9 research outputs found

    The storage condition, composition and application of platelet-rich plasma for cartilage regeneration

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์˜๊ณผ๋Œ€ํ•™ ์˜ํ•™๊ณผ, 2020. 8. ์ด๋ช…์ฒ .Purpose: The purpose of this study was to investigate the practical use of plateletโ€rich plasma (PRP) for cartilage regeneration. For this purpose, the author evaluated 1) the concentrations of growth factors in PRP, depending on the storage conditions; 2) the effects of leukocyte concentrations in PRP on the proliferation and chondrogenesis of synovial membrane-derived mesenchymal stem cells (SDSCs) and chondrocytes; and 3) in vivo effectiveness of PRP with a hyaluronic acid (HA) hydrogel for cartilage regeneration. Materials and Methods: To evaluate growth factor concentration in PRP based on storage conditions, PRP samples were stored at 24โ„ƒ (room temperature group), 4โ„ƒ (refrigerator group), and โˆ’70โ„ƒ (deepโ€freezer group). In each temperature, four aliquots were prepared based on the time of analysis (immediately, 1, 3, 7 days after preparation). After storage, concentrations of plateletโ€derived growth factorโ€AA (PDGFโ€AA), transforming growth factorโ€ฮฒ (TGFโ€ฮฒ), vascular endothelial growth factor (VEGF), insulinโ€like growth factorโ€1 (IGFโ€1), and fibroblast growth factorโ€basic (FGFโ€B) were assessed with/without activation using Quantikine colorimetric sandwich immunoassay kits. PRP was activated with 10% Tritonโ€X for PDGFโ€AA, VEGF, FGFโ€B, IGFโ€1 measurement and sonication for TGFโ€ฮฒ1 measurement. To evaluate the effect of leukocyte concentrations in PRP on the proliferation and chondrogenesis of SDSCs and chondrocytes, we prepared two PRP formulations: (1) leukocyte-poor PRP (P-PRP) and (2) leukocyte-rich PRP (L-PRP). SDSCs and chondrocytes were obtained by enzymatic digestion of synovial tissues and the cartilage from a knee joint undergoing total knee arthroplasty. The primary cells were expanded in Dulbeccos modified Eagles medium supplemented with fetal bovine serum (FBS), L-PRP, or P-PRP. Cell proliferation was measured using the MTT assay. SDSCs and chondrocytes were cultured with chondrogenic medium (CM) only, CM with L-PRP, or CM with P-PRP using a high-density pellet culture system for 3 weeks. The expression of chondrogenesis-related genes (type II collagen, type X collagen, aggrecan, and SOX-9) were analyzed by RT-qPCR. Pellets were stained with safranin-O for proteoglycan detection. The expression of type II collagen was detected by immunohistochemical staining. To evaluate the effect of PRP in combination with the HA hydrogel on in vivo cartilage regeneration, eighteen rabbit osteochondral defect models (round shape defect in the femoral trochlear groove with 4 mm in radius and 3 mm in depth) were made and divided into 3 groups: control group, in which the defect was left untreated; HA group, in which the defect was filled with the HA hydrogel; and HA-PRP group, in which the defect was filled with HA hydrogel and PRP. After 12 weeks, tissue specimens were assessed by macroscopic examination, histological evaluation, and by measuring the glycosaminoglycan (GAG) content. Results: Regarding growth factor concentration in PRP based on storage conditions, PDGFโ€AA concentration was highest on day 7 in the room temperature group without activation. With activation, the concentration of PDGFโ€AA was constant over the