Biochemical Characterization and Use of Mogroside V From Siraitia grosvenorii

학위논문 (석사) -- 서울대학교 대학원 : 국제농업기술대학원 국제농업기술학과, 2020. 8. 김도만.Mogrosides are cucurbitane-type triterpene glycosides found in certain plants, such as the fruit of the gourd vine, luo han guo (Siraitia grosvenorii, monk fruit) that are principle sweet components from fruits. Among them, Mogroside V is the main component composed of 30% extraction yield with over 300-times sweeter compared to sucrose. In addition, it has a low caloric value and low toxicity. However, the price of mogroside V is very high due to lack of efficient purification process for large scale production. In this study, we investigated the purification method of mogroside V by chromatography (HP20 and MPLC). The purity of mogroside V was determined by HPLC and MALDI-TOF. The purified mogroside V was used as solubilizer for idebenone, curcumin, bisdemethoxylcurcumin, oleanolic acid, resveratrol, quercetin, and taxol. The optimization of curcumin for solubilization and its biochemical characterization including antioxidant activities, anti-inflammatory activity, anti-melanin formation were conducted. The anti-inflammation activity on mouse macrophage cell RAW264.7 was studies and water soluble curcumin with mogorisde V effect was lower than that of normal curcumin. The anti-melanin formation such as melanin content assay and celluar tyrosinase activity assay were conducted using B16F10 cells and extra-celluar showed similar performance of water soluble curcumin than curcumin only. In intra-celluar, the effect was higher than normal curcumim. Also cellular tyrosinase showed similar effect than curcumin only.모그로사이드 V는 나한과로 알려진 luo han guo (Siraitia grosvenorii, monk fruit)의 주요 성분이다. 모그로사이드 V는 설탕 대체 감미 소재로써 설탕보다 300배 이상 단맛을 갖고 있고 이에 음식 소재로 사용된다. 그러나 모그로사이드 V는 가격이 비싸고 설탕대체 감미 소재 외 다른 특성의 연구가 부족한 상황이다. 이에 모그로사이드V의 특성 및 활용방법을 제시하고자 연구하였다. 모그로사이드V는 나한과에서 추출한뒤 HP20로 정제 할 경우 순도 55%이상의 모그로사이드V을 얻을수 있으며 이를 MPLC로 재정제 할 경우 순도 92%의 고순도 모그로사이드V을 추출 할수 있다. 기능성 연구 결과 이데베논(Idebenone), 레스베라트롤(Resveratrol), 올레아놀산(Oleanolic acid), 커큐민(Curcumin), 비스데메톡시커큐민(Bisdemethoxycurcumin), 타솔(Taxol), 쿼세틴(Quercetin) 의 수용성을 증가시켰으며 이는 천연 계면활성제로서의 모그로사이드V 사용 가능성을 나타낸다. 수용성이 가장 증가한 커큐민을 이용해서 추가 기능성 연구를 하였다. 세포 독성과 항염증 작용은 쥐의 대식세포인 RAW 264.7 세포를 이용해 연구하였으며 모그로사이드V을 이용해서 물에 녹인 커큐민은 17.86 µg/mL에서 75% 억제 능력을 보였다. 이는 12.5 µg/mL에서 75% 억제 능력을 보이는 기존의 유기용매에 녹인 커큐민에 비해 효과는 다소 낮아졌으나 물에 전혀 녹지 않던 커큐민을 모그로사이드V을 이용하여 녹였을 경우 항염 특성은 갖고 있는 것을 확인 하였다. 또한, 멜라닌 형성 억제 및 멜라닌 형성에 큰 영향을 미치는 Tyrosinase 억제 능력을 B16F10 세포를 이용해 연구하였으며 extra-celluar 에서는 물에 녹인 커큐민이 기존의 유기용매에 녹인 커큐민에 비해 비슷한 효능을 보였으며 intra-celluar 에서는 물에 녹인 커큐민이 기존의 커큐민보다 더 좋은 특성을 갖는 것을 확인하였다. Tyrosinase 억제 능력은 물에 녹인 커큐민과 유기용매에 녹인 커큐민의 특성이 비슷한 것으로 확인되었다.Introduction 1 1. Mogroside V 1 2. RAW264.7 mouse macrophage cell 2 3. RAW 264.7 mouse macrophage cell 3 4. Purpose of this study 4 Materials and Methods 5 1. Sample preparation 5 2. Purification of mogroside V using HP-20 5 3. Purification of mogroside V using MPLC 6 4. Thin Layer Chromatography (TLC) analysis 6 5. Matrix-Assisted Laser Desorption Ionization Time-Of-Flight (MALDI-TOF-MS) Analysis 7 6. Analysis of mogroside V using HPLC 7 7. Solubilization ability of mogroside V for insoluble compounds 7 8. Optimization of curcumin solubilization conditions with mogroside V 8 8.1 Effect of ethanol to curcumin solubility 8 8.2 Effect of mogroside V concentration to solubility 8 8.3 Effect of curcumin concentration 9 9. Ferric Reducing Antioxidant Power Assay (FRAP) 9 10. Cell Viability Assay 10 11. Nitric oxide production inhibition assay using RAW264.7 cell 11 11.1 Cell culture and treatment 11 11.2 NO inhibition measurement 11 12. B16F10 cell melanin synthesis assay 12 12.1 Cell culture and treatment 12 12.2 Melanin assay 12 12.3 Cellular tyrosinase activity assay 13 Results 14 1. Purification of mogroside V from monk fruit 14 1.1. Purification mogroside V using HP-20 14 1.2. Purification mogroside V using MPLC 16 2. Analysis of mogroside V using HPLC and MALDI-TOF 19 2.1 Analysis of mogroside V using HPLC 20 2.2 Molecular weight measurement of mogroside V 21 3. Solubilization of insoluble compounds with mogroside V 23 3.1 Idebenone 23 3.2 Resveratrol 24 3.3 Oleanolic acid 25 3.4 Curcumin 30 3.5 Bisdemethoxycurcumin 31 3.6 Taxol 35 3.7 Quercetin 36 4. Curcumin solubilization conditions with mogroside V for water solubility 40 5. Analysis of antioxidant activity 44 6. Cell cytotoxicity of mogroside V 46 7. Nitric oxide production inhibition of mogroside V 49 8. Effect on mogroside V on melanin content in B16F10 51 Conclusion 56 References 59 Abstract in Korean 66Maste

