• Title/Summary/Keyword: MADD

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TRAIL Suppresses Human Breast Cancer Cell Migration via MADD/CXCR7

  • Wang, Rui;Li, Jin-Cheng
    • Asian Pacific Journal of Cancer Prevention
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    • v.16 no.7
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    • pp.2751-2756
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    • 2015
  • Background: Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) can specifically induce apoptosis limited to various cancer cells, so this reagent is considered a promising medicine for cancer therapy. TRAIL also exerts effects on non-apoptotic signals, relevant to processes such as metastasis, autophagy and proliferation in cancer cells. However, the mechanisms of TRAIL-regulated non-apoptotic signals are unclear. The purpose of this study was to investigate MADD/CXCR7 effects in TRAIL-mediated breast cancer cell migration. Materials and Methods: The ability of MADD/CXCR7 to regulate MVP signaling in TRAIL-mediated breast cancer cells migration was evaluated by transwell migration assay, quantitative RT-PCR, Western blotting and knock down experiments. Results: In this study, we found that treatment with TRAIL resulted in induced expression levels of MADD and CXCR7 in breast cancer cells. Knock down of MADD followed by treatment with TRAIL resulted in increased cell migration compared to either treatment alone. Similarly, through overexpression and knockdown experiments, we demonstrated that CXCR7 also positively regulated TRAIL-inhibited migration. Surprisingly, knock down of MADD lead to inhibition of TRAIL-induced CXCR7 mRNA and protein expression and overexpression of CXCR7 lead to the reduction of MADD expression, indicating that MADD is an upstream regulatory factor of TRAIL-triggered CXCR7 production and a negative feedback mechanism between MADD and CXCR7. Furthermore, we showed that CXCR7 is involved in MADD-inhibited migration in breast cancer cells. Conclusions: Our work defined a novel signaling pathway implicated in the control of breast cancer migration.

An Efficient Contact Angle Computation using MADD Edge Detection (적응성 방향 미분의 에지 검출에 의한 효율적인 접촉각 연산)

  • Yang, Myung-Sup;Lee, Jong-Gu;Kim, Eun-Mi;Pahk, Cherl-Soo
    • Convergence Security Journal
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    • v.8 no.4
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    • pp.127-134
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    • 2008
  • In this paper, we try to improve the accuracy of automatic measurement for analysis equipment by detecting efficiently the edge of a waterdrop with transparency. In order to detect the edge of a waterdrop with transparency, we use an edge detecting technique, MADD (Modified Adaptive Directional Derivative), which can identify the ramp edges with various widths as the perfectly sharp edges and respond effectively regardless of enlarging or reducing the image. The proposed edge detecting technique by means of perfect sharpening of ramp edges employs the modified adaptive directional derivatives instead of the usual local differential operators in order to detect the edges of image. The modified adaptive directional derivatives are defined by introducing the perfect sharpening map into the adaptive directional derivatives. Finally we apply the proposed method to contact angle arithmetic and show the effiency and validity of the proposed method.

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An Edge Detector by Using Perfect Sharpening of Ramps (램프의 완전 선명화를 이용한 에지 검출기)

  • Lee, Jong-Gu;Yoo, Cheol-Jung;Chang, Ok-Bae
    • Journal of KIISE:Software and Applications
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    • v.34 no.11
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    • pp.961-970
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    • 2007
  • Since the usual conventional edge detectors employ the local differential derivatives, the detected edges are not uniform in their widths or some edges are missed out of the detection on magnified images. We employ a mapping from the exactly monotonic intensity distributions of ramp edges to the simple step functions of intensity, which is referred to as perfect sharpening map of ramp edges. This map is based on the non-local feature of intensity distribution and used to introduce a modified differentiation, in terms of which we can construct an efficient edge detector adaptive to the variation of edge width. By adopting the operator MADD in this paper, we developed an edge detector that works stably against the magnification of image or the variation of edge width. It is shown by comparing to the conventional algorithms that the proposed one is very excellent.