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.

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.

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.

Realistic calculations of carbon-based disordered systems

Carbon nanotubes rank amongst potential candidates for a new family of nanoscopic devices, in particular for sensing applications. At the same time that defects in carbon nanotubes act as binding sites for foreign species, our current level of control over the fabrication process does not allow one to specifically choose where these binding sites will actually be positioned. In this work we present a theoretical framework for accurately calculating the electronic and transport properties of long disordered carbon nanotubes containing a large number of binding sites randomly distributed along a sample. This method combines the accuracy and functionality of ab initio density functional theory to determine the electronic structure with a recursive Green`s functions method. We apply this methodology on the problem of nitrogen-rich carbon nanotubes, first considering different types of defects and then demonstrating how our simulations can help in the field of sensor design by allowing one to compute the transport properties of realistic nanotube devices containing a large number of randomly distributed binding sites.

Disorder-based graphene spintronics

The use of the spin of the electron as the ultimate logic bit-in what has been dubbed spintronics-can lead to a novel way of thinking about information flow. At the same time single-layer graphene has been the subject of intense research due to its potential application in nanoscale electronics. While defects can significantly alter the electronic properties of nanoscopic systems, the lack of control can lead to seemingly deleterious effects arising from the random arrangement of such impurities. Here we demonstrate, using ab initio density functional theory and non-equilibrium Green`s functions calculations, that it is possible to obtain perfect spin selectivity in doped graphene nanoribbons to produce a perfect spin filter. We show that initially unpolarized electrons entering the system give rise to 100% polarization of the current due to random disorder. This effect is explained in terms of different localization lengths for each spin channel which leads to a new mechanism for the spin filtering effect that is disorder-driven.

U-curve: A branch-and-bound optimization algorithm for U-shaped cost functions on Boolean lattices applied to the feature selection problem

This paper presents the formulation of a combinatorial optimization problem with the following characteristics: (i) the search space is the power set of a finite set structured as a Boolean lattice; (ii) the cost function forms a U-shaped curve when applied to any lattice chain. This formulation applies for feature selection in the context of pattern recognition. The known approaches for this problem are branch-and-bound algorithms and heuristics that explore partially the search space. Branch-and-bound algorithms are equivalent to the full search, while heuristics are not. This paper presents a branch-and-bound algorithm that differs from the others known by exploring the lattice structure and the U-shaped chain curves of the search space. The main contribution of this paper is the architecture of this algorithm that is based on the representation and exploration of the search space by new lattice properties proven here. Several experiments, with well known public data, indicate the superiority of the proposed method to the sequential floating forward selection (SFFS), which is a popular heuristic that gives good results in very short computational time. In all experiments, the proposed method got better or equal results in similar or even smaller computational time. (C) 2009 Elsevier Ltd. All rights reserved.

Regression analysis of mean quality-adjusted survival time based on pseudo-observations

Regression models for the mean quality-adjusted survival time are specified from hazard functions of transitions between two states and the mean quality-adjusted survival time may be a complex function of covariates. We discuss a regression model for the mean quality-adjusted survival (QAS) time based on pseudo-observations, which has the advantage of directly modeling the effect of covariates in the QAS time. Both Monte Carlo Simulations and a real data set are studied. Copyright (C) 2009 John Wiley & Sons, Ltd.

Silver Nanoparticles Obtained in PAH/PAA-Based Multilayers by Photochemical Reaction

Carboxylic acid groups in PAH/PAA-based multilayers bind silver cations by ion exchange with the acid protons. The aggregation and spatial distribution of the nanoparticles proved to be dependent oil the process used to reduce the silver acetate aqueous solution. The reducing method with ambient light formed larger nanoparticles with diameters ranging from 4-50 nm in comparison with the reduction method using UV light, which gave particles with diameters of 2-4 nm The high toughness of samples reduced by ambient light is a result of two population distributions of particle sizes caused by different mechanisms when compared with the UV light process. According to these phenomena, a judicious choice of the spectral source call be used as a way to control the type and size of silver nanoparticles formed on PEMs. Depending on the energy of the light source, the Ag nanoparticles present cubic and/or hexagonal crystallographic structures, as confirmed by XRD. Beyond the kinetically controlled process of UV photoinduced cluster formation, the annealing produced by UV light allowed a second mechanism to modify the growth rates, spatial distribution, and phases.