토론

고맙습니다. 지금 주제 발표에서 여러 가지 문제를 제기해 주셨는데, 가능하면 거기서 제기된 문제를 가지고 그걸 좀 자세히 다루어 볼까 합니다. 먼저 우리가 하나 짚고 넘어가야 할 것은 용어 오해 때문에 오는 문제가 많다는 것입니다. 가령, 언어학 그리고 어학(또는 언어 교육)의 세 가지 개념의 혼동 때문에 저희들 그룹에서 사전 토의를 하면서도 문제가 생겼읍니다. 언어학하면 순수 언어학, 언어학과에서 가르치는 언어학일 것이고 개별 언어학이라고 하면 영문과에서 가르치는 영어학, 독문과에서 가르치는 독어학 등을 이야기 하겠죠. 그리고 어학이라고 하면 저는 언어 교육이라고 하고 싶은데, 어학 교육이라고 하면 주로 개별 언어 기능, 그러니까 듣기, 말하기, 쓰기, 읽기의 기능을 가르치는 것을 보통은 어학 교육 또는 언어 교육이라고 하죠

討論

사회 : 李廷攻선생께서 그 동안 complementation에 대해 시도된 기술 방법에 대해 잘 요약해서 말씀해 주셨읍니다. 맨 먼저 본격적으로 complementation에 대해 시도하신 분이 李廷攻선생님이신데 먼저 李선생님께서 좀 말씀해 주시지요. 그 당시 취했던 기술방법과 지금 어떤 차이가 있다던지..

討論

사회: 수고하셨습니다. 세부분으로 나누어 자세히 말씀해주셨습니다. 토론회 순서는 주제 논문이 진행된 것과는 거꾸로， processing, 범주화， 언어습득의 순으로 다루겠습니다. 자세히 말씀해주셨지만 먼저 심리학을 하시는 김정오 선생님께서 언어 처리 문제에 있어서 전단계가 되는 지각측면과 관련하여 processing에 대하여 상세히 말씀해주시고 조선생님의 말씀에 대해서 의견을 제시해 주시겠습니다

A Model for the Lexicon in a Unification Grammar: the Case for English-Korean Machine Translation

This paper examines proposals concerning the organization of a lexicon in Head-driven Phrase Structure Grammar and Generalized Phrase Structure Grammar from a practical point of view. It discusses questions of how the theory of lexicon can be used in constructing an English dictionary, an English-Korean transfer dictionary, and a Korean dictionary as parts of an English-Korean machine translation system. It is shown that strong lexicalism presupposed by the two Unification Grammars and feature structures expressed in attribute-value matrixes employed in the grammars make it possible to utilize the lexicon model in machine translation in a flexible manner

Condensation 알고리즘을 이용한 운동추정

학위논문(석사)--서울대학교 대학원 :기계항공공학부,2003.Maste

Deep learning-based prediction of split glomerular filtration rate with 99mTc-diethylenetriamine pentaacetic acid renal scan

