Induction of CRP3/MLP expression during vein arterialization is dependent on stretch rather than shear stress

Aims Cysteine- and glycine-rich protein 3/muscle LIM-domain protein (CRP3/MLP) mediates protein-protein interaction with actin filaments in the heart and is involved in muscle differentiation and vascular remodelling. Here, we assessed the induction of CRP3/MLP expression during arterialization in human and rat veins. Methods and results Vascular CRP3/MLP expression was mainly observed in arterial samples from both human and rat. Using quantitative real time RT-PCR, we demonstrated that the CRP3/MLP expression was 10 times higher in smooth muscle cells (SMCs) from human mammary artery (h-MA) vs. saphenous vein (h-SV). In endothelial cells (ECs), CRP3/MLP was scarcely detected in either h-MA or h-SV. Using an ex vivo flow through system that mimics arterial condition, we observed induction of CRP3/MLP expression in arterialized h-SV. Interestingly, the upregulation of CRP3/MLP was primarily dependent on stretch stimulus in SMCs, rather than shear stress in ECs. Finally, using a rat vein in vivo arterialization model, early (1-14 days) CRP3/MLP immunostaining was observed predominantly in the inner layer and later (28-90 days) it appeared more scattered in the vessel layers. Conclusion Here we provide evidence that CRP3/MLP is primarily expressed in arterial SMCs and that stretch is the main stimulus for CRP3/MLP induction in veins exposed to arterial haemodynamic conditions.

Perinuclear Mlp proteins down-regulate gene expression in response to a defect in mRNA export

