899 resultados para Neuronal Organization


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Prenatal stress, rodent, limbic system, neuronal development, dendritic spines, sex difference

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Weaning, social environment, dendrites, dendritic spines, limbic system

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Magdeburg, Univ., Fak. für Naturwiss., Diss., 2009

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Magdeburg, Univ., Fak. für Naturwiss., Diss., 2009

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Magdeburg, Univ., Fak. für Naturwiss., Diss., 2012

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The modern computer systems that are in use nowadays are mostly processor-dominant, which means that their memory is treated as a slave element that has one major task – to serve execution units data requirements. This organization is based on the classical Von Neumann's computer model, proposed seven decades ago in the 1950ties. This model suffers from a substantial processor-memory bottleneck, because of the huge disparity between the processor and memory working speeds. In order to solve this problem, in this paper we propose a novel architecture and organization of processors and computers that attempts to provide stronger match between the processing and memory elements in the system. The proposed model utilizes a memory-centric architecture, wherein the execution hardware is added to the memory code blocks, allowing them to perform instructions scheduling and execution, management of data requests and responses, and direct communication with the data memory blocks without using registers. This organization allows concurrent execution of all threads, processes or program segments that fit in the memory at a given time. Therefore, in this paper we describe several possibilities for organizing the proposed memory-centric system with multiple data and logicmemory merged blocks, by utilizing a high-speed interconnection switching network.

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Magdeburg, Univ., Fak. für Naturwiss., Diss., 2015

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Magdeburg, Univ., Med. Fak., Diss., 2015

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Magdeburg, Univ., Fak. für Informatik, Diss., 2015

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Otto-von-Guericke-Universtität Magdeburg, Fakultät für Naturwissenschaften, Univ., Dissertation, 2016

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The morphology of the cyst cells in Apis mellifera Linné, 1758, Scaptotrigona postica Latreille, 1804, and Melipona bicolor bicolor Lepeletier, 1836 testis, as well as the average number of spermatic cells are reported. The data indicates a supporting and nourrishing role of the cyst cells to the developing cystocytes. The counts of immature spermatozoa in the cysts show an average of 202.8 ± 21.2 spermatozoa for A. mellifera, 117.4 ± 8.68 for S. postica and 88.8 ± 15.57 for M. bicolor, which predict the occurrence of 8 mitotic cycles in the cystocytes of A. mellifera and 7 in the meliponines, considering that only one spermatozoom originates of each final spermatogonium.

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MicroRNAs (miRNAs) have been shown to play important roles in both brain development and the regulation of adult neural cell functions. However, a systematic analysis of brain miRNA functions has been hindered by a lack of comprehensive information regarding the distribution of miRNAs in neuronal versus glial cells. To address this issue, we performed microarray analyses of miRNA expression in the four principal cell types of the CNS (neurons, astrocytes, oligodendrocytes, and microglia) using primary cultures from postnatal d 1 rat cortex. These analyses revealed that neural miRNA expression is highly cell-type specific, with 116 of the 351 miRNAs examined being differentially expressed fivefold or more across the four cell types. We also demonstrate that individual neuron-enriched or neuron-diminished RNAs had a significant impact on the specification of neuronal phenotype: overexpression of the neuron-enriched miRNAs miR-376a and miR-434 increased the differentiation of neural stem cells into neurons, whereas the opposite effect was observed for the glia-enriched miRNAs miR-223, miR-146a, miR-19, and miR-32. In addition, glia-enriched miRNAs were shown to inhibit aberrant glial expression of neuronal proteins and phenotypes, as exemplified by miR-146a, which inhibited neuroligin 1-dependent synaptogenesis. This study identifies new nervous system functions of specific miRNAs, reveals the global extent to which the brain may use differential miRNA expression to regulate neural cell-type-specific phenotypes, and provides an important data resource that defines the compartmentalization of brain miRNAs across different cell types.