Population structure of the migratory fish Prochilodus lineatus (Characiformes) from rio Grande basin (Brazil), an area fragmented by dams

1. Prochilodus lineatus (Prochilodontidae, Characiformes) is a migratory species of great economic importance both in fisheries and aquaculture that is found throughout the Jacui, Paraiba do Sul, Parana, Paraguay and Uruguay river basins in South America. Earlier population studies of P. lineatus in the rio Grande basin (Parana basin) indicated the existence of a single population; however, the range of this species has been fragmented by the construction of several dams. Such dams modified the environmental conditions and could have constrained the reproductive migration of P. lineatus, possibly leading to changes in the population genetic structure. 2. In order to evaluate how genetic diversity is allocated in the rio Grande basin, 141 specimens of P. lineatus from eight collection sites were analysed using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) with 15 restriction enzymes. 3. Forty-six haplotypes were detected, and 70% of them are restricted. The mean genetic variability indexes (h = 0.7721 and pi = 1.6%) were similar to those found in natural populations with a large effective size. Fst and Exact Test values indicated a lack of structuring among the samples, and the model of isolation by distance was tested and rejected. 4. The haplotype network indicated that this population of P. lineatus has been maintained as a single variable stock with some differences in the genetic composition (haplotypes) between samples. Indications of population expansion were detected, and this finding was supported by neutrality tests and mismatch distribution analyses. 5. The present study focused on regions between dams to serve as a parameter for further evaluations of genetic variability and the putative impact of dams and repopulation programmes in natural populations of P. lineatus. Copyright (C) 2011 John Wiley & Sons, Ltd.

Mitochondrial DNA Diversity of Orchid Bee Euglossa fimbriata (Hymenoptera: Apidae) Populations Assessed by PCR-RFLP

Euglossa fimbriata is a euglossine species widely distributed in Brazil and occurring primarily in Atlantic Forest remnants. In this study, the genetic mitochondrial structure of E. fimbriata from six Atlantic Forest fragments was studied by RFLP analysis of three PCR-amplified mtDNA gene segments (16S, COI-COII, and cyt b). Ten composite haplotypes were identified, six of which were exclusive and represented singleton mitotypes. Low haplotype diversity (0.085-0.289) and nucleotide diversity (0.000-0.002) were detected within samples. AMOVA partitioned 91.13% of the overall genetic variation within samples and 8.87% (I center dot(st) = 0.089; P < 0.05) among samples. Pairwise comparisons indicated high levels of differentiation among some pairs of samples (I center dot(st) = 0.161-0.218; P < 0.05). These high levels indicate that these populations of E. fimbriata, despite their highly fragmented landscape, apparently have not suffered loss of genetic variation, suggesting that this particular population is not currently endangered.

A PCR-RFLP assay for gender assignment in the three-toed sloths (Bradypus, Pilosa, Bradypodidae)

The three-toed sloths (Bradypus) are slow-moving arboreal neotropical mammals. Understanding demographic variables (such as sex ratio) of populations is a key for conservation purposes. Nevertheless, gender assignment of Bradypus is particularly challenging because of the lack of sexual dimorphism in infants and in adults, particularly B. torquatus, the most endangered of the three-toed sloths, in which sex is attributed by visual observation of the reproductively active males. Here, we standardized a method for sexing Bradypus individuals using PCR-RFLP of sex-linked genes ZFX/ZFY. This assay was validated with known-gender animals and proved accurate to assign gender on three Bradypus species.

Evaluation of Quantitative RT-PCR Using Nonamplified and Amplified RNA

Quantitative reverse-transcription polymerase chain reaction (qRT-PCR) is a standard assay in molecular medicine for gene expression analysis. Samples from incisional/needle biopsies, laser-microdissected tumor cells and other biologic sources, normally available in clinical cancer studies, generate very small amounts of RNA that are restrictive for expression analysis. As a consequence, an RNA amplification procedure is required to assess the gene expression levels of such sample types. The reproducibility and accuracy of relative gene expression data produced by sensitive methodology as qRT-PCR when cDNA converted from amplified (A) RNA is used as template has not yet been properly addressed. In this study, to properly evaluate this issue, we performed 1 round of linear RNA amplification in 2 breast cell lines (C5.2 and HB4a) and assessed the relative expression of 34 genes using cDNA converted from both nonamplified (NA) and A RNA. Relative gene expression was obtained from beta actin or glyceraldehyde 3-phosphate dehydrogenase normalized data using different dilutions of cDNA, wherein the variability and fold-change differences in the expression of the 2 methods were compared. Our data showed that 1 round of linear RNA amplification, even with suboptimal-quality RNA, is appropriate to generate reproducible and high-fidelity qRT-PCR relative expression data that have similar confidence levels as those from NA samples. The use of cDNA that is converted from both A and NA RNA in a single qRT-PCR experiment clearly creates bias in relative gene expression data.

