In vitro analysis of thermocompaction time and gutta-percha type on quality of main canal and lateral canals filling

The aim of this study was to evaluate the quality of filling in main and lateral root canals performed with the McSpadden technique, regarding the time spent on the procedure and the type of gutta-percha employed. Fifty simulated root canals, made with six lateral canals placed two apiece in the cervical, middle and apical thirds of the root, were divided into 5 groups. Group A: McSpadden technique with conventional gutta-percha, performed with sufficient time for canal filling; Group B: McSpadden technique with conventional gutta-percha, performed in twice the mean time used in Group A; Group C: McSpadden technique with TP gutta-percha, performed with sufficient time for canal filling; Group D: McSpadden technique with TP gutta-percha, performed in twice the mean time used in Group C; Group E: lateral condensation technique. Images of the filled root canals were taken using a stereomicroscope and analyzed using the Leica QWIN Pro software for filling material flow, gutta-percha filling extension and sealer flow. Data were analyzed by analysis of variance (ANOVA) and Tukey test (p < 0.05). The best values of penetration in lateral canals in the middle third occurred in the groups where TP gutta-percha was used. However, in the apical third, group B showed the best values. Although a longer time of compactor use allows greater penetration of the filling material into the lateral canals, the presence of voids resulted in bad quality radiographic images, suggesting porosity. The best quality of filling material was observed in Group A (McSpadden technique with conventional Gutta-Percha, performed with sufficient time for root canal filling).

Sample size and statistical power in the hierarchical analysis of variance: applications in morphometry of the nervous system.

Analysis of variance is commonly used in morphometry in order to ascertain differences in parameters between several populations. Failure to detect significant differences between populations (type II error) may be due to suboptimal sampling and lead to erroneous conclusions; the concept of statistical power allows one to avoid such failures by means of an adequate sampling. Several examples are given in the morphometry of the nervous system, showing the use of the power of a hierarchical analysis of variance test for the choice of appropriate sample and subsample sizes. In the first case chosen, neuronal densities in the human visual cortex, we find the number of observations to be of little effect. For dendritic spine densities in the visual cortex of mice and humans, the effect is somewhat larger. A substantial effect is shown in our last example, dendritic segmental lengths in monkey lateral geniculate nucleus. It is in the nature of the hierarchical model that sample size is always more important than subsample size. The relative weight to be attributed to subsample size thus depends on the relative magnitude of the between observations variance compared to the between individuals variance.

Estimating the spatial scales of regionalized variables by nested sampling, hierarchical analysis of variance and residual maximum likelihood

The variogram is essential for local estimation and mapping of any variable by kriging. The variogram itself must usually be estimated from sample data. The sampling density is a compromise between precision and cost, but it must be sufficiently dense to encompass the principal spatial sources of variance. A nested, multi-stage, sampling with separating distances increasing in geometric progression from stage to stage will do that. The data may then be analyzed by a hierarchical analysis of variance to estimate the components of variance for every stage, and hence lag. By accumulating the components starting from the shortest lag one obtains a rough variogram for modest effort. For balanced designs the analysis of variance is optimal; for unbalanced ones, however, these estimators are not necessarily the best, and the analysis by residual maximum likelihood (REML) will usually be preferable. The paper summarizes the underlying theory and illustrates its application with data from three surveys, one in which the design had four stages and was balanced and two implemented with unbalanced designs to economize when there were more stages. A Fortran program is available for the analysis of variance, and code for the REML analysis is listed in the paper. (c) 2005 Elsevier Ltd. All rights reserved.

Estimating the spatial scale of herbicide and soil interactions by nested sampling, hierarchical analysis of variance and residual maximum likelihood

An unbalanced nested sampling design was used to investigate the spatial scale of soil and herbicide interactions at the field scale. A hierarchical analysis of variance based on residual maximum likelihood (REML) was used to analyse the data and provide a first estimate of the variogram. Soil samples were taken at 108 locations at a range of separating distances in a 9 ha field to explore small and medium scale spatial variation. Soil organic matter content, pH, particle size distribution, microbial biomass and the degradation and sorption of the herbicide, isoproturon, were determined for each soil sample. A large proportion of the spatial variation in isoproturon degradation and sorption occurred at sampling intervals less than 60 m, however, the sampling design did not resolve the variation present at scales greater than this. A sampling interval of 20-25 m should ensure that the main spatial structures are identified for isoproturon degradation rate and sorption without too great a loss of information in this field.

Estimating the spatial scales of regionalized variables by nested sampling, hierarchical analysis of variance and residual maximum likelihood

The variogram is essential for local estimation and mapping of any variable by kriging. The variogram itself must usually be estimated from sample data. The sampling density is a compromise between precision and cost, but it must be sufficiently dense to encompass the principal spatial sources of variance. A nested, multi-stage, sampling with separating distances increasing in geometric progression from stage to stage will do that. The data may then be analyzed by a hierarchical analysis of variance to estimate the components of variance for every stage, and hence lag. By accumulating the components starting from the shortest lag one obtains a rough variogram for modest effort. For balanced designs the analysis of variance is optimal; for unbalanced ones, however, these estimators are not necessarily the best, and the analysis by residual maximum likelihood (REML) will usually be preferable. The paper summarizes the underlying theory and illustrates its application with data from three surveys, one in which the design had four stages and was balanced and two implemented with unbalanced designs to economize when there were more stages. A Fortran program is available for the analysis of variance, and code for the REML analysis is listed in the paper. (c) 2005 Elsevier Ltd. All rights reserved.

