42 resultados para Plots (Drama, novel, etc.)


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Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

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Dissertação apresentada para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Ciências da Comunicação – Comunicação e Artes

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Dissertation for the Master’s Degree in Structural and Functional Biochemistry

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Dissertation presented to obtain the Ph.D degree in Biology

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Dissertation presented to obtain the Ph.D degree in Biology

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Dissertation presented to obtain the Ph.D degree in Biochemistry

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática

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Dissertation presented to obtain the Ph.D degree in Biology.

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Tese de mestrado, Ciências da Comunicação, Estudo dos Media e do Jornalismo

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Dissertação para obtenção do Grau de Doutor em Química, especialidade Química Orgânica

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Dissertação apresentada para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Estudos Ingleses e Norte Americanos

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ABSTRACT: Background: Sleep is integral to biological function and sleep disruption can result in both physiological and psychological dysfunction. The acute cognitive consequences of sleep loss has been an active field of recent investigation, evidence suggests that sleep disruption in critically ill older adults can result in acute decrements in cognitive functioning. Surgery activates the innate immune system, inducing neuroinflammatory changes that interfere with cognition. The fact that patients with sleep disorders have an increased likelihood of exhibiting postoperative delirium encourages us to investigate the contribution of perioperative SF to the neuroinflammatory and cognitive responses of surgery. Methods: The effects of 24h sleep fragmentation (SF) and surgery were explored on adult C57BL/6J male mice. SF procedure started at 7 am with the home-cages being placed on a large platform orbital shaker cycled every 120 seconds (30 sec on/90 sec off). This procedure lasted for 24h. Stabilized tibia fracture was performed either before or after the 24h SF procedure. Separate cohorts of mice were tested for systemic and hippocampal inflammation and cognition. Results: Twenty-four hours of SF induced non-hippocampal memory dysfunction and increase in systemic IL-6. SF and surgery caused hippocampal-dependent memory impairment, although memory impairment was not exacerbated by combining SF with surgery. One day after either SF or surgery there was a significant increase in IL6 mRNA and TNF-alpha mRNA. These increments were more pronounced when either pre or post operative SF was combined with surgery. Conclusions: We show that while SF and surgery can independently produce significant memory impairment, perioperative SF significantly increased hippocampal inflammation without further cognitive impairment. The dissociation between neuroinflammation and cognitive decline may relate to our use of a sole memory paradigm that does not capture other aspects of cognition, especially learning.

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Energy conservation in chemotrophic anaerobic bacteria is achieved by two possible processes, substrate level phosphorylation (SLP) and electron transfer phosphorylation (ETP). This second mechanism, also known as respiration, involves chemiosmotic coupling. However, a third mechanism for energy coupling was recently proposed: the flavin-based electron bifurcation (FBEB). (...)

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Phage display technology is a powerful platform for the generation of highly specific human monoclonal antibodies (Abs) with potential use in clinical applications. Moreover, this technique has also proven to be a reliable approach in identifying and validating new cancer-related targets. For scientific or medical applications, different types of Ab libraries can be constructed. The use of Fab Immune libraries allows the production of high quality and affinity antigen-specific Abs. In this work, two immune human phage display IgG Fab libraries were generated from the Ab repertoire of 16 breast cancer patients, in order to obtain a tool for the development of new therapeutic Abs for breast cancer, a condition that has great impact worldwide. The generated libraries are estimated to contain more than 108 independent clones and a diversity over 90%. Libraries validation was pursued by selection against BSA, a foreign and highly immunogenic protein, and HER2, a well established cancer target. Preliminary results suggested that phage pools with affinity for these antigens were selected and enriched. Individual clones were isolated, however, it was not possible to obtain enough data to further characterize them. Selection against the DLL1 protein was also performed, once it is a known ligand of the Notch pathway, whose deregulation is associated to breast cancer, making it an interesting target for the generation of function-blocking Abs. Selection resulted in the isolation of a clone with low affinity and Fab expression levels. The validation process was not completed and further effort will have to be put in this task in the future. Although immune libraries concept implies limited applicability, the library reported here has a wide range of use possibilities, since it was not restrained to a single antigen but instead thought to be used against any breast cancer associated target, thus being a valuable tool.

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Human Activity Recognition systems require objective and reliable methods that can be used in the daily routine and must offer consistent results according with the performed activities. These systems are under development and offer objective and personalized support for several applications such as the healthcare area. This thesis aims to create a framework for human activities recognition based on accelerometry signals. Some new features and techniques inspired in the audio recognition methodology are introduced in this work, namely Log Scale Power Bandwidth and the Markov Models application. The Forward Feature Selection was adopted as the feature selection algorithm in order to improve the clustering performances and limit the computational demands. This method selects the most suitable set of features for activities recognition in accelerometry from a 423th dimensional feature vector. Several Machine Learning algorithms were applied to the used accelerometry databases – FCHA and PAMAP databases - and these showed promising results in activities recognition. The developed algorithm set constitutes a mighty contribution for the development of reliable evaluation methods of movement disorders for diagnosis and treatment applications.