Immunization of neonatal mice with LAMP/p55 HIV gag DNA elicits robust immune responses that last to adulthood

Successful T cell priming in early postnatal life that can generate effective long-lasting responses until adulthood is critical in HIV vaccination strategies because it prevents early sexual initiation and breastfeeding transmission of HIV. A chimeric DNA vaccine encoding p55 HIV gag associated with lysosome-associated membrane protein 1 (LAMP-1; which drives the antigen to the MIIC compartment), has been used to enhance cellular and humoral antigen-specific responses in adult mice and macaques. Herein, we investigated LAMP-1/gag vaccine immunogenicity in the neonatal period in mice and its ability to generate long-lasting effects. Neonatal vaccination with chimeric LAMP/gag generated stronger Gag-specific immune responses, as measured by the breadth of the Gag peptide-specific IFN-gamma, proliferative responsiveness, cytokine production and antibody production, all of which revealed activation of CD4+ T cells as well as the generation of a more robust CTL response compared to gag vaccine alone. To induce long-lived T and B cell memory responses, it was necessary to immunize neonates with the chimeric IAMP/gag DNA vaccine. The LAMP/gag DNA vaccine strategy could be particularly useful for generating an anti-HIV immune response in the early postnatal period capable of inducing long-term immunological memory. (C) 2010 Elsevier Inc. All rights reserved.

Verification of the role of the low level jets in Amazon squall lines

In this study we present a climatology of the Amazon squall lines (ASLs), between the years 2000 and 2008, using satellite imagery and European Centre for Medium-Range Weather Forecasts (ECMWF) reanalyses. The ASLs we are interested in are typically formed along the northern coast of Brazil and sometimes propagate for long distances inland. Results show that, on average, an ASL occurs every 2 days. ASLs are more frequent between April and June and less frequent between October and November. The years of 2005 and 2006 showed 25% more cases than the other years. This might be related to an increase of the Atlantic sea surface temperature. Of the total number of ASL cases, 54% propagated less than 170 km, 26% propagated between 170 and 400 km, and 20% propagated more than 400 km. We also studied the occurrence of low level jets (LLJs) associated with the coastal ASLs. Although LLJs are always present in the environment before the formation of the ASL and even on days without ASL cases, important differences were found, mainly related to the LLJ depths. (C) 2010 Elsevier B.V. All rights reserved.

Development of an adenoviral vector with robust expression driven by p53

Here we introduce a new adenoviral vector where transgene expression is driven by p53. We first developed a synthetic promoter, referred to as PGTx beta containing a p53-responsive element, a minimal promoter and the first intron of the rabbit P-globin gene. Initial assays using plasmid-based vectors indicated that expression was tightly controlled by p53 and was 5-fold stronger than the constitutive CMV immediate early promoter/enhancer. The adenoviral vector, AdPG, was also shown to offer p53-responsive expression in prostate carcinoma cells LNCaP (wt p53), DU-145 (temperature sensitive mutant of p53) and PC3 (p53-null, but engineered to express temperature-sensitive p53 mutants). AdPG served as a sensor of p53 activity in LNCaP cells treated with chemotherapeutic agents. Since p53 can be induced by radiotherapy and chemotherapy, this new vector could be further developed for use in combination with conventional therapies to bring about cooperation between the genetic and pharmacologic treatment modalities. (c) 2007 Elsevier Inc. All rights reserved.

Gene optimization leads to robust expression of human respiratory syncytial virus nucleoprotein and phosphoprotein in human cells and induction of humoral immunity in mice

Human respiratory syncytial virus (HRSV) is the major pathogen leading to respiratory disease in infants and neonates worldwide. An effective vaccine has not yet been developed against this virus, despite considerable efforts in basic and clinical research. HRSV replication is independent of the nuclear RNA processing constraints, since the virus genes are adapted to the cytoplasmic transcription, a process performed by the viral RNA-dependent RNA polymerase. This study shows that meaningful nuclear RNA polymerase II dependent expression of the HRSV nucleoprotein (N) and phosphoprotein (F) proteins can only be achieved with the optimization of their genes, and that the intracellular localization of N and P proteins changes when they are expressed out of the virus replication context. Immunization tests performed in mice resulted in the induction of humoral immunity using the optimized genes. This result was not observed for the non-optimized genes. In conclusion, optimization is a valuable tool for improving expression of HRSV genes in DNA vaccines. (c) 2009 Elsevier B.V. All rights reserved.

