924 resultados para Metabolite Mimics
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RESUMO - O ácido δ-aminolevulínico presente na urina (ALA-U) é generalizadamente aceite como um indicador adequado para a vigilância de saúde de trabalhadores expostos a chumbo. A necessidade ou não de recurso a colheitas de urina de 24 horas para um correcto doseamento desse metabolito tem, entretanto, suscitado algumas dúvidas. Num estudo abrangendo 45 indivíduos (28 dos quais profissionalmente expostos a chumbo inorgânico) efectuou-se o doseamento do ALA em urinas colhidas durante 24 horas e em urina de colheita única. Confirmou-se a existência de uma boa correlação entre o ALA urinário e a plumbemia e que o tipo de colheita de urina efectuada não influencia significativamente essa associação. Contudo, pela apreciação das variações interindividuais registadas, parece aconselhável que seja privilegiado o doseamento em urinas de 24 horas.
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Dissertação de mestrado em Bioinformática
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Dissertação de mestrado em Bioinformática
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PhD thesis in Bioengineering
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Tese de Doutoramento Engenharia Têxtil.
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Natural selection favors the survival and reproduction of organisms that are best adapted to their environment. Selection mechanism in evolutionary algorithms mimics this process, aiming to create environmental conditions in which artificial organisms could evolve solving the problem at hand. This paper proposes a new selection scheme for evolutionary multiobjective optimization. The similarity measure that defines the concept of the neighborhood is a key feature of the proposed selection. Contrary to commonly used approaches, usually defined on the basis of distances between either individuals or weight vectors, it is suggested to consider the similarity and neighborhood based on the angle between individuals in the objective space. The smaller the angle, the more similar individuals. This notion is exploited during the mating and environmental selections. The convergence is ensured by minimizing distances from individuals to a reference point, whereas the diversity is preserved by maximizing angles between neighboring individuals. Experimental results reveal a highly competitive performance and useful characteristics of the proposed selection. Its strong diversity preserving ability allows to produce a significantly better performance on some problems when compared with stat-of-the-art algorithms.
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Buruli Ulcer (BU) is a necrotizing skin disease caused by Mycobacterium ulcerans infection. BU is characterized by a wide range of clinical forms, including non-ulcerative cutaneous lesions that can evolve into severe ulcers if left untreated. Nevertheless, spontaneous healing has been reported to occur, although knowledge on this process is scarce both in naturally infected humans and experimental models of infection. Animal models are useful since they mimic different spectrums of human BU disease and have the potential to elucidate the pathogenic/protective pathway(s) involved in disease/healing. In this time-lapsed study, we characterized the guinea pig, an animal model of resistance to M. ulcerans, focusing on the macroscopic, microbiological and histological evolution throughout the entire experimental infectious process. Subcutaneous infection of guinea pigs with a virulent strain of M. ulcerans led to early localized swelling, which evolved into small well defined ulcers. These macroscopic observations correlated with the presence of necrosis, acute inflammatory infiltrate and an abundant bacterial load. By the end of the infectious process when ulcerative lesions healed, M. ulcerans viability decreased and the subcutaneous tissue organization returned to its normal state after a process of continuous healing characterized by tissue granulation and reepethelialization. In conclusion, we show that the experimental M. ulcerans infection of the guinea pig mimics the process of spontaneous healing described in BU patients, displaying the potential to uncover correlates of protection against BU, which can ultimately contribute to the development of new prophylactic and therapeutic strategies.
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The currently available clinical imaging methods do not provide highly detailed information about location and severity of axonal injury or the expected recovery time of patients with traumatic brain injury [1]. High-Definition Fiber Tractography (HDFT) is a novel imaging modality that allows visualizing and quantifying, directly, the degree of axons damage, predicting functional deficits due to traumatic axonal injury and loss of cortical projections. This imaging modality is based on diffusion technology [2]. The inexistence of a phantom able to mimic properly the human brain hinders the possibility of testing, calibrating and validating these medical imaging techniques. Most research done in this area fails in key points, such as the size limit reproduced of the brain fibers and the quick and easy reproducibility of phantoms [3]. For that reason, it is necessary to develop similar structures matching the micron scale of axon tubes. Flexible textiles can play an important role since they allow producing controlled packing densities and crossing structures that match closely the human crossing patterns of the brain. To build a brain phantom, several parameters must be taken into account in what concerns to the materials selection, like hydrophobicity, density and fiber diameter, since these factors influence directly the values of fractional anisotropy. Fiber cross-section shape is other important parameter. Earlier studies showed that synthetic fibrous materials are a good choice for building a brain phantom [4]. The present work is integrated in a broader project that aims to develop a brain phantom made by fibrous materials to validate and calibrate HDFT. Due to the similarity between thousands of hollow multifilaments in a fibrous arrangement, like a yarn, and the axons, low twist polypropylene multifilament yarns were selected for this development. In this sense, extruded hollow filaments were analysed in scanning electron microscope to characterize their main dimensions and shape. In order to approximate the dimensional scale to human axons, five types of polypropylene yarns with different linear density (denier) were used, aiming to understand the effect of linear density on the filament inner and outer areas. Moreover, in order to achieve the required dimensions, the polypropylene filaments cross-section was diminished in a drawing stage of a filament extrusion line. Subsequently, tensile tests were performed to characterize the mechanical behaviour of hollow filaments and to evaluate the differences between stretched and non-stretched filaments. In general, an increase of the linear density causes the increase in the size of the filament cross section. With the increase of structure orientation of filaments, induced by stretching, breaking tenacity increases and elongation at break decreases. The production of hollow fibers, with the required characteristics, is one of the key steps to create a brain phantom that properly mimics the human brain that may be used for the validation and calibration of HDFT, an imaging approach that is expected to contribute significantly to the areas of brain related research.
