Emplacement mechanism of the main granite pluton of the Lavras do Sul intrusive complex, South Brazil, determined by magnetic anisotropies

Magnetic fabric and rock magnetism studies were performed on apparently isotropic granite facies from the main intrusion of the Lavras do Sul Intrusive Complex pluton (LSIC, Rio Grande do Sul, South Brazil). This intrusion is roughly circular (similar to 12 x 13.5 km), composed of alkali-calcic and alkaline granitoids, with the latter occupying the margin of the pluton. Magnetic fabrics were determined by applying both anisotropy of low-field magnetic susceptibility (AMS) and anisotropy of anhysteretic remanent magnetization (AARM). The two fabrics are coaxial. The parallelism between AMS and AARM tensors excludes the presence of a single domain (SD) effect on the AMS fabric of the granites. Several rock-magnetism experiments performed in one specimen from each sampled site show that for all sites the magnetic susceptibility is dominantly carried by ferromagnetic minerals, while mainly magnetite carries the magnetic fabrics. Lineations and foliations in the granite facies were successful determined by applying magnetic methods. Magnetic lineations are gently plunging and roughly parallel to the boundaries of the pluton facies, except at the few sites in the central facies which have a radial orientation pattern. In contrast, the magnetic foliations tend to follow the contacts between the different granite facies. They are gently outerward-dipping inside the pluton, and become either steeply southwesterly dipping or vertical towards its margin. The lack of solid-state and subsolidus deformations at outcrop scale and in thin sections precludes deformation after full crystallization of the pluton. This evidence allows us to interpret the observed magnetic fabrics as primary in origin (magmatic) acquired when the rocks were solidified as a result of processes reflecting magma flow. The foliation pattern displays a dome-shaped form for the main LSIC-pluton. However, the alkaline granites which outcrop in the southern part of the studied area have an inward-dipping foliation, and the steeply plunging magnetic lineation suggests that this area could be part of a feeder zone. The magma ascent probably occurred due to ring-diking. (C) 2008 Elsevier B.V. All rights reserved.

Improved likelihood inference for the shape parameter in Weibull regression

We obtain adjustments to the profile likelihood function in Weibull regression models with and without censoring. Specifically, we consider two different modified profile likelihoods: (i) the one proposed by Cox and Reid [Cox, D.R. and Reid, N., 1987, Parameter orthogonality and approximate conditional inference. Journal of the Royal Statistical Society B, 49, 1-39.], and (ii) an approximation to the one proposed by Barndorff-Nielsen [Barndorff-Nielsen, O.E., 1983, On a formula for the distribution of the maximum likelihood estimator. Biometrika, 70, 343-365.], the approximation having been obtained using the results by Fraser and Reid [Fraser, D.A.S. and Reid, N., 1995, Ancillaries and third-order significance. Utilitas Mathematica, 47, 33-53.] and by Fraser et al. [Fraser, D.A.S., Reid, N. and Wu, J., 1999, A simple formula for tail probabilities for frequentist and Bayesian inference. Biometrika, 86, 655-661.]. We focus on point estimation and likelihood ratio tests on the shape parameter in the class of Weibull regression models. We derive some distributional properties of the different maximum likelihood estimators and likelihood ratio tests. The numerical evidence presented in the paper favors the approximation to Barndorff-Nielsen`s adjustment.

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].

Epsilon Birnbaum-Saunders distribution family: properties and inference

In this paper we introduce a new extension for the Birnbaum-Saunder distribution based on the family of the epsilon-skew-symmetric distributions studied in Arellano-Valle et al. (J Stat Plan Inference 128(2):427-443, 2005). The extension allows generating Birnbaun-Saunders type distributions able to deal with extreme or outlying observations (Dupuis and Mills, IEEE Trans Reliab 47:88-95, 1998). Basic properties such as moments and Fisher information matrix are also studied. Results of a real data application are reported illustrating good fitting properties of the proposed model.

Improved likelihood inference in beta regression

We consider the issue of performing accurate small-sample likelihood-based inference in beta regression models, which are useful for modelling continuous proportions that are affected by independent variables. We derive small-sample adjustments to the likelihood ratio statistic in this class of models. The adjusted statistics can be easily implemented from standard statistical software. We present Monte Carlo simulations showing that inference based on the adjusted statistics we propose is much more reliable than that based on the usual likelihood ratio statistic. A real data example is presented.

