• Journal of Biomedical Engineering Research
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• v.28 no.5
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• pp.601-608
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• 2007

2 Dimensional Gel Electrophoresis(2DGE) is an essentialmethodology for analysis on the expression of various proteins. For example, information for the location, mass, expression, size and shape of the proteins obtained by 2DGE can be used for diagnosis, prognosis and biological progress by comparison of patients with the normal persons. Protein spot matching for this purpose is comparative analysis of protein expression pattern for the 2DGE images generated under different conditions. However, visual analysis of protein spots which are more than several hundreds included in a 2DGE image requires long time and heavy effort. Furthermore, geometrical distortion makes the spot matching for the same protein harder. In this paper, an iterative algorithm is introduced for more efficient spot matching. Proposed method is first performing global matching step, which reduces the geometrical difference between the landmarks and the spot to be matched. Thus, movement for a spot is defined by a weighted sum of the movement of the landmark spots. Weight for the summation is defined by the inverse of the distance from the spots to the landmarks. This movement is iteratively performed until the total sum of the difference between the corresponding landmarks is larger than a pre-selected value. Due to local distortion generally occurred in 2DGE images, there are many regions in whichmany spot pairs are miss-matched. In the second stage, the same spot matching algorithm is applied to such local regions with the additional landmarks for those regions. In other words, the same method is applied with the expanded landmark set to which additional landmarks are added. Our proposed algorithm for spot matching empirically proved reliable analysis of protein separation image by producing higher accuracy.

• Journal of Radiation Protection and Research
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• v.36 no.3
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• pp.107-118
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• 2011

Conventional (SRS) and fractionated (FSRS) stereotactic radiosurgery necessarily require stringent overall target point accuracy and precision. We determine three-dimensional intracranial target point deviations (TPDs) in a whole treatment procedure using magnetic resonance image (MRI)-based polymer-gel dosimetry, and suggest a technique for overall system tests. TPDs were measured using a custom-made head phantom and gel dosimetry. We calculated TPDs using a treatment planning system. Then, we compared TPDs using mid bi-plane and three-dimensional volume methods with spherical and elliptical targets to determine their inherent analysis errors; finally, we analyzed regional TPDs using the latter method. Average and maximum additive errors for ellipses were 0.62 and 0.69 mm, respectively. Total displacements were 0.92 ${\pm}$ 0.25 and 0.77 ${\pm}$ 0.15 mm for virtual SRS and FSRS, respectively. Average TPDtotal at peripheral regions was greater than that at central regions for both. Overall system accuracy was similar to that reported previously. Our technique could be used as an overall system accuracy test that considers the real radiation field shape.

• Journal of the Korean Society of Visualization
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• v.12 no.2
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• pp.18-22
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• 2014

Caenorhabditis elegans (C. elegans) is an undulatory nematode which exhibits two distinct locomotion types of swimming and crawling. Although in its natural habitat C. elegans lives in a non-Newtonian fluidic environment, our current understanding has been limited to the behavior of C. elegans in a simple Newtonian fluid. Here, we present some experimental results on the penetrating behavior of C. elegans at the interface from liquid to solid environment. Once C. elegans, which otherwise swims freely in a liquid, makes a contact to the solid gel boundary, it begins to penetrate vertically to the surface by changing its stroke motion characterized by a stiffer body shape and a slow stroke frequency. The particle image velocimetry (PIV) analysis reveals the flow streamlines produced by the stroke of worm. For the worm that crawls on a solid surface, we utilize a technique of traction force microscopy (TFM) to find that the crawling nematode forms localized force islands along the body where makes direct contacts to the gel surface.

