The Genetics of Alzheimer`s Disease in Brazil: 10 Years of Analysis in a Unique Population

Alzheimer`s Disease (AD) is the most common type of dementia among the elderly, with devastating consequences for the patient, their relatives, and caregivers. More than 300 genetic polymorphisms have been involved with AD, demonstrating that this condition is polygenic and with a complex pattern of inheritance. This paper aims to report and compare the results of AD genetics studies in case-control and familial analysis performed in Brazil since our first publication, 10 years ago. They include the following genes/markers: Apolipoprotein E (APOE), 5-hidroxytryptamine transporter length polymorphic region (5-HTTLPR), brain-derived neurotrophin factor (BDNF), monoamine oxidase A (MAO-A), and two simple-sequence tandem repeat polymorphisms (DXS1047 and D10S1423). Previously unpublished data of the interleukin-1 alpha (IL-1 alpha) and interleukin-1 beta (IL-1 beta) genes are reported here briefly. Results from others Brazilian studies with AD patients are also reported at this short review. Four local families studied with various markers at the chromosome 21, 19, 14, and 1 are briefly reported for the first time. The importance of studying DNA samples from Brazil is highlighted because of the uniqueness of its population, which presents both intense ethnical miscegenation, mainly at the east coast, but also clusters with high inbreeding rates in rural areas at the countryside. We discuss the current stage of extending these studies using high-throughput methods of large-scale genotyping, such as single nucleotide polymorphism microarrays, associated with bioinformatics tools that allow the analysis of such extensive number of genetics variables, with different levels of penetrance. There is still a long way between the huge amount of data gathered so far and the actual application toward the full understanding of AD, but the final goal is to develop precise tools for diagnosis and prognosis, creating new strategies for better treatments based on genetic profile.

Systematic revision and cladistic analysis of the Brazilian subfamily Sodreaninae (Opiliones: Gonyleptidae)

Sodreaninae is reviewed and all ten species are combined under its type genus, Sodreana Mello-Leitao, 1922, according to a cladistic analysis of morphological characters, which revealed a pectinate pattern of clades. The subfamily is endemic to the Brazilian Atlantic rainforest from Santa Catarina state to Rio de Janeiro state. Sodreana is herein considered a senior synonym of Stygnobates Mello-Leitao, 1927, Zortalia Mello-Leitao, 1936, Gertia B. Soares & H. Soares, 1946 and Annampheres H. Soares, 1979. The following new combinations are proposed: Sodreana barbiellinii (Mello-Leitao, 1927), Sodreana hatschbachi (B. Soares & H. Soares, 1946), Sodreana inscripta (Mello-Leitao, 1939), Sodreana leprevosti (B. Soares & H. Soares, 1947b), Sodreana bicalcarata (Mello-Leitao, 1936). Sodreana granulata (Mello-Leitao, 1937) is revalidated from the synonymy of Sodreana sodreana Mello-Leitao, 1922. Three new species are described: Sodreana glaucoi from Ilhabela and Boraceia, Sao Paulo state; S. curupira from Parque Nacional da Serra dos Orgaos, Rio de Janeiro state, and S. caipora from Ubatuba, Sao Paulo state. Sodreaninae species are restricted to forested areas and most occur in the southern part of the coastal Atlantic rainforest, one species occurs in interior Atlantic rainforest. The biogeographical analysis (Brooks Parsimony Analysis) resulted in a single and fully resolved most parsimonious tree with three main: components: northern (Bahia and Serra do Espinhaco), southern (Santa Catarina, Parana, Serra do Mar of Sao Paulo), and central (Espirito Santo, Serra da Bocaina, southern state of Rio de Janeiro, Serra dos Orgaos, Serra da Mantiqueira, Serra do Mar of Sao Paulo).