Résumé Une caractéristique des cellules eucaryotes est le confinement du matériel génétique (ADN/DNA) dans le noyau. Pour décoder cette information, un ARN messager (mRNA) est d'abord transcrit sous forme d'un ARN prémessager (pré-mRNA). Ce-dernier doit subir plusieurs étapes de maturation pour aboutir à une particule ribonucléoprotéique (mRNP) qui sera exportée vers le cytoplasme et traduite en protéine. La protéine de levure Mex67p et son homologue humain TAP sont des récepteurs d'export médiant la translocation du mRNP au travers des complexes du pore nucléaire (NPC). Mex67p/TAP ne se lient pas directement au mRNA, mais nécessitent la présence de protéines adaptatrices, telles que Yra1p et son homologue humain REF1. Afin d'identifier de nouveaux facteurs impliqués dans l'export des mRNPs ou de nouvelles fonctions pour Yra1p, nous avons effectué un crible génétique avec un mutant thermosensible de Yra1p, GFP-yra 1 -8. Ce mutant présente un défaut d'export des mRNAs et une diminution des niveaux de transcrits du gène rapporteur LacZ ainsi que de certains transcrits endogènes. Nous avons trouvé que la perte de Mlp2p, ou d'une protéine hautement similaire, Mlp1p, restaure la croissance du mutant GFP-yra1-8 à température restrictive. Mlp1p et Mlp2p sont des protéines nucléaires, dont l'homologue humain est TPR. Les Mlp (myosin¬like proteins) ainsi que TPR forment des structures filamenteuses ancrées aux NPC. Bien que la fonction des Mlp ne soit pas clairement définie, un rôle dans la biogenèse et la surveillance des mRNPs a été récemment proposé. Notre étude montre que la perte des Mlp, non seulement restaure la croissance de GFP-yra1-8, mais augmente aussi les niveaux des transcrits LacZ et facilite leur apparition dans le cytoplasme. Des expériences d'immunoprécipitations de la chromatine révèlent que Mlp2p diminue le taux de synthèse du transcrit LacZ dans GFP-yra1-8. Des analyses du transcriptome montrent que Mlp2p réduit aussi les niveaux d'une population de transcrits endogènes dans le mutant. Finalement, des localisations in situ suggèrent que la transcription du rapporteur LacZ a lieu à la périphérie du noyau, à proximité des Mlp. Ainsi, les protéines Mlp pourraient préférentiellement diminuer la transcription de gènes exprimés à la périphérie nucléaire. Nous montrons aussi que Yra1p interagit génétiquement avec Nab2p une protéine liée au mRNA et impliquée dans son export, mais non avec d'autres protéines également impliquées dans l'export des mRNAs. Les résultats obtenus soutiennent un modèle où les protéines Yra1p et Nab2p sont nécessaires à l'arrimage des mRNPs sur la plate-forme des Mlp. Si ces signaux manquent ou sont défectueux, les mRNPs ne peuvent pas poursuivre leur trajet vers le canal central du NPC. Ce bloc induirait par la suite une diminution de la transcription d'une population de gènes potentiellement localisée à la périphérie nucléaire. Dans son ensemble, cette étude suggère que les protéines Mlp établissent un lien entre la transcription de certains mRNAs et leur export au travers du pore nucléaire. Summary A hallmark of the eukaryotic cell is the packaging of DNA in the nucleus. To decode the genetic information, a messenger RNA (mRNA) is first synthesized as a pre-mRNA molecule, which undergoes different maturation steps resulting in an mRNP (messenger RNA ribonucleoprotein), which can be actively transported to the cytoplasm and translated into a protein. Yeast Mex67p and its human homologue TAP are export receptors mediating mRNP translocation through the nuclear pore complex (NPC). The recruitment of Mex67p/TAP to mRNA is mediated by mRNA export adaptors of the evolutionarily conserved REF (RNA and Export Factor binding) family: yeast Yra1p and human REF1. To uncover new functions of Yra1p or new factors implicated in mRNA export, we performed a genetic screen with a themiosensitive (ts) yra1 mutant, GFP-yra1-8. This mutant exhibits mRNA export defects and a decrease in the levels of LacZ reporter and certain endogenous transcripts. We found that the loss of Mlp2p, or the related Mlp1p protein, substantially rescues the growth defect of the GFP-yra1 -8 mutant. Mlp1p and M1p2p are large non-essential proteins, homologous to human TPR, proposed to form intra-nuclear filamentous structures anchored at the NPC. Their role is not clearly defined, but they have been implicated in mRNP biogenesis and surveillance. Our study shows that loss of Mlp proteins not only restores growth of GFP-yra1-8, but also rescues LacZ mRNA levels and increases their appearance in the cytoplasm. Chromatin immunoprecipitation and pulse chase experiments indicate that Mlp2p down-regulates LacZ mRNA synthesis in GFP-yra1-8. DNA micro- array analyses reveal that Mlp2p also reduces the levels of a subset of cellular transcripts in the yra1 mutant strain. In situ localizations suggest that LacZ transcription occurs at the nuclear periphery, in close proximity to Mlp proteins. Thus, Mlp proteins may preferentially down-regulate genes expressed at the nuclear periphery. Finally, we show that Yra1p genetically interacts with the shuttling mRNA-binding protein Nab2p and that loss of Mlp proteins rescues the growth defect of yra1 and nab2, but not other mRNA export mutants. The data support a model in which Nab2p and Yra1p are required for rnRNP docking to the Mlp platform. Lack of these signals prevents mRNPs from crossing the Mlp gate. This block may then negatively feed-back on the transcription of a subset of genes, potentially located at the nuclear envelope. Overall, this study suggests that perinuclear Mlp proteins establish a link between mRNA transcription and export.

Artificial keys for botanical identification using a multilayer perceptron neural network (MLP)

In this paper, practical generation of identification keys for biological taxa using a multilayer perceptron neural network is described. Unlike conventional expert systems, this method does not require an expert for key generation, but is merely based on recordings of observed character states. Like a human taxonomist, its judgement is based on experience, and it is therefore capable of generalized identification of taxa. An initial study involving identification of three species of Iris with greater than 90% confidence is presented here. In addition, the horticulturally significant genus Lithops (Aizoaceae/Mesembryanthemaceae), popular with enthusiasts of succulent plants, is used as a more practical example, because of the difficulty of generation of a conventional key to species, and the existence of a relatively recent monograph. It is demonstrated that such an Artificial Neural Network Key (ANNKEY) can identify more than half (52.9%) of the species in this genus, after training with representative data, even though data for one character is completely missing.

Detection of faults in a high speed packaging machine using a multilayer perceptron (MLP)

In high speed manufacturing systems, continuous operation is desirable, with minimal disruption for repairs and service. An intelligent diagnostic monitoring system, designed to detect developing faults before catastrophic failure, or prior to undesirable reduction in output quality, is a good means of achieving this. Artificial neural networks have already been found to be of value in fault diagnosis of machinery. The aim here is to provide a system capable of detecting a number of faults, in order that maintenance can be scheduled in advance of sudden failure, and to reduce the necessity to replace parts at intervals based on mean time between failures. Instead, parts will need to be replaced only when necessary. Analysis of control information in the form of position error data from two servomotors is described.