• KOGO NEWS
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• v.6 no.1
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• pp.24-28
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• 2006

프로테오믹스는 생물체 안에 포함되어 있는 단백질을 통합적으로 연구한다. 단백질을 동정(Protein identification)하고, 단백질의 상태를 분석(Protein characterization)하며, 단백질의 양적 변화를 관찰(Protein quantitation)한다. 단백질에 대한 분석, 특히 질량분석기에 의해 초고속으로 대량의 단백질 데이터를 생산하는 프테테오믹스의 연구는 정량적인 단백질 발현양상분석의 정확도를 높이고 분석시간을 단축하기 위해 다양한 실험기법과 데이터 분석기법을 동원하고 있다. 1) 단백질의 양적 차이나 양적 변화의 관찰은 바이오마커를 발굴하고 생명현상의 메카니즘을 규명하여 그 결과를 신약개발에 활용하기 위한 기초 연구이다. 이 글에서는 프로테오믹스 연구의 초창기부터 사용되어온 2차원 전기영동법에 의해 생성되는 2D-gel image에서의 스팟(spot)분석법과 함께, 탄뎀 질량분석기를 사용하는 ICAT, SILAC 등의 동위 원소를 사용한 라벨링(labeling) 방법, 라벨링을 하지 않는 label-free 방법 등 프로테오믹스에서의 정량분석법에 대한 기본 개념을 살펴보고, 이들에서의 데이터 분석 기술의 적용에 대해 간략히 소개하였다.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.6
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• pp.788-795
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• 2015

Two dimensional-fluorescence difference gel electrophoresis (2D DIGE) is an emerging technique for comparative proteomics, which improves the reproducibility and reliability of differential protein expression analysis between samples. The purpose of this study was to investigate bovine pregnancy-specific proteins in the proteome between bovine pregnant and non-pregnant serum using DIGE technique. Serums of 2 pregnant Holstein dairy cattle at day 21 after artificial insemination and those of 2 non-pregnant were used in this study. The pre-electrophoretic labeling of pregnant and non-pregnant serum proteins were mixed with Cy3 and Cy5 fluorescent dyes, respectively, and an internal standard was labeled with Cy2. Labeled proteins with Cy2, Cy3, and Cy5 were separated together in a single gel, and then were detected by fluorescence image analyzer. The 2D DIGE method using fluorescence CyDye DIGE flour had higher sensitivity than conventional 2D gel electrophoresis, and showed reproducible results. Approximately 1,500 protein spots were detected by 2D DIGE. Several proteins showed a more than 1.5-fold up and down regulation between non-pregnant and pregnant serum proteins. The differentially expressed proteins were identified by MALDI-TOF mass spectrometer. A total 16 protein spots were detected to regulate differentially in the pregnant serum, among which 7 spots were up-regulated proteins such as conglutinin precursor, modified bovine fibrinogen and IgG1, and 6 spots were down-regulated proteins such as hemoglobin, complement component 3, bovine fibrinogen and IgG2a three spots were not identified. The identified proteins demonstrate that early pregnant bovine serum may have several pregnancy-specific proteins, and these could be a valuable information for the development of pregnancy-diagnostic markers in early pregnancy bovine serum.

• Molecules and Cells
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• v.22 no.1
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• pp.36-43
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• 2006

Mesenchymal stem cells (MSCs) are promising candidates for cell therapy and tissue engineering, but their application has been impeded by lack of knowledge of their core biological properties. In order to identify MSC-specific proteins, the hydrophobic protein fraction was individually prepared from two different umbilical cord blood (UCB)-derived MSC populations; these were then subjected to two-dimensional (2D) gel electrophoresis and peptide mass fingerprinting matrix-assisted laser desorption/ionization (MALDI)-time of flight (TOF)-mass spectrometry (MS). Although the 2D gel patterns differed somewhat between the two samples, computer-assisted image analysis identified shared protein spots. 35 spots were reliably identified corresponding to 32 different proteins, many of which were chaperones. Based on their primary sub-cellular locations the proteins could be grouped into 6 categories: extracellular, cell surface, endoplasmic reticular, mitochondrial, cytoplasmic and cytoskeletal proteins. This map of the water-insoluble proteome may provide valuable insights into the biology of the cell surface and other compartments of human MSCs.

