Application of the log-conformation tensor to three-dimensional time-dependent free surface flows

The numerical simulation of flows of highly elastic fluids has been the subject of intense research over the past decades with important industrial applications. Therefore, many efforts have been made to improve the convergence capabilities of the numerical methods employed to simulate viscoelastic fluid flows. An important contribution for the solution of the High-Weissenberg Number Problem has been presented by Fattal and Kupferman [J. Non-Newton. Fluid. Mech. 123 (2004) 281-285] who developed the matrix-logarithm of the conformation tensor technique, henceforth called log-conformation tensor. Its advantage is a better approximation of the large growth of the stress tensor that occur in some regions of the flow and it is doubly beneficial in that it ensures physically correct stress fields, allowing converged computations at high Weissenberg number flows. In this work we investigate the application of the log-conformation tensor to three-dimensional unsteady free surface flows. The log-conformation tensor formulation was applied to solve the Upper-Convected Maxwell (UCM) constitutive equation while the momentum equation was solved using a finite difference Marker-and-Cell type method. The resulting developed code is validated by comparing the log-conformation results with the analytic solution for fully developed pipe flows. To illustrate the stability of the log-conformation tensor approach in solving three-dimensional free surface flows, results from the simulation of the extrudate swell and jet buckling phenomena of UCM fluids at high Weissenberg numbers are presented. (C) 2012 Elsevier B.V. All rights reserved.

Application of Electrochemical Degradation of Wastewater Composed of Mixtures of Phenol-Formaldehyde

The industrial wastewater from resin production plants contains as major components phenol and formaldehyde, which are traditionally treated by biological methods. As a possible alternative method, electrochemical treatment was tested using solutions containing a mixture of phenol and formaldehyde simulating an industrial effluent. The anode used was a dimensionally stable anode (DSAA (R)) of nominal composition Ti/Ru0.3Ti0.7O2, and the solution composition during the degradation process was analyzed by liquid chromatography and the removal of total organic carbon. From cyclic voltammetry, it is observed that for formaldehyde, a small offset of the beginning of the oxygen evolution reaction occurs, but for phenol, the reaction is inhibited and the current density decreases. From the electrochemical degradations, it was determined that 40 mA cm(-2) is the most efficient current density and the comparison of different supporting electrolytes (Na2SO4, NaNO3, and NaCl) indicated a higher removal of total organic carbon in NaCl medium.

A General Latent Class Model for Performance Evaluation of Diagnostic Tests in the Absence of a Gold Standard: An Application to Chagas Disease

We propose a new general Bayesian latent class model for evaluation of the performance of multiple diagnostic tests in situations in which no gold standard test exists based on a computationally intensive approach. The modeling represents an interesting and suitable alternative to models with complex structures that involve the general case of several conditionally independent diagnostic tests, covariates, and strata with different disease prevalences. The technique of stratifying the population according to different disease prevalence rates does not add further marked complexity to the modeling, but it makes the model more flexible and interpretable. To illustrate the general model proposed, we evaluate the performance of six diagnostic screening tests for Chagas disease considering some epidemiological variables. Serology at the time of donation (negative, positive, inconclusive) was considered as a factor of stratification in the model. The general model with stratification of the population performed better in comparison with its concurrents without stratification. The group formed by the testing laboratory Biomanguinhos FIOCRUZ-kit (c-ELISA and rec-ELISA) is the best option in the confirmation process by presenting false-negative rate of 0.0002% from the serial scheme. We are 100% sure that the donor is healthy when these two tests have negative results and he is chagasic when they have positive results.

Computation of (3)J(HH) coupling constants with a combination of density functional theory and semiempirical calculations. Application to complex molecules

This work evaluates the efficiency of economic levels of theory for the prediction of (3)J(HH) spin-spin coupling constants, to be used when robust electronic structure methods are prohibitive. To that purpose, DFT methods like mPW1PW91. B3LYP and PBEPBE were used to obtain coupling constants for a test set whose coupling constants are well known. Satisfactory results were obtained in most of cases, with the mPW1PW91/6-31G(d,p)//B3LYP/6-31G(d,p) leading the set. In a second step. B3LYP was replaced by the semiempirical methods PM6 and RM1 in the geometry optimizations. Coupling constants calculated with these latter structures were at least as good as the ones obtained by pure DFT methods. This is a promising result, because some of the main objectives of computational chemistry - low computational cost and time, allied to high performance and precision - were attained together. (C) 2012 Elsevier B.V. All rights reserved.

