Induction of neutralizing antibodies in mice immunized with an amino-terminal polypeptide of Streptococcus mutans P1 protein produced by a recombinant Bacillus subtilis strain

The oral pathogen Streptococcus mutans expresses a surface protein, P1, which interacts with the salivary pellicle on the tooth surface or with fluid-phase saliva, resulting in bacterial adhesion or aggregation, respectively. P1 is a target of protective immunity. Its N-terminal region has been associated with adhesion and aggregation functions and contains epitopes recognized by efficacious antibodies. In this study, we used Bacillus subtilis, a gram-positive expression host, to produce a recombinant N-terminal polypeptide of P1 (P1(39-512)) derived from the S. mutans strain UA159. Purified P1(39-512) reacted with an anti-full-length P1 antiserum as well as one raised against intact S. mutans cells, indicating preserved antigenicity. Immunization of mice with soluble and heat-denatured P1(39-512) induced antibodies that reacted specifically with native P1 on the surface of S. mutans cells. The anti-P1(39-512) antiserum was as effective at blocking saliva-mediated aggregation of S. mutans cells and better at blocking bacterial adhesion to saliva-coated plastic surfaces compared with the anti-full-length P1 antiserum. In addition, adsorption of the anti-P1 antiserum with P1(39-512) eliminated its ability to block the adhesion of S. mutans cells to abiotic surfaces. The present results indicate that P1(39-512), expressed and purified from a recombinant B. subtilis strain, maintains important immunological features of the native protein and represents an additional tool for the development of anticaries vaccines.

Fuzzy pole placement based on piecewise Lyapunov functions

This paper presents a controller design method for fuzzy dynamic systems based on piecewise Lyapunov functions with constraints on the closed-loop pole location. The main idea is to use switched controllers to locate the poles of the system to obtain a satisfactory transient response. It is shown that the global fuzzy system satisfies the requirements for the design and that the control law can be obtained by solving a set of linear matrix inequalities, which can be efficiently solved with commercially available softwares. An example is given to illustrate the application of the proposed method. Copyright (C) 2009 John Wiley & Sons, Ltd.

Exact Search Directions for Optimization of Linear and Nonlinear Models Based on Generalized Orthonormal Functions

A novel technique for selecting the poles of orthonormal basis functions (OBF) in Volterra models of any order is presented. It is well-known that the usual large number of parameters required to describe the Volterra kernels can be significantly reduced by representing each kernel using an appropriate basis of orthonormal functions. Such a representation results in the so-called OBF Volterra model, which has a Wiener structure consisting of a linear dynamic generated by the orthonormal basis followed by a nonlinear static mapping given by the Volterra polynomial series. Aiming at optimizing the poles that fully parameterize the orthonormal bases, the exact gradients of the outputs of the orthonormal filters with respect to their poles are computed analytically by using a back-propagation-through-time technique. The expressions relative to the Kautz basis and to generalized orthonormal bases of functions (GOBF) are addressed; the ones related to the Laguerre basis follow straightforwardly as a particular case. The main innovation here is that the dynamic nature of the OBF filters is fully considered in the gradient computations. These gradients provide exact search directions for optimizing the poles of a given orthonormal basis. Such search directions can, in turn, be used as part of an optimization procedure to locate the minimum of a cost-function that takes into account the error of estimation of the system output. The Levenberg-Marquardt algorithm is adopted here as the optimization procedure. Unlike previous related work, the proposed approach relies solely on input-output data measured from the system to be modeled, i.e., no information about the Volterra kernels is required. Examples are presented to illustrate the application of this approach to the modeling of dynamic systems, including a real magnetic levitation system with nonlinear oscillatory behavior.

New insights on surface-enhanced Raman scattering based on controlled aggregation and spectroscopic studies, DFT calculations and symmetry analysis for 3,6-bi-2-pyridyl-1,2,4,5-tetrazine adsorbed onto citrate-stabilized gold nanoparticles

Asystematic study on the surface-enhanced Raman scattering (SERS) for 3,6-bi-2-pyridyl-1,2,4,5-tetrazine (bptz) adsorbed onto citrate-modified gold nanoparticles (cit-AuNps) was carried out based on electronic and vibrational spectroscopy and density functional methods. The citrate/bptz exchange was carefully controlled by the stepwise addition of bptz to the cit-AuNps, inducing flocculation and leading to the rise of a characteristic plasmon coupling band in the visible region. Such stepwise procedure led to a uniform decrease of the citrate SERS signals and to the rise of characteristic peaks of bptz, consistent with surface binding via the N heterocyclic atoms. In contrast, single addition of a large amount of bptz promoted complete aggregation of the nanoparticles, leading to a strong enhancement of the SERS signals. In this case, from the distinct Raman profiles involved, the formation of a new SERS environment became apparent, conjugating the influence of the local hot spots and charge-transfer (CT) effects. The most strongly enhanced vibrations belong to a(1) and b(2) representations, and were interpreted in terms of the electromagnetic and the CT mechanisms: the latter involving significant contribution of vibronic coupling in the system. Copyright (C) 2010 John Wiley & Sons, Ltd.

