Polarization effects in molecular dynamics simulations of glass-formers Ca(NO(3))(2)center dot nH(2)O, n=4, 6, and 8

Thermodynamics, equilibrium structure, and dynamics of glass-forming liquids Ca(NO(3))(2)center dot nH(2)O, n=4, 6, and 8, have been investigated by molecular dynamics (MD) simulations. A polarizable model was considered for H(2)O and NO(3)- on the basis of previous fluctuating charge models for pure water and the molten salt 2Ca(NO(3))(2)center dot 3KNO(3). Similar thermodynamic properties have been obtained with nonpolarizable and polarizable models. The glass transition temperature, T(g), estimated from MD simulations was dependent on polarization, in particular the dependence of T(g) with electrolyte concentration. Significant polarization effects on equilibrium structure were observed in cation-cation, cation-anion, and water-water structures. Polarization increases the diffusion coefficient of H(2)O, but does not change significantly the diffusion coefficients of ions. Viscosity decreases upon inclusion of polarization, but the conductivity calculated with the polarizable model is smaller than the nonpolarizable model because polarization enhances anion-cation interactions.

Fragility and glassy dynamics of 2Ca(NO(3))(2)center dot 3KNO(3) under pressure: Molecular dynamics simulations

Molecular dynamics simulations of the glass-forming liquid 2Ca(NO(3))(2)center dot 3KNO(3) (CKN) were performed from high temperature liquid states down to low temperature glassy states at six different pressures from 10(-4) to 5.0 GPa. The temperature dependence of the structural relaxation time indicates that the fragility of liquid CKN changes with pressure. In line with recent proposal [Scopigno , Science 302, 849 (2003)], the change on liquid fragility is followed by a proportional change of the nonergodicity factor of the corresponding glass at low temperature. (c) 2008 American Institute of Physics.

Validation of dot blot hybridization and denaturing high performance liquid chromatography as reliable methods for TP53 codon 72 genotyping in molecular epidemiologic studies

Background: Mutations in TP53 are common events during carcinogenesis. In addition to gene mutations, several reports have focused on TP53 polymorphisms as risk factors for malignant disease. Many studies have highlighted that the status of the TP53 codon 72 polymorphism could influence cancer susceptibility. However, the results have been inconsistent and various methodological features can contribute to departures from Hardy-Weinberg equilibrium, a condition that may influence the disease risk estimates. The most widely accepted method of detecting genotyping error is to confirm genotypes by sequencing and/or via a separate method. Results: We developed two new genotyping methods for TP53 codon 72 polymorphism detection: Denaturing High Performance Liquid Chromatography (DHPLC) and Dot Blot hybridization. These methods were compared with Restriction Fragment Length Polymorphism (RFLP) using two different restriction enzymes. We observed high agreement among all methodologies assayed. Dot-blot hybridization and DHPLC results were more highly concordant with each other than when either of these methods was compared with RFLP. Conclusions: Although variations may occur, our results indicate that DHPLC and Dot Blot hybridization can be used as reliable screening methods for TP53 codon 72 polymorphism detection, especially in molecular epidemiologic studies, where high throughput methodologies are required.

Molecular and morphological characterization of Amathia distans Busk and Amathia brasiliensis Busk (Bryozoa: Ctenostomata) from the tropical and subtropical Western Atlantic

Morphological and molecular analyses have proven to be complementary tools of taxonomic information for the redescription of the ctenostome bryozoans Amathia brasiliensis Busk, 1886 and Amathia distans Busk, 1886. The two species, originally described from material collected by the `Challenger` expedition but synonymized by later authors, now have their status fixed by means of the selection of lectotypes, morphological observations and analyses of DNA sequences described here. The morphological characters allowing the identification of living and/or preserved specimens are (1) A. brasiliensis: whitish-pale pigment spots in the frontal surface of stolons and zooids, and a wide stolon with biserial zooid clusters growing in clockwise and anti-clockwise spirals along it, the spirality direction being maintained from maternal to daughter stolons; and (2) A. distans: bright yellow pigment spots in stolonal and zooidal surfaces including lophophores, and a slender stolon, thickly cuticularized, with biserial zooid clusters growing in clockwise and anti-clockwise spirals along it and the spirality direction not maintained from maternal to daughter stolons. Pairwise comparisons of DNA sequences of the mitochondrial genes cytochrome c oxidase subunit I and large ribosomal RNA subunit revealed deep genetic divergence between A. brasiliensis and A. distans. Finally, analyses of those sequences within a Bayesian phylogenetic context recovered their genealogical species status.

