984 resultados para Large isoform of rubisco activase


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The usual high cost of commercial codes, and some technical limitations, clearly limits the employment of numerical modelling tools in both industry and academia. Consequently, the number of companies that use numerical code is limited and there a lot of effort put on the development and maintenance of in-house academic based codes. Having in mind the potential of using numerical modelling tools as a design aid, of both products and processes, different research teams have been contributing to the development of open source codes/libraries. In this framework, any individual can take advantage of the available code capabilities and/or implement additional features based on his specific needs. These type of codes are usually developed by large communities, which provide improvements and new features in their specific fields of research, thus increasing significantly the code development process. Among others, OpenFOAM® multi-physics computational library, developed by a very large and dynamic community, nowadays comprises several features usually only available in their commercial counterparts; e.g. dynamic meshes, large diversity of complex physical models, parallelization, multiphase models, to name just a few. This computational library is developed in C++ and makes use of most of all language capabilities to facilitate the implementation of new functionalities. Concerning the field of computational rheology, OpenFOAM® solvers were recently developed to deal with the most relevant differential viscoelastic rheological models, and stabilization techniques are currently being verified. This work describes the implementation of a new solver in OpenFOAM® library, able to cope with integral viscoelastic models based on the deformation field method. The implemented solver is verified through the comparison of the predicted results with analytical solutions, results published in the literature and by using the Method of Manufactured Solutions.

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Extreme value theory (EVT) deals with the occurrence of extreme phenomena. The tail index is a very important parameter appearing in the estimation of the probability of rare events. Under a semiparametric framework, inference requires the choice of a number k of upper order statistics to be considered. This is the crux of the matter and there is no definite formula to do it, since a small k leads to high variance and large values of k tend to increase the bias. Several methodologies have emerged in literature, specially concerning the most popular Hill estimator (Hill, 1975). In this work we compare through simulation well-known procedures presented in Drees and Kaufmann (1998), Matthys and Beirlant (2000), Beirlant et al. (2002) and de Sousa and Michailidis (2004), with a heuristic scheme considered in Frahm et al. (2005) within the estimation of a different tail measure but with a similar context. We will see that the new method may be an interesting alternative.

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The main features of most components consist of simple basic functional geometries: planes, cylinders, spheres and cones. Shape and position recognition of these geometries is essential for dimensional characterization of components, and represent an important contribution in the life cycle of the product, concerning in particular the manufacturing and inspection processes of the final product. This work aims to establish an algorithm to automatically recognize such geometries, without operator intervention. Using differential geometry large volumes of data can be treated and the basic functional geometries to be dealt recognized. The original data can be obtained by rapid acquisition methods, such as 3D survey or photography, and then converted into Cartesian coordinates. The satisfaction of intrinsic decision conditions allows different geometries to be fast identified, without operator intervention. Since inspection is generally a time consuming task, this method reduces operator intervention in the process. The algorithm was first tested using geometric data generated in MATLAB and then through a set of data points acquired by measuring with a coordinate measuring machine and a 3D scan on real physical surfaces. Comparison time spent in measuring is presented to show the advantage of the method. The results validated the suitability and potential of the algorithm hereby proposed

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Achatina fulica or "giant African snail" is an exotic species, considered to be one of the world's hundred most invasive species, causing serious environmental damages. In the present study we report, for the first time, the occurrence of Aelurostrongylus abstrusus infecting A.fulica in the Amazon region. This nematode is described parasitizing mainly the pulmonary system of felines, which causes "aelurostrongilose", also known as feline cardio-pulmonary strongyloidosis. New morphometric data of third stage larvae are presented herein. The present study demonstrated that 40% of all the snails were infected by A. abstrusus. Achatina fulica specimens were collected from three different areas in Manaus namely: rural; east and west areas. The east area presents the highest prevalence of 80%. The large number of A.fulica found in inhabited areas increases the chances of emergent zoonoses, which highlights the need of further studies so as to better control this disease.

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Lakes play an important role in biogeochemical, ecological and hydrological processes in the river-floodplain system. The aim of this study was to evaluate the dynamics of the limnological conditions of Catalão Lake, an Amazon floodplain lake. Thus, some of the main limnological environment variables (O2, temperature, pH, nutrient, electrical conductivity) of the Catalão Lake were analyzed under temporal and spacial scales. The study was conducted between November/2004 and August/2005. Sampling excursion were carried out every three months; one excursion for each of the four different hydrological periods (low water, rising water, high water and falling water). Sampling points were chosen so that it could be obtained a gradient of the distance from Negro River. Limnological profiles in Catalão Lake showed generally acidic to slightly alcaline water, with low levels of dissolved oxygen and low concentrations of soluble reactive phosphorous. The Negro River seems to exert the main influence during the rising water period, while the Solimões River is the principal controlling river during peak water. The Principal Component Analysis (PCA) grouped the seasonal collections by hydrological period, showing the formation of a north-south spatial gradient within the lake in relation to the limnological variables. Multivariate dispersion analysis based on distance-to-centroid method demonstrated an increase in similarity over the course of the hydrological cycle, as the lake was inundated in response to the flood pulse of the main river channels. However, the largest spatial homogeneity in the lake was observed in the epilimnion layer, during the falling water period. The daily analysis of variation indicated an oligomitic pattern during the years in which the lake was permanently connected to the Negro River. Although Catalão Lake receives large quantities of both black water from the Negro River and sediment-filled water from the Solimões River, the physical and chemical characteristics of the lake are more similar to those of the Solimões (várzea lake) than the Negro (blackwater lake).