Detection of hantaviruses in Brazilian rodents by SYBR-Green-based real-time RT-PCR

Current knowledge of the pathogenic hantavirus indicates that wild rodents are its primary natural reservoir. Specific primers to detect the presence of viral genomes were developed using an SYBR-Green-based real-time RT-PCR protocol. One hundred sixty-four rodents native to the Atlantic Forest biome were captured in So Paulo State, Brazil, and their tissues were tested. The presence of hantavirus RNA was detected in sixteen rodents: three specimens of Akodon montensis, three of Akodon cursor, two of Necromys lasiurus, one of Juliomys sp., one of Thaptomys nigrita, five of Oligoryzomys nigripes, and one of Oryzomys sp. This SYBR Green real-time RT-PCR method for detection of hantavirus may be useful for surveying hantaviruses in Brazil.

Use of PCR for detecting Aspergillus flavus in maize treated by gamma radiation process

The aim of this study was to verify the effects of gamma radiation process on the fungal DNA and the application of PCR in the detection of Aspergillus flavus in irradiated maize grains. The samples were inoculated with a toxigenic strain and incubated under controlled conditions of relative humidity, water activity, and temperature for 15 days. After incubation, the samples were treated with gamma radiation with doses of 5 and 10 kGy and individually analyzed. The use of PCR technique showed the presence of DNA bands of Aspergillus flavus in all irradiated samples that showed no fungal growth in agar medium.

A quantitative TaqMan PCR assay for the detection of Mycoplasma suis

Aim: To develop a TaqMan probe-based, highly sensitive and specific quantitative PCR (qPCR) assay for the detection and quantification of Mycoplasma suis in the blood of pigs. Methods and Results: Primers and probes specific to Myc. suis 16S rRNA gene were designed. The qPCR assay`s specificity, detection limit, intra- and inter-assay variability were evaluated and its performance was compared with a Myc. suis conventional PCR assay (cPCR). Blood of two experimentally infected pigs, 40 Indiana pigs, 40 Brazilian sows and 28 peccaries were tested. The assay detected as few as ten copies of Myc. suis plasmids and was 100-fold more sensitive than the cPCR. No cross-reactivity with nontarget pig mycoplasmas was observed. An average of 1.62 x 10(11) and 2.75 x 10(8) target copies ml(-1) of blood were detected in the acutely and chronically infected pigs, respectively. Three (7.5%) pigs and 32 (80.0%) sows were positive while all peccaries were negative for Myc. suis. Conclusion: The developed qPCR assay is highly sensitive and specific for Myc. suis detection and quantification. Significance and Impact of the Study: TaqMan qPCR is an accurate and quick test for detection of Myc. suis infected pigs, which can be used on varied instrumentation platforms.

Age-Dependent Acquisition of Protective Immunity to Malaria in Riverine Populations of the Amazon Basin of Brazil

Five community-based cross-sectional surveys of malaria morbidity and associated risk factors in remote riverine populations in northwestern Brazil showed average parasite rates of 4.2% (thick-smear microscopy) and 14.4% (polymerase chain reaction [PCR]) in the overall population, with a spleen rate of 13.9% among children 2-9 years of age. Plasmodium vivax was 2.8 times more prevalent than P. falciparum, with rare instances of P. malariae and mixed-species infections confirmed by PCR; 9.6% of asymptomatic subjects had parasitemias detected by PCR. Low-grade parasitemia detected by PCR only was a risk factor for anemia, after controlling for age and other covariates. Although clinical and subclinical infections occurred in all age groups, the risk of infection and disease decreased significantly with increasing age, after adjustment for several covariates in multilevel logistic regression models. These findings suggest that the continuous exposure to hypo- or mesoendemic malaria may induce significant anti-parasite and anti-disease immunity in native Amazonians.