AN EFFICIENT HPLC-UV METHOD FOR THE QUANTITATIVE DETERMINATION OF CEFADROXIL IN HUMAN PLASMA AND ITS APPLICATION IN PHARMACOKINETIC STUDIES

Cefadroxil is a semi-synthetic first-generation oral cephalosporin used in the treatment of mild to moderate infections of the respiratory and urinary tracts, skin and soft tissue infections. In this work a simple, rapid, economic and sensitive HPLC-UV method is described for the quantitative determination of cefadroxil in human plasma samples using lamivudine as internal standard. Sample pre-treatment was accomplished through protein precipitation with acetonitrile and chromatographic separation was performed with a mobile phase consisting of a mixture of sodium dihydrogen phosphate monohydrate solution, methanol and acetonitrile in the ratio of 90:8:2 (v/v/v) at a flow rate of 1.0mL/min. The proposed method is linear between 0.4 to 40.0 mu g/mL and its average recovery is 102.21% for cefadroxil and 97.94% for lamivudine. The method is simple, sensitive, reproducible, less time consuming for determination of cefadroxil in human plasma. The method can therefore be recommended for pharmacokinetics studies, including bioavailability and bioequivalence studies.

Effect of topical clay application on the synthesis of collagen in skin: an experimental study

Background. Clay is often used in cosmetic treatments, although little is known about its action. Aim. To evaluate the effect of topical clay application on the histoarchitecture of collagen fibres in rat skin. Methods. Animals received a daily application of clay and retinoic acid (RA) 0.025% to the dorsal skin over 7 and 14 days, under vaporization at 37 degrees C for 40 min. Control skin was not vaporized. Samples from each region were excised, and stained with picrosirius red for collagen evaluation. Results. Seven days after clay treatment, an increase in the number of collagen fibres was observed in treated skin compared with control skin (51.74 +/- 1.28 vs. 43.39 +/- 1.79%, respectively, P < 0.01), whereas RA did not alter the collagen level (45.66 +/- 1.10%). Clay application over 14 days did not induce a further increase in skin collagen, whereas treatment with RA did (58.07 +/- 1.59%; P = 0.001 vs. control). Conclusion. Clay application promotes an increase in the number of collagen fibres, which may account for its beneficial effects.

Software Application That Evaluates the Diagnostic Accuracy of Nursing Students

PURPOSE: Apply the educational software Fuzzy Kitten with undergraduate Brazilian nursing students. METHODS: This software, based on fuzzy logic, generates performance scores that evaluate the ability to identify defining characteristics/risk factors present in clinical cases, relate them with nursing diagnoses, and determine the diagnoses freely or using a decision support model. FINDINGS: There were differences in student performance compared to the year of the course. The time to perform the activity did not present a significant relation to the performance. The students' scores in the diagnoses indicated by the model was superior (p = .01). CONCLUSIONS: The software was able to evaluate the diagnostic accuracy of students. IMPLICATIONS: The software enables an objective evaluation of diagnostic accuracy.

Antimicrobial Properties and Cytotoxicity of an Antimicrobial Monomer for Application in Prosthodontics

Purpose: This study aimed to investigate the antimicrobial properties and cytotoxicity of the monomer methacryloyloxyundecylpyridinium bromide (MUPB), an antiseptic agent capable of copolymerizing with denture base acrylic resins. Materials and Methods: The antimicrobial activity of MUPB was tested against the species Candida albicans, Candida dubliniensis, Candida glabrata, Lactobacillus casei, Staphylococcus aureus, and Streptococcus mutans. The minimum inhibitory and fungicidal/bactericidal concentrations (MIC, MFC/MBC) of MUPB were determined by serial dilutions in comparison with cetylpyridinium chloride (CPC). The cytotoxic effects of MUPB at concentrations ranging from 0.01 to 1 g/L were assessed by MTT test on L929 cells and compared with methyl methacrylate (MMA). The antimicrobial activity of copolymerized MUPB was tested by means of acrylic resin specimens containing three concentrations of the monomer (0, 0.3, 0.6% w/w). Activity was quantified by means of a disc diffusion test and a quantification of adhered planktonic cells. Statistical analysis employed the Mann-Whitney test for MIC and MFC/MBC, and ANOVA for the microbial adherence test (a= 0.05). Results: MUBP presented lower MIC values when compared with CPC, although differences were significant for C. dubliniensis and S. mutans only (p= 0.046 and 0.043, respectively). MFC/MBC values were similar for all species except C. albicans; in that case, MUPB presented significantly higher values (p= 0.046). MUPB presented higher cytotoxicity than MMA for all tested concentrations (p < 0.001) except at 0.01 g/L. Irrespective of the concentration incorporated and species, there was no inhibition halo around the specimens. The incorporation of MUPB influenced the adhesion of C. albicans only (p= 0.003), with lower CFU counts for the 0.6% group. Conclusions: It was concluded that non-polymerized MUPB has an antimicrobial capacity close to that of CPC and high cytotoxicity when compared with MMA. The antimicrobial activity of MUPB after incorporation within a denture base acrylic resin did not depend on its elution, but was shown to be restricted to C. albicans.