observation period at all temperatures. Without activation, the TGFโ€ฮฒ1 concentration remained negligible over the observation period at all temperatures. However, with activation, TGFโ€ฮฒ1 concentration was highest on day 7 at all temperatures. Over the observation period, VEGF and IGFโ€1 concentration were constant with and without activation at all temperatures. Without activation, FGFโ€B concentration was highest on day 7 in the deepโ€freezer group. With activation, FGFโ€B concentration decreased after day 1 in the room temperature group. Regarding the effect of the leukocyte concentration in PRP on the proliferation and chondrogenesis of SDSCs and chondrocytes, L-PRP showed a stronger proliferative effect on both types of cells than P-PRP and FBS. Meanwhile, RT-qPCR revealed higher cartilage-related gene expression in SDSCs and chondrocytes in the P-PRP group compared with that in the L-PRP and CM groups. However, SDSCs and chondrocytes in both PRP groups showed weaker safranin-O staining than those in the CM group. In immunohistochemical analysis, positive staining of SDSCs were not observed in either of the PRP groups and staining of chondrocytes in both PRP groups were weaker than those in the CM group. Regarding the effect of PRP combined with the HA hydrogel on in vivo cartilage regeneration, the macroscopic ICRS scores were not different among the three groups. The HA and HA-PRP groups showed significantly higher microscopic ODriscoll scores and a significantly higher GAG content than the control group, although the values were not different between the HA and HA-PRP groups. Conclusion: The growth factor concentrations significantly differed in PRP, depending on the storage temperature, duration of storage, and activation. Regardless of the leukocyte concentration, PRP showed a negative effect on chondrogenesis of SDSCs and chondrocytes. In addition, a combined use of the HA hydrogel and PRP did not show better chondrogenic effects in vivo compared with those of the HA hydrogel alone. Considering the results of our study, a further study is necessary to clarify the ideal composition and application of PRP for cartilage regeneration.๋ชฉ ์ : ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ํ˜ˆ์†ŒํŒ ํ’๋ถ€ ํ˜ˆ์žฅ์„ ์ด์šฉํ•œ ์—ฐ๊ณจ์žฌ์ƒ์— ๋Œ€ํ•ด ์•Œ์•„๋ณด๊ณ ์ž ํ•œ๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ๋จผ์ € ๋ณด๊ด€์กฐ๊ฑด์— ๋”ฐ๋ฅธ ํ˜ˆ์†ŒํŒ ํ’๋ถ€ ํ˜ˆ์žฅ ๋‚ด ์„ฑ์žฅ์ธ์ž ๋†๋„๋ฅผ ์กฐ์‚ฌํ•˜๊ณ , ํ˜ˆ์†ŒํŒ ํ’๋ถ€ ํ˜ˆ์žฅ ๋‚ด ๋ฐฑํ˜ˆ๊ตฌ ๋†๋„ ์ฐจ์ด๊ฐ€ ์ธ์ฒดํ™œ๋ง‰์„ธํฌ์™€ ์—ฐ๊ณจ์„ธํฌ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ์•Œ์•„๋ณธ ํ›„, ๋งˆ์ง€๋ง‰์œผ๋กœ ํ˜ˆ์†ŒํŒ ํ’๋ถ€ ํ˜ˆ์žฅ๊ณผ ์ง€์ง€์ฒด์˜ ๋ณตํ•ฉ์ฒด ํ˜•์„ฑ์ด ์—ฐ๊ณจ์žฌ์ƒ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ์•Œ์•„๋ณด์•˜๋‹ค. ๋Œ€์ƒ ๋ฐ ๋ฐฉ๋ฒ•: ๋ณด๊ด€์กฐ๊ฑด์— ๋”ฐ๋ฅธ ํ˜ˆ์†ŒํŒ ํ’๋ถ€ ํ˜ˆ์žฅ ๋‚ด ์„ฑ์žฅ์ธ์ž ๋†๋„๋ฅผ ์กฐ์‚ฌํ•˜๊ธฐ ์œ„ํ•ด, ํ˜ˆ์†ŒํŒ ํ’๋ถ€ ํ˜ˆ์žฅ์„ 24๋„, 4๋„, -70๋„์—์„œ 7์ผ ๋™์•ˆ ๋ณด๊ด€ํ•œ ํ›„ ํ™œ์„ฑํ™” ์ „ํ›„๋กœ PDGFโ€AA, TGFโ€ฮฒ, VEGF, IGFโ€1, FGFโ€B ๋†๋„๋ฅผ ELISA๋ฅผ ์ด์šฉํ•˜์—ฌ ์ธก์ •ํ•˜์˜€๋‹ค. ๋˜ํ•œ ํ˜ˆ์†ŒํŒ ํ’๋ถ€ ํ˜ˆ์žฅ ๋‚ด ๋ฐฑํ˜ˆ๊ตฌ ๋†๋„ ์ฐจ์ด๊ฐ€ ์ธ์ฒดํ™œ๋ง‰์„ธํฌ์™€ ์—ฐ๊ณจ์„ธํฌ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ์•Œ์•„๋ณด๊ธฐ ์œ„ํ•ด, ๋ฐฑํ˜ˆ๊ตฌ ํ’๋ถ€ (Leukocyte-rich)์™€ ์ˆœ์ˆ˜ (Leukocyte-poor) ํ˜ˆ์†ŒํŒ ํ’๋ถ€ ํ˜ˆ์žฅ์„ ์ œ์กฐํ•˜๊ณ  ์ด๋“ค์„ ๊ฐ๊ฐ ์ธ์ฒดํ™œ๋ง‰์„ธํฌ, ์—ฐ๊ณจ์„ธํฌ์™€ ๊ฐ™์ด 3์ฃผ๊ฐ„ pellet ๋ฐฐ์–‘ํ•˜์˜€๋‹ค. ์ดํ›„ ์„ธํฌ ์ฆ์‹์„ MTT assay๋กœ ํ‰๊ฐ€ํ•˜๊ณ , ์—ฐ๊ณจํ˜•์„ฑ๋Šฅ์€ RT-PCR๋กœ ์—ฐ๊ณจํ˜•์„ฑ์— ๊ด€๋ จ๋œ ์œ ์ „์ž (Type II collagen, Type X collagen, SOX-9, aggrecan) ๋ฐœํ˜„์„ ์ธก์ •ํ•œ ํ›„ ์กฐ์งํ•™/๋ฉด์—ญํ•™์  ์—ผ์ƒ‰์„ ์‹œํ–‰ํ•˜์˜€๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ํ˜ˆ์†ŒํŒ ํ’๋ถ€ ํ˜ˆ์žฅ๊ณผ ์ง€์ง€์ฒด์˜ ๋ณตํ•ฉ์ฒด ํ˜•์„ฑ์ด ์—ฐ๊ณจ์žฌ์ƒ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ์กฐ์‚ฌํ•˜๊ธฐ ์œ„ํ•ด, ํ† ๋ผ ๋Œ€ํ‡ด ํ™œ์ฐจ์— ๊ณจ์—ฐ๊ณจ ๊ฒฐ์†์„ ๋งŒ๋“ค๊ณ  ๋Œ€์กฐ๊ตฐ, ์ง€์ง€์ฒด๊ตฐ, ๋ณตํ•ฉ์ฒด๊ตฐ (ํ˜ˆ์†ŒํŒ ํ’๋ถ€ ํ˜ˆ์žฅ+์ง€์ง€์ฒด)์œผ๋กœ ๋‚˜๋ˆˆ ํ›„ 12์ฃผ์— ICRS macroscopic score์™€ Modified ODriscoll score๋ฅผ ์–ป๊ณ  DMB assay๋ฅผ ํ†ตํ•ด GAG ํ•ฉ์„ฑ์„ ํ‰๊ฐ€ํ•˜์˜€๋‹ค. ๊ฒฐ ๊ณผ: ๋ณด๊ด€์กฐ๊ฑด์— ๋”ฐ๋ฅธ ํ˜ˆ์†ŒํŒ ํ’๋ถ€ ํ˜ˆ์žฅ ๋‚ด ์„ฑ์žฅ์ธ์ž ๋†๋„์˜ ๊ฒฝ์šฐ, ํ™œ์„ฑํ™” ์ „ PDGFโ€AA ๋†๋„๋Š” 24๋„์—์„œ 7์ผ์งธ ๊ฐ€์žฅ ๋†’์•˜๊ณ , TGFโ€ฮฒ๋Š” ๋ชจ๋“  ์˜จ๋„์—์„œ 7์ผ ๋™์•ˆ ์ž˜ ๊ฒ€์ถœ๋˜์ง€ ์•Š์•˜์œผ๋ฉฐ, VEGF์™€ IGFโ€1 ๋†๋„๋Š” ๋ชจ๋“  ์˜จ๋„์—์„œ 7์ผ ๋™์•ˆ ์ผ์ •ํ•˜๊ฒŒ ์œ ์ง€๋˜๊ณ , FGFโ€B ๋†๋„๋Š” -4๋„์—์„œ 7์ผ์งธ ๊ฐ€์žฅ ๋†’์•˜๋‹ค. ํ™œ์„ฑํ™” ํ›„ PDGFโ€AA, VEGF, IGFโ€1 ๋†๋„๊ฐ€ ๋ชจ๋“  ์˜จ๋„์—์„œ 7์ผ ๋™์•ˆ ์ผ์ •ํ•˜๊ฒŒ ์œ ์ง€๋œ ๊ฒƒ์— ๋ฐ˜ํ•ด, TGFโ€ฮฒ ๋†๋„๋Š” ๋ชจ๋“  ์˜จ๋„์—์„œ 7์ผ์— ๊ฐ€์žฅ ๋†’์•˜๊ณ , FGFโ€B ๋†๋„๋Š” 24๋„์—์„œ 1์ผ ํ›„ ๊ธ‰๊ฒฉํžˆ ๊ฐ์†Œํ•˜๋Š” ์–‘์ƒ์„ ๋ณด์˜€๋‹ค. ํ˜ˆ์†ŒํŒ ํ’๋ถ€ ํ˜ˆ์žฅ ๋‚ด ๋ฐฑํ˜ˆ๊ตฌ ๋†๋„ ์ฐจ์ด๊ฐ€ ์ธ์ฒดํ™œ๋ง‰์„ธํฌ์™€ ์—ฐ๊ณจ์„ธํฌ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์˜ ๊ฒฝ์šฐ, ๋ฐฑํ˜ˆ๊ตฌ ํ’๋ถ€ ํ˜ˆ์†ŒํŒ ํ’๋ถ€ ํ˜ˆ์žฅ์—์„œ ์ธ์ฒดํ™œ๋ง‰์„ธํฌ์™€ ์—ฐ๊ณจ์„ธํฌ ๋ชจ๋‘ ๋ณด๋‹ค ํฐ ์ฆ์‹๋Šฅ๋ ฅ์„ ๋ณด์˜€์œผ๋‚˜, RT-PCR์˜ ๊ฒฝ์šฐ ๋‘ ์„ธํฌ ๋ชจ๋‘ ๋ฐฑํ˜ˆ๊ตฌ ์ˆœ์ˆ˜ ํ˜ˆ์†ŒํŒ ํ’๋ถ€ ํ˜ˆ์žฅ์—์„œ ๋ณด๋‹ค ๋งŽ์€ ์œ ์ „์ž ๋ฐœํ˜„์ด ๊ด€์ฐฐ๋˜์—ˆ๋‹ค. ํ•˜์ง€๋งŒ ์ธ์ฒดํ™œ๋ง‰์„ธํฌ์™€ ์—ฐ๊ณจ์„ธํฌ์˜ ์กฐ์งํ•™/๋ฉด์—ญํ•™์  ์—ผ์ƒ‰์ƒ, ๋ฐฑํ˜ˆ๊ตฌ ๋†๋„์— ๊ด€๊ณ„์—†์ด ๋‘ ํ˜ˆ์†ŒํŒ ํ’๋ถ€ ํ˜ˆ์žฅ ๋ชจ๋‘์—์„œ ์—ฐ๊ณจ ๋ถ„ํ™”๊ฐ€ ์–ต์ œ๋˜๋Š” ์–‘์ƒ์ด ๊ด€์ฐฐ๋˜์—ˆ๋‹ค. ํ˜ˆ์†ŒํŒ ํ’๋ถ€ ํ˜ˆ์žฅ๊ณผ ์ง€์ง€์ฒด์˜ ๋ณตํ•ฉ์ฒด ํ˜•์„ฑ์ด ์—ฐ๊ณจ์žฌ์ƒ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์˜ ๊ฒฝ์šฐ, ์„ธ๊ตฐ ๋ชจ๋‘์—์„œ ICRS macroscopic score์— ์ฐจ์ด๊ฐ€ ์—†์—ˆ๋‹ค. Modified ODriscoll score์™€ GAG ๋†๋„์˜ ๊ฒฝ์šฐ, ์ง€์ง€์ฒด๊ตฐ๊ณผ ๋ณตํ•ฉ์ฒด๊ตฐ ๋ชจ๋‘ ๋Œ€์กฐ๊ตฐ๋ณด๋‹ค ๋†’์•˜์œผ๋‚˜, ๋‘ ๊ตฐ ๊ฐ„์—๋Š” ์ฐจ์ด๊ฐ€ ๊ด€์ฐฐ๋˜์ง€ ์•Š์•˜๋‹ค. ๊ฒฐ ๋ก : ํ˜ˆ์†ŒํŒ ํ’๋ถ€ ํ˜ˆ์žฅ์—์„œ ๋ฐฉ์ถœ๋˜๋Š” ์„ฑ์žฅ์ธ์ž๋“ค์˜ ๋†๋„๋Š” ๋ณด๊ด€์˜จ๋„, ๋ณด๊ด€๊ธฐ๊ฐ„, ํ™œ์„ฑํ™” ์—ฌ๋ถ€์— ๋”ฐ๋ผ ํฐ ์ฐจ์ด๊ฐ€ ์žˆ์—ˆ๋‹ค. ๋˜ํ•œ ํ˜ˆ์†ŒํŒ ํ’๋ถ€ ํ˜ˆ์žฅ ๋‚ด ๋ฐฑํ˜ˆ๊ตฌ ๋†๋„์— ๊ด€๊ณ„์—†์ด ํ˜ˆ์†ŒํŒ ํ’๋ถ€ ํ˜ˆ์žฅ์€ ์ธ์ฒดํ™œ๋ง‰์„ธํฌ์™€ ์—ฐ๊ณจ์„ธํฌ์˜ ์—ฐ๊ณจํ˜•์„ฑ์— ๋ถ€์ •์ ์ธ ์˜ํ–ฅ์„ ๋ณด์˜€์œผ๋ฉฐ, ํ˜ˆ์†ŒํŒ ํ’๋ถ€ ํ˜ˆ์žฅ๊ณผ ์ง€์ง€์ฒด์˜ ๋ณตํ•ฉ์ฒด ์‚ฌ์šฉ์€ ์ง€์ง€์ฒด ๋‹จ๋… ์‚ฌ์šฉ์— ๋น„ํ•ด ํ–ฅ์ƒ๋œ ์—ฐ๊ณจํ˜•์„ฑ์œผ๋กœ ์ด์–ด์ง€์ง€ ๋ชปํ–ˆ๋‹ค. ์ด๋ฒˆ ์—ฐ๊ตฌ๊ฒฐ๊ณผ๋“ค์„ ๊ธฐ๋ฐ˜์œผ๋กœ ์—ฐ๊ณจ์žฌ์ƒ์„ ์œ„ํ•œ ์ตœ์ ์˜ ํ˜ˆ์†ŒํŒ ํ’๋ถ€ ํ˜ˆ์žฅ ์‚ฌ์šฉ์— ๋Œ€ํ•œ ์ถ”๊ฐ€์—ฐ๊ตฌ๊ฐ€ ํ•„์š” ํ•  ๊ฒƒ์œผ๋กœ ์ƒ๊ฐ๋œ๋‹ค.Introduction 1 Chapter I. Effect of storage conditions and activation on growth factor concentration in plateletโ€rich plasma 6 I-1. Materials and Methods 7 I-2. Results 8 I-3. Discussion 17 Chapter II. The effect of leukocyte concentration in plateletโ€rich plasma on the proliferation and chondrogenesis of synovium-derived mesenchymal stem cell and chondrocytes 22 II-1. Materials and Methods 23 II-2. Results 28 II-3. Discussion 35 Chapter III. The effect of plateletโ€rich plasma with hyaluronic acid hydrogel on in vivo chondrogenesis in a rabbit osteochondral defect model 40 III-1. Materials and Methods 41 III-2. Results 47 III-3. Discussion 53 Conclusion 56 References 57 ๊ตญ๋ฌธ ์ดˆ๋ก 69Docto