Heteroscedastic Nonlinear Regression Models

In this article, we present a generalization of the Bayesian methodology introduced by Cepeda and Gamerman (2001) for modeling variance heterogeneity in normal regression models where we have orthogonality between mean and variance parameters to the general case considering both linear and highly nonlinear regression models. Under the Bayesian paradigm, we use MCMC methods to simulate samples for the joint posterior distribution. We illustrate this algorithm considering a simulated data set and also considering a real data set related to school attendance rate for children in Colombia. Finally, we present some extensions of the proposed MCMC algorithm.

Regression Models with Heteroscedasticity using Bayesian Approach

In this paper, we compare the performance of two statistical approaches for the analysis of data obtained from the social research area. In the first approach, we use normal models with joint regression modelling for the mean and for the variance heterogeneity. In the second approach, we use hierarchical models. In the first case, individual and social variables are included in the regression modelling for the mean and for the variance, as explanatory variables, while in the second case, the variance at level 1 of the hierarchical model depends on the individuals (age of the individuals), and in the level 2 of the hierarchical model, the variance is assumed to change according to socioeconomic stratum. Applying these methodologies, we analyze a Colombian tallness data set to find differences that can be explained by socioeconomic conditions. We also present some theoretical and empirical results concerning the two models. From this comparative study, we conclude that it is better to jointly modelling the mean and variance heterogeneity in all cases. We also observe that the convergence of the Gibbs sampling chain used in the Markov Chain Monte Carlo method for the jointly modeling the mean and variance heterogeneity is quickly achieved.

Methods of Estimation in Multiple Linear Regression: Application to Clinical Data

Nesse artigo, tem-se o interesse em avaliar diferentes estratégias de estimação de parâmetros para um modelo de regressão linear múltipla. Para a estimação dos parâmetros do modelo foram utilizados dados de um ensaio clínico em que o interesse foi verificar se o ensaio mecânico da propriedade de força máxima (EM-FM) está associada com a massa femoral, com o diâmetro femoral e com o grupo experimental de ratas ovariectomizadas da raça Rattus norvegicus albinus, variedade Wistar. Para a estimação dos parâmetros do modelo serão comparadas três metodologias: a metodologia clássica, baseada no método dos mínimos quadrados; a metodologia Bayesiana, baseada no teorema de Bayes; e o método Bootstrap, baseado em processos de reamostragem.

Bayesian nonlinear regression models with scale mixtures of skew-normal distributions: Estimation and case influence diagnostics

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.

A bivariate regression model for matched paired survival data: local influence and residual analysis

The use of bivariate distributions plays a fundamental role in survival and reliability studies. In this paper, we consider a location scale model for bivariate survival times based on the proposal of a copula to model the dependence of bivariate survival data. For the proposed model, we consider inferential procedures based on maximum likelihood. Gains in efficiency from bivariate models are also examined in the censored data setting. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the bivariate regression model for matched paired survival data. Sensitivity analysis methods such as local and total influence are presented and derived under three perturbation schemes. The martingale marginal and the deviance marginal residual measures are used to check the adequacy of the model. Furthermore, we propose a new measure which we call modified deviance component residual. The methodology in the paper is illustrated on a lifetime data set for kidney patients.

A nonlinear regression model with skew-normal errors

In this paper we have discussed inference aspects of the skew-normal nonlinear regression models following both, a classical and Bayesian approach, extending the usual normal nonlinear regression models. The univariate skew-normal distribution that will be used in this work was introduced by Sahu et al. (Can J Stat 29:129-150, 2003), which is attractive because estimation of the skewness parameter does not present the same degree of difficulty as in the case with Azzalini (Scand J Stat 12:171-178, 1985) one and, moreover, it allows easy implementation of the EM-algorithm. As illustration of the proposed methodology, we consider a data set previously analyzed in the literature under normality.

On estimation and influence diagnostics for log-Birnbaum-Saunders Student-t regression models: Full Bayesian analysis

The purpose of this paper is to develop a Bayesian approach for log-Birnbaum-Saunders Student-t regression models under right-censored survival data. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the considered model. In order to attenuate the influence of the outlying observations on the parameter estimates, we present in this paper Birnbaum-Saunders models in which a Student-t distribution is assumed to explain the cumulative damage. Also, some discussions on the model selection to compare the fitted models are given and case deletion influence diagnostics are developed for the joint posterior distribution based on the Kullback-Leibler divergence. The developed procedures are illustrated with a real data set. (C) 2010 Elsevier B.V. All rights reserved.