HSV-2 gG peptide

PURPOSE. Herpes simplex virus type I (HSV-1) infection of corneal epithelial cells activates ataxia telangiectasia mutated (ATM), an apical kinase in the host DNA damage response pathway, whose activity is necessary for the progression of lytic HSV-1 infection. The purpose of this study is to investigate the mechanism of ATM activation by HSV-1 in the corneal epithelium, as well as its functional significance. METHODS. Mechanistic studies were performed in cultured human corneal epithelial cell lines (hTCEpi, HCE), as well as in esophageal (EPC2) and oral (OKF6) cell lines. Transfection-based experiments were performed in HEK293 cells. HSV-1 infection was carried out using the wild-type KOS strain, various mutant strains (tsB7, dl20, 7134, i13, n208), and bacterial artificial chromosomes (fHSV Delta pac, pM24). Inhibitors of ATM (KU-55933), protein synthesis (cycloheximide), and viral DNA replication (phosphonoacetic acid) were used. Outcomes of infection were assayed using Western blotting, qRT-PCR, immunofluorescence, and comet assay. RESULTS. This study demonstrates that HSV-1-mediated ATM activation in corneal epithelial cells relies on the viral immediate early gene product ICP4 and requires the presence of the viral genome in the host nucleus. We show that ATM activation is independent of viral genome replication, the ICP0 protein, and the presence of DNA lesions. Interestingly, ATM activity appears to be necessary at the onset of infection, but dispensable at the later stages. CONCLUSIONS. This study expands our understanding of HSV-1 virus-host interactions in the corneal epithelium and identifies potential areas of future investigation and therapeutic intervention in herpes keratitis.

Shadow often results in difficulties for subsequent image applications of multispectral satellite remote sensing images, like object recognition and change detection. With continuous improvement in both spatial and spectral resolutions of satellite remote sensing images, a more serious impact occurs on satellite remote sensing image interpretation due to the existence of shadow. Though various shadow detection methods have been developed, problems of both shadow omission and nonshadow misclassification still exist for detecting shadow well in high-resolution multispectral satellite remote sensing images. These shadow detection problems mainly include high small shadow omission and typical nonshadow misclassification (like bluish and greenish nonshadow misclassification, and large dark nonshadow misclassification). For further resolving these problems, a new shadow index is developed based on the analysis of the property difference between shadow and the corresponding nonshadow with several multispectral band components (i.e., near-infrared, red, green and blue components) and hue and intensity components in various invariant color spaces (i.e., HIS, HSV, CIELCh, YCbCr and YIQ), respectively. The shadow mask is further acquired by applying an optimal threshold determined automatically on the shadow index image. The final shadow image is further optimized with a definite morphological operation of opening and closing. The proposed algorithm is verified with many images from WorldView-3 and WorldView-2 acquired at different times and sites. The proposed algorithm performance is particularly evaluated by qualitative visual sense comparison and quantitative assessment of shadow detection results in comparative experiments with two WorldView-3 test images of Tripoli, Libya. Both the better visual sense and the higher overall accuracy (over 92% for the test image Tripoli-1 and approximately 91% for the test image Tripoli-2) of the experimental results together deliver the excellent performance and robustness of the proposed shadow detection approach for shadow detection of high-resolution multispectral satellite remote sensing images. The proposed shadow detection approach is promised to further alleviate typical shadow detection problems of high small shadow omission and typical nonshadow misclassification for high-resolution multispectral satellite remote sensing images.