Morphometric analysis of the AMPA-type neurons in the Deiters vestibular complex of the chick brain

Chicken (Gallus gallus) brains were used to investigate the typology and the immunolabel pattern for the subunits composing the AMPA-type glutamate receptors (GluR) of hindbrain neurons of the dorsal (dND) and ventral nuclei (vND) of the Deiter`s vestibular complex (CD), which is the avian correspondent of the lateral vestibular nucleus (LVN) of mammals. Our results revealed that neurons of both divisions were poor in GluR1. The vND, the GluR2/3+ and GluR4+ label presented no area or neuronal size preference, although most neurons were around 75%. The dND neurons expressing GluR2/3 are primarily around 85%, medium to large-sized 85%, and predominantly 60% located in the medial portion of the rostral pole and in the lateral portion of the caudal pole. The majority of dND neurons containing GluR4 are also around 75%, larger (70% are large and giant), exhibiting a distribution that seems to be complementary to that of GluR2/3+ neurons. This distinct arrangement indicates functional differences into and between the DC nuclei, also signaling that such variation could be attributed to the diverse nature of the subunit composition of the GluRs. Discussion addresses the morphological and functional correlation of the avian DC with the LVN of mammals in addition to the high morphological correspondence, To include these data into the modern comparative approach we propose to adopt a similar nomenclature for the avian divisions dND and vND that could be referred as dLVN and vLVN. (C) 2008 Elsevier B.V. All rights reserved.

Topological multi-contour decomposition for image analysis and image retrieval

Successful classification, information retrieval and image analysis tools are intimately related with the quality of the features employed in the process. Pixel intensities, color, texture and shape are, generally, the basis from which most of the features are Computed and used in such fields. This papers presents a novel shape-based feature extraction approach where an image is decomposed into multiple contours, and further characterized by Fourier descriptors. Unlike traditional approaches we make use of topological knowledge to generate well-defined closed contours, which are efficient signatures for image retrieval. The method has been evaluated in the CBIR context and image analysis. The results have shown that the multi-contour decomposition, as opposed to a single shape information, introduced a significant improvement in the discrimination power. (c) 2008 Elsevier B.V. All rights reserved,

Mechanical analysis of infant carrying in hominoids

In all higher nonhuman primates, species survival depends upon safe carrying of infants clinging to body hair of adults. In this work, measurements of mechanical properties of ape hair (gibbon, orangutan, and gorilla) are presented, focusing on constraints for safe infant carrying. Results of hair tensile properties are shown to be species-dependent. Analysis of the mechanics of the mounting position, typical of heavier infant carrying among African apes, shows that both clinging and friction are necessary to carry heavy infants. As a consequence, a required relationship between infant weight, hair-hair friction coefficient, and body angle exists. The hair-hair friction coefficient is measured using natural ape skin samples, and dependence on load and humidity is analyzed. Numerical evaluation of the equilibrium constraint is in agreement with the knuckle-walking quadruped position of African apes. Bipedality is clearly incompatible with the usual clinging and mounting pattern of infant carrying, requiring a revision of models of hominization in relation to the divergence between apes and hominins. These results suggest that safe carrying of heavy infants justify the emergence of biped form of locomotion. Ways to test this possibility are foreseen here.

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.

Texture analysis and classification using deterministic tourist walk

In this paper, we present a study on a deterministic partially self-avoiding walk (tourist walk), which provides a novel method for texture feature extraction. The method is able to explore an image on all scales simultaneously. Experiments were conducted using different dynamics concerning the tourist walk. A new strategy, based on histograms. to extract information from its joint probability distribution is presented. The promising results are discussed and compared to the best-known methods for texture description reported in the literature. (C) 2009 Elsevier Ltd. All rights reserved.

Texture analysis using graphs generated by deterministic partially self-avoiding walks

Texture is one of the most important visual attributes for image analysis. It has been widely used in image analysis and pattern recognition. A partially self-avoiding deterministic walk has recently been proposed as an approach for texture analysis with promising results. This approach uses walkers (called tourists) to exploit the gray scale image contexts in several levels. Here, we present an approach to generate graphs out of the trajectories produced by the tourist walks. The generated graphs embody important characteristics related to tourist transitivity in the image. Computed from these graphs, the statistical position (degree mean) and dispersion (entropy of two vertices with the same degree) measures are used as texture descriptors. A comparison with traditional texture analysis methods is performed to illustrate the high performance of this novel approach. (C) 2011 Elsevier Ltd. All rights reserved.

