969 resultados para immune activity


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Chronic difficulties arising from mild brain injury (TBI) are difficult to predict because the processes underlying changes after TBI are poorly understood. In mild brain injury the extent of neuropsychiatric and cognitive symptoms correspond poorly to overt tissue loss (Barth 1983; Liu 2010). Cellular, immune and hormonal cascades occurring after injury and continuing during the healing process may impact uninjured brain regions sensitive to the effects of physiological and emotional stress, which receive projections from the injury site. Changes in these most basic properties due to injury or disease have profound implications for virtually every aspect of brain function through disruption of neurotransmitter, neuroendocrine and metabolic systems. In order to screen for changes in transmitter and metabolic activity, in this study we developed Single voxel proton Magnetic Resonance Spectroscopy (1H-MRS) for use in both injured and control animals. We first evaluated if 1H-MRS could be used to evaluate in vivo, alterations in brain metabolism and catabolism of the prefrontal cortex, amygdala and ventral hippocampus in both control and injured animals after controlled cortical impact injury to the rat prefrontal cortex. We found that metabolite measurements for Myo-Inositol, Choline, creatine, Glutamate+Glutamine, and N-acetyl-acetate are attainable in deep brain structures in vivo in injured and controls rats. We next seek to evaluate longitudinally, in vivo, alterations in brain metabolism and catabolism of the prefrontal cortex, amygdala and ventral hippocampus during the first month after controlled cortical impact injury to the rat prefrontal cortex. These ongoing studies will provide data on the changes in transmitters and metabolites over time in injured and non-injured subjects. These studies address some of the fundamental questions about how mild brain injury has such diverse effects on overall brain health and function.

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Market segmentation has received relatively limited attention in social marketing, particularly within the context of changing children’s physical activity behaviour. This is an important area of investigation given growing concern over childhood obesity globally. The present research aims to extend current understanding of the applicability of market segmentation within this context. The results of a two-step cluster analysis on data from 512 respondents of an online survey show three distinct segments of caregivers, each with unique beliefs about their primary school children walking to/from school. The results demonstrate the validity of employing the process of market segmentation within this social context and provide further insights for targeting the identified segments through tailored social marketing programs.

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This thesis is an analyzing creative processes that can be fostered through computer gaming. Outcomes from the research build on our knowledge of how computer games foster creative thinking. The research proposes guidelines that build upon our understanding of the relationship between the creative processes that players undertake during a game and the components of the game that allow these processes to occur. These guidelines may be used in the game design process to better facilitate creative gameplay activity. A significant research contribution is the ability to create games that facilitate creative thinking through engaging interactions with technology.

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Local spatio-temporal features with a Bag-of-visual words model is a popular approach used in human action recognition. Bag-of-features methods suffer from several challenges such as extracting appropriate appearance and motion features from videos, converting extracted features appropriate for classification and designing a suitable classification framework. In this paper we address the problem of efficiently representing the extracted features for classification to improve the overall performance. We introduce two generative supervised topic models, maximum entropy discrimination LDA (MedLDA) and class- specific simplex LDA (css-LDA), to encode the raw features suitable for discriminative SVM based classification. Unsupervised LDA models disconnect topic discovery from the classification task, hence yield poor results compared to the baseline Bag-of-words framework. On the other hand supervised LDA techniques learn the topic structure by considering the class labels and improve the recognition accuracy significantly. MedLDA maximizes likelihood and within class margins using max-margin techniques and yields a sparse highly discriminative topic structure; while in css-LDA separate class specific topics are learned instead of common set of topics across the entire dataset. In our representation first topics are learned and then each video is represented as a topic proportion vector, i.e. it can be comparable to a histogram of topics. Finally SVM classification is done on the learned topic proportion vector. We demonstrate the efficiency of the above two representation techniques through the experiments carried out in two popular datasets. Experimental results demonstrate significantly improved performance compared to the baseline Bag-of-features framework which uses kmeans to construct histogram of words from the feature vectors.

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This study aimed to quantify the intensity of physical activity (PA) of children during school recess (RE), compare the AF gender and seasonal influences. The sample consisted of 30 girls (11.2 ± 1.3 years) and 20 boys (11.3 ± 0.8 years). Heart rate was monitored for three consecutive REs in winter (INV) and spring (PRI) with intensity of the activity being classified as low, moderate and vigorous. Descriptive statistics were used for general data, t test for independent samples for differences between the sexes, paired t test for seasonality. Differences were found between INV and PRI temperatures. Girls had a significant reduction in the AF INV to PRI, which was not observed among boys. The RE represented a small contribution to daily recommendations of AF.

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IgA is an important mucosal antibody that can neutralize mucosal pathogens by either preventing attachment to epithelia (immune exclusion) or alternatively inhibit intraepithelial replication following transcytosis by the polymeric immunoglobulin receptor (pIgR). Chlamydia trachomatis is a major human pathogen that initially targets the endocervical or urethral epithelium in women and men, respectively. As both tissues contain abundant SIgA we assessed the protection afforded by IgA targeting different chlamydial antigens expressed during the extra and intraepithelial stages of infection. We developed an in vitro model utilizing polarizing cells expressing the murine pIgR together with antigen-specific mouse IgA, and an in vivo model utilizing pIgR-/- mice. SIgA targeting the extraepithelial chlamydial antigen, the major outer membrane protein (MOMP), significantly reduced infection in vitro by 24 % and in vivo by 44 %. Conversely, pIgR-mediated delivery of IgA targeting the intraepithelial inclusion membrane protein A (IncA) bound to the inclusion but did not reduce infection in vitro or in vivo. Similarly, intraepithelial IgA targeting the secreted protease Chlamydia protease-like activity factor (CPAF) also failed to reduce infection. Together, these data suggest the importance of pIgR-mediated delivery of IgA targeting extra but not intraepithelial chlamydial antigens for protection against a genital tract infection.

