Analysis of four gutta-percha techniques used to fill mesial root canals of mandibular molars

P>Aim To compare the percentage of gutta-percha, sealer and voids and the influence of isthmuses in mesial root canals of mandibular molars filled with different techniques. Methodology Canals in 60 mesial roots of mandibular first molars were prepared with ProTaper instruments to size F2 (size 25, 0.08 taper) and filled using a single-cone, lateral compaction, System B or Thermafil techniques. An epoxy resin sealer was labelled with Rhodamine-B dye to allow analysis under a confocal microscope. The percentage of gutta-percha, sealer and area of voids was calculated at 2, 4 and 6 mm from the apex, using Image Tool 3.0 software. Statistical analysis was performed using nonparametric Kruskal-Wallis and Dunn tests (P < 0.05). The influence of isthmuses on the presence or absence of voids was evaluated using the Fisher test. Results At the 2 mm level, the percentage of gutta-percha, sealer and voids was similar amongst the System B, lateral compaction and single-cone techniques. The single-cone technique revealed significantly less gutta-percha, more sealer and voids in comparison with the Thermafil technique at the 2 and 4 mm level (P < 0.05). The analysis of all sections (2, 4 and 6 mm) revealed that more gutta-percha and less sealer and voids were found in root canals filled with Thermafil and System B techniques (P < 0.05). The Fisher test revealed that the presence of isthmuses increased the occurence of voids in the lateral compaction group only (P < 0.05). Conclusion Gutta-percha, sealer filled area and voids were dependent on the canal-filling technique. The presence of isthmuses may influence the quality of root filling.

Outcome Analysis of Immediate and Delayed Conservative Breast Surgery Reconstruction With Mastopexy and Reduction Mammaplasty Techniques

Background: Bilateral mammaplasty or mastopexy is frequently used for oncoplastic objectives. However, little information has been available regarding outcome following immediate and delayed reconstruction. Method: Patients were divided into Group I (immediate reconstruction) and Group II (delayed reconstruction). Retrospective review was performed to compare complications, length of hospital stay, revision surgeries, and satisfaction. The associations between the complications with potential risk factors (timing, age, body mass index, smoking, and comorbid medical conditions) were analyzed. Results: There were a total of 144 patients with a mean follow-up of 47 months. Of the 106 patients in Group I, complications occurred in 24 (22.6%), skin necrosis was observed in 7.5%, fat necrosis in 5.6%, and 6.6% patients developed local recurrence. Mean period of hospitalization was 1.89 days. Of the 38 patients of the Group II, complications occurred in 12 (31.5%), skin necrosis was observed in 7 (18.4%), fat necrosis in 4 (10.5%), and 5.2% patients developed local recurrence. Mean period of hospitalization was 1.35 days. Increased length of hospital stay greater than 1 day (P < 0.001) and the number of revision surgeries (P = 0.043) were associated with the timing of the reconstruction. In univariate analysis, no difference between groups was found with respect to complication incidence (P = 0.275); however, after adjusting for other risk factors, the probability of complications tend to be higher for Group II (OR = 2.65; 95% confidence interval - 1.01-7.00; P = 0.049). Conclusions: On the basis of the results of our study, the probability of complications tends to be higher for delayed reconstructions, and it is demonstrated that obesity and smoking are risk factors for complications. Ultimately, these data may facilitate the provision of individualized risk information for shared medical decision-making.

Bayesian analysis of skew-t multivariate null intercept measurement error model

The multivariate skew-t distribution (J Multivar Anal 79:93-113, 2001; J R Stat Soc, Ser B 65:367-389, 2003; Statistics 37:359-363, 2003) includes the Student t, skew-Cauchy and Cauchy distributions as special cases and the normal and skew-normal ones as limiting cases. In this paper, we explore the use of Markov Chain Monte Carlo (MCMC) methods to develop a Bayesian analysis of repeated measures, pretest/post-test data, under multivariate null intercept measurement error model (J Biopharm Stat 13(4):763-771, 2003) where the random errors and the unobserved value of the covariate (latent variable) follows a Student t and skew-t distribution, respectively. The results and methods are numerically illustrated with an example in the field of dentistry.

