• The Journal of Korean Obstetrics and Gynecology
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• v.19 no.3
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• pp.1-12
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• 2006

Purpose : This study was aimed to investigate the inhibitory effect of Leonurus sibiricus on the proliferation of human uterine leiomyoma cells and the expression of gene related the mechanism of cell apoptosis. Methods : We counted the number of death cells treated with indicated concentration of Leonurus sibiricus and investigated cell death rate by MTS assay. Furthermore, flow cytometry analysis and DNA fragmentation assay were used to dissect between necrosis and apoptosis and then we observed the differential gene expression by western blot analysis. Results : Leonurus sibiricus significantly inhibited the proliferation of uterine leiomyoma cell in a dose-dependent and time dependent manner. Fluorescence activated cell sorter (FACS) analysis indicated that Leonurus sibiricus induced G1 cell cycle arrest. Leonurus sibiricus enhanced the expression of p27 and p53 with cell cycle arrest. Conclusion : These findings suggest that Leonurus sibiricus is a candidate agent for the treatment of uterine leiomyoma. p27, $p53^{1}$ may play an important role in Leonurus sibiricus-induced cell cycle arrest and cell growth inhibition.

• Journal of Microbiology
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• v.40 no.3
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• pp.219-223
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• 2002

In order to investigate the function of Soo1p/${\alpha}$-COP during post-translational modification and intra-cellular transport of cell wall proteins in Saccharomyces cerevisiae, cell wall proteins from the soo1-1/ret1-1 mutant cells were analyzed. SDS-PAGE analysis of biotin labeled cell wall proteins suggested that the soo1-1 mutation impairs post-translational modification of cell wall proteins, such as N- and/ or Ο-glycosylation. Analysis of cell wall proteins with antibodies against ${\beta}$-1,3-glucan and ${\beta}$-1,6-glucan revealed alteration of the linkage between cell wall proteins and ${\beta}$-glucans in the soo1-1 mutant cells. Compositional sugar analysis of the cell wall proteins also suggested that the soo1-1 mutation impairs glycosylation of cell wall protein in the ER, which is crucial for the maintenance of cell wall integrity.

• IMMUNE NETWORK
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• v.8 no.2
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• pp.53-58
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• 2008

Background: Molecular mechanisms of natural killer (NK) cell development from hematopoietic stem cells (HSCs) have not been clearly elucidated, although the roles of some genes in NK cell development have been reported previously. Thus, searching for molecules and genes related NK cell developmental stage is important to understand the molecular events of NK cell development. Methods: From our previous SAGE data-base, Gpnmb (Glycoprotein non-metastatic melanoma protein B) was selected for further analysis. We confirmed the level of mRNA and protein of Gpnmb through RT-PCR, quantitative PCR, and FACS analysis. Then we performed cell-based ELISA and FACS analysis, to know whether there are some molecules which can bind to Gpnmb. Using neutralizing antibody, we blocked the interaction between NK cells and OP9 cells, and checked IFN-${\gamma}$ production by ELISA kit. Results: Gpnmb expression was elevated during in vitro developmental stage and bound to OP9 cells, but not to NK precursor cells. In addition, we confirmed that the levels of Gpnmb were increased at NK precursor stage in vivo. We confirmed syndecan4 as a candidate of Gpnmb's binding molecule. When the interaction between NK cells and OP9 cells were inhibited in vitro, IFN-${\gamma}$ production from NK cells were reduced. Conclusion: Based on these observations, it is concluded that Gpnmb has a potential role in NK cell development from HSCs.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.2
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• pp.226-232
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• 2011

In this study, an optimized design of a triaxial load cell has been developed by the use of finite element analysis, design of experiment and response surface method. The developed optimal design was further validated by both stress-strain analysis and natural vibration analysis under an applied load of 30 kgf. When vertical, horizontal, and axial loads of 30 kgf were applied to the load cell with the optimal design, the calculated strains were satisfied with the required strain range of $500{\times}10^{-6}{\pm}10%$. The natural vibration analysis exhibited that the fundamental natural frequency of the optimally designed load cell was 5.56 kHz and higher enough than a maximum frequency of 0.17 kHz which can be applied to the load cell for wind-tunnel tests. The satisfactory sensitivity in all triaxial directions also suggests that the currently proposed design of the triaxial load cell enables accurate measurements of the multi-axial forces in wind-tunnel tests.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.6
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• pp.267-272
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• 2016

Microscope cell image is an important indicator for obtaining the biological information in a bio-informatics fields. Since human observers have been examining the cell image with microscope, a lot of time and high concentration are required to analyze cell images. Furthermore, It is difficult for the human eye to quantify objectively features in cell images. In this study, we developed HCS algorithm for automatic analysis of cell image using an OpenCV library. HCS algorithm contains the cell image preprocessing, cell counting, cell cycle and mitotic index analysis algorithm. We used human cancer cell (MKN-28) obtained by the confocal laser microscope for image analysis. We compare the value of cell counting to imageJ and to a professional observer to evaluate our algorithm performance. The experimental results showed that the average accuracy of our algorithm is 99.7%.

