Avaliação retrospectiva de sistema de pontuação pelo Ministério da Saúde do Brasil, no diagnóstico de tuberculose pulmonar na criança: estudo controle de casos

Based on a retrospective case-control study we evaluated the score system adopted by the Ministry of Health of Brazil (Ministério da Saúde - MS), to diagnose pulmonary tuberculosis (PTB) in childhood. This system is independent of bacteriological or histopathological data to define a very likely (>; or = 40 points), possible (30-35 points) or unlikely (;10mm (OR = 8.23). The best cut-off point to the diagnosis of PTB was 30 points, where the score system was more accurate, with sensitivity of 88.9% and specificity of 86.5%.Avaliou-se o sistema de pontuação adotado pelo Ministério da Saúde do Brasil para o diagnóstico de tuberculose pulmonar (TP) na infância através de estudo caso-controle retrospectivo. Tal sistema independe de dados bacteriológicos ou histopatológicos e define o diagnóstico de tuberculose como muito provável (>; ou = 40 pontos); possível (30 a 35 pontos) ou pouco provável (; 10 mm (OR = 8,23). O melhor ponto de corte para o diagnóstico de TP foi 30 pontos, no qual houve maior acurácia do sistema, com sensibilidade de 99,9% e especificidade de 86,5%

Animal production in different integrated crop-livestock systems in a lowland of Southern Brazil.

To achieve higher lowland use efficiency in Brazilian Southern, a region commonly used for rice production, the livestock activity during the winter period (in succession to summer crops) is a sustainable alternative..

Performance of winter pasture species in different integrated crop-livestock systems in lowlands of Southern Brazil.

The introduction of winter forage species in succession to rice cropping in lowlands of Southern Brazil is an option for the productive system diversification..

Aeromonas spp. isoladas de ostras (Crassostrea rhizophorea) coletadas em um criadouro natural, Ceará, Brazil

Between April and October 2002, thirty fortnightly collections of oysters (Crassostrea rhizophorea) from a natural oyster bed at the Cocó River estuary in the Sabiaguaba region (Fortaleza, Ceará, Brazil) were carried out, aiming to isolate Aeromonas spp. strains. Oyster samples were submitted to the direct plating (DP) and the presence/absence (P/A) methods. Aeromonas were identified in 15 (50%) samples analyzed by the DP method and in 13 (43%) analyzed by the P/A method. A. caviae, A. eucrenophila, A. media, A. sobria, A. trota, A. veronii bv. sobria, A. veronii bv. veronii and Aeromonas sp. were isolated. The predominant species was A. veronii (both biovars), which was identified in 13 (43%) samples, followed by A. media in 11 (37%) and A. caviae in seven (23%). From the 59 strains identified, 28 (48%) presented resistance to at least one of the eight antibiotics tested.Foram realizadas 30 coletas quinzenais, entre abril e outubro de 2002, de ostras (Crassostrea rhizophorea) de um criadouro natural, no estuário do rio Cocó (Fortaleza/Ceará/Brasil), objetivando-se isolar cepas de Aeromonas spp. As amostras de ostras foram submetidas aos métodos de plaqueamento direto (PD) e presença/ausência (P/A). Foram identificadas Aeromonas em 15 (50%) amostras analisadas pelo método PD e em 13 (43%) pelo método P/A. Foram isoladas: A. caviae, A. eucrenophila, A. media, A. sobria, A. trota, A. veronii bv. sobria, A. veronii bv. veronii e Aeromonas sp. A espécie predominate foi A. veronii (ambos biovars), identificada em 13 (43%) amostras, seguida de A. media em 11 (37%) e A. caviae em 7 (23%). Das 59 cepas identificadas, 28 (48%) apresentaram resistência a pelo menos um, dos oitos antibióticos testados

Avaliação de dois cultivares de azevém sob diferentes épocas de plantio ao longo do período de utilização.

JAI

Implementation of different integrated crop-livestock systems in lowlands of Southern Brazil: an animal production approach.

The introduction of integrated crop-livestock systems (ICLS) is an alternative to rice monoculture in lowlands of Southern Brazil..

Artificial neural networks compared with Bayesian generalized linear regression for leaf rust resistance prediction in Arabica coffee.

The objective of this work was to evaluate the use of artificial neural networks in comparison with Bayesian generalized linear regression to predict leaf rust resistance in Arabica coffee (Coffea arabica). This study used 245 individuals of a F2 population derived from the self-fertilization of the F1 H511-1 hybrid, resulting from a crossing between the susceptible cultivar Catuaí Amarelo IAC 64 (UFV 2148-57) and the resistant parent Híbrido de Timor (UFV 443-03). The 245 individuals were genotyped with 137 markers. Artificial neural networks and Bayesian generalized linear regression analyses were performed. The artificial neural networks were able to identify four important markers belonging to linkage groups that have been recently mapped, while the Bayesian generalized model identified only two markers belonging to these groups. Lower prediction error rates (1.60%) were observed for predicting leaf rust resistance in Arabica coffee when artificial neural networks were used instead of Bayesian generalized linear regression (2.4%). The results showed that artificial neural networks are a promising approach for predicting leaf rust resistance in Arabica coffee.Título em português: Redes neurais artificiais comparadas com modelos lineares generalizados sob o enfoque bayesiano para predição de resistência à ferrugem em café arábica