Exploration of X-ray, optical and radio emission of the radio-galaxy 3C 277.3

This thesis explores the X-ray nuclear and extended properties of the radio galaxy 3C 277.3, where a recent optical observation performed with the multi-unit spectroscopic explorer (MUSE) has revealed star-forming regions triggered by the propagation of non-thermal plasma in the intergalactic medium. This work aims to study the nuclear engine and its environment and, possibly, discover signatures of non-thermal plasma-gas interaction at high energies. 3C 277.3 was observed with the Chandra satellite five times from 2010 to 2014 for a total of about 200 ks. Data in the Chandra public archive were retrieved and analyzed. When necessary, the different pointings were combined to improve the signal-to-noise ratio. A detailed analysis of the Chandra image (obtained by combining all the observations) has revealed several emission regions. In addition to a bright nucleus, two jet knots and the northern hot spot were clearly detected by overlapping the X-ray data to a VLA map of the source at 1.4 GHz. An X-ray spectral analysis was performed for all these structures. Finally, the X-ray image was over-imposed on the MUSE data.

Sensores ópticos com detecção no infravermelho próximo e médio

Optical chemical sensors with detection in the near and mid infrared region are reviewed. Fundamental concepts of infrared spectroscopy and optical chemical sensors are briefly described, before presenting some aspects on optical chemical sensors, such as synthesis of NIR and IR reagents, preparation of new materials as well as application in determinations of species of biological, industrial and environmental importance.

Alterações do trato digestório de cães da raça Golden Retriever afetados pela distrofia muscular

O modelo experimental canino Golden Retriever portador da Distrofia Muscular (GRMD) é o melhor substituto entre os modelos animais para estudar a Distrofia Muscular de Duchenne. Além da musculatura estriada, a doença pode afetar a musculatura estriada cardíaca e a musculatura lisa, e desta forma, o funcionamento do trato digestório, já que o músculo liso é o elemento primário dos órgãos tubulares. Através de estudo morfológico descritivo, o objetivo deste trabalho foi verificar se a distrofia muscular afeta a arquitetura geral do trato digestório e como se dispõe sua estrutura muscular em animais afetados. Foram realizadas avaliações descritivas macro e microscópicas com colorações de Hematoxilina-Eosina, Tricrômio de Masson e Picrosirius. Entre os resultados apresentados, verificou-se que o esôfago e o fígado dos animais afetados encontraram-se alterados, assim como o estômago não ocupava seu lugar habitual. O músculo diafragma apresentava-se atrofiado e diferenças histológicas foram encontradas na camada muscular do sistema gastrointestinal, em geral. Outras estruturas do tubo digestório de GRMDs apresentaram-se de maneira similar a de um animal normal.

Impact of adiposity on immunological parameters

Studies evaluating immune function in obese humans and experimental animals indicate that the excess adiposity is associated with impaired in immune responses. Obesity is related to a higher rate of infections and to some types of cancer. Nutritional, metabolic and endocrine factors are implicated in the immunological changes. The adipose tissue directly produces substances with various functions related to immune system. Furthermore, some investigations suggest that certain types of weight reduction strategies can alter the immune function. Nevertheless, long-term studies should be carried out to address whether these changes positively affects the ability of these obese individuals to control infections and tumor development.

Isoprenoid biosynthesis in the erythrocytic stages of Plasmodium falciparum

The development of new drugs is one strategy for malaria control. Biochemical pathways localised in the apicoplast of the parasite, such as the synthesis of isoprenic precursors, are excellent targets because they are different or absent in the human host. Isoprenoids are a large and highly diverse group of natural products with many functions and their synthesis is essential for the parasite's survival. During the last few years, the genes, enzymes, intermediates and mechanisms of this biosynthetic route have been elucidated. In this review, we comment on some aspects of the methylerythritol phosphate pathway and discuss the presence of diverse isoprenic products such as dolichol, ubiquinone, carotenoids, menaquinone and isoprenylated proteins, which are biosynthesised during the intraerythrocytic stages of Plasmodium falciparum.

