋‹ค. [์˜๋ฌธ]Protease-activated receptor-2 (PAR-2), subgroup of G-protein coupled receptor family, is known to be associated with the expression of cyclooxygenase-2 (COX-2) and integrins. Infection of Helicobacter pylori (H. pylori) increased the expression of COX-2 and adhesion molecule such as integrin ฮฑ5ฮฒ1 with enhanced cell adhesion in human gastric carcinoma cell line, AGS cells. The aim of this study is whether H. pylori infection induced the PAR-2 expression and its expression is related to COX-2 and integrins which were increased by H. pylori infection. After treatment of H. pylori to AGS cells at the ratio of 100:1, mRNA and protein expression of PAR-2 and integrins were determined by RT-PCR and immunoblotting. Involvement of integrin isoforms in cell adhesion was determined by adhesion assay. PAR-2 activation and induction of integrin ฮฑ5ฮฒ1 were observed in H. pylori-infected AGS cells. H. pylori promoted cell adhesion through integrin ฮฑ5ฮฒ1 - dependent manner in AGS cells. When AGS cells were treated with antisense oligodeoxynucleotide for PAR-2, H. pylori-induced expression of COX-2 and integrin ฮฑ5ฮฒ1 were suppressed. The results suggest that the expression of COX-2 and integrin ฮฑ5ฮฒ1 are mediated by PAR-2 in H. pylori infected AGS cells. The H. pylori-stimulated cell adhesion to poly-L-lysine, fibronectin, collagen IV or laminin was effectively inhibited by the Gi protein blocker pertussis toxin, and Src kinase inhibitor herbimycin A. These results show that H. pylori regulates cellular adhesion by inducing PAR-2/G protein signalings.In conclusion, H. pylori induces cell adhesion mediated by COX-2 and integrin ฮฑ5ฮฒ1, which may be initiated by PAR-2 activation in AGS cells.ope

    PEGylation of conjugated linoleic acid as an anti-cancer prodrug

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    Thesis(masters) --์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๋†์ƒ๋ช…๊ณตํ•™๋ถ€,2008.8.Maste

    ํ•œ๊ตญ์—์„œ 1์ƒ ์ž„์ƒ์‹œํ—˜์— ์ฐธ์—ฌํ•˜๋Š” ๊ฑด๊ฐ• ์ž์›์ž์˜ ๋™๊ธฐ ๋ฐ ์ธ์‹์— ๊ด€ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์˜๊ณผ๋Œ€ํ•™ ์˜ํ•™๊ณผ ์ธ๋ฌธ์˜ํ•™์ „๊ณต, 2016. 2. ๊น€์˜ฅ์ฃผ.์„œ๋ก : ๋ณธ ๋…ผ๋ฌธ์€ 1์ƒ ์ž„์ƒ์‹œํ—˜์— ์ฐธ์—ฌํ•œ ๊ฑด๊ฐ•ํ•œ ์ž์›์ž๋“ค์˜ ์ธ์‹์„ ํ†ตํ•ด ํ•œ๊ตญ์—์„œ ํ–‰ํ•ด์ง€๋Š” 1์ƒ ์ž„์ƒ์‹œํ—˜์˜ ํŠน์ง•๊ณผ ์—ฐ๊ตฌ์— ์ฐธ์—ฌํ•˜๋Š” ๊ฑด๊ฐ•ํ•œ ์ž์›์ž๋“ค์˜ ํŠน์ง•์„ ๋ฐํžˆ๋Š” ๊ฒƒ์„ ๋ชฉํ‘œ๋กœ ํ•œ๋‹ค. ์ž„์ƒ์‹œํ—˜์€ ์‹ ์•ฝ์„ ๋น„๋กฏํ•œ ์ƒˆ๋กœ์šด ์น˜๋ฃŒ๋ฒ•์— ๋Œ€ํ•œ ์œ ํšจ์„ฑ๊ณผ ์•ˆ์ „์„ฑ์„ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์‚ฌ๋žŒ์„ ๋Œ€์ƒ์œผ๋กœ ์‹ค์‹œํ•˜๋Š” ์‹คํ—˜์  ์—ฐ๊ตฌ์ด๋‹ค. ์ž„์ƒ์‹œํ—˜์€ ์—ฐ๊ตฌ ๋‹จ๊ณ„์— ๋”ฐ๋ผ 1์ƒ์—์„œ 4์ƒ์œผ๋กœ ๊ตฌ๋ถ„ํ•  ์ˆ˜ ์žˆ๊ณ  ํ™˜์ž๋ฅผ ๋Œ€์ƒ์œผ๋กœ ํ•˜๋Š” 2, 3, 4์ƒ ์ž„์ƒ์‹œํ—˜๊ณผ๋Š” ๋‹ฌ๋ฆฌ ์ œ1์ƒ ์‹œํ—˜์€ ํ•œ์ •๋œ ์ธ์›์˜ ๊ฑด๊ฐ•ํ•œ ์ž์›์ž์—๊ฒŒ ์‹ ์•ฝ์„ ํˆฌ์—ฌํ•˜๊ณ  ๊ทธ ์•ฝ๋ฌผ์˜ ์ฒด๋‚ด๋™ํƒœ, ์ธ์ฒด์—์„œ์˜ ์•ฝ๋ฆฌ์ž‘์šฉ, ๋ถ€์ž‘์šฉ ๋ฐ ์•ˆ์ „ํ•˜๊ฒŒ ํˆฌ์—ฌํ•  ์ˆ˜ ์žˆ๋Š” ํˆฌ์—ฌ๋Ÿ‰์˜ ํญ ๋“ฑ์„ ๊ฒฐ์ •ํ•˜๋Š” ๊ฒƒ์„ ๋ชฉ์ ์œผ๋กœ ํ•˜๋Š” ์—ฐ๊ตฌ์ด๋‹ค. ์ด๋Š” ์ธ๊ฐ„์„ ๋Œ€์ƒ์œผ๋กœ ํ•˜๋Š” ์•ฝ๋ฌผํˆฌ์—ฌ์˜ ์ฒซ ๋‹จ๊ณ„์ด์ง€๋งŒ ์น˜๋ฃŒ์ ์ธ ๋ชฉ์ ์„ ๊ฐ€์ง€์ง€ ์•Š๋Š”๋‹ค. 1์ƒ ์ž„์ƒ์‹œํ—˜์— ์ฐธ์—ฌํ•˜๋Š” ๊ฑด๊ฐ•ํ•œ ์ž์›์ž๋Š” ์ž„์ƒ์‹œํ—˜์— ์˜ํ–ฅ์„ ์ค„๋งŒํ•œ ์งˆ๋ณ‘์„ ์•“์€ ์ ์ด ์—†๊ณ , ์‹ ์ฒด ์ธก์ •์˜ ๊ฒฐ๊ณผ๊ฐ€ ์ผ๋ฐ˜์ ์ธ ๋ฒ”์œ„ ๋‚ด์— ์žˆ์–ด์•ผ ํ•œ๋‹ค. ๋˜ํ•œ ์—ฐ๊ตฌ๋‚ด์šฉ์„ ์ดํ•ดํ•˜๊ณ  ์ž๋ฐœ์ ์œผ๋กœ ๋™์˜ํ•  ์ˆ˜ ์žˆ๋Š” ๊ฐœ์ธ์œผ๋กœ ์ •์˜ํ•œ๋‹ค. ์ž„์ƒ์‹œํ—˜์€ ์ธ์ฒด๋ฅผ ๋Œ€์ƒ์œผ๋กœ ์ง„ํ–‰ํ•˜๋Š” ์—ฐ๊ตฌ์ด๊ธฐ ๋•Œ๋ฌธ์— ๊ฑด๊ฐ•ํ•œ ์ž์›์ž์˜ ์•ˆ์ „๊ณผ ๋ณต์ง€๋ฅผ ๊ณ ๋ คํ•˜์—ฌ ์œค๋ฆฌ์ ์œผ๋กœ ์ˆ˜ํ–‰ํ•˜๋Š” ๊ฒƒ์ด ๋ฌด์—‡๋ณด๋‹ค ์ค‘์š”ํ•˜๋‹ค. ์ง€๊ธˆ๊นŒ์ง€ ํ•œ๊ตญ์˜ 1์ƒ ์ž„์ƒ์‹œํ—˜์˜ ์œค๋ฆฌ์  ์ธก๋ฉด์— ๋Œ€ํ•ด์„œ ์—ฐ๊ตฌํ•œ ๊ฒƒ์ด ์—†์œผ๋ฉฐ, 1์ƒ ์ž„์ƒ์‹œํ—˜์— ์ฐธ์—ฌํ•˜๋Š” ๊ฑด๊ฐ•ํ•œ ์ž์›์ž๋“ค์ด ์ƒ๊ฐํ•˜๋Š” ์ž„์ƒ์‹œํ—˜์— ๋Œ€ํ•œ ์ธ์‹์ด๋‚˜ ์ฐธ์—ฌ ๋™๊ธฐ์— ๋Œ€ํ•ด์„œ ์‹ฌ์ธต์ ์œผ๋กœ ๋ถ„์„ํ•œ ์—ฐ๊ตฌ๊ฐ€ ๋ฏธํกํ•˜๋‹ค. ๋ฐฉ๋ฒ•: ๋ณธ ์—ฐ๊ตฌ๋Š” ํ•œ๊ตญ์—์„œ 1์ƒ ์ž„์ƒ์‹œํ—˜์— ์ฐธ์—ฌ ๊ฒฝํ—˜์ด ์žˆ๋Š” 20์„ธ ์ด์ƒ 45์„ธ ์ดํ•˜์˜ ๊ฑด๊ฐ•ํ•œ ์ž์›์ž๋ฅผ ์„ ์ •ํ•˜์—ฌ ์„ค๋ฌธ์กฐ์‚ฌ, ์งˆ์˜์‘๋‹ต, ์‹ฌ์ธต๋ฉด๋‹ด์„ ์ง„ํ–‰ํ•œ ๊ฒƒ์ด๋‹ค. 1์ฐจ๋กœ ๊ฑด๊ฐ•ํ•œ ์ž์›์ž์˜ ์ธ๊ตฌํ•™์  ์ •๋ณด์™€ ์ž„์ƒ์‹œํ—˜ ์ฐธ์—ฌ ๊ฒฝํ—˜์„ ์•Œ์•„๋ณด๊ธฐ ์œ„ํ•ด 121๋ช…์˜ ์ž์›์ž๋ฅผ ๋Œ€์ƒ์œผ๋กœ ์„ค๋ฌธ์กฐ์‚ฌ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๊ณ , 2์ฐจ ์งˆ์˜์‘๋‹ต์€ 12๋ช…์„ ์„ ์ •ํ•˜๊ณ  ์งˆ๋ฌธ์ง€๋ฅผ ์ด์šฉํ•˜์—ฌ ์ธํ„ฐ๋ทฐ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. 3์ฐจ ์‹ฌ์ธต๋ฉด๋‹ด์€ 11๋ช…์˜ ์ž์›์ž๋ฅผ ์„ ์ •ํ•˜์—ฌ ๋ณธ์ธ์˜ ๊ธฐ๋ณธ ์ •๋ณด ๋ฐ ์ž„์ƒ์‹œํ—˜ ์ฐธ์—ฌ ๊ฒฝํ—˜์— ์•Œ์•„๋ณด๊ณ ์ž ์ง„ํ–‰ํ•˜์˜€๋‹ค. ๊ฒฐ๊ณผ: ํ•œ๊ตญ์˜ ๊ฑด๊ฐ•ํ•œ ์ž์›์ž๋ฅผ ๋Œ€์ƒ์œผ๋กœ ์„ค๋ฌธ์กฐ์‚ฌ๋ฅผ ์ง„ํ–‰ํ•˜์—ฌ ์ธ๊ตฌํ•™์  ์ •๋ณด์™€ ์—ฐ๊ตฌ ์ฐธ์—ฌ ๋™๊ธฐ๋ฅผ ์•Œ์•„๋ณด์•˜๋‹ค. ํ•œ๊ตญ์˜ ๊ฑด๊ฐ•ํ•œ ์ž์›์ž๋Š” ๋Œ€๋ถ€๋ถ„์ด ๋ฏธํ˜ผ ๋‚จ์„ฑ์œผ๋กœ ๋Œ€ํ•™์ƒ์ด๊ฑฐ๋‚˜ ์ทจ์—…์ค€๋น„์ƒ์œผ๋กœ ๊ฒฝ์ œ์  ๋…๋ฆฝ์ด ์ด๋ค„์ง€์ง€ ์•Š์€ ๊ฒฝ์šฐ๊ฐ€ ๋งŽ์•˜๋‹ค. ์—ฐ๊ตฌ ์ฐธ์—ฌ์˜ ์ฃผ๋œ ๋™๊ธฐ๋Š” ๊ธˆ์ „์  ๋ณด์ƒ์ด๋‹ค. ๊ธˆ์ „์  ๋ณด์ƒ์„ ์ฑ…์ •ํ•˜๋Š” ๋ฐ์— ๊ฐ€์žฅ ์ค‘์š”ํ•œ ์š”์†Œ๋Š” ์—ฐ๊ตฌ์ฐธ์—ฌ ๊ธฐ๊ฐ„์ด๋ฉฐ, ๊ฑด๊ฐ•ํ•œ ์ž์›์ž๋“ค์ด ์•ˆ์ „์„ฑ์— ๋Œ€ํ•ด ๋œ ์ค‘์š”ํ•˜๊ฒŒ ์ƒ๊ฐํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋ณด์ธ๋‹ค. 70% ์ด์ƒ์ด ์‹ฌ๊ฐํ•œ ๋ถ€์ž‘์šฉ์˜ ๋ฐœ์ƒ๊ฐ€๋Šฅ์„ฑ์— ๋Œ€ํ•ด์„œ ์—ผ๋ คํ•˜์ง€ ์•Š๊ณ , ๋˜ํ•œ ๋‹ค์Œ ์—ฐ๊ตฌ์— ์ฐธ์—ฌํ•  ์˜์‚ฌ๊ฐ€ ์žˆ์Œ์„ ๋ฐํ˜”๋‹ค. ์‹ฌ์ธต๋ฉด๋‹ด์„ ํ†ตํ•ด ๊ฑด๊ฐ•ํ•œ ์ž์›์ž์˜ ํŠน์ง•๊ณผ ๊ฑด๊ฐ•ํ•œ ์ž์›์ž๊ฐ€ ๊ฐ–๊ณ  ์žˆ๋Š” ์ž„์ƒ์‹œํ—˜์— ๋Œ€ํ•œ ์ธ์‹์— ๋Œ€ํ•ด์„œ ์‚ดํŽด๋ณด์•˜๋‹ค. ์‹ฌ์ธต๋ฉด๋‹ด์„ ์ง„ํ–‰ํ•œ ๊ฒฐ๊ณผ ๊ฑด๊ฐ•ํ•œ ์ž์›์ž๋“ค์€ ๋ชธ, ๋ณด์ƒ, ์œ„ํ—˜์— ๋Œ€ํ•ด์„œ ๊ฐœ์ธ์ ์ธ ๊ฒฝํ—˜์„ ๋ฐ”ํƒ•์œผ๋กœ ํ•œ ์ธ์‹์„ ๊ฐ–๊ณ  ์žˆ์—ˆ๋‹ค. ๊ฑด๊ฐ•ํ•œ ์ž์›์ž๋“ค์€ ๋ˆ์„ ๋ฒŒ๊ธฐ ์œ„ํ•ด์„œ ์ž์‹ ์˜ ๋ชธ์„ ์‚ฌ์šฉํ•œ๋‹ค๊ณ  ์ƒ๊ฐํ•˜๊ณ  ์žˆ๊ณ , ์ž„์ƒ์‹œํ—˜์— ์ฐธ์—ฌ๋ฅผ ํ•˜๊ธฐ ์œ„ํ•ด์„œ ๋ชธ์„ ์ค€๋น„ํ•œ๋‹ค๊ณ  ๋งํ•˜์˜€๋‹ค. ์ž„์ƒ์‹œํ—˜ ์ฐธ์—ฌ๋Š” ์ „์ ์œผ๋กœ ์ž์‹ ์˜ ์˜์ง€๋กœ ์ฐธ์—ฌํ•˜๋Š” ๊ฒƒ์ด์ง€๋งŒ, ์ž„์ƒ์‹œํ—˜ ๊ณผ์ • ์ž์ฒด๋Š” ์ˆ˜๋™์ ์ด๊ณ , ๊ทธ๋ ‡๊ธฐ ๋•Œ๋ฌธ์— ์ฑ…์ž„์„ ์ง€์ง€ ์•Š๋Š”๋‹ค๊ณ  ๋งํ•˜๊ณ  ์žˆ๋‹ค. ์œ„ํ—˜์— ๋Œ€ํ•ด์„œ๋Š” ์œ„ํ—˜์ด ๋†’์„์ˆ˜๋ก ๊ธˆ์ „์  ๋ณด์ƒ์•ก์ด ์ปค์งˆ ๊ฒƒ์ด๋ผ๋Š” ์ธ์‹์ด ์กด์žฌํ•˜๊ณ , ๋ฐ˜๋ฉด, ๋ณธ์ธ์˜ ์—ฐ๊ตฌ ์ฐธ์—ฌ ๊ฒฝํ—˜์œผ๋กœ ํ˜•์„ฑ๋œ ์œ„ํ—˜ ์ถ•์†Œ์˜ ๊ฒฝํ–ฅ์ด ๋ณด์ด๊ธฐ๋„ ํ•œ๋‹ค. ๋˜ํ•œ ๋ถ€์ž‘์šฉ์ด ๋ณธ์ธ์˜ ์—ฐ์•ฝํ•จ ๋•Œ๋ฌธ์ด๋ผ๋Š” ๊ฒฌํ•ด๋„ ์กด์žฌํ•œ๋‹ค. ๋ณด์ƒ์— ๋Œ€ํ•ด์„œ๋Š” ๊ธฐ๋ณธ์ ์œผ๋กœ ๊ฑด๊ฐ•ํ•œ ์ž์›์ž๋“ค์€ ์‚ฌํšŒ์  ๊ฐ€์น˜๋‚˜ ์ดํƒ€์ฃผ์˜์— ์˜ํ•ด์„œ ์ž„์ƒ์‹œํ—˜์— ์ฐธ์—ฌํ•˜๋Š” ๊ฒƒ์ด ์•„๋‹ˆ๋ผ ๊ฐœ์ธ์  ๊ฐ€์น˜ ์ถ”๊ตฌ๋ฅผ ์œ„ํ•ด์„œ ์ž„์ƒ์‹œํ—˜์— ์ฐธ์—ฌํ•˜๊ณ  ๊ทธ๊ฒƒ์€ ๋Œ€๋ถ€๋ถ„ ๊ธˆ์ „์  ๋ณด์ƒ์ด๋‹ค. ์‹ฌ์ธต๋ฉด๋‹ด์„ ํ†ตํ•ด ๊ฐœ์ธ์ ์ธ ๊ฒฌํ•ด๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ํ•œ ์ธ์‹์ด ์กด์žฌํ•˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๊ณ , ์ด๋ฅผ ํ†ตํ•ด ์ž„์ƒ์‹œํ—˜ ์ž์ฒด์— ๋Œ€ํ•œ ์ธ์‹์„ ์‚ดํŽด๋ณผ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์šฐ์„  ์ž„์ƒ์‹œํ—˜์— ๋Œ€ํ•œ ๋Œ€์ค‘์˜ ์ธ์‹์€ ๋ถ€์ •์ ์ด๊ณ  ๊ทธ๋ ‡๋‹ค ๋ณด๋‹ˆ ๊ฑด๊ฐ•ํ•œ ์ž์›์ž๋“ค์€ ๋ณธ์ธ์˜ ์—ฐ๊ตฌ ์ฐธ์—ฌ๋ฅผ ์•Œ๋ฆฌ๊ธฐ ๊บผ๋ คํ•œ๋‹ค. ์ž„์ƒ์‹œํ—˜์— ๋Œ€ํ•ด์„œ ๋ถ€์ •์ ์ธ ์ด์œ ๋Š” ์ž„์ƒ์‹œํ—˜์„ ์ž์„ธํžˆ ์•Œ์ง€ ๋ชปํ•˜๊ณ  ์‹คํ—˜๋™๋ฌผ์ฒ˜๋Ÿผ ์ž์‹ ์˜ ์‹ ์ฒด๋ฅผ ์—ฐ๊ตฌ์— ์‚ฌ์šฉํ•œ๋‹ค๊ณ  ์ƒ๊ฐํ•˜๋Š” ๊ฒƒ ๋•Œ๋ฌธ์ด๋‹ค. ์ด๋“ค์€ ๋ณธ์ธ์€ ์ž„์ƒ์‹œํ—˜์— ๋Œ€ํ•ด์„œ ๊ธ์ •์ ์ด์ง€๋งŒ ๋Œ€์ค‘์€ ๋ถ€์ •์ ์ธ ์ธ์‹์„ ๊ฐ–๊ณ  ์žˆ๋‹ค๊ณ  ์ƒ๊ฐํ•˜๋ฉฐ, ๊ทธ๋กœ ์ธํ•ด ์ž์‹ ์˜ ์—ฐ๊ตฌ ์ฐธ์—ฌ ์‚ฌ์‹ค์„ ์•Œ๋ฆฌ๋Š” ๊ฒƒ์„ ๊บผ๋ คํ•œ๋‹ค. ์ž„์ƒ์‹œํ—˜์€ ํ•˜๋‚˜์˜ ํŠน์ˆ˜ ์ง์—ญ์œผ๋กœ ์ž๋ฆฌ์žก์•˜๋‹ค. ๋ชจ๋“  ๊ฑด๊ฐ•ํ•œ ์ž์›์ž๋“ค์€ ์ž„์ƒ์‹œํ—˜์„ ์•„๋ฅด๋ฐ”์ดํŠธ๋ผ๊ณ  ํ‘œํ˜„ํ•˜์˜€๋‹ค. ๋‹ค๋ฅธ ์•„๋ฅด๋ฐ”์ดํŠธ์— ๋น„ํ•ด ๋“ค์ด๋Š” ๋…ธ๋™์˜ ์–‘์ด ์ ๊ณ , ํŽธํ•˜๊ธฐ ๋•Œ๋ฌธ์— ๋ฐ˜๋ณต์ ์œผ๋กœ ์—ฐ๊ตฌ์— ์ฐธ์—ฌํ•˜๊ฒŒ ๋œ๋‹ค. ๊ทธ๋ ‡๋‹ค ๋ณด๋‹ˆ ์ „๋ฌธํ™”๋œ ๊ฑด๊ฐ•ํ•œ ์ž์›์ž๋“ค์ด ๋งŒ๋“ค์–ด ์ง€๊ณ , ํ•˜๋‚˜์˜ ์•„๋ฅด๋ฐ”์ดํŠธ๋กœ ์ž๋ฆฌ์žก๊ณ  ์žˆ๋‹ค. ์ž„์ƒ์‹œํ—˜์— ์ฐธ์—ฌํ•œ ๊ฑด๊ฐ•ํ•œ ์ž์›์ž๋“ค์€ ๋ณธ์ธ์˜ ๋™์˜๋ฅผ ๊ณ„์•ฝ๊ด€๊ณ„๋กœ ์ธ์‹ํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ๋™์˜์„œ๋Š” ๊ณ„์•ฝ์„œ๋กœ ๋ณด๊ณ  ์žˆ๋‹ค. ๋˜ํ•œ ๋ณธ์ธ์€ ์ œ์•ฝํšŒ์‚ฌ๋‚˜ ์ž„์ƒ์‹œํ—˜ ์„ผํ„ฐ์— ๋ชธ์„ ์ œ๊ณตํ•˜๊ณ  ๊ทธ๋“ค์€ ์ž์‹ ๋“ค์˜ ๋ชธ, ์‹œ๊ฐ„์˜ ๋Œ€๊ฐ€๋กœ ๋ˆ์„ ์ง€๋ถˆํ•˜๋Š” ๋น„์ฆˆ๋‹ˆ์Šค๋กœ ์ธ์‹ํ•˜๊ณ  ์žˆ์—ˆ๋‹ค. ๊ฒฐ๋ก : ์ด๋ฒˆ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ํ•œ๊ตญ์—์„œ 1์ƒ ์ž„์ƒ์‹œํ—˜์— ์ฐธ์—ฌํ•˜๋Š” ๊ฑด๊ฐ•ํ•œ ์ž์›์ž๋Š” 2-30๋Œ€์˜ ๋ฏธํ˜ผ๋‚จ์„ฑ์ด ๋Œ€๋ถ€๋ถ„์ด๊ณ , ๊ธˆ์ „์  ๋ณด์ƒ์„ ๋™๊ธฐ๋กœ ์—ฐ๊ตฌ์— ์ฐธ์—ฌํ•˜๋Š” ๊ฒƒ์ด ํ™•์ธ๋˜์—ˆ๋‹ค. ๋˜ํ•œ ์—ฐ๊ตฌ์— ์ฐธ์—ฌํ•œ ๊ฑด๊ฐ•ํ•œ ์ž์›์ž๋“ค์˜ ๊ฐœ์ธ์ ์ธ ์ธ์‹์œผ๋กœ ์ž์‹ ์˜ ๋ชธ, ์ž„์ƒ์‹œํ—˜์˜ ์œ„ํ—˜, ๋ณด์ƒ์— ๊ด€ํ•œ ๊ฐœ๋…์ด ๊ตฌ์„ฑ๋˜์–ด ์žˆ๊ณ , ์ž„์ƒ์‹œํ—˜ ์ฐธ์—ฌ๊ฐ€ ํ•˜๋‚˜์˜ ์ง์—ญ์œผ๋กœ ์ž๋ฆฌ์žก๊ณ  ์žˆ์Œ์„ ํ™•์ธํ•˜์˜€๋‹ค.์ œ 1 ์žฅ ์„œ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ 1 ์ œ 2 ์ ˆ ์„ ํ–‰ ์—ฐ๊ตฌ 12 ์ œ 3 ์ ˆ ์—ฐ๊ตฌ ๋ชฉ์  22 ์ œ 2 ์žฅ ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 24 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ ์„ค๊ณ„ 24 ์ œ 2 ์ ˆ ์„ค๋ฌธ ์กฐ์‚ฌ 25 ์ œ 3 ์ ˆ ์งˆ์˜ ์‘๋‹ต ํ˜•ํƒœ์˜ ๊ฐœ์ธ ๋ฉด์ ‘ 27 ์ œ 4 ์ ˆ ์‹ฌ์ธต ๋ฉด๋‹ด 29 ์ œ 3 ์žฅ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ 37 ์ œ 1 ์ ˆ ํ•œ๊ตญ์˜ ์„ค๋ฌธ์กฐ์‚ฌ ๋ฐ ๊ฐœ์ธ ๋ฉด์ ‘ ๊ฒฐ๊ณผ 37 ์ œ 2 ์ ˆ ํ•œ์ผ ๊ฐ„์˜ ์„ค๋ฌธ ์กฐ์‚ฌ ๋น„๊ต 60 ์ œ 3 ์ ˆ ๋ณ€์ˆ˜๊ฐ„์˜ ์ƒ๊ด€๊ด€๊ณ„ ๋ถ„์„ ๊ฒฐ๊ณผ 79 ์ œ 4 ์ ˆ ์‹ฌ์ธต๋ฉด๋‹ด ๊ฒฐ๊ณผ 85 ์ œ 4 ์žฅ ๊ณ ์ฐฐ 134 ์ œ 5 ์žฅ ๊ฒฐ๋ก  150 ์ œ 6 ์žฅ ์ฐธ๊ณ  ๋ฌธํ—Œ 155 ๋ถ€๋ก 164 Abstract 171Docto

    Variable matrix-type step-size affine projection algorithm with orthogonalized input vectors

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    MasterThis thesis proposes a variable matrix-type step-size affine projection algorithm (APA) with orthogonalized input vectors. We generate orthogonalized input vectors using theGram-Schmidt process so as to implement the weight update equation of the APA using the sum of normalized least mean square (NLMS)-like updating equations. This method allows us to use individual step sizes corresponding to each NLMS-like equation. This is equivalent to adopting the step size in the form of a diagonal matrix in the APA. A variable step-size scheme is adopted to improve the performance of the filter. The individual step sizes are determined to minimize the mean square deviation of the APA. The experimental results show that the proposed algorithm has a faster convergence rate and a smaller steady-state estimation error than the existing APAs

    Nuclear transcription factor and signal transduction for chemokine expression in hel