A novel polar-based human face recognition computational model

Motivated by a recently proposed biologically inspired face recognition approach, we investigated the relation between human behavior and a computational model based on Fourier-Bessel (FB) spatial patterns. We measured human recognition performance of FB filtered face images using an 8-alternative forced-choice method. Test stimuli were generated by converting the images from the spatial to the FB domain, filtering the resulting coefficients with a band-pass filter, and finally taking the inverse FB transformation of the filtered coefficients. The performance of the computational models was tested using a simulation of the psychophysical experiment. In the FB model, face images were first filtered by simulated V1- type neurons and later analyzed globally for their content of FB components. In general, there was a higher human contrast sensitivity to radially than to angularly filtered images, but both functions peaked at the 11.3-16 frequency interval. The FB-based model presented similar behavior with regard to peak position and relative sensitivity, but had a wider frequency band width and a narrower response range. The response pattern of two alternative models, based on local FB analysis and on raw luminance, strongly diverged from the human behavior patterns. These results suggest that human performance can be constrained by the type of information conveyed by polar patterns, and consequently that humans might use FB-like spatial patterns in face processing.

Designing real nanotube-based gas sensors

Using a combination of density functional theory and recursive Green's functions techniques, we present a full description of a large scale sensor, accounting for disorder and different coverages. Here, we use this method to demonstrate the functionality of nitrogen-rich carbon nanotubes as ammonia sensors as an example. We show how the molecules one wishes to detect bind to the most relevant defects on the nanotube, describe how these interactions lead to changes in the electronic transport properties of each isolated defect, and demonstrate that there are significative resistance changes even in the presence of disorder, elucidating how a realistic nanosensor works.

Toward Optimal Design of Piezoelectric Transducers Based on Multifunctional and Smoothly Graded Hybrid Material Systems

This work explores the design of piezoelectric transducers based on functional material gradation, here named functionally graded piezoelectric transducer (FGPT). Depending on the applications, FGPTs must achieve several goals, which are essentially related to the transducer resonance frequency, vibration modes, and excitation strength at specific resonance frequencies. Several approaches can be used to achieve these goals; however, this work focuses on finding the optimal material gradation of FGPTs by means of topology optimization. Three objective functions are proposed: (i) to obtain the FGPT optimal material gradation for maximizing specified resonance frequencies; (ii) to design piezoelectric resonators, thus, the optimal material gradation is found for achieving desirable eigenvalues and eigenmodes; and (iii) to find the optimal material distribution of FGPTs, which maximizes specified excitation strength. To track the desirable vibration mode, a mode-tracking method utilizing the `modal assurance criterion` is applied. The continuous change of piezoelectric, dielectric, and elastic properties is achieved by using the graded finite element concept. The optimization algorithm is constructed based on sequential linear programming, and the concept of continuum approximation of material distribution. To illustrate the method, 2D FGPTs are designed for each objective function. In addition, the FGPT performance is compared with the non-FGPT one.

A calibration approach based on Takagi-Sugeno fuzzy inference system for digital electronic compasses

Recently, the development of industrial processes brought on the outbreak of technologically complex systems. This development generated the necessity of research relative to the mathematical techniques that have the capacity to deal with project complexities and validation. Fuzzy models have been receiving particular attention in the area of nonlinear systems identification and analysis due to it is capacity to approximate nonlinear behavior and deal with uncertainty. A fuzzy rule-based model suitable for the approximation of many systems and functions is the Takagi-Sugeno (TS) fuzzy model. IS fuzzy models are nonlinear systems described by a set of if then rules which gives local linear representations of an underlying system. Such models can approximate a wide class of nonlinear systems. In this paper a performance analysis of a system based on IS fuzzy inference system for the calibration of electronic compass devices is considered. The contribution of the evaluated IS fuzzy inference system is to reduce the error obtained in data acquisition from a digital electronic compass. For the reliable operation of the TS fuzzy inference system, adequate error measurements must be taken. The error noise must be filtered before the application of the IS fuzzy inference system. The proposed method demonstrated an effectiveness of 57% at reducing the total error based on considered tests. (C) 2011 Elsevier Ltd. All rights reserved.

