Population and Computational Analysis of the MGEA6 P521A Variation as a Risk Factor for Familial Idiopathic Basal Ganglia Calcification (Fahr`s Disease)

Familial idiopathic basal ganglia calcification, also known as ""Fahr`s disease"" (FD), is a neuropsychiatric disorder with autosomal dominant pattern of inheritance and characterized by symmetric basal ganglia calcifications and, occasionally, other brain regions. Currently, there are three loci linked to this devastating disease. The first one (IBGC1) is located in 14q11.2-21.3 and the other two have been identified in 2q37 (IBGC2) and 8p21.1-q11.13 (IBGC3). Further studies identified a heterozygous variation (rs36060072) which consists in the change of the cytosine to guanine located at MGEA6/CTAGE5 gene, present in all of the affected large American family linked to IBGC1. This missense substitution, which induces changes of a proline to alanine at the 521 position (P521A), in a proline-rich and highly conserved protein domain was considered a rare variation, with a minor allele frequency (MAF) of 0.0058 at the US population. Considering that the population frequency of a given variation is an indirect indicative of potential pathogenicity, we screened 200 chromosomes in a random control set of Brazilian samples and in two nuclear families, comparing with our previous analysis in a US population. In addition, we accomplished analyses through bioinformatics programs to predict the pathogenicity of such variation. Our genetic screen found no P521A carriers. Polling these data together with the previous study in the USA, we have now a MAF of 0.0036, showing that this mutation is very rare. On the other hand, the bioinformatics analysis provided conflicting findings. There are currently various candidate genes and loci that could be involved with the underlying molecular basis of FD etiology, and other groups suggested the possible role played by genes in 2q37, related to calcium metabolism, and at chromosome 8 (NRG1 and SNTG1). Additional mutagenesis and in vivo studies are necessary to confirm the pathogenicity for variation in the P521A MGEA6.

A psychophysical and computational analysis of the spatio-temporal mechanisms underlying the flash-lag effect

Several accounts put forth to explain the flash-lag effect (FLE) rely mainly on either spatial or temporal mechanisms. Here we investigated the relationship between these mechanisms by psychophysical and theoretical approaches. In a first experiment we assessed the magnitudes of the FLE and temporal-order judgments performed under identical visual stimulation. The results were interpreted by means of simulations of an artificial neural network, that wits also employed to make predictions concerning the F LE. The model predicted that a spatio-temporal mislocalisation would emerge from two, continuous and abrupt-onset, moving stimuli. Additionally, a straightforward prediction of the model revealed that the magnitude of this mislocalisation should be task-dependent, increasing when the use of the abrupt-onset moving stimulus switches from a temporal marker only to both temporal and spatial markers. Our findings confirmed the model`s predictions and point to an indissoluble interplay between spatial facilitation and processing delays in the FLE.

Efficiency issues of evolutionary k-means

One of the top ten most influential data mining algorithms, k-means, is known for being simple and scalable. However, it is sensitive to initialization of prototypes and requires that the number of clusters be specified in advance. This paper shows that evolutionary techniques conceived to guide the application of k-means can be more computationally efficient than systematic (i.e., repetitive) approaches that try to get around the above-mentioned drawbacks by repeatedly running the algorithm from different configurations for the number of clusters and initial positions of prototypes. To do so, a modified version of a (k-means based) fast evolutionary algorithm for clustering is employed. Theoretical complexity analyses for the systematic and evolutionary algorithms under interest are provided. Computational experiments and statistical analyses of the results are presented for artificial and text mining data sets. (C) 2010 Elsevier B.V. All rights reserved.

An incremental space to visualize dynamic data sets

In Information Visualization, adding and removing data elements can strongly impact the underlying visual space. We have developed an inherently incremental technique (incBoard) that maintains a coherent disposition of elements from a dynamic multidimensional data set on a 2D grid as the set changes. Here, we introduce a novel layout that uses pairwise similarity from grid neighbors, as defined in incBoard, to reposition elements on the visual space, free from constraints imposed by the grid. The board continues to be updated and can be displayed alongside the new space. As similar items are placed together, while dissimilar neighbors are moved apart, it supports users in the identification of clusters and subsets of related elements. Densely populated areas identified in the incSpace can be efficiently explored with the corresponding incBoard visualization, which is not susceptible to occlusion. The solution remains inherently incremental and maintains a coherent disposition of elements, even for fully renewed sets. The algorithm considers relative positions for the initial placement of elements, and raw dissimilarity to fine tune the visualization. It has low computational cost, with complexity depending only on the size of the currently viewed subset, V. Thus, a data set of size N can be sequentially displayed in O(N) time, reaching O(N (2)) only if the complete set is simultaneously displayed.

