Analysis of the combined effect of lasers of different wavelengths for PDT outcome using 600, 630, and 660 nm

We investigated the effects of photodynamic therapy (PDT) outcome when combining three laser systems that produce light in three different wavelengths (600, 630, and 660 nm). Cooperative as well as independent effects can be observed. We compared the results of the combined wavelengths of light with the effect of single laser for the excitation of the photosensitizer. In the current experiment, the used photosensitizer was Photogem (R) (1.5 mg/kg). Combining two wavelengths for PDT, their cumulative dose and different penetrability may change the overall effect of the fluence of light, which can be effective for increasing the depth of necrosis. This evaluation was performed by comparing the depth and specific aspect of necrosis obtained by using single and dual wavelengths for irradiation of healthy liver of male Wistar rats. We used 15 animals and divided them in five groups of three animals. First, Photogem (R) was administered; follow by measurement of the fluorescence spectrum of the liver before PDT to confirm the level of accumulation of photosensitizer in the tissue. After that, an area of 1 cm(2) of the liver was illuminated using different laser combinations. Qualitative analysis of the necrosis was carried out through histological and morphological study. [GRAPHICS] (a) - microscopic images of rat liver cells, (b) - superficial necrosis caused by PDT using dual-wavelength illumination, (c) - neutrophilic infiltration around the vessel inside the necrosis, and (d) - neutrophilic infiltration around the vessel between necrosis and live tissue (C) 2011 by Astro Ltd. Published exclusively by WILEY-VCH Verlag GmbH & Co. KGaA

A robust Bayesian approach to null intercept measurement error model with application to dental data

Measurement error models often arise in epidemiological and clinical research. Usually, in this set up it is assumed that the latent variable has a normal distribution. However, the normality assumption may not be always correct. Skew-normal/independent distribution is a class of asymmetric thick-tailed distributions which includes the Skew-normal distribution as a special case. In this paper, we explore the use of skew-normal/independent distribution as a robust alternative to null intercept measurement error model under a Bayesian paradigm. We assume that the random errors and the unobserved value of the covariate (latent variable) follows jointly a skew-normal/independent distribution, providing an appealing robust alternative to the routine use of symmetric normal distribution in this type of model. Specific distributions examined include univariate and multivariate versions of the skew-normal distribution, the skew-t distributions, the skew-slash distributions and the skew contaminated normal distributions. The methods developed is illustrated using a real data set from a dental clinical trial. (C) 2008 Elsevier B.V. All rights reserved.