A real-time polymerase chain reaction assay for the identification and quantification of American Leishmania species on the basis of glucose-6-phosphate dehydrogenase

A real-time polymerase chain reaction (PCR) test was developed on the basis of the Leishmania glucose-6-phosphate dehydrogenase locus that enables identification and quantification of parasites. Using two independent pairs of primers in SYBR-Green assays, the test identified etiologic agents of cutaneous leishmaniasis belonging to both subgenera, Leishmania (Viannia) and Leishmania (Leishmania) in the Americas. Furthermore, use of TaqMan probes enables distinction between L. (V.) braziliensis or L. (V.) peruviania from the other L. (Viannia) species. All assays were negative with DNA of related trypanosomatids, humans, and mice. The parasite burden was estimated by normalizing the number of organisms per total amount of DNA in the sample or per host glyceraldehyde-3-phosphate dehydrogenase copies. The real-time PCR assay for L. (Leishmania) subgenus showed a good linear correlation with quantification on the basis of a limiting dilution assay in experimentally infected mice. The test successfully identifies and quantifies Leishmania in human biopsy specimens and represents a new tool to study leishmaniasis.

QUASISTATIONARY DISTRIBUTIONS AND FLEMING-VIOT PROCESSES IN FINITE SPACES

Consider a continuous-time Markov process with transition rates matrix Q in the state space Lambda boolean OR {0}. In In the associated Fleming-Viot process N particles evolve independently in A with transition rates matrix Q until one of them attempts to jump to state 0. At this moment the particle jumps to one of the positions of the other particles, chosen uniformly at random. When Lambda is finite, we show that the empirical distribution of the particles at a fixed time converges as N -> infinity to the distribution of a single particle at the same time conditioned on not touching {0}. Furthermore, the empirical profile of the unique invariant measure for the Fleming-Viot process with N particles converges as N -> infinity to the unique quasistationary distribution of the one-particle motion. A key element of the approach is to show that the two-particle correlations are of order 1/N.

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.

Billiards in a General Domain with Random Reflections

We study stochastic billiards on general tables: a particle moves according to its constant velocity inside some domain D R(d) until it hits the boundary and bounces randomly inside, according to some reflection law. We assume that the boundary of the domain is locally Lipschitz and almost everywhere continuously differentiable. The angle of the outgoing velocity with the inner normal vector has a specified, absolutely continuous density. We construct the discrete time and the continuous time processes recording the sequence of hitting points on the boundary and the pair location/velocity. We mainly focus on the case of bounded domains. Then, we prove exponential ergodicity of these two Markov processes, we study their invariant distribution and their normal (Gaussian) fluctuations. Of particular interest is the case of the cosine reflection law: the stationary distributions for the two processes are uniform in this case, the discrete time chain is reversible though the continuous time process is quasi-reversible. Also in this case, we give a natural construction of a chord ""picked at random"" in D, and we study the angle of intersection of the process with a (d - 1) -dimensional manifold contained in D.

Estimating the number of ozone peaks in Mexico City using a non-homogeneous Poisson model

In this paper, we consider the problem of estimating the number of times an air quality standard is exceeded in a given period of time. A non-homogeneous Poisson model is proposed to analyse this issue. The rate at which the Poisson events occur is given by a rate function lambda(t), t >= 0. This rate function also depends on some parameters that need to be estimated. Two forms of lambda(t), t >= 0 are considered. One of them is of the Weibull form and the other is of the exponentiated-Weibull form. The parameters estimation is made using a Bayesian formulation based on the Gibbs sampling algorithm. The assignation of the prior distributions for the parameters is made in two stages. In the first stage, non-informative prior distributions are considered. Using the information provided by the first stage, more informative prior distributions are used in the second one. The theoretical development is applied to data provided by the monitoring network of Mexico City. The rate function that best fit the data varies according to the region of the city and/or threshold that is considered. In some cases the best fit is the Weibull form and in other cases the best option is the exponentiated-Weibull. Copyright (C) 2007 John Wiley & Sons, Ltd.

