Correlation between vertical misfits and stresses transmitted to implants from metal frameworks

An inappropriate prosthetic fit could cause stress over the interface implant/bone. The objective of this study was to compare stresses transmitted to implants from frameworks cast using different materials and to investigate a possible correlation between vertical misfits and these stresses. Fifteen one-piece cast frameworks simulating bars for fixed prosthesis in a model with five implants were fabricated and arranged into three different groups according to the material used for casting: CP Ti (commercially pure titanium), Co-Cr (cobalt-chromium) or Ni-Cr-Ti (nickel-chromium-titanium) alloys. Each framework was installed over the metal model with all screws tightened to a 10 N cm torque and then, vertical misfits were measured using an optical microscope. The stresses transmitted to implants were measured using quantitative photoelastic analysis in values of maximum shear stress (T), when each framework was tightened to the photoelastic model to a 10 N cm standardized torque. Stress data were statistically analyzed using one-way ANOVA and Tukey`s test and correlation tests were performed using Pearson`s rank correlation (alpha = 0.05). Mean and standard deviation values of vertical misfit are presented for CP Ti (22.40 +/- 9.05 mu m), Co-Cr (66.41 +/- 35.47 mu m) and Ni-Cr-Ti (32.20 +/- 24.47 mu m). Stresses generated by Co-Cr alloy (tau = 7.70 +/- 2.16 kPa) were significantly higher than those generated by CP Ti (tau = 5.86 +/- 1.55 kPa, p = 0.018) and Ni-Cr-Ti alloy (tau =5.74 +/- 3.05 kPa, p = 0.011), which were similar (p = 0.982). Correlations between vertical misfits and stresses around the implants were not significant as for any evaluated materials. (C) 2011 Elsevier Ltd. All rights reserved.

The beta Laplace distribution

The Laplace distribution is one of the earliest distributions in probability theory. For the first time, based on this distribution, we propose the so-called beta Laplace distribution, which extends the Laplace distribution. Various structural properties of the new distribution are derived, including expansions for its moments, moment generating function, moments of the order statistics, and so forth. We discuss maximum likelihood estimation of the model parameters and derive the observed information matrix. The usefulness of the new model is illustrated by means of a real data set. (C) 2011 Elsevier B.V. All rights reserved.