miRNA analysis of prostate cancer by quantitative real time PCR: Comparison between formalin-fixed paraffin embedded and fresh-frozen tissue

Objective: Micro RNA (miRNA) is a class of small noncoding RNA that plays a major role in the regulation of gene expression, which has been related to cancer behavior. The possibility of analyzing miRNA from the archives of pathology laboratories is exciting, as it allows for large retrospective studies. Formalin is the most common fixative used in the surgical pathology routine, and its promotion of nucleic acid degradation is well known. Our aim is to compare miRNA profiles from formalin-fixed paraffin embedded (FFPE) tissues with fresh-frozen prostate cancer tissues. Methods: The expression of 14 miRNAs was determined by quantitative real time polymerase chain reaction (qRT-PCR) in 5 paired fresh-frozen and FFPE tissues, which were representative of prostate carcinoma. Results: There was a very good correlation of the miRNA expression of miR-let7c and miR-32 between the fresh-frozen and FFPE tissues, with Pearson`s correlation coefficients of 0.927 (P = 0.023) and 0.960 (P = 0.010), respectively. For the remaining miRNAs, the correlation was good with Spearman correlation coefficient of 0.638 (P < 0.001). Conclusion: Analysis of miRNAs from routinely processed and stored FFPE prostate tissue is feasible for some miRNAs using qRT-PCR. Further studies should be conducted to confirm the reliability of using stock tissues for miRNA expression determination. (C) 2011 Elsevier Inc. All rights reserved.

Behavioral Types for Embedded Software - A Survey

At present, there is a variety of formalisms for modeling and analyzing the communication behavior of components. Due to a tremendous increase in size and complexity of embedded systems accompanied by shorter time to market cycles and cost reduction, so called behavioral type systems become more and more important. This chapter presents an overview and a taxonomy of behavioral types. The intentions of this taxonomy are to provide a guidance for software engineers and to form the basis for future research.

Ultrastructure of Motor Nerve Terminals in the Anterior Third of Wistar Rat Tongue

The nerve terminals of intrinsic muscular fibers of the tongue of adult wistar rats was studied by using silver impregnation techniques, transmission electron microscopy (TEM), and high resolution scanning electron microscopy (HRSEM) to observe the nerve fibers and their terminals. Silver impregnation was done according to Winkelman and Schmit, 1957. For TEM, small blocks were fixed in modified Karnovsky solution, postfixed in 1% buffered osmium tetroxide solution, and embedded in Spurr resin. For HRSEM, the parts were fixed in 2% osmium tetroxide solution with 1/15 M sodium phosphate buffer (pH 7.4) at 4 degrees C for 2 h, according to the technique described by Tanaka, 1989. Thick myelinated nerve bundles were histologically observed among the muscular fibers. The intrafusal nerve fiber presented a tortuous pathway with punctiform terminal axons in clusters contacting the surface of sarcolemma. Several myelinated nerve fibers involved by collagen fibers of the endoneurium were observed in HRSEM in three-dimensional aspects. The concentric lamellae of the myelin sheath and the axoplasm containing neurofilaments interspersed among the mitochondria were also noted. In TEM, myofibrils, mitochondria, rough endoplasmic reticulum, Golgi`s apparatus, and glycogen granules were observed in sarcoplasm. It is also noted that the sarcomeres constituted by myofilaments with their A, I, and H bands and the electron dense Z lines. In areas adjacent to muscular fibers, there were myelinated and unmyelinated nerve fibers involved by endoneurium and perineurium. In the region of the neuromuscular junction, the contact with the sarcolemma of the muscular cell occurs forming several terminal buttons and showing numerous evaginations of the cell membrane. In the terminal button, mitochondria and numerous synaptic vesicles were observed. Microsc. Res. Tech. 72:464-470, 2009. (C) 2009 Wiley-Liss. Inc.