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    ์˜๊ณผํ•™์‚ฌ์—…๋‹จ/์„์‚ฌ[ํ•œ๊ธ€] Helicobacter pylori (H. pylori)๋Š” ๋‹ค์–‘ํ•œ ์œ„์žฅ๊ด€์งˆํ™˜์„ ์ผ์œผํ‚ค๋Š” ์›์ธ๊ท ์œผ๋กœ ์•Œ๋ ค์ ธ ์žˆ๋‹ค. H. pylori๋Š” ์ง€์—ญ๊ณผ ์‚ฌํšŒ, ๊ฒฝ์ œ์  ์—ฌ๊ฑด์— ๋”ฐ๋ผ ์œ ๋ณ‘๋ฅ ์˜ ๋งŽ์€ ์ฐจ์ด๋ฅผ ๋ณด์ด๋ฉฐ ๊ตญ๊ฐ€๋ณ„๋กœ H. pylori strain์˜ ์œ ์ „์žํ˜•์— ์ฐจ์ด๋ฅผ ๋ณด์ธ๋‹ค๊ณ  ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ์‚ฐํ™”, ํ™˜์›์— ์˜ํ•˜์—ฌ ํ™œ์„ฑ์ด ๋ฏผ๊ฐํ•˜๊ฒŒ ์กฐ์ ˆ๋˜๋Š” ํ•ต์ „์‚ฌ์กฐ์ ˆ์ธ์ž์ธ NF-ฮบB์™€ AP-1์€ ์นœ์—ผ์ฆ์„ฑ chemokine์ธ IL-8๊ณผ MCP-1 ์ƒ์„ฑ์„ ์กฐ์ ˆํ•˜๋Š” ๊ฒƒ์œผ๋กœ ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ํ‘œ์ค€ํ˜• H. pylori ๊ท ์ฃผ์ธ NCTC11637๊ณผ ํ•œ๊ตญ์ธ ํ™˜์ž์˜ ์ ๋ง‰์—์„œ ๋ถ„๋ฆฌํ•œ H. pylori ๊ท ์ฃผ์ธ HP99๋ฅผ ์ธ์ฒด ์œ„ ์ƒํ”ผ์„ธํฌ์ฃผ์ธ AGS์— ๊ฐ์—ผ์‹œ์ผœ ๊ท ์ฃผ ์ฐจ์ด์— ์˜ํ•œ ์„ธํฌ์˜ ํ•ต์ „์‚ฌ์กฐ์ ˆ์ธ์ž ๋ฐ Mitogen-activated protein kinase(MAPK)์˜ ํ™œ์„ฑ์„ ๊ทœ๋ช…ํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ์•„์šธ๋Ÿฌ ์ด๋“ค ๊ท ์ฃผ์— ๋Œ€ํ•œ chemokine ์œ ์ „์ž ๋ฐœํ˜„์˜ ์ฐจ์ด์™€ chemokine ์œ ์ „์ž ๋ฐœํ˜„์— ๋Œ€ํ•œ ํ•ต์ „์‚ฌ์ธ์ž ๋ฐ MAPK ํ™œ์„ฑ์˜ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๊ทœ๋ช…ํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ๋จผ์ € H. pylori strain์˜ ์ฐจ์ด๋ฅผ ๊ทœ๋ช…ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์ด๋“ค ๊ท ์ฃผ์˜ ๋ณ‘๋…์ธ์ž์ธ cagA, iceA, vacA์˜ ์œ ์ „์žํ˜•์„ ํ™•์ธํ•œ ๋ฐ” ๋‘ ๊ท ์ฃผ์˜ vacA ์œ ์ „์žํ˜•์ด ์„œ๋กœ ๋‹ฌ๋ž๋‹ค. Urease ํ™œ์„ฑ๋„ ๋ฐ ์ด๋“ค ๊ท ์ฃผ์— ์˜ํ•œ AGS ์„ธํฌ์˜ H2O2์˜ ์ƒ์„ฑ๋Ÿ‰์„ ์ธก์ •ํ•œ ๊ฒฐ๊ณผ, NCTC ๊ท ์ฃผ์˜ urease ํ™œ์„ฑ๋„ ๋ฐ AGS ์„ธํฌ์˜ H2O2 ์ƒ์„ฑ๋Ÿ‰์€ HP99์˜ ๊ท ์ฃผ์— ๋น„ํ•˜์—ฌ ๋†’์•˜๋‹ค. ๋˜ํ•œ ์ด๋“ค H. pylori ๊ท ์ฃผ ๊ฐ์—ผ์— ์˜ํ•œ AGS ์„ธํฌ์˜ chemokine์ธ IL-8 ๋ฐ MCP-1 mRNA ๋ฐœํ˜„๊ณผ ๋‹จ๋ฐฑ ์ƒ์„ฑ, NF-ฮบB์™€ AP-1 ์˜ ํ™œ์„ฑ๋„ ๋ฐ MAPK (ERK, JNK, p38)์˜ ํ™œ์„ฑ๋„๋ฅผ ์ธก์ •ํ•˜์˜€๋‹ค. ๊ทธ ๊ฒฐ๊ณผ NCTC11637 ๋ฐ HP99 H. pylori ๊ท ์ฃผ ๋ชจ๋‘ AGS ์„ธํฌ์˜ NF-ฮบB ํ™œ์„ฑ๊ณผ IL-8 ์ƒ์„ฑ ์ฆ๊ฐ€์— ์žˆ์–ด์„œ๋Š” ๋น„์Šทํ•˜์˜€๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ HP99 ๊ท ์ฃผ๊ฐ€ ๊ฐ์—ผ๋œ AGS ์„ธํฌ์˜ AP-1 ํ™œ์„ฑ, MCP-1 ๋ฐœํ˜„ ๋ฐ MAPK (ERK, JNK, p38)์˜ ํ™œ์„ฑ์€ NCTC11637 ๊ท ์ฃผ๋กœ ๊ฐ์—ผ๋œ AGS ์„ธํฌ์—์„œ๋ณด๋‹ค ๋†’์•˜๋‹ค. H. pylori ๊ท ์ฃผ์— ์˜ํ•œ AGS ์„ธํฌ์˜ IL-8 ๋ฐ MCP-1 ๋ฐœํ˜„ ์ฆ๊ฐ€๊ฐ€ ์–ด๋–ค ํ•ต์ „์‚ฌ์ธ์ž์— ์˜ํ•˜์—ฌ ๋งค๊ฐœ๋˜๋Š”์ง€ ์—ฌ๋ถ€ ๋ฐ MAPK์˜ ๊ด€์—ฌ๋ฅผ ์—ฌ๋ถ€๋ฅผ ์•Œ์•„๋ณด๊ธฐ ์œ„ํ•˜์—ฌ, IฮบBฮฑ mutant ์œ ์ „์ž์ธ MAD3 ๋˜๋Š” c-jun ๋ฐ ras์˜ dominant negative ์œ ์ „์ž์ธ TAM67, rasN-17 ์œ ์ „์ž๋ฅผ ์„ธํฌ๋‚ด๋กœ transfection ์‹œ์ผœ ๊ฐ๊ฐ NF-ฮบB, AP-1 ๊ทธ๋ฆฌ๊ณ  ras์˜ ํ™œ์„ฑํ™”๋ฅผ ์–ต์ œ์‹œํ‚ค๊ฑฐ๋‚˜, MEK1/2์˜ ์–ต์ œ์ œ์ธ U0126 ๊ณผ p38 ์–ต์ œ์ œ์ธ SB203580์„ ์ฒ˜์น˜ํ•˜์—ฌ ERK ๋ฐ p38์˜ ํ™œ์„ฑํ™”๋ฅผ ๊ฐ๊ฐ ์–ต์ œ์‹œํ‚จ ํ›„ IL-8 ๋ฐ MCP-1 ๋ฐœํ˜„์„ ์ธก์ •ํ•˜์˜€๋‹ค. H. pylori์— ์˜ํ•œ IL-8์˜ ๋ฐœํ˜„ ์ฆ๊ฐ€๋Š” ์ฃผ๋กœ H. pylori์— ์˜ํ•˜์—ฌ ์ฆ๊ฐ€ํ•˜๋Š” NF-ฮบB์— ์˜ํ•˜์—ฌ ๋งค๊ฐœ๋˜๋ฉฐ, MCP-1 ๋ฐœํ˜„ ์ฆ๊ฐ€์—๋Š” AP-1 ๋ฐ MAPK์˜ ์ƒ์œ„๋‹จ๊ณ„์— ์žˆ๋Š” ras์— ์˜ํ•˜์—ฌ ๋งค๊ฐœ๋œ๋‹ค. ๊ทธ๋ฆฌ๊ณ  H. pylori์— ์˜ํ•˜์—ฌ ์ฆ๊ฐ€ํ•˜๋Š” IL-8 ๋ฐ MCP-1 ๋ฐœํ˜„ ์ฆ๊ฐ€๋Š” MAPK ์ค‘ ERK ๋ฐ p38์— ์˜ํ•˜์—ฌ ์ฃผ๋กœ ๋งค๊ฐœ๋œ๋‹ค. ๊ฒฐ๋ก ์ ์œผ๋กœ H. pylori ๊ฐ์—ผ์— ์˜ํ•œ ์œ„ ์ƒํ”ผ์„ธํฌ์˜ ํ•ต์ „์‚ฌ์กฐ์ ˆ์ธ์ž, MAPK์˜ ํ™œ์„ฑ ๋ฐ chemokine์˜ ๋ฐœํ˜„ ์ฆ๊ฐ€๋Š” ๊ท ์ฃผ์— ๋”ฐ๋ผ ๋‹ค๋ฅด๊ฒŒ ๋‚˜ํƒ€๋‚˜๋ฉฐ, H. pylori ๊ท ์ฃผ์— ์˜ํ•˜์—ฌ ์ฆ๊ฐ€ํ•˜๋Š” chemokine์˜ ๋ฐœํ˜„๋„ ํ•ต์ „์‚ฌ์กฐ์ ˆ์ธ์ž ๋ฐ MAPK์— ์˜ํ•˜์—ฌ ์„œ๋กœ ๋‹ค๋ฅด๊ฒŒ ์กฐ์ ˆ๋œ๋‹ค. [์˜๋ฌธ] Helicobacter pylori (H. pylori) is a major cause of chronic gastritis, peptic ulcer and gastric carcinoma. HP99 and NCTC11637 are H. pylori strains which are isolated from gastric mucosa from the patients in Korea and