Gene expression regulation and lineage evolution: the North and South tale of the hybrid polyploid Squalius alburnoides complex

The evolution of hybrid polyploid vertebrates, their viability and their perpetuation over evolutionary time have always been questions of great interest. However, little is known about the impact of hybridization and polyploidization on the regulatory networks that guarantee the appropriate quantitative and qualitative gene expression programme. The Squalius alburnoides complex of hybrid fish is an attractive system to address these questions, as it includes a wide variety of diploid and polyploid forms, and intricate systems of genetic exchange. Through the study of genome-specific allele expression of seven housekeeping and tissue-specific genes, we found that a gene copy silencing mechanism of dosage compensation exists throughout the distribution range of the complex. Here we show that the allele-specific patterns of silencing vary within the complex, according to the geographical origin and the type of genome involved in the hybridization process. In southern populations, triploids of S. alburnoides show an overall tendency for silencing the allele from the minority genome, while northern population polyploids exhibit preferential biallelic gene expression patterns, irrespective of genomic composition. The present findings further suggest that gene copy silencing and variable expression of specific allele combinations may be important processes in vertebrate polyploid evolution.

Polimorfismos genéticos no gene XRCC3 e dano no DNA em trabalhadores expostos ocupacionalmente a formaldeído

A exposição a formaldeído (FA), classificado como cancerígeno pela International Agency for Cancer Research (IARC), está epidemiologicamente associada a cancro e a alterações nucleares detectáveis pelo ensaio dos micronúcleos por bloqueio da citocinese (CBMN). Este método permite determinar vários marcadores de genotoxicidade, nomeadamente micronúcleos – biomarcadores de quebra ou perda de cromossomas; pontes nucleoplásmicas – biomarcador de re-arranjo cromossómico, pouca reparação e fusão de telómeros e, protusões nucleares – biomarcador de DNA amplificado. O gene X-ray repair cross-complementing group 3 (XRCC3) está envolvido na reparação de ligações cruzadas na recombinação de homólogos e quebras na cadeia dupla de DNA. Foi reportado pelo menos um polimorfismo no gene, o Thr241Met que tem sido associado a um aumento do dnao no DNA em vários estudos.