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.

Missing data mechanisms and their implications on the analysis of categorical data

We review some issues related to the implications of different missing data mechanisms on statistical inference for contingency tables and consider simulation studies to compare the results obtained under such models to those where the units with missing data are disregarded. We confirm that although, in general, analyses under the correct missing at random and missing completely at random models are more efficient even for small sample sizes, there are exceptions where they may not improve the results obtained by ignoring the partially classified data. We show that under the missing not at random (MNAR) model, estimates on the boundary of the parameter space as well as lack of identifiability of the parameters of saturated models may be associated with undesirable asymptotic properties of maximum likelihood estimators and likelihood ratio tests; even in standard cases the bias of the estimators may be low only for very large samples. We also show that the probability of a boundary solution obtained under the correct MNAR model may be large even for large samples and that, consequently, we may not always conclude that a MNAR model is misspecified because the estimate is on the boundary of the parameter space.

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.

Improved likelihood inference in Birnbaum-Saunders regressions

The Birnbaum-Saunders regression model is commonly used in reliability studies. We address the issue of performing inference in this class of models when the number of observations is small. Our simulation results suggest that the likelihood ratio test tends to be liberal when the sample size is small. We obtain a correction factor which reduces the size distortion of the test. Also, we consider a parametric bootstrap scheme to obtain improved critical values and improved p-values for the likelihood ratio test. The numerical results show that the modified tests are more reliable in finite samples than the usual likelihood ratio test. We also present an empirical application. (C) 2009 Elsevier B.V. All rights reserved.

Properties and Inference on the Skew-Curved-Symmetric Family of Distributions

In this article, we study some results related to a specific class of distributions, called skew-curved-symmetric family of distributions that depends on a parameter controlling the skewness and kurtosis at the same time. Special elements of this family which are studied include symmetric and well-known asymmetric distributions. General results are given for the score function and the observed information matrix. It is shown that the observed information matrix is always singular for some special cases. We illustrate the flexibility of this class of distributions with an application to a real dataset on characteristics of Australian athletes.

Improved testing inference in mixed linear models

Mixed linear models are commonly used in repeated measures studies. They account for the dependence amongst observations obtained from the same experimental unit. Often, the number of observations is small, and it is thus important to use inference strategies that incorporate small sample corrections. In this paper, we develop modified versions of the likelihood ratio test for fixed effects inference in mixed linear models. In particular, we derive a Bartlett correction to such a test, and also to a test obtained from a modified profile likelihood function. Our results generalize those in [Zucker, D.M., Lieberman, O., Manor, O., 2000. Improved small sample inference in the mixed linear model: Bartlett correction and adjusted likelihood. Journal of the Royal Statistical Society B, 62,827-838] by allowing the parameter of interest to be vector-valued. Additionally, our Bartlett corrections allow for random effects nonlinear covariance matrix structure. We report simulation results which show that the proposed tests display superior finite sample behavior relative to the standard likelihood ratio test. An application is also presented and discussed. (C) 2008 Elsevier B.V. All rights reserved.

Inhibition of myeloperoxidase-mediated protein nitration by tempol: Kinetics, mechanism, and implications

Despite the therapeutic potential of tempol (4-hydroxy-2,2,6,6-tetra-methyl-1-piperidinyloxy) and related nitroxides as antioxidants, their effects on peroxidase-mediated protein tyrosine nitration remain unexplored. This posttranslational protein modification is a biomarker of nitric oxide-derived oxidants, and, relevantly, it parallels tissue injury in animal models of inflammation and is attenuated by tempol treatment. Here, we examine tempol effects on ribonuclease (RNase) nitration mediated by myeloperoxidase (MPO), a mammalian enzyme that plays a central role in various inflammatory processes.. Some experiments were also performed with horseradish peroxidase (HRP). We show that tempol efficiently inhibits peroxidase-mediated RNase nitration. For instance, 10 mu M tempol was able to inhibit by 90% the yield of 290 mu M 3-nitrotyrosine produced from 370 mu M RNase. The effect of tempol was not completely catalytic because part of it was consumed by recombination with RNase-tyrosyl radicals. The second-order rate constant of the reaction of tempol with MPO compound I and 11 were determined by stopped-flow kinetics as 3.3 x 10(6) and 2.6 x 10(4) M-1 s(-1), respectively (pH 7.4, 25 degrees C); the corresponding HRP constants were orders of magnitude smaller. Time-dependent hydrogen peroxide and nitrite consumption and oxygen production in the incubations were quantified experimentally and modeled by kinetic simulations. The results indicate that tempol inhibits peroxidase-mediated RNase nitration mainly because of its reaction with nitrogen dioxide to produce the oxammonium cation, which, in turn, recycles back to tempol by reacting with hydrogen peroxide and superoxide radical to produce oxygen and regenerate nitrite. The implications for nitroxide antioxidant mechanisms are discussed.