Bayesian analysis for a skew extension of the multivariate null intercept measurement error model

Skew-normal distribution is a class of distributions that includes the normal distributions as a special case. In this paper, we explore the use of Markov Chain Monte Carlo (MCMC) methods to develop a Bayesian analysis in a multivariate, null intercept, measurement error model [R. Aoki, H. Bolfarine, J.A. Achcar, and D. Leao Pinto Jr, Bayesian analysis of a multivariate null intercept error-in -variables regression model, J. Biopharm. Stat. 13(4) (2003b), pp. 763-771] where the unobserved value of the covariate (latent variable) follows a skew-normal distribution. The results and methods are applied to a real dental clinical trial presented in [A. Hadgu and G. Koch, Application of generalized estimating equations to a dental randomized clinical trial, J. Biopharm. Stat. 9 (1999), pp. 161-178].

Morphometric analysis of the urethra of castrated female rats treated with tamoxifen

Objectives: The aim of this study was to evaluate the effects of tamoxifen on the weight and thickness of the urethral epithelium of castrated female rats. Methods: Forty castrated adult female Wistar-Hannover rats were randomly divided into two groups: Group I (n = 20) in which the animals received only the vehicle (propylene glycol) and Group 11 (n = 20) in which the rats received tamoxifen 250 mu g/day by gavage. After 30 days of treatment, all animals were sacrificed and the urethra was immediately removed for weighing. Next, the urethra was divided into the proximal and distal segments, which were fixed in 10% formaldehyde and submitted to routine histological techniques for morphometric study. The data were analyzed using the weighted minimum mean-square error method and Student`s t-test for two independent samples (p < 0.05). Results: There was a significant increase in the mean weight of the urethra in the rats of Group 11 compared to the control group, 32.0 +/- 2.0 mg and 22.0 +/- 1.6 mg, respectively (p < 0.001). The mean thickness of the distal urethral epithelium of the animals treated with tamoxifen was significantly greater than that of the control group, 42.8 +/- 2.0 mu m and 36.6 +/- 1.5 mu m, respectively (p < 0.001). There was no statistically significant difference between the two groups with respect to the epithelial thickness of the proximal urethra (p = 0.514). Conclusion: Treating castrated adult rats with 250 mu g/day of tamoxifen for 30 days may increase the weight of the urethra and the thickness of the distal urethral epithelium. (c) 2008 Elsevier Ireland Ltd. All rights reserved.

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.

DIAGNOSTIC TECHNIQUES OF LOCAL INFLUENCE IN SPATIAL ANALYSIS OF SOYBEAN YIELD

Modeling of spatial dependence structure, concerning geoestatistics approach, is an indispensable tool for fixing parameters that define this structure, applied on interpolation of values in places that are not sampled, by kriging techniques. However, the estimation of parameters can be greatly affected by the presence of atypical observations on sampled data. Thus, this trial aimed at using diagnostics techniques of local influence in spatial linear Gaussians models, applied at geoestatistics in order to evaluate sensitivity of maximum likelihood estimators and restrict maximum likelihood to small perturbations in these data. So, studies with simulated and experimental data were performed. Those results, obtained from the study of real data, allowed us to conclude that the presence of atypical values among the sampled data can have a strong influence on thematic maps, changing, therefore, the spatial dependence. The application of diagnostics techniques of local influence should be part of any geoestatistic analysis, ensuring that the information from thematic maps has better quality and can be used with greater security by farmers.

Comparison for three Classification Techniques

In this paper we show the results of a comparison simulation study for three classification techniques: Multinomial Logistic Regression (MLR), No Metric Discriminant Analysis (NDA) and Linear Discriminant Analysis (LDA). The measure used to compare the performance of the three techniques was the Error Classification Rate (ECR). We found that MLR and LDA techniques have similar performance and that they are better than DNA when the population multivariate distribution is Normal or Logit-Normal. For the case of log-normal and Sinh(-1)-normal multivariate distributions we found that MLR had the better performance.

