17,252 research outputs found

    A Novel Antigen Sensitive to Calcium Chelation That is Associated with the Tip Links and Kinocilial Links of Sensory Hair Bundles

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    Tip links are extracellular, cell-surface-associated filaments of unknown molecular composition that are thought to gate the mechanotransducer channel of the sensory hair cell. They disappear from the hair bundle in response to calcium chelation and lanthanum treatment and resist degradation by the protease subtilisin. A monoclonal antibody derived from a hybridoma screen identified a novel antigen associated with tip links, the tip-link antigen. The tip-link antigen is also associated with kinocilial links, subtilisin-resistant filaments that are sensitive to calcium chelation and connect the kinocilium to the tallest stereocilia of the hair bundle. Furthermore, the tip-link antigen is expressed in the retina, where it is associated with the ciliary calyx, a ring of microvilli that surrounds the outer segment of the photoreceptor. The tip-link antigen rapidly disappears from the surface of the hair bundle in response to calcium chelation. It is also subtilisin resistant, relative to the ankle-link antigen, an antigen associated with another type of hair bundle link. The tip-link antigen is lanthanum sensitive and, like tip links, reappears on the surface of the hair bundle after calcium chelation. The monoclonal antibody to the tip-link antigen immunoprecipitates two concanavalin A-reactive polypeptides with apparent molecular masses of 200 and 250 kDa from detergent extracts of the retina. These results provide the first identification of a cell surface antigen associated with tip links, indicate that tip links share properties in common with kinocilial links, and reveal a second epitope that, along with the ankle-link antigen, is common to both sensory hair bundles and the ciliary calyx of photoreceptors

    LS2W: Implementing the Locally Stationary 2D Wavelet Process Approach in R

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    Locally stationary process representations have recently been proposed and applied to both time series and image analysis applications. This article describes an implementation of the locally stationary two-dimensional wavelet process approach in R. This package permits construction of estimates of spatially localized spectra and localized autocovariance which can be used to characterize structure within images.
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