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Park S.-W.,Korea University | Do H.-J.,Korea University | Huh S.-H.,Korea University | Sung B.,Korea University | And 4 more authors.
Biochemical and Biophysical Research Communications | Year: 2012

NANOG is a homeobox-containing transcription factor that plays an important role in pluripotent stem cells and tumorigenic cells. To understand how nuclear localization of human NANOG is regulated, the NANOG sequence was examined and a leucine-rich nuclear export signal (NES) motif ( 125MQELSNILNL 134) was found in the homeodomain (HD). To functionally validate the putative NES motif, deletion and site-directed mutants were fused to an EGFP expression vector and transfected into COS-7 cells, and the localization of the proteins was examined. While hNANOG HD exclusively localized to the nucleus, a mutant with both NLSs deleted and only the putative NES motif contained (hNANOG HD-ΔNLSs) was predominantly cytoplasmic, as observed by nucleo/cytoplasmic fractionation and Western blot analysis as well as confocal microscopy. Furthermore, site-directed mutagenesis of the putative NES motif in a partial hNANOG HD only containing either one of the two NLS motifs led to localization in the nucleus, suggesting that the NES motif may play a functional role in nuclear export. Furthermore, CRM1-specific nuclear export inhibitor LMB blocked the hNANOG potent NES-mediated export, suggesting that the leucine-rich motif may function in CRM1-mediated nuclear export of hNANOG. Collectively, a NES motif is present in the hNANOG HD and may be functionally involved in CRM1-mediated nuclear export pathway. © 2012 Elsevier Inc. Source

Park S.-W.,Korea University | Do H.-J.,Korea University | Ha W.T.,Korea University | Han M.-H.,Korea University | And 4 more authors.
Biological and Pharmaceutical Bulletin | Year: 2014

E26 transformation-specific (ETS) transcription factors play important roles in normal and tumorigenic processes during development, differentiation, homeostasis, proliferation, and apoptosis. To identify critical ETS factor(s) in germ cell-derived cancer cells, we examined the expression patterns of the 27 ETS transcription factors in naive and differentiated NCCIT human embryonic carcinoma cells, which exhibit both pluripotent and tumorigenic characteristics. Overall, expression of ETS factors was relatively low in NCCIT cells. Among the 27 ETS factors, polyomavirus enhancer activator 3 (PEA3) and epithelium-specific ETS transcription factor-1 (ESE-1) exhibited the most significant changes in their expression levels. Western blot analysis confirmed these patterns, revealing reduced levels of PEA3 protein and elevated levels of ESE-1 protein in differentiated cells. PEA3 increased the proportion of cells in S-phase and promoted cell growth, whereas ESE-1 reduced proliferation potential. These data suggest that PEA3 and ESE-1 may play important roles in pluripotent and tumorigenic embryonic carcinoma cells. These findings contribute to our understanding of the functions of oncogenic ETS factors in germ cell-derived stem cells during processes related to tumorigenesis and pluripotency. © 2014 The Pharmaceutical Society of Japan. Source

Choi Y.M.,Konkuk University | An S.,Konkuk University | Lee E.-M.,Konkuk University | Kim K.,Konkuk University | And 5 more authors.
International Journal of Oncology | Year: 2012

Cytochrome P450 1A1 (CYP1A1) is a member of the cytochrome p450 enzyme family, which is involved in the metabolisms of carcinogenic metabolites, such as benzo(a)pyrene. In this study, we identified miR-892a as a negative regulator of CYP1A1 expression. Luciferase assays revealed a sequence in the 3′-untranslated region of CYP1A1 that displayed a perfect match with miR-892a, and revealed that this sequence was a specific miR-892a target site. The overexpression of miR-892a inhibited the expression of the CYP1A1 protein, and the miR-892a antagonist increased CYP1A1 expression. Of note, benzo(a)pyrene, a major inducer of CYP1A1 transcription, decreased the expression of miR-892a. Moreover, the miR-892a-induced CYP1A1 repression inhibited the benzo(a)pyrene-mediated decrease in cell viability. These data provide insight into the CYP1A1 regulatory network. Source

Oh J.,Korea University | Min J.,Sangji Youngseo College
Canadian Journal of Civil Engineering | Year: 2011

The image-based incident detection system is capable of not only replacing the loop detector, which has limited management and operation functions, but can also record the sequential conditions before and after a traffic accident. Thus, it is possible to analyze its mechanisms objectively using this data. In this study, the researchers developed a reliable video image based accident detection system with a high detection rate and low error rates. The proposed accident detection algorithm in this study provides the preliminary judgment of potential accident by detecting stopped objects using the Gaussian Mixture Model. Afterwards, it measures the traces of vehicles, the speed variance, and the occupancy per detecting area to propose an algorithm that makes the final accident decision. The proposed algorithm performs accident detection by extracting the stopped objects based on the video image, the trajectory movement of the trailing vehicle, and the variance of speed and traffic volume in the detection area. Thus, it can minimize false detections and maximize the detection rate, making it possible to accurately interpret an accident site and the circumstances surrounding it. Moreover, it is advantageous that the detection rate does not decline under bad weather conditions such as cloudy, rainy, foggy, or snowy. Source

Yoon S.-H.,Semyung University | Min J.,Sangji Youngseo College
Journal of Information Processing Systems | Year: 2013

The most important things for a forest fire detection system are the exact extraction of the smoke from image and being able to clearly distinguish the smoke from those with similar qualities, such as clouds and fog. This research presents an intelligent forest fire detection algorithm via image processing by using the Gaussian Mixture model (GMM), which can be applied to detect smoke at the earliest time possible in a forest. GMMs are usually addressed by making the model adaptive so that its parameters can track changing illuminations and by making the model more complex so that it can represent multimodal backgrounds more accurately for smoke plume segmentation in the forest. Also, in this paper, we suggest a way to classify the smoke plumes via a feature extraction using HSL(Hue, Saturation and Lightness or Luminanace) color space analysis. © 2013 KIPS. Source

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