Phylogenetic relationship of dengue virus type 3 isolated in Brazil and Paraguay and global evolutionary divergence dynamics

Background: Dengue is the most important mosquito-borne viral disease worldwide. Dengue virus comprises four antigenically related viruses named dengue virus type 1 to 4 (DENV1-4). DENV-3 was re-introduced into the Americas in 1994 causing outbreaks in Nicaragua and Panama. DENV-3 was introduced in Brazil in 2000 and then spread to most of the Brazilian States, reaching the neighboring country, Paraguay in 2002. In this study, we have analyzed the phylogenetic relationship of DENV-3 isolated in Brazil and Paraguay with viruses isolated worldwide. We have also analyzed the evolutionary divergence dynamics of DENV-3 viruses. Results: The entire open reading frame (ORF) of thirteen DENV-3 isolated in Brazil (n = 9) and Paraguay (n = 4) were sequenced for phylogenetic analysis. DENV-3 grouped into three main genotypes (I, II and III). Several internal clades were found within each genotype that we called lineage and sub-lineage. Viruses included in this study belong to genotype III and grouped together with viruses isolated in the Americas within the lineage III. The Brazilian viruses were further segregated into two different sub-lineage, A and B, and the Paraguayan into the sub-lineage B. All three genotypes showed internal grouping. The nucleotide divergence was in average 6.7% for genotypes, 2.7% for lineages and 1.5% for sub-lineages. Phylogenetic trees constructed with any of the protein gene sequences showed the same segregation of the DENV-3 in three genotypes. Conclusion: Our results showed that two groups of DENV-3 genotypes III circulated in Brazil during 2002-2009, suggesting different events of introduction of the virus through different regions of the country. In Paraguay, only one group DENV-3 genotype III is circulating that is very closely related to the Brazilian viruses of sub-lineage B. Different degree of grouping can be observed for DENV-3 and each group showed a characteristic evolutionary divergence. Finally, we have observed that any protein gene sequence can be used to identify the virus genotype.

On the impact of disproportional samples in credit scoring models: An application to a Brazilian bank data

Statistical methods have been widely employed to assess the capabilities of credit scoring classification models in order to reduce the risk of wrong decisions when granting credit facilities to clients. The predictive quality of a classification model can be evaluated based on measures such as sensitivity, specificity, predictive values, accuracy, correlation coefficients and information theoretical measures, such as relative entropy and mutual information. In this paper we analyze the performance of a naive logistic regression model (Hosmer & Lemeshow, 1989) and a logistic regression with state-dependent sample selection model (Cramer, 2004) applied to simulated data. Also, as a case study, the methodology is illustrated on a data set extracted from a Brazilian bank portfolio. Our simulation results so far revealed that there is no statistically significant difference in terms of predictive capacity between the naive logistic regression models and the logistic regression with state-dependent sample selection models. However, there is strong difference between the distributions of the estimated default probabilities from these two statistical modeling techniques, with the naive logistic regression models always underestimating such probabilities, particularly in the presence of balanced samples. (C) 2012 Elsevier Ltd. All rights reserved.

Are the preference and selection patterns of hermit crabs for gastropod shells species- or site-specific?

