982 resultados para MAP kinase


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Raman spectroscopy on single, living epithelial cells captured in a laser trap is shown to have diagnostic power over colorectal cancer. This new single-cell technology comprises three major components: primary culture processing of human tissue samples to produce single-cell suspensions, Raman detection on singly trapped cells, and diagnoses of the cells by artificial neural network classifications. it is compared with DNA flow cytometry for similarities and differences. Its advantages over tissue Raman spectroscopy are also discussed. In the actual construction of a diagnostic model for colorectal cancer, real patient data were taken to generate a training set of 320 Raman spectra and, a test set of 80. By incorporating outlier corrections to a conventional binary neural classifier, our network accomplished significantly better predictions than logistic regressions, with sensitivity improved from 77.5% to 86.3% and specificity improved from 81.3% to 86.3% for the training set and moderate improvements for the test set. Most important, the network approach enables a sensitivity map analysis to quantitate the relevance of each Raman band to the normal-to-cancer transform at the cell level. Our technique has direct clinic applications for diagnosing cancers and basic science potential in the study of cell dynamics of carcinogenesis. (C) 2007 Society of Photo-Optical Instrumentation Engineers.

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A novel method to construct a quality map, called modulation-phase-gradient variance (MPGV), is proposed, based on modulation and the phase gradient. The MPGV map is successfully applied to two phase-unwrapping algorithms - the improved weighted least square and the quality-guided unwrapping algorithm. Both simulated and experimental data testify to the validity of our proposed quality map. Moreover, the unwrapped-phase results show that the new quality map can have higher reliability than the conventional phase-derivative variance quality map in helping to unwrap noisy, low-modulation, and/or discontinuous phase maps. (c) 2006 Society of Photo-Optical Instrumentation Engineers.

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A fast and reliable phase unwrapping (PhU) algorithm, based on the local quality-guided fitting plane, is presented. Its framework depends on the basic plane-approximated assumption for phase values of local pixels and on the phase derivative variance (PDV) quality map. Compared with other existing popular unwrapping algorithms, the proposed algorithm demonstrated improved robustness and immunity to strong noise and high phase variations, given that the plane assumption for local phase is reasonably satisfied. Its effectiveness is demonstrated by computer-simulated and experimental results.

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A novel method to construct a quality map, called modulation-phase-gradient variance (MPGV), is proposed, based on modulation and the phase gradient. The MPGV map is successfully applied to two phase-unwrapping algorithms - the improved weighted least square and the quality-guided unwrapping algorithm. Both simulated and experimental data testify to the validity of our proposed quality map. Moreover, the unwrapped-phase results show that the new quality map can have higher reliability than the conventional phase-derivative variance quality map in helping to unwrap noisy, low-modulation, and/or discontinuous phase maps. (c) 2006 Society of Photo-Optical Instrumentation Engineers.

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Among different phase unwrapping approaches, the weighted least-squares minimization methods are gaining attention. In these algorithms, weighting coefficient is generated from a quality map. The intrinsic drawbacks of existing quality maps constrain the application of these algorithms. They often fail to handle wrapped phase data contains error sources, such as phase discontinuities, noise and undersampling. In order to deal with those intractable wrapped phase data, a new weighted least-squares phase unwrapping algorithm based on derivative variance correlation map is proposed. In the algorithm, derivative variance correlation map, a novel quality map, can truly reflect wrapped phase quality, ensuring a more reliable unwrapped result. The definition of the derivative variance correlation map and the principle of the proposed algorithm are present in detail. The performance of the new algorithm has been tested by use of a simulated spherical surface wrapped data and an experimental interferometric synthetic aperture radar (IFSAR) wrapped data. Computer simulation and experimental results have verified that the proposed algorithm can work effectively even when a wrapped phase map contains intractable error sources. (c) 2006 Elsevier GmbH. All rights reserved.

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The notion of information processing has dominated the study of the mind for over six decades. However, before the advent of cognitivism, one of the most prominent theoretical ideas was that of Habit. This is a concept with a rich and complex history, which is again starting to awaken interest, following recent embodied, enactive critiques of computationalist frameworks. We offer here a very brief history of the concept of habit in the form of a genealogical network-map. This serves to provide an overview of the richness of this notion and as a guide for further re-appraisal. We identify 77 thinkers and their influences, and group them into seven schools of thought. Two major trends can be distinguished. One is the associationist trend, starting with the work of Locke and Hume, developed by Hartley, Bain, and Mill to be later absorbed into behaviorism through pioneering animal psychologists (Morgan and Thorndike). This tradition conceived of habits atomistically and as automatisms (a conception later debunked by cognitivism). Another historical trend we have called organicism inherits the legacy of Aristotle and develops along German idealism, French spiritualism, pragmatism, and phenomenology. It feeds into the work of continental psychologists in the early 20th century, influencing important figures such as Merleau-Ponty, Piaget, and Gibson. But it has not yet been taken up by mainstream cognitive neuroscience and psychology. Habits, in this tradition, are seen as ecological, self-organizing structures that relate to a web of predispositions and plastic dependencies both in the agent and in the environment. In addition, they are not conceptualized in opposition to rational, volitional processes, but as transversing a continuum from reflective to embodied intentionality. These are properties that make habit a particularly attractive idea for embodied, enactive perspectives, which can now re-evaluate it in light of dynamical systems theory and complexity research.