Using stochastic volatility models to analyse weekly ozone averages in Mexico City

In this paper we make use of some stochastic volatility models to analyse the behaviour of a weekly ozone average measurements series. The models considered here have been used previously in problems related to financial time series. Two models are considered and their parameters are estimated using a Bayesian approach based on Markov chain Monte Carlo (MCMC) methods. Both models are applied to the data provided by the monitoring network of the Metropolitan Area of Mexico City. The selection of the best model for that specific data set is performed using the Deviance Information Criterion and the Conditional Predictive Ordinate method.

A flexible model for survival data with a cure rate: a Bayesian approach

In this paper we deal with a Bayesian analysis for right-censored survival data suitable for populations with a cure rate. We consider a cure rate model based on the negative binomial distribution, encompassing as a special case the promotion time cure model. Bayesian analysis is based on Markov chain Monte Carlo (MCMC) methods. We also present some discussion on model selection and an illustration with a real dataset.

Random sums of exchangeable variables and actuarial applications

In this paper we study the accumulated claim in some fixed time period, skipping the classical assumption of mutual independence between the variables involved. Two basic models are considered: Model I assumes that any pair of claims are equally correlated which means that the corresponding square-integrable sequence is exchangeable one. Model 2 states that the correlations between the adjacent claims are the same. Recurrence and explicit expressions for the joint probability generating function are derived and the impact of the dependence parameter (correlation coefficient) in both models is examined. The Markov binomial distribution is obtained as a particular case under assumptions of Model 2. (C) 2007 Elsevier B.V. All rights reserved.

Expression of Circadian Clock and Melatonin Receptors within Cultured Rat Cardiomyocytes

Melatonin, the pineal gland hormone, provides entrainment of many circadian rhythms to the ambient light/dark cycle. Recently, cardiovascular studies have demostrated melatonin interactions with many physiological processes and diseases, such as hypertension and cardiopathologies. Although membrane melatonin receptors (MT1, MT2) and the transcriptional factor ROR alpha have been reported to be expressed in the heart, there is no evidence of the cell-type expressing receptors as well as the possible role of melatonin on the expression of the circadian clock of cardiomyocytes, which play an important role in cardiac metabolism and function. Therefore, the aim of this study was to evaluate the mRNA and protein expressions of MT1, MT2, and ROR alpha and to determine whether melatonin directly influences expression of circadian clocks within cultured rat cardiomyocytes. Adult rat cardiomyocyte cultures were created, and the cells were stimulated with 1 nM melatonin or vehicle. Gene expressions were assayed by real-time polymerase chain reaction (PCR). The mRNA and protein expressions of membrane melatonin receptors and RORa were established within adult rat cardiomyocytes. Two hours of melatonin stimulation did not alter the expression pattern of the analyzed genes. However, given at the proper time, melatonin kept Rev-erb alpha expression chronically high, specifically 12 h after melatonin treatment, avoiding the rhythmic decline of Rev-erb alpha mRNA. The blockage of MT1 and MT2 by luzindole did not alter the observed melatonin-induced expression of Rev-erb alpha mRNA, suggesting the nonparticipation of MT1 and MT2 on the melatonin effect within cardiomyocytes. It is possible to speculate that melatonin, in adult rat cardiomyocytes, may play an important role in the light signal transduction to peripheral organs, such as the heart, modulating its intrinsic rhythmicity. (Author correspondence: cipolla@icb.usp.br)

Expression Profile and Distribution of Efhc1 Gene Transcript During Rodent Brain Development

One of the putative causative genes for juvenile myoclonic epilepsy (JME) is EFHC1. We report here the expression profile and distribution of Efhc1 messenger RNA (mRNA) during mouse and rat brain development. Real-time polymerase chain reaction revealed that there is no difference in the expression of Efhc1 mRNA between right and left hemispheres in both species. In addition, the highest levels of Efhc1 mRNA were found at intra-uterine stages in mouse and in adulthood in rat. In common, there was a progressive decrease in Efhc1 expression from 1-day-old neonates to 14-day-old animals in both species. In situ hybridization studies showed that rat and mouse Efhc1 mRNAs are expressed in ependymal cells of ventricle walls. Our findings suggest that Efhc1 expression is more important during initial phases of brain development and that at this stage it could be involved in key developmental mechanisms underlying JME.