Using clusters of computers for large QU-GENE simulation experiments

The QU-GENE Computing Cluster (QCC) is a hardware and software solution to the automation and speedup of large QU-GENE (QUantitative GENEtics) simulation experiments that are designed to examine the properties of genetic models, particularly those that involve factorial combinations of treatment levels. QCC automates the management of the distribution of components of the simulation experiments among the networked single-processor computers to achieve the speedup.

A zebrafish homologue of deleted in colorectal cancer (zdcc) is expressed in the first neuronal clusters of the developing brain

DCC (deleted in colon cancer), Neogenin and UNC-5 are all members of the immunoglobulin superfamily of transmembrane receptors which are believed to play a role in axon guidance by binding to their ligands, the Netrin/UNC-40 family of secreted molecules (Cell. Mol. Life Sci. 56 (1999) 62; Curr. Opin. Genet. Dev. 7 (1997) 87). Although zebrafish homologues of the Netrin family of secreted molecules have been reported, to date there has been no published description of zebrafish DCC homologues (Mol. Cell. Neurosci. 9 (1997) 293., Mol. Cell. Neurosci. I I ( 1998) 194; Mech. Dev. 62 (1997) 147). We report here the expression pattern of a zebrafish dcc (zdcc) homologue during the initial period of neurogenesis and axon tract formation within the developing central nervous system. Between 12 and 33 h post-fertilisation zdcc is expressed in a dynamic spatiotemporal pattern in all major subdivisions of the central nervous system. Double-labelling for zdcc and the post-mitotic neuronal marker HNK-1 revealed that subpopulations of neurons within the first nuclei of the zebrafish brain express zdcc. These results support our previous observation that patterning of neuronal clusters in the zebrafish brain occurs early in development (Dev. Bioi, 229 (2001) 271). (C) 2001 Elsevier Science Ireland Ltd. All rights reserved.

Working memory correlates of three symptom clusters in schizophrenia

This study was designed to examine whether discrete working memory deficits underlie positive, negative and disorganised symptoms of schizophrenia. Symptom dimension ratings were assigned to 52 outpatients with schizophrenia (ICD-10 criteria), using items drawn from the Positive and Negative Syndrome Scale (PANSS). Linear regression and correlational analyses were conducted to examine whether symptom dimension scores were related to performance on several tests of working memory function. Severity of negative symptoms correlated with reduced production of words during a verbal fluency task, impaired ability to hold letter and number sequences on-line and manipulate them Simultaneously, reduced performance during a dual task, and compromised visuospatial working memory under distraction-free conditions. Severity of disorganisation symptoms correlated with impaired visuospatial working memory under conditions of distraction, failure of inhibition during a verbal fluency task, perseverative responding on a test of set-shifting ability, and impaired ability to judge the veracity of simple declarative statements. Severity of positive symptoms was uncorrelated with performance on any of the measures examined. The present study provides evidence that the positive, negative and disorganised symptom dimensions of the PANSS constitute independent clusters, associated with unique patterns of working memory impairment. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.

Learning the dynamics of embedded clauses

Recent work by Siegelmann has shown that the computational power of recurrent neural networks matches that of Turing Machines. One important implication is that complex language classes (infinite languages with embedded clauses) can be represented in neural networks. Proofs are based on a fractal encoding of states to simulate the memory and operations of stacks. In the present work, it is shown that similar stack-like dynamics can be learned in recurrent neural networks from simple sequence prediction tasks. Two main types of network solutions are found and described qualitatively as dynamical systems: damped oscillation and entangled spiraling around fixed points. The potential and limitations of each solution type are established in terms of generalization on two different context-free languages. Both solution types constitute novel stack implementations - generally in line with Siegelmann's theoretical work - which supply insights into how embedded structures of languages can be handled in analog hardware.

