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Using flow channel, we report that the application of a laminar shear stress induced a transient increase of tissue factor (TF) procoagulant activity in human umbilical vein endothelial cells (HUVEC), which was accompanied by a rapid and transient induction of the TF mRNA in the HUVEC. Functional analysis of the 2.2 kb TF 5 Ј promoter indicated that a GC-rich region containing three copies each of the EGR-1 and Sp1 sites was required for induction. Mutation of the Sp1 sites, but not the EGR-1 sites, attenuated the response of TF promoter to shear stress. Thus, Sp1 is a newly defined shear stress responsive element. Electrophoretic mobility shift assays showed there was no increase in binding of nuclear extracts from sheared cells to an Sp1 consensus site. In contrast, immunoblotting of these nuclear extracts with antibody against transcription factor Sp1 demonstrated that shear stress increased the phosphorylation of Sp1. We also showed that shear stress, like the phosphatase inhibitor okadaic acid, increased the transcriptional activity of Sp1. These findings suggest that the shear stress induction of TF gene expression is mediated through an increased Sp1 transcriptional activity with a concomitant hyperphosphorylation of Sp1. ( J. Clin. Invest. 1997. 99:737-744.)

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In this paper, we propose a color-based segmentation method that uses the K-means clustering technique to track tumor objects in magnetic resonance (MR) brain images. The key concept in this color-based segmentation algorithm with K-means is to convert a given gray-level MR image into a color space image and then separate the position of tumor objects from other items of an MR image by using Kmeansclustering and histogram-clustering. Experiments demonstrate that the method can successfully achieve segmentation for MR brain images to help pathologists distinguish exactly lesion size and region.

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