A complex network-based approach for boundary shape analysis

This paper introduces a novel methodology to shape boundary characterization, where a shape is modeled into a small-world complex network. It uses degree and joint degree measurements in a dynamic evolution network to compose a set of shape descriptors. The proposed shape characterization method has all efficient power of shape characterization, it is robust, noise tolerant, scale invariant and rotation invariant. A leaf plant classification experiment is presented on three image databases in order to evaluate the method and compare it with other descriptors in the literature (Fourier descriptors, Curvature, Zernike moments and multiscale fractal dimension). (C) 2008 Elsevier Ltd. All rights reserved.

A pattern recognition approach to complex networks

Complex networks exist in many areas of science such as biology, neuroscience, engineering, and sociology. The growing development of this area has led to the introduction of several topological and dynamical measurements, which describe and quantify the structure of networks. Such characterization is essential not only for the modeling of real systems but also for the study of dynamic processes that may take place in them. However, it is not easy to use several measurements for the analysis of complex networks, due to the correlation between them and the difficulty of their visualization. To overcome these limitations, we propose an effective and comprehensive approach for the analysis of complex networks, which allows the visualization of several measurements in a few projections that contain the largest data variance and the classification of networks into three levels of detail, vertices, communities, and the global topology. We also demonstrate the efficiency and the universality of the proposed methods in a series of real-world networks in the three levels.

ENHANCING MULTISCALE FRACTAL DESCRIPTORS USING FUNCTIONAL DATA ANALYSIS

This work presents a novel approach in order to increase the recognition power of Multiscale Fractal Dimension (MFD) techniques, when applied to image classification. The proposal uses Functional Data Analysis (FDA) with the aim of enhancing the MFD technique precision achieving a more representative descriptors vector, capable of recognizing and characterizing more precisely objects in an image. FDA is applied to signatures extracted by using the Bouligand-Minkowsky MFD technique in the generation of a descriptors vector from them. For the evaluation of the obtained improvement, an experiment using two datasets of objects was carried out. A dataset was used of characters shapes (26 characters of the Latin alphabet) carrying different levels of controlled noise and a dataset of fish images contours. A comparison with the use of the well-known methods of Fourier and wavelets descriptors was performed with the aim of verifying the performance of FDA method. The descriptor vectors were submitted to Linear Discriminant Analysis (LDA) classification method and we compared the correctness rate in the classification process among the descriptors methods. The results demonstrate that FDA overcomes the literature methods (Fourier and wavelets) in the processing of information extracted from the MFD signature. In this way, the proposed method can be considered as an interesting choice for pattern recognition and image classification using fractal analysis.

Texture analysis based on maximum contrast walker

Recently, the deterministic tourist walk has emerged as a novel approach for texture analysis. This method employs a traveler visiting image pixels using a deterministic walk rule. Resulting trajectories provide clues about pixel interaction in the image that can be used for image classification and identification tasks. This paper proposes a new walk rule for the tourist which is based on contrast direction of a neighborhood. The yielded results using this approach are comparable with those from traditional texture analysis methods in the classification of a set of Brodatz textures and their rotated versions, thus confirming the potential of the method as a feasible texture analysis methodology. (C) 2010 Elsevier B.V. All rights reserved.

Single Synapse Information Coding in Intraburst Spike Patterns of Central Pattern Generator Motor Neurons

