Neuroscience
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The aim of this study was to investigate the effect of paradoxical sleep deprivation (PSD) on the BDNF-related miRNA expression in ovariectomized (OVX) rats. The animals were randomly divided into eight groups (control, PSD, wide platform, sham surgery, anti-miR-191, anti-miR-191/PSD, scrambled and PSD in intact). Bilateral-ovariectomy was performed one month before the experiment in the OVX rats. ⋯ Intracerebroventricular (ICV) injection of anti-miR-191a improved the down-regulation of BDNF and attenuated PSD-induced cognitive impairment. Hippocampal BDNF is probably one of the targets of miR-191a in sleep-deprived OVX rats. Our results suggest that miR-191a may be increased in the sleep-deprived OVX rats to regulate BDNF levels.
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Accumulating evidence suggests that glutamatergic signaling and synaptic plasticity underlie one of a number of ways psychiatric disorders appear. The present study reveals a possible mechanism by which this occurs, through highlighting the importance of LMTK3, in the brain. Behavioral analysis of Lmtk3-KO mice revealed a number of abnormalities that have been linked to psychiatric disease such as hyper-sociability, PPI deficits and cognitive dysfunction. ⋯ As synaptic dysfunction is implicated in human psychiatric disease, we analyzed the LTP of Lmtk3-KO mice and found that induction is severely impaired. Further investigation revealed abnormalities in GluA1 trafficking after AMPA stimulation in Lmtk3-KO neurons, along with a reduction in GluA1 expression in the post-synaptic density. Therefore, we hypothesize that LMTK3 is an important factor involved in the trafficking of GluA1 during LTP, and that disruption of this pathway contributes to the appearance of behavior associated with human psychiatric disease in mice.
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Trigeminal neuropathic pain (TGN) is an attacking, abrupt, electric-shock headache involving abnormal cortical activity. The neural mechanism underlying TGN remains elusive. In this study, we explored the role of microglia in the primary somatosensory barrel cortex (S1BF), which is a critical region for TGN, of a mouse model of TGN that displayed significant pain-related behaviors. ⋯ In addition, we found that microglia in the S1BF (microgliaS1BF) were significantly activated, with density and morphology changes. Intraperitoneal administration of minocycline, a microglia inhibitor, attenuated pain sensitization, and decreased GluS1BF neuronal activity. Together, these findings demonstrate the putative importance of microglia as a key regulator in TGN through actions on GluS1BF neuronal adaptation.
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Computer-aided diagnosis has become a widely-used auxiliary tool for the diagnosis of Alzheimer's disease (AD). In this study, we developed an extreme learning machine (ELM) model to discriminate between patients with AD and normal controls (NCs) using voxel-based morphometry (VBM) obtained from magnetic resonance imaging. Support vector machine (SVM), Gaussian process regression (GPR), and partial least squares (PLS) regression were compared with the ELM model. ⋯ We applied the proposed methods to data from 58 patients with AD and 94 NCs, and achieved a classification accuracy of up to 0.96 with all classification features of the ELM model, while the results of the other three models were 0.82 (PLS), 0.79 (GPR), and 0.75 (SVM). Furthermore, the effect of VBM parameter modeling is better than texture parameter. Thus, our method was optimal in distinguishing patients with AD from NCs, and may therefore be useful for the diagnosis of AD.
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An important prerequisite for the analysis of spike synchrony in extracellular recordings is the extraction of single-unit activity from the multi-unit signal. To identify single units, potential spikes are separated with respect to their potential neuronal origins ('spike sorting'). However, different sorting algorithms yield inconsistent unit assignments, which seriously influences subsequent spike train analyses. ⋯ If the latter is less important ('clean' data) the K-Means algorithm is a better option. Our results strongly argue for the need of standardized validation procedures based on ground truth data. The recipe suggested here is simple enough to become a standard procedure.