A Wireless EEG Acquisition Platform based on Embedded Systems

This paper proposes a wireless EEG acquisition platform based on Open Multimedia Architecture Platform (OMAP) embedded system. A high-impedance active dry electrode was tested for improving the scalp- electrode interface. It was used the sigma-delta ADS1298 analog-to-digital converter, and developed a “kernelspace” character driver to manage the communications between the converter unit and the OMAP’s ARM core. The acquired EEG signal data is processed by a “userspace” application, which accesses the driver’s memory, saves the data to a SD-card and transmits them through a wireless TCP/IP-socket to a PC. The electrodes were tested through the alpha wave replacement phenomenon. The experimental results presented the expected alpha rhythm (8-13 Hz) reactiveness to the eyes opening task. The driver spends about 725 μs to acquire and store the data samples. The application takes about 244 μs to get the data from the driver and 1.4 ms to save it in the SD-card. A WiFi throughput of 12.8Mbps was measured which results in a transmission time of 5 ms for 512 kb of data. The embedded system consumes about 200 mAh when wireless off and 400 mAh when it is on. The system exhibits a reliable performance to record EEG signals and transmit them wirelessly. Besides the microcontroller-based architectures, the proposed platform demonstrates that powerful ARM processors running embedded operating systems can be programmed with real-time constrains at the kernel level in order to control hardware, while maintaining their parallel processing abilities in high level software applications.

Knowledge cities: a taxonomy for analyzing software and information service clusters

Software and information services (SIS) have become a field of increasing opportunities for international trade due to the worldwide diffusion of a combination of technological and organizational innovations. In several regions, the software industry is organized in clusters, usually referred to as "knowledge cities" because of the growing importance of knowledge-intensive services in their economy. This paper has two primary objectives. First, it raises three major questions related to the attractiveness of different cities in Argentina and Brazil for hosting software companies and to their impact on local development. Second, a new taxonomy is proposed for grouping clusters according to their dominant business segment, ownership pattern and scope of operations. The purpose of this taxonomy is to encourage further studies and provide an exploratory analytical tool for analyzing software clusters.

Clusters e APL's: análise bibliométrica das publicações nacionais no período de 2000 a 2011

O objetivo do presente estudo é analisar as publicações científicas sobre clusters e arranjos produtivos locais (APL's) no Brasil, no período de 2000 a 2011. Realizou-se a pesquisa em periódicos, classificados pela Qualis (Capes), das áreas de Administração, Economia e Engenharia, obtendo-se um total de 80 artigos. A análise permitiu identificar as características das publicações quanto às abordagens metodológicas e os métodos de pesquisa, os autores mais referenciados, os clusters e APL's pesquisados e os temas mais estudados. Verificou-se a tendência das pesquisas recentes de empregar abordagens teóricas com maior ênfase na questão da cooperação. Constatou-se que a pesquisa empírica, em geral, restringe-se a identificar a existência de clusters em determinadas localidades e a descrevê-los com base no tema de pesquisa escolhido. Portanto, existe uma oportunidade para avanço da pesquisa e para uma efetiva contribuição para o desenvolvimento da teoria.

Modelos de resposta à interação entre fármacos anestésicos : análise de regressão e análise de Clusters

