Hyaluronidase from the venom of the social wasp Polybia paulista (Hymenoptera, Vespidae): Cloning, structural modeling, purification, and immunological analysis

In this study, we describe the cDNA cloning, sequencing, and 3-D structure of the allergen hyaluronidase from Polybia paulista venom (Pp-Hyal). Using a proteomic approach, the native form of Pp-Hyal was purified to homogeneity and used to produce a Pp-specific polyclonal antibody. The results revealed that Pp-Hyal can be classified as a glycosyl hydrolase and that the full-length Pp-Hyal cDNA (1315 bp; GI: 302201582) is similar (80-90%) to hyaluronidase from the venoms of endemic Northern wasp species. The isolated mature protein is comprised of 338 amino acids, with a theoretical pI of 8.77 and a molecular mass of 39,648.8 Da versus a pI of 8.13 and 43,277.0 Da indicated by MS. The Pp-Hyal 3D-structural model revealed a central core (α/β)7 barrel, two sulfide bonds (Cys 19-308 and Cys 185-197), and three putative glycosylation sites (Asn79, Asn187, and Asn325), two of which are also found in the rVes v 2 protein. Based on the model, residues Ser299, Asp107, and Glu109 interact with the substrate and potential epitopes (five conformational and seven linear) located at surface-exposed regions of the structure. Purified native Pp-Hyal showed high similarity (97%) with hyaluronidase from Polistes annularis venom (Q9U6V9). Immunoblotting analysis confirmed the specificity of the Pp-Hyal-specific antibody as it recognized the Pp-Hyal protein in both the purified fraction and P. paulista crude venom. No reaction was observed with the venoms of Apis mellifera, Solenopsis invicta, Agelaia pallipes pallipes, and Polistes lanio lanio, with the exception of immune cross-reactivity with venoms of the genus Polybia (sericea and ignobilis). Our results demonstrate cross-reactivity only between wasp venoms from the genus Polybia. The absence of cross-reactivity between the venoms of wasps and bees observed here is important because it allows identification of the insect responsible for sensitization, or at least of the phylogenetically closest insect, in order to facilitate effective immunotherapy in allergic patients. © 2013 Elsevier Ltd.

Aspects of Mechanical Behavior and Modeling of a Tropical Unsaturated Soil

The research studies the applicability of two elastoplastic models for the collapse prediction of the lateritic soil profile from Southeastern Brazil. These tropical soils have peculiar geotechnical behavior, due to their mineralogical composition and porous structure coming from intense process of formation. Two elastoplastic models were analyzed: the Barcelona Basic Model (BBM) and another one based on BBM, however developed for tropical soils. Oedometric tests with suction control were performed at three distinct depths of the soil profile. The BBM was not suitable for the upper layer of the soil profile, because BBM considers the compressible behavior of the soil in function of the reduction of the elastoplastic compressibility index with the increase of the matric suction. The model developed for tropical soils showed better suited to the compressible behavior of the soil profile, resulting in good prediction of the collapse potential, mainly by accepting increasing values of the elastoplastic compressibility index of the soil profile with the matric suction rise. © 2013 Springer Science+Business Media Dordrecht.

Basic ingredients for mathematical modeling of tumor growth in vitro: Cooperative effects and search for space

Based on the literature data from HT-29 cell monolayers, we develop a model for its growth, analogous to an epidemic model, mixing local and global interactions. First, we propose and solve a deterministic equation for the progress of these colonies. Thus, we add a stochastic (local) interaction and simulate the evolution of an Eden-like aggregate by using dynamical Monte Carlo methods. The growth curves of both deterministic and stochastic models are in excellent agreement with the experimental observations. The waiting times distributions, generated via our stochastic model, allowed us to analyze the role of mesoscopic events. We obtain log-normal distributions in the initial stages of the growth and Gaussians at long times. We interpret these outcomes in the light of cellular division events: in the early stages, the phenomena are dependent each other in a multiplicative geometric-based process, and they are independent at long times. We conclude that the main ingredients for a good minimalist model of tumor growth, at mesoscopic level, are intrinsic cooperative mechanisms and competitive search for space. © 2013 Elsevier Ltd.

