Paullinia cupana Mart. var. sorbilis, Guarana, Increases Survival of Ehrlich Ascites Carcinoma (EAC) Bearing Mice by Decreasing Cyclin-D1 Expression and Inducing a G0/G1 Cell Cycle Arrest in EAC Cells

The objective of this work is to report the antiproliferative effect of P. cupana treatment in Ehrlich Ascites Carcinoma (EAC)-bearing animals. Female mice were treated with three doses of powdered P. cupana (100, 1000 and 2000 mg/kg) for 7 days, injected with 10(5) EAC cells and treated up to day 21. In addition, a survival experiment was carried out with the same protocol. P. cupana decreased the ascites volume (p = 0.0120), cell number (p = 0.0004) and hemorrhage (p = 0.0054). This occurred through a G1-phase arrest (p < 0.01) induced by a decreased gene expression of Cyclin D1 in EAC cells. Furthermore, P. cupana significantly increased the survival of EAC-bearing animals (p = 0.0012). In conclusion, the P. cupana growth control effect in this model was correlated with a decreased expression of cyclin D1 and a G1 phase arrest. These results reinforce the cancer therapeutic potential of this Brazilian plant. Copyright (C) 2010 John Wiley & Sons, Ltd.

Vivipary in Alternanthera littoralis var. maritima - first record for the Amaranthaceae

This first record of vivipary in the Amaranthaceae is reported for the foredune plant Alternanthera littoralis var. maritima (July 2008, northern coast of Brazil). Vivipary is the precocious and uninterrupted growth of the seedlings while still attached to the maternal body. We propose a hypothesis for the viviparous germination of this species based on field observations. Our record adds new perspectives to the reproductive biology of the Amaranthaceae.

Germination and survival of tetraspores of Kappaphycus alvarezii var. alvarezii (Solieriaceae, Rhodophyta) introduced in subtropical waters of Brazil

The carrageenophyte Kappaphycus alvarezii was introduced in 1995 and vegetatively propagated in Ubatuba, Sao Paulo State, Brazil, for the purpose of commercial cultivation. This species produces tetraspores mainly in the austral summer and fall. Tetraspore germination and survival were studied under different conditions of temperature, photon flux density, and photoperiod in the laboratory. Field experiments were also carried out. Although tetraspores of K. alvarezii germinated, they had low survival rates, most dying after 20 days. Recruitment of K. alvarezii tetraspores did not occur in experiments conducted in the field. The results indicated that the establishment of K. alvarezii via spore production in the natural environment of the south-east coast of Brazil is rather remote.

The South American Plasmodium falciparum var gene repertoire is limited, highly shared and possibly lacks several antigenic types

The Plasmodium falciparum var gene family encodes large variant antigens, which are important virulence factors, and also targets of the humoral host response. The frequently observed mild outcomes of falciparum malaria in many places of the Amazon area prompted us to ask whether a globally restricted variant (var) gene repertoire is present in currently circulating and older isolates of this area. By exhaustive analysis of var gene tags from 89 isolates and clones taken during many years from all over the Brazilian Amazon, we estimate that there are probably no more than 350-430 distinct sequence types, less than for any similar sized area studied so far. Detailed analysis of the var tags from genetically distinct clones obtained from single isolates revealed restricted and redundant repertoires suggesting either a low incidence of infective bites or restricted variant gene diversity in inoculated parasites. Additionally, we found a structuring of var gene repertoires observed as a higher pairwise typing sharing in isolates from the same microregion compared to isolates from different regions. Fine analysis of translated var tags revealed that certain Distinct Sequence Identifiers (DSIDs) were differently represented in Brazilian/South American isolates when compared to datasets from other continents. By global alignment of worldwide var DBL alpha sequences and sorting in groups with more than 76% identity, 125 clusters were formed and more than half of all genes were found in nine clusters with 50 or more sequences. While Brazilian/South American sequences were represented only in 64 groups, African sequences were found in the majority of clusters. DSID type 1 related sequences accumulated almost completely in one single cluster, indicating that limited recombination occurs in these specific var gene types. These data demonstrate the so far highest pairwise type sharing values for the var gene family in isolates from all over an entire subcontinent. The apparent lack of specific sequences types suggests that the P. falciparum transmission dynamics in the whole Amazon are probably different from any other endemic region studied and possibly interfere with the parasite`s ability to efficiently diversify its variant gene repertoires. (C) 2010 Elsevier B.V. All rights reserved.

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.

Hypotheses Testing on a Multivariate Null Intercept Errors-in-Variables Model

Considering the Wald, score, and likelihood ratio asymptotic test statistics, we analyze a multivariate null intercept errors-in-variables regression model, where the explanatory and the response variables are subject to measurement errors, and a possible structure of dependency between the measurements taken within the same individual are incorporated, representing a longitudinal structure. This model was proposed by Aoki et al. (2003b) and analyzed under the bayesian approach. In this article, considering the classical approach, we analyze asymptotic test statistics and present a simulation study to compare the behavior of the three test statistics for different sample sizes, parameter values and nominal levels of the test. Also, closed form expressions for the score function and the Fisher information matrix are presented. We consider two real numerical illustrations, the odontological data set from Hadgu and Koch (1999), and a quality control data set.