Australia repectively. Predominant genotype of H. pylori showed the discrepancy for activating transcription factors NF-ฮบB and AP-1 and stimulating the expression of chemokines, IL-8 and MCP-1 in AGS cells. iceA, vacA and cagA of H. pylori genes were genotyped by PCR. After treatment of H. pylori to AGS cells, activation of transcription factors were assessed by EMSA. Chemokine levels for mRNA and protein were determined by RT-PCR and ELISA. MAPK(ERK, JNK, p38) activation was assessed by Western blot. Both H. pylori strains resulted in NF-ฮบB activation and IL-8 expression. However, HP99 showed high AP-1 activation, MCP-1 expression and MAPKinase activation as compared to NCTC11637. H. pylori induced chemokine expression was inhibited in the cells transfected with mutant genes for ras, c-jun and I-ฮบB. The specific MAPK inhibitors, U0126 (20uM; MAPKinase kinase (MEK1/2)) and SB203580 (20uM; p38 inhibitor), reduced both H. pylori-induced IL-8 and MCP-1 production. In conclusion, different genotype of H. pylori strains showed different / signaling pathway for activation of transcription factors and MAP / Kinase, resulting in different chemokine expression in gastric epithelial /cells.ope

    OWC-MB Hybrid Wave Energy Harvesting System with Multi-Resonators Attached to Vertical Breakwaters

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    Ocean wave is one of renewable energy sources, of which the theoretical energy potential is estimated to be 32,000 TWh/yr according to Mรธrk et al. (2010), however, that is highly underutilized up to recently. In this study, a new system is proposed, that can enhance not only the efficiency of the system by using resonant phenomena in wave channel but also the economic feasibility by using existing caissonโ€“type breakwater as support structure. To evaluate the performance of proposed system, numerical analyses by using Galerkinโ€™s finite element model based on the linear potential theory were carried out for various damping ratio which is directly related to extracting wave power. Numerical results reveal that the performance of the proposed system is fairly good compared with that of the conventional one, and the resonance of the oscillating water column in wave channel is dominated. Hydraulic model tests were carried out for three different wave channels including floaters by using regular waves. To evaluate viscous damping effects of PTO system, it was measured the floater motions, free surface fluctuations, and wave reflections. To quantify the viscous damping, numerical experiments were also performed for the hydraulic model cases. The comparative results from hydraulic model tests and numerical analysis show that the viscous damping is about 5% of the critical damping of the vertical movement of the floater in the wave channel. It was also found that the viscous damping increases, as the width of the channel decreases. Viscous damping might come from mainly flow separations at the gap between side wall of wave channel and moving floater. Friction between them may also be contributed to attenuation of floater heave motion. In addition, on the basis of reflection coefficients obtained from experiment, the closest viscous damping ratio of floater can be found to be about 20% through a numerical analysis, and the reflection coefficients was investigated according to the existence