    A network analysis of ยนโตO-Hโ‚‚O PET reveals deep brain stimulation effects on brain network of Parkinson's disease

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    PURPOSE: As Parkinson's disease (PD) can be considered a network abnormality, the effects of deep brain stimulation (DBS) need to be investigated in the aspect of networks. This study aimed to examine how DBS of the bilateral subthalamic nucleus (STN) affects the motor networks of patients with idiopathic PD during motor performance and to show the feasibility of the network analysis using cross-sectional positron emission tomography (PET) images in DBS studies. MATERIALS AND METHODS: We obtained [ยนโตO]Hโ‚‚O PET images from ten patients with PD during a sequential finger-to-thumb opposition task and during the resting state, with DBS-On and DBS-Off at STN. To identify the alteration of motor networks in PD and their changes due to STN-DBS, we applied independent component analysis (ICA) to all the cross-sectional PET images. We analysed the strength of each component according to DBS effects, task effects and interaction effects. RESULTS: ICA blindly decomposed components of functionally associated distributed clusters, which were comparable to the results of univariate statistical parametric mapping. ICA further revealed that STN-DBS modifies usage-strengths of components corresponding to the basal ganglia-thalamo-cortical circuits in PD patients by increasing the hypoactive basal ganglia and by suppressing the hyperactive cortical motor areas, ventrolateral thalamus and cerebellum. CONCLUSION: Our results suggest that STN-DBS may affect not only the abnormal local activity, but also alter brain networks in patients with PD. This study also demonstrated the usefulness of ICA for cross-sectional PET data to reveal network modifications due to DBS, which was not observable using the subtraction method.ope

    A Study of Expression through Reinterpretation of Images in Terms of Visual Perception: With a Focus on the Researchers Own Works