Application of magnetically induced hyperthermia in the model protozoan Crithidia fasciculata as a potential therapy against parasitic infections

Background: Magnetic hyperthermia is currently a clinical therapy approved in the European Union for treatment of tumor cells, and uses magnetic nanoparticles (MNPs) under time-varying magnetic fields (TVMFs). The same basic principle seems promising against trypanosomatids causing Chagas disease and sleeping sickness, given that the therapeutic drugs available have severe side effects and that there are drug-resistant strains. However, no applications of this strategy against protozoan-induced diseases have been reported so far. In the present study, Crithidia fasciculata, a widely used model for therapeutic strategies against pathogenic trypanosomatids, was targeted with Fe3O4 MNPs in order to provoke cell death remotely using TVMFs. Methods: Iron oxide MNPs with average diameters of approximately 30 nm were synthesized by precipitation of FeSO4 in basic medium. The MNPs were added to C. fasciculata choanomastigotes in the exponential phase and incubated overnight, removing excess MNPs using a DEAE-cellulose resin column. The amount of MNPs uploaded per cell was determined by magnetic measurement. The cells bearing MNPs were submitted to TVMFs using a homemade AC field applicator (f = 249 kHz, H = 13 kA/m), and the temperature variation during the experiments was measured. Scanning electron microscopy was used to assess morphological changes after the TVMF experiments. Cell viability was analyzed using an MTT colorimetric assay and flow cytometry. Results: MNPs were incorporated into the cells, with no noticeable cytotoxicity. When a TVMF was applied to cells bearing MNPs, massive cell death was induced via a nonapoptotic mechanism. No effects were observed by applying TVMF to control cells not loaded with MNPs. No macroscopic rise in temperature was observed in the extracellular medium during the experiments. Conclusion: As a proof of principle, these data indicate that intracellular hyperthermia is a suitable technology to induce death of protozoan parasites bearing MNPs. These findings expand the possibilities for new therapeutic strategies combating parasitic infection.

A Bayesian Approach for Decision Making on the Identification of Genes with Different Expression Levels: An Application to Escherichia coli Bacterium Data

A common interest in gene expression data analysis is to identify from a large pool of candidate genes the genes that present significant changes in expression levels between a treatment and a control biological condition. Usually, it is done using a statistic value and a cutoff value that are used to separate the genes differentially and nondifferentially expressed. In this paper, we propose a Bayesian approach to identify genes differentially expressed calculating sequentially credibility intervals from predictive densities which are constructed using the sampled mean treatment effect from all genes in study excluding the treatment effect of genes previously identified with statistical evidence for difference. We compare our Bayesian approach with the standard ones based on the use of the t-test and modified t-tests via a simulation study, using small sample sizes which are common in gene expression data analysis. Results obtained report evidence that the proposed approach performs better than standard ones, especially for cases with mean differences and increases in treatment variance in relation to control variance. We also apply the methodologies to a well-known publicly available data set on Escherichia coli bacterium.

Chiral HPLC analysis of donepezil, 5-O-desmethyl donepezil and 6-O-desmethyl donepezil in culture medium: application to fungal biotransformation studies

An high performance liquid chromatography (HPLC) method for the enantioselective determination of donepezil (DPZ), 5-O-desmethyl donepezil (5-ODD), and 6-O-desmethyl donepezil (6-ODD) in Czapek culture medium to be applied to biotransformation studies with fungi is described for the first time. The HPLC analysis was carried out using a Chiralpak AD-H column with hexane/ethanol/methanol (75:20:5, v/v/v) plus 0.3 % triethylamine as mobile phase and UV detection at 270 nm. Sample preparation was carried out by liquid-liquid extraction using ethyl acetate as extractor solvent. The method was linear over the concentration range of 100-10,000 ng mL(-1) for each enantiomer of DPZ (r a parts per thousand yenaEuro parts per thousand 0.9985) and of 100-5,000 ng mL(-1) for each enantiomer of 5-ODD (r a parts per thousand yenaEuro parts per thousand 0.9977) and 6-ODD (r a parts per thousand yenaEuro parts per thousand 0.9951). Within-day and between-day precision and accuracy evaluated by relative standard deviations and relative errors, respectively, were lower than 15 % for all analytes. The validated method was used to assess DPZ biotransformation by the fungi Beauveria bassiana American Type Culture Collection (ATCC) 7159 and Cunninghamella elegans ATCC 10028B. Using the fungus B. bassiana ATCC 7159, a predominant formation of (R)-5-ODD was observed while for the fungus C. elegans ATCC 10028B, DPZ was biotransformed to (R)-6-ODD with an enantiomeric excess of 100 %.