DISTRIBUTION OF CAPYBARAS IN AN AGROECOSYSTEM, SOUTHEASTERN BRAZIL, BASED ON ECOLOGICAL NICHE MODELING

Southeastern Brazil has seen dramatic landscape modifications in recent decades, due to expansion of agriculture and urban areas; these changes have influenced the distribution and abundance of vertebrates. We developed predictive models of ecological and spatial distributions of capybaras (Hydrochoerus hydrochaeris) using ecological niche modeling. Most Occurrences of capybaras were in flat areas with water bodies Surrounded by sugarcane and pasture. More than 75% of the Piracicaba River basin was estimated as potentially habitable by capybara. The models had low omission error (2.3-3.4%), but higher commission error (91.0-98.5%); these ""model failures"" seem to be more related to local habitat characteristics than to spatial ones. The potential distribution of capybaras in the basin is associated with anthropogenic habitats, particularly with intensive land use for agriculture.

MODELING SCIENTIFIC AGENTS FOR A BETTER SCIENCE

Science is a fundamental human activity and we trust its results because it has several error-correcting mechanisms. It is subject to experimental tests that are replicated by independent parts. Given the huge amount of information available and the information asymetry between producers and users of knowledge, scientists have to rely on the reports of others. This makes it possible for social effects to influence the scientific community. Here, an Opinion Dynamics agent model is proposed to describe this situation. The influence of Nature through experiments is described as an external field that acts on the experimental agents. We will see that the retirement of old scientists can be fundamental in the acceptance of a new theory. We will also investigate the interplay between social influence and observations. This will allow us to gain insight in the problem of when social effects can have negligible effects in the conclusions of a scientific community and when we should worry about them.

Exploring the emission intensities of ICP OES aided by chemometrics in the geographical discrimination of mineral waters

A rapid method for classification of mineral waters is proposed. The discrimination power was evaluated by a novel combination of chemometric data analysis and qualitative multi-elemental fingerprints of mineral water samples acquired from different regions of the Brazilian territory. The classification of mineral waters was assessed using only the wavelength emission intensities obtained by inductively coupled plasma optical emission spectrometry (ICP OES), monitoring different lines of Al, B, Ba, Ca, Cl, Cu, Co, Cr, Fe, K, Mg, Mn, Na, Ni, P, Pb, S, Sb, Si, Sr, Ti, V, and Zn, and Be, Dy, Gd, In, La, Sc and Y as internal standards. Data acquisition was done under robust (RC) and non-robust (NRC) conditions. Also, the combination of signal intensities of two or more emission lines for each element were evaluated instead of the individual lines. The performance of two classification-k-nearest neighbor (kNN) and soft independent modeling of class analogy (SIMCA)-and preprocessing algorithms, autoscaling and Pareto scaling, were evaluated for the ability to differentiate between the various samples in each approach tested (combination of robust or non-robust conditions with use of individual lines or sum of the intensities of emission lines). It was shown that qualitative ICP OES fingerprinting in combination with multivariate analysis is a promising analytical tool that has potential to become a recognized procedure for rapid authenticity and adulteration testing of mineral water samples or other material whose physicochemical properties (or origin) are directly related to mineral content.

