948 resultados para Saccharomyces


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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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Produção de glicose e frutose por invertase de Saccharomyces cerevisiae imobilizada em suporte MANAE-Agarose Invertase de Saccharomyces cerevisiaefoi imobilizada em agarose ativada com diferentes grupos (glioxil, MANAE ou glutaraldeído) e suportes epóxidos comerciais (Eupergit e Sepabeads). Derivados de invertase ativos e estabilizados foram produzidos pela adsorção da enzima em suportes MANAE-agarose, MANAE-agarose tratado com glutaraldeído e glutaraldeído-agarose. Em pH 5,0 estes derivados retiveram total atividade até 24h a 40 ºC e 50 ºC. Quando os ensaios foram a 40 °C e 50 °C com o pH alterado para 7,0, o derivado invertase-MANAE-agarose tratado com glutaraldeído apresentou 80% da atividade inicial. As atividades recuperadas dos derivados foram 73,5%, 44,4% e 36,8%, respectivamente para MANAE, MANAE tratado com glutaraldeído e glutaraldeído. Essas três preparações foram empregadas com sucesso em 3 ciclos de hidrólise da sacarose para produzir glicose e frutose.

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The objective of this work was to evaluate the inter-relationship between dietary supplementation with Saccharomyces cerevisiae cell wall and vaccination against Streptococcus agalactiae, and its effect on the productive performance and hematological variables of Nile tilapia (Oreochromis niloticus). Eighty-four Nile tilapia were distributed in 12 fiber boxes (n=7), in a 2x2x3 factorial arrangement, corresponding to two levels of supplementation with yeast cell wall, two types of inoculation, and three evaluation times. Fish were fed during 77 days. Vaccination of fish was done 60 days after feeding started. Fifteen days after vaccination, all fish were subjected to challenge with live strain of S. agalactiae, and 6, 24, and 48 hours after the challenge, blood was collected from the caudal vein for evaluations. Fish fed with supplemented diets show greater weight gain and specific growth rate, and the interaction between the diet and vaccination effects results in higher hematocrit, hemoglobin, and leukocyte rates.

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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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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Biological processes are complex and possess emergent properties that can not be explained or predict by reductionism methods. To overcome the limitations of reductionism, researchers have been used a group of methods known as systems biology, a new interdisciplinary eld of study aiming to understand the non-linear interactions among components embedded in biological processes. These interactions can be represented by a mathematical object called graph or network, where the elements are represented by nodes and the interactions by edges that link pair of nodes. The networks can be classi- ed according to their topologies: if node degrees follow a Poisson distribution in a given network, i.e. most nodes have approximately the same number of links, this is a random network; if node degrees follow a power-law distribution in a given network, i.e. small number of high-degree nodes and high number of low-degree nodes, this is a scale-free network. Moreover, networks can be classi ed as hierarchical or non-hierarchical. In this study, we analised Escherichia coli and Saccharomyces cerevisiae integrated molecular networks, which have protein-protein interaction, metabolic and transcriptional regulation interactions. By using computational methods, such as MathematicaR , and data collected from public databases, we calculated four topological parameters: the degree distribution P(k), the clustering coe cient C(k), the closeness centrality CC(k) and the betweenness centrality CB(k). P(k) is a function that calculates the total number of nodes with k degree connection and is used to classify the network as random or scale-free. C(k) shows if a network is hierarchical, i.e. if the clusterization coe cient depends on node degree. CC(k) is an indicator of how much a node it is in the lesse way among others some nodes of the network and the CB(k) is a pointer of how a particular node is among several ...(Complete abstract click electronic access below)

