Determination of trace elements in human brain tissues using neutron activation analysis

Neutron activation analysis was applied to assess trace element concentrations in brain tissues from normal (n = 21) and demented individuals (n = 21) of both genders aged more than 50 years. Concentrations of the elements Br, Fe, K, Na, Rb, Se and Zn were determined. Comparisons were made between the results obtained for the hippocampus and frontal cortex tissues, as well as, those obtained in brains of normal and demented individuals. Certified reference materials, NIST 1566b Oyster Tissue and NIST 1577b Bovine Liver were analyzed for quality of the analytical results.

Factors determining normal adult height in girls with gonadotropin-dependent precocious puberty treated with depot gonadotropin-releasing hormone analogs

Context: Several factors can affect adult height (AH) of patients with gonadotropin-dependent precocious puberty (GDPP) treated with depot GnRH analogs. Objective: Our objective was to determine factors influencing AH in patients with GDPP treated with depot GnRH analogs. Patients: A total of 54 patients (45 girls) with GDPP treated with depot GnRH analog who reached AH was included in the study. Design: Univariate and multivariate analyses of the factors potentially associated with AH were performed in all girls with GDPP. In addition, clinical features of the girls who attained target height (TH) range were compared with those who did not. Predicted height using Bayley and Pinneau tables was compared with attained AH. Results: In girls the mean AH was 155.3 +/- 6.9 cm (-1.2 +/- 1 SD) with TH range achieved by 81% of this group. Multiple regression analysis revealed that the interval between chronological age at onset of puberty and at the start of GnRH analog therapy, height SD scores (SDSs) at the start and end of therapy, and TH explained 74% of AH variance. The predicted height at interruption of GnRH therapy, obtained from Bayley and Pinneau tables for average bone age, was more accurate than for advanced bone age in both sexes. In boys the mean AH was 170.6 +/- 9.2 cm (-1 +/- 1.3 SDS), whereas TH was achieved by 89% of this group. Conclusions: The major factors determining normal AH in girls with GDPP treated with depot GnRH analogs were shorter interval between the onset of puberty and start of therapy, higher height SDS at the start and end of therapy, and TH. Therefore, prompt depot GnRH analog therapy in properly selected patients with GDPP is critical to obtain normal AH.

High frequency of submicroscopic chromosomal imbalances in patients with syndromic craniosynostosis detected by a combined approach of microsatellite segregation analysis, multiplex ligation-dependent probe amplification and array-based comparative genome hybridisation

We present the first comprehensive study, to our knowledge, on genomic chromosomal analysis in syndromic craniosynostosis. In total, 45 patients with craniosynostotic disorders were screened with a variety of methods including conventional karyotype, microsatellite segregation analysis, subtelomeric multiplex ligation-dependent probe amplification) and whole-genome array-based comparative genome hybridisation. Causative abnormalities were present in 42.2% (19/45) of the samples, and 27.8% (10/36) of the patients with normal conventional karyotype carried submicroscopic imbalances. Our results include a wide variety of imbalances and point to novel chromosomal regions associated with craniosynostosis. The high incidence of pure duplications or trisomies suggests that these are important mechanisms in craniosynostosis, particularly in cases involving the metopic suture.

Gene expression profile analysis of primary glioblastomas and non-neoplastic brain tissue: identification of potential target genes by oligonucleotide microarray and real-time quantitative PCR

