154 resultados para Epidemic encephalitis.
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Background: Opportunistic infections are an increasingly common problem in hospitals, and the yeast Candida parapsilosis has emerged as an important nosocomial pathogen, especially in neonatal intensive care units (NICUs) where it has been responsible for outbreak cases. Risk factors for C. parapsilosis infection in neonates include prematurity, very low birth weight, prolonged hospitalization, indwelling central venous catheters, hyperalimentation, intravenous fatty emulsions and broad spectrum antibiotic therapy. Molecular methods are widely used to elucidate these hospital outbreaks, establishing genetic variations among strains of yeast. Aims: The aim of this study was to detect an outbreak of C. parapsilosis in an NICU at the Hospital das Clinicas , Faculty of Medicine of Botucatu, a tertiary hospital located in São Paulo, Brazil, using the molecular genotyping by the microsatellite markers analysis. Methods: A total of 11 cases of fungemia caused by C. parapsilosis were identified during a period of 43 days in the NICU. To confirm the outbreak all strains were molecularly typed using the technique of microsatellites. Results: Out of the 11 yeast samples studied, nine showed the same genotypic profile using the technique of microsatellites. Conclusions: Our study shows that the technique of microsatellites can be useful for these purposes. In conclusion, we detected the presence of an outbreak of C. parapsilosis in the NICU of the hospital analyzed, emphasizing the importance of using molecular tools, for the early detection of hospital outbreaks, and for the introduction of effective preventive measures, especially in NICUs. © 2012 Revista Iberoamericana de Micología.
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Based on the literature data from HT-29 cell monolayers, we develop a model for its growth, analogous to an epidemic model, mixing local and global interactions. First, we propose and solve a deterministic equation for the progress of these colonies. Thus, we add a stochastic (local) interaction and simulate the evolution of an Eden-like aggregate by using dynamical Monte Carlo methods. The growth curves of both deterministic and stochastic models are in excellent agreement with the experimental observations. The waiting times distributions, generated via our stochastic model, allowed us to analyze the role of mesoscopic events. We obtain log-normal distributions in the initial stages of the growth and Gaussians at long times. We interpret these outcomes in the light of cellular division events: in the early stages, the phenomena are dependent each other in a multiplicative geometric-based process, and they are independent at long times. We conclude that the main ingredients for a good minimalist model of tumor growth, at mesoscopic level, are intrinsic cooperative mechanisms and competitive search for space. © 2013 Elsevier Ltd.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Alimentos e Nutrição - FCFAR
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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 Design - FAAC
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Pós-graduação em Geografia - FCT
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Pós-graduação em Educação - FFC
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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)
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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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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)