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A metilação de ilhas CpG em regiões regulatórias de vários genes tem sido descrita como um processo importante no silenciamento de genes supressores de tumor e diretamente envolvida no processo de carcinogênese de uma série de tumores. O estudo desses genes afetados pela metilação em tumores visa identificar possíveis marcadores moleculares para o diagnóstico, prognóstico e tratamento de tumores, além de possibilitar a descoberta de fatores importantes no processo biológico do câncer. Os genes MX1 e ADAM23 foram identificados como diferencialmente metilados em linhagens celulares provenientes de carcinoma de cabeça e pescoço. Neste sentido, ao estudar o perfil diferencial de metilação de genes em carcinomas de células escamosas de cabeça e pescoço, o gene MX1 foi identificado como diferencialmente expresso. Dessa forma, para elucidar a função destes genes no controle da carcinogênese, o presente estudo buscou identificar ligantes celulares das proteínas MX1 e ADAM23 por meio de rastreamentos de duplo-híbrido, usando bibliotecas de cDNA de cérebro fetal humano. Os rastreamentos com a proteína ADAM23 não geraram resultados positivos por isso não são aqui discutidos. Foi realizado rastreamento com a proteína MX1, que resultou em aproximadamente 1,0x106 transformantes, dos quais 74 foram confirmados pelo ensaio de duplo-híbrido e codificam para 9 ligantes já conhecidos e 21novos ligantes prováveis de MX1. Entre esses novos ligantes prováveis estão proteínas que já haviam sido descritas como ligantes de MX1, incluindo a própria proteína MX1, o que valida os resultados obtidos com este rastreamento. Além disso, grande parte dos ligantes identificados são fatores envolvidos no processo de SUMOilação de proteínas, na formação de corpúsculos nucleares denominados PML-NB e uma série de proteínas relacionadas ao controle da transcrição e apoptose... (Resumo completo, clicar acesso eletrônico abaixo)

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This paper presents a study of the applicability of adsorption isotherms, known as Langmuir and Freundlich isotherm, between the biosorptive interaction of yeast lyophilized Saccharomyces cerevisiae and textile dyes. To that end, we prepared stock solutions of the textile dyes Direct Red 23 and Direct Red 75 in the concentration of 1.000μg/mL and a yeast suspension at 2,5%. We did experiments for two cases, firstly for the case that we have a fix concentration of yeast at 0,500mg/mL and an variable concentration of dye range from40, 50, 60, 80 and 100μg/mL, then for the case that we fixed the concentration of dye at 100μg/mL and the yeast concentration was variable range from 0,250, 0,500, 0,750, 1,000, 1,250mg/mL. For the dye Direct Red 23 we did analysis in the pH 2,5, 4,5 and 6,5; for the Direct Red 75, we just did for the pH 2,5. We leave the dye solution in contact with the yeast for 2 hours at a constant temperature of 30°C and then centrifuged and analyzed the sample in a spectrophotometer and finally made and analysis of parameters for the removal and study of the isotherms. After the biosorption, was observed that for the Direct Red 23 in the pH 2,5 was needed 1,407mg/mL of yeast for total removal, while for the pH 4,5 was needed 8,806mg/mL and in pH 6,5 was 9,286mg/mL; for the Direct Red 75 in pH 2,5 was needed 1,337mg/mL. This difference can be explain by the adsorption isotherms, was observed that in the case when the yeast was fix when we had in a acid pH the behavior of the system was compatible with the Langmuir isotherm, and thus, an monolayer pattern. And that when we decrease the acidity of the medium the system became more compatible with a Freundlich isotherm, and thus, a multilayer pattern; for the case that the yeast was variable this is not much evident, however for the pH 2,5 she became compatible with a Langmuir isotherm... (Complete abstract click electronic access below)

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The reducionism method has helped in the clari cation of functioning of many biological process. However, such process are extremely complex and have emergent properties that can not be explained or even predicted by reducionism methods. To overcome these limits, researchers have been used a set of methods known as systems biology, a new area of biology aiming to understand the interactions between the multiple components of biological processes. These interactions can be represented by a mathematical object called graph or network, where the interacting elements are represented by a vertex and the interactions by edges that connect a pair of vertexes. Into graphs it is possible to nd subgraphs, occurring in complex networks at numbers that are signi cantly higher than those in randomized networks, they are de ned as motifs. As motifs in biological networks may represent the structural units of biological processess, their detection is important. Therefore, the aim of this present work was detect, count and classify motifs present in biological integrated networks of bacteria Escherichia coli and yeast Saccharomyces cere- visiae. For this purpose, we implemented codes in MathematicaR and Python environments for detecting, counting and classifying motifs in these networks. The composition and types of motifs detected in these integrated networks indicate that such networks are organized in three main bridged modules composed by motifs in which edges are all the same type. The connecting bridges are composed by motifs in which the types of edges are diferent