• BMB Reports
• /
• 제44권12호
• /
• pp.805-810
• /
• 2011

Methionine sulfoxide reductase A (MSRA) is a ubiquitous enzyme that has been demonstrated to reduce the S enantiomer of methionine sulfoxide (MetSO) to methionine (Met) and can protect cells against oxidative damage. In this study, we isolated a novel MSRA (SlMSRA2) from Micro-Tom (Solanum lycopersicum L. cv. Micro-Tom) and characterized it by subcloning the coding sequence into a pET expression system. Purified recombinant protein was assayed by HPLC after expression and refolding. This analysis revealed the absolute specificity for methionine-S-sulfoxide and the enzyme was able to convert both free and protein-bound MetSO to Met in the presence of DTT. In addition, the optimal pH, appropriate temperature, and $K_m$ and $K_{cat}$ values for MSRA2 were observed as 8.5, $25^{\circ}C$, $352{\pm}25\;{\mu}M$, and $0.066{\pm}0.009\;S^{-1}$, respectively. Disk inhibition and growth rate assays indicated that SlMSRA2 may play an essential function in protecting E. coli against oxidative damage.

• Archives of Pharmacal Research
• /
• 제28권10호
• /
• pp.1164-1169
• /
• 2005

Brain microglia are phagocytic cells that are the major inflammatory response cells of the central nervous system and widely held to play important pathophysiologic roles in Alzheimer's disease (AD) in both potentially neurotoxic responses and potentially beneficial phagocytic responses. In the study, we examined whether ginsonoside Rg3, a by-product of red ginseng, enhances the microglial phagocytosis of $A{\beta}$. We found that Rg3 promoted $A{\beta}$ uptake, internalization, and digestion. Increased maximal $A{\beta}$ uptake was observed at 4 and 8 h after Rg3 pretreatment (25 ${\mu}g/mL$), and the internalized $A{\beta}$ was almost completely digested from cells within 36 h when pretreated with Rg3 comparing with single non-Rg3-treated groups. The expression of MSRA (type A MSR) was also up-regulated by Rg3 treatment in a dose- and time-dependent manner which was coincidently identified in western blots for MSRA proteins in cytosol. These results indicate that microglial phagocytosis of $A{\beta}$ may be enhanced by Rg3 and the effect of Rg3 on promoting clearance of $A{\beta}$ may be related to the MSRA-associated action of Rg3. Thus, stimulation of the MSRA might contribute to the therapeutic potentials of Rg3 in microglial phagocytosis and digestion in the treatment of AD.

• Journal of Plant Biotechnology
• /
• 제35권2호
• /
• pp.133-140
• /
• 2008

DNA와 histone 단백질의 변형은 식물 발달에 상당히 중요한 역할을 하는 것으로 알려져 있다. 식물 조직 배양 및 식물 발달 단계에서 methylation의 영향을 알아보고자 벼 종자로부터 캘러스 형성 및 식물체 재분화 단계에서 demethylation 물질인 5-azacytidine을 처리하여 유전자 발현 양상을 분석하였다. 식물체로의 재분화 능력이 있는 벼 배상체 캘러스는 5-azaC가 첨가된 H6A 배지에서는 형성되지 않았으며 갈색을 띠는 캘러스가 형성되었다. 또한 정상적인 캘러스를 5-azaC가 첨가된 MSRA 재분화 배지에서 배양했을 때도 대조구와는 달리 식물체 재분화는 이루어지지 않았다. 이러한 결과는 5-azaC가 정상적인 배상체 캘러스 및 shoot 분화에 부정적인 영향을 미친다는 것을 나타냈으며 따라서 DNA methylation이 식물 조직배양에서의 정상적인 세포 dedifferentiation과 differentiation에 필수 요인이라는 것을 알 수 있었다. 벼 캘러스 형성 및 재분화 과정 동안의 methylation 영향을 알아보고자 각 단계별로 5-azaC를 처리 후 $GeneFishig^{TM}$ DEG와 DNA chip을 사용하여 유전자 발현 양상을 분석하였다. Epigenetic regulation, 전자전달, 핵산대사, 스트레스 반응에 관여하는 일부 유전자들의 발현이 증가하거나 감소하는 것을 알 수 있었다. 발현 차이가 있는 일부 유전자를 클로닝하여 확인하였고 RT-PCR 및 northern 분석으로 각 단계에서의 발현 차이를 할인하였다.