The prognosis of glioblastomas is still extremely poor and the discovery of novel molecular therapeutic targets can be important to optimize treatment strategies. Gene expression analyses comparing normal and neoplastic tissues have been used to identify genes associated with tumorigenesis and potential therapeutic targets. We have used this approach to identify differentially expressed genes between primary glioblastomas and non-neoplastic brain tissues. We selected 20 overexpressed genes related to cell cycle, cellular movement and growth, proliferation and cell-to-cell signaling and analyzed their expression levels by real time quantitative PCR in cDNA obtained from microdissected fresh tumor tissue from 20 patients with primary glioblastomas and from 10 samples of non-neoplastic white matter tissue. The gene expression levels were significantly higher in glioblastomas than in non-neoplastic white matter in 18 out of 20 genes analyzed: P < 0.00001 for CDKN2C, CKS2, EEF1A1, EMP3, PDPN, BNIP2, CA12, CD34, CDC42EP4, PPIE, SNAI2, GDF15 and MMP23b; and NFIA (P: 0.0001), GPS1 (P: 0.0003), LAMA1 (P: 0.002), STIM1 (P: 0.006), and TASP1 (P: 0.01). Five of these genes are located in contiguous loci at 1p31-36 and 2 at 17q24-25 and 8 of them encode surface membrane proteins. PDPN and CD34 protein expression were evaluated by immunohistochemistry and they showed concordance with the PCR results. The present results indicate the presence of 18 overexpressed genes in human primary glioblastomas that may play a significant role in the pathogenesis of these tumors and that deserve further functional investigation as attractive candidates for new therapeutic targets.

Analysis of the Nicotiana tabacum Stigma/Style Transcriptome Reveals Gene Expression Differences between Wet and Dry Stigma Species

The success of plant reproduction depends on pollen-pistil interactions occurring at the stigma/style. These interactions vary depending on the stigma type: wet or dry. Tobacco (Nicotiana tabacum) represents a model of wet stigma, and its stigmas/styles express genes to accomplish the appropriate functions. For a large-scale study of gene expression during tobacco pistil development and preparation for pollination, we generated 11,216 high-quality expressed sequence tags (ESTs) from stigmas/styles and created the TOBEST database. These ESTs were assembled in 6,177 clusters, from which 52.1% are pistil transcripts/genes of unknown function. The 21 clusters with the highest number of ESTs (putative higher expression levels) correspond to genes associated with defense mechanisms or pollen-pistil interactions. The database analysis unraveled tobacco sequences homologous to the Arabidopsis (Arabidopsis thaliana) genes involved in specifying pistil identity or determining normal pistil morphology and function. Additionally, 782 independent clusters were examined by macroarray, revealing 46 stigma/style preferentially expressed genes. Real-time reverse transcription-polymerase chain reaction experiments validated the pistil-preferential expression for nine out of 10 genes tested. A search for these 46 genes in the Arabidopsis pistil data sets demonstrated that only 11 sequences, with putative equivalent molecular functions, are expressed in this dry stigma species. The reverse search for the Arabidopsis pistil genes in the TOBEST exposed a partial overlap between these dry and wet stigma transcriptomes. The TOBEST represents the most extensive survey of gene expression in the stigmas/styles of wet stigma plants, and our results indicate that wet and dry stigmas/styles express common as well as distinct genes in preparation for the pollination process.

Grade II atypical choroid plexus papilloma with normal karyotype

Cytogenetic studies of atypical choroid plexus papillomas (CPP) have been poorly described. In the present report, the cytogenetic investigation of an atypical CPP occurring in an infant is detailed. CPP chromosome preparations were analyzed by giemsa-trypsin-banding (GTG-banding) and comparative genome hybridization (CGH). Conventional karyotype analysis of tumor culture showed a normal chromosome complement. The results were confirmed by CGH, showing normal hybridization patterns for the sample. To date, the few atypical CPPs described in the literature have shown disparate cytogenetic information. This is the first report of a normal chromosome complement in atypical CPP. The heterogenic genetic features observed in these small series may reflect the diverse genetic background of choroid plexus tumors in children.