The role of proliferator-activated receptor gamma coactivator-1 alpha in the fatty-acid -dependent transcriptional control of interleukin-10 in hepatic cells of rodents

Interleukin-10 (IL-10) is an endogenous factor that restrains hepatic insulin resistance in diet-induced steatosis Reducing IL-10 expression increases proinflammatory activity in the steatotic liver and worsens insulin resistance As the transcriptional coactivator proliferator-activated receptor gamma coactivator-1 alpha (PGC-1 alpha) plays a central role in dysfunctional hepatocytic activity in diet-induced steatosis, we hypothesized that at least part of the action of PGC-1 alpha could be mediated by reducing the transcription of the IL-10 gene Here, we used immunoblotting, real-time polymerase chain reaction, immunocytochemistry, and chromatin immunoprecipitation assay to investigate the role of PGC-1 alpha in the control of IL-10 expression in hepatic cells First, we show that, in the intact steatotic liver, the expressions of IL-10 and PGC-1 alpha are increased Inhibiting PGC-1 alpha expression by antisense oligonucleotide increases IL-10 expression and reduces the steatotic phenotype. In cultured hepatocytes, the treatment with saturated and unsaturated fatty acids increased IL-10 expression. This was accompanied by increased association of PGC-1 alpha with c-Maf and p50-nuclear factor (NF) kappa B, 2 transcription factors known to modulate IL-10 expression In addition, after fatty acid treatment. PGC-1 alpha, c-Maf, and p50-NF kappa B migrate from the cytosol to the nuclei of hepatocytes and bind to the IL-10 promoter region Inhibiting NF kappa B activation with salicylate reduces IL-10 expression and the association of PGC-1 alpha with p50-NF kappa B Thus, PGC-1 alpha emerges as a potential transcriptional regulator of the inflammatory phenomenon taking place in the steatotic liver (C) 2010 Elsevier Inc All rights reserved

GTPases RhoA and Rac1 are important for amelogenin and DSPP expression during differentiation of ameloblasts and odontoblasts

Morphogenesis and cytodifferentiation are distinct processes in tooth development. Cell proliferation predominates in morphogenesis; differentiation involves changes in form and gene expression. The cytoskeleton is essential for both processes, being regulated by Rho GTPases. The aim of this study was to verify the expression, distribution, and role of Rho GTPases in ameloblasts and odontoblasts during tooth development in correlation with actin and tubulin arrangements and amelogenin and dentin sialophosphoprotein (DSPP) expression. RhoA, Rac1, and Cdc42 were strongly expressed during morphogenesis; during cytodifferentiation, RhoA was present in ameloblasts and odontoblasts, Rac1 and its effector Pak3 were observed in ameloblasts; and Cdc42 was present in all cells of the tooth germ and mesenchyme. The expression of RhoA mRNA and its effectors RockI and RockII, Rac1 and Pak3, as analyzed by real-time polymerase chain reaction, increased after ameloblast and odontoblast differentiation, according to the mRNA expression of amelogenin and DSPP. The inhibition of all Rho GTPases by Clostridium difficile toxin A completely abolished amelogenin and DSPP expression in tooth germs cultured in anterior eye chamber, whereas the specific inhibition of the Rocks showed only a partial effect. Thus, both GTPases are important during tooth morphogenesis. During cytodifferentiation, Rho proteins are essential for the complete differentiation of ameloblasts and odontoblasts by regulating the expression of amelogenin and DSPP. RhoA and its effector RockI contribute to this role. A specific function for Rac1 in ameloblasts remains to be elucidated; its punctate distribution indicates its possible role in exocytosis/endocytosis.