• 수산경영론집
• /
• 제41권3호
• /
• pp.103-127
• /
• 2010

The FAO reports that IUU fishing activities have widespread economic, social, and management consequences, including depriving legitimate fishers of harvest opportunities. It affects all fisheries from small scale to industrial. It also affects the ability of governments to support sustainable livelihoods for fishers and, more broadly, to achieve food security. The complexity of IUU requires various measures to combat IUU fishing such as adoption of IUU vessel lists; stronger port State controls; improved monitoring, control and surveillance (MCS); implementation of market-related measures to help ensure compliance; and capacity-building assistance. Trade and market measures reduce opportunities for IUU fishing activities by precluding or impeding access to markets for IUU product in a manner consistent with international law. ICCAT, CCAMLR, and IATTC, have put in place trade tracking programs or catch documentation schemes, and WCPFC is considering such a program. Vessel lists assist enforcement authorities in determining which vessels are or are not authorized to be fishing or conducting fishing support activities in specified areas. A number of RFMOs maintain records of IUU vessels: CCAMLR, IATTC, ICCAT, NAFO, NASCO, NPAFC, WCPFC. Section 608 of the US MSRA calling on the Secretary of Commerce, in consultation with the Secretary of State, and in cooperation with relevant regional fishery management councils and any relevant advisory committees, to take actions to improve the effectiveness of international fishery management organizations in conserving and managing stocks under their jurisdiction. EU IUU Regulation entered into force on 1 January 2010, was intended to regulate the highly complex multi-channel fisheries supply system of the European Community (EC) in an effort to improve global fisheries sustainability.

• 한국방송∙미디어공학회:학술대회논문집
• /
• 한국방송∙미디어공학회 2019년도 추계학술대회
• /
• pp.124-127
• /
• 2019

본 논문에서는 단일 이미지의 관심 영역에 기반한 저심도 후처리 방법을 제안한다. 저심도 이미지란 사진에서 초점이 선명하게 포착되는 깊이의 범위가 좁은 이미지를 말한다. 기존의 광학적 특성을 이용한 저심도 이미지를 만드는 과정은 물리적인 구조 설계비용 문제가 존재한다. 또한, 이미지의 후처리 보정을 통한 방법은 이미지상의 사물 깊이 정보를 알기 어렵기 때문에 이미지의 심도를 후처리하기 어려웠다. 이에 따라 본 논문에서는 슈퍼 픽셀 군집화 방법을 통해 관심 영역을 찾고, 이에 기반하여 관심 영역이 부각될 수 있는 저심도 후처리 방법을 제안한다. 제안하는 후처리 방법은 슈퍼픽셀 군집화 방법을 통해 관심영역을 설정하여 배경 영역을 분리하고 블러 과정을 수행한다. 관심 영역을 제외한 부분을 확장 한 뒤 배경 블러를 거치기 때문에 후광효과가 현저히 줄어든 저심도 효과가 적용된 이미지를 얻을 수 있었고 MSRA-1000 데이터 셋 이미지에서 우수한 주관적 화질 결과를 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제10권9호
• /
• pp.4386-4404
• /
• 2016

Most existing salient object detection algorithms commonly employed segmentation techniques to eliminate background noise and reduce computation by treating each segment as a processing unit. However, individual small segments provide little information about global contents. Such schemes have limited capability on modeling global perceptual phenomena. In this paper, a novel salient object detection algorithm is proposed based on region merging. An adaptive-based merging scheme is developed to reassemble regions based on their color dissimilarities. The merging strategy can be described as that a region R is merged with its adjacent region Q if Q has the lowest dissimilarity with Q among all Q's adjacent regions. To guide the merging process, superpixels that located at the boundary of the image are treated as the seeds. However, it is possible for a boundary in the input image to be occupied by the foreground object. To avoid this case, we optimize the boundary influences by locating and eliminating erroneous boundaries before the region merging. We show that even though three simple region saliency measurements are adopted for each region, encouraging performance can be obtained. Experiments on four benchmark datasets including MSRA-B, SOD, SED and iCoSeg show the proposed method results in uniform object enhancement and achieve state-of-the-art performance by comparing with nine existing methods.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제12권2호
• /
• pp.676-692
• /
• 2018

