162 resultados para Chrysophyceae cysts


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Two experiments were performed using the aromatase inhibitor (AI) letrozole (100mg/kg) to promote sex change, from female-to-male, in protogynous dusky grouper. One experiment was performed during the breeding season (spring) and the other at the end of the breeding season (summer). During the spring, AI promoted sex change after 9weeks and the sperm produced was able to fertilize grouper oocytes. During the summer, the sex change was incomplete; intersex individuals were present and sperm was not released by any of the animals. Sex changed gonads had a lamellar architecture; cysts of spermatocytes and spermatozoa in the lumen of the germinal compartment. In the spring, after 4weeks, 11ketotestosterone (11KT) levels were higher in the AI than in control fish, and after 9weeks, coincident with semen release, testosterone levels increased in the AI group, while 11KT returned to the initial levels. Estradiol (E2) levels remained unchanged during the experimental period. Instead of decreasing throughout the period, as in control group, 17 α-OH progesterone levels did not change in the AI-treated fish, resulting in higher values after 9weeks when compared with control fish. fshβ and lhβ gene expression in the AI animals were lower compared with control fish after 9weeks. The use of AI was effective to obtain functional males during the breeding season. The increase in androgens, modulated by gonadotropins, triggered the sex change, enabling the development of male germ cells, whereas a decrease in E2 levels was not required to change sex in dusky grouper. © 2013 Elsevier Inc.

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Human intestinal parasites constitute a problem in most tropical countries, causing death or physical and mental disorders. Their diagnosis usually relies on the visual analysis of microscopy images, with error rates that may range from moderate to high. The problem has been addressed via computational image analysis, but only for a few species and images free of fecal impurities. In routine, fecal impurities are a real challenge for automatic image analysis. We have circumvented this problem by a method that can segment and classify, from bright field microscopy images with fecal impurities, the 15 most common species of protozoan cysts, helminth eggs, and larvae in Brazil. Our approach exploits ellipse matching and image foresting transform for image segmentation, multiple object descriptors and their optimum combination by genetic programming for object representation, and the optimum-path forest classifier for object recognition. The results indicate that our method is a promising approach toward the fully automation of the enteroparasitosis diagnosis. © 2012 IEEE.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Pós-graduação em Ciência Animal - FMVA

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Pós-graduação em Medicina Veterinária - FMVZ

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Biociências e Biotecnologia Aplicadas à Farmácia - FCFAR