537 resultados para Dermatite nodular ulcerativa


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Mast cell tumor manifests as a localized proliferation of mast cells in the skin, or less frequently as a systemic disorder, which may be accompanied by the presence of neoplastic mast cells in the peripheral blood (mastocythemia). In some cases, the neoplastic circulating mast cells originate in the bone marrow, designated as mast cell leukemia, rarely observed in dogs, or the cells may arise from visceral mast cell tumors, characterizing systemic mastocytosis. The aim of this report was to describe a case of a six-year-old female German shepherd dog presenting with history of anorexia, hematemesis and diarrhea. The blood work revealed intense mastocythemia (43%), with degranulated mast cells, and anisocytosis. At necropsy, white nodular lesions in the thymic region and an infiltrative mass in mesenteric and abdominal lymph nodes were observed. Those lymph nodes were enlarged and off-white. Histopathological examination revealed neoplastic mast cells in the liver, spleen, lymph nodes, kidneys, lungs, gastric and enteric mucosae, and adrenal glands. The clinical, hematological and histopathological findings were compatible with mastocythemia, associated with a moderately differentiated visceral mast cell tumor.

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The automatic characterization of particles in metallographic images has been paramount, mainly because of the importance of quantifying such microstructures in order to assess the mechanical properties of materials common used in industry. This automated characterization may avoid problems related with fatigue and possible measurement errors. In this paper, computer techniques are used and assessed towards the accomplishment of this crucial industrial goal in an efficient and robust manner. Hence, the use of the most actively pursued machine learning classification techniques. In particularity, Support Vector Machine, Bayesian and Optimum-Path Forest based classifiers, and also the Otsu's method, which is commonly used in computer imaging to binarize automatically simply images and used here to demonstrated the need for more complex methods, are evaluated in the characterization of graphite particles in metallographic images. The statistical based analysis performed confirmed that these computer techniques are efficient solutions to accomplish the aimed characterization. Additionally, the Optimum-Path Forest based classifier demonstrated an overall superior performance, both in terms of accuracy and speed. © 2012 Elsevier Ltd. All rights reserved.

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Pós-graduação em Medicina Veterinária - FMVZ

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

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Pós-graduação em Ciências Biológicas (Farmacologia) - IBB

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Pós-graduação em Ciências Biológicas (Farmacologia) - IBB

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Ciência Animal - FMVA

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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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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)