Experimental analyses of hermit crabs and their preferences for shells are essential to understand the intrinsic relationship of the crabs` dependence on shells, and may be useful to explain their shell use pattern in nature. The aim of this study was to evaluate the effect of crab species and site on the pattern of shell use, selection, and preference in the south-western Atlantic hermit crabs Pagurus brevidactylus and Pagurus criniticornis, comparing sympatric and allopatric populations. Differently from the traditional approach to evaluate shell preference by simply determining the shell selection pattern (i.e., the number of shells of each type selected), preference was defined (according to [Liszka, D., Underwood, AJ., 1990. An experimental design to determine preferences for gastropod shells by a hermit-crab. J. Exp. Mar. Biol. Ecol., 137(1), 47-62]) by the comparison of the number of crabs changing for a particular shell type when three options were given (Cerithium atratum, Morula nodulosa, and Tegula viridula) with the number of crabs changing for this same type when only this type was offered. The effect of crab species was tested at Cabelo Gordo Beach, where P. brevidacrylus was found occupying shells of C. atratum, M. nodulosa, and T viridula in similar frequencies, whereas P. criniticornis occupied predominantly shells of C atratum. In laboratory experiments the selection patterns of the two hermit-crab species for these three gastropods were different, with P criniticornis selecting mainly shells of C atratum, and R brevidactylus selecting more shells of M. nodulosa. The shell preference was also dependent on crab species, with P. criniticornis showing a clear preference for shells of C atratum, whereas P. brevidactylus did not show a preference for any of the tested shells. The effect of site was tested for the two species comparing data from Cabelo Gordo to Preta (P brevidactylus) and Araca beaches (P. criniticornis). The pattern of shell use, selection, and preference was demonstrated to be dependent on site only for P. brevidactylus. The results also showed that the shell use pattern of P criniticornis can be explained by its preference at both sites, whereas for P. brevidactylus it occurred only at Cabelo Gordo, where the absence of preference was correlated with the similar use of the three gastropod species studied. Finally, the results showed that the shell selection pattern cannot be considered as a measure of shell preference, since it overestimates crab selectivity. (C) 2009 Elsevier B.V. All rights reserved.

CONTEXT TREE SELECTION AND LINGUISTIC RHYTHM RETRIEVAL FROM WRITTEN TEXTS

The starting point of this article is the question "How to retrieve fingerprints of rhythm in written texts?" We address this problem in the case of Brazilian and European Portuguese. These two dialects of Modern Portuguese share the same lexicon and most of the sentences they produce are superficially identical. Yet they are conjectured, on linguistic grounds, to implement different rhythms. We show that this linguistic question can be formulated as a problem of model selection in the class of variable length Markov chains. To carry on this approach, we compare texts from European and Brazilian Portuguese. These texts are previously encoded according to some basic rhythmic features of the sentences which can be automatically retrieved. This is an entirely new approach from the linguistic point of view. Our statistical contribution is the introduction of the smallest maximizer criterion which is a constant free procedure for model selection. As a by-product, this provides a solution for the problem of optimal choice of the penalty constant when using the BIC to select a variable length Markov chain. Besides proving the consistency of the smallest maximizer criterion when the sample size diverges, we also make a simulation study comparing our approach with both the standard BIC selection and the Peres-Shields order estimation. Applied to the linguistic sample constituted for our case study, the smallest maximizer criterion assigns different context-tree models to the two dialects of Portuguese. The features of the selected models are compatible with current conjectures discussed in the linguistic literature.

Estimation and diagnostics for heteroscedastic nonlinear regression models based on scale mixtures of skew-normal distributions

An extension of some standard likelihood based procedures to heteroscedastic nonlinear regression models under scale mixtures of skew-normal (SMSN) distributions is developed. This novel class of models provides a useful generalization of the heteroscedastic symmetrical nonlinear regression models (Cysneiros et al., 2010), since the random term distributions cover both symmetric as well as asymmetric and heavy-tailed distributions such as skew-t, skew-slash, skew-contaminated normal, among others. A simple EM-type algorithm for iteratively computing maximum likelihood estimates of the parameters is presented and the observed information matrix is derived analytically. In order to examine the performance of the proposed methods, some simulation studies are presented to show the robust aspect of this flexible class against outlying and influential observations and that the maximum likelihood estimates based on the EM-type algorithm do provide good asymptotic properties. Furthermore, local influence measures and the one-step approximations of the estimates in the case-deletion model are obtained. Finally, an illustration of the methodology is given considering a data set previously analyzed under the homoscedastic skew-t nonlinear regression model. (C) 2012 Elsevier B.V. All rights reserved.