Cell cycle and apoptosis in normal and cloned bovine near-term placentae

The bovine maternal epithelium is composed of cuboidal cells interspersed with low columnar cells having centrally located nuclei. Bovine trophoblast is composed of two cell types: mononuclear trophoblastic and giant trophoblastic cells that can have two or more nuclei. Number of apoptotic cells and proliferative cells are variable in both cell populations. This study compared tissue growth and apoptosis by flow cytometry in the cell population found at distinct placental regions (central region of placentomes, <= 1-cm microplacentomes and the interplacentomal region) between normal and cloned near-term bovine pregnancies. After a morphological comparison between regions and groups (controls vs. clones), a lesser proportion of diploid to tetraploid cells was observed in the central region of placentomes and in microplacentomes from cloned-derived pregnancies. In addition, cloned animals had a fewer apoptotic cells in the central region of the placentome and in interplacentomal region and a greater proliferative capacity in all regions (cells in G(2)/M) near term as opposed to control animals. These results may reveal the existence of a relationship between such changes in the proportions of uterine and trophoblastic epithelial cells at the end of pregnancy and normal placental function. This could be related to faulty placentation in early pregnancy, placental insufficiency during pregnancy or lack of placental and/or fetal maturation in late pregnancy, which may contribute to someof the abnormalities after in vitro embryo manipulations, such as poor preparation and initiation of parturition, prolonged gestation and lesser post-natal survival in some cloned animals. (C) 2008 Elsevier B.V. All rights reserved.

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.

Bayesian analysis of skew-t multivariate null intercept measurement error model

The multivariate skew-t distribution (J Multivar Anal 79:93-113, 2001; J R Stat Soc, Ser B 65:367-389, 2003; Statistics 37:359-363, 2003) includes the Student t, skew-Cauchy and Cauchy distributions as special cases and the normal and skew-normal ones as limiting cases. In this paper, we explore the use of Markov Chain Monte Carlo (MCMC) methods to develop a Bayesian analysis of repeated measures, pretest/post-test data, under multivariate null intercept measurement error model (J Biopharm Stat 13(4):763-771, 2003) where the random errors and the unobserved value of the covariate (latent variable) follows a Student t and skew-t distribution, respectively. The results and methods are numerically illustrated with an example in the field of dentistry.

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.

Bayesian analysis for a skew extension of the multivariate null intercept measurement error model

Skew-normal distribution is a class of distributions that includes the normal distributions as a special case. In this paper, we explore the use of Markov Chain Monte Carlo (MCMC) methods to develop a Bayesian analysis in a multivariate, null intercept, measurement error model [R. Aoki, H. Bolfarine, J.A. Achcar, and D. Leao Pinto Jr, Bayesian analysis of a multivariate null intercept error-in -variables regression model, J. Biopharm. Stat. 13(4) (2003b), pp. 763-771] where the unobserved value of the covariate (latent variable) follows a skew-normal distribution. The results and methods are applied to a real dental clinical trial presented in [A. Hadgu and G. Koch, Application of generalized estimating equations to a dental randomized clinical trial, J. Biopharm. Stat. 9 (1999), pp. 161-178].

Analysis of the combined effect of lasers of different wavelengths for PDT outcome using 600, 630, and 660 nm

We investigated the effects of photodynamic therapy (PDT) outcome when combining three laser systems that produce light in three different wavelengths (600, 630, and 660 nm). Cooperative as well as independent effects can be observed. We compared the results of the combined wavelengths of light with the effect of single laser for the excitation of the photosensitizer. In the current experiment, the used photosensitizer was Photogem (R) (1.5 mg/kg). Combining two wavelengths for PDT, their cumulative dose and different penetrability may change the overall effect of the fluence of light, which can be effective for increasing the depth of necrosis. This evaluation was performed by comparing the depth and specific aspect of necrosis obtained by using single and dual wavelengths for irradiation of healthy liver of male Wistar rats. We used 15 animals and divided them in five groups of three animals. First, Photogem (R) was administered; follow by measurement of the fluorescence spectrum of the liver before PDT to confirm the level of accumulation of photosensitizer in the tissue. After that, an area of 1 cm(2) of the liver was illuminated using different laser combinations. Qualitative analysis of the necrosis was carried out through histological and morphological study. [GRAPHICS] (a) - microscopic images of rat liver cells, (b) - superficial necrosis caused by PDT using dual-wavelength illumination, (c) - neutrophilic infiltration around the vessel inside the necrosis, and (d) - neutrophilic infiltration around the vessel between necrosis and live tissue (C) 2011 by Astro Ltd. Published exclusively by WILEY-VCH Verlag GmbH & Co. KGaA

