Mild cognitive deficits associated to neocortical microgyria in mice with genetic deletion of cellular prion protein

The cellular prion protein (PrP(c)) has been implicated with the modulation of neuronal apoptosis, adhesion, neurite outgrowth and maintenance which are processes involved in the neocortical development. Malformations of cortical development (MCD) are frequently associated with neurological conditions including mental retardation, autism, and epilepsy. Here we investigated the behavioral performance of female adult PrP(c)-null mice (Prnp(%)) and their wild-type controls (Prnp(+/+)) presenting unilateral polymicrogyria, a MCD experimentally induced by neonatal freeze-lesion in the right hemisphere. injured mice from both genotypes presented similar locomotor activity but Prnp(%) mice showed a tendency to increase anxiety-related responses when compared to Prnp(+/+) animals. Additionally, injured Prnp(%) mice have a poorer performance in the social recognition task than sham-operated and Prnp(%) injured ones. Moreover the step-down inhibitory avoidance task was not affected by the procedure or the genotype of the animals. These data suggest that the genetic deletion of PrP(c) confers increased susceptibility to short-term social memory deficits induced by neonatal freezing model of polymicrogyria in mice. (C) 2008 Published by Elsevier B.V.

Absence and hypoplasia of the mental foramen detected in CBCT images: a case report

The mental foramen (MF) is an important anatomic landmark of the mandible, through which the mental nerve and blood vessels emerge. The importance of MF in dental practice is especially related to dental implants placement and other surgical procedures in the region. It is fundamental to be careful in order to avoid nerve and vessels injury during procedures. Anatomic variations of the MF can be found, such as occurrence of multiple foramina and unusual location. In very rare occasions, the absence of MF can be detected. The observation of this variation is not always possible using only conventional radiographs. The modern imaging resource cone beam computed tomography (CBCT) allows an accurate three-dimensional assessment of MF, as well as the identification of its variations. The aim of this article is to report MF absence and hypoplasia detected in CBCT images of a 27-year-old daughter and her 63-year-old mother, both from Brazil. Despite the MF anatomic variations, they presented no sensorial disturbance in the regions supplied by the mental nerve.

EXACT AND QUASI-EXACT MODELS OF STRANGE STARS

We construct and compare in this work a variety of simple models for strange stars, namely, hypothetical self-bound objects made of a cold stable version of the quark-gluon plasma. Exact, quasi-exact and numerical models are examined to find the most economical description for these objects. A simple and successful parametrization of them is given in terms of the central density, and the differences among the models are explicitly shown and discussed. In particular, we present a model starting with a Gaussian ansatz for the density profile that provides a very accurate and almost complete analytical integration of the problem, modulo a small difference for one of the metric potentials.

Black-box decomposition approach for computational hemodynamics: One-dimensional models

Increasing efforts exist in integrating different levels of detail in models of the cardiovascular system. For instance, one-dimensional representations are employed to model the systemic circulation. In this context, effective and black-box-type decomposition strategies for one-dimensional networks are needed, so as to: (i) employ domain decomposition strategies for large systemic models (1D-1D coupling) and (ii) provide the conceptual basis for dimensionally-heterogeneous representations (1D-3D coupling, among various possibilities). The strategy proposed in this article works for both of these two scenarios, though the several applications shown to illustrate its performance focus on the 1D-1D coupling case. A one-dimensional network is decomposed in such a way that each coupling point connects two (and not more) of the sub-networks. At each of the M connection points two unknowns are defined: the flow rate and pressure. These 2M unknowns are determined by 2M equations, since each sub-network provides one (non-linear) equation per coupling point. It is shown how to build the 2M x 2M non-linear system with arbitrary and independent choice of boundary conditions for each of the sub-networks. The idea is then to solve this non-linear system until convergence, which guarantees strong coupling of the complete network. In other words, if the non-linear solver converges at each time step, the solution coincides with what would be obtained by monolithically modeling the whole network. The decomposition thus imposes no stability restriction on the choice of the time step size. Effective iterative strategies for the non-linear system that preserve the black-box character of the decomposition are then explored. Several variants of matrix-free Broyden`s and Newton-GMRES algorithms are assessed as numerical solvers by comparing their performance on sub-critical wave propagation problems which range from academic test cases to realistic cardiovascular applications. A specific variant of Broyden`s algorithm is identified and recommended on the basis of its computer cost and reliability. (C) 2010 Elsevier B.V. All rights reserved.

Transformed generalized linear models

The estimation of data transformation is very useful to yield response variables satisfying closely a normal linear model, Generalized linear models enable the fitting of models to a wide range of data types. These models are based on exponential dispersion models. We propose a new class of transformed generalized linear models to extend the Box and Cox models and the generalized linear models. We use the generalized linear model framework to fit these models and discuss maximum likelihood estimation and inference. We give a simple formula to estimate the parameter that index the transformation of the response variable for a subclass of models. We also give a simple formula to estimate the rth moment of the original dependent variable. We explore the possibility of using these models to time series data to extend the generalized autoregressive moving average models discussed by Benjamin er al. [Generalized autoregressive moving average models. J. Amer. Statist. Assoc. 98, 214-223]. The usefulness of these models is illustrated in a Simulation study and in applications to three real data sets. (C) 2009 Elsevier B.V. All rights reserved.

Likelihood ratio tests for variance components in linear mixed models

Although the asymptotic distributions of the likelihood ratio for testing hypotheses of null variance components in linear mixed models derived by Stram and Lee [1994. Variance components testing in longitudinal mixed effects model. Biometrics 50, 1171-1177] are valid, their proof is based on the work of Self and Liang [1987. Asymptotic properties of maximum likelihood estimators and likelihood tests under nonstandard conditions. J. Amer. Statist. Assoc. 82, 605-610] which requires identically distributed random variables, an assumption not always valid in longitudinal data problems. We use the less restrictive results of Vu and Zhou [1997. Generalization of likelihood ratio tests under nonstandard conditions. Ann. Statist. 25, 897-916] to prove that the proposed mixture of chi-squared distributions is the actual asymptotic distribution of such likelihood ratios used as test statistics for null variance components in models with one or two random effects. We also consider a limited simulation study to evaluate the appropriateness of the asymptotic distribution of such likelihood ratios in moderately sized samples. (C) 2008 Elsevier B.V. All rights reserved.