Application of neural networks for pavement evaluation

As vias de comunicação são indispensáveis para o desenvolvimento de uma nação, económica e socialmente. Num mundo globalizado, onde tudo deve chegar ao seu destino no menor espaço de tempo, as vias de comunicação assumem um papel vital. Assim, torna-se essencial construir e manter uma rede de transportes eficiente. Apesar de não ser o método mais eficiente, o transporte rodoviário é muitas vezes o mais económico e possibilita o transporte porta-a-porta, sendo em muitos casos o único meio de transporte possível. Por estas razões, o modo rodoviário tem uma quota significativa no mercado dos transportes, seja de passageiros ou mercadorias, tornando-o extremamente importante na rede de transportes de um país. Os países europeus fizeram um grande investimento na criação de extensas redes de estradas, cobrindo quase todo o seu território. Neste momento, começa-se a atingir o ponto onde a principal preocu+ação das entidades gestoras de estradas deixa de ser a construção de novas vias, passando a focar-se na necessidade de manutenção e conservação das vias existentes. Os pavimentos rodoviários, como todas as outras construções, requerem manutenção de forma a garantir bons níveis de serviço com qualidade, conforto e segurança. Devido aos custos inerentes às operações de manutenção de pavimentos, estas devem rigorosamente e com base em critérios científicos bem definidos. Assim, pretende-se evitar intervenções desnecessárias, mas também impedir que os danos se tornem irreparáveis e economicamente prejudiciais, com repercussões na segurança dos utilizadores. Para se estimar a vida útil de um pavimento é essencial realizar primeiro a caracterização estrutural do mesmo. Para isso, torna-se necessário conhecer o tipo de estrutura de um pavimento, nomeadamente a espessura e o módulo de elasticidade constituintes. A utilização de métodos de ensaio não destrutivos é cada vez mais reconhecida como uma forma eficaz para obter informações sobre o comportamento estrutural de pavimentos. Para efectuar estes ensaios, existem vários equipamentos. No entanto, dois deles, o Deflectómetro de Impacto e o Radar de Prospecção, têm demonstrado ser particularmente eficientes para avaliação da capacidade de carga de um pavimento, sendo estes equipamentos utilizados no âmbito deste estudo. Assim, para realização de ensaios de carga em pavimentos, o equipamento Deflectómetro de Impacto tem sido utilizado com sucesso para medir as deflexões à superfície de um pavimento em pontos pré-determinados quando sujeito a uma carga normalizada de forma a simular o efeito da passagem da roda de um camião. Complementarmente, para a obtenção de informações contínuas sobre a estrutura de um pavimento, o equipamento Radar de Prospecção permite conhecer o número de camadas e as suas espessuras através da utilização de ondas electromagnéticas. Os dados proporcionam, quando usados em conjunto com a realização de sondagens à rotação e poços em alguns locais, permitem uma caracterização mais precisa da condição estrutural de um pavimento e o estabelecimento de modelos de resposta, no caso de pavimentos existentes. Por outro lado, o processamento dos dados obtidos durante os ensaios “in situ” revela-se uma tarefa morosa e complexa. Actualmente, utilizando as espessuras das camadas do pavimento, os módulos de elasticidade das camadas são calculados através da “retro-análise” da bacia de deflexões medida nos ensaios de carga. Este método é iterativo, sendo que um engenheiro experiente testa várias estruturas diferentes de pavimento, até se obter uma estrutura cuja resposta seja o mais próximo possível da obtida durante os ensaios “in Situ”. Esta tarefa revela-se muito dependente da experiência do engenheiro, uma vez que as estruturas de pavimento a serem testadas maioritariamente do seu raciocínio. Outra desvantagem deste método é o facto de apresentar soluções múltiplas, dado que diferentes estruturas podem apresentar modelos de resposta iguais. A solução aceite é, muitas vezes, a que se julga mais provável, baseando-se novamente no raciocínio e experiência do engenheiro. A solução para o problema da enorme quantidade de dados a processar e das múltiplas soluções possíveis poderá ser a utilização de Redes Neuronais Artificiais (RNA) para auxiliar esta tarefa. As redes neuronais são elementos computacionais virtuais, cujo funcionamento é inspirado na forma como os sistemas nervosos biológicos, como o cérebro, processam a informação. Estes elementos são compostos por uma série de camadas, que por sua vez são compostas por neurónios. Durante a transmissão da informação entre neurónios, esta é modificada pela aplicação de um coeficiente, denominado “peso”. As redes neuronais apresentam uma habilidade muito útil, uma vez que são capazes de mapear uma função sem conhecer a sua fórmula matemática. Esta habilidade é utilizada em vários campos científicos como o reconhecimento