Experimental chronic low-frequency resistance training produces skeletal muscle hypertrophy in the absence of muscle damage and metabolic stress markers

Volitional animal resistance training constitutes an important approach to modeling human resistance training. However, the lack of standardization protocol poses a frequent impediment to the production of skeletal muscle hypertrophy and the study of related physiological variables (i.e., cellular damage/inflammation or metabolic stress). Therefore, the purposes of the present study were: (1) to test whether a long-term and low frequency experimental resistance training program is capable of producing absolute increases in muscle mass; (2) to examine whether cellular damage/inflammation or metabolic stress is involved in the process of hypertrophy. In order to test this hypothesis, animals were assigned to a sedentary control (C, n = 8) or a resistance trained group (RT, n = 7). Trained rats performed 2 exercise sessions per week (16 repetitions per day) during 12 weeks. Our results demonstrated that the resistance training strategy employed was capable of producing absolute mass gain in both soleus and plantaris muscles (12%, p<0.05). Furthermore, muscle tumor necrosis factor (TNF-alpha) protein expression (soleus muscle) was reduced by 24% (p<0.01) in trained group when compared to sedentary one. Finally, serum creatine kinase (CK) activity and serum lactate concentrations were not affected in either group. Such information may have practical applications if reproduced in situations where skeletal muscle hypertrophy is desired but high mechanical stimuli of skeletal muscle and inflammation are not. Copyright (C) 2010 John Wiley & Sons, Ltd.

Ringo: Discordance between the molecular and clinical manifestation in a Golden Retriever Muscular Dystrophy dog

Of the various genetic homologues to Duchenne Muscular Dystrophy (DMD), the Golden Retriever Muscular Dystrophy (GRMD) dog, which presents a variable but usually severe and progressive muscle weakness, has the closest relevance to DMD in both clinical severity and histopathological change. Among 77 GRMD dogs born in our colony in Brazil, we have identified a very mildly affected dog, Ringo, born July 2003. Among his descendants, at least one male, Suflair, is also showing a mild course. In an attempt to better characterize these two dogs, we studied the pattern of muscle proteins expression in Ringo and Suflair, as compared to severely affected and normal control dogs. Dystrophin was absent in both and utrophin was overexpressed in a pattern similar to the observed in severely affected dogs. Understanding the mechanism that is protecting Ringo and Suflair from the deleterious effect of the dystrophin gene mutation is of utmost interest, In addition it points out that the clinical impact of therapeutic trials should be interpreted with caution. (C) 2009 Elsevier B.V. All rights reserved.

Improved xylitol production in media containing phenolic aldehydes: application of response surface methodology for optimization and modeling of bioprocess

BACKGROUND: The combined effects of vanillin and syringaldehyde on xylitol production by Candida guilliermondii using response surface methodology (RSM) have been studied. A 2(2) full-factorial central composite design was employed for experimental design and analysis of the results. RESULTS: Maximum xylitol productivities (Q(p) = 0.74 g L(-1) h(-1)) and yields (Y(P/S) = 0.81 g g(-1)) can be attained by adding only vanillin at 2.0 g L(-1) to the fermentation medium. These data were closely correlated with the experimental results obtained (0.69 +/- 0.04 g L(-1) h(-1) and 0.77 +/- 0.01 g g(-1)) indicating a good agreement with the predicted value. C. guilliermondii was able to convert vanillin completely after 24 h of fermentation with 94% yield of vanillyl alcohol. CONCLUSIONS: The bioconversion of xylose into xylitol by C. guilliermondii is strongly dependent on the combination of aldehydes and phenolics in the fermentation medium. Vanillin is a source of phenolic compound able to improve xylitol production by yeast. The conversion of vanillin to alcohol vanilyl reveals the potential of this yeast for medium detoxification. (C) 2009 Society of Chemical Industry

Biomimetic oxidative treatment of spruce wood studied by pyrolysis-molecular beam mass spectrometry coupled with multivariate analysis and (13)C-labeled tetramethylammonium hydroxide thermochemolysis: implications for fungal degradation of wood

