54 resultados para Camarão marinho


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ORF 31 is a unique baculovirus gene in the genome of Anticarsia gemmatalis multiple nucleopolyhedrovirus isolate 2D (AgMNPV-2D). It encodes a putative polypeptide of 369 aa homologous to poly (ADP-ribose) polymerase (PARP) found in the genomes of several organisms. Moreover, we found a phylogenetic association with Group I PARP proteins and a 3D homology model of its conserved PARP C-terminal catalytic domain indicating that had almost an exact spatial superimposition of < 1 angstrom with other PARP available structures. The 5` end of ORF 31 mRNA was located at the first nucleotide of a CATT motif at position -27. Using real-time PCR we detected transcripts at 3 h post-infection (p.i.) increasing until 24 h p.i., which coincides with the onset of DNA replication, suggestive of a possible role in DNA metabolism.

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Dengue virus type 4 (DENV-4) circulates in tropical and subtropical countries from Asia and the Americas. Despite the importance of dengue virus distribution, little is known about the worldwide viral spread. Following a Bayesian phylogenetic approach we inferred the evolutionary history of 310 isolates sampled from 37 countries during the time period 1956-2008 and the spreading dynamics for genotypes I and II. The region (tropical rainforest biome) comprised by Malaysia-Thailand was the most likely ancestral area from which the serotype has originated and spread. Interestingly, cross-correlation analysis on demographic time series with the Asian sequences showed a statistically significant negative correlation that could be suggestive of competition among genotypes within the same serotype. (C) 2011 Elsevier B.V. All rights reserved.

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The genome of the most virulent among 22 Brazilian geographical isolates of Spodoptera frugiperda nucleopolyhedrovirus, isolate 19 (SfMNPV-1 9), was completely sequenced and shown to comprise 132 565 bp and 141 open reading frames (ORFs). A total of 11 ORFs with no homology to genes in the GenBank database were found. Of those, four had typical baculovirus; promoter motifs and polyadenylation sites. Computer-simulated restriction enzyme cleavage patterns of SfMNPV-1 9 were compared with published physical maps of other SfMNPV isolates. Differences were observed in terms of the restriction profiles and genome size. Comparison of SfMNPV-1 9 with the sequence of the SfMNPV isolate 3AP2 indicated that they differed due to a 1427 bp deletion, as well as by a series of smaller deletions and point mutations. The majority of genes of SfMNPV-1 9 were conserved in the closely related Spodoptera exigua NPV (SeMNPV) and Agrotis segetum NPV (AgseMNPV-A), but a few regions experienced major changes and rearrangements. Synthenic maps for the genomes of group 11 NPVs revealed that gene collinearity was observed only within certain clusters. Analysis of the dynamics of gene gain and loss along the phylogenetic tree of the NPVs showed that group 11 had only five defining genes and supported the hypothesis that these viruses form ten highly divergent ancient lineages. Crucially, more than 60% of the gene gain events followed a power-law relation to genetic distance among baculoviruses, indicative of temporal organization in the gene accretion process.

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The purpose of this paper is to develop a Bayesian analysis for nonlinear regression models under scale mixtures of skew-normal distributions. This novel class of models provides a useful generalization of the symmetrical nonlinear regression models since the error distributions cover both skewness and heavy-tailed distributions such as the skew-t, skew-slash and the skew-contaminated normal distributions. The main advantage of these class of distributions is that they have a nice hierarchical representation that allows the implementation of Markov chain Monte Carlo (MCMC) methods to simulate samples from the joint posterior distribution. In order to examine the robust aspects of this flexible class, against outlying and influential observations, we present a Bayesian case deletion influence diagnostics based on the Kullback-Leibler divergence. Further, some discussions on the model selection criteria are given. The newly developed procedures are illustrated considering two simulations study, and a real data previously analyzed under normal and skew-normal nonlinear regression models. (C) 2010 Elsevier B.V. All rights reserved.