of floater to examine the trend of nonlinearities due to the wave channel and indicated by the energy loss coefficients of incident wave. it was evaluated efforts to minimize the attenuation as needed because viscous damping occurring in the channel and around the moving floater is significant in generation efficiency. Viscous damping can be reduced significantly if two damping sources aforementioned can be removed. However, it is impossible to remove the damping sources completely, therefore the PTO system should be designed considering the viscous damping properly through further optimization.CHAPTER 1. INTRODUCTION 1.1 BACKGROUND 1.2 LITERATURE SURVEY 1.3 RESEARCH OBJECTIVES 1.4 SCOPE OF THIS STUDY CHAPTER 2. FORMULATION OF THE PROBLEM 2.1 WAVE MOTION 2.2 FLOATER MOTION 2.3 FINITE ELEMENT FORMULATION CHAPTER 3. PERFORMANCE ANALYSIS 3.1 DESIGN OF PROPOSED PTO SYSTEM 3.2 FINITE ELEMENT MESH 3.3 NUMERICAL RESULTS 3.4 CONCLUDING REMARKS CHAPTER 4. HYDRAULIC MODEL TEST 4.1 GENERAL 4.2 WAVE FLUME AND MODEL SETUP 4.3 EXPERIMENTAL RESULTS 4.4 COMPARISON WITH NUMERICAL AND EXPERIMENTAL RESULTS 4.5 CONCLUDING REMARKS CHAPTER 5. CONCLUSION 5.1 SUMMARY AND CONCLUSION 5.2 FUTURE WORKS SUMMARY (in Korean) REFERENCES ACKNOWLEDGEMENTS CURRICULUM VITA

    Performance Improvement of Subband Adaptive Filtering Algorithm based on Mean-Square Analysis and Its Extension to Distributed Estimation

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    DoctorThis dissertation presents study on performance improvement of subband adaptive filtering (SAF) algorithm and its extension to distributed estimation over network. The mean-square deviation (MSD) is analyzed in advance to examine the behavior of the SAF algorithm, where it gives us chance to improve the performance of the algorithm in terms of the convergence rate and the steady-state estimation errors as well as to improve the accuracy of the distributed estimation. First, in Chapter 2, we propose the SAF algorithm which improves its performance by deriving optimal step sizes based on the MSD analysis. The proposed algorithm deals with the individual step sizes for each subband update instead of a common step size for multiple subband updates. The derivation of the step sizes is based on the MSD minimization with respect to the individual step size in order to achieve the fastest convergence at the instant. Furthermore, the individual step size contain the squared norm of the input vector at each subband update, so it leads to the regularization effect that helps the proposed algorithm work well in the case of badly-excited input signals. Simulation results show that the proposed algorithm achieves faster convergence rate and smaller steady-state estimation error than the existing algorithms for highly correlated input cases. Second, in Chapter 3, the work of Chapter 2 is extended to distributed estimation over network by introducing a novel diffusion SAF algorithm. The MSD behavior of the diffusion SAF algorithm is analyzed and the performance improvement strategies are developed in two ways; the MSD-optimal variable step size for computation at each node (adaptation step) and the MSD-based combination method for communication among neighboring nodes (combination step). For the adaptation step, the upper bound of the MSD for the intermediate estimate is derived and the step size is