Aluminum as an endocrine disruptor in female Nile tilapia (Oreochromis niloticus)

The effects of aluminum on plasma ion, lipid, protein and steroid hormone concentration were evaluated in Oreochromis niloticus broodstock females. Lipid and protein concentrations from the gonads and liver were also measured Experiments were performed at neutral and acidic water pH Four groups of fish were tested for 96 h. 1) control conditions at neutral water pH, 2) control conditions at acidic water pH (CTR-Ac). 3) aluminum at neutral water pH (Al-N), and 4) aluminum at acidic water pH (Al-Ac) Aluminum and acidic water pH exposure caused no ionoregulatory disturbances Total lipid concentration increased in the mature gonads and decreased in the liver, suggesting an acceleration of lipid mobilization to the ovaries in animals exposed to aluminum However, a decreased protein concentration in ovaries was also observed Exposure of control fish to acidic water pH caused an increased concentration of plasma 17 alpha-hydroxyprogesterone However, females exposed to aluminum at acidic water pH showed a decreased of plasma 17 alpha-hydroxyprogesterone and cortisol. No differences in plasma 17 beta-estradiol were observed The physiological mechanisms underlying the disturbances observed are discussed focusing on reproduction We suggest that aluminum can be considered an endocrine disrupting compound in mature O. mloticus females (C) 2010 Elsevier Inc. All rights reserved

Pharmacological properties of purinergic receptors and their effects on proliferation and induction of neuronal differentiation of P19 embryonal carcinoma cells

We have used P19 embryonal carcinoma cells as in vitro model for early neurogenesis to study ionotropic P2X and metabotropic P2Y receptor-induced Ca2+ transients and their participation in induction of proliferation and differentiation. In embryonic P19 cells, P2Y(1), P2Y(2) and P2X(4) receptors or P2X-heteromultimers with similar P2X4 pharmacology were responsible for ATP and ATP analogue-induced Ca2+ transients. In neuronal-differentiated cells, P2Y(2), P2Y(6), P2X(2) and possibly P2X(2)/P2X(6) heteromeric receptors were the major mediators of the elevations in intracellular free calcium concentration [Ca2+](i). We have collected evidence for the involvement of metabotropic purinergic receptors in proliferation induction of undifferentiated and neural progenitor cells by using a BrdU-incorporation assay. ATP-, UTP-, ADP-, 2-MeS-ATP- and ADP-beta S-induced proliferation in P19 cells was mediated by P2Y, and P2Y2 receptors as judged from pharmacological profiles of receptor responses. ATP-provoked acceleration of neuronal differentiation, determined by analysis of nestin and neuron-specific enolase gene and protein expression, also resulted from P2Y, and P2Y2 receptor activation. Proliferation- and differentiation-induction involved the activation of inositol-trisphosphate sensitive intracellular Ca2+ stores. (C) 2008 ISDN. Published by Elsevier Ltd. 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.

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.

Generalized log-gamma regression models with cure fraction

In this paper, the generalized log-gamma regression model is modified to allow the possibility that long-term survivors may be present in the data. This modification leads to a generalized log-gamma regression model with a cure rate, encompassing, as special cases, the log-exponential, log-Weibull and log-normal regression models with a cure rate typically used to model such data. The models attempt to simultaneously estimate the effects of explanatory variables on the timing acceleration/deceleration of a given event and the surviving fraction, that is, the proportion of the population for which the event never occurs. The normal curvatures of local influence are derived under some usual perturbation schemes and two martingale-type residuals are proposed to assess departures from the generalized log-gamma error assumption as well as to detect outlying observations. Finally, a data set from the medical area is analyzed.

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].

Correlation of the highest-energy cosmic rays with the positions of nearby active galactic nuclei

Data collected by the Pierre Auger Observatory provide evidence for anisotropy in the arrival directions of the cosmic rays with the highest-energies, which are correlated with the positions of relatively nearby active galactic nuclei (AGN) [Pierre Auger Collaboration, Science 318 (2007) 938]. The correlation has maximum significance for cosmic rays with energy greater than similar to 6 x 10(19) eV and AGN at a distance less than similar to 75 Mpc. We have confirmed the anisotropy at a confidence level of more than 99% through a test with parameters specified a priori, using an independent data set. The observed correlation is compatible with the hypothesis that cosmic rays with the highest-energies originate from extra-galactic sources close enough so that their flux is not significantly attenuated by interaction with the cosmic background radiation (the Greisen-Zatsepin-Kuz`min effect). The angular scale of the correlation observed is a few degrees, which suggests a predominantly light composition unless the magnetic fields are very weak outside the thin disk of our galaxy. Our present data do not identify AGN as the sources of cosmic rays unambiguously, and other candidate sources which are distributed as nearby AGN are not ruled out. We discuss the prospect of unequivocal identification of individual sources of the highest-energy cosmic rays within a few years of continued operation of the Pierre Auger Observatory. (C) 2008 Elsevier B.V. All rights reserved.