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๋™์–‘ํ™”๊ณผ, 2012. 8. ์ •ํ˜•๋ฏผ.์‹œ๊ฐ์˜ˆ์ˆ ์€ ๋ณด๋Š” ๊ฒƒ์„ ๊ทผ๊ฐ„์œผ๋กœ ํ•œ๋‹ค. ์šฐ๋ฆฌ๋Š” ๋ณด๋Š” ๊ฒƒ์œผ๋กœ๋ถ€ํ„ฐ ๊ฐ€์žฅ ๋งŽ์€ ์ •๋ณด๋ฅผ ์™ธ๋ถ€๋กœ๋ถ€ํ„ฐ ๋ฐ›์•„๋“ค์ด๊ณ , ์ด์— ์˜์กดํ•˜๋ฉฐ ์‚ด์•„๊ฐ€๊ณ  ์žˆ๊ธฐ ๋•Œ๋ฌธ์— , ๋ณธ๋‹ค๋Š” ํ–‰์œ„๊ฐ€ ๊ฐ€์ง€๋Š” ์ฃผ๊ด€์ ์ธ ์ธก๋ฉด์„ ์‰ฝ๊ฒŒ ์žŠ์–ด๋ฒ„๋ฆฐ๋‹ค. ๋ˆˆ์„ ํ†ตํ•ด ๋ณธ๋‹ค๋Š” ๊ฒƒ์€, ์šฐ๋ฆฌ๊ฐ€ ์ธ๊ฐ„์ด๊ธฐ ๋•Œ๋ฌธ์— ์ธ๊ฐ„์˜ ๋ฐฉ์‹์œผ๋กœ๋งŒ ๋ณผ ์ˆ˜ ์žˆ๋‹ค. ๋ˆˆ์ด ์—†๋Š” ์ƒ๋ฌผ์€ ๋น›์ด ์—†๋Š” ํ™˜๊ฒฝ์—์„œ๋„ ๋‹ค๋ฅธ ์ •๋ณด๋“ค์„ ์ด์šฉํ•ด ์‚ด์•„๊ฐ„๋‹ค. ์ธ๊ฐ„์œผ๋กœ์„œ ๋ฌด์—‡์„ ๋ณธ๋‹ค๋Š” ํ–‰์œ„๋Š” ๊ฐ๊ด€์ ์ด๋ฉฐ ์ˆ˜๋™์ ์ธ ๊ฒƒ์ด ์•„๋‹ˆ๋ผ, ์ƒ๋Œ€์ ์ด๋ฉฐ ๋Šฅ๋™์ ์ธ ํ–‰์œ„์ด๋‹ค. ๋ณธ๋‹ค๋Š” ํ–‰์œ„์˜ ์ƒ๋Œ€์ ์ธ ํŠน์„ฑ์€ ๋” ๋‚˜์•„๊ฐ€ ๊ฐ ๊ฐœ์ธ์—๊ฒŒ ์ž์‹ ์„ ๋‘˜๋Ÿฌ์‹ผ ํ™˜๊ฒฝ์— ์˜ํ•œ ์ž์‹ ๋งŒ์˜ ๊ณ ์œ ํ•œ ์‹œ๊ฐ์  ์ƒ์ง•์ฒด๊ณ„, ์ฆ‰ ๋ณด๋Š” ๋ฒ•์„ ๊ฐ€์ง€๊ฒŒ ํ•œ๋‹ค. ๋ณด๋Š” ๋ฒ•์€ ์ธ๊ฐ„์ด ์„ฑ์žฅํ•จ์— ๋”ฐ๋ผ ๋‘˜๋Ÿฌ์‹ผ ํ™˜๊ฒฝ์— ์ ์‘ํ•˜๋Š” ๊ณผ์ •์—์„œ ์ˆ˜์ •๋˜๊ณ  ๋ฐœ์ „๋œ๋‹ค. ๋ณด๋Š” ๋ฒ•์€ ์ฒ ๋กœ์™€ ๊ฐ™๋‹ค. ์šฐ๋ฆฌ๋Š” ์–ด๋–ค ์ฒ ๋กœ๋ฅผ ๋‹ฌ๋ฆด ๊ฒƒ์ธ์ง€ ๊ฒฐ์ •ํ•  ์ˆ˜ ์žˆ๋Š” ๊ธฐ๊ด€์‚ฌ์ผ ์ˆ˜ ์žˆ์ง€๋งŒ ์ฒ ๋กœ๊ฐ€ ์—†์ด๋Š” ์•„์˜ˆ ๊ธฐ์ฐจ๊ฐ€ ๋‹ฌ๋ฆด ์ˆ˜ ์—†๋‹ค. ๋ฌด์–ธ๊ฐ€๋ฅผ ์•Œ์•„๋ณธ๋‹ค๋Š” ๊ฒƒ์€ ์ด๋ฏธ ๊ทธ๊ฒƒ์— ๋Œ€ํ•ด ์ฒ ๋กœ๊ฐ€ ๋†“์—ฌ์žˆ๋Š” ๊ฒƒ์ด๋‹ค. ์ƒˆ๋กœ ์ƒ๊ธฐ๋Š” ์ง€์ ์ด๋‚˜ ์‚ฌ๋ผ์ง€๋Š” ๊ธธ๋“ค์€ ๊ธฐ์ฐจ๋“ค์˜ ํ๋ฆ„๊ณผ ์•ž์„œ ์กด์žฌํ•˜๋Š” ์ฒ ๋กœ๋กœ๋ถ€ํ„ฐ ์ž์œ ๋กœ์šธ ์ˆ˜ ์—†๋‹ค. ์•ž์„œ ์กด์žฌํ•˜๋Š” ์‚ฌํšŒ๋ฌธํ™”์  ํ˜„์ƒ์„ ๋ณด๊ธฐ ์œ„ํ•ด ์šฐ๋ฆฌ๋Š” ๋งค์ฒด๋ฅผ ํ•™์Šตํ•ด์•ผ ํ•œ๋‹ค. ์—ฌ๊ธฐ์„œ ๋งค์ฒด๋ž€ ์‚ฌ๋žŒ๊ณผ ์‚ฌ๋žŒ ์‚ฌ์ด๋ฅผ, ์–ด์ œ์™€ ์˜ค๋Š˜์„ ์ด์–ด ์ฃผ๋Š” ๊ด‘๋ฒ”์œ„ํ•œ ์‚ฌํšŒ์  ์—ฐ๊ฒฐ๋ง์ด๋‹ค. ์ด ๋งค์ฒด๋Š” ์‹œ๋Œ€, ์‚ฌํšŒ๋งˆ๋‹ค ๋‹ค๋ฅด๋‹ค. ๊ณผ๊ฑฐ์—๋Š” ์ด๋Ÿฌํ•œ ์ฐจ์ด๋“ค์ด ์ž์—ฐํ™˜๊ฒฝ๊ณผ ์ง€๋ฆฌ์  ๊ฑฐ๋ฆฌ์— ๊ธฐ์ธํ–ˆ์ง€๋งŒ, ์˜ค๋Š˜๋‚ ์—๋Š” ๋น ๋ฅด๊ฒŒ ๋ณ€ํ™”ํ•˜๊ณ  ์žˆ๋‹ค. ์ด ๋ณ€ํ™”์˜ ๋ฐฉํ–ฅ์€ ๋ฌด์—‡๋ณด๋‹ค๋„ ๋น ๋ฅธ ์ •๋ณด์˜ ์ „๋‹ฌ์†๋„์— ์˜ํ•ด ๊ฒฐ์ •๋œ๋‹ค. ๋น ๋ฅด๊ฒŒ ์ •๋ณด๊ฐ€ ๊ตํ™˜๋˜์–ด ์งˆ์ˆ˜๋ก ๋งค์ฒด๋Š” ๋‹จ์ˆœํžˆ ์‚ฌ๋žŒ๊ณผ ์‚ฌํšŒ๋ฅผ ์ด์–ด์ฃผ๋Š” ๊ธฐ๋Šฅ์„ ๋„˜์–ด ์ œ2์˜ ์„ธ๊ณ„, ๊ฐ€์ƒ์„ธ๊ณ„๊ฐ€ ๋˜์—ˆ๋‹ค. ์ƒˆ๋กœ์šด ๋งค์ฒด์˜ ๋ณ€ํ™”๋Š” ์˜ˆ์ˆ ๊ฐ€์—๊ฒŒ ๋งค์ฒด์— ๋Œ€ํ•œ ์ดํ•ด๋ฅผ ์ƒˆ๋กœ์šด ๊ณผ์ œ๋กœ์„œ ์š”๊ตฌํ•œ๋‹ค. ์ด ๋…ผ๋ฌธ์€ ๋ณด๋Š” ๋ฒ•์— ๋Œ€ํ•œ ์œ„์˜ ๋‚ด์šฉ๋“ค์„ ํฌ๊ฒŒ ๋‘ ์žฅ์œผ๋กœ ๋‚˜๋ˆ„์–ด ๋ณธ์ธ์˜ ์ž‘์—…๊ณผ ๊ด€๋ จํ•˜์—ฌ ๋ถ„์„ํ•˜๋ ค ํ•˜์˜€๋‹ค. ๋จผ์ €, ๋ˆˆ์˜ ๋น›์„ ๋ฐ›์•„๋“ค์ด๋Š” ์‹œ๊ฐ๊ตฌ์กฐ์ƒ์˜ ํŠน์ง•์„ ์ด์šฉํ•˜์—ฌ ์ฐฉ์‹œ๋ฅผ ์œ ๋„ํ•œ ์ž‘์—…์„ ์ง„ํ–‰ํ•˜์˜€๊ณ , ๋” ๋‚˜์•„๊ฐ€ ๊ฐ๊ฐ์  ์ฐฉ์‹œ๋งŒ์„ ์ด์šฉํ•˜๋Š” ๊ฒƒ์„ ๋„˜์–ด ๋ฌธํ™”์ ์œผ๋กœ ๊ณ ์ •๋œ ๋ณด๋Š” ๋ฒ•์— ๊ฐœ์ž…ํ•˜์—ฌ ์ง€๊ฐ์  ์ฐฉ์‹œ๋ฅผ ์œ ๋„ํ•˜์˜€๋‹ค. ๋‘˜์งธ, ๊ธฐ์กด์˜ ์œ ๋ช…ํ•œ ๋„์ƒ๋“ค์„ ์ฐจ์šฉํ•˜์—ฌ ํ˜„์žฌ ์ผ์–ด๋‚˜๊ณ  ์žˆ๋Š” ๋งค์ฒด์˜ ๋ณ€ํ™”๋ฅผ ์€์œ ์ ์œผ๋กœ ํ‘œํ˜„ํ•˜๋Š” ์ž‘์—…์„ ์ง„ํ–‰ํ•˜๊ธฐ์œ„ํ•ด, ์ฐจ์šฉํ•œ ๊ฐ ๋„์ƒ์˜ ์ƒ์ง•์„ ํ˜„ ์‹œ์ ์— ํ†ต์šฉ๋˜๊ณ  ์žˆ๋Š” ์˜๋ฏธ๋กœ ๋ถ„์„ํ•˜๊ณ , ์ด๋ฅผ ์‘์šฉํ•ด ์ƒˆ๋กœ์šด ์ƒ์ง•์„ ๋„์ƒ๊ฒฐํ•ฉ์„ ํ†ตํ•ด ๋งŒ๋“ค์–ด๋‚ด์—ˆ๋‹ค. ์œ„์™€ ๊ฐ™์€ ์ผ๋ จ์˜ ์ž‘์—…๋“ค์€ ์„์‚ฌ๊ณผ์ • ๋™์•ˆ ํ•ด์™”๋˜ ์—ฌ๋Ÿฌ ๊ฐ€์ง€ ์ƒ๊ฐ๋“ค์„ ์‹œ๊ฐ์ ์œผ๋กœ ๊ตฌ์ฒดํ™”ํ•œ ๊ฒƒ์ด๋‹ค. ์ž‘์—…๋“ค์˜ ์ด๋ฏธ์ง€ ์ž์ฒด๋Š” ์‚ฌ์‹ค ์•„๋ฌด๊ฒƒ๋„ ์•„๋‹ˆ๋‹ค. ์ด๋Š” ๋‚ด ์ƒ๊ฐ์„ ์ „๋‹ฌํ•˜๋Š” ์ˆ˜๋‹จ์ด์ง€ ๋ชฉ์ ์ด ์•„๋‹ˆ๋‹ค. ๋˜ํ•œ ์ด ๋…ผ๋ฌธ์˜ ๋ชฉ์  ์—ญ์‹œ ๋‚ด ์ž‘์—…์„ ์„ค๋ช…ํ•˜๊ธฐ ์œ„ํ•œ ๊ฒƒ์ด ์•„๋‹ˆ๋ผ ์ด์™€ ๊ฐ™์€ ์‹œ๋Œ€์  ์ƒํ™ฉ์„ ์ดํ•ดํ•˜๊ณ  ๊ทธ ์†์—์„œ ๋‚˜์˜ ์—ญํ• ์„ ์ •์˜ํ•˜๋Š” ๊ฒƒ์— ์žˆ๋‹ค. ์ฆ‰, ์˜ˆ์ˆ ๊ฐ€๋Š” ์ƒ์ง•์˜ ๊ตํ™˜์„ ํ†ตํ•˜์—ฌ ์‹ค์žฌ์™€ ํ—ˆ๊ตฌ๋ฅผ ๋›ฐ์–ด๋„˜์–ด ์ง€๊ฐ์  ์ฐจ์›์—์„œ ๊ด€๋žŒ์ž์—๊ฒŒ ์ด์ƒ์ ์ธ ๊ฟˆ์„ ๊ฒฝํ—˜ํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•ด ์ฃผ๋Š” ๋ฐฐ์—ญ์ด๋‹ค. ์ฃผ์š”์–ด : ์ƒ์ง•, ์ด๋ฏธ์ง€, ์‹œ๊ฐ, ๋ณต์ œ, ๋งค์ฒด, ๋„์‹, ์ฐฉ์‹œ ํ•™ ๋ฒˆ : 2010-21265The visual arts are based on seeing. Because we receive the greatest amount of information from the outside through and live by depending on seeing, we easily forget the subjective aspect of the act of seeing. Because we are