NO EVIDENCE OF PATHOLOGICAL AUTOIMMUNITY FOLLOWING MYCOBACTERIUM LEPRAE HEAT-SHOCK PROTEIN 65-DNA VACCINATION IN MICE

Heat-shock proteins (HSPs) are currently one of the most promising targets for the development of immunotherapy against tumours and autoimmune disorders. This protein family has the capacity to activate or modulate the function of different immune system cells. They induce the activation of monocytes, macrophages and dendritic cells, and contribute to cross-priming, an important mechanism of presentation of exogenous antigen in the context of MHC class I molecules, These various immunological properties of HSP have encouraged their use in several clinical trials. Nevertheless, an important issue regarding these proteins is whether the high homology among HSPs across different species may trigger the breakdown of immune tolerance and induce autoimmune diseases. We have developed a DNA vaccine codifying the Mycobacterium leprae Hsp65 (DNAhsp65), which showed to be highly immunogenic and protective against experimental tuberculosis. Here, we address the question of whether DNAhsp65 immunization could induce pathological autoimmunity in mice. Our results show that DNAhsp65 vaccination induced antibodies that can recognize the human Hsp60 but did not induce harmful effects in 16 different organs analysed by histopathology up to 210 days after vaccination. We also showed that anti-DNA antibodies were not elicited after DNA vaccination. The results are important for the development of both HSP and DNA-based immunomodulatory agents.

Comprehensive gene expression profiling in lungs of mice infected with Mycobacterium tuberculosis following DNAhsp65 immunotherapy

Background The continued increase in tuberculosis (TB) rates and the appearance of extremely resistant Mycobacterium tuberculosis strains (XDR-TB) worldwide are some of the great problems of public health. In this context, DNA immunotherapy has been proposed as an effective alternative that could circumvent the limitations of conventional drugs. Nonetheless, the molecular events underlying these therapeutic effects are poorly understood. Methods We characterized the transcriptional signature of lungs from mice infected with M. tuberculosis and treated with heat shock protein 65 as a genetic vaccine (DNAhsp65) combining microarray and real-time polymerase chain reaction analysis. The gene expression data were correlated with the histopathological analysis of lungs. Results The differential modulation of a high number of genes allowed us to distinguish DNAhsp65-treated from nontreated animals (saline and vector-injected mice). Functional analysis of this group of genes suggests that DNAhsp65 therapy could not only boost the T helper (Th)1 immune response, but also could inhibit Th2 cytokines and regulate the intensity of inflammation through fine tuning of gene expression of various genes, including those of interleukin-17, lymphotoxin A, tumour necrosis factor-cl, interleukin-6, transforming growth factor-beta, inducible nitric oxide synthase and Foxp3. In addition, a large number of genes and expressed sequence tags previously unrelated to DNA-therapy were identified. All these findings were well correlated with the histopathological lesions presented in the lungs. Conclusions The effects of DNA therapy are reflected in gene expression modulation; therefore, the genes identified as differentially expressed could be considered as transcriptional biomarkers of DNAhsp65 immunotherapy against TB. The data have important implications for achieving a better understanding of gene-based therapies. Copyright (C) 2008 John Wiley & Sons, Ltd.

Functional interferences in host inflammatory immune response by airway allergic inflammation restrain experimental periodontitis development in mice

Aims Periodontal disease (PD) and airway allergic inflammation (AL) present opposing inflammatory immunological features and clinically present an inverse correlation. However, the putative mechanisms underlying such opposite association are unknown. Material and Methods Balb/C mice were submitted to the co-induction of experimental PD (induced by Actinobacillus actinomycetemcomitans oral inoculation) and AL [induced by sensitization with ovalbumin (OVA) and the subsequent OVA challenges], and evaluated regarding PD and AL severity, immune response [cytokine production at periodontal tissues, and T-helper transcription factors in submandibular lymph nodes (LNs)] and infection parameters. Results PD/AL co-induction decreased PD alveolar bone loss and periodontal inflammation while experimental AL parameters were unaltered. An active functional interference was verified, because independent OVA sensitization and challenge not modulate PD outcome. PD+AL group presented decreased tumour necrosis factor-alpha (TNF-alpha), interleukin (IL)-1 beta, -gamma, IL-17A, receptor activator of nuclear factor kappa-light-chain-enhancer of activated B cells ligand and matrix metalloproteinase (MMP)-13 levels in periodontal tissues, while IL-4 and IL-10 levels were unaltered by AL co-induction. AL co-induction also resulted in upregulated T-bet and related orphan receptor gamma and downregulated GATA3 levels expression in submandibular LNs when compared with PD group. Conclusion Our results demonstrate that the interaction between experimental periodontitis and allergy involves functional immunological interferences, which restrains experimental periodontitis development by means of a skewed immune response.