Velocity-dependent KAM islands

We revisit the non-dissipative time-dependent annular billiard and we consider the chaotic dynamics in two planes of conjugate variables in order to describe the behavior of the growth, or saturation, of the mean velocity of an ensemble of particles. We observed that the changes in the 4-d phase space occur without changing any parameter. They occur depending on where the initial conditions start. The emerging KAM islands interfere in the behavior of the particle dynamics especially in the Fermi acceleration mechanism. We show that Fermi acceleration can be suppressed, without dissipation, even considering the non-dissipative energy context. (C) 2011 Published by Elsevier Ltd.

Three-Color Entanglement

Entanglement is an essential quantum resource for the acceleration of information processing as well as for sophisticated quantum communication protocols. Quantum information networks are expected to convey information from one place to another by using entangled light beams. We demonstrated the generation of entanglement among three bright beams of light, all of different wavelengths (532.251, 1062.102, and 1066.915 nanometers). We also observed disentanglement for finite channel losses, the continuous variable counterpart to entanglement sudden death.

Anisotropy and chemical composition of ultra-high energy cosmic rays using arrival directions measured by the Pierre Auger Observatory

The Pierre Auger Collaboration has reported. evidence for anisotropy in the distribution of arrival directions of the cosmic rays with energies E > E(th) = 5.5 x 10(19) eV. These show a correlation with the distribution of nearby extragalactic objects, including an apparent excess around the direction of Centaurus A. If the particles responsible for these excesses at E > E(th) are heavy nuclei with charge Z, the proton component of the sources should lead to excesses in the same regions at energies E/Z. We here report the lack of anisotropies in these directions at energies above E(th)/Z (for illustrative values of Z = 6, 13, 26). If the anisotropies above E(th) are due to nuclei with charge Z, and under reasonable assumptions about the acceleration process, these observations imply stringent constraints on the allowed proton fraction at the lower energies.

The stability and aggregation properties of the GTPase domain from human SEPT4

The septins are a family of conserved proteins involved in cytokinesis and cortical organization. An increasing amount of data implicates different septins in diverse pathological conditions including neurodegenerative disorders, neoplasia and infections. Human SEPT4 is a member of this family and its tissue-specific ectopic expression profile in colorectal and urologic cancer makes it a useful diagnostic biomarker. Thermal unfolding of the GTPase domain of SEPT4 (SEPT4-G) revealed an unfolding intermediate which rapidly aggregates into amyloid-like fibers under physiological conditions. In this study, we examined the effects of protein concentration, pH and metals ions on the aggregation process of recombinant SEPT4-G using a series of biophysical techniques, which were also employed to study chemical unfolding and stability. Divalent metal ions caused significant acceleration to the rate of SEPT4-G aggregation. Urea induced unfolding was shown to proceed via the formation of a partially unfolded intermediate state which unfolds further at higher urea concentrations. The intermediate is a compact dimer which is unable to bind GTR At 1 M urea concentration, the intermediate state was plagued by irreversible aggregation at temperatures above 30 degrees C. However, higher urea concentration resulted in a marked decay of the aggregation, indicating that the partially folded structures may be necessary for the formation of these aggregates. The results presented here are consistent with the recently determined crystal structure of human septins and shed light on the aggregation properties of SEPT4 pertinent to its involvement in neurodegenerative disease. (C) 2008 Elsevier B.V. All rights reserved.

Inference and local influence assessment in skew-normal null intercept measurement error model

In this article, we discuss inferential aspects of the measurement error regression models with null intercepts when the unknown quantity x (latent variable) follows a skew normal distribution. We examine first the maximum-likelihood approach to estimation via the EM algorithm by exploring statistical properties of the model considered. Then, the marginal likelihood, the score function and the observed information matrix of the observed quantities are presented allowing direct inference implementation. In order to discuss some diagnostics techniques in this type of models, we derive the appropriate matrices to assessing the local influence on the parameter estimates under different perturbation schemes. The results and methods developed in this paper are illustrated considering part of a real data set used by Hadgu and Koch [1999, Application of generalized estimating equations to a dental randomized clinical trial. Journal of Biopharmaceutical Statistics, 9, 161-178].

On the Skew-Normal-Cauchy Distribution

In this article, we study further properties of a skew normal distribution, called the skew-normal-Cauchy (SNC) distribution by Nadarajah and Kotz (2003). A stochastic representation is obtained which allows alternative derivations for moments, moments generating function, and skewness and kurtosis coefficients. Issues related to singularity of the Fisher information matrix are investigated.

Inference for a skew extension of the Grubbs model

In this paper, we discuss inferential aspects for the Grubbs model when the unknown quantity x (latent response) follows a skew-normal distribution, extending early results given in Arellano-Valle et al. (J Multivar Anal 96:265-281, 2005b). Maximum likelihood parameter estimates are computed via the EM-algorithm. Wald and likelihood ratio type statistics are used for hypothesis testing and we explain the apparent failure of the Wald statistics in detecting skewness via the profile likelihood function. The results and methods developed in this paper are illustrated with a numerical example.