human beings, even seeing with the eyes can occur only in a human way. Living beings without eyes live even in environments without light by using other types of information. The act of seeing as a human being is not an objective and passive one but a relative and active one. Furthermore, the relative characteristics of the act of seeing prompt each individual to possess a unique visual symbol system according to the surrounding environment, or a way of seeing. Ways of seeing are modified and developed in the process through which humans adapt to the surrounding environment as they grow. They are like railroads. While we may be engineers who can decide which railroad to travel, trains cannot travel at all without railroads. Recognizing something means that there already is a railroad to that object. Nor can newly generated points and disappearing roads be free from the flow of trains and preexisting railroads. To see preexisting sociocultural phenomena, we must study media. Here, media are broad social network that connect one person to another and yesterday to today. These media differ for each era and society. In the past, such differences arose from the natural environment and geographical distancetoday, they are changing swiftly. The direction of such changes is determined above all by the rapid rates at which information is transmitted. With the increasingly rapid exchange of information, media have become a second world, a virtual world, transcending the role simply of connecting people and society. Changes in new media make a demand, as a new task, that artists understand them. The present study analyzed the above contents regarding ways of seeing in two parts, with respect to the present researchers artistic works. First, it created optical illusions by using the characteristics of the optical structure that receives light and, moreover, created cognitive optical illusions by intervening in culturally fixed ways of seeing, transcending merely sensory optical illusions. Second, to express metaphorically current changes in media by borrowing famous existing symbol images, the symbolism of each of the borrowed images was analyzed in terms of currently common significance and, by applying this, new symbolism was created through combination with the symbols. The series of tasks above are visual concretization of diverse ideas that the present researcher held throughout the masters program. In fact, however, the images from these tasks are nothing. They are but the means to deliver my thoughts, not the ends. In addition, the purpose of the present study likewise lies not in explaining my artistic works but in understanding the situation of the present age and to define the role of the present researcher in it. In other words, the artists role is to allow the viewer to experience ideal dreams on a cognitive level by transcending actuality and fiction and through the exchange of symbols. Keywords: Symbols, images, vision, replication, media, schemata, optical illusions Student ID: 2010-21265์ฐจ ๋ก€ ๊ตญ๋ฌธ์ดˆ๋ก ยทโ…ฐ ์ฐจ ๋ก€ ยทโ…ฒ ๋„ํŒ๋ชฉ๋ก ยทโ…ด โ… . ์„œ๋ก  1. ์—ฐ๊ตฌ๋ชฉ์ ยท1 2. ์—ฐ๊ตฌ๋‚ด์šฉยท1 3. ์—ฐ๊ตฌ๋ฐฉ๋ฒ•ยท3 โ…ก. ์‹œ์ง€๊ฐ์  ๊ฐœ์ž…์„ ํ†ตํ•œ ์ฐฉ์‹œํ‘œํ˜„ 1. ์ธ๊ฐ„์˜ ์‹œ๊ฐ๊ฐ์  ํŠน์ง•์„ ์ด์šฉํ•œ ์ฐฉ์‹œํ‘œํ˜„ยท9 2. ๋งค์ฒด๋กœ์˜ ๊ฐœ์ž…์„ ํ†ตํ•œ ์ง€๊ฐ์  ์ฐฉ์‹œํ‘œํ˜„ยท21 3. ๊ฐ€์น˜์ฒด๊ณ„ ๊ฐœ์ž…์„ ํ†ตํ•œ ์ง€๊ฐ์  ์ฐฉ์‹œํ‘œํ˜„ยท30 4. ์ด๋ฏธ์ง€์˜ ์ง€๊ฐ์  ์žฌํ•ด์„์„ ํ†ตํ•œ ํ‘œํ˜„ยท51 โ…ข. ๋„์ƒ์˜ ์žฌํ•ด์„์„ ํ†ตํ•œ ๋งค์ฒด๋ณ€ํ™”์˜ ์€์œ ์  ํ‘œํ˜„ 1. ๋ฐ˜๊ฐ€์‚ฌ์œ ์ƒ์„ ์ฐจ์šฉํ•œ ํ‘œํ˜„ยท60 2. Apple์‚ฌ(็คพ)์˜ ๋กœ๊ณ ๋ฅผ ์ฐจ์šฉํ•œ ํ‘œํ˜„ยท72 โ…ฃ. ๋งบ์Œ๋ง 1. ๊ฒฐ๋ก ยท84 2. ํ›„์†์—ฐ๊ตฌยท86 ์ฐธ๊ณ ๋ฌธํ—Œ ยท88 ๋ถ€๋ก ยท92 ์˜๋ฌธ์ดˆ๋ก ยท95Maste

