Cytotoxicity of dimethyl sulfoxide (DMSO) in direct contact with odontoblast-like cells

To evaluate the cytotoxicity of dimethyl sulfoxide (DMSO) on the repair-related activity of cultured odontoblast-like MDPC-23 cells. Methods Solutions with different concentrations of DMSO (0.05, 0.1, 0.3, 0.5 and 1.0 mM), diluted in culture medium (DMEM), were placed in contact with MDPC-23 cells (5 × 104 cells/cm2) for 24 h. Eight replicates (n = 8) were prepared for each solutions for the following methods of analysis: violet crystal dye for cell adhesion (CA), quantification of total protein (TP), alizarin red for mineralization nodules formation (MN) and cell death by necrosis (flow cytometry); while twelve replicates (n = 12) were prepared for viable cell number (Trypan Blue) and cell viability (MTT assay). Data were analyzed by ANOVA and Tukey or Kruskal–Wallis and Mann–Whitney's tests (p < 0.05). Results Cell viability, adhesion and percentage of cell death by necrosis were not affected by DMSO at any concentration, with no statistical significant difference among the groups. A significant reduction in total protein production was observed for 0.5 and 1.0 mM of DMSO compared to the control while increased mineralized nodules formation was seen only for 1.0 mM DMSO. Significance: DMSO caused no or minor cytotoxic effects on the pulp tissue repair-related activity of odontoblast-like cells.

Comparative study on direct and indirect bracket bonding techniques regarding time length and bracket detachment

OBJECTIVE: The aim of this study was to assess the time spent for direct (DBB - direct bracket bonding) and indirect (IBB - indirect bracket bonding) bracket bonding techniques. The time length of laboratorial (IBB) and clinical steps (DBB and IBB) as well as the prevalence of loose bracket after a 24-week follow-up were evaluated. METHODS: Seventeen patients (7 men and 10 women) with a mean age of 21 years, requiring orthodontic treatment were selected for this study. A total of 304 brackets were used (151 DBB and 153 IBB). The same bracket type and bonding material were used in both groups. Data were submitted to statistical analysis by Wilcoxon non-parametric test at 5% level of significance. RESULTS: Considering the total time length, the IBB technique was more time-consuming than the DBB (p < 0.001). However, considering only the clinical phase, the IBB took less time than the DBB (p < 0.001). There was no significant difference (p = 0.910) for the time spent during laboratorial positioning of the brackets and clinical session for IBB in comparison to the clinical procedure for DBB. Additionally, no difference was found as for the prevalence of loose bracket between both groups. CONCLUSION: the IBB can be suggested as a valid clinical procedure since the clinical session was faster and the total time spent for laboratorial positioning of the brackets and clinical procedure was similar to that of DBB. In addition, both approaches resulted in similar frequency of loose bracket.

Comparative evaluation of several methods for Canine Visceral Leishmaniasis diagnosis

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

HAWAIIAN SUGAR CANE RAT CONTROL METHODS AND PROBLEMS

The problem of rats in our Hawaiian sugar cane fields has been with us for a long time. Early records tell of heavy damage at various times on all the islands where sugar cane is grown. Many methods were tried to control these rats. Trapping was once used as a control measure, a bounty was used for a time, gangs of dogs were trained to catch the rats as the cane was harvested. Many kinds of baits and poisons were used. All of these methods were of some value as long as labor was cheap. Our present day problem started when the labor costs started up and the sugar industry shifted to long cropping. Until World War II cane was an annual crop. After the war it was shifted to a two year crop, three years in some places. Depending on variety, location, and soil we raise 90 to 130 tons of sugar cane per acre, which produces 7 to 15 tons of sugar per acre for a two year crop. This sugar brings about $135 dollars per ton. This tonnage of cane is a thick tangle of vegetation. The cane grows erect for almost a year, as it continues to grow it bends over at the base. This allows the stalk to rest on the ground or on other stalks of cane as it continues to grow. These stalks form a tangled mat of stalks and dead leaves that may be two feet thick at the time of harvest. At the same time the leafy growing portion of the stalk will be sticking up out of the mat of cane ten feet in the air. Some of these individual stalks may be 30 feet long and still growing at the time of harvest. All this makes it very hard to get through a cane field as it is one long, prolonged stumble over and through the cane. It is in this mat of cane that our three species of rats live. Two species are familiar to most people in the pest control field. Rattus norvegicus and Rattus rattus. In the latter species we include both the black rat and the alexandrine rats, their habits seem to be the same in Hawaii. Our third rat is the Polynesian rat, Rattus exlans, locally called the Hawaiian rat. This is a small rat, the average length head to tip of tail is nine inches and the average body weight is 65 grams. It has dark brownish fur like the alexandrine rats, and a grey belly. It is found in Indonesia, on most of the islands of Oceania and in New Zealand. All three rats live in our cane fields and the brushy and forested portions of our islands. The norway and alexandrine rats are found in and around the villages and farms, the Polynesian rat is only found in the fields and waste areas. The actual amount of damage done by rats is small, but destruction they cause is large. The rats gnaw through the rind of the cane stalk and eat the soft juicy and sweet tissues inside. They will hollow out one to several nodes per stalk attacked. The effect to the cane stalk is like ringing a tree. After this attack the stalk above the chewed portion usually dies, and sometimes the lower portion too. If the rat does not eat through the stalk the cane stalk could go on living and producing sugar at a reduced rate. Generally an injured stalk does not last long. Disease and souring organisms get in the injury and kill the stalk. And if this isn't enough, some insects are attracted to the injured stalk and will sometimes bore in and kill it. An injured stalk of cane doesn't have much of a chance. A rat may only gnaw out six inches of a 30 foot stalk and the whole stalk will die. If the rat only destroyed what he ate we could ignore them but they cause the death of too much cane. This dead, dying, and souring cane cause several direct and indirect tosses. First we lose the sugar that the cane would have produced. We harvest all of our cane mechanically so we haul the dead and souring cane to the mill where we have to grind it with our good cane and the bad cane reduces the purity of the sugar juices we squeeze from the cane. Rats reduce our income and run up our overhead.

