3,589 research outputs found

    Automatic Aortic Root Segmentation with Shape Constraints and Mesh Regularisation

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    Analysis of face and segment level descriptors for robust 3D co-segmentation

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    Analysis of face and segment level descriptors for robust 3D co-segmentation

    MicroRNA-762 is upregulated in human corneal epithelial cells in response to tear fluid and Pseudomonas aeruginosa antigens and negatively regulates the expression of host defense genes encoding RNase7 and ST2.

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    Mucosal surfaces regulate defenses against infection and excessive inflammation. We previously showed that human tears upregulated epithelial expression of genes encoding RNase7 and ST2, which inhibited Pseudomonas aeruginosa invasion of human corneal epithelial cells. Here, microRNA microarrays were used to show that a combination of tear fluid exposure (16 h) then P. aeruginosa antigens (3 h) upregulated miR-762 and miR-1207, and down-regulated miR-92 and let-7b (all > 2-fold) in human corneal epithelial cells compared to P. aeruginosa antigens alone. RT-PCR confirmed miR-762 upregulation ∼ 3-fold in tear-antigen exposed cells. Without tears or antigens, an antagomir reduced miR-762 expression relative to scrambled controls by ∼50%, increased expression of genes encoding RNase7 (∼80 %), ST2 (∼58%) and Rab5a (∼75%), without affecting P. aeruginosa internalization. However, P. aeruginosa invasion was increased > 3-fold by a miR-762 mimic which reduced RNase7 and ST2 gene expression. Tear fluid alone also induced miR-762 expression ∼ 4-fold, which was reduced by the miR-762 antagomir. Combination of tear fluid and miR-762 antagomir increased RNase7 and ST2 gene expression. These data show that mucosal fluids, such as tears, can modulate epithelial microRNA expression to regulate innate defense genes, and that miR-762 negatively regulates RNase7, ST2 and Rab5a genes. Since RNase7 and ST2 inhibit P. aeruginosa internalization, and are upregulated by tear fluid, other tear-induced mechanisms must counteract inhibitory effects of miR-762 to regulate resistance to bacteria. These data also suggest a complex relationship between tear induction of miR-762, its modulation of innate defense genes, and P. aeruginosa internalization

    Scene Context-Aware Salient Object Detection

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    Consistent segment-wise matching with multi-layer graphs (CGVC2018 Poster)

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    An Efficient Approach to Correspondences between Multiple Non-Rigid Parts

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    Identifying multiple deformable parts on meshes and establishing dense correspondences between them are tasks of fundamental importance to computer graphics, with applications to e.g. geometric edit propagation and texture transfer. Much research has considered establishing correspondences between non-rigid surfaces, but little work can both identify similar multiple deformable parts and handle partial shape correspondences. This paper addresses two related problems, treating them as a whole: (i) identifying similar deformable parts on a mesh, related by a non-rigid transformation to a given query part, and (ii) establishing dense point correspondences automatically between such parts. We show that simple and efficient techniques can be developed if we make the assumption that these parts locally undergo isometric deformation. Our insight is that similar deformable parts are suggested by large clusters of point correspondences that are isometrically consistent. Once such parts are identified, dense point correspondences can be obtained by an iterative propagation process. Our techniques are applicable to models with arbitrary topology. Various examples demonstrate the effectiveness of our techniques
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