Study of using marker assisted selection on a beef cattle breeding program by model comparison

A data set of a commercial Nellore beef cattle selection program was used to compare breeding models that assumed or not markers effects to estimate the breeding values, when a reduced number of animals have phenotypic, genotypic and pedigree information available. This herd complete data set was composed of 83,404 animals measured for weaning weight (WW), post-weaning gain (PWG), scrotal circumference (SC) and muscle score (MS), corresponding to 116,652 animals in the relationship matrix. Single trait analyses were performed by MTDFREML software to estimate fixed and random effects solutions using this complete data. The additive effects estimated were assumed as the reference breeding values for those animals. The individual observed phenotype of each trait was adjusted for fixed and random effects solutions, except for direct additive effects. The adjusted phenotype composed of the additive and residual parts of observed phenotype was used as dependent variable for models' comparison. Among all measured animals of this herd, only 3160 animals were genotyped for 106 SNP markers. Three models were compared in terms of changes on animals' rank, global fit and predictive ability. Model 1 included only polygenic effects, model 2 included only markers effects and model 3 included both polygenic and markers effects. Bayesian inference via Markov chain Monte Carlo methods performed by TM software was used to analyze the data for model comparison. Two different priors were adopted for markers effects in models 2 and 3, the first prior assumed was a uniform distribution (U) and, as a second prior, was assumed that markers effects were distributed as normal (N). Higher rank correlation coefficients were observed for models 3_U and 3_N, indicating a greater similarity of these models animals' rank and the rank based on the reference breeding values. Model 3_N presented a better global fit, as demonstrated by its low DIC. The best models in terms of predictive ability were models 1 and 3_N. Differences due prior assumed to markers effects in models 2 and 3 could be attributed to the better ability of normal prior in handle with collinear effects. The models 2_U and 2_N presented the worst performance, indicating that this small set of markers should not be used to genetically evaluate animals with no data, since its predictive ability is restricted. In conclusion, model 3_N presented a slight superiority when a reduce number of animals have phenotypic, genotypic and pedigree information. It could be attributed to the variation retained by markers and polygenic effects assumed together and the normal prior assumed to markers effects, that deals better with the collinearity between markers. (C) 2012 Elsevier B.V. All rights reserved.

Anderson-like Transition for a Class of Random Sparse Models in d >= 2 Dimensions

We show that the Kronecker sum of d >= 2 copies of a random one-dimensional sparse model displays a spectral transition of the type predicted by Anderson, from absolutely continuous around the center of the band to pure point around the boundaries. Possible applications to physics and open problems are discussed briefly.

The inactive form of glycogen synthase kinase-3 beta is associated with the development of carcinomas in galectin-3 wild-type mice, but not in galectin-3-deficient mice

Galectin-3 has been implicated in the tumor development via its mediation of the Wnt signaling pathway. Likewise, glycogen synthase kinase-3beta (GSK3 beta) also plays a role in the Wnt signaling pathway by controlling the levels of cytoplasmic beta-catenin. Altered GSK3 beta expression has been described in various tumors, but to date, there are no studies evaluating its expression in models of oral carcinogenesis. Additionally, it is unknown whether the absence of galectin-3 regulates the expression of GSK3 beta. To this end, Gal3-deficient (Gal3(-/-)) and wild-type (Gal3(+/+)) male mice were treated with 4NQO for 16 weeks and sacrificed at week 16 and 32. The tongues were removed, processed, and stained with H&E to detect dysplasias and carcinomas. An immunohistochemical assay was performed to determine the level of P-GSK3 beta-Ser9 expression in both groups. Carcinomas were more prevalent in Gal3(+/+) than Gal3(-/-) mice (55.5% vs. 28.5%), but no statistical difference was reached. In the dysplasias, the proportion of cells positive for P-GSK3 beta-Ser9 was slightly higher in Gal3(+/+) than Gal3(-/-) mice (63% vs. 61%). In the carcinomas, a significant difference between Gal3(+/+) and Gal3(-/-) mice was found (74% vs. 59%; p=0.02). P-GSK3 beta-Ser9-positive cells slightly decreased from the progression of dysplasias to carcinomas in Gal3(-/-) mice (61% vs. 59%; p>0.05). However, a significant increase in P-GSK3 beta-Ser9 expression was observed from dysplasias to carcinomas in Gal3(+/+) mice (63% vs. 74%; p=0.01). In conclusion, these findings suggest that fully malignant transformation of the tongue epithelium is associated with increased P-GSK3 beta-Ser9 expression in Gal3(+/+) mice, but not in Gal3(-/-) mice.