Systematic Evaluation of Extraction Methods for Multiplatform-Based Metabotyping: Application to the Fasciola hepatica Metabolome

Combining data from multiple analytical platforms is essential for comprehensive study of the molecular phenotype (metabotype) of a given biological sample. The metabolite profiles generated are intrinsically dependent on the analytical platforms, each requiring optimization of instrumental parameters, separation conditions, and sample extraction to deliver maximal biological information. An in-depth evaluation of extraction protocols for characterizing the metabolome of the hepatobiliary fluke Fasciola hepatica, using ultra performance liquid chromatography and capillary electrophoresis coupled with mass spectroscopy is presented. The spectrometric methods were characterized by performance, and metrics of merit were established, including precision, mass accuracy, selectivity, sensitivity, and platform stability. Although a core group of molecules was common to all methods, each platform contributed a unique set, whereby 142 metabolites out of 14,724 features were identified. A mixture design revealed that the chloroform:methanol:water proportion of 15:59:26 was globally the best composition for metabolite extraction across UPLC-MS and CE-MS platforms accommodating different columns and ionization modes. Despite the general assumption of the necessity of platform-adapted protocols for achieving effective metabotype characterization, we show that an appropriately designed single extraction procedure is able to fit the requirements of all technologies. This may constitute a paradigm shift in developing efficient protocols for high-throughput metabolite profiling with more-general analytical applicability.

An optimization study of PtSn/C catalysts applied to direct ethanol fuel cell: Effect of the preparation method on the electrocatalytic activity of the catalysts

The aim of this work was to perform a systematic study of the parameters that can influence the composition, morphology, and catalytic activity of PtSn/C nanoparticles and compare two different methods of nanocatalyst preparation, namely microwave-assisted heating (MW) and thermal decomposition of polymeric precursors (DPP). An investigation of the effects of the reducing and stabilizing agents on the catalytic activity and morphology of Pt75Sn25/C catalysts prepared by microwave-assisted heating was undertaken for optimization purposes. The effect of short-chain alcohols such as ethanol, ethylene glycol, and propylene glycol as reducing agents was evaluated, and the use of sodium acetate and citric acid as stabilizing agents for the MW procedure was examined. Catalysts obtained from propylene glycol displayed higher catalytic activity compared with catalysts prepared in ethylene glycol. Introduction of sodium acetate enhanced the catalytic activity, but this beneficial effect was observed until a critical acetate concentration was reached. Optimization of the MW synthesis allowed for the preparation of highly dispersed catalysts with average sizes lying between 2.0 and 5.0 nm. Comparison of the best catalyst prepared by MW with a catalyst of similar composition prepared by the polymeric precursors method showed that the catalytic activity of the material can be improved when a proper condition for catalyst preparation is achieved. (C) 2012 Elsevier B.V. All rights reserved.