On the efficiency of evolutionary fuzzy clustering

This paper tackles the problem of showing that evolutionary algorithms for fuzzy clustering can be more efficient than systematic (i.e. repetitive) approaches when the number of clusters in a data set is unknown. To do so, a fuzzy version of an Evolutionary Algorithm for Clustering (EAC) is introduced. A fuzzy cluster validity criterion and a fuzzy local search algorithm are used instead of their hard counterparts employed by EAC. Theoretical complexity analyses for both the systematic and evolutionary algorithms under interest are provided. Examples with computational experiments and statistical analyses are also presented.

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.

A computational study of some rheological influences on the ""splashing experiment""

In various attempts to relate the behaviour of highly-elastic liquids in complex flows to their rheometrical behaviour, obvious candidates for study have been the variation of shear viscosity with shear rate, the two normal stress differences N(1) and N(2), especially N(1), the extensional viscosity, and the dynamic moduli G` and G ``. In this paper, we shall confine attention to `constant-viscosity` Boger fluids, and, accordingly, we shall limit attention to N(1), eta(E), G` and G ``. We shall concentrate on the ""splashing"" problem (particularly that which arises when a liquid drop falls onto the free surface of the same liquid). Modern numerical techniques are employed to provide the theoretical predictions. We show that high eta(E) can certainly reduce the height of the so-called Worthington jet, thus confirming earlier suggestions, but other rheometrical influences (steady and transient) can also have a role to play and the overall picture may not be as clear as it was once envisaged. We argue that this is due in the main to the fact that splashing is a manifestly unsteady flow. To confirm this proposition, we obtain numerical simulations for the linear Jeffreys model. (C) 2010 Elsevier B.V. All rights reserved.

Medical image retrieval based on complexity analysis

Texture is one of the most important visual attributes used in image analysis. It is used in many content-based image retrieval systems, where it allows the identification of a larger number of images from distinct origins. This paper presents a novel approach for image analysis and retrieval based on complexity analysis. The approach consists of a texture segmentation step, performed by complexity analysis through BoxCounting fractal dimension, followed by the estimation of complexity of each computed region by multiscale fractal dimension. Experiments have been performed with MRI database in both pattern recognition and image retrieval contexts. Results show the accuracy of the method and also indicate how the performance changes as the texture segmentation process is altered.

Fractal dimension applied to plant identification

This article discusses methods to identify plants by analysing leaf complexity based on estimating their fractal dimension. Leaves were analyzed according to the complexity of their internal and external shapes. A computational program was developed to process, analyze and extract the features of leaf images, thereby allowing for automatic plant identification. Results are presented from two experiments, the first to identify plant species from the Brazilian Atlantic forest and Brazilian Cerrado scrublands, using fifty leaf samples from ten different species, and the second to identify four different species from genus Passiflora, using twenty leaf samples for each class. A comparison is made of two methods to estimate fractal dimension (box-counting and multiscale Minkowski). The results are discussed to determine the best approach to analyze shape complexity based on the performance of the technique, when estimating fractal dimension and identifying plants. (C) 2008 Elsevier Inc. All rights reserved.

Complexity and anisotropy in host morphology make populations less susceptible to epidemic outbreaks

One of the challenges in epidemiology is to account for the complex morphological structure of hosts such as plant roots, crop fields, farms, cells, animal habitats and social networks, when the transmission of infection occurs between contiguous hosts. Morphological complexity brings an inherent heterogeneity in populations and affects the dynamics of pathogen spread in such systems. We have analysed the influence of realistically complex host morphology on the threshold for invasion and epidemic outbreak in an SIR (susceptible-infected-recovered) epidemiological model. We show that disorder expressed in the host morphology and anisotropy reduces the probability of epidemic outbreak and thus makes the system more resistant to epidemic outbreaks. We obtain general analytical estimates for minimally safe bounds for an invasion threshold and then illustrate their validity by considering an example of host data for branching hosts (salamander retinal ganglion cells). Several spatial arrangements of hosts with different degrees of heterogeneity have been considered in order to separately analyse the role of shape complexity and anisotropy in the host population. The estimates for invasion threshold are linked to morphological characteristics of the hosts that can be used for determining the threshold for invasion in practical applications.

Study of the phenanthroline-Mn-imidazole bonding in Mn(I) triscarbonyl complex: A X-ray and DFT computational analysis

355 nm light irradiation of fac-[Mn(CO)(3)(phen)(imH)](+) (fac-1) produces the mer-1 isomer and a long lived radical which can be efficiently trapped by electron acceptor molecules. EPR experiments shows that when excited, the manganese(I) complex can be readily oxidized by one-electron process to produce Mn(II) and phen(.-). In the present study, DFT calculations have been used to investigated the photochemical isomerization of the parent Mn(I) complex and to characterize the electronic structures of the long lived radical. The theoretical calculations have been performed on both the fac-1 and mer-1 species as well as on their one electron oxidized species fac-1+ and mer-1+ for the lowest spin configurations (S = 1/2) and fac-6 and mer-6 (S = 5/2) for the highest one to characterize these complexes. In particular, we used a charge decomposition analysis (CDA) and a natural bonding orbital (NBO) to have a better understanding of the chemical bonding in terms of the nature of electronic interactions. The observed variations in geometry and bond energies with an increasing oxidation state in the central metal ion are interpreted in terms of changes in the nature of metal-ligand bonding interactions. The X-ray structure of fac-1 is also described. (C) 2011 Elsevier B.V. All rights reserved.

