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The gonyaulacoid dinoflagellate Alexandrium taylori Balech is reported for the first time from Italian waters. In July 1997, nonmotile stages of this species, both temporary and sexual resting cysts, were found in surface Ionian coastal waters (Mediterranean Sea) producing localized brownish‐yellow patches. Clonal cultures were established, and the life history of A. taylori was studied in the laboratory. Asexual reproduction took place during a motile phase and produced two daughter cells remaining temporarily attached in pairs. This species exhibited isogamy. Small gametes were produced from vegetative cells through the release of a division cyst and multiple fission of the protoplast. Isogametes from the same clonal strain fused and underwent sexual reproduction, forming planozygotes that subsequently developed storage bodies and dark pigmentation. The maturation of the planozygote into hypnozygote also involved an increase in size and final shedding of flagella and theca. Hypnozygotes germinated within 15 days of their formation, and a naked planomeiocyte emerged from the archeopyle to undergo successive divisions and reestablish a haploid motile population.

Background: Mutations leading to changes in properties, regulation, or expression of connexin-made channels have been implicated in 28 distinct human hereditary diseases. Eight of these result from variants of connexin 26 (Cx26), a protein critically involved in cell-cell signaling in the inner ear and skin. Lack of non-toxic drugs with defined mechanisms of action poses a serious obstacle to therapeutic interventions for diseases caused by mutant connexins. In particular, molecules that specifically modulate connexin hemichannel function without affecting gap junction channels are considered of primary importance for the study of connexin hemichannel role in physiological as well as pathological conditions. Monoclonal antibodies developed in the last three decades have become the most important class of therapeutic biologicals. Recombinant methods permit rapid selection and improvement of monoclonal antibodies from libraries with large diversity.Methods: By screening a combinatorial library of human single-chain fragment variable (scFv) antibodies expressed in phage, we identified a candidate that binds an extracellular epitope of Cx26. We characterized antibody action using a variety of biochemical and biophysical assays in HeLa cells, organotypic cultures of mouse cochlea and human keratinocyte-derived cells.Results: We determined that the antibody is a remarkably efficient, non-toxic, and completely reversible inhibitor of hemichannels formed by connexin 26 and does not affect direct cell-cell communication via gap junction channels. Importantly, we also demonstrate that the antibody efficiently inhibits hyperative mutant Cx26 hemichannels implicated in autosomal dominant non-syndromic hearing impairment accompanied by keratitis and hystrix-like ichthyosis-deafness (KID/HID) syndrome. We solved the crystal structure of the antibody, identified residues that are critical for binding and used molecular dynamics to uncover its mechanism of action.Conclusions: Although further studies will be necessary to validate the effect of the antibody in vivo, the methodology described here can be extended to select antibodies against hemichannels composed by other connexin isoforms and, consequently, to target other pathologies associated with hyperactive hemichannels. Our study highlights the potential of this approach and identifies connexins as therapeutic targets addressable by screening phage display libraries expressing human randomized antibodies.

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To improve the accuracy and generalization ability of hyperspectral image classification, a feature extraction method integrating principal component analysis(PCA) and local binary pattern (LBP) is developed for hyperspectral images in this paper. The PCA is employed to reduce the dimension of the spectral features of hyperspectral images. The LBP with low computational complexity is used to extract the local spatial texture features of hyperspectral images to construct multi-feature vectors. Then the gray wolf optimization(GWO) algorithm with global search capability is employed to optimize the parameters of kernel extreme learning machine(KELM) to construct an optimized KELM model, which is used to effectively realize a hyperspectral image classification (PLG-KELM) method. Finally, the Indian pines dataset, Houston dataset and Pavia University dataset and an application of WHU-Hi-LongKou dataset are selected to verify the effectiveness of the PLG-KELM. The comparison experiment results show that the PLG-KELM can obtain higher classification accuracy, and takes on better generalization ability for small samples. It provides a new idea for processing hyperspectral images.