Expression of Pancreatic Endocrine Markers by Prolactin-Treated Rat Bone Marrow Mesenchymal Stem Cells

Background. Mesenchymal stem cells (MSCs) are an attractive source for generation of cells with beta-cell properties. Previous studies have demonstrated the ability of prolactin to induce an increase in beta-cell mass and maturation, which suggests beneficial effects of its use in MSC differentiation protocols. Objective. To evaluate the expression of endocrine differentiation markers in rat MSCs treated in vitro with prolactin. Methods. Mesenchymal stem cells from bone marrow of Wistar rats were isolated, expanded, and characterized. Differentiation of MSCs was induced in medium containing 23 mmol/L of glucose, and nicotinamide, 2-mercaptoethanol, and exendin-4, in the presence or absence of 500 ng/mL of rat recombinant prolactin. Expression of endocrine markers and prolactin receptor genes was evaluated using real-time polymerase chain reaction, and compared between culture stages and presence vs absence of prolactin in the culture medium. Expression of insulin, somatostatin, glucagon, and pancreatic and duodenal homeobox 1 was also evaluated at immunofluorescence microscopy. Results. Isolated cells were mostly MSCs, as confirmed at fluorescent-activated cell sorting and cytochemistry. Pax6, Ngn-3, Isl1, NeuroD1, Nkx2.2, and Nkx6.1 exhibited varied expression during culture stages. The long form of the prolactin receptor messenger RNA was induced in prolactin-treated cultures (P < .05). The somatostatin gene was induced in early stages of differentiation (P < .05), and its expression was induced by prolactin, as confirmed using immunofluorescence. Conclusion. Culture of rat bone marrow MSCs in differentiation medium induces expression of pancreatic endocrine-specific genes, and somatostatin and prolactin receptor expression was also induced by prolactin.

Tumor necrosis factor-alpha-308G/A single nucleotide polymorphism and red-complex periodontopathogens are independently associated with increased levels of tumor necrosis factor-alpha in diseased periodontal tissues

Background and Objective: Inflammatory cytokines such as tumor necrosis factor-alpha are involved in the pathogenesis of periodontal diseases. A high between-subject variation in the level of tumor necrosis factor-alpha mRNA has been verified, which may be a result of genetic polymorphisms and/or the presence of periodontopathogens such as Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola (called the red complex) and Aggregatibacter actinomycetemcomitans. In this study, we investigated the effect of the tumor necrosis factor-alpha (TNFA) -308G/A gene polymorphism and of periodontopathogens on the tumor necrosis factor-alpha levels in the periodontal tissues of nonsmoking patients with chronic periodontitis (n = 127) and in control subjects (n = 177). Material and Methods: The TNFA-308G/A single nucleotide polymorphism was investigated using polymerase chain reaction-restriction fragment length polymorphism analysis, whereas the tumor necrosis factor-alpha levels and the periodontopathogen load were determined using real-time polymerase chain reaction. Results: No statistically significant differences were found in the frequency of the TNFA-308 single nucleotide polymorphism in control and chronic periodontitis groups, in spite of the higher frequency of the A allele in the chronic periodontitis group. The concomitant analyses of genotypes and periodontopathogens demonstrated that TNFA-308 GA/AA genotypes and the red-complex periodontopathogens were independently associated with increased levels of tumor necrosis factor-alpha in periodontal tissues, and no additive effect was seen when both factors were present. P. gingivalis, T. forsythia and T. denticola counts were positively correlated with the level of tumor necrosis factor-alpha. TNFA-308 genotypes were not associated with the periodontopathogen detection odds or with the bacterial load. Conclusion: Our results demonstrate that the TNFA-308 A allele and red-complex periodontopathogens are independently associated with increased levels of tumor necrosis factor-alpha in diseased tissues of nonsmoking chronic periodontitis patients and consequently are potentially involved in determining the disease outcome.

Longitudinal Poisson modeling: an application for CD4 counting in HIV-infected patients

In this paper, we present different ofrailtyo models to analyze longitudinal data in the presence of covariates. These models incorporate the extra-Poisson variability and the possible correlation among the repeated counting data for each individual. Assuming a CD4 counting data set in HIV-infected patients, we develop a hierarchical Bayesian analysis considering the different proposed models and using Markov Chain Monte Carlo methods. We also discuss some Bayesian discrimination aspects for the choice of the best model.