Effects of chlorogenic acid on neutrophil locomotion functions in response to inflammatory stimulus

Aim of the study: Species of Lychnophora are used in Brazilian folk medicine as analgesic and anti-inflammatory agents. Chlorogenic acid (CGA) and their analogues are important components of polar extracts of these species, as well in several European and Asian medicinal plants. Some of these phenolic compounds display anti-inflammatory effects. In this paper we report the isolation of CGA from Lychnophora salicifolia and its effects on functions involved in neutrophils locomotion. Materials and methods: LC-MS(n) data confirmed the presence of CGA in the plant. Actions of CGA were investigated on neutrophils obtained from peritoneal cavity of Wistar rats (4h after 1% oyster glycogen solution injection; 10 ml), and incubated with vehicle or with 50, 100 or 1000 mu M CGA in presence of lipopolysaccharide from Escherichia coil (LPS, 5 mu g/ml). Nitric oxide (NO; Griess reaction); prostaglandin E(2) (PGE(2)), interleukin-1 beta (IL-1 beta) and tumor necrosis factor-alpha [TNF-alpha; enzyme-linked immunosorbent assay (EIA)]; protein (flow cytometry) and gene (RT-PCR) expression of L-selectin, beta(2)integrin and platelet-endothelial cell adhesion molecule-1 (PECAM-1) were quantified. In vitro neutrophil adhesion to primary culture of microvascular endothelial cell (PMEC) and neutrophil migration in response to formyl-methionil-leucil-phenilalanine (fMLP, 10(-8)M, Boyden chamber) was determined. Results: CGA treatment did not modify the secretion of inflammatory mediators, but inhibited L-selectin cleavage and reduced beta(2) integrin, independently from its mRNA synthesis, and reduced membrane PECAM-1 expression: inhibited neutrophil adhesion and neutrophil migration induced by fMLP. Conclusions: Based on these findings, we highlight the direct inhibitory actions of CGA on adhesive and locomotion properties of neutrophils, which may contribute to its anti-inflammatory effects and help to explain the use of Lychnophora salicifolia as an anti-inflammatory agent. (C) 2011 Elsevier Ireland Ltd. All rights reserved.

Stakeholders Theory and Theory of the Firm: a study on the hierarchy of objective-functions in Brazilian companies

Discussion opposing the Theory of the Firm to the Theory of Stakeholders are contemporaneous and polemical. One focal point of such debates refers to which objective-function companies, should choose, whether that of the shareholders or that of the stakeholders, and whether it is possible to opt for both simultaneously. Several empirical studies. have attempted-to test a possible correlation between both functions, and there has not been any consensus-so far. The objective of the present research is to examine a gap in such discussions: is there (or not) a subordination of the stakeholders` objective-function to that of the shareholders? The research is empirical,and analytical and employs quantitative methods. Hypotheses were tested and data analyzed by using non-parametrical (chi-square test) and parametrical procedures (frequency. correlation `coefficient). Secondary data was collected from he Economitica database and from the Brazilian Institute of Social and-Economic Analyses (IBASE) website, relative to public companies that have published their Social Balance Statements following the IBASE model from 1999 to 2006, whose sample amounted to 65 companies; In order to assess the objective-function of shareholders a proxy was created based on the following three indices: ROE (return on equity), EnterpriseValue and Tobin`s Q. In order to assess the objective-function of stakeholders a proxy was created by employing the following IBASE social balance indices: internal ones (ISI), external ones (ISE), and environmental ones (IAM). The results have shown no evidence of subordination of stakeholders` objective-function to that of the shareholders in analyzed companies, negating initial expectations and calling for deeper investigation of results. Its main conclusion, which states that the attempted subordination does not take place, is limited to the sample herein investigated and calls for ongoing research aiming at improvements which may lead to sample enlargement and, as a consequence, may make feasible the application of other statistical techniques which may yield a more thorough, analysis of the studied phenomehon.