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In this paper, dynamic modeling and simulation of the hydropurification reactor in a purified terephthalic acid production plant has been investigated by gray-box technique to evaluate the catalytic activity of palladium supported on carbon (0.5 wt.% Pd/C) catalyst. The reaction kinetics and catalyst deactivation trend have been modeled by employing artificial neural network (ANN). The network output has been incorporated with the reactor first principle model (FPM). The simulation results reveal that the gray-box model (FPM and ANN) is about 32 percent more accurate than FPM. The model demonstrates that the catalyst is deactivated after eleven months. Moreover, the catalyst lifetime decreases about two and half months in case of 7 percent increase of reactor feed flowrate. It is predicted that 10 percent enhancement of hydrogen flowrate promotes catalyst lifetime at the amount of one month. Additionally, the enhancement of 4-carboxybenzaldehyde concentration in the reactor feed improves CO and benzoic acid synthesis. CO is a poison to the catalyst, and benzoic acid might affect the product quality. The model can be applied into actual working plants to analyze the Pd/C catalyst efficient functioning and the catalytic reactor performance.

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This study focuses on trying to understand why the range of experience with respect to HIV infection is so diverse, especially as regards to the latency period. The challenge is to determine what assumptions can be made about the nature of the experience of antigenic invasion and diversity that can be modelled, tested and argued plausibly. To investigate this, an agent-based approach is used to extract high-level behaviour which cannot be described analytically from the set of interaction rules at the cellular level. A prototype model encompasses local variation in baseline properties contributing to the individual disease experience and is included in a network which mimics the chain of lymphatic nodes. Dealing with massively multi-agent systems requires major computational efforts. However, parallelisation methods are a natural consequence and advantage of the multi-agent approach. These are implemented using the MPI library.

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In this paper we present an update on our novel visualization technologies based on cellular immune interaction from both large-scale spatial and temporal perspectives. We do so with a primary motive: to present a visually and behaviourally realistic environment to the community of experimental biologists and physicians such that their knowledge and expertise may be more readily integrated into the model creation and calibration process. Visualization aids understanding as we rely on visual perception to make crucial decisions. For example, with our initial model, we can visualize the dynamics of an idealized lymphatic compartment, with antigen presenting cells (APC) and cytotoxic T lymphocyte (CTL) cells. The visualization technology presented here offers the researcher the ability to start, pause, zoom-in, zoom-out and navigate in 3-dimensions through an idealised lymphatic compartment.

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Cochrane Journal Club resource for the Cochrane Systematic Review: Community wide interventions for increasing physical activity. The resource includes a power-point presentation describing the essential components of the paper, summary, Discussion points: a critical appraisal and an author profile.

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Synaptic plasticity in the lateral amygdala (LA) may underlie auditory fear conditioning. Hebb postulated that sustained activity in reverberating cellular ensembles can facilitate temporal coincidence detection. Our anatomical data show that LA neurons have extensive local axon collaterals that are topographically organized and that could provide the anatomical basis for reverberatory activity...

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Background Women with young children (<5 years) are an important group for physical activity intervention. Purpose To evaluate the feasibility, acceptability and efficacy of MobileMums- a physical activity intervention for women with young children. Methods Women were randomized to MobileMums (n=133) or a control group (n=130). MobileMums was delivered primarily via individually-tailored text messages. Moderate to vigorous physical activity (MVPA) was measured by self-report and accelerometer at baseline, end of the intervention (13-weeks) and 6-months later (9-months). Changes were analyzed using repeated measures models. Results MobileMums was feasible to deliver and acceptable to women. Self-reported MVPA duration (minutes/week) and frequency (days/week) increased significantly post intervention (13-week intervention effect 48.5 min/week, 95%CI [13.4, 82.9] and 1.6 days/week, 95%CI [0.6, 2.6]). Intervention effects were not maintained 6-months later. No effects observed in accelerometer-derived MVPA. Conclusions MobileMums increased women’s self-reported MVPA immediately post intervention. Future investigations need to target sustained physical activity improvements.

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We develop a hybrid cellular automata model to describe the effect of the immune system and chemokines on a growing tumor. The hybrid cellular automata model consists of partial differential equations to model chemokine concentrations, and discrete cellular automata to model cell–cell interactions and changes. The computational implementation overlays these two components on the same spatial region. We present representative simulations of the model and show that increasing the number of immature dendritic cells (DCs) in the domain causes a decrease in the number of tumor cells. This result strongly supports the hypothesis that DCs can be used as a cancer treatment. Furthermore, we also use the hybrid cellular automata model to investigate the growth of a tumor in a number of computational “cancer patients.” Using these virtual patients, the model can explain that increasing the number of DCs in the domain causes longer “survival.” Not surprisingly, the model also reflects the fact that the parameter related to tumor division rate plays an important role in tumor metastasis.