• 한국정보통신설비학회:학술대회논문집
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• 2007.08a
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• pp.251-255
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• 2007

In this paper, propagation analysis method in using 3D Ray Tracing propagation model in wireless cell planning is proposed. Through 3D Ray Tracing model, we can predict the distribution of propagation loss of the received signal. For correct and a low complex analysis, Quad Tree and Pre-Ordering and Hash Function algorithms are included in 3D Ray Tracing algorithm. And 3D Ray Tracing model is embodied in CellTREK that is developed by KT and used to plan Wibro system analysis. In CellTREK, propagation analysis is performed and that result is represented in 3D viewer. In numerical results, it is showed that the proposed scheme outperforms Modified HATA model when comparing with measurement data.

• Transactions of the Korean hydrogen and new energy society
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• v.26 no.1
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• pp.35-44
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• 2015

This paper deals with the economic analysis of domestic fuel cell vehicles considering subsidy and hydrogen price in 2015 and 2025. We selected TFCV (Tucson fuel cell vehicle) and TDV (Tucson diesel vehicle) to identify the economic feasibility of fuel cell vehicles compared with conventional internal combustion engine vehicles. We made some sensitivity analysis by changing input factors such as the size of the subsidy, the hydrogen price and the discount rate. Also, we made a break-even point analysis on hydrogen prices that equalize the economic feasibility of TFCV and TDV in 2025. As a result, TFCV is not economical in 2015 due to the relatively high prices of hydrogen and vehicles. If the sale prices of TFCV are 30,000,000 won and 35,000,000 won in 2025, then the break-even points of hydrogen prices are equal to 7,483 won/kg and 5,043 won/kg.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.1
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• pp.24-35
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• 2013

A cell formation approach based on cluster analysis is developed for the configuration of manufacturing cells. Cell formation, which is to group machines and parts into machine cells and the associated part families, is implemented to add the flexibility and efficiency to manufacturing systems. In order to develop an efficient clustering procedure, this paper proposes a cluster analysis-based approach developed by incorporating and modifying two cluster analysis methods, a hierarchical clustering and a non-hierarchical clustering method. The objective of the proposed approach is to minimize intercellular movements and maximize the machine utilization within clusters. The proposed approach is tested on the cell formation problems and is compared with other well-known methodologies available in the literature. The result shows that the proposed approach is efficient enough to yield a good quality solution no matter what the difficulty of data sets is, ill or well-structured.

• Journal of Korea Multimedia Society
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• v.11 no.12
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• pp.1635-1648
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• 2008

The extraction of important features in cancer cell image analysis is a key process in grading renal cell carcinoma. In this study, we applied three-dimensional (3D) texture feature extraction methods to cell nuclei images and evaluated the validity of them for computerized cell nuclei grading. Individual images of 2,423 cell nuclei were extracted from 80 renal cell carcinomas (RCCs) using confocal laser scanning microscopy (CLSM). First, we applied the 3D texture mapping method to render the volume of entire tissue sections. Then, we determined the chromatin texture quantitatively by calculating 3D gray-level co-occurrence matrices (3D GLCM) and 3D run length matrices (3D GLRLM). Finally, to demonstrate the suitability of 3D texture features for grading, we performed a discriminant analysis. In addition, we conducted a principal component analysis to obtain optimized texture features. Automatic grading of cell nuclei using 3D texture features had an accuracy of 78.30%. Combining 3D textural and 3D morphological features improved the accuracy to 82.19%. As a comparative study, we also performed a stepwise feature selection. Using the 4 optimized features, we could obtain more improved accuracy of 84.32%. Three dimensional texture features have potential for use as fundamental elements in developing a new nuclear grading system with accurate diagnosis and predicting prognosis.

• Molecules and Cells
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• v.37 no.6
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• pp.457-466
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• 2014

Proteomic analysis is helpful in identifying cancerassociated proteins that are differentially expressed and fragmented that can be annotated as dysregulated networks and pathways during metastasis. To examine metastatic process in lung cancer, we performed a proteomics study by label-free quantitative analysis and N-terminal analysis in 2 human non-small-cell lung cancer cell lines with disparate metastatic potentials - NCI-H1703 (primary cell, stage I) and NCI-H1755 (metastatic cell, stage IV). We identified 2130 proteins, 1355 of which were common to both cell lines. In the label-free quantitative analysis, we used the NSAF normalization method, resulting in 242 differential expressed proteins. For the N-terminal proteome analysis, 325 N-terminal peptides, including 45 novel fragments, were identified in the 2 cell lines. Based on two proteomic analysis, 11 quantitatively expressed proteins and 8 N-terminal peptides were enriched for the focal adhesion pathway. Most proteins from the quantitative analysis were upregulated in metastatic cancer cells, whereas novel fragment of CRKL was detected only in primary cancer cells. This study increases our understanding of the NSCLC metastasis proteome.