On the impact of disproportional samples in credit scoring models: An application to a Brazilian bank data

Statistical methods have been widely employed to assess the capabilities of credit scoring classification models in order to reduce the risk of wrong decisions when granting credit facilities to clients. The predictive quality of a classification model can be evaluated based on measures such as sensitivity, specificity, predictive values, accuracy, correlation coefficients and information theoretical measures, such as relative entropy and mutual information. In this paper we analyze the performance of a naive logistic regression model (Hosmer & Lemeshow, 1989) and a logistic regression with state-dependent sample selection model (Cramer, 2004) applied to simulated data. Also, as a case study, the methodology is illustrated on a data set extracted from a Brazilian bank portfolio. Our simulation results so far revealed that there is no statistically significant difference in terms of predictive capacity between the naive logistic regression models and the logistic regression with state-dependent sample selection models. However, there is strong difference between the distributions of the estimated default probabilities from these two statistical modeling techniques, with the naive logistic regression models always underestimating such probabilities, particularly in the presence of balanced samples. (C) 2012 Elsevier Ltd. All rights reserved.

Application of MALDI-MS analysis of Rainforest chemodiversity: a keystone for biodiversity conservation and sustainable use

FAPESP/BIOTA

A Bayesian destructive weighted Poisson cure rate model and an application to a cutaneous melanoma data

In this article, we propose a new Bayesian flexible cure rate survival model, which generalises the stochastic model of Klebanov et al. [Klebanov LB, Rachev ST and Yakovlev AY. A stochastic-model of radiation carcinogenesis - latent time distributions and their properties. Math Biosci 1993; 113: 51-75], and has much in common with the destructive model formulated by Rodrigues et al. [Rodrigues J, de Castro M, Balakrishnan N and Cancho VG. Destructive weighted Poisson cure rate models. Technical Report, Universidade Federal de Sao Carlos, Sao Carlos-SP. Brazil, 2009 (accepted in Lifetime Data Analysis)]. In our approach, the accumulated number of lesions or altered cells follows a compound weighted Poisson distribution. This model is more flexible than the promotion time cure model in terms of dispersion. Moreover, it possesses an interesting and realistic interpretation of the biological mechanism of the occurrence of the event of interest as it includes a destructive process of tumour cells after an initial treatment or the capacity of an individual exposed to irradiation to repair altered cells that results in cancer induction. In other words, what is recorded is only the damaged portion of the original number of altered cells not eliminated by the treatment or repaired by the repair system of an individual. Markov Chain Monte Carlo (MCMC) methods are then used to develop Bayesian inference for the proposed model. Also, some discussions on the model selection and an illustration with a cutaneous melanoma data set analysed by Rodrigues et al. [Rodrigues J, de Castro M, Balakrishnan N and Cancho VG. Destructive weighted Poisson cure rate models. Technical Report, Universidade Federal de Sao Carlos, Sao Carlos-SP. Brazil, 2009 (accepted in Lifetime Data Analysis)] are presented.

Different approaches for dealing with rare variants in family-based genetic studies: application of a Genetic Analysis Workshop 17 problem

Rare variants are becoming the new candidates in the search for genetic variants that predispose individuals to a phenotype of interest. Their low prevalence in a population requires the development of dedicated detection and analytical methods. A family-based approach could greatly enhance their detection and interpretation because rare variants are nearly family specific. In this report, we test several distinct approaches for analyzing the information provided by rare and common variants and how they can be effectively used to pinpoint putative candidate genes for follow-up studies. The analyses were performed on the mini-exome data set provided by Genetic Analysis Workshop 17. Eight approaches were tested, four using the trait’s heritability estimates and four using QTDT models. These methods had their sensitivity, specificity, and positive and negative predictive values compared in light of the simulation parameters. Our results highlight important limitations of current methods to deal with rare and common variants, all methods presented a reduced specificity and, consequently, prone to false positive associations. Methods analyzing common variants information showed an enhanced sensibility when compared to rare variants methods. Furthermore, our limited knowledge of the use of biological databases for gene annotations, possibly for use as covariates in regression models, imposes a barrier to further research.