1000 resultados para SAO SEBASTIAO CHANNEL
Resumo:
We have recently isolated a cDNA (SKV1.1) encoding a Shakei-related K+ channel from the human parasitic trematode Schistosoma mansoni. In order to better understand the functions of SKv1.1 protein, the distribution of SKv1.1 protein in adult S. mansoni was analyzed by immunohistochemistry using a region-specific antibody. SKV1.1 proteins were widely expressed in the nervous and muscular systems. The strongest immunoreactivity (IR) was observed in the nervous system of both male and female. In the nervous system, IR for SKv1.1 proteins was localized in cell bodies and nerve fibers of the anterior ganglia, the central commissure, and the main nerve cords. IR was also observed in the dorsal and the ventral peripheral nerve nets, fine nerve fibers entering into a variety of structures such as the dorsal tubercles, longitudinal and ventral muscle fibers, and oral and ventral suckers. In the muscular system, SKv1.1 proteins were localized to the longitudinal, circular, and ventral muscle fibers of male as well as in isolated muscle fibers where native A-type K+ currents were measured. Moderate IR was also seen in a large number of cell bodies in the parenchyma. These results indicate that SKv1.1 protein may play an important role in the regulation of the excitability of neurons and muscle cells of S. mansoni. (C) 1995 Academic Press, Inc.
Resumo:
This study provides a general diversity analysis for joint complex diversity coding (CDC) and channel coding-based space-time-frequency codeing is provided. The mapping designs from channel coding to CDC are crucial for efficient exploitation of the diversity potential. This study provides and proves a sufficient condition of full diversity construction with joint three-dimensional CDC and channel coding, bit-interleaved coded complex diversity coding and symbol-interleaved coded complex diversity coding. Both non-iterative and iterative detections of joint channel code and CDC transmission are investigated. The proposed minimum mean-square error-based iterative soft decoding achieves the performance of the soft sphere decoding with reduced complexity.