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Previous studies on monocarboxylate transporters expression in prostate cancer (PCa) have shown that monocarboxylate transporter 2 (MCT2) was clearly overexpressed in prostate malignant glands, pointing it out as a putative biomarker for PCa. However, its localization and possible role in PCa cells remained unclear. In this study, we demonstrate that MCT2 localizes mainly at peroxisomes in PCa cells and is able to take advantage of the peroxisomal transport machinery by interacting with Pex19. We have also shown an increase in MCT2 expression from non-malignant to malignant cells that was directly correlated with its peroxisomal localization. Upon analysis of the expression of several peroxisomal ß-oxidation proteins in PIN lesions and PCa cells from a large variety of human prostate samples, we suggest that MCT2 presence at peroxisomes is related to an increase in ß -oxidation levels which may be crucial for malignant transformation. Our results present novel evidence that may not only contribute to the study of PCa development mechanisms but also pinpoint novel targets for cancer therapy.

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Currently, the quality of the Indonesian national road network is inadequate due to several constraints, including overcapacity and overloaded trucks. The high deterioration rate of the road infrastructure in developing countries along with major budgetary restrictions and high growth in traffic have led to an emerging need for improving the performance of the highway maintenance system. However, the high number of intervening factors and their complex effects require advanced tools to successfully solve this problem. The high learning capabilities of Data Mining (DM) are a powerful solution to this problem. In the past, these tools have been successfully applied to solve complex and multi-dimensional problems in various scientific fields. Therefore, it is expected that DM can be used to analyze the large amount of data regarding the pavement and traffic, identify the relationship between variables, and provide information regarding the prediction of the data. In this paper, we present a new approach to predict the International Roughness Index (IRI) of pavement based on DM techniques. DM was used to analyze the initial IRI data, including age, Equivalent Single Axle Load (ESAL), crack, potholes, rutting, and long cracks. This model was developed and verified using data from an Integrated Indonesia Road Management System (IIRMS) that was measured with the National Association of Australian State Road Authorities (NAASRA) roughness meter. The results of the proposed approach are compared with the IIRMS analytical model adapted to the IRI, and the advantages of the new approach are highlighted. We show that the novel data-driven model is able to learn (with high accuracy) the complex relationships between the IRI and the contributing factors of overloaded trucks

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Cancer cells rely mostly on glycolysis to meet their energetic demands, producing large amounts of lactate that are extruded to the tumour microenvironment by monocarboxylate transporters (MCTs). The role of MCTs in the survival of colorectal cancer (CRC) cells is scarce and poorly understood. In this study, we aimed to better understand this issue and exploit these transporters as novel therapeutic targets alone or in combination with the CRC classical chemotherapeutic drug 5-Fluorouracil. For that purpose, we characterized the effects of MCT activity inhibition in normal and CRC derived cell lines and assessed the effect of MCT inhibition in combination with 5-FU. Here, we demonstrated that MCT inhibition using CHC (a-cyano-4-hydroxycinnamic acid), DIDS (4,4'-diisothiocyanatostilbene-2,2'-disulphonic acid) and quercetin decreased cell viability, disrupted the glycolytic phenotype, inhibited proliferation and enhanced cell death in CRC cells. These results were confirmed by specific inhibition of MCT1/4 by RNA interference. Notably, we showed that 5-FU cytotoxicity was potentiated by lactate transport inhibition in CRC cells, either by activity inhibition or expression silencing. These findings provide novel evidence for the pivotal role of MCTs in CRC maintenance and survival, as well as for the use of these transporters as potential new therapeutic targets in combination with CRC conventional therapy.