Synthesis of novel O-acylated-D-ribono-1,5-lactones and structural assignment supported by conventional NOESY-NMR and x-ray analysis

A practical method for the structural assignment of 3,4-O-benzylidene-D-ribono-1,5-lactones and analogues using conventional NMR techniques and NOESY measurements in solution is described. 2-O-Acyl-3,4-O-benzylidene-D-ribono-1,5-lactones were prepared in good yields by acylation of Zinner’s lactone with acyl chlorides under mildly basic conditions. Structural determination of 2-O-(4-nitrobenzoyl)-3,4-O-benzylidene-D-ribono-1,5-lactone was achieved by single crystal x-ray diffraction, which supports the results based on spectroscopic data.

Neural networks and statistical analysis for classification of corneal videokeratography maps based on Zernike coefficients: a quantitative comparison

PURPOSE: The main goal of this study was to develop and compare two different techniques for classification of specific types of corneal shapes when Zernike coefficients are used as inputs. A feed-forward artificial Neural Network (NN) and discriminant analysis (DA) techniques were used. METHODS: The inputs both for the NN and DA were the first 15 standard Zernike coefficients for 80 previously classified corneal elevation data files from an Eyesys System 2000 Videokeratograph (VK), installed at the Departamento de Oftalmologia of the Escola Paulista de Medicina, São Paulo. The NN had 5 output neurons which were associated with 5 typical corneal shapes: keratoconus, with-the-rule astigmatism, against-the-rule astigmatism, "regular" or "normal" shape and post-PRK. RESULTS: The NN and DA responses were statistically analyzed in terms of precision ([true positive+true negative]/total number of cases). Mean overall results for all cases for the NN and DA techniques were, respectively, 94% and 84.8%. CONCLUSION: Although we used a relatively small database, results obtained in the present study indicate that Zernike polynomials as descriptors of corneal shape may be a reliable parameter as input data for diagnostic automation of VK maps, using either NN or DA.

Study of mural paintings by Fulvio Pennacchi in São Paulo City by mineralogical techniques

The present research deals with two mural paintings made in 1947 with the fresco technique by Fulvio Pennacchi in the Catholic Chapel of the Hospital das Clínicas (São Paulo City, Brazil), namely the Virgin Annunciation and the Supper at Emmaus. This study regards the materials and painting techniques used by the artist, based on historical research,on in situ observations and laboratory analytical techniques (stereomicroscopy,scanning electron microscopy with an energy dispersive spectrometer, X-ray diffractometry, electron microprobe, images obtained with UV-light), aiming to improve the methods of characterization of objects of our cultural heritage, and to enhance its preservation accordingly. The results lead to the identification of the plaster components and of distinct layers in the frescoes, besides further information on grain size, impurities and textures, composition of pigments, and features of deterioration, such as efflorescences. The degree of degradation of the murals painting was assessed by this way. Our data suggest that a single layer of plaster was used by Pennacchi, as a common mortar with fine- and medium-grained aggregates. Differences in texture were obtained by adding gypsum to the plaster.

Evaluation of follicular lymphoid depletion in the Bursa of Fabricius: an alternative methodology using digital image analysis and artificial neural networks

Fifty Bursa of Fabricius (BF) were examined by conventional optical microscopy and digital images were acquired and processed using Matlab® 6.5 software. The Artificial Neuronal Network (ANN) was generated using Neuroshell® Classifier software and the optical and digital data were compared. The ANN was able to make a comparable classification of digital and optical scores. The use of ANN was able to classify correctly the majority of the follicles, reaching sensibility and specificity of 89% and 96%, respectively. When the follicles were scored and grouped in a binary fashion the sensibility increased to 90% and obtained the maximum value for the specificity of 92%. These results demonstrate that the use of digital image analysis and ANN is a useful tool for the pathological classification of the BF lymphoid depletion. In addition it provides objective results that allow measuring the dimension of the error in the diagnosis and classification therefore making comparison between databases feasible.