de padrões, classificação ou compactação de dados. De forma a possibilitar o uso desta característica, a rede deverá ser devidamente “treinada” antes, processo realizado através da introdução de dois conjuntos de dados: os valores de entrada e os valores de saída pretendidos. Através de um processo cíclico de propagação da informação através das ligações entre neurónios, as redes ajustam-se gradualmente, apresentando melhores resultados. Apesar de existirem vários tipos de redes, as que aparentam ser as mais aptas para esta tarefa são as redes de retro-propagação. Estas possuem uma característica importante, nomeadamente o treino denominado “treino supervisionado”. Devido a este método de treino, as redes funcionam dentro da gama de variação dos dados fornecidos para o “treino” e, consequentemente, os resultados calculados também se encontram dentro da mesma gama, impedindo o aparecimento de soluções matemáticas com impossibilidade prática. De forma a tornar esta tarefa ainda mais simples, foi desenvolvido um programa de computador, NNPav, utilizando as RNA como parte integrante do seu processo de cálculo. O objectivo é tornar o processo de “retro-análise” totalmente automático e prevenir erros induzidos pela falta de experiência do utilizador. De forma a expandir ainda mais as funcionalidades do programa, foi implementado um processo de cálculo que realiza uma estimativa da capacidade de carga e da vida útil restante do pavimento, recorrendo a dois critérios de ruína. Estes critérios são normalmente utilizados no dimensionamento de pavimentos, de forma a prevenir o fendilhamento por fadiga e as deformações permanentes. Desta forma, o programa criado permite a estimativa da vida útil restante de um pavimento de forma eficiente, directamente a partir das deflexões e espessuras das camadas, medidas nos ensaios “in situ”. Todos os passos da caracterização estrutural do pavimento são efectuados pelo NNPav, seja recorrendo à utilização de redes neuronais ou a processos de cálculo matemático, incluindo a correcção do módulo de elasticidade da camada de misturas betuminosas para a temperatura de projecto e considerando as características de tráfego e taxas de crescimento do mesmo. Os testes efectuados às redes neuronais revelaram que foram alcançados resultados satisfatórios. Os níveis de erros na utilização de redes neuronais são semelhantes aos obtidos usando modelos de camadas linear-elásticas, excepto para o cálculo da vida útil com base num dos critérios, onde os erros obtidos foram mais altos. No entanto, este processo revela-se bastante mais rápido e possibilita o processamento dos dados por pessoal com menos experiência. Ao mesmo tempo, foi assegurado que nos ficheiros de resultados é possível analisar todos os dados calculados pelo programa, em várias fases de processamento de forma a permitir a análise detalhada dos mesmos. A possibilidade de estimar a capacidade de carga e a vida útil restante de um pavimento, contempladas no programa desenvolvido, representam também ferramentas importantes. Basicamente, o NNPav permite uma análise estrutural completa de um pavimento, estimando a sua vida útil com base nos ensaios de campo realizados pelo Deflectómetro de Impacto e pelo Radar de Prospecção, num único passo. Complementarmente, foi ainda desenvolvido e implementado no NNPav um módulo destinado ao dimensionamento de pavimentos novos. Este módulo permite que, dado um conjunto de estruturas de pavimento possíveis, seja estimada a capacidade de carga e a vida útil daquele pavimento. Este facto permite a análise de uma grande quantidade de estruturas de pavimento, e a fácil comparação dos resultados no ficheiro exportado. Apesar dos resultados obtidos neste trabalho serem bastante satisfatórios, os desenvolvimentos futuros na aplicação de Redes Neuronais na avaliação de pavimentos são ainda mais promissores. Uma vez que este trabalho foi limitado a uma moldura temporal inerente a um trabalho académico, a possibilidade de melhorar ainda mais a resposta das RNA fica em aberto. Apesar dos vários testes realizados às redes, de forma a obter as arquitecturas que apresentassem melhores resultados, as arquitecturas possíveis são virtualmente ilimitadas e pode ser uma área a aprofundar. As funcionalidades implementadas no programa foram as possíveis, dentro da moldura temporal referida, mas existem muitas funcionalidades a serem adicinadas ou expandidas, aumentando a funcionalidade do programa e a sua produtividade. Uma vez que esta é uma ferramenta que pode ser aplicada ao nível de gestão de redes rodoviárias, seria necessário estudar e desenvolver redes similares de forma a avaliar outros tipos de estruturas de pavimentos. Como conclusão final, apesar dos vários aspectos que podem, e devem ser melhorados, o programa desenvolvido provou ser uma ferramenta bastante útil e eficiente na avaliação estrutural de pavimentos com base em métodos de ensaio não destrutivos.