Purpose: To automate glomerular filtration rate (GFR) measurement by developing deep learning (DL) models for generating automated regions of interest (ROIs) on 99mTc-diethylenetriamine pentaacetic acid (99mTc-DTPA) renal scans and/or for directly regressing the GFR from the 99mTc-DTPA renal scans. Methods: Manually-drawn ROIs as well as the corresponding GFR values were retrieved from a Picture Archiving and Communications System were used as ground-truth (GT) (or silver standard) labels and target values, respectively. To this end, we developed two models: one using a two-dimensional U-Net convolutional neural network (CNN) architecture (ROI generator network) with multichannel input to automatically generate kidney and background ROIs, from which GFR was calculated using the Gates formula, and another model using a two-dimensional encoder CNN architecture (GFR regressor network) with multichannel input to directly predict GFR values without the need for ROIs, respectively. The agreement between GFR values from GT and DL ROIs was evaluated using Lin’s concordance correlation coefficient (CCC) and slope coefficients for linear regressor analyses. Bias and 95% limits of agreement (LOA) were assessed using Bland-Altman plots. Results: A total of 24364 scans (12821 patients) were included. Regarding the ROI generator network, we found excellent concordance between GT and DL GFR for left (CCC 0.982, 95% confidence interval [CI] 0.981–0.982; slope 1.004, 95% CI 1.003–1.004), for right (CCC 0.969, 95% CI 0.968–0.969; slope 0.954, 95% CI 0.953–0.955), and for both kidneys (CCC 0.978, 95% CI 0.978–0.979; slope 0.979, 95% CI 0.978–0.979). Bland-Altman analysis revealed minimal bias between GT and DL GFR, with mean differences of −0.2 (95% LOA −4.4–4.0), 1.4 (95% LOA −3.5–6.3) and 1.2 (95% LOA −6.5–8.8) mL/min/1.73 m² for left, right and both kidneys, respectively. Regarding the regressor network, GT and DL estimated GFR values is as follows for the left kidney (CCC 0.969, 95% CI 0.969–0.970), right kidney (CCC 0.969, 95% CI 0.968–0.969), and for both kidneys (CCC 0.972, 95% CI 0.971–0.972). Bland-Altman analysis revealed with mean differences of −0.06 (95% LOA −5.5–5.4), 0.15 (95% LOA −5.4–5.7) and 0.08 (95% LOA −8.9–9.1) mL/min/1.73 m² for left, right and both kidneys. Notably, 19960 scans (81.9%) showed an absolute difference in GFR of less than 5 mL/min/1.73 m² by the ROI generator network. Similarly, the regressor network showed an absolute difference in GFR of less than 5 mL/min/1.73 m² in 18,770 scans (77.0%). Conclusion: Our ROI generator network and GFR regressor network exhibited excellent performance in the generation of ROIs and estimate GFR on 99mTc-DTPA renal scans. This automated approach could potentially reduce manual effort and enhance the precision of GFR measurement in clinical practice.Maste

Split Device Driver Model for GPU Virtualization in KVM / ARM Environment

MasterMobile virtualization is currently a hot issue, because of growing security concern in Bring Your Own Device (BYOD) environment. Most workers use their mobile devices for work without any security policy enforced. Therefore, company secrets can be leaked by malignant code in a worker’s mobile devices, so the company want to separate the business environment from the private usage environment. Virtualization is one of the promising solutions to separate environments logically. It is quite challenging to virtualize GPU device in mobile platform because of its proprietary device driving architecture. GPU virtualization is essential in mobile virtualization, because GPU conducts core roles such as fast UI and web flash service. There are two types of device virtualization techniques: full virtualization and para-virtualization. In this thesis, GPU device is virtualized by para-virtualization. The para-virtualized GPU driver consists of the frontend driver in guest domain and the backend driver in host domain. This kind of device driver is called Split device driver. According to communication methods between the frontend driver and the backend driver, three different device driver models are designed and implemented. Firstly, Model 1 uses hypercall-based communication. Model 2 uses host polling to receive requests (e.g. file operations) from the guest domain and virtual interrupt to send results back to the guest domain. Model 3 uses polling-based communication for both guest and host domains. It is shown from experimental evaluations that Model 3 is the best solution for communication between guest and host when a guest VM runs only one GPU benchmark or a lightweight GPU benchmark with CPU-intensive benchmarks. Model 2 is the best solution when a VM runs a heavy GPU benchmark with CPU-intensive benchmarks or a GPU benchmark with latency-intensive job. Model 2 is also best solution from a point of CPU-intensive benchmarks. Model 1 is not bad when VM runs only one GPU benchmark, because a VM stop running a vCPU when running a hypercall. That is, Model 1 is not a choice when the VM runs several benchmarks and there is/are GPU benchmark(s) among them. In summary, when it comes to performance, Model 3 shows the best result. However it results in worst background jobs performance because it consumes lots of CPU cycles due to the polling mechanism. In contrast, Model 2 gives the best results for the background jobs because it does not require additional CPU cycles. To take advantage of both approaches, we have plan to combine the polling approach with the H/W based low-overhead communication mechanism such as IPI

안드로이드 호스트 기반 KVM/ARM 가상화 환경에서의 GPU 디바이스 구동기법

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