Electrically detected magnetic resonance modeling and fitting: An equivalent circuit approach

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Thermochemical equilibrium modeling of biomass downdraft gasifier: Stoichiometric models

The aim of this work is to develop stoichiometric equilibrium models that permit the study of parameters effect in the gasification process of a particular feedstock. In total four models were tested in order to determine the syngas composition. One of these four models, called M2, was based on the theoretical equilibrium constants modified by two correction factors determined using published experimental data. The other two models, M3 and M4 were based in correlations, while model M4 was based in correlations to determine the equilibrium constants, model M3 was based in correlations that relate the H-2, CO and CO2 content on the synthesis gas. Model M2 proved to be the more accurate and versatile among these four models, and also showed better results than some previously published models. Also a case study for the gasification of a blend of hardwood chips and glycerol at 80% and 20% respectively, was performed considering equivalence ratios form 0.3 to 0.5, moisture contents from 0%-20% and oxygen percentages in the gasification agent of 100%, 60% and 21%. (C) 2013 Elsevier Ltd. All rights reserved.

Delaunay Tetrahedralization of the Heart Based on Integration of Open Source Codes

The Finite Element Method (FEM) is a way of numerical solution applied in different areas, as simulations used in studies to improve cardiac ablation procedures. For this purpose, the meshes should have the same size and histological features of the focused structures. Some methods and tools used to generate tetrahedral meshes are limited mainly by the use conditions. In this paper, the integration of Open Source Softwares is presented as an alternative to solid modeling and automatic mesh generation. To demonstrate its efficiency, the cardiac structures were considered as a first application context: atriums, ventricles, valves, arteries and pericardium. The proposed method is feasible to obtain refined meshes in an acceptable time and with the required quality for simulations using FEM.

The zero-inflated Conway-Maxwell-Poisson distribution: Bayesian inference, regression modeling and influence diagnostic

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Lumped element modeling of operational structures by inverting the mobility models

This paper is concerned with what a source precisely sees when it drives a receiver such as a continuous structural object. An equivalent lumped element system consisting of masses, springs and dampers is developed to visually represent the operational structural dynamics of a single-input structure at the driving point. The development is solely based on the mobility model of the driving point response. The mobility model is mathematically inverted to give the impedance model that is suitable for lumped element modeling. The two types of structures studied are unconstrained inertial objects and constrained resilient objects. The lumped element systems presented suggest a new view to dynamics that a single-input flexible structure in operation can be decomposed into the two subsystems: a base system of single degree of freedom (or of a mass for an inertial object) whose mass is in contact with the source and an appendage system consisting of a series of oscillators each of which is attached to the base mass. The driving point response is a result of the coupling between the two subsystems. (C) 2014 Elsevier Ltd. All rights reserved.

Inverse Modeling of GPS Multipath for Snow Depth Estimation-Part I: Formulation and Simulations

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A new biomimetic sensor based on molecularly imprinted polymers for highly sensitive and selective determination of hexazinone herbicide

A new selective sensor based on molecularly imprinted polymers (MIPs) was developed for the determination of hexazinone (HXZ) in environmental samples. MIPs were synthesized using a non-covalent approach, and selection of the monomers employed in the polymerization reaction was carried out by molecular modeling. Three functional monomers with high (2-vinylpyridine (MP17)) and intermediate (methacrylic acid (MP12) and acrylamide (MP5)) energies of binding to the template (HXZ) were selected for preparation of the MIPs, in order to conduct comparative studies and validate the theoretical data. For sensor construction, carbon pastes were modified with each MIP or NIP (non-imprinted polymer), and HXZ determination was performed using differential pulse adsorptive cathodic stripping voltammetry (DPAdCSV). All parameters affecting the sensor response were optimized. In HCl at pH 2.5, the sensor prepared with MP17 (5% w/w in the paste) showed a dynamic linear range between 1.9 × 10−11 and 1.1 × 10−10 mol L−1, and a detection limit of 2.6 × 10−12 mol L−1, under the following conditions: accumulation time of 200 s at a potential of −0.5V, scan rate of 50 mVs−1, pulse amplitude of 60 mV, and pulse width of 50 ms. The sensor was selective in the presence of other similar compounds, and was successfully applied to the analysis of HXZ in river water samples.