Elements of a methodology to assess the alignment of core-values in collaborative networks

Collaborative networks are typically formed by heterogeneous and autonomous entities, and thus it is natural that each member has its own set of core-values. Since these values somehow drive the behaviour of the involved entities, the ability to quickly identify partners with compatible or common core-values represents an important element for the success of collaborative networks. However, tools to assess or measure the level of alignment of core-values are lacking. Since the concept of 'alignment' in this context is still ill-defined and shows a multifaceted nature, three perspectives are discussed. The first one uses a causal maps approach in order to capture, structure, and represent the influence relationships among core-values. This representation provides the basis to measure the alignment in terms of the structural similarity and influence among value systems. The second perspective considers the compatibility and incompatibility among core-values in order to define the alignment level. Under this perspective we propose a fuzzy inference system to estimate the alignment level, since this approach allows dealing with variables that are vaguely defined, and whose inter-relationships are difficult to define. Another advantage provided by this method is the possibility to incorporate expert human judgment in the definition of the alignment level. The last perspective uses a belief Bayesian network method, and was selected in order to assess the alignment level based on members' past behaviour. An example of application is presented where the details of each method are discussed.

A Service Integration Platform for Collaborative Networks

Integrated manufacturing constitutes a complex system made of heterogeneous information and control subsystems. Those subsystems are not designed to the cooperation. Typically each subsystem automates specific processes, and establishes closed application domains, therefore it is very difficult to integrate it with other subsystems in order to respond to the needed process dynamics. Furthermore, to cope with ever growing marketcompetition and demands, it is necessary for manufacturing/enterprise systems to increase their responsiveness based on up-to-date knowledge and in-time data gathered from the diverse information and control systems. These have created new challenges for manufacturing sector, and even bigger challenges for collaborative manufacturing. The growing complexity of the information and communication technologies when coping with innovative business services based on collaborative contributions from multiple stakeholders, requires novel and multidisciplinary approaches. Service orientation is a strategic approach to deal with such complexity, and various stakeholders' information systems. Services or more precisely the autonomous computational agents implementing the services, provide an architectural pattern able to cope with the needs of integrated and distributed collaborative solutions. This paper proposes a service-oriented framework, aiming to support a virtual organizations breeding environment that is the basis for establishing short or long term goal-oriented virtual organizations. The notion of integrated business services, where customers receive some value developed through the contribution from a network of companies is a key element.

Short-term wind power forecasting in Portugal by neural networks and wavelet transform

This paper proposes artificial neural networks in combination with wavelet transform for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. Results from a real-world case study are presented. A comparison is carried out, taking into account the results obtained with other approaches. Finally, conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.

Symbolic Knowledge Extraction from Trained Neural Networks Governed by Lukasiewicz Logics

This work describes a methodology to extract symbolic rules from trained neural networks. In our approach, patterns on the network are codified using formulas on a Lukasiewicz logic. For this we take advantage of the fact that every connective in this multi-valued logic can be evaluated by a neuron in an artificial network having, by activation function the identity truncated to zero and one. This fact simplifies symbolic rule extraction and allows the easy injection of formulas into a network architecture. We trained this type of neural network using a back-propagation algorithm based on Levenderg-Marquardt algorithm, where in each learning iteration, we restricted the knowledge dissemination in the network structure. This makes the descriptive power of produced neural networks similar to the descriptive power of Lukasiewicz logic language, minimizing the information loss on the translation between connectionist and symbolic structures. To avoid redundance on the generated network, the method simplifies them in a pruning phase, using the "Optimal Brain Surgeon" algorithm. We tested this method on the task of finding the formula used on the generation of a given truth table. For real data tests, we selected the Mushrooms data set, available on the UCI Machine Learning Repository.

Non-coding RNAs: multi-tasking molecules in the cell

In the last years it has become increasingly clear that the mammalian transcriptome is highly complex and includes a large number of small non-coding RNAs (sncRNAs) and long noncoding RNAs (lncRNAs). Here we review the biogenesis pathways of the three classes of sncRNAs, namely short interfering RNAs (siRNAs), microRNAs (miRNAs) and PIWI-interacting RNAs (piRNAs). These ncRNAs have been extensively studied and are involved in pathways leading to specific gene silencing and the protection of genomes against virus and transposons, for example. Also, lncRNAs have emerged as pivotal molecules for the transcriptional and post-transcriptional regulation of gene expression which is supported by their tissue-specific expression patterns, subcellular distribution, and developmental regulation. Therefore, we also focus our attention on their role in differentiation and development. SncRNAs and lncRNAs play critical roles in defining DNA methylation patterns, as well as chromatin remodeling thus having a substantial effect in epigenetics. The identification of some overlaps in their biogenesis pathways and functional roles raises the hypothesis that these molecules play concerted functions in vivo, creating complex regulatory networks where cooperation with regulatory proteins is necessary. We also highlighted the implications of biogenesis and gene expression deregulation of sncRNAs and lncRNAs in human diseases like cancer.