Bayesian Estimation for Performance Measures of Two Diagnostic Tests in the Presence of Verification Bias

Sensitivity and specificity are measures that allow us to evaluate the performance of a diagnostic test. In practice, it is common to have situations where a proportion of selected individuals cannot have the real state of the disease verified, since the verification could be an invasive procedure, as occurs with biopsy. This happens, as a special case, in the diagnosis of prostate cancer, or in any other situation related to risks, that is, not practicable, nor ethical, or in situations with high cost. For this case, it is common to use diagnostic tests based only on the information of verified individuals. This procedure can lead to biased results or workup bias. In this paper, we introduce a Bayesian approach to estimate the sensitivity and the specificity for two diagnostic tests considering verified and unverified individuals, a result that generalizes the usual situation based on only one diagnostic test.

UNIFORM DISSIPATIVENESS, ROBUST SYNCHRONIZATION AND LOCATION OF THE ATTRACTOR OF PARAMETRIZED NONAUTONOMOUS DISCRETE SYSTEMS

In this series of papers, we study issues related to the synchronization of two coupled chaotic discrete systems arising from secured communication. The first part deals with uniform dissipativeness with respect to parameter variation via the Liapunov direct method. We obtain uniform estimates of the global attractor for a general discrete nonautonomous system, that yields a uniform invariance principle in the autonomous case. The Liapunov function is allowed to have positive derivative along solutions of the system inside a bounded set, and this reduces substantially the difficulty of constructing a Liapunov function for a given system. In particular, we develop an approach that incorporates the classical Lagrange multiplier into the Liapunov function method to naturally extend those Liapunov functions from continuous dynamical system to their discretizations, so that the corresponding uniform dispativeness results are valid when the step size of the discretization is small. Applications to the discretized Lorenz system and the discretization of a time-periodic chaotic system are given to illustrate the general results. We also show how to obtain uniform estimation of attractors for parametrized linear stable systems with nonlinear perturbation.

Robust inference in an heteroscedastic measurement error model

In this paper we deal with robust inference in heteroscedastic measurement error models Rather than the normal distribution we postulate a Student t distribution for the observed variables Maximum likelihood estimates are computed numerically Consistent estimation of the asymptotic covariance matrices of the maximum likelihood and generalized least squares estimators is also discussed Three test statistics are proposed for testing hypotheses of interest with the asymptotic chi-square distribution which guarantees correct asymptotic significance levels Results of simulations and an application to a real data set are also reported (C) 2009 The Korean Statistical Society Published by Elsevier B V All rights reserved

Robust linear mixed models with skew-normal independent distributions from a Bayesian perspective

Linear mixed models were developed to handle clustered data and have been a topic of increasing interest in statistics for the past 50 years. Generally. the normality (or symmetry) of the random effects is a common assumption in linear mixed models but it may, sometimes, be unrealistic, obscuring important features of among-subjects variation. In this article, we utilize skew-normal/independent distributions as a tool for robust modeling of linear mixed models under a Bayesian paradigm. The skew-normal/independent distributions is an attractive class of asymmetric heavy-tailed distributions that includes the skew-normal distribution, skew-t, skew-slash and the skew-contaminated normal distributions as special cases, providing an appealing robust alternative to the routine use of symmetric distributions in this type of models. The methods developed are illustrated using a real data set from Framingham cholesterol study. (C) 2009 Elsevier B.V. All rights reserved.

Robust tori in a double-waved Hamiltonian model

A Hamiltonian system perturbed by two waves with particular wave numbers can present robust tori, which are barriers created by the vanishing of the perturbed Hamiltonian at some defined positions. When robust tori exist, any trajectory in phase space passing close to them is blocked by emergent invariant curves that prevent the chaotic transport. Our results indicate that the considered particular solution for the two waves Hamiltonian model shows plenty of robust tori blocking radial transport. (C) 2010 Elsevier B.V. All rights reserved.

The non-twist standard map with robust tori

The non-twist standard map occurs frequently in many fields of science specially in modelling the dynamics of the magnetic field lines in tokamaks. Robust tori, dynamical barriers that impede the radial transport among different regions of the phase space, are introduced in the non-twist standard map in a conservative fashion. The resulting non-twist standard map with robust tori is an improved model to study transport barriers in plasmas confined in tokamaks.

Plasma confinement in tokamaks with robust torus

We present a non-linear symplectic map that describes the alterations of the magnetic field lines inside the tokamak plasma due to the presence of a robust torus (RT) at the plasma edge. This RT prevents the magnetic field lines from reaching the tokamak wall and reduces, in its vicinity, the islands and invariant curve destruction due to resonant perturbations. The map describes the equilibrium magnetic field lines perturbed by resonances created by ergodic magnetic limiters (EMLs). We present the results obtained for twist and non-twist mappings derived for monotonic and non-monotonic plasma current density radial profiles, respectively. Our results indicate that the RT implementation would decrease the field line transport at the tokamak plasma edge. (C) 2010 Elsevier B.V. All rights reserved.