In this work, pyrolysis-molecular beam mass spectrometry analysis coupled with principal components analysis and (13)C-labeled tetramethylammonium hydroxide thermochemolysis were used to study lignin oxidation, depolymerization, and demethylation of spruce wood treated by biomimetic oxidative systems. Neat Fenton and chelator-mediated Fenton reaction (CMFR) systems as well as cellulosic enzyme treatments were used to mimic the nonenzymatic process involved in wood brown-rot biodegradation. The results suggest that compared with enzymatic processes, Fenton-based treatment more readily opens the structure of the lignocellulosic matrix, freeing cellulose fibrils from the matrix. The results demonstrate that, under the current treatment conditions, Fenton and CMFR treatment cause limited demethoxylation of lignin in the insoluble wood residue. However, analysis of a water-extractable fraction revealed considerable soluble lignin residue structures that had undergone side chain oxidation as well as demethoxylation upon CMFR treatment. This research has implications for our understanding of nonenzymatic degradation of wood and the diffusion of CMFR agents in the wood cell wall during fungal degradation processes.

Modeling associations between genetic markers using Bayesian networks

Motivation: Understanding the patterns of association between polymorphisms at different loci in a population ( linkage disequilibrium, LD) is of fundamental importance in various genetic studies. Many coefficients were proposed for measuring the degree of LD, but they provide only a static view of the current LD structure. Generative models (GMs) were proposed to go beyond these measures, giving not only a description of the actual LD structure but also a tool to help understanding the process that generated such structure. GMs based in coalescent theory have been the most appealing because they link LD to evolutionary factors. Nevertheless, the inference and parameter estimation of such models is still computationally challenging. Results: We present a more practical method to build GM that describe LD. The method is based on learning weighted Bayesian network structures from haplotype data, extracting equivalence structure classes and using them to model LD. The results obtained in public data from the HapMap database showed that the method is a promising tool for modeling LD. The associations represented by the learned models are correlated with the traditional measure of LD D`. The method was able to represent LD blocks found by standard tools. The granularity of the association blocks and the readability of the models can be controlled in the method. The results suggest that the causality information gained by our method can be useful to tell about the conservability of the genetic markers and to guide the selection of subset of representative markers.

Node-Depth Encoding and Multiobjective Evolutionary Algorithm Applied to Large-Scale Distribution System Reconfiguration

The power loss reduction in distribution systems (DSs) is a nonlinear and multiobjective problem. Service restoration in DSs is even computationally hard since it additionally requires a solution in real-time. Both DS problems are computationally complex. For large-scale networks, the usual problem formulation has thousands of constraint equations. The node-depth encoding (NDE) enables a modeling of DSs problems that eliminates several constraint equations from the usual formulation, making the problem solution simpler. On the other hand, a multiobjective evolutionary algorithm (EA) based on subpopulation tables adequately models several objectives and constraints, enabling a better exploration of the search space. The combination of the multiobjective EA with NDE (MEAN) results in the proposed approach for solving DSs problems for large-scale networks. Simulation results have shown the MEAN is able to find adequate restoration plans for a real DS with 3860 buses and 632 switches in a running time of 0.68 s. Moreover, the MEAN has shown a sublinear running time in function of the system size. Tests with networks ranging from 632 to 5166 switches indicate that the MEAN can find network configurations corresponding to a power loss reduction of 27.64% for very large networks requiring relatively low running time.

A Study on Unconditionally Stable FDTD Methods for the Modeling of Metamaterials

We assess the performance of three unconditionally stable finite-difference time-domain (FDTD) methods for the modeling of doubly dispersive metamaterials: 1) locally one-dimensional FDTD; 2) locally one-dimensional FDTD with Strang splitting; and (3) alternating direction implicit FDTD. We use both double-negative media and zero-index media as benchmarks.

GOOAL: A routine based on Genetic Algorithms to track harmonics in electric power systems

Voltage and current waveforms of a distribution or transmission power system are not pure sinusoids. There are distortions in these waveforms that can be represented as a combination of the fundamental frequency, harmonics and high frequency transients. This paper presents a novel approach to identifying harmonics in power system distorted waveforms. The proposed method is based on Genetic Algorithms, which is an optimization technique inspired by genetics and natural evolution. GOOAL, a specially designed intelligent algorithm for optimization problems, was successfully implemented and tested. Two kinds of representations concerning chromosomes are utilized: binary and real. The results show that the proposed method is more precise than the traditional Fourier Transform, especially considering the real representation of the chromosomes.