On the solubility of proteins as a function of pH: Mathematical development and application

Thermodynamic relations between the solubility of a protein and the solution pH are presented in this work. The hypotheses behind the development are that the protein chemical potential in liquid phase can be described by Henry`s law and that the solid-liquid equilibrium is established only between neutral molecules. The mathematical development results in an analytical expression of the solubility curve, as a function of the ionization equilibrium constants, the pH and the solubility at the isoelectric point. It is shown that the same equation can be obtained either by directly calculating the fraction of neutral protein molecules or by integrating the curve of the protein average charge. The methodology was successfully applied to the description of the solubility of porcine insulin as a function of pH at three different temperatures and of bovine beta-lactoglobulin at four different ionic strengths. (C) 2011 Elsevier B.V. All rights reserved.

A reliable measure of similarity based on dependency for short time series: an application to gene expression networks

Background: Microarray techniques have become an important tool to the investigation of genetic relationships and the assignment of different phenotypes. Since microarrays are still very expensive, most of the experiments are performed with small samples. This paper introduces a method to quantify dependency between data series composed of few sample points. The method is used to construct gene co-expression subnetworks of highly significant edges. Results: The results shown here are for an adapted subset of a Saccharomyces cerevisiae gene expression data set with low temporal resolution and poor statistics. The method reveals common transcription factors with a high confidence level and allows the construction of subnetworks with high biological relevance that reveals characteristic features of the processes driving the organism adaptations to specific environmental conditions. Conclusion: Our method allows a reliable and sophisticated analysis of microarray data even under severe constraints. The utilization of systems biology improves the biologists ability to elucidate the mechanisms underlying celular processes and to formulate new hypotheses.

Directed Abelian algebras and their application to stochastic models

With each directed acyclic graph (this includes some D-dimensional lattices) one can associate some Abelian algebras that we call directed Abelian algebras (DAAs). On each site of the graph one attaches a generator of the algebra. These algebras depend on several parameters and are semisimple. Using any DAA, one can define a family of Hamiltonians which give the continuous time evolution of a stochastic process. The calculation of the spectra and ground-state wave functions (stationary state probability distributions) is an easy algebraic exercise. If one considers D-dimensional lattices and chooses Hamiltonians linear in the generators, in finite-size scaling the Hamiltonian spectrum is gapless with a critical dynamic exponent z=D. One possible application of the DAA is to sandpile models. In the paper we present this application, considering one- and two-dimensional lattices. In the one-dimensional case, when the DAA conserves the number of particles, the avalanches belong to the random walker universality class (critical exponent sigma(tau)=3/2). We study the local density of particles inside large avalanches, showing a depletion of particles at the source of the avalanche and an enrichment at its end. In two dimensions we did extensive Monte-Carlo simulations and found sigma(tau)=1.780 +/- 0.005.

The Kumaraswamy Weibull distribution with application to failure data

For the first time, we introduce and study some mathematical properties of the Kumaraswamy Weibull distribution that is a quite flexible model in analyzing positive data. It contains as special sub-models the exponentiated Weibull, exponentiated Rayleigh, exponentiated exponential, Weibull and also the new Kumaraswamy exponential distribution. We provide explicit expressions for the moments and moment generating function. We examine the asymptotic distributions of the extreme values. Explicit expressions are derived for the mean deviations, Bonferroni and Lorenz curves, reliability and Renyi entropy. The moments of the order statistics are calculated. We also discuss the estimation of the parameters by maximum likelihood. We obtain the expected information matrix. We provide applications involving two real data sets on failure times. Finally, some multivariate generalizations of the Kumaraswamy Weibull distribution are discussed. (C) 2010 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

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.

Bayesian Analysis for Nonlinear Regression Model Under Skewed Errors, with Application in Growth Curves

We have considered a Bayesian approach for the nonlinear regression model by replacing the normal distribution on the error term by some skewed distributions, which account for both skewness and heavy tails or skewness alone. The type of data considered in this paper concerns repeated measurements taken in time on a set of individuals. Such multiple observations on the same individual generally produce serially correlated outcomes. Thus, additionally, our model does allow for a correlation between observations made from the same individual. We have illustrated the procedure using a data set to study the growth curves of a clinic measurement of a group of pregnant women from an obstetrics clinic in Santiago, Chile. Parameter estimation and prediction were carried out using appropriate posterior simulation schemes based in Markov Chain Monte Carlo methods. Besides the deviance information criterion (DIC) and the conditional predictive ordinate (CPO), we suggest the use of proper scoring rules based on the posterior predictive distribution for comparing models. For our data set, all these criteria chose the skew-t model as the best model for the errors. These DIC and CPO criteria are also validated, for the model proposed here, through a simulation study. As a conclusion of this study, the DIC criterion is not trustful for this kind of complex model.