adapted by minimizing it in order to attain the fastest convergence rate on every iteration. Furthermore, for the combination step realized by a convex combination of the neighboring-node estimates, the proposed algorithm uses the MSD, which contains information on the reliability of the estimates, to determine combination coefficients. Simulation results show that the proposed algorithm outperforms the existing diffusion adaptive filtering algorithms in terms of the convergence rate and the steady-state errors when the network has spatial variation of node profile including input coloredness and noise statistics

    Discovery of new therapeutic agents using extracellular vesicles based sepsis drug screening system

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    MasterSepsis is a systemic inflammatory response syndrome triggered by an infection, with the symptoms such as hypothermia, tachypnea and leukopenia. Secretion of pro-inflammatory cytokines like TNF-ฮฑ is induced in septic environment, and especially, TNF-ฮฑ, a master regulator, excessively activates the host immune system by triggering inflammatory cascades. This massive activation provokes the successive intravascular coagulopathy and multiple organ failure eventually. Due to this severe consequence of sepsis, its mortality rate reaches up to 30%, which increases the social cost of treatment. Though antibiotics treatment is usually used to treat sepsis, it can even exacerbate the status of disease by the activation of host immune system with increased amount of released bacterial cell wall components. Because there is no commercial and specific drug for sepsis, new therapeutic agents are urgently required. To discover new therapeutic agents, I used the extracellular vesicles (EVs)-based in vitro screening system. The EVs derived from Escherichia coli were treated to Raw264.7 to induce the secretion of TNF-ฮฑ. The 80 different kinds of kinase inhibitors were screened the ability to reduce TNF-ฮฑ secretion in the system. From the screening, Damnacanthal was selected for the potent drug candidate, which is previously known as an inhibitor of p56 Lck. Moreover, Damnacathal showed the inhibitory effects on TNF-ฮฑ secretion induced by various single PAMPs in vitro and on the infiltration of immune cells in skin inflammation model induced by EVs in vivo. To verify the mechanism of anti-inflammatory function of Damnacanthal, the inhibitory effects on TNF-ฮฑ secretion was verified in Src family kinase inhibitors such as PP1, PP2 and PP3 (negative control for PP2); PP1 and PP2 also reduced the TNF-ฮฑ secretion induced by EVs. Then, the kinase inhibitor activities of Damnacanthal, PP1 and PP2 were assessed to confirm the relationship between the suppression of TNF-ฮฑ secretion and the inhibition of Src family kinase. As a result, PP1 and PP2 inhibited the phosphorylation (Tyr416) of Src family kinase, but Damnacanthal did not inhibit the phosphorylation despite the existence of Hck, Lck and c-Src in Raw264.7 cell. These indicated that the anti-inflammatory effects of Damnacanthal are not dependent on the inhibition of Src family kinase activity. As an alternative, I focused on the anti-inflammatory cytokines, especially interleukin-10, which is known to suppress the production and release of TNF-ฮฑ. Since Damnacanthal induced the secretion of interleukin-10 in the EV-based screening system, the inhibitory effects on TNF-ฮฑ secretion by Damnacanthal seem to be mediated by interleukin-10. Therefore, the inhibitory ability of Damnacanthal for TNF-ฮฑ secretion, which reduces the damages on cells or tissues, can be used to treat sepsis.