    ๋‡ŒํŒŒ์™€ ๊ธฐ๋Šฅ์  ์ž๊ธฐ๊ณต๋ช…์˜์ƒ์˜ ๋™์‹œ ์ธก์ • ๊ธฐ๋ฒ•์„ ์ด์šฉํ•œ ์ˆ˜๋ฉด๊ณผ ๊ฐ์„ฑ์‹œ ๊ธฐ๋Šฅ์  ๋‡Œ ๋„คํŠธ์›Œํฌ์˜ ํƒ์ƒ‰ ์—ฐ๊ตฌ

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    Dept. of Medical Science/๋ฐ•์‚ฌSleep is regulated by modulation of neural interaction between particular brain regions. Brain neural activity can be estimated by various neuroimaging methods such as electroencephalography (EEG), functional magnetic resonance imaging (fMRI) and so on. Further analysis of the acquired data based on graph theoretical approaches aims to identify the functional brain networks. Moreover, in the recent neuroscience field, many research studies have defined the brain as a large complex system that is organized by the reciprocal interactions between brain regions.To investigate the changes of functional brain network during sleep and wakefulness (awake), we acquired the data from 11 healthy participants using simultaneous EEG and fMRI. The sleep data were obtained approximately 7 hours while participants are sleeping. Unfortunately, the artifacts caused by movements of participants as well as characteristics of instruments had occurred inevitably during the process of data acquisition. Thus we removed these artifacts using the average artifact subtraction for EEG data and the sub-volume utilization for fMRI data. Then, the preprocessed sleep data were visually classified and scored for every 30 sec epochs by sleep S1, S2, S3 and REM according to the international standard of AASM (American Academy of Sleep Medicine) guideline. In network analysis, to construct the functional brain network, we defined nodes depicting 95 regions of interest using brain anatomical atlas from the Automated Anatomical Labeling (AAL) and Freesurfer. For the construction of functional connectivity we applied the Pearsonโ€™s correlation coefficient between pairs of node time series.The ventral diencephalon (vDC) seeded functional connectivity has dense connections in the sleep associated regions with subcortex during sleep stages rather than wakefulness. Comparing the network topology of whole brain, we observed the main effect of sleep in the mean clustering coefficient that was significantly increased during sleep S2, S3 and REM compared with wakefulness. The global / local efficiency showed significant differences between the pairs of only sleep S1, the transitional state from wake to sleep. This functional brain network could be decomposed with independent functional subnetworks revealed by graph ICA (independent component analysis). Our results support the assumption that the functional brain network is organized by locally distributed unit functions and it is functionally segregated during sleep.In this study, we observed that the sleep data could be acquired by concordant EEG and fMRI during very long time. Our result demonstrated that the functional brain network could be reorganized by the dynamic changes of spontaneous brain activity depending on sleep stages.restrictio