Bleaching of melanin in the epidermis of South American fur seal and its application on enzyme immunohistochemistry

The South American fur seal (Arctocephalus australis) is an amphibious marine mammal distributed along the Atlantic and Pacific coasts of South America. The species is well adjusted to different habitats due to the morphology of its fin-like members and due to some adaptations in their integumentary system. Immunohistochemical studies are very important to evaluate the mechanisms of skin adaptation due the differential expression of the antigens present in the tissue depending of the region of the body surface. However, its strongly pigmented (melanin) epidermis prevents the visualization of the immuno-histochemical chromogens markers. In this study a melanin bleaching method was developed aimed to allow the visualization of the chromogens without interfering in the antigen-antibody affinity for immunohistochemistry. The analysis of PCNA (proliferating cell nuclear antigen) index in the epidermis of A. australis by immunohistochemistry with diaminobenzidine (DAB) as chromogen was used to test the method. The bleaching of the melanin allowed to obtain the cell proliferation index in epidermis and to avoid false positive results without affecting the immunohistochemical results.

A method to determine volatile contaminants in polyethylene terephthalate (PET) packages by HDC-GC-FID and its application to post-consumer materials

A simple and low cost method to determine volatile contaminants in post-consumer recycled PET flakes was developed and validated by Headspace Dynamic Concentration and Gas Chromatography-Flame Ionization Detection (HDC-GC-FID). The analytical parameters evaluated by using surrogates include: correlation coefficient, detection limit, quantification limit, accuracy, intra-assay precision, and inter-assay precision. In order to compare the efficiency of the proposed method to recognized automated techniques, post-consumer PET packaging samples collected in Brazil were used. GC-MS was used to confirm the identity of the substances identified in the PET packaging. Some of the identified contaminants were estimated in the post-consumer material at concentrations higher than 220 ng.g-1. The findings in this work corroborate data available in the scientific literature pointing out the suitability of the proposed analytical method.

Comparative analysis of microsatellite variability in five macaw species (Psittaciformes, Psittacidae): application for conservation

Cross-amplification was tested and variability in microsatellite primers (designed for Neotropical parrots) compared, in five macaw species, viz., three endangered blue macaws (Cyanopsitta spixii [extinct in the wild], Anodorhynchus leari [endangered] and Anodorhynchus hyacinthinus [vulnerable]), and two unthreatened red macaws (Ara chloropterus and Ara macao). Among the primers tested, 84.6% successfully amplified products in C. spixii, 83.3% in A. leari, 76.4% in A. hyacinthinus, 78.6% in A. chloropterus and 71.4% in A. macao. The mean expected heterozygosity estimated for each species, and based on loci analyzed in all the five, ranged from 0.33 (A. hyacinthinus) to 0.85 (A. macao). As expected, the results revealed lower levels of genetic variability in threatened macaw species than in unthreatened. The low combined probability of genetic identity and the moderate to high potential for paternity exclusion, indicate the utility of the microsatellite loci set selected for each macaw species in kinship and population studies, thus constituting an aid in planning in-situ and ex-situ conservation.

Sensitivity evaluation of a single-step PCR assay using Ehrlichia canis p28 gene as a target and its application in diagnosis of canine ehrlichiosis

The aim of this study was to optimize a PCR assay that amplifies an 843 pb fragment from the p28 gene of Ehrlichia canis and compare it with two other PCR methods used to amplify portions of the 16S rRNA and dsb genes of Ehrlichia. Blood samples were collected from dogs suspected of having a positive diagnosis for canine ehrlichiosis. Amplification of the p28 gene by PCR produced an 843-bp fragment and this assay could detect DNA from one gene copy among 1 billion cells. All positive samples detected by the p28-based PCR were also positive by the 16S rRNA nested-PCR and also by the dsb-based PCR. Among the p28-based PCR negative samples, 55.3% were co-negatives, but 27.6% were positive in 16S rRNA and dsb based PCR assays. The p28-based PCR seems to be a useful test for the molecular detection of E. canis, however improvements in this PCR sensitivity are desired, so that it can become an important alternative in the diagnosis of canine ehrlichiosis.

Chaotic Patterns in Aeroelastic Signals

This work presents the analysis of nonlinear aeroelastic time series from wing vibrations due to airflow separation during wind tunnel experiments. Surrogate data method is used to justify the application of nonlinear time series analysis to the aeroelastic system, after rejecting the chance for nonstationarity. The singular value decomposition (SVD) approach is used to reconstruct the state space, reducing noise from the aeroelastic time series. Direct analysis of reconstructed trajectories in the state space and the determination of Poincare sections have been employed to investigate complex dynamics and chaotic patterns. With the reconstructed state spaces, qualitative analyses may be done, and the attractors evolutions with parametric variation are presented. Overall results reveal complex system dynamics associated with highly separated flow effects together with nonlinear coupling between aeroelastic modes. Bifurcations to the nonlinear aeroelastic system are observed for two investigations, that is, considering oscillations-induced aeroelastic evolutions with varying freestream speed, and aeroelastic evolutions at constant freestream speed and varying oscillations. Finally, Lyapunov exponent calculation is proceeded in order to infer on chaotic behavior. Poincare mappings also suggest bifurcations and chaos, reinforced by the attainment of maximum positive Lyapunov exponents. Copyright (C) 2009 F. D. Marques and R. M. G. Vasconcellos.

