Efeitos do potencial probiótico Enterococcus faecium 32 e de sua associação com o extrato da alga marinha Caulerpa mexicana no tratamento de colite experimental murina

Ulcerative colitis comprising an inflammatory bowel disease, whose most severe consequence is the development of intestinal neoplasia. The drugs currently used to treat the disease trigger a variety of serious adverse effects and are not effective in many cases. Recent studies demonstrated the effectiveness of natural products for the treatment of inflammatory processes. Seaweed extracts and their purified products have shown protective effects in models of inflammation and the association of traditional therapies with probiotics has significantly improved the clinical symptoms of ulcerative colitis. Therefore, the aims of this study include evaluating the potential effects of the use of probiotic strain Enterococcus faecium 32 (Ef32), the methanolic extract of the green seaweed Caulerpa mexicana (M.E.) and their concomitant administration in a murine model of colitis induced by dextran sodium sulfate (DSS). Accordingly, C57BL /6 mice were pretreated orally with Ef32 (109 CFU/ml) for seven days. In the seven days following, the colitis was induced by administration of 3% DSS (w/v) diluted in the animals drinking water. During this period, animals were treated daily with Ef32 and the M.E. (2.0 mg/kg) every other day by intravenous route. The development of colitis was monitored by the disease activity index (DAI), which takes into account the loss of body weight, consistency and presence of blood in stools. After euthanasia, the colon was removed, its length measured and tissue samples were destined for histological analysis and culture for cytokine quantification. The levels of cytokines in the culture supernatant of the colon were measured by ELISA. The treatments with the probiotic Ef32 or the M.E. alone or the combination of these two substances provoked significant improvement as to weight loss and DAI, and prevented the shortening of the colon in response to DSS. The isolated treatments triggered a slight improvement in intestinal mucosal tissue damage. However, their combination was able to completely repair the injury triggered by DSS. The association was also able to reduce the levels of all the cytokines analyzed (IFN-γ, IL-4, IL-6, IL-12, IL-17A and TNF-α). On the other hand, the treatment with Ef32 did not interfere with the levels of TNF-α, whereas treatment with M.E. did not alter the levels of IL-6. Moreover, the treatment with Ef32 not interferes in TNF-α levels, whereas treatment with M.E. did not alter the levels of IL-6. Therefore, the potential probiotic Ef32 and M.E. and especially when these samples were associated proved promising alternatives in the treatment of ulcerative colitis as demonstrated in an experimental model because of its beneficial effects on morphological and clinical parameters, and by reducing the production of proinflammatory cytokines of Th1, Th2 and Th17

Neurofisiologia hipocampal durante sessões de sono intercaladas por exploração espacial: Reverberação do passado ou predição do futuro?

The ability to predict future rewards or threats is crucial for survival. Recent studies have addressed future event prediction by the hippocampus. Hippocampal neurons exhibit robust selectivity for spatial location. Thus, the activity of hippocampal neurons represents a cognitive map of space during navigation as well as during planning and recall. Spatial selectivity allows the hippocampus to be involved in the formation of spatial and episodic memories, including the sequential ordering of events. On the other hand, the discovery of reverberatory activity in multiple forebrain areas during slow wave and REM sleep underscored the role of sleep on the consolidation of recently acquired memory traces. To this date, there are no studies addressing whether neuronal activity in the hippocampus during sleep can predict regular environmental shifts. The aim of the present study was to investigate the activity of neuronal populations in the hippocampus during sleep sessions intercalated by spatial exploration periods, in which the location of reward changed in a predictable way. To this end, we performed the chronic implantation of 32-channel multielectrode arrays in the CA1 regions of the hippocampus in three male rats of the Wistar strain. In order to activate different neuronal subgroups at each cycle of the task, we exposed the animals to four spatial exploration sessions in a 4-arm elevated maze in which reward was delivered in a single arm per session. Reward location changed regularly at every session in a clockwise manner, traversing all the arms at the end of the daily recordings. Animals were recorded from 2-12 consecutive days. During spatial exploration of the 4-arm elevated maze, 67,5% of the recorded neurons showed firing rate differences across the maze arms. Furthermore, an average of 42% of the neurons showed increased correlation (R>0.3) between neuronal pairs in each arm. This allowed us to sort representative neuronal subgroups for each maze arm, and to analyze the activity of these subgroups across sleep sessions. We found that neuronal subgroups sorted by firing rate differences during spatial exploration sustained these differences across sleep sessions. This was not the case with neuronal subgroups sorted according to synchrony (correlation). In addition, the correlation levels between sleep sessions and waking patterns sampled in each arm were larger for the entire population of neurons than for the rate or synchrony subgroups. Neuronal activity during sleep of the entire neuronal population or subgroups did not show different correlations among the four arm mazes. On the other hand, we verified that neuronal activity during pre-exploration sleep sessions was significantly more similar to the activity patterns of the target arm than neuronal activity during pre-exploration sleep sessions. In other words, neuronal activity during sleep that precedes the task reflects more strongly the location of reward than neuronal activity during sleep that follows the task. Our results suggest that neuronal activity during sleep can predict regular environmental changes

X-ARM: um modelo de representação de artefatos de software

A great challenge of the Component Based Development is the creation of mechanisms to facilitate the finding of reusable assets that fulfill the requirements of a particular system under development. In this sense, some component repositories have been proposed in order to answer such a need. However, repositories need to represent the asset characteristics that can be taken into account by the consumers when choosing the more adequate assets for their needs. In such a context, the literature presents some models proposed to describe the asset characteristics, such as identification, classification, non-functional requirements, usage and deployment information and component interfaces. Nevertheless, the set of characteristics represented by those models is insufficient to describe information used before, during and after the asset acquisition. This information refers to negotiation, certification, change history, adopted development process, events, exceptions and so on. In order to overcome this gap, this work proposes an XML-based model to represent several characteristics, of different asset types, that may be employed in the component-based development. Besides representing metadata used by consumers, useful for asset discovering, acquisition and usage, this model, called X-ARM, also focus on helping asset developers activities. Since the proposed model represents an expressive amount of information, this work also presents a tool called X-Packager, developed with the goal of helping asset description with X-ARM