Estimation methods of non-additive effects for characteristics of weight and scrotal circumference in crossbred beef cattle

The objective of this study was to investigate, in a population of crossbred cattle, the obtainment of the non-additive genetic effects for the characteristics weight at 205 and 390 days and scrotal circumference, and to evaluate the consideration of these effects in the prediction of breeding values of sires using different estimation methodologies. In method 1, the data were pre-adjusted for the non-additive effects obtained by least squares means method in a model that considered the direct additive, maternal and non-additive fixed genetic effects, the direct and total maternal heterozygosities, and epistasis. In method 2, the non-additive effects were considered covariates in genetic model. Genetic values for adjusted and non-adjusted data were predicted considering additive direct and maternal effects, and for weight at 205 days, also the permanent environmental effect, as random effects in the model. The breeding values of the categories of sires considered for the weight characteristic at 205 days were organized in files, in order to verify alterations in the magnitude of the predictions and ranking of animals in the two methods of correction data for the non-additives effects. The non-additive effects were not similar in magnitude and direction in the two estimation methods used, nor for the characteristics evaluated. Pearson and Spearman correlations between breeding values were higher than 0.94, and the use of different methods does not imply changes in the selection of animals.

Direct Determination of Sugar Cane Quality Parameters by X-ray Spectrometry and Multivariate Analysis

Current methods for quality control of sugar cane are performed in extracted juice using several methodologies, often requiring appreciable time and chemicals (eventually toxic), making the methods not green and expensive. The present study proposes the use of X-ray spectrometry together with chemometric methods as an innovative and alternative technique for determining sugar cane quality parameters, specifically sucrose concentration, POL, and fiber content. Measurements in stem, leaf, and juice were performed, and those applied directly in stem provided the best results. Prediction models for sugar cane stem determinations with a single 60 s irradiation using portable X-ray fluorescence equipment allows estimating the % sucrose, % fiber, and POL simultaneously. Average relative deviations in the prediction step of around 8% are acceptable if considering that field measurements were done. These results may indicate the best period to cut a particular crop as well as for evaluating the quality of sugar cane for the sugar and alcohol industries.

Evaluation of reference-based two-color methods for measurement of gene expression ratios using spotted cDNA microarrays

Abstract Background Spotted cDNA microarrays generally employ co-hybridization of fluorescently-labeled RNA targets to produce gene expression ratios for subsequent analysis. Direct comparison of two RNA samples in the same microarray provides the highest level of accuracy; however, due to the number of combinatorial pair-wise comparisons, the direct method is impractical for studies including large number of individual samples (e.g., tumor classification studies). For such studies, indirect comparisons using a common reference standard have been the preferred method. Here we evaluated the precision and accuracy of reconstructed ratios from three indirect methods relative to ratios obtained from direct hybridizations, herein considered as the gold-standard. Results We performed hybridizations using a fixed amount of Cy3-labeled reference oligonucleotide (RefOligo) against distinct Cy5-labeled targets from prostate, breast and kidney tumor samples. Reconstructed ratios between all tissue pairs were derived from ratios between each tissue sample and RefOligo. Reconstructed ratios were compared to (i) ratios obtained in parallel from direct pair-wise hybridizations of tissue samples, and to (ii) reconstructed ratios derived from hybridization of each tissue against a reference RNA pool (RefPool). To evaluate the effect of the external references, reconstructed ratios were also calculated directly from intensity values of single-channel (One-Color) measurements derived from tissue sample data collected in the RefOligo experiments. We show that the average coefficient of variation of ratios between intra- and inter-slide replicates derived from RefOligo, RefPool and One-Color were similar and 2 to 4-fold higher than ratios obtained in direct hybridizations. Correlation coefficients calculated for all three tissue comparisons were also similar. In addition, the performance of all indirect methods in terms of their robustness to identify genes deemed as differentially expressed based on direct hybridizations, as well as false-positive and false-negative rates, were found to be comparable. Conclusion RefOligo produces ratios as precise and accurate as ratios reconstructed from a RNA pool, thus representing a reliable alternative in reference-based hybridization experiments. In addition, One-Color measurements alone can reconstruct expression ratios without loss in precision or accuracy. We conclude that both methods are adequate options in large-scale projects where the amount of a common reference RNA pool is usually restrictive.