Automatic method to classify images based on multiscale fractal descriptors and paraconsistent logic

In this study is presented an automatic method to classify images from fractal descriptors as decision rules, such as multiscale fractal dimension and lacunarity. The proposed methodology was divided in three steps: quantification of the regions of interest with fractal dimension and lacunarity, techniques under a multiscale approach; definition of reference patterns, which are the limits of each studied group; and, classification of each group, considering the combination of the reference patterns with signals maximization (an approach commonly considered in paraconsistent logic). The proposed method was used to classify histological prostatic images, aiming the diagnostic of prostate cancer. The accuracy levels were important, overcoming those obtained with Support Vector Machine (SVM) and Bestfirst Decicion Tree (BFTree) classifiers. The proposed approach allows recognize and classify patterns, offering the advantage of giving comprehensive results to the specialists.

Classification of histological images based on the stationary wavelet transform

Non-Hodgkin lymphomas are of many distinct types, and different classification systems make it difficult to diagnose them correctly. Many of these systems classify lymphomas only based on what they look like under a microscope. In 2008 the World Health Organisation (WHO) introduced the most recent system, which also considers the chromosome features of the lymphoma cells and the presence of certain proteins on their surface. The WHO system is the one that we apply in this work. Herewith we present an automatic method to classify histological images of three types of non-Hodgkin lymphoma. Our method is based on the Stationary Wavelet Transform (SWT), and it consists of three steps: 1) extracting sub-bands from the histological image through SWT, 2) applying Analysis of Variance (ANOVA) to clean noise and select the most relevant information, 3) classifying it by the Support Vector Machine (SVM) algorithm. The kernel types Linear, RBF and Polynomial were evaluated with our method applied to 210 images of lymphoma from the National Institute on Aging. We concluded that the following combination led to the most relevant results: detail sub-band, ANOVA and SVM with Linear and RBF kernels.

Surface coverage in wireless sensor networks based on delaunay tetrahedralization

In this work is presented a new method for sensor deployment on 3D surfaces. The method was structured on different steps. The first one aimed discretizes the relief of interest with Delaunay algorithm. The tetrahedra and relative values (spatial coordinates of each vertex and faces) were input to construction of 3D Voronoi diagram. Each circumcenter was calculated as a candidate position for a sensor node: the corresponding circular coverage area was calculated based on a radius r. The r value can be adjusted to simulate different kinds of sensors. The Dijkstra algorithm and a selection method were applied to eliminate candidate positions with overlapped coverage areas or beyond of surface of interest. Performance evaluations measures were defined using coverage area and communication as criteria. The results were relevant, once the mean coverage rate achieved on three different surfaces were among 91% and 100%.

Investigation, expression, and molecular modeling of ORF2, a metagenomic lipolytic enzyme

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Semiautomatic object-space road extraction combining a stereoscopic image pair and a TIN-Based DTM

In this letter, a semiautomatic method for road extraction in object space is proposed that combines a stereoscopic pair of low-resolution aerial images with a digital terrain model (DTM) structured as a triangulated irregular network (TIN). First, we formulate an objective function in the object space to allow the modeling of roads in 3-D. In this model, the TIN-based DTM allows the search for the optimal polyline to be restricted along a narrow band that is overlaid upon it. Finally, the optimal polyline for each road is obtained by optimizing the objective function using the dynamic programming optimization algorithm. A few seed points need to be supplied by an operator. To evaluate the performance of the proposed method, a set of experiments was designed using two stereoscopic pairs of low-resolution aerial images and a TIN-based DTM with an average resolution of 1 m. The experimental results showed that the proposed method worked properly, even when faced with anomalies along roads, such as obstructions caused by shadows and trees.