Insights into the mechanism of progressive RNA degradation by the archaeal exosome

Initially identified in yeast, the exosome has emerged as a central component of the RNA maturation and degradation machinery both in Archaea and eukaryotes. Here we describe a series of high-resolution structures of the RNase PH ring from the Pyrococcus abyssi exosome, one of them containing three 10-mer RNA strands within the exosome catalytic chamber, and report additional nucleotide interactions involving positions N5 and N7. Residues from all three Rrp41-Rrp42 heterodimers interact with a single RNA molecule, providing evidence for the functional relevance of exosome ring-like assembly in RNA processivity. Furthermore, an ADP-bound structure showed a rearrangement of nucleotide interactions at site N1, suggesting a rationale for the elimination of nucleoside diphosphate after catalysis. In combination with RNA degradation assays performed with mutants of key amino acid residues, the structural data presented here provide support for a model of exosome-mediated RNA degradation that integrates the events involving catalytic cleavage, product elimination, and RNA translocation. Finally, comparisons between the archaeal and human exosome structures provide a possible explanation for the eukaryotic exosome inability to catalyze phosphate-dependent RNA degradation.

Inhibition Mechanism of Rat alpha(3)beta(4) Nicotinic Acetylcholine Receptor by the Alzheimer Therapeutic Tacrine

Nicotinic acetylcholine receptors (nAChRs) were studied in detail in the past regarding their interaction with therapeutic and drug addiction related compounds. Using fast kinetic whole-cell recording, we have now studied effects of tacrine, an agent used clinically to treat Alzheimer`s disease, on currents elicited by activation of rat alpha(3)beta(4) nAChR heterologously expressed in KX alpha(3)beta(4)R2 cells. Characterization of receptor activation by nicotine used as agonist revealed a K(d) of 23 +/- 0.2 mu M and 4.3 +/- 1.3 for the channel opening equilibrium constant, Phi(-1). Experiments were performed to investigate whether tacrine is able to activate the alpha(3)beta(4) nAChR. Tacrine did not activate whole-cell currents in KX alpha(3)beta(4)R2 cells but inhibited receptor activity at submicromolar concentration. Dose response curves obtained with increasing agonist or inhibitor concentration revealed competitive inhibition of nAChRs by tacrine, with an apparent inhibition constant, K(I), of 0.8 mu M. The increase of Phi(-1) in the presence of tacrine suggests that the drug stabilizes a nonconducting open channel form of the receptor. Binding studies with TCP and MK-801 ruled out tacrine binding to common allosteric sites of the receptor. Our study suggests a novel mechanism for action of tacrine on nAChRs besides inhibition of acetylcholine esterase.

Nanoparticle Platform to Modulate Reaction Mechanism of Phenothiazine Photosensitizers

Herein, we report on the synthesis of photosensitizing nanoparticles in which the generation of different oxidizing species, i.e., singlet oxygen ((1)O(2)) or radicals, was modulated. Sol gel and surface chemistry were used to obtain nanoparticles with specific ratios of dimer to monomer species of phenothiazine photosensitizers (PSs). Due to competition between the reactions involving electron transfer within dimer species and energy transfer from monomer triplets to oxygen, the efficiency of (1)O(2) generation could be controlled. Nanoparticles with an excess of dimer have an (1)O(2) generation efficiency (S(Delta)) of 0.01 while those without dimer have a S, value of 0.4. Furthermore, we demonstrate that the PS properties of the nanoparticles are not subjected to interference from the external medium as is commonly the case for free PSs, i.e., PS ground and triplet states are not reduced by NADH and ascorbate, respectively, and singlet excited states are less suppressed by bromide. The modulated (1)O(2) generation and the PS protection from external interferences make this nanoparticle platform a promising tool to aid in performing mechanistic studies in biological systems. Also, it offers potential application in technological areas in which photo-induced processes take place.