Comparison of two laboratory-developed PCR methods for the diagnosis of Pulmonary Tuberculosis in Brazilian patients with and without HIV infection

Abstract Background Direct smear examination with Ziehl-Neelsen (ZN) staining for the diagnosis of pulmonary tuberculosis (PTB) is cheap and easy to use, but its low sensitivity is a major drawback, particularly in HIV seropositive patients. As such, new tools for laboratory diagnosis are urgently needed to improve the case detection rate, especially in regions with a high prevalence of TB and HIV. Objective To evaluate the performance of two in house PCR (Polymerase Chain Reaction): PCR dot-blot methodology (PCR dot-blot) and PCR agarose gel electrophoresis (PCR-AG) for the diagnosis of Pulmonary Tuberculosis (PTB) in HIV seropositive and HIV seronegative patients. Methods A prospective study was conducted (from May 2003 to May 2004) in a TB/HIV reference hospital. Sputum specimens from 277 PTB suspects were tested by Acid Fast Bacilli (AFB) smear, Culture and in house PCR assays (PCR dot-blot and PCR-AG) and their performances evaluated. Positive cultures combined with the definition of clinical pulmonary TB were employed as the gold standard. Results The overall prevalence of PTB was 46% (128/277); in HIV+, prevalence was 54.0% (40/74). The sensitivity and specificity of PCR dot-blot were 74% (CI 95%; 66.1%-81.2%) and 85% (CI 95%; 78.8%-90.3%); and of PCR-AG were 43% (CI 95%; 34.5%-51.6%) and 76% (CI 95%; 69.2%-82.8%), respectively. For HIV seropositive and HIV seronegative samples, sensitivities of PCR dot-blot (72% vs 75%; p = 0.46) and PCR-AG (42% vs 43%; p = 0.54) were similar. Among HIV seronegative patients and PTB suspects, ROC analysis presented the following values for the AFB smear (0.837), Culture (0.926), PCR dot-blot (0.801) and PCR-AG (0.599). In HIV seropositive patients, these area values were (0.713), (0.900), (0.789) and (0.595), respectively. Conclusion Results of this study demonstrate that the in house PCR dot blot may be an improvement for ruling out PTB diagnosis in PTB suspects assisted at hospitals with a high prevalence of TB/HIV.

Self-assembled films from chitosan and poly(vinyl sulfonic acid) on Nafion® for direct methanol fuel cell

Chitosan/poly(vinyl sulfonic acid) (PVS) films have been prepared on Nafion® membranes by the layer-by-layer (LbL) method for use in direct methanol fuel cell (DMFC). Computational methods and Fourier transform infrared (FTIR) spectra suggest that an ionic pair is formed between the sulfonic group of PVS and the protonated amine group of chitosan, thereby promoting the growth of LbL films on the Nafion® membrane as well as partial blocking of methanol. Chronopotentiometry and potential linear scanning experiments have been carried out for investigation of methanol crossover through the Nafion® and chitosan/PVS/Nafion® membranes in a diaphragm diffusion cell. On the basis of electrical impedance measurements, the values of proton resistance of the Nafion® and chitosan/PVS/Nafion® membranes are close due to the small thickness of the LbL film. Thus, it is expected an improved DMFC performance once the additional resistance of the self-assembled film is negligible compared to the result associated with the decrease in the crossover effect.

In vitro study on radiographic gray levels of biomaterials using two digital image methods

PURPOSE: To compare the direct and indirect radiographic methods for assessing the gray levels of biomaterials employing the Digora for Windows and the Adobe Photoshop CS2 systems. METHODS: Specimens of biomaterials were made following manusfacturer's instructions and placed on phosphor storage plates (PSP) and on radiographic film for subsequent gray level assessment using the direct and indirect radiographic method, respectively. The radiographic density of each biomaterial was analyzed using Adobe Photoshop CS2 and Digora for Windows software. RESULTS: The distribution of gray levels found using the direct and indirect methods suggests that higher exposure times are correlated to lower reproducibility rates between groups. CONCLUSION: The indirect method is a feasible alternative to the direct method in assessing the radiographic gray levels of biomaterials, insofar as significant reproducibility was observed between groups for the exposure times of 0.2 to 0.5 seconds.

Variance Reduction in Analytical Chemistry : New Numerical Methods in Chemometrics and Molecular Simulation

This thesis is based on five papers addressing variance reduction in different ways. The papers have in common that they all present new numerical methods. Paper I investigates quantitative structure-retention relationships from an image processing perspective, using an artificial neural network to preprocess three-dimensional structural descriptions of the studied steroid molecules. Paper II presents a new method for computing free energies. Free energy is the quantity that determines chemical equilibria and partition coefficients. The proposed method may be used for estimating, e.g., chromatographic retention without performing experiments. Two papers (III and IV) deal with correcting deviations from bilinearity by so-called peak alignment. Bilinearity is a theoretical assumption about the distribution of instrumental data that is often violated by measured data. Deviations from bilinearity lead to increased variance, both in the data and in inferences from the data, unless invariance to the deviations is built into the model, e.g., by the use of the method proposed in paper III and extended in paper IV. Paper V addresses a generic problem in classification; namely, how to measure the goodness of different data representations, so that the best classifier may be constructed. Variance reduction is one of the pillars on which analytical chemistry rests. This thesis considers two aspects on variance reduction: before and after experiments are performed. Before experimenting, theoretical predictions of experimental outcomes may be used to direct which experiments to perform, and how to perform them (papers I and II). After experiments are performed, the variance of inferences from the measured data are affected by the method of data analysis (papers III-V).