Otimização de superfícies seletivas de frequência com elementos pré-fractais utilizando rede neural MLP e algoritmos de busca populacional

This thesis describes design methodologies for frequency selective surfaces (FSSs) composed of periodic arrays of pre-fractals metallic patches on single-layer dielectrics (FR4, RT/duroid). Shapes presented by Sierpinski island and T fractal geometries are exploited to the simple design of efficient band-stop spatial filters with applications in the range of microwaves. Initial results are discussed in terms of the electromagnetic effect resulting from the variation of parameters such as, fractal iteration number (or fractal level), fractal iteration factor, and periodicity of FSS, depending on the used pre-fractal element (Sierpinski island or T fractal). The transmission properties of these proposed periodic arrays are investigated through simulations performed by Ansoft DesignerTM and Ansoft HFSSTM commercial softwares that run full-wave methods. To validate the employed methodology, FSS prototypes are selected for fabrication and measurement. The obtained results point to interesting features for FSS spatial filters: compactness, with high values of frequency compression factor; as well as stable frequency responses at oblique incidence of plane waves. This thesis also approaches, as it main focus, the application of an alternative electromagnetic (EM) optimization technique for analysis and synthesis of FSSs with fractal motifs. In application examples of this technique, Vicsek and Sierpinski pre-fractal elements are used in the optimal design of FSS structures. Based on computational intelligence tools, the proposed technique overcomes the high computational cost associated to the full-wave parametric analyzes. To this end, fast and accurate multilayer perceptron (MLP) neural network models are developed using different parameters as design input variables. These neural network models aim to calculate the cost function in the iterations of population-based search algorithms. Continuous genetic algorithm (GA), particle swarm optimization (PSO), and bees algorithm (BA) are used for FSSs optimization with specific resonant frequency and bandwidth. The performance of these algorithms is compared in terms of computational cost and numerical convergence. Consistent results can be verified by the excellent agreement obtained between simulations and measurements related to FSS prototypes built with a given fractal iteration

Método experimental para determinação das capacitancias parasitas do motor de indução trifásico acionado por inversor MLP

A proposta deste trabalho é apresentar uma nova metodologia para determinação experimental das capacitancias parasitas do motor de indução trifásico de rotor em gaiola. As capacitancias parasitas fazem parte do circuito equivalente do motor para estudos de interferência eletromagnética causada no motor de indução em modo comum quando ele for acionado por inversor controlado por modulação por largura de pulsos (MLP). Os procedimentos propostos para o desenvolvimento deste novo método consistem em: a) determinação dos parâmetros do circuito equivalente do motor de indução trifásico, em regime permanente, através de ensaio em laboratório; b) estabelecer configurações de ligações entre o inversor MLP e o motor para medições das grandezas de interesse que são as seguintes: tensões de modo comum e de eixo, correntes de fuga e de eixo, através de circuito de medição desenvolvido para este fim; c) calcular os valores das capacitancias parasitas entre estator e carcaça do motor; estator e rotor; rotor e carcaça e de rolamento utilizando a expressão matemática da definição de capacitancia; d) utilizar o software Pspice para simular o sistema motor de indução trifásico, alimentado por inversor MLP, com os circuitos equivalentes em baixas e altas frequências; e) obter as formas de onda características do fenômeno de modo comum.

Avaliação estatística de métodos de poda aplicados em neurônios intermediários da rede neural MLP

There are several papers on pruning methods in the artificial neural networks area. However, with rare exceptions, none of them presents an appropriate statistical evaluation of such methods. In this article, we proved statistically the ability of some methods to reduce the number of neurons of the hidden layer of a multilayer perceptron neural network (MLP), and to maintain the same landing of classification error of the initial net. They are evaluated seven pruning methods. The experimental investigation was accomplished on five groups of generated data and in two groups of real data. Three variables were accompanied in the study: apparent classification error rate in the test group (REA); number of hidden neurons, obtained after the application of the pruning method; and number of training/retraining epochs, to evaluate the computational effort. The non-parametric Friedman's test was used to do the statistical analysis.