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The estimation of data transformation is very useful to yield response variables satisfying closely a normal linear model, Generalized linear models enable the fitting of models to a wide range of data types. These models are based on exponential dispersion models. We propose a new class of transformed generalized linear models to extend the Box and Cox models and the generalized linear models. We use the generalized linear model framework to fit these models and discuss maximum likelihood estimation and inference. We give a simple formula to estimate the parameter that index the transformation of the response variable for a subclass of models. We also give a simple formula to estimate the rth moment of the original dependent variable. We explore the possibility of using these models to time series data to extend the generalized autoregressive moving average models discussed by Benjamin er al. [Generalized autoregressive moving average models. J. Amer. Statist. Assoc. 98, 214-223]. The usefulness of these models is illustrated in a Simulation study and in applications to three real data sets. (C) 2009 Elsevier B.V. All rights reserved.

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For the first time, we introduce a class of transformed symmetric models to extend the Box and Cox models to more general symmetric models. The new class of models includes all symmetric continuous distributions with a possible non-linear structure for the mean and enables the fitting of a wide range of models to several data types. The proposed methods offer more flexible alternatives to Box-Cox or other existing procedures. We derive a very simple iterative process for fitting these models by maximum likelihood, whereas a direct unconditional maximization would be more difficult. We give simple formulae to estimate the parameter that indexes the transformation of the response variable and the moments of the original dependent variable which generalize previous published results. We discuss inference on the model parameters. The usefulness of the new class of models is illustrated in one application to a real dataset.

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We introduce in this paper a new class of discrete generalized nonlinear models to extend the binomial, Poisson and negative binomial models to cope with count data. This class of models includes some important models such as log-nonlinear models, logit, probit and negative binomial nonlinear models, generalized Poisson and generalized negative binomial regression models, among other models, which enables the fitting of a wide range of models to count data. We derive an iterative process for fitting these models by maximum likelihood and discuss inference on the parameters. The usefulness of the new class of models is illustrated with an application to a real data set. (C) 2008 Elsevier B.V. All rights reserved.

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Here we present a status report of the first spherical antenna project equipped with a set of parametric transducers for gravitational detection. The Mario Schenberg, as it is called, started its commissioning phase at the Physics Institute of the University of Sao Paulo, in September 2006, under the full support of FAPESP. We have been testing the three preliminary parametric transducer systems in order to prepare the detector for the next cryogenic run, when it will be calibrated. We are also developing sapphire oscillators that will replace the current ones thereby providing better performance. We also plan to install eight transducers in the near future, six of which are of the two-mode type and arranged according to the truncated icosahedron configuration. The other two, which will be placed close to the sphere equator, will be mechanically non-resonant. In doing so, we want to verify that if the Schenberg antenna can become a wideband gravitational wave detector through the use of an ultra-high sensitivity non-resonant transducer constructed using the recent achievements of nanotechnology.

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Methanolic extract powders of acerola, passion fruit and pineapple industrial residues, including pulp, seeds and peel, altogether (except for acerola) devoid of seeds, were screened for antioxidant capacity. The total phenolic contents (TPCs) of the extract powders were compared with their radical-scavenging activities (RSA) against both DPPH(center dot) and superoxide anion (O(2)(center dot-)) radicals, and their protective effect against liposome peroxidation, triggered by peroxyl radical. Lipid peroxidation was followed by the fluorescence decay of the probe, 4,4-difluoro-5-(4-phenyl-1,3-butadienyl)-4-bora-3a,4a-diaza-s-indacene-3-undecanoic acid (C(11)-BODIPY(581/591)). The TPCs of acerola, passion fruit and pineapple extract powders were (94.6 +/- 7.4); (41.2 +/- 4.2) and (9.1 +/- 1.3) mg of gallic acid equivalents g(-1) of dry extract, respectively. Acerola showed the best RSA-DPPH(center dot) scores, whereas passion fruit was more protective on the RSA-O(2)(center dot-) system. Together with the protective effects against lipid peroxidation (rate of BODIPY decay) which, were similar for acerola and passion fruit extracts, these data suggest that the methanolic extracts of acerola and passion fruit residues may be useful as antioxidant supplements, particularly the acerola extract, due to its high phenolic content. (C) 2008 Elsevier Ltd. All rights reserved