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Shiratsuchi, Akiko,Shimizu, Kaori,Watanabe, Ikuko,Hashimoto, Yumi,Kurokawa, Kenji,Razanajatovo, Iony M.,Park, Keun H.,Park, Hae K.,Lee, Bok L.,Sekimizu, Kazuhisa,Nakanishi, Yoshinobu Blackwell Publishing Ltd 2010 Immunology Vol.129 No.2
<P>Summary</P><P>We previously reported that <I>Staphylococcus aureus</I> avoids killing within macrophages by exploiting the action of Toll-like receptor 2 (TLR2), which leads to the c-Jun N-terminal kinase (JNK)-mediated inhibition of superoxide production. To search for bacterial components responsible for this event, a series of <I>S. aureus</I> mutants, in which the synthesis of the cell wall was interrupted, were screened for the level of JNK activation in macrophages. In addition to a mutant lacking the lipoproteins that have been suggested to act as a TLR2 ligand, two mutant strains were found to activate the phosphorylation of JNK to a lesser extent than the parental strain, and this defect was recovered by acquisition of the corresponding wild-type genes. Macrophages that had phagocytosed the mutant strains produced more superoxide than those engulfing the parental strain, and the mutant bacteria were more efficiently killed in macrophages than the parent. The genes mutated, <I>dltA</I> and <I>tagO</I>, encoded proteins involved in the synthesis of <SMALL>D</SMALL>-alanylated wall teichoic acid. Unlike a cell wall fraction rich in lipoproteins, <SMALL>D</SMALL>-alanine-bound wall teichoic acid purified from the parent strain by itself did not activate JNK phosphorylation in macrophages. These results suggest that the <SMALL>D</SMALL>-alanylated wall teichoic acid of <I>S. aureus</I> modulates the cell wall milieu for lipoproteins so that they effectively serve as a ligand for TLR2.</P>
Tan Dat Trinh,Pham The Bao,Le Nhi Lam Thuy,Ikuko Shimizu,김진영,Pham The Bao 한국전기전자학회 2019 전기전자학회논문지 Vol.23 No.2
In this study, a novel hierarchical approach is investigated to extract coronary vessel from X-ray angiogram. First, we propose to combine Decimation-free Directional Filter Bank (DDFB) and Homographic Filtering (HF)in order to enhance X-ray coronary angiographic image for segmentation purposes. Because the blood vesselensures that blood flows in only one direction on vessel branch, the DDFB filter is suitable to be used toenhance the vessels at different orientations and radius. In the combination with HF filter, our method cansimultaneously normalize the brightness across the image and increases contrast. Next, a coarse-to-finestrategy for iterative segmentation based on Otsu algorithm is applied to extract the main coronary vessels indifferent sizes. Furthermore, we also propose a new approach to segment very small vessels. Specifically,based on information of the main extracted vessels, we introduce a new method to extract junctions on thevascular tree and level of nodes on the tree. Then, the window based segmentation is applied to locate andextract the small vessels. Experimental results on our coronary X-ray angiography dataset demonstrate thatthe proposed approach can outperform standard method and attain the accuracy of 71.34%.
Trinh, Tan Dat,Tran, Thieu Bao,Thuy, Le Nhi Lam,Shimizu, Ikuko,Kim, Jin Young,Bao, Pham The Institute of Korean Electrical and Electronics Eng 2019 전기전자학회논문지 Vol.23 No.2
In this study, a novel hierarchical approach is investigated to extract coronary vessel from X-ray angiogram. First, we propose to combine Decimation-free Directional Filter Bank (DDFB) and Homographic Filtering (HF) in order to enhance X-ray coronary angiographic image for segmentation purposes. Because the blood vessel ensures that blood flows in only one direction on vessel branch, the DDFB filter is suitable to be used to enhance the vessels at different orientations and radius. In the combination with HF filter, our method can simultaneously normalize the brightness across the image and increases contrast. Next, a coarse-to-fine strategy for iterative segmentation based on Otsu algorithm is applied to extract the main coronary vessels in different sizes. Furthermore, we also propose a new approach to segment very small vessels. Specifically, based on information of the main extracted vessels, we introduce a new method to extract junctions on the vascular tree and level of nodes on the tree. Then, the window based segmentation is applied to locate and extract the small vessels. Experimental results on our coronary X-ray angiography dataset demonstrate that the proposed approach can outperform standard method and attain the accuracy of 71.34%.