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Nitric oxide (NO)-dependent pathways may play a significant role in the decline of synaptic and cognitive functions in Alzheimer's disease (AD). However, whether NO in the hippocampal dentate gyrus (DG) is involved in the spatial learning and memory impairments of AD by affecting the glutamate (Glu) response during these processes is not well-understood. Here, we prepared an AD rat model by long-term i.p. of D-galactose into ovariectomized rats, and then the effects of L-NMMA (a NO synthase inhibitor) on Glu concentration and amplitude of field excitatory postsynaptic potential (fEPSP) were measured in the DG region during the Morris water maze (MWM) test in freely-moving rats. During the MWM test, compared with the sham group, the escape latency was increased in the place navigation trial, and the percentage of time spent in target quadrant and the number of platform crossings were decreased in the spatial probe trial, in addition, the increase of fEPSP amplitude in the DG was significantly attenuated in AD group rats. L-NMMA significantly attenuated the spatial learning and memory impairment in AD rats, and reversed the inhibitory effect of AD on increase of fEPSP amplitude in the DG during the MWM test. In sham group rats, the Glu level in the DG increased significantly during the MWM test, and this response was markedly enhanced in AD rats. Furthermore, the response of Glu in the DG during spatial learning was recovered by microinjection of L-NMMA into the DG. Our results suggest that NO in the DG impairs spatial learning and memory and related synaptic plasticity in AD rats, by disturbing the Glu response during spatial learning.
Pubmed ID: 35033612 RIS Download
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THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. The NeuroLOG consortium is addressing: *Management and access of partly structured data, heterogeneous and distributed in an open environment. *Access control and protection of private medical data. *Control of workflows implied in complex computing process on grid infrastructures. *Extraction and quantification of relevant parameters for different pathologies: Multiple sclerosis, Brain Vascular Stroke, Brain tumors Four application pipelines have been proposed in the context of the project. The pipelines are formalized using the Scufl data flow language. *Multiple Sclerosis image analysis pipelines *Brain Stroke application pipeline (from GIN) *Stroke / tumours Anacom application pipeline (from IFR49) Different softwares developed and/or used in this project are presented.
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