Saliency detection in neurobiology is a vehement research during the last few years, several cognitive and interactive systems are designed to simulate saliency model (an attentional mechanism, which focuses on the worthiest part in the image). In this paper, a bottom up saliency detection model is proposed by taking into account the color and luminance frequency features of RGB, CIE $L^*a^*b^*$ color space of the image. We employ low-level features of image and apply band pass filter to estimate and highlight salient region. We compute the likelihood probability by applying Bayesian framework at pixels. Experiments on two publically available datasets (MSRA and SED2) show that our saliency model performs better as compared to the ten state of the art algorithms by achieving higher precision, better recall and F-Measure.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제10권1호
• /
• pp.272-287
• /
• 2016

Recently, various and effective contrast based salient object detection models to focus on a single target have been proposed. However, there is a lack of research on detection of multiple objects, and also it is a more challenging task than single target process. In the multiple target problem, we are confronted by new difficulties caused by distinct difference between properties of objects. The characteristic of existing models depending on the global maximum distribution of data point would become a drawback for detection of multiple objects. In this paper, by analyzing limitations of the existing methods, we have devised three main processes to detect multiple salient objects. In the first stage, regional features are extracted from over-segmented regions. In the second stage, the regional features are categorized into homogeneous cluster using the mean-shift algorithm with the kernel function having various sizes. In the final stage, we compute saliency scores of the categorized regions using only spatial features without the contrast features, and then all scores are integrated for the final salient regions. In the experimental results, the scheme achieved superior detection accuracy for the SED2 and MSRA-ASD benchmarks with both a higher precision and better recall than state-of-the-art approaches. Especially, given multiple objects having different properties, our model significantly outperforms all existing models.

• 한국언어정보학회:학술대회논문집
• /
• 한국언어정보학회 2007년도 정기학술대회
• /
• pp.303-310
• /
• 2007

Named Entity Recognition (NER) is always limited by its lower recall resulting from the asymmetric data distribution where the NONE class dominates the entity classes. This paper presents an approach that exploits non-local information to improve the NER recall. Several kinds of non-local features encoding entity token occurrence, entity boundary and entity class are explored under Conditional Random Fields (CRFs) framework. Experiments on SIGHAN 2006 MSRA (CityU) corpus indicate that non-local features can effectively enhance the recall of the state-of-the-art NER systems. Incorporating the non-local features into the NER systems using local features alone, our best system achieves a 23.56% (25.26%) relative error reduction on the recall and 17.10% (11.36%) relative error reduction on the F1 score; the improved F1 score 89.38% (90.09%) is significantly superior to the best NER system with F1 of 86.51% (89.03%) participated in the closed track.

• 한국방송∙미디어공학회:학술대회논문집
• /
• 한국방송∙미디어공학회 2018년도 하계학술대회
• /
• pp.322-325
• /
• 2018

영상의 관심 영역 검출은 영상처리 및 컴퓨터 비전 응용 분야에서 꾸준하게 사용되고 있는 기법이다. 특히, 근래 심층신경망 연구의 급격한 발전에 힘입어 심층신경망을 이용한 관심 영역 검출 기법에 대한 연구가 활발하게 진행되고 있다. 한편 Fully Convolutional Network(이하 FCN)은 본래 심층 예측(Dense Prediction)을 통한 의미론적 영상 분할(Semantic Segmentation)을 수행하기 위해 제안된 심층신경망 구조이다. FCN을 영상의 관심 영역 검출에 활용하여도 기존 관심 영역 검출 기법과 비교하여 충분히 좋은 성능을 발휘할 수 있다. 그러나 FCN에 사용되는 convolution 층의 수가 많고, 이에 따른 가중치(weight)의 개수도 기하급수적으로 늘어나 검출에 필요한 시간 복잡도가 매우 크다는 문제점이 있다. 따라서 본 논문에서는 기존 FCN이 가진 검출 시간 복잡도의 문제점을 convolution 층의 가중치 관점에서 해결하고자 이를 조절하여 FCN의 관심 영역 검출 속도를 향상시키는 방법을 제안한다. 적절한 convolution 층의 가중치를 조절함으로써, MSRA10K 데이터셋 환경에서 검출 정확도를 크게 저하시키지 않고도 최대 약 20.5%만큼 검출 속도를 향상시킬 수 있었다.