Bayesian inference for a skew-normal IRT model under the centred parameterization

Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is interest in studying latent variables. These latent variables are directly considered in the Item Response Models (IRM) and they are usually called latent traits. A usual assumption for parameter estimation of the IRM, considering one group of examinees, is to assume that the latent traits are random variables which follow a standard normal distribution. However, many works suggest that this assumption does not apply in many cases. Furthermore, when this assumption does not hold, the parameter estimates tend to be biased and misleading inference can be obtained. Therefore, it is important to model the distribution of the latent traits properly. In this paper we present an alternative latent traits modeling based on the so-called skew-normal distribution; see Genton (2004). We used the centred parameterization, which was proposed by Azzalini (1985). This approach ensures the model identifiability as pointed out by Azevedo et al. (2009b). Also, a Metropolis Hastings within Gibbs sampling (MHWGS) algorithm was built for parameter estimation by using an augmented data approach. A simulation study was performed in order to assess the parameter recovery in the proposed model and the estimation method, and the effect of the asymmetry level of the latent traits distribution on the parameter estimation. Also, a comparison of our approach with other estimation methods (which consider the assumption of symmetric normality for the latent traits distribution) was considered. The results indicated that our proposed algorithm recovers properly all parameters. Specifically, the greater the asymmetry level, the better the performance of our approach compared with other approaches, mainly in the presence of small sample sizes (number of examinees). Furthermore, we analyzed a real data set which presents indication of asymmetry concerning the latent traits distribution. The results obtained by using our approach confirmed the presence of strong negative asymmetry of the latent traits distribution. (C) 2010 Elsevier B.V. All rights reserved.

Bayesian Analysis for Nonlinear Regression Model Under Skewed Errors, with Application in Growth Curves

We have considered a Bayesian approach for the nonlinear regression model by replacing the normal distribution on the error term by some skewed distributions, which account for both skewness and heavy tails or skewness alone. The type of data considered in this paper concerns repeated measurements taken in time on a set of individuals. Such multiple observations on the same individual generally produce serially correlated outcomes. Thus, additionally, our model does allow for a correlation between observations made from the same individual. We have illustrated the procedure using a data set to study the growth curves of a clinic measurement of a group of pregnant women from an obstetrics clinic in Santiago, Chile. Parameter estimation and prediction were carried out using appropriate posterior simulation schemes based in Markov Chain Monte Carlo methods. Besides the deviance information criterion (DIC) and the conditional predictive ordinate (CPO), we suggest the use of proper scoring rules based on the posterior predictive distribution for comparing models. For our data set, all these criteria chose the skew-t model as the best model for the errors. These DIC and CPO criteria are also validated, for the model proposed here, through a simulation study. As a conclusion of this study, the DIC criterion is not trustful for this kind of complex model.

Bayesian density estimation using Skew Student-t-Normal mixtures

We present a Bayesian approach for modeling heterogeneous data and estimate multimodal densities using mixtures of Skew Student-t-Normal distributions [Gomez, H.W., Venegas, O., Bolfarine, H., 2007. Skew-symmetric distributions generated by the distribution function of the normal distribution. Environmetrics 18, 395-407]. A stochastic representation that is useful for implementing a MCMC-type algorithm and results about existence of posterior moments are obtained. Marginal likelihood approximations are obtained, in order to compare mixture models with different number of component densities. Data sets concerning the Gross Domestic Product per capita (Human Development Report) and body mass index (National Health and Nutrition Examination Survey), previously studied in the related literature, are analyzed. (c) 2008 Elsevier B.V. All rights reserved.