Kernel Methods for Tree Structured Data

Machine learning comprises a series of techniques for automatic extraction of meaningful information from large collections of noisy data. In many real world applications, data is naturally represented in structured form. Since traditional methods in machine learning deal with vectorial information, they require an a priori form of preprocessing. Among all the learning techniques for dealing with structured data, kernel methods are recognized to have a strong theoretical background and to be effective approaches. They do not require an explicit vectorial representation of the data in terms of features, but rely on a measure of similarity between any pair of objects of a domain, the kernel function. Designing fast and good kernel functions is a challenging problem. In the case of tree structured data two issues become relevant: kernel for trees should not be sparse and should be fast to compute. The sparsity problem arises when, given a dataset and a kernel function, most structures of the dataset are completely dissimilar to one another. In those cases the classifier has too few information for making correct predictions on unseen data. In fact, it tends to produce a discriminating function behaving as the nearest neighbour rule. Sparsity is likely to arise for some standard tree kernel functions, such as the subtree and subset tree kernel, when they are applied to datasets with node labels belonging to a large domain. A second drawback of using tree kernels is the time complexity required both in learning and classification phases. Such a complexity can sometimes prevents the kernel application in scenarios involving large amount of data. This thesis proposes three contributions for resolving the above issues of kernel for trees. A first contribution aims at creating kernel functions which adapt to the statistical properties of the dataset, thus reducing its sparsity with respect to traditional tree kernel functions. Specifically, we propose to encode the input trees by an algorithm able to project the data onto a lower dimensional space with the property that similar structures are mapped similarly. By building kernel functions on the lower dimensional representation, we are able to perform inexact matchings between different inputs in the original space. A second contribution is the proposal of a novel kernel function based on the convolution kernel framework. Convolution kernel measures the similarity of two objects in terms of the similarities of their subparts. Most convolution kernels are based on counting the number of shared substructures, partially discarding information about their position in the original structure. The kernel function we propose is, instead, especially focused on this aspect. A third contribution is devoted at reducing the computational burden related to the calculation of a kernel function between a tree and a forest of trees, which is a typical operation in the classification phase and, for some algorithms, also in the learning phase. We propose a general methodology applicable to convolution kernels. Moreover, we show an instantiation of our technique when kernels such as the subtree and subset tree kernels are employed. In those cases, Direct Acyclic Graphs can be used to compactly represent shared substructures in different trees, thus reducing the computational burden and storage requirements.

Machine learning methods for prediction of disulphide bonding states of cysteine residues in proteins

The goal of this thesis work is to develop a computational method based on machine learning techniques for predicting disulfide-bonding states of cysteine residues in proteins, which is a sub-problem of a bigger and yet unsolved problem of protein structure prediction. Improvement in the prediction of disulfide bonding states of cysteine residues will help in putting a constraint in the three dimensional (3D) space of the respective protein structure, and thus will eventually help in the prediction of 3D structure of proteins. Results of this work will have direct implications in site-directed mutational studies of proteins, proteins engineering and the problem of protein folding. We have used a combination of Artificial Neural Network (ANN) and Hidden Markov Model (HMM), the so-called Hidden Neural Network (HNN) as a machine learning technique to develop our prediction method. By using different global and local features of proteins (specifically profiles, parity of cysteine residues, average cysteine conservation, correlated mutation, sub-cellular localization, and signal peptide) as inputs and considering Eukaryotes and Prokaryotes separately we have reached to a remarkable accuracy of 94% on cysteine basis for both Eukaryotic and Prokaryotic datasets, and an accuracy of 90% and 93% on protein basis for Eukaryotic dataset and Prokaryotic dataset respectively. These accuracies are best so far ever reached by any existing prediction methods, and thus our prediction method has outperformed all the previously developed approaches and therefore is more reliable. Most interesting part of this thesis work is the differences in the prediction performances of Eukaryotes and Prokaryotes at the basic level of input coding when ‘profile’ information was given as input to our prediction method. And one of the reasons for this we discover is the difference in the amino acid composition of the local environment of bonded and free cysteine residues in Eukaryotes and Prokaryotes. Eukaryotic bonded cysteine examples have a ‘symmetric-cysteine-rich’ environment, where as Prokaryotic bonded examples lack it.