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Invasive cervical cancer (ICC) is the third most frequent cancer among women worldwide and is associated with persistent infection by carcinogenic human papillomaviruses (HPVs). The combination of large populations of viral progeny and decades of sustained infection may allow for the generation of intra-patient diversity, in spite of the assumedly low mutation rates of PVs. While the natural history of chronic HPVs infections has been comprehensively described, within-host viral diversity remains largely unexplored. In this study we have applied next generation sequencing to the analysis of intra-host genetic diversity in ten ICC and one condyloma cases associated to single HPV16 infection. We retrieved from all cases near full-length genomic sequences. All samples analyzed contained polymorphic sites, ranging from 3 to 125 polymorphic positions per genome, and the median probability of a viral genome picked at random to be identical to the consensus sequence in the lesion was only 40%. We have also identified two independent putative duplication events in two samples, spanning the L2 and the L1 gene, respectively. Finally, we have identified with good support a chimera of human and viral DNA. We propose that viral diversity generated during HPVs chronic infection may be fueled by innate and adaptive immune pressures. Further research will be needed to understand the dynamics of viral DNA variability, differentially in benign and malignant lesions, as well as in tissues with differential intensity of immune surveillance. Finally, the impact of intralesion viral diversity on the long-term oncogenic potential may deserve closer attention.

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Text Mining has opened a vast array of possibilities concerning automatic information retrieval from large amounts of text documents. A variety of themes and types of documents can be easily analyzed. More complex features such as those used in Forensic Linguistics can gather deeper understanding from the documents, making possible performing di cult tasks such as author identi cation. In this work we explore the capabilities of simpler Text Mining approaches to author identification of unstructured documents, in particular the ability to distinguish poetic works from two of Fernando Pessoas' heteronyms: Alvaro de Campos and Ricardo Reis. Several processing options were tested and accuracies of 97% were reached, which encourage further developments.

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In this study, a mathematical model for the production of Fructo-oligosaccharides (FOS) by Aureobasidium pullulans is developed. This model contains a relatively large set of unknown parameters, and the identification problem is analyzed using simulation data, as well as experimental data. Batch experiments were not sufficiently informative to uniquely estimate all the unknown parameters, thus, additional experiments have to be achieved in fed-batch mode to supplement the missing information. © 2015 IEEE.

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Tese de Doutoramento em Engenharia Civil.

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Spinocerebellar ataxia type 3 (SCA3), also known as Machado-Joseph disease (MJD), is an untreatable autosomal dominant neurodegenerative disease, and the most common such inherited ataxia worldwide. The mutation in SCA3 is the expansion of a polymorphic CAG tri-nucleotide repeat sequence in the C-terminal coding region of the ATXN3 gene at chromosomal locus 14q32.1. The mutant ATXN3 protein encoding expanded glutamine (polyQ) sequences interacts with multiple proteins in vivo, and is deposited as aggregates in the SCA3 brain. A large body of literature suggests that the loss of function of the native ATNX3-interacting proteins that are deposited in the polyQ aggregates contributes to cellular toxicity, systemic neurodegeneration and the pathogenic mechanism in SCA3. Nonetheless, a significant understanding of the disease etiology of SCA3, the molecular mechanism by which the polyQ expansions in the mutant ATXN3 induce neurodegeneration in SCA3 has remained elusive. In the present study, we show that the essential DNA strand break repair enzyme PNKP (polynucleotide kinase 3'-phosphatase) interacts with, and is inactivated by, the mutant ATXN3, resulting in inefficient DNA repair, persistent accumulation of DNA damage/strand breaks, and subsequent chronic activation of the DNA damage-response ataxia telangiectasia-mutated (ATM) signaling pathway in SCA3. We report that persistent accumulation of DNA damage/strand breaks and chronic activation of the serine/threonine kinase ATM and the downstream p53 and protein kinase C-d pro-apoptotic pathways trigger neuronal dysfunction and eventually neuronal death in SCA3. Either PNKP overexpression or pharmacological inhibition of ATM dramatically blocked mutant ATXN3-mediated cell death. Discovery of the mechanism by which mutant ATXN3 induces DNA damage and amplifies the pro-death signaling pathways provides a molecular basis for neurodegeneration due to PNKP inactivation in SCA3, and for the first time offers a possible approach to treatment.

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A large group of low molecular weight natural compounds that exhibit antimicrobial activity has been isolated from animals and plants during the past two decades. Among them, peptides are the most widespread resulting in a new generation of antimicrobial agents with higher specific activity. In the present study we have developed a new strategy to obtain antimicrobial wound-dressings based on the incorporation of antimicrobial peptides into polyelectrolyte multilayer films built by the alternate deposition of polycation (chitosan) and polyanion (alginic acid sodium salt) over cotton gauzes. Energy dispersive X ray microanalysis technique was used to determine if antimicrobial peptides penetrated within the films. FTIR analysis was performed to assess the chemical linkages, and antimicrobial assays were performed with two strains: Staphylococcus aureus (Gram-positive bacterium) and Klebsiella pneumonia (Gram-negative bacterium). Results showed that all antimicrobial peptides used in this work have provided a higher antimicrobial effect (in the range of 4 log–6 log reduction) for both microorganisms, in comparison with the controls, and are non-cytotoxic to normal human dermal fibroblasts at the concentrations tested.