• Reproductive and Developmental Biology
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• v.32 no.4
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• pp.255-261
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• 2008

The early diagnosis of bovine pregnancy is an essential component of successful reproductive planning on farms, because lack of bovine pregnancy over the long term results in reproductive failure and low milk yield-the latter of which is a special concern on dairy farms. This study was designed to identify early pregnancy-specific whey proteins in bovine, by comparing milk samples collected from cattle during pregnancy (Days 30 and 50) and from non-pregnant cattle. In this study, differentially expressed proteins in five pregnant and five non-pregnant Holstein dairy cattle were investigated and compared, using proteomics analysis. The first dimension was applied to a pH $3.0{\sim}10.0$ strip, by loading a 2-mg milk protein sample. After the second-dimension separation was performed, the gels were stained with colloidal Coomassie brilliant blue. The stained gels were scanned and the images were analyzed, to detect variations in protein spots between non-pregnant and pregnant cattle milk protein spots, using ImageMaster, this was followed by analysis with MALDI TOF-MS. Analysis of the 2-DE gel image resulted in a total of approximately $500{\sim}600$ protein spots, of which 12 spots were differentially expressed, six spots were up-regulated, and four spots were down-regulated; two spots were identified as pregnancy-specific proteins. These proteins were identified as lactoferrin, NA-DH dehydrogenase subunit 2, albumin, serum albumin precursor and transferrin. Our results via 2-D PAGE analysis revealed composite profiles of several milk proteins related to early bovine pregnancy, implying the possible use of these milk proteins in the early detection of bovine pregnancy.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.898-902
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• 2003

In this paper we proposes a new technique for identification of breast cancer by classification of proteome pattern generated from 2-D polyacrylamide gel electrophoresis (2-D PAGE) and development of cancer diagnosis system : HABIT. Proteome patterns reflect the underlying pathological state of a human organ and it is believed that the anomalies or diseases of human organs are identified by the analysis or classification of the patterns. Proteome patterns consist of quantitative information of the spots such as their size, position, and density in the proteome image produced from 2-D PAGE, for the Image mining of proteome pattern, SVM(support vector machine) and GA(genetic algorithm) are used to generate a decision model for the identification of breast cancer The decision model was then used to classify an independent set of test proteome patterns into the affecter and unaffecter classes. The proposed technique was tested by actual clinical test samples and showed a good performance of a hit ratio of 90%.

• Korean Journal of Animal Reproduction
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• v.26 no.4
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• pp.377-384
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• 2002

To investigate the expression patterns of proteins and growth factor signals in differentiated rabbit embryonic stem (ES) cells, ES cells with confluent stage grown of feeder layer and differentiated cells into embryoid bodies (EB) without feeder cell were applied to protein gel and Western blotting analysis. There were 66kDa and 28kDa specifically expressed in differentiated ES cell but not in undifferentiated ES cell while 25kDa protein band showed up in only undifferentiated ES cells. Also there were some difference of protein bands in several area of gel between differentiated and undifferentiated ES cells such as about 100 kDa, 50kDa and 27kDa areas, but there was no difference in band pattern of one-dimensional gel analysis between mouse ES cells and rabbit ES cells. IGF-I receptor and EGF receptor were expressed in differentiated cells and undifferentiated cells. And ICF-I and EGF were not expressed in both differentiated and undifferentiated cells. These results indicated that ES cells express their own proteins to inhibit differentiation while EB cells synthesize different proteins to differentiate, and 16F-I receptor and EGF receptor were expressed in both ES and EB cells probably for the different functions.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.577-580
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• 2017

중합 효소 연쇄 반응 (PCR) 젤 전기영동 이미지에서 DNA 지문을 분석하기 위한 새로운 레인 검출 및 추적 알고리즘이 제안하였다. 이전에 여러 연구 결과가 보고되었지만 갑작스런 배경 밝기 차이와 구부러진 레인이 있는 이미지에서 레인을 정확하게 추출하는 것은 여전히 어려움이 있다. 우리는 평균 레인 폭과 레인 주기를 계산하기 위한 에지 기반 알고리즘을 제안한다. 본 논문에서 제안한 방법은 k-means 클러스터링 알고리즘을 이용하여 상승 에지와 하강 에지를 정확하게 추출하는 부화소(sub-pixel) 알고리즘을 적용하여 레인 폭과 주기를 추정한다. 구부러진 레인을 처리하기 위해 젤 이미지를 정상영역과 비정상영역으로 분할하고, 각 분할 된 이미지의 레인 중심을 추적한다. 우리가 제안한 방법의 성능을 평가하기 위해 534 레인을 포함한 32 개의 젤 이미지가 사용되었다. 실험 결과는 우리의 방법이 전처리 과정 없이 배경 차이와 구부러진 레인을 갖는 이미지에 강인함을 보여 주었다.