366 resultados para Corporate self-regulation


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Background Methamphetamine is a highly addictive central nervous system stimulant with increasing levels of abuse worldwide. Alterations to mRNA and miRNA expression within the mesolimbic system can affect addiction-like behaviors and thus play a role in the development of drug addiction. While many studies have investigated the effects of high-dose methamphetamine, and identified neurotoxic effects, few have looked at the role that persistent changes in gene regulation play following methamphetamine self-administration. Therefore, the aim of this study was to identify RNA changes in the ventral tegmental area following methamphetamine self-administration. We performed microarray analyses on RNA extracted from the ventral tegmental area of Sprague–Dawley rats following methamphetamine self-administration training (2 h/day) and 14 days of abstinence. Results We identified 78 miRNA and 150 mRNA transcripts that were differentially expressed (fdr adjusted p < 0.05, absolute log2 fold change >0.5); these included genes not previously associated with addiction (miR-125a-5p, miR-145 and Foxa1), loci encoding receptors related to drug addiction behaviors and genes with previously recognized roles in addiction such as miR-124, miR-181a, DAT and Ret. Conclusion This study provides insight into the effects of methamphetamine on RNA expression in a key brain region associated with addiction, highlighting the possibility that persistent changes in the expression of genes with both known and previously unknown roles in addiction occur.

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This paper discusses a framework in which catalog service communities are built, linked for interaction, and constantly monitored and adapted over time. A catalog service community (represented as a peer node in a peer-to-peer network) in our system can be viewed as domain specific data integration mediators representing the domain knowledge and the registry information. The query routing among communities is performed to identify a set of data sources that are relevant to answering a given query. The system monitors the interactions between the communities to discover patterns that may lead to restructuring of the network (e.g., irrelevant peers removed, new relationships created, etc.).