Efficient solutions to robust, semi-implicit discretizations of the immersed boundary method

The immersed boundary method is a versatile tool for the investigation of flow-structure interaction. In a large number of applications, the immersed boundaries or structures are very stiff and strong tangential forces on these interfaces induce a well-known, severe time-step restriction for explicit discretizations. This excessive stability constraint can be removed with fully implicit or suitable semi-implicit schemes but at a seemingly prohibitive computational cost. While economical alternatives have been proposed recently for some special cases, there is a practical need for a computationally efficient approach that can be applied more broadly. In this context, we revisit a robust semi-implicit discretization introduced by Peskin in the late 1970s which has received renewed attention recently. This discretization, in which the spreading and interpolation operators are lagged. leads to a linear system of equations for the inter-face configuration at the future time, when the interfacial force is linear. However, this linear system is large and dense and thus it is challenging to streamline its solution. Moreover, while the same linear system or one of similar structure could potentially be used in Newton-type iterations, nonlinear and highly stiff immersed structures pose additional challenges to iterative methods. In this work, we address these problems and propose cost-effective computational strategies for solving Peskin`s lagged-operators type of discretization. We do this by first constructing a sufficiently accurate approximation to the system`s matrix and we obtain a rigorous estimate for this approximation. This matrix is expeditiously computed by using a combination of pre-calculated values and interpolation. The availability of a matrix allows for more efficient matrix-vector products and facilitates the design of effective iterative schemes. We propose efficient iterative approaches to deal with both linear and nonlinear interfacial forces and simple or complex immersed structures with tethered or untethered points. One of these iterative approaches employs a splitting in which we first solve a linear problem for the interfacial force and then we use a nonlinear iteration to find the interface configuration corresponding to this force. We demonstrate that the proposed approach is several orders of magnitude more efficient than the standard explicit method. In addition to considering the standard elliptical drop test case, we show both the robustness and efficacy of the proposed methodology with a 2D model of a heart valve. (C) 2009 Elsevier Inc. All rights reserved.

A Robust, Fully Adaptive Hybrid Level-Set/Front-Tracking Method for Two-Phase Flows with an Accurate Surface Tension Computation

We present a variable time step, fully adaptive in space, hybrid method for the accurate simulation of incompressible two-phase flows in the presence of surface tension in two dimensions. The method is based on the hybrid level set/front-tracking approach proposed in [H. D. Ceniceros and A. M. Roma, J. Comput. Phys., 205, 391400, 2005]. Geometric, interfacial quantities are computed from front-tracking via the immersed-boundary setting while the signed distance (level set) function, which is evaluated fast and to machine precision, is used as a fluid indicator. The surface tension force is obtained by employing the mixed Eulerian/Lagrangian representation introduced in [S. Shin, S. I. Abdel-Khalik, V. Daru and D. Juric, J. Comput. Phys., 203, 493-516, 2005] whose success for greatly reducing parasitic currents has been demonstrated. The use of our accurate fluid indicator together with effective Lagrangian marker control enhance this parasitic current reduction by several orders of magnitude. To resolve accurately and efficiently sharp gradients and salient flow features we employ dynamic, adaptive mesh refinements. This spatial adaption is used in concert with a dynamic control of the distribution of the Lagrangian nodes along the fluid interface and a variable time step, linearly implicit time integration scheme. We present numerical examples designed to test the capabilities and performance of the proposed approach as well as three applications: the long-time evolution of a fluid interface undergoing Rayleigh-Taylor instability, an example of bubble ascending dynamics, and a drop impacting on a free interface whose dynamics we compare with both existing numerical and experimental data.

A fast and robust statistical test based on likelihood ratio with Bartlett correction to identify Granger causality between gene sets

We propose a likelihood ratio test ( LRT) with Bartlett correction in order to identify Granger causality between sets of time series gene expression data. The performance of the proposed test is compared to a previously published bootstrapbased approach. LRT is shown to be significantly faster and statistically powerful even within non- Normal distributions. An R package named gGranger containing an implementation for both Granger causality identification tests is also provided.

A robust Bayesian approach to null intercept measurement error model with application to dental data

Measurement error models often arise in epidemiological and clinical research. Usually, in this set up it is assumed that the latent variable has a normal distribution. However, the normality assumption may not be always correct. Skew-normal/independent distribution is a class of asymmetric thick-tailed distributions which includes the Skew-normal distribution as a special case. In this paper, we explore the use of skew-normal/independent distribution as a robust alternative to null intercept measurement error model under a Bayesian paradigm. We assume that the random errors and the unobserved value of the covariate (latent variable) follows jointly a skew-normal/independent distribution, providing an appealing robust alternative to the routine use of symmetric normal distribution in this type of model. Specific distributions examined include univariate and multivariate versions of the skew-normal distribution, the skew-t distributions, the skew-slash distributions and the skew contaminated normal distributions. The methods developed is illustrated using a real data set from a dental clinical trial. (C) 2008 Elsevier B.V. All rights reserved.