Determination and fractionation of barium in Brazil nuts

Several sample preparation strategies were employed for determination and fractionation of barium in Brazil nuts using measurements by graphite furnace atomic absorption spectrometry (GF AAS) and inductively coupled plasma optical emission spectrometry with axial view (ICP OES). This food is widely consumed because of its nutritional value and good taste. The chemical analysis of Brazil nuts is not trivial due to their complex matrix. The fractionation of barium in Brazil nuts was studied owing to the toxicity of this element and the strong correlation between chemical form and absorption. Total concentrations of barium varied from 860 to 2084 mg kg-1. Sequential extractions were performed based on solubility in different media and also according to lipids, proteins and low molecular weight fractions (LMW). The greatest contents of barium were determined in the LMW and in the water insoluble fractions with concentrations in the range 778 to 1606 and 551 to 1520 mg kg-1, respectively. Based on these results it can be inferred that Ba is not absorbed when Brazil nuts are ingested. Considering both the contents of barium and sulfur in different fractions and stoichiometric calculations it was also possible to assume that barium occurs mainly in the BaSO4 form. The presence of this chemical form was also confirmed by thermogravimetric measurements.

Computational adjustment technique for digital mammographic images based on the digitizer characteristic curve

We evaluated the performance of a novel procedure for segmenting mammograms and detecting clustered microcalcifications in two types of image sets obtained from digitization of mammograms using either a laser scanner, or a conventional ""optical"" scanner. Specific regions forming the digital mammograms were identified and selected, in which clustered microcalcifications appeared or not. A remarkable increase in image intensity was noticed in the images from the optical scanner compared with the original mammograms. A procedure based on a polynomial correction was developed to compensate the changes in the characteristic curves from the scanners, relative to the curves from the films. The processing scheme was applied to both sets, before and after the polynomial correction. The results indicated clearly the influence of the mammogram digitization on the performance of processing schemes intended to detect microcalcifications. The image processing techniques applied to mammograms digitized by both scanners, without the polynomial intensity correction, resulted in a better sensibility in detecting microcalcifications in the images from the laser scanner. However, when the polynomial correction was applied to the images from the optical scanner, no differences in performance were observed for both types of images. (C) 2008 SPIE and IS&T [DOI: 10.1117/1.3013544]

Collaborative e-learning and Learning Objects

The Learning Object (OA) is any digital resource that can be reused to support learning with specific functions and objectives. The OA specifications are commonly offered in SCORM model without considering activities in groups. This deficiency was overcome by the solution presented in this paper. This work specified OA for e-learning activities in groups based on SCORM model. This solution allows the creation of dynamic objects which include content and software resources for the collaborative learning processes. That results in a generalization of the OA definition, and in a contribution with e-learning specifications.

Accelerating autonomous learning by using heuristic selection of actions

This paper investigates how to make improved action selection for online policy learning in robotic scenarios using reinforcement learning (RL) algorithms. Since finding control policies using any RL algorithm can be very time consuming, we propose to combine RL algorithms with heuristic functions for selecting promising actions during the learning process. With this aim, we investigate the use of heuristics for increasing the rate of convergence of RL algorithms and contribute with a new learning algorithm, Heuristically Accelerated Q-learning (HAQL), which incorporates heuristics for action selection to the Q-Learning algorithm. Experimental results on robot navigation show that the use of even very simple heuristic functions results in significant performance enhancement of the learning rate.

Distributed Estimation Over an Adaptive Incremental Network Based on the Affine Projection Algorithm

We study the problem of distributed estimation based on the affine projection algorithm (APA), which is developed from Newton`s method for minimizing a cost function. The proposed solution is formulated to ameliorate the limited convergence properties of least-mean-square (LMS) type distributed adaptive filters with colored inputs. The analysis of transient and steady-state performances at each individual node within the network is developed by using a weighted spatial-temporal energy conservation relation and confirmed by computer simulations. The simulation results also verify that the proposed algorithm provides not only a faster convergence rate but also an improved steady-state performance as compared to an LMS-based scheme. In addition, the new approach attains an acceptable misadjustment performance with lower computational and memory cost, provided the number of regressor vectors and filter length parameters are appropriately chosen, as compared to a distributed recursive-least-squares (RLS) based method.