Numerical prediction of three-dimensional time-dependent viscoelastic extrudate swell using differential and algebraic models

This study investigates the numerical simulation of three-dimensional time-dependent viscoelastic free surface flows using the Upper-Convected Maxwell (UCM) constitutive equation and an algebraic explicit model. This investigation was carried out to develop a simplified approach that can be applied to the extrudate swell problem. The relevant physics of this flow phenomenon is discussed in the paper and an algebraic model to predict the extrudate swell problem is presented. It is based on an explicit algebraic representation of the non-Newtonian extra-stress through a kinematic tensor formed with the scaled dyadic product of the velocity field. The elasticity of the fluid is governed by a single transport equation for a scalar quantity which has dimension of strain rate. Mass and momentum conservations, and the constitutive equation (UCM and algebraic model) were solved by a three-dimensional time-dependent finite difference method. The free surface of the fluid was modeled using a marker-and-cell approach. The algebraic model was validated by comparing the numerical predictions with analytic solutions for pipe flow. In comparison with the classical UCM model, one advantage of this approach is that computational workload is substantially reduced: the UCM model employs six differential equations while the algebraic model uses only one. The results showed stable flows with very large extrudate growths beyond those usually obtained with standard differential viscoelastic models. (C) 2010 Elsevier Ltd. All rights reserved.

Evaluation of a bounded high order upwind scheme for 3D incompressible free surface flow computations

fit the context of normalized variable formulation (NVF) of Leonard and total variation diminishing (TVD) constraints of Harten. this paper presents an extension of it previous work by the authors for solving unsteady incompressible flow problems. The main contributions of the paper are threefold. First, it presents the results of the development and implementation of a bounded high order upwind adaptative QUICKEST scheme in the 3D robust code (Freeflow), for the numerical solution of the full incompressible Navier-Stokes equations. Second, it reports numerical simulation results for 1D hock tube problem, 2D impinging jet and 2D/3D broken clam flows. Furthermore, these results are compared with existing analytical and experimental data. And third, it presents the application of the numerical method for solving 3D free surface flow problems. (C) 2007 IMACS. Published by Elsevier B.V. All rights reserved,

Twofold adaptive partition of unity implicits

Partition of Unity Implicits (PUI) has been recently introduced for surface reconstruction from point clouds. In this work, we propose a PUI method that employs a set of well-observed solutions in order to produce geometrically pleasant results without requiring time consuming or mathematically overloaded computations. One feature of our technique is the use of multivariate orthogonal polynomials in the least-squares approximation, which allows the recursive refinement of the local fittings in terms of the degree of the polynomial. However, since the use of high-order approximations based only on the number of available points is not reliable, we introduce the concept of coverage domain. In addition, the method relies on the use of an algebraically defined triangulation to handle two important tasks in PUI: the spatial decomposition and an adaptive polygonization. As the spatial subdivision is based on tetrahedra, the generated mesh may present poorly-shaped triangles that are improved in this work by means a specific vertex displacement technique. Furthermore, we also address sharp features and raw data treatment. A further contribution is based on the PUI locality property that leads to an intuitive scheme for improving or repairing the surface by means of editing local functions.

Topological triangle characterization with application to object detection from images

A novel mathematical framework inspired on Morse Theory for topological triangle characterization in 2D meshes is introduced that is useful for applications involving the creation of mesh models of objects whose geometry is not known a priori. The framework guarantees a precise control of topological changes introduced as a result of triangle insertion/removal operations and enables the definition of intuitive high-level operators for managing the mesh while keeping its topological integrity. An application is described in the implementation of an innovative approach for the detection of 2D objects from images that integrates the topological control enabled by geometric modeling with traditional image processing techniques. (C) 2008 Published by Elsevier B.V.