Os avanços tecnológicos e científicos, na área da saúde, têm vindo a aliar áreas como a Medicina e a Matemática, cabendo à ciência adequar de forma mais eficaz os meios de investigação, diagnóstico, monitorização e terapêutica. Os métodos desenvolvidos e os estudos apresentados nesta dissertação resultam da necessidade de encontrar respostas e soluções para os diferentes desafios identificados na área da anestesia. A índole destes problemas conduz, necessariamente, à aplicação, adaptação e conjugação de diferentes métodos e modelos das diversas áreas da matemática. A capacidade para induzir a anestesia em pacientes, de forma segura e confiável, conduz a uma enorme variedade de situações que devem ser levadas em conta, exigindo, por isso, intensivos estudos. Assim, métodos e modelos de previsão, que permitam uma melhor personalização da dosagem a administrar ao paciente e por monitorizar, o efeito induzido pela administração de cada fármaco, com sinais mais fiáveis, são fundamentais para a investigação e progresso neste campo. Neste contexto, com o objetivo de clarificar a utilização em estudos na área da anestesia de um ajustado tratamento estatístico, proponho-me abordar diferentes análises estatísticas para desenvolver um modelo de previsão sobre a resposta cerebral a dois fármacos durante sedação. Dados obtidos de voluntários serão utilizados para estudar a interação farmacodinâmica entre dois fármacos anestésicos. Numa primeira fase são explorados modelos de regressão lineares que permitam modelar o efeito dos fármacos no sinal cerebral BIS (índice bispectral do EEG – indicador da profundidade de anestesia); ou seja estimar o efeito que as concentrações de fármacos têm na depressão do eletroencefalograma (avaliada pelo BIS). Na segunda fase deste trabalho, pretende-se a identificação de diferentes interações com Análise de Clusters bem como a validação do respetivo modelo com Análise Discriminante, identificando grupos homogéneos na amostra obtida através das técnicas de agrupamento. O número de grupos existentes na amostra foi, numa fase exploratória, obtido pelas técnicas de agrupamento hierárquicas, e a caracterização dos grupos identificados foi obtida pelas técnicas de agrupamento k-means. A reprodutibilidade dos modelos de agrupamento obtidos foi testada através da análise discriminante. As principais conclusões apontam que o teste de significância da equação de Regressão Linear indicou que o modelo é altamente significativo. As variáveis propofol e remifentanil influenciam significativamente o BIS e o modelo melhora com a inclusão do remifentanil. Este trabalho demonstra ainda ser possível construir um modelo que permite agrupar as concentrações dos fármacos, com base no efeito no sinal cerebral BIS, com o apoio de técnicas de agrupamento e discriminantes. Os resultados desmontram claramente a interacção farmacodinâmica dos dois fármacos, quando analisamos o Cluster 1 e o Cluster 3. Para concentrações semelhantes de propofol o efeito no BIS é claramente diferente dependendo da grandeza da concentração de remifentanil. Em suma, o estudo demostra claramente, que quando o remifentanil é administrado com o propofol (um hipnótico) o efeito deste último é potenciado, levando o sinal BIS a valores bastante baixos.

Simulation of defects in bubble clusters

Topological defects in foam, either isolated (disclinations and dislocations) or in pairs, affect the energy and stress, and play an important role in foam deformation. Surface Evolver simulations were performed on large finite clusters of bubbles. These allow us to evaluate the effect of the topology of the defects, and the distance between defects, on the energy and pressure of foam clusters of different sizes. The energy of such defects follows trends similar to known analytical results for a continuous medium.

Effect of the number of shells on the pressure and energy of two-dimensional free bubble clusters

We have performed Surface Evolver simulations of two-dimensional hexagonal bubble clusters consisting of a central bubble of area lambda surrounded by s shells or layers of bubbles of unit area. Clusters of up to twenty layers have been simulated, with lambda varying between 0.01 and 100. In monodisperse clusters (i.e., for lambda = 1) [M.A. Fortes, F Morgan, M. Fatima Vaz, Philos. Mag. Lett. 87 (2007) 561] both the average pressure of the entire Cluster and the pressure in the central bubble are decreasing functions of s and approach 0.9306 for very large s, which is the pressure in a bubble of an infinite monodisperse honeycomb foam. Here we address the effect of changing the central bubble area lambda. For small lambda the pressure in the central bubble and the average pressure were both found to decrease with s, as in monodisperse clusters. However, for large,, the pressure in the central bubble and the average pressure increase with s. The average pressure of large clusters was found to be independent of lambda and to approach 0.9306 asymptotically. We have also determined the cluster surface energies given by the equation of equilibrium for the total energy in terms of the area and the pressure in each bubble. When the pressures in the bubbles are not available, an approximate equation derived by Vaz et al. [M. Fatima Vaz, M.A. Fortes, F. Graner, Philos. Mag. Lett. 82 (2002) 575] was shown to provide good estimations for the cluster energy provided the bubble area distribution is narrow. This approach does not take cluster topology into account. Using this approximate equation, we find a good correlation between Surface Evolver Simulations and the estimated Values of energies and pressures. (C) 2008 Elsevier B.V. All rights reserved.

Análise de clusters e volatilidade de índices de acções

Mestrado em Contabilidade e Gestão das Instituições Financeiras