A New Family of Distance Functions for Perceptual Similarity Retrieval of Medical Images

A long-standing challenge of content-based image retrieval (CBIR) systems is the definition of a suitable distance function to measure the similarity between images in an application context which complies with the human perception of similarity. In this paper, we present a new family of distance functions, called attribute concurrence influence distances (AID), which serve to retrieve images by similarity. These distances address an important aspect of the psychophysical notion of similarity in comparisons of images: the effect of concurrent variations in the values of different image attributes. The AID functions allow for comparisons of feature vectors by choosing one of two parameterized expressions: one targeting weak attribute concurrence influence and the other for strong concurrence influence. This paper presents the mathematical definition and implementation of the AID family for a two-dimensional feature space and its extension to any dimension. The composition of the AID family with L (p) distance family is considered to propose a procedure to determine the best distance for a specific application. Experimental results involving several sets of medical images demonstrate that, taking as reference the perception of the specialist in the field (radiologist), the AID functions perform better than the general distance functions commonly used in CBIR.

Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

Comparison of different nonlinear functions to describe Nelore cattle growth

This work aims to compare different nonlinear functions for describing the growth curves of Nelore females. The growth curve parameters, their (co) variance components, and environmental and genetic effects were estimated jointly through a Bayesian hierarchical model. In the first stage of the hierarchy, 4 nonlinear functions were compared: Brody, Von Bertalanffy, Gompertz, and logistic. The analyses were carried out using 3 different data sets to check goodness of fit while having animals with few records. Three different assumptions about SD of fitting errors were considered: constancy throughout the trajectory, linear increasing until 3 yr of age and constancy thereafter, and variation following the nonlinear function applied in the first stage of the hierarchy. Comparisons of the overall goodness of fit were based on Akaike information criterion, the Bayesian information criterion, and the deviance information criterion. Goodness of fit at different points of the growth curve was compared applying the Gelfand`s check function. The posterior means of adult BW ranged from 531.78 to 586.89 kg. Greater estimates of adult BW were observed when the fitting error variance was considered constant along the trajectory. The models were not suitable to describe the SD of fitting errors at the beginning of the growth curve. All functions provided less accurate predictions at the beginning of growth, and predictions were more accurate after 48 mo of age. The prediction of adult BW using nonlinear functions can be accurate when growth curve parameters and their (co) variance components are estimated jointly. The hierarchical model used in the present study can be applied to the prediction of mature BW in herds in which a portion of the animals are culled before adult age. Gompertz, Von Bertalanffy, and Brody functions were adequate to establish mean growth patterns and to predict the adult BW of Nelore females. The Brody model was more accurate in predicting the birth weight of these animals and presented the best overall goodness of fit.

Tooth Tissue Engineering: Optimal Dental Stem Cell Harvest Based on Tooth Development

Our long-term objective is to devise reliable methods to generate biological replacement teeth exhibiting the physical properties and functions of naturally formed human teeth. Previously, we demonstrated the successful use of tissue engineering approaches to generate small, bioengineered tooth crowns from harvested pig and rat postnatal dental stem cells (DSCs). To facilitate characterizations of human DSCs, we have developed a novel radiographic staging system to accurately correlate human third molar tooth developmental stage with anticipated harvested DSC yield. Our results demonstrated that DSC yields were higher in less developed teeth (Stages 1 and 2), and lower in more developed teeth (Stages 3, 4, and 5). The greatest cell yields and colony-forming units (CFUs) capability was obtained from Stages 1 and 2 tooth dental pulp. We conclude that radiographic developmental staging can be used to accurately assess the utility of harvested human teeth for future dental tissue engineering applications.

Scalable model-based configuration management of security services in complex enterprise networks

Security administrators face the challenge of designing, deploying and maintaining a variety of configuration files related to security systems, especially in large-scale networks. These files have heterogeneous syntaxes and follow differing semantic concepts. Nevertheless, they are interdependent due to security services having to cooperate and their configuration to be consistent with each other, so that global security policies are completely and correctly enforced. To tackle this problem, our approach supports a comfortable definition of an abstract high-level security policy and provides an automated derivation of the desired configuration files. It is an extension of policy-based management and policy hierarchies, combining model-based management (MBM) with system modularization. MBM employs an object-oriented model of the managed system to obtain the details needed for automated policy refinement. The modularization into abstract subsystems (ASs) segment the system-and the model-into units which more closely encapsulate related system components and provide focused abstract views. As a result, scalability is achieved and even comprehensive IT systems can be modelled in a unified manner. The associated tool MoBaSeC (Model-Based-Service-Configuration) supports interactive graphical modelling, automated model analysis and policy refinement with the derivation of configuration files. We describe the MBM and AS approaches, outline the tool functions and exemplify their applications and results obtained. Copyright (C) 2010 John Wiley & Sons, Ltd.