Bladder expression of CD cell surface antigens and cell-type-specific transcriptomes

Many cell types have no known functional attributes. In the bladder and prostate, basal epithelial and stromal cells appear similar in cytomorphology and share several cell surface markers. Their total gene expression (transcriptome) should provide a clear measure of the extent to which they are alike functionally. Since urologic stromal cells are known to mediate organ-specific tissue formation, these cells in cancers might exhibit aberrant gene expression affecting their function. For transcriptomes, cluster designation (CD) antigens have been identified for cell sorting. The sorted cell populations can be analyzed by DNA microarrays. Various bladder cell types have unique complements of CD molecules. CD9(+) urothelial, CD104(+) basal and CD13(+) stromal cells of the lamina propria were therefore analyzed, as were CD9(+) cancer and CD13(+) cancer-associated stromal cells. The transcriptome datasets were compared by principal components analysis for relatedness between cell types; those with similarity in gene expression indicated similar function. Although bladder and prostate basal cells shared CD markers such as CD104, CD44 and CD49f, they differed in overall gene expression. Basal cells also lacked stem cell gene expression. The bladder luminal and stromal transcriptomes were distinct from their prostate counterparts. In bladder cancer, not only the urothelial but also the stromal cells showed gene expression alteration. The cancer process in both might thus involve defective stromal signaling. These cell-type transcriptomes provide a means to monitor in vitro models in which various CD-isolated cell types can be combined to study bladder differentiation and bladder tumor development based on cell-cell interaction.

Strategies in identifying individuals in a segregant population of common bean and implications of genotype x environment interaction in the success of selection

The objective of this study was to compare the BLUP selection method with different selection strategies in F-2:4 and assess the efficiency of this method on the early choice of the best common bean (Phaseolus vulgaris) lines. Fifty-one F-2:4 progenies were produced from a cross between the CVIII8511 x RP-26 lines. A randomized block design was used with 20 replications and one-plant field plots. Character data on plant architecture and grain yield were obtained and then the sum of the standardized variables was estimated for simultaneous selection of both traits. Analysis was carried out by mixed models (BLUP) and the least squares method to compare different selection strategies, like mass selection, stratified mass selection and between and within progeny selection. The progenies selected by BLUP were assessed in advanced generations, always selecting the greatest and smallest sum of the standardized variables. Analyses by the least squares method and BLUP procedure ranked the progenies in the same way. The coincidence of the individuals identified by BLUP and between and within progeny selection was high and of the greatest magnitude when BLUP was compared with mass selection. Although BLUP is the best estimator of genotypic value, its efficiency in the response to long term selection is not different from any of the other methods, because it is also unable to predict the future effect of the progenies x environments interaction. It was inferred that selection success will always depend on the most accurate possible progeny assessment and using alternatives to reduce the progenies x environments interaction effect.

Equid herpesvirus type-1 exhibits neurotropism and neurovirulence in a mouse model

Intranasal inoculation of equid herpesvirus type-1 (EHV-1) Brazilian strains A4/72 and A9/92 induced an acute and lethal infection in four different inbred mouse strains. Clinical and neurological signs appeared between the 2nd and 3rd day post inoculation (dpi) and included weight loss, ruffled fur, a hunched posture, crouching in corners, nasal and ocular discharges, dyspnoea, dehydration and increased salivation. These signs were followed by increased reactivity to external stimulation, seizures, recumbency and death. The virus was recovered consistently from the brain and viscera of all mice with neurological signs. Histopathological changes consisted of leptomeningitis, focal haemorrhage, ventriculitis, neuronal degeneration and necrosis, neuronophagia, non-suppurative inflammation, multifocal gliosis and perivascular infiltration of polymorphonuclear and mononuclear cells. Immunohistochemical examination demonstrated that EHV-1 strains A4/72 and A9/92 replicated in neurons of the olfactory bulb, the cortex and the hippocampus. In contrast, mice inoculated with the EHV-1 Brazilian strain A3/97 showed neither weight loss nor apparent clinical or neurological signs; however, the virus was recovered consistently from their lungs at 3 dpi. These three EHV-1 strains showed distinct degrees of virulence and tissue tropism in mice. EHV-1 strains A4/72 and A9/92 exhibited a high degree of central nervous system tropism with neuroinvasion and neurovirulence. EHV-1 strain A3/97 was not neurovirulent despite being detected in the brains of infected BALB/c nude mice. These findings indicate that several inbred mouse strains are susceptible to neuropathogenic EHV-1 strains and should be useful models for studying the pathogenesis and mechanisms contributing to EHV-induced myeloencephalopathy in horses. (C) 2011 Elsevier Ltd. All rights reserved.