Conservation of dual-targeted proteins in Arabidopsis and rice points to a similar pattern of gene-family evolution

Gene duplication followed by acquisition of specific targeting information and dual targeting were evolutionary strategies enabling organelles to cope with overlapping functions. We examined the evolutionary trend of dual-targeted single-gene products in Arabidopsis and rice genomes. The number of paralogous proteins encoded by gene families and the dual-targeted orthologous proteins were analysed. The number of dual-targeted proteins and the corresponding gene-family sizes were similar in Arabidopsis and rice irrespective of genome sizes. We show that dual targeting of methionine aminopeptidase, monodehydroascorbate reductase, glutamyl-tRNA synthetase, and tyrosyl-tRNA synthetase was maintained despite occurrence of whole-genome duplications in Arabidopsis and rice as well as a polyploidization followed by a diploidization event (gene loss) in the latter.

A Practical Teaching Course in Directed Protein Evolution Using the Green Fluorescent Protein as a Model

Protein engineering is a powerful tool, which correlates protein structure with specific functions, both in applied biotechnology and in basic research. Here, we present a practical teaching course for engineering the green fluorescent protein (GFP) from Aequorea victoria by a random mutagenesis strategy using error-prone polymerase chain reaction. Screening of bacterial colonies transformed with random mutant libraries identified GFP variants with increased fluorescence yields. Mapping the three-dimensional structure of these mutants demonstrated how alterations in structural features such as the environment around the fluorophore and properties of the protein surface can influence functional properties such as the intensity of fluorescence and protein solubility.

Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

Expression of vitamin D receptor mRNA in the hippocampal formation of rats submitted to a model of temporal lobe epilepsy induced by pilocarpine

Vitamin D (VD), is a steroid hormone with multiple functions in the central nervous system (CNS), producing numerous physiological effects mediated by its receptor (VDR). Clinical and experimental studies have shown a link between VD dysfunction and epilepsy. Along these lines, the purpose of our work was to analyze the relative expression of VDR mRNA in the hippocampal formation of rats during the three periods of pilocarpine-induced epilepsy. Male Wistar rats were divided into five groups: (1) control group; rats that received saline 0.9%, i.p. and were killed 7 days after its administration (CTRL, n = 8), (2) SE group; rats that received pilocarpine and were killed 4 h after SE (SE, n = 8), (3) Silent group-7 days; rats that received pilocarpine and were killed 7 days after SE (SIL 7d, n = 8), (4) Silent group-14 days; rats that received pilocarpine and were killed 14 days after SE (SIL 14d, n = 8), (5) Chronic group; rats that received pilocarpine and were killed 60 days after the first spontaneous seizure, (chronic, n = 8). The relative expression of VDR mRNA was determined by real-time PCR. Our results showed an increase of the relative expression of VDR mRNA in the SIL 7 days, SIL 14 days and Chronic groups, respectively (0.060 +/- 0.024; 0.052 +/- 0.035; 0.085 +/- 0.055) when compared with the CTRL and SE groups (0.019 +/- 0.017; 0.019 +/- 0.025). These data suggest the VDR as a possible candidate participating in the epileptogenesis process of the pilocarpine model of epilepsy. (C) 2008 Elsevier Inc. All rights reserved.

Cognitive training increases platelet PLA(2) activity in healthy elderly subjects

Phospholipases A(2) (PLA(2)) are ubiquitous enzymes involved in membrane fatty acid metabolism and intracellular signalling. Recent studies have shown that PLA(2) subtypes are implicated in the modulation of pathways related to memory acquisition and retrieval. We investigated the effects of cognitive training on platelet PLA(2) activity in healthy elderly individuals. Twenty-three cognitively unimpaired older adults were randomly assigned to receive memory training or standard outpatient care only. Both groups were cognitively assessed by the same protocol, and the experimental group (EG) underwent a four-session memory training intervention. Pre- and post-test measures included prose and list recall, WAIS-III digit symbol, strategy use measures and platelet PLA(2) group activity. After cognitive training, patients in the EG group had significant increase in cytosolic, calcium-dependent PLA(2) (cPLA(2)), extracellular (or secreted), calcium-dependent PLA(2) (sPLA(2)), total platelet PLA(2) activity, and significant decrease in platelet calcium-independent PLA(2) (iPLA(2)) activity. Our results suggest that memory training may have a modulating effect in PLA(2)-mediated biological systems associated with cognitive functions and neurodegenerative diseases. (c) 2008 Elsevier Ltd. All rights reserved.