Sliding wear of weld layers with application to cane mill shaft rebuilding

Three welding procedures used to rebuild worn shafts in sugar cane mills were analysed: two submerged arc welding processes and one flux cored arc welding (FCAW) process. Sliding wear tests were in accordance with ASTM G 77 standard, using rings of welding material, blocks of bronze SAE 67, and oil as lubricant. The worn surfaces of rings and blocks were analysed by scanning electron microscopy to determine the wear mechanisms. High contact pressure, high operating temperature, and low relative speed were applied in sliding wear tests to match the conditions in sugar cane mills. Transferred material and evidence of adhesive junctions were detected. Additionally, hardened fragments produced abrasive grooves on the worn surfaces. The welding deposits that presented strong adhesion on the worn surface showed higher mass loss than the materials that presented more abrasive characteristics. Plastic mechanical properties were measured and related to the mass loss. The tested materials presented similar hardness but different yield stress and hardening coefficient. A relationship between wear, strain hardening coefficient, and yield stress was found. The welding deposit that presented the highest hardening coefficient showed the highest mass loss, with evidence of severe adhesion on the worn surface.

ProbFAST: Probabilistic Functional Analysis System Tool

Background: The post-genomic era has brought new challenges regarding the understanding of the organization and function of the human genome. Many of these challenges are centered on the meaning of differential gene regulation under distinct biological conditions and can be performed by analyzing the Multiple Differential Expression (MDE) of genes associated with normal and abnormal biological processes. Currently MDE analyses are limited to usual methods of differential expression initially designed for paired analysis. Results: We proposed a web platform named ProbFAST for MDE analysis which uses Bayesian inference to identify key genes that are intuitively prioritized by means of probabilities. A simulated study revealed that our method gives a better performance when compared to other approaches and when applied to public expression data, we demonstrated its flexibility to obtain relevant genes biologically associated with normal and abnormal biological processes. Conclusions: ProbFAST is a free accessible web-based application that enables MDE analysis on a global scale. It offers an efficient methodological approach for MDE analysis of a set of genes that are turned on and off related to functional information during the evolution of a tumor or tissue differentiation. ProbFAST server can be accessed at http://gdm.fmrp.usp.br/probfast.

Possibility for a full optical determination of photodynamic therapy outcome

The efficacy of photodynamic therapy (PDT) depends on a variety of parameters: concentration of the photosensitizer at the time of treatment, light wavelength, fluence, fluence rate, availability of oxygen within the illuminated volume, and light distribution in the tissue. Dosimetry in PDT requires the congregation of adequate amounts of light, drug, and tissue oxygen. The adequate dosimetry should be able to predict the extension of the tissue damage. Photosensitizer photobleaching rate depends on the availability of molecular oxygen in the tissue. Based on photosensitizers photobleaching models, high photobleaching has to be associated with high production of singlet oxygen and therefore with higher photodynamic action, resulting in a greater depth of necrosis. The purpose of this work is to show a possible correlation between depth of necrosis and the in vivo photosensitizer (in this case, Photogem (R)) photodegradation during PDT. Such correlation allows possibilities for the development of a real time evaluation of the photodynamic action during PDT application. Experiments were performed in a range of fluence (0-450 J/cm(2)) at a constant fluence rate of 250 mW/cm(2) and applying different illumination times (0-1800 s) to achieve the desired fluence. A quantity was defined (psi) as the product of fluorescence ratio (related to the photosensitizer degradation at the surface) and the observed depth of necrosis. The correlation between depth of necrosis and surface fluorescence signal is expressed in psi and could allow, in principle, a noninvasive monitoring of PDT effects during treatment. High degree of correlation is observed and a simple mathematical model to justify the results is presented.

A score system for quality evaluation of RNA sequence tags: an improvement for gene expression profiling

Background: High-throughput molecular approaches for gene expression profiling, such as Serial Analysis of Gene Expression (SAGE), Massively Parallel Signature Sequencing (MPSS) or Sequencing-by-Synthesis (SBS) represent powerful techniques that provide global transcription profiles of different cell types through sequencing of short fragments of transcripts, denominated sequence tags. These techniques have improved our understanding about the relationships between these expression profiles and cellular phenotypes. Despite this, more reliable datasets are still necessary. In this work, we present a web-based tool named S3T: Score System for Sequence Tags, to index sequenced tags in accordance with their reliability. This is made through a series of evaluations based on a defined rule set. S3T allows the identification/selection of tags, considered more reliable for further gene expression analysis. Results: This methodology was applied to a public SAGE dataset. In order to compare data before and after filtering, a hierarchical clustering analysis was performed in samples from the same type of tissue, in distinct biological conditions, using these two datasets. Our results provide evidences suggesting that it is possible to find more congruous clusters after using S3T scoring system. Conclusion: These results substantiate the proposed application to generate more reliable data. This is a significant contribution for determination of global gene expression profiles. The library analysis with S3T is freely available at http://gdm.fmrp.usp.br/s3t/.S3T source code and datasets can also be downloaded from the aforementioned website.