Time-frequency and time-scale analysis of Barkhausen noise signals

Carrying out information about the microstructure and stress behaviour of ferromagnetic steels, magnetic Barkhausen noise (MBN) has been used as a basis for effective non-destructive testing methods, opening new areas in industrial applications. One of the factors that determines the quality and reliability of the MBN analysis is the way information is extracted from the signal. Commonly, simple scalar parameters are used to characterize the information content, such as amplitude maxima and signal root mean square. This paper presents a new approach based on the time-frequency analysis. The experimental test case relates the use of MBN signals to characterize hardness gradients in a AISI4140 steel. To that purpose different time-frequency (TFR) and time-scale (TSR) representations such as the spectrogram, the Wigner-Ville distribution, the Capongram, the ARgram obtained from an AutoRegressive model, the scalogram, and the Mellingram obtained from a Mellin transform are assessed. It is shown that, due to nonstationary characteristics of the MBN, TFRs can provide a rich and new panorama of these signals. Extraction techniques of some time-frequency parameters are used to allow a diagnostic process. Comparison with results obtained by the classical method highlights the improvement on the diagnosis provided by the method proposed.

Analysis of the tip roundness effects on the micro- and macroindentation response of elastic-plastic materials

In this work, the effects of indenter tip roundness oil the load-depth indentation curves were analyzed using finite element modeling. The tip roundness level was Studied based on the ratio between tip radius and maximum penetration depth (R/h(max)), which varied from 0.02 to 1. The proportional Curvature constant (C), the exponent of depth during loading (alpha), the initial unloading slope (S), the correction factor (beta), the level of piling-up or sinking-in (h(c)/h(max)), and the ratio h(max)/h(f) are shown to be strongly influenced by the ratio R/h(max). The hardness (H) was found to be independent of R/h(max) in the range studied. The Oliver and Pharr method was successful in following the variation of h(c)/h(max) with the ratio R/h(max) through the variation of S with the ratio R/h(max). However, this work confirmed the differences between the hardness values calculated using the Oliver-Pharr method and those obtained directly from finite element calculations; differences which derive from the error in area calculation that Occurs when given combinations of indented material properties are present. The ratio of plastic work to total work (W(p)/W(t)) was found to be independent of the ratio R/h(max), which demonstrates that the methods for the Calculation of mechanical properties based on the *indentation energy are potentially not Susceptible to errors caused by tip roundness.

Analysis of the effects of conical indentation variables on the indentation response of elastic-plastic materials through factorial design of experiment

In this work, the effects of conical indentation variables on the load-depth indentation curves were analyzed using finite element modeling and dimensional analysis. A factorial design 2(6) was used with the aim of quantifying the effects of the mechanical properties of the indented material and of the indenter geometry. Analysis was based on the input variables Y/E, R/h(max), n, theta, E, and h(max). The dimensional variables E and h(max) were used such that each value of dimensionless Y/E was obtained with two different values of E and each value of dimensionless R/h(max) was obtained with two different h(max) values. A set of dimensionless functions was defined to analyze the effect of the input variables: Pi(1) = P(1)/Eh(2), Pi(2) = h(c)/h, Pi(3) = H/Y, Pi(4) = S/Eh(max), Pi(6) = h(max)/h(f) and Pi(7) = W(P)/W(T). These six functions were found to depend only on the dimensionless variables studied (Y/E, R/h(max), n, theta). Another dimension less function, Pi(5) = beta, was not well defined for most of the dimensionless variables and the only variable that provided a significant effect on beta was theta. However, beta showed a strong dependence on the fraction of the data selected to fit the unloading curve, which means that beta is especially Susceptible to the error in the Calculation of the initial unloading slope.