Improved maximum likelihood estimators in a heteroskedastic errors-in-variables model

This paper develops a bias correction scheme for a multivariate heteroskedastic errors-in-variables model. The applicability of this model is justified in areas such as astrophysics, epidemiology and analytical chemistry, where the variables are subject to measurement errors and the variances vary with the observations. We conduct Monte Carlo simulations to investigate the performance of the corrected estimators. The numerical results show that the bias correction scheme yields nearly unbiased estimates. We also give an application to a real data set.

A multivariate ultrastructural errors-in-variables model with equation error

This paper deals with asymptotic results on a multivariate ultrastructural errors-in-variables regression model with equation errors Sufficient conditions for attaining consistent estimators for model parameters are presented Asymptotic distributions for the line regression estimators are derived Applications to the elliptical class of distributions with two error assumptions are presented The model generalizes previous results aimed at univariate scenarios (C) 2010 Elsevier Inc 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.

Influence diagnostics for linear models with first-order autoregressive elliptical errors

We introduce in this paper the class of linear models with first-order autoregressive elliptical errors. The score functions and the Fisher information matrices are derived for the parameters of interest and an iterative process is proposed for the parameter estimation. Some robustness aspects of the maximum likelihood estimates are discussed. The normal curvatures of local influence are also derived for some usual perturbation schemes whereas diagnostic graphics to assess the sensitivity of the maximum likelihood estimates are proposed. The methodology is applied to analyse the daily log excess return on the Microsoft whose empirical distributions appear to have AR(1) and heavy-tailed errors. (C) 2008 Elsevier B.V. All rights reserved.

Hypothesis testing in an errors-in-variables model with heteroscedastic measurement errors

In many epidemiological studies it is common to resort to regression models relating incidence of a disease and its risk factors. The main goal of this paper is to consider inference on such models with error-prone observations and variances of the measurement errors changing across observations. We suppose that the observations follow a bivariate normal distribution and the measurement errors are normally distributed. Aggregate data allow the estimation of the error variances. Maximum likelihood estimates are computed numerically via the EM algorithm. Consistent estimation of the asymptotic variance of the maximum likelihood estimators is also discussed. Test statistics are proposed for testing hypotheses of interest. Further, we implement a simple graphical device that enables an assessment of the model`s goodness of fit. Results of simulations concerning the properties of the test statistics are reported. The approach is illustrated with data from the WHO MONICA Project on cardiovascular disease. Copyright (C) 2008 John Wiley & Sons, Ltd.

Wavelet regression with correlated errors on a piecewise Holder class

This paper generalizes the methodology of Cat and Brown [Cai, T., Brown, L.D., 1998. Wavelet shrinkage for nonequispaced samples. The Annals of Statistics 26, 1783-1799] for wavelet shrinkage for nonequispaced samples, but in the presence of correlated stationary Gaussian errors. If the true function is a member of a piecewise Holder class, it is shown that, even for long memory errors, the rate of convergence of the procedure is almost-minimax relative to the independent and identically distributed errors case. (c) 2008 Elsevier B.V. All rights reserved.

A new class of survival regression models with heavy-tailed errors: robustness and diagnostics

Birnbaum-Saunders models have largely been applied in material fatigue studies and reliability analyses to relate the total time until failure with some type of cumulative damage. In many problems related to the medical field, such as chronic cardiac diseases and different types of cancer, a cumulative damage caused by several risk factors might cause some degradation that leads to a fatigue process. In these cases, BS models can be suitable for describing the propagation lifetime. However, since the cumulative damage is assumed to be normally distributed in the BS distribution, the parameter estimates from this model can be sensitive to outlying observations. In order to attenuate this influence, we present in this paper BS models, in which a Student-t distribution is assumed to explain the cumulative damage. In particular, we show that the maximum likelihood estimates of the Student-t log-BS models attribute smaller weights to outlying observations, which produce robust parameter estimates. Also, some inferential results are presented. In addition, based on local influence and deviance component and martingale-type residuals, a diagnostics analysis is derived. Finally, a motivating example from the medical field is analyzed using log-BS regression models. Since the parameter estimates appear to be very sensitive to outlying and influential observations, the Student-t log-BS regression model should attenuate such influences. The model checking methodologies developed in this paper are used to compare the fitted models.

Withanolides from Aureliana fasciculata var. fasciculata

In the first phytochemical study of the Aureliana genus (Solanaceae), two new withanolides, 1 and 2, together with two known sterols, were isolated from the MeOH extract of the leaves of Aureliana fasciculata var. fasciculata. The structures were established as (4S,22R)-16 alpha-acetoxy-5 beta,6 beta-epoxy-4 beta,17 alpha-dihydroxy-1-oxowitha-2,24-dienolide (aurelianolide A) and (4S,22R)-16 alpha-acetoxy-4 beta,17 alpha-dihydroxy-1-oxowitha-2,5,24-trienolide (aurelianolide B). The new compounds possessed the unusual 16 alpha,17 alpha-dioxygenated group and were fully characterized by spectroscopic techniques, including (1)H- and (13)C-NMR (DEPT), as well as 2D-NMR (HMBC, HMQC, (1)H, (1)H-COSY, NOESY) experiments, and HR-MS.