A model for heterogeneous networks management and Performance evaluation

In general, modern networks are analysed by taking several Key Performance Indicators (KPIs) into account, their proper balance being required in order to guarantee a desired Quality of Service (QoS), particularly, cellular wireless heterogeneous networks. A model to integrate a set of KPIs into a single one is presented, by using a Cost Function that includes these KPIs, providing for each network node a single evaluation parameter as output, and reflecting network conditions and common radio resource management strategies performance. The proposed model enables the implementation of different network management policies, by manipulating KPIs according to users' or operators' perspectives, allowing for a better QoS. Results show that different policies can in fact be established, with a different impact on the network, e.g., with median values ranging by a factor higher than two.

Distributed process execution in collaborative networks

Processes are a central entity in enterprise collaboration. Collaborative processes need to be executed and coordinated in a distributed Computational platform where computers are connected through heterogeneous networks and systems. Life cycle management of such collaborative processes requires a framework able to handle their diversity based on different computational and communication requirements. This paper proposes a rational for such framework, points out key requirements and proposes it strategy for a supporting technological infrastructure. Beyond the portability of collaborative process definitions among different technological bindings, a framework to handle different life cycle phases of those definitions is presented and discussed. (c) 2007 Elsevier Ltd. All rights reserved.

FMRI 3D registration based on Fourier space subsets using neural networks

In this work, we present a neural network (NN) based method designed for 3D rigid-body registration of FMRI time series, which relies on a limited number of Fourier coefficients of the images to be aligned. These coefficients, which are comprised in a small cubic neighborhood located at the first octant of a 3D Fourier space (including the DC component), are then fed into six NN during the learning stage. Each NN yields the estimates of a registration parameter. The proposed method was assessed for 3D rigid-body transformations, using DC neighborhoods of different sizes. The mean absolute registration errors are of approximately 0.030 mm in translations and 0.030 deg in rotations, for the typical motion amplitudes encountered in FMRI studies. The construction of the training set and the learning stage are fast requiring, respectively, 90 s and 1 to 12 s, depending on the number of input and hidden units of the NN. We believe that NN-based approaches to the problem of FMRI registration can be of great interest in the future. For instance, NN relying on limited K-space data (possibly in navigation echoes) can be a valid solution to the problem of prospective (in frame) FMRI registration.

Regulation of antioxidant enzymes gene expression in the yeast Saccharomyces cerevisiae during stationary phase

Gene expression of three antioxidant enzymes, Mn superoxide dismutase (MnSOD), Cu,Zn superoxide dismutase (Cu,ZnSOD), and glutathione reductase (GR) was investigated in stationary phase Saccharomyces cerevisiae during menadione-induced oxidative stress. Both GR and Cu,ZnSOD mRNA steady state levels increased, reaching a plateau at about 90 min exposure to menadione. GR mRNA induction was higher than that of Cu,ZnSOD (about 14-fold and 9-fold after 90 min, respectively). A different pattern of response was obtained for MnSOD mRNA, with a peak at about 15 min (about 8-fold higher) followed by a decrease to a plateau approximately 4-fold higher than the control value. However, these increased mRNA levels did not result in increased protein levels and activities of these enzymes. Furthermore, exposure to menadione decreased MnSOD activity to half its value, indicating that the enzyme is partially inactivated due to oxidative damage. Cu,ZnSOD protein levels were increased 2-fold, but MnSOD protein levels were unchanged after exposure to menadione in the presence of the proteolysis inhibitor phenylmethylsulfonyl fluoride. These results indicate that the rates of Cu,ZnSOD synthesis and proteolysis are increased, while the rates of MnSOD synthesis and proteolysis are unchanged by exposure to menadione. Also, the translational efficiency for both enzymes is probably decreased, since increases in protein levels when proteolysis is inhibited do not reflect the increases in mRNA levels. Our results indicate that oxidative stress modifies MnSOD, Cu,ZnSOD, and GR gene expression in a complex way, not only at the transcription level but also at the post-transcriptional, translational, and post-translational levels.