Burst firing is ubiquitous in nervous systems and has been intensively studied in central pattern generators (CPGs). Previous works have described subtle intraburst spike patterns (IBSPs) that, despite being traditionally neglected for their lack of relation to CPG motor function, were shown to be cell-type specific and sensitive to CPG connectivity. Here we address this matter by investigating how a bursting motor neuron expresses information about other neurons in the network. We performed experiments on the crustacean stomatogastric pyloric CPG, both in control conditions and interacting in real-time with computer model neurons. The sensitivity of postsynaptic to presynaptic IBSPs was inferred by computing their average mutual information along each neuron burst. We found that details of input patterns are nonlinearly and inhomogeneously coded through a single synapse into the fine IBSPs structure of the postsynaptic neuron following burst. In this way, motor neurons are able to use different time scales to convey two types of information simultaneously: muscle contraction (related to bursting rhythm) and the behavior of other CPG neurons (at a much shorter timescale by using IBSPs as information carriers). Moreover, the analysis revealed that the coding mechanism described takes part in a previously unsuspected information pathway from a CPG motor neuron to a nerve that projects to sensory brain areas, thus providing evidence of the general physiological role of information coding through IBSPs in the regulation of neuronal firing patterns in remote circuits by the CNS.

Crystal structure and statistical coupling analysis of highly glycosylated peroxidase from royal palm tree (Roystonea regia)

Royal palm tree peroxidase (RPTP) is a very stable enzyme in regards to acidity, temperature, H(2)O(2), and organic solvents. Thus, RPTP is a promising candidate for developing H(2)O(2)-sensitive biosensors for diverse applications in industry and analytical chemistry. RPTP belongs to the family of class III secretory plant peroxidases, which include horseradish peroxidase isozyme C, soybean and peanut peroxidases. Here we report the X-ray structure of native RPTP isolated from royal palm tree (Roystonea regia) refined to a resolution of 1.85 angstrom. RPTP has the same overall folding pattern of the plant peroxidase superfamily, and it contains one heme group and two calcium-binding sites in similar locations. The three-dimensional structure of RPTP was solved for a hydroperoxide complex state, and it revealed a bound 2-(N-morpholino) ethanesulfonic acid molecule (MES) positioned at a putative substrate-binding secondary site. Nine N-glycosylation sites are clearly defined in the RPTP electron-density maps, revealing for the first time conformations of the glycan chains of this highly glycosylated enzyme. Furthermore, statistical coupling analysis (SCA) of the plant peroxidase superfamily was performed. This sequence-based method identified a set of evolutionarily conserved sites that mapped to regions surrounding the heme prosthetic group. The SCA matrix also predicted a set of energetically coupled residues that are involved in the maintenance of the structural folding of plant peroxidases. The combination of crystallographic data and SCA analysis provides information about the key structural elements that could contribute to explaining the unique stability of RPTP. (C) 2009 Elsevier Inc. All rights reserved.

Structural analysis of the Itapucumi Group in the Vallemi region, northern Paraguay: Evidence of a new Brasiliano/Pan-African mobile belt

The Neoproterozoic (Ediacaran) Itapucumi Group in northern Paraguay is composed of carbonate and siliciclastic rocks, including ooid grainstones, marls, shales and sandstones, containing Cloudina fossils in the eastern region. It is almost undeformed over the Rio Apa Cratonic Block but shows a strong deformational pattern at its western edge. A detailed structural analysis of the Itapucumi Group was conducted in the Vallemi Mine, along with a regional survey in other outcrops downstream in the Paraguay River and in the San Alfredo, Cerro Paiva and Sargent Jose E. Lopez regions. In the main Vallemi quarry, the structural style is characterized by an axial-plane slaty cleavage in open to isoclinal folds, sometimes overturned, associated with N-S trending thrust faults and shear zones of E-vergence and with a low-grade chlorite zone metamorphism. The structural data presented here are compatible with the hypothesis of a newly recognized mobile belt on the western side of the Rio Apa Cratonic Block, with opposite vergence to that of the Paraguay Mobile Belt in Brazil. Both belts are related to the Late Brasiliano/Pan-African tectonic cycle with a Lower Cambrian deformation and metamorphism age. The deformation could be due to the late collision of the Amazonian Craton with the remainder of Western Gondwana or to the western active plate boundary related to the Pampean Belt. The structural and lithologic differences between the western Itapucumi Group in the Vallemi and Paraguay River region and the eastern region, near San Alfredo and Cerro Paiva, suggest that this group could be divided into two lithostratigraphic units, but more stratigraphic and geochronological analyses are required to confirm this possibility. (C) 2010 Elsevier Ltd. All rights reserved.