Immune Evasion of Leptospira Species by Acquisition of Human Complement Regulator C4BP

Leptospirosis is a spirochetal zoonotic disease of global distribution with a high incidence in tropical regions. In the last 15 years it has been recognized as an important emerging infectious disease due to the occurrence of large outbreaks in warm-climate countries and, occasionally, in temperate regions. Pathogenic leptospires efficiently colonize target organs after penetrating the host. Their invasiveness is attributed to the ability to multiply in blood, adhere to host cells, and penetrate into tissues. Therefore, they must be able to evade the innate host defense. The main purpose of the present study was to evaluate how several Leptospira strains evade the protective function of the complement system. The serum resistance of six Leptospira strains was analyzed. We demonstrate that the pathogenic strain isolated from infected hamsters avoids serum bactericidal activity more efficiently than the culture-attenuated or the nonpathogenic Leptospira strains. Moreover, both the alternative and the classical pathways of complement seem to be responsible for the killing of leptospires. Serum-resistant and serum-intermediate strains are able to bind C4BP, whereas the serum-sensitive strain Patoc I is not. Surface-bound C4BP promotes factor I-mediated cleavage of C4b. Accordingly, we found that pathogenic strains displayed reduced deposition of the late complement components C5 to C9 upon exposure to serum. We conclude that binding of C4BP contributes to leptospiral serum resistance against host complement.

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.

Local influence for Student-t partially linear models

In this paper we extend partial linear models with normal errors to Student-t errors Penalized likelihood equations are applied to derive the maximum likelihood estimates which appear to be robust against outlying observations in the sense of the Mahalanobis distance In order to study the sensitivity of the penalized estimates under some usual perturbation schemes in the model or data the local influence curvatures are derived and some diagnostic graphics are proposed A motivating example preliminary analyzed under normal errors is reanalyzed under Student-t errors The local influence approach is used to compare the sensitivity of the model estimates (C) 2010 Elsevier B V All rights reserved

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.