Application of MLP and Kohonen networks for recognition of wear patterns of single-point dressers

Grinding is a parts finishing process for advanced products and surfaces. However, continuous friction between the workpiece and the grinding wheel causes the latter to lose its sharpness, thus impairing the grinding results. This is when the dressing process is required, which consists of sharpening the worn grains of the grinding wheel. The dressing conditions strongly affect the performance of the grinding operation; hence, monitoring them throughout the process can increase its efficiency. The objective of this study was to estimate the wear of a single-point dresser using intelligent systems whose inputs were obtained by the digital processing of acoustic emission signals. Two intelligent systems, the multilayer perceptron and the Kohonen neural network, were compared in terms of their classifying ability. The harmonic content of the acoustic emission signal was found to be influenced by the condition of dresser, and when used to feed the neural networks it is possible to classify the condition of the tool under study.

O uso de rede neural artificial MLP na predição de estruturas secundárias de proteínas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Aplicação da rede neural MLP (Multilayer Perceptron) em indústria de pisos e revestimentos do Pólo Cerâmico de Santa Gertrudes - SP

Pós-graduação em Geociências e Meio Ambiente - IGCE

Comparação dos algoritmos C4.5 e MLP usados na avaliação da segurança dinâmica e no auxílio ao controle preventivo no contexto da estabilidade transitória de sistemas de potência

Esse trabalho compara os algoritmos C4.5 e MLP (do inglês “Multilayer Perceptron”) aplicados a avaliação de segurança dinâmica ou (DSA, do inglês “Dynamic Security Assessment”) e em projetos de controle preventivo, com foco na estabilidade transitória de sistemas elétricos de potência (SEPs). O C4.5 é um dos algoritmos da árvore de decisão ou (DT, do inglês “Decision Tree”) e a MLP é um dos membros da família das redes neurais artificiais (RNA). Ambos os algoritmos fornecem soluções para o problema da DSA em tempo real, identificando rapidamente quando um SEP está sujeito a uma perturbação crítica (curto-circuito, por exemplo) que pode levar para a instabilidade transitória. Além disso, o conhecimento obtido de ambas as técnicas, na forma de regras, pode ser utilizado em projetos de controle preventivo para restaurar a segurança do SEP contra perturbações críticas. Baseado na formação de base de dados com exaustivas simulações no domínio do tempo, algumas perturbações críticas específicas são tomadas como exemplo para comparar os algoritmos C4.5 e MLP empregadas a DSA e ao auxílio de ações preventivas. O estudo comparativo é testado no sistema elétrico “New England”. Nos estudos de caso, a base de dados é gerada por meio do programa PSTv3 (“Power System Toolbox”). As DTs e as RNAs são treinada e testadas usando o programa Rapidminer. Os resultados obtidos demonstram que os algoritmos C4.5 e MLP são promissores nas aplicações de DSA e em projetos de controle preventivo.

Pruning methods to MLP neural networks considering proportional apparent error rate for classification problems with unbalanced data

This article deals with classification problems involving unequal probabilities in each class and discusses metrics to systems that use multilayer perceptrons neural networks (MLP) for the task of classifying new patterns. In addition we propose three new pruning methods that were compared to other seven existing methods in the literature for MLP networks. All pruning algorithms presented in this paper have been modified by the authors to do pruning of neurons, in order to produce fully connected MLP networks but being small in its intermediary layer. Experiments were carried out involving the E. coli unbalanced classification problem and ten pruning methods. The proposed methods had obtained good results, actually, better results than another pruning methods previously defined at the MLP neural network area. (C) 2014 Elsevier Ltd. All rights reserved.

Comparative study between powers of sigmoid functions, MLP-backpropagation and polynomials in function approximation problems

Function approximation is a very important task in environments where the computation has to be based on extracting information from data samples in real world processes. So, the development of new mathematical model is a very important activity to guarantee the evolution of the function approximation area. In this sense, we will present the Polynomials Powers of Sigmoid (PPS) as a linear neural network. In this paper, we will introduce one series of practical results for the Polynomials Powers of Sigmoid, where we will show some advantages of the use of the powers of sigmiod functions in relationship the traditional MLP-Backpropagation and Polynomials in functions approximation problems.