    SI ์—”์ง„์˜ ํก๊ธฐ๊ด€ ๋‚ด์—์„œ์˜ ์œ ๋Ÿ‰ ์ธก์ •์— ๊ด€ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ธฐ๊ณ„๊ณตํ•™๊ณผ,1995.Maste

    Transient air fuel ratio control of a gasoline engine using an integration type ultrasonic flow meter

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ธฐ๊ณ„๊ณตํ•™๊ณผ,2000.Docto

    Activation of the Occipital Cortex and Deactivation of the Default Mode Network During Working Memory in the Early Blind.

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    Although blind people heavily depend on working memory to manage daily life without visual information, it is not clear yet whether their working memory processing involves functional reorganization of the memory-related cortical network. To explore functional reorganization of the cortical network that supports various types of working memory processes in the early blind, we investigated activation differences between 2-back tasks and 0-back tasks using fMRI in 10 congenitally blind subjects and 10 sighted subjects. We used three types of stimulus sequences: words for a verbal task, pitches for a non-verbal task, and sound locations for a spatial task. When compared to the sighted, the blind showed additional activations in the occipital lobe for all types of stimulus sequences for working memory and more significant deactivation in the posterior cingulate cortex of the default mode network. The blind had increased effective connectivity from the default mode network to the left parieto-frontal network and from the occipital cortex to the right parieto-frontal network during the 2-back tasks than the 0-back tasks. These findings suggest not only cortical plasticity of the occipital cortex but also reorganization of the cortical network for the executive control of working memory. (JINS, 2011, 17, 1-16).ope

    Are brain networks stable during a 24-hour period?

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    Despite the widespread view of the brain as a large complex network, the dynamicity of the brain network over the course of a day has yet to be explored. To investigate whether the spontaneous human brain network maintains long-term stability throughout a day, we evaluated the intra-class correlation coefficient (ICC) of results from an independent component analysis (ICA), seed correlation analysis, and graph-theoretical analysis of resting state functional MRI, acquired from 12 young adults at three-hour intervals over 24 consecutive hours. According to the ICC of the usage strength of the independent network component defined by the root mean square of the temporal weights of the network components, the default mode network centered at the posterior cingulate cortex and precuneus, the superior parietal, and secondary motor networks showed a high temporal stability throughout the day (ICC>0.5). However, high intra-individual dynamicity was observed in the default mode network, including the anterior cingulate cortex and medial prefrontal cortex or posterior-anterior cingulate cortex, the hippocampal network, and the parietal and temporal networks. Seed correlation analysis showed a highly stable (ICC>0.5) extent of functionally connected regions from the posterior cingulate cortex, but poor stability from the hippocampus throughout the day. Graph-theoretical analysis using local and global network efficiency suggested that local brain networks are temporally stable but that long-range integration behaves dynamically in the course of a day. These results imply that dynamic network properties are a nature of the resting state brain network, which remains to be further researched.ope
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