ํŒจํ˜ˆ์ฆ (sepsis)๋Š” ๊ฐ์—ผ์— ์˜ํ•ด ์ „์‹ ์— ์‹ฌ๊ฐํ•œ ์—ผ์ฆ ๋ฐ˜์‘์ด ๋‚˜ํƒ€๋‚˜๋Š” ์งˆ๋ณ‘์ด๋‹ค. ์ €์ฒด์˜จ์ฆ, ๋นˆํ˜ธํก, ๋ฐฑํ˜ˆ๊ตฌ ๊ฐ์†Œ ๋“ฑ์˜ ์ฆ์ƒ์„ ๋™๋ฐ˜ํ•˜๋ฉฐ, TNF-ฮฑ ์™€ ๊ฐ™์€ ์—ผ์ฆ์„ฑ ์‚ฌ์ดํ† ์นด์ธ ๋ถ„๋น„๋ฅผ ์ด‰์ง„ ์‹œ์ผœ ๋ฉด์—ญ ์ฒด๊ณ„๋ฅผ ๊ณผ๋„ํ•˜๊ฒŒ ํ™œ์„ฑํ™”ํ•˜๊ณ , ์ด๋Š” ํ˜ˆ๊ด€ ๋‚ด ํ˜ˆ์•ก ์‘๊ณ  ์žฅ์• ๋ฅผ ์•ผ๊ธฐ์‹œ์ผœ, ๋งˆ์นจ๋‚ด ๋ณตํ•ฉ ์žฅ๊ธฐ ๋ถ€์ „์„ ์œ ๋ฐœ์‹œํ‚จ๋‹ค. ์ด๋Ÿฌํ•œ ํŒจํ˜ˆ์ฆ ํ™˜์ž์˜ ์‚ฌ๋ง๋ฅ ์€ 30%์— ์ด๋ฅด๊ณ , ์ด๋กœ ์ธํ•œ ์‚ฌํšŒ์  ๋น„์šฉ ์—ญ์‹œ ํฌ๊ฒŒ ์ฆ๊ฐ€ํ•˜๊ณ  ์žˆ๋‹ค. ์ด๋ฅผ ์น˜๋ฃŒํ•˜๊ธฐ ์œ„ํ•ด ํ”ํžˆ ์‚ฌ์šฉ๋˜๋Š” ํ•ญ์ƒ์ œ ์น˜๋ฃŒ์˜ ๊ฒฝ์šฐ ์˜คํžˆ๋ ค ์„ธ๊ท ์˜ ๊ตฌ์„ฑ ์„ฑ๋ถ„๋“ค์„ ํ˜ˆ์•ก ๋‚ด๋กœ ํผ์ง€๊ฒŒ ํ•˜์—ฌ ํŒจํ˜ˆ์ฆ์„ ๋”์šฑ ์•…ํ™”์‹œํ‚ฌ ์ˆ˜ ์žˆ์œผ๋ฉฐ, ์ด ๋ฐ–์— ๋‹ค๋ฅธ ์น˜๋ฃŒ์ œ์˜ ๊ฐœ๋ฐœ์ด ์‹œ๊ธ‰ํ•œ ์ƒํ™ฉ์ด๋‹ค. ์ด๋Ÿฌํ•œ ํŒจํ˜ˆ์ฆ์˜ ์ƒˆ๋กœ์šด ์•ฝ๋ฌผ์„ ๋ฐœ๊ตดํ•˜๊ธฐ ์œ„ํ•ด Raw264.7 ์„ธํฌ์— ์„ธ๊ท  ์œ ๋ž˜ Extracellular vesicle์„ ์ฒ˜๋ฆฌํ•˜์—ฌ TNF-ฮฑ ๋ถ„๋น„๋ฅผ ์œ ๋„ํ•˜๋Š” screening system์„ ์ด์šฉํ•˜์˜€๋‹ค. Extracellular vesicles-based screening system์—์„œ 80 ์ข…์˜ Kinase inhibitor๊ฐ€ EV๋กœ ์œ ๋„๋œ TNF-ฮฑ ๋ถ„๋น„๋ฅผ ์ €ํ•ดํ•˜๋Š” ์ •๋„๋ฅผ ํ™•์ธํ•˜์˜€๊ณ , ๊ทธ ๊ฒฐ๊ณผ p56 Lck์˜ ๊ธฐ๋Šฅ์„ ์ €ํ•ดํ•œ๋‹ค๊ณ  ์•Œ๋ ค์ง„ Damnacanthal์ด ์น˜๋ฃŒ ์•ฝ๋ฌผ ํ›„๋ณด๋กœ ์„ ์ •๋˜์—ˆ๋‹ค. Damnacanthal์˜ ํ•ญ ์—ผ์ฆ ํšจ๊ณผ๋ฅผ ํ™•์ธํ•˜๋Š” ์‹คํ—˜์—์„œ Damnacanthal์€ ๋‹ค์–‘ํ•œ single PAMP๋กœ ์ธํ•ด ์œ ๋„๋œ TNF-ฮฑ ๋ถ„๋น„๋ฅผ ์–ต์ œํ•˜์˜€๊ณ , EV๋กœ ํ”ผ๋ถ€์— ์œ ๋„๋œ ์—ผ์ฆ์—์„œ ํŒจํ˜ˆ์ฆ์˜ ์ฆ์ƒ ์ค‘ ํ•˜๋‚˜์ธ ๋ฉด์—ญ ์„ธํฌ์˜ ์กฐ์ง ๋‚ด ์นจ์ž…์„ ์ €ํ•ดํ•˜๋Š” ํšจ๊ณผ๋ฅผ ๋ณด์˜€๋‹ค. Damnacanthal์ด ๋Œ€์‹์„ธํฌ์—์„œ TNF-ฮฑ ๋ถ„๋น„๋ฅผ ์ €ํ•ดํ•˜๋Š” ํ•ญ ์—ผ์ฆ ์ž‘์šฉ์˜ ๊ธฐ์ „์„ ์•Œ์•„๋ณด๊ณ ์ž Damnacanthal๊ณผ ๊ฐ™์ด Src family kinase๋ฅผ ์ €ํ•ดํ•˜๋Š” PP1, PP2์™€ PP2์˜ ๋Œ€์กฐ๊ตฐ์œผ๋กœ ์‚ฌ์šฉ๋˜๋Š” PP3์— ๋Œ€ํ•ด TNF-ฮฑ ๋ถ„๋น„ ์ €ํ•ด ๋Šฅ๋ ฅ์„ ์‚ดํŽด ๋ณธ ๊ฒฐ๊ณผ, PP1๊ณผ PP2 ์—ญ์‹œ TNF-ฮฑ ๋ถ„๋น„๋ฅผ ์ €ํ•ดํ•˜์˜€๋‹ค. Src family kinase ์–ต์ œ๊ฐ€ TNF-ฮฑ ๋ถ„๋น„ ์ €ํ•ด ๋Šฅ๋ ฅ๊ณผ ๊ด€๊ณ„๊ฐ€ ์žˆ๋Š”์ง€ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•ด Damnacanthal, PP1, PP2๊ฐ€ Src family kinase ํ™œ์„ฑํ™”๋ฅผ ์–ต์ œํ•˜๋Š” ์ง€ ์—ฌ๋ถ€๋ฅผ ํ™•์ธํ•˜์˜€๋‹ค. Hck, Lck, c-Src๊ณผ ๊ฐ™์€ Src family kinase ๊ฐ€ Raw264.7 ์„ธํฌ์— ์กด์žฌํ•˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€์œผ๋‚˜, Damnacanthal์˜ ๊ฒฝ์šฐ Src family kinase์˜ ์ธ์‚ฐํ™” (ํ™œ์„ฑํ™”)๋ฅผ ์ €ํ•ดํ•˜์ง€ ๋ชปํ•ด, Damnacanthal์˜ TNF-ฮฑ ๋ถ„๋น„ ์ €ํ•ด ๋Šฅ๋ ฅ์€ Src family kinase ๋น„ํ™œ์„ฑํ™”์— ์˜์กด์ ์ด์ง€ ์•Š๋‹ค๋Š” ๊ฒฐ๋ก ์„ ๋‚ด๋ฆด ์ˆ˜ ์žˆ์—ˆ๋‹ค. TNF-ฮฑ์™€ ๊ฐ™์€ ์—ผ์ฆ์„ฑ ์‚ฌ์ดํ† ์นด์ธ์˜ ์ƒ์„ฑ๊ณผ ๋ถ„๋น„๋ฅผ ์–ต์ œํ•œ๋‹ค๊ณ  ์•Œ๋ ค์ง„ ํ•ญ ์—ผ์ฆ์„ฑ ์‚ฌ์ดํ† ์นด์ธ IL-10์— ์ฃผ๋ชฉํ•˜์—ฌ, EV-based screening system์—์„œ Damnacanthal์ด IL-10 ์ƒ์„ฑ์„ ์œ ๋„ํ•˜๋Š”์ง€ ์—ฌ๋ถ€๋ฅผ ํ™•์ธํ•œ ๊ฒฐ๊ณผ, Damnacanthal์€ ๋Œ€์‹์„ธํฌ์—์„œ IL-10 ์ƒ์„ฑ ๋ฐ ๋ถ„๋น„๋ฅผ ์ด‰์ง„ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ํ™•์ธ๋˜์—ˆ๋‹ค. ์ด๋กœ์จ Damnacanthal์˜ TNF-ฮฑ ๋ถ„๋น„ ์ €ํ•ด ๋Šฅ๋ ฅ์€ IL-10์„ ํ†ตํ•œ ํ•ญ ์—ผ์ฆ์„ฑ ๋ฐ˜์‘์— ์˜ํ•ด ๋งค๊ฐœ๋˜๋Š” ๊ฒƒ์œผ๋กœ ๋ณด์ด๋ฉฐ, TNF-ฮฑ ๋ถ„๋น„๋ฅผ ์ €ํ•ดํ•˜์—ฌ ๋ฉด์—ญ ์ฒด๊ณ„๊ฐ€ ๊ณผ๋„ํ•˜๊ฒŒ ํ™œ์„ฑํ™”๋˜๋Š” ๊ฒƒ์„ ๋ง‰๋Š” Damnacanthal์€ ํŒจํ˜ˆ์ฆ์˜ ์น˜๋ฃŒ ์•ฝ๋ฌผ๋กœ ์‚ฌ์šฉ๋  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๋ณด์ธ๋‹ค
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