Tubulin cofactor A gene silencing in mammalian cells induces changes in microtubule cytoskeleton, cell cycle arrest and cell death

Microtubules are polymers of alpha/beta-tubulin participating in essential cell functions. A multistep process involving distinct molecular chaperones and cofactors produces new tubulin heterodimers competent to polymerise. In vitro cofactor A (TBCA) interacts with beta-tubulin in a quasi-native state behaving as a molecular chaperone. We have used siRNA to silence TBCA expression in HeLa and MCF-7 mammalian cell lines. TBCA is essential for cell viability and its knockdown produces a decrease in the amount of soluble tubulin, modifications in microtubules and G1 cell cycle arrest. In MCF-7 cells, cell death was preceded by a change in cell shape resembling differentiation.

Q192R polymorphism of the paraoxonase-1 gene as a risk factor for obesity in Portuguese women

Introduction - Obesity became a major public health problem as a result of its increasing prevalence worldwide. Paraoxonase-1 (PON1) is an esterase able to protect membranes and lipoproteins from oxidative modifications. At the PON1 gene, several polymorphisms in the promoter and coding regions have been identified. The aims of this study were i) to assess PON1 L55M and Q192R polymorphisms as a risk factor for obesity in women; ii) to compare PON1 activity according to the expression of each allele in L55M and Q192R polymorphisms; iii) to compare PON1 activity between obese and normal-weight women. Materials and methods - We studied 75 healthy (35.9±8.2 years) and 81 obese women (34.3±8.2 years). Inclusion criteria for obese subjects were body mass index ≥30 kg/m2 and absence of inflammatory/neoplasic conditions or kidney/hepatic dysfunction. The two PON1 polymorphisms were assessed by real-time PCR with TaqMan probes. PON1 enzymatic activity was assessed by spectrophotometric methods, using paraoxon as a substrate. Results - No significant differences were found for PON1 activity between normal and obese women. Nevertheless, PON1 activity was greater (P<0.01) for the RR genotype (in Q192R polymorphism) and for the LL genotype (in L55M polymorphism). The frequency of allele R of Q192R polymorphism was significantly higher in obese women (P<0.05) and was associated with an increased risk of obesity (odds ratio=2.0 – 95% confidence interval (1.04; 3.87)). Conclusion - 55M and Q192R polymorphisms influence PON1 activity. The allele R of the Q192R polymorphism is associated with an increased risk for development of obesity among Portuguese Caucasian premenopausal women.

Relationship of PON1 192 and 55 gene polymorphisms to calcific valvular aortic stenosis

Introduction and Objectives - Paraoxonases may exert anti-atherogenic action by reducing lipid peroxidation. Previous studies examined associations between polymorphisms in the paraoxonase 1 (PON1) gene and development of coronary artery disease (CAD), with inconsistent results. Given the similarities in clinical and pathophysiological risk factors of CAD and calcific aortic valve stenosis (CAVS), we postulated a link between PON1 alleles and CAVS progression. Methods - We investigated the association between PON1 55 and 192 single nucleotide polymorphisms (SNPs), their enzyme activity, and CAVS progression assessed by aortic valve area and transvalvular peak velocity in 67 consecutive patients with moderate CAVS and 251 healthy controls. Results - PON1 paraoxonase activity was higher in CAVS patients (P<0.001). The PON1 genotype Q192R SNP (P=0.03) and variant allele (R192) (P=0.01) frequencies differed between CAVS patients and controls. Significant association existed between PON1 enzyme activity, phenotypic effects of PON1 192 genotype polymorphisms, and CAVS progression, but not between PON1 55 and high-density lipoprotein (P=0.44) or low-density lipoprotein cholesterol (P=0.12), between 192 genotype and high-density lipoprotein (P=0.24) or low-density lipoprotein cholesterol (P=0.52). Conclusion - The PON1 genotype Q192R SNP has an important effect on CAVS disease progression. This study helps outline a genotype-phenotype relationship for PON1 in this unique population.