Ixodes scapularis transmits the agent of human granulocytic anaplasmosis, among other pathogens. The mechanisms used by the tick to control Anaplasma phagocytophilum are not known. We demonstrate that the I. scapularis Janus kinase (JAK)-signaling transducer activator of transcription (STAT) pathway plays a critical role in A. phagocytophilum infection of ticks. The A. phagocytophilum burden increases in salivary glands and hemolymph when the JAK-STAT pathway is suppressed by RNA interference. The JAK-STAT pathway exerts its anti-Anaplasma activity presumably through STAT-regulated effectors. A salivary gland gene family encoding 5.3-kDa antimicrobial peptides is highly induced upon A. phagocytophilum infection of tick salivary glands. Gene expression and electrophoretic mobility shift assays showed that the 5.3-kDa antimicrobial peptide-encoding genes are regulated by tick STAT. Silencing of these genes increased A. phagocytophilum infection of tick salivary glands and transmission to mammalian host. These data suggest that the JAK-STAT signaling pathway plays a key role in controlling A. phagocytophilum infection in ticks by regulating the expression of antimicrobial peptides.
Additional information:Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. We also propose a modification of Cho et al.'s watermarking algorithms with the watermark embedded by changing the histogram of the radial coordinates of the vertices. Rather than targeting a continuous statistics such as the mean or variance of the values in a bin, the proposed watermarking modifies a discrete statistic, which here is the height of the histogram bin, to achieve watermark embedding. Experimental results demonstrate that the modified algorithm offers not only better resistance against the steganalytic attack we developed, but also an improved robustness/capacity trade-off.
Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. We propose a steganalytic algorithm for triangle meshes, based on the supervised training of a classifier by discriminative feature vectors. After a normalization step, the triangle mesh is calibrated by one step of Laplacian smoothing and then a feature vector is computed, encoding geometric information corresponding to vertices, edges and faces. For a given steganographic or watermarking algorithm, we create a training set containing unmarked meshes and meshes marked by that algorithm, and train a classifier using Quadratic Discriminant Analysis. The performance of the proposed method was evaluated on six well-known watermarking/steganographic schemes with satisfactory accuracy rates.
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