Analysis of depth of the microporosity in a nickel-chromium system alloy: effects of electrolytic, chemical and sandblasting etching

The present study was designed to analyse the average depth of the microporosity of a nickel-chromium (Ni-Cr) system alloy (Verabond II). The metal surface was subject to one of the following surface treatment: (i) Electrolytic etching in nitric acid 0.5 N at a current density of 250 mA cm(-2) ; (ii) chemical etching with CG-Etch etchant; and (iii) Sandblasting with alumina particles 50 mum. Half of the samples were polished before the surface treatments. The depth of porosity was measured through photomicrographs (500x) with a profilometer, and the data were statistically analysed using an analysis of variance (anova) followed by Tukey's test. The conclusions were (i) Differents surface treatment of the Ni-Cr system alloy lead to different depths of microporosity; (ii) the greatest depth of porosity was observed in non-polished alloy; (iii) the greatest and identical depth of microporosity was observed following electrolytic etching and chemical etching; (iv) the least and identical depth of microporosity was observed with chemical etching and sandblasting with alumina particles 50 mum, and (v) Chemical etching showed an intermediary depth.

Densitometric analysis of the autogenous demineralized dentin matrix on the dental socket wound healing process in humans

The aim of this study was to evaluate the effects of the autogenous demineralized dentin matrix (ADDM) on the third molar socket wound healing process in humans, using the guided bone regeneration technique and a polytetrafluoroethylene barrier (PTFE). Twenty-seven dental sockets were divided into three groups: dental socket (Control), dental socket with PTFE barrier (PTFE), and dental socket with ADDM slices associated to PTFE banier (ADDM + PTFE). The dental sockets were submitted to radiographic bone densitometry analysis and statistical analysis on the 15th, 30th, 60th and 90th days using analysis of variance (ANOVA) and Tukey's test (p ≤ 0.05). The radiographic analysis of the ADDM + PTFE group showed greater homogeneity of bone radiopacity than the Control group and the PTFE group, during all the observation times. The dentin matrix gradually disappeared from the dental socket during the course of the repair process, suggesting its resorption during the bone remodeling process. It was concluded that the radiographic bone density of the dental sockets treated with ADDM was similar to that of the surrounding normal bone on the 90th day. The ADDM was biocompatible with the bone tissue of the surgical wounds of human dental sockets. The radiographic analysis revealed that the repair process was discreetly faster in the ADDM + PTFE group than in the Control and PTFE groups, although the difference was not statistically significant. In addition, the radiographic image of the ADDM + PTFE group suggested that its bone architecture was better than that of the Control and PFTE groups.

Histological analysis of effects of 24% EDTA gel for nonsurgical treatment of periodontal tissues

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Quantitative Chemical Profile and Multivariate Statistical Analysis of Alembic Distilled Sugarcane Spirit Fractions

Concentrations of 39 organic compounds were determined in three fractions (head, heart and tail) obtained from the pot still distillation of fermented sugarcane juice. The results were evaluated using analysis of variance (ANOVA), Tukey's test, principal component analysis (PCA), hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA). According to PCA and HCA, the experimental data lead to the formation of three clusters. The head fractions give rise to a more defined group. The heart and tail fractions showed some overlap consistent with its acid composition. The predictive ability of calibration and validation of the model generated by LDA for the three fractions classification were 90.5 and 100%, respectively. This model recognized as the heart twelve of the thirteen commercial cachacas (92.3%) with good sensory characteristics, thus showing potential for guiding the process of cuts.

Effects of an adapted physical activity program on the physical condition of elderly women: an analysis of efficiency

Background: Specific research tools and designs can assist in identifying the efficiency of physical activity in elderly women. Objectives: To identify the effects of physical activity on the physical condition of older women. Method: A one-year-long physical activity program (123 sessions) was implemented for women aged 60 years or older. Four physical assessments were conducted, in which weight, height, BMI, blood pressure, heart rate, absences, grip strength, flexibility, VO2max, and static and dynamic balance were assessed. The statistical analyses included a repeated measures analysis, both inferential (analysis of variance - ANOVA) and effect size (Cohen's d coefficient), as well as identification of the participants' efficiency (Data Envelopment Analysis - DEA). Results: Despite the observation of differences that depended on the analysis used, the results were successful in the sense that they showed that physical activity adapted to older women can effectively change the decline in physical ability associated with aging, depending on the purpose of the study. The 60-65 yrs group was the most capable of converting physical activity into health benefits in both the short and long term. The >65 yrs group took less advantage of physical activity. Conclusions: Adherence to the program and actual time spent on each type of exercise are the factors that determine which population can benefit from physical activity programs. The DEA allows the assessment of the results related to time spent on physical activity in terms of health concerns. Article registered in Clinicaltrials.gov under number NCT01558401.

An exploratory analysis of variance and volatility in epileptic electroencephalograms

The electroencephalogram (EEG) is a physiological time series that measures electrical activity at different locations in the brain, and plays an important role in epilepsy research. Exploring the variance and/or volatility may yield insights for seizure prediction, seizure detection and seizure propagation/dynamics.^ Maximal Overlap Discrete Wavelet Transforms (MODWTs) and ARMA-GARCH models were used to determine variance and volatility characteristics of 66 channels for different states of an epileptic EEG – sleep, awake, sleep-to-awake and seizure. The wavelet variances, changes in wavelet variances and volatility half-lives for the four states were compared for possible differences between seizure and non-seizure channels.^ The half-lives of two of the three seizure channels were found to be shorter than all of the non-seizure channels, based on 95% CIs for the pre-seizure and awake signals. No discernible patterns were found the wavelet variances of the change points for the different signals. ^

Comparisons among treatment means in an analysis of variance /

Issued Oct. 1977.