Assessment of variance components in nonlinear mixed-effects elliptical models

The issue of assessing variance components is essential in deciding on the inclusion of random effects in the context of mixed models. In this work we discuss this problem by supposing nonlinear elliptical models for correlated data by using the score-type test proposed in Silvapulle and Silvapulle (1995). Being asymptotically equivalent to the likelihood ratio test and only requiring the estimation under the null hypothesis, this test provides a fairly easy computable alternative for assessing one-sided hypotheses in the context of the marginal model. Taking into account the possible non-normal distribution, we assume that the joint distribution of the response variable and the random effects lies in the elliptical class, which includes light-tailed and heavy-tailed distributions such as Student-t, power exponential, logistic, generalized Student-t, generalized logistic, contaminated normal, and the normal itself, among others. We compare the sensitivity of the score-type test under normal, Student-t and power exponential models for the kinetics data set discussed in Vonesh and Carter (1992) and fitted using the model presented in Russo et al. (2009). Also, a simulation study is performed to analyze the consequences of the kurtosis misspecification.

Scalar field description for parametric models of dark energy

We investigate theoretical and observational aspects of a time-dependent parameterization for the dark energy equation of state w(z), which is a well behaved function of the redshift z over the entire cosmological evolution, i.e., z is an element of [-1, infinity). By using a theoretical algorithm of constructing the quintes-sence potential directly from the w(z) function, we derive and discuss the general features of the resulting potential for the cases in which dark energy is separately conserved and when it is coupled to dark matter. Since the parameterization here discussed allows us to divide the parametric plane in defined regions associated to distinct classes of dark energy models, we use some of the most recent observations from type Ia supernovae, baryon acoustic oscillation peak and Cosmic Microwave Background shift parameter to check which class is observationally preferred. We show that the largest portion of the confidence contours lies into the region corresponding to a possible crossing of the so-called phantom divide line at some point of the cosmic evolution.

Response plateau models fitting via isotonic regression

Within the nutritional context, the supplementation of microminerals in bird food is often made in quantities exceeding those required in the attempt to ensure the proper performance of the animals. The experiments of type dosage x response are very common in the determination of levels of nutrients in optimal food balance and include the use of regression models to achieve this objective. Nevertheless, the regression analysis routine, generally, uses a priori information about a possible relationship between the response variable. The isotonic regression is a method of estimation by least squares that generates estimates which preserves data ordering. In the theory of isotonic regression this information is essential and it is expected to increase fitting efficiency. The objective of this work was to use an isotonic regression methodology, as an alternative way of analyzing data of Zn deposition in tibia of male birds of Hubbard lineage. We considered the models of plateau response of polynomial quadratic and linear exponential forms. In addition to these models, we also proposed the fitting of a logarithmic model to the data and the efficiency of the methodology was evaluated by Monte Carlo simulations, considering different scenarios for the parametric values. The isotonization of the data yielded an improvement in all the fitting quality parameters evaluated. Among the models used, the logarithmic presented estimates of the parameters more consistent with the values reported in literature.

MODULARITY, NOISE, AND NATURAL SELECTION

Most biological systems are formed by component parts that are to some degree interrelated. Groups of parts that are more associated among themselves and are relatively autonomous from others are called modules. One of the consequences of modularity is that biological systems usually present an unequal distribution of the genetic variation among traits. Estimating the covariance matrix that describes these systems is a difficult problem due to a number of factors such as poor sample sizes and measurement errors. We show that this problem will be exacerbated whenever matrix inversion is required, as in directional selection reconstruction analysis. We explore the consequences of varying degrees of modularity and signal-to-noise ratio on selection reconstruction. We then present and test the efficiency of available methods for controlling noise in matrix estimates. In our simulations, controlling matrices for noise vastly improves the reconstruction of selection gradients. We also perform an analysis of selection gradients reconstruction over a New World Monkeys skull database to illustrate the impact of noise on such analyses. Noise-controlled estimates render far more plausible interpretations that are in full agreement with previous results.