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The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.
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The recent focus on the cystic fibrosis (CF) complex microbiome has led to the recognition that the microbes can interact between them and with the host immune system, affecting the disease progression and treatment routes. Although the main focus remains on the interactions between traditional pathogens, growing evidence supports the contribution and the role of emergent species. Understanding the mechanisms and the biological effects involved in polymicrobial interactions may be the key to improve effective therapies and also to define new strategies for disease control. This review focuses on the interactions between microbe-microbe and host-microbe, from an ecological point of view, discussing their impact on CF disease progression. There are increasing indications that these interactions impact the success of antimicrobial therapy. Consequently, a new approach where therapy is personalized to patients by taking into account their individual CF microbiome is suggested.
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Bacteriophage-host interaction studies in biofilm structures are still challenging due to the technical limitations of traditional methods. The aim of this study was to provide a direct fluorescence in situ hybridization (FISH) method based on locked nucleic acid (LNA) probes, which targets the phage replication phase, allowing the study of population dynamics during infection. Bacteriophages specific for two biofilm-forming bacteria, Pseudomonas aeruginosa and Acinetobacter, were selected. Four LNA probes were designed and optimized for phage-specific detection and for bacterial counterstaining. To validate the method, LNA-FISH counts were compared with the traditional plaque forming unit (PFU) technique. To visualize the progression of phage infection within a biofilm, colony-biofilms were formed and infected with bacteriophages. A good correlation (r=0.707) was observed between LNA-FISH and PFU techniques. In biofilm structures, LNA-FISH provided a good discrimination of the infected cells and also allowed the assessment of the spatial distribution of infected and non-infected populations.
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Zeolites Y (faujasite) and MOR (mordonite) were used as hosts for temozolomide (TMZ), a current good-standard chemotherapeutic agent used in the treatment of glioblastoma brain tumors. TMZ was loaded into zeolites by liquid-phase adsorption at controlled pH. FTIR, 1H NMR, MS, SEM, UV/vis and chemical analysis demonstrated the successful loading of TMZ into zeolite hosts. The hydrolysis of TMZ in MTIC (TMZ metabolite) after the preparation of drug delivery systems (DDS) was observed in simulated body fluid. The effect of zeolites and DDS were evaluated on the viability of glioblastoma cell lines. Unloaded Y zeolite presented toxicity to cancer cells in contrast to MOR. In accordance, the best results in potentiation of the TMZ effect was obtained with MOR. We found that mordonite loaded with 0.026 mmol of TMZ was able to decrease the half maximal inhibitory concentrations (IC50) at least 3-fold in comparison to free temozolomide both in vitro and in vivo.
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Accepted Manuscript
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Fluorescence in situ hybridization (FISH) is a molecular technique widely used for the detection and characterization of microbial populations. FISH is affected by a wide variety of abiotic and biotic variables and the way they interact with each other. This is translated into a wide variability of FISH procedures found in the literature. The aim of this work is to systematically study the effects of pH, dextran sulfate and probe concentration in the FISH protocol, using a general peptide nucleic acid (PNA) probe for the Eubacteria domain. For this, response surface methodology was used to optimize these 3 PNA-FISH parameters for Gram-negative (Escherichia coli and Pseudomonas fluorescens) and Gram-positive species (Listeria innocua, Staphylococcus epidermidis and Bacillus cereus). The obtained results show that a probe concentration higher than 300 nM is favorable for both groups. Interestingly, a clear distinction between the two groups regarding the optimal pH and dextran sulfate concentration was found: a high pH (approx. 10), combined with lower dextran sulfate concentration (approx. 2% [w/v]) for Gram-negative species and near-neutral pH (approx. 8), together with higher dextran sulfate concentrations (approx. 10% [w/v]) for Gram-positive species. This behavior seems to result from an interplay between pH and dextran sulfate and their ability to influence probe concentration and diffusion towards the rRNA target. This study shows that, for an optimum hybridization protocol, dextran sulfate and pH should be adjusted according to the target bacteria.
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Dissertação de mestrado em Técnicas de Caracterização e Análise Química