3D face computational photography using PCA spaces

In this paper, we present a 3D face photography system based on a facial expression training dataset, composed of both facial range images (3D geometry) and facial texture (2D photography). The proposed system allows one to obtain a 3D geometry representation of a given face provided as a 2D photography, which undergoes a series of transformations through the texture and geometry spaces estimated. In the training phase of the system, the facial landmarks are obtained by an active shape model (ASM) extracted from the 2D gray-level photography. Principal components analysis (PCA) is then used to represent the face dataset, thus defining an orthonormal basis of texture and another of geometry. In the reconstruction phase, an input is given by a face image to which the ASM is matched. The extracted facial landmarks and the face image are fed to the PCA basis transform, and a 3D version of the 2D input image is built. Experimental tests using a new dataset of 70 facial expressions belonging to ten subjects as training set show rapid reconstructed 3D faces which maintain spatial coherence similar to the human perception, thus corroborating the efficiency and the applicability of the proposed system.

A note on influence diagnostics in nonlinear mixed-effects elliptical models

This paper provides general matrix formulas for computing the score function, the (expected and observed) Fisher information and the A matrices (required for the assessment of local influence) for a quite general model which includes the one proposed by Russo et al. (2009). Additionally, we also present an expression for the generalized leverage on fixed and random effects. The matrix formulation has notational advantages, since despite the complexity of the postulated model, all general formulas are compact, clear and have nice forms. (C) 2010 Elsevier B.V. All rights reserved.

Oxindole-Schiff base copper(II) complexes interactions with human serum albumin: Spectroscopic, oxidative damage, and computational studies

CD and EPR were used to characterize interactions of oxindole-Schiff base copper(II) complexes with human serum albumin (HSA). These imine ligands form very stable complexes with copper, and can efficiently compete for this metal ion towards the specific N-terminal binding site of the protein, consisting of the amino acid sequence Asp-Ala-His. Relative stability constants for the corresponding complexes were estimated from CD data, using the protein as competitive ligand, with values of log K(CuL) in the range 15.7-18.1, very close to that of [Cu(HSA)] itself, with log K(CuHSA) 16.2. Some of the complexes are also able to interfere in the a-helix structure of the protein, while others seem not to affect it. EPR spectra corroborate those results, indicating at least two different metal species in solution, depending on the imine ligand. Oxidative damage to the protein after incubation with these copper(II) complexes, particularly in the presence of hydrogen peroxide, was monitored by carbonyl groups formation, and was observed to be more severe when conformational features of the protein were modified. Complementary EPR spin-trapping data indicated significant formation of hydroxyl and carbon centered radicals, consistent with an oxidative mechanism. Theoretical calculations at density functional theory (DFT) level were employed to evaluate Cu(II)-L binding energies, L -> Cu(II) donation, and Cu(II) -> L back-donation, by considering the Schiff bases and the N-terminal site of HSA as ligands. These results complement previous studies on cytotoxicity, nuclease and pro-apoptotic properties of this kind of copper(II) complexes, providing additional information about their possibilities of transport and disposition in blood plasma. (C) 2009 Elsevier Inc. All rights reserved.

Structural studies of prephenate dehydratase from Mycobacterium tuberculosis H37Rv by SAXS, ultracentrifugation, and computational analysis

Tuberculosis (TB) is one of the most common infectious diseases known to man and responsible for millions of human deaths in the world. The increasing incidence of TB in developing countries, the proliferation of multidrug resistant strains, and the absence of resources for treatment have highlighted the need of developing new drugs against TB. The shikimate pathway leads to the biosynthesis of chorismate, a precursor of aromatic amino acids. This pathway is absent from mammals and shown to be essential for the survival of Mycobacterium tuberculosis, the causative agent of TB. Accordingly, enzymes of aromatic amino acid biosynthesis pathway represent promising targets for structure-based drug design. The first reaction in phenylalanine biosynthesis involves the conversion of chorismate to prephenate, catalyzed by chorismate mutase. The second reaction is catalyzed by prephenate dehydratase (PDT) and involves decarboxylation and dehydratation of prephenate to form phenylpyruvate, the precursor of phenylalanine. Here, we describe utilization of different techniques to infer the structure of M. tuberculosis PDT (MtbPDT) in solution. Small angle X-ray scattering and ultracentrifugation analysis showed that the protein oligomeric state is a tetramer and MtbPDT is a flat disk protein. Bioinformatics tools were used to infer the structure of MtbPDT A molecular model for MtbPDT is presented and molecular dynamics simulations indicate that MtbPDT i.s stable. Experimental and molecular modeling results were in agreement and provide evidence for a tetrameric state of MtbPDT in solution.