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O presente trabalho tem por finalidade realizar uma análise econômica dos possíveis impactos gerados na economia brasileira pelo Programa Nacional de Produção e Uso do Biodiesel (PNPB) e pela Lei N 11.097, que define percentuais mínimos obrigatórios de adição de biodiesel ao óleo diesel. Para atingir tal objetivo, apresenta-se uma avaliação econômica por meio do método de investigação conhecido como Matriz de Análise de Política (MAP). O emprego deste instrumental proporciona uma avaliação em termos de competitividade e eficiência do sistema de produção com base em um estudo comparativo da cadeia produtiva de biodiesel selecionando duas matérias-primas a soja e a mamona. Neste sentido, inicialmente investiga-se a cadeia produtiva do biodiesel no Brasil para diagnosticar as vantagens no que tange a escala de produção, a escolha de matérias-primas, bem como o custo de oportunidade, método de comercialização e distribuição e também a questão tributária. Os resultados da analise econômica revelaram que o emprego do óleo de soja para geração do biodiesel apresenta maior rentabilidade privada e social indicando ser mais competitivo e eficiente frente ao sistema produtivo que emprega o óleo de mamona. Os resultados da pesquisa evidenciando não apenas os aspectos econômicos como os sócio-ambientais favoráveis ao PNPB mostrando que o Brasil tem todas as condições para tornar-se um grande produtor de biodiesel.

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[EN] Protein Kinase G (PKG) or cGMP-dependent protein kinases (PKG) have been shown to play an important role in resistance to abiotic stressors such as high temperatures or oxygen deprivation in Drosophila melanogaster. In Drosophila, the foraging gene encodes a PKG; natural variants for this gene exist, which differ in the level of expression of PKG: rovers (forR allele) which express high PKG levels, and sitters (forS allele) which express lower PKG levels. This project explores the differences in recovery from short periods of anoxia between natural variants (focusing on forS2, flies with a sitter gene in a rover background), as well as mutants with insertions in the foraging gene and RNAi recombinants that show a reduced PKG expression. The parameters measured were time to recovery and level of activity after anoxia. The results showed lower activity after anoxia in sitters than in rovers, reflecting a worse recovery from the anoxic coma in flies with lower PKG levels.

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Adenylate Kinase (AK) is a signal transducing protein that regulates cellular energy homeostasis balancing between different conformations. An alteration of its activity can lead to severe pathologies such as heart failure, cancer and neurodegenerative diseases. A comprehensive elucidation of the large-scale conformational motions that rule the functional mechanism of this enzyme is of great value to guide rationally the development of new medications. Here using a metadynamics-based computational protocol we elucidate the thermodynamics and structural properties underlying the AK functional transitions. The free energy estimation of the conformational motions of the enzyme allows characterizing the sequence of events that regulate its action. We reveal the atomistic details of the most relevant enzyme states, identifying residues such as Arg119 and Lys13, which play a key role during the conformational transitions and represent druggable spots to design enzyme inhibitors. Our study offers tools that open new areas of investigation on large-scale motion in proteins.

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Historic map of the River Lune Fishery District.

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O presente trabalho realiza uma análise econômica dos possíveis impactos gerados na economia brasileira pelo Programa Nacional de Produção e Uso do Biodiesel (PNPB) e pela Lei N 11.097/2005, que define percentuais mínimos obrigatórios de adição de biodiesel ao óleo diesel. Para atingir tal objetivo, apresenta-se uma avaliação econômica por meio de um método de investigação conhecido como Matriz de Análise de Política (MAP). Este instrumental permite uma avaliação em termos de competitividade e eficiência do sistema produtivo de biodiesel com base em um estudo comparativo da cadeia produtiva de biodiesel selecionando duas matérias-primas a soja e a mamona. Neste sentido, inicialmente investiga-se a cadeia produtiva do biodiesel no Brasil para diagnosticar as vantagens no que tange a escala de produção, a escolha de matérias-primas, bem como o custo de oportunidade, método de comercialização e distribuição e também a questão tributária. Por fim são apresentados os resultados da pesquisa evidenciando que os dois sistemas são rentáveis, competitivos e eficientes, no entanto, maiores ganhos, em termos de uso dos recursos disponíveis e de custos de produção podem ser obtidos no sistema de produção do biodiesel a partir da soja. O lucro maior apresentado para a produção de biodiesel da soja permite confirmar a preferência por este sistema de produção dada sua maior rentabilidade.