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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The cerebrospinal fluid (CSF) movement and its influence on substance distribution and elimination from the CSF system have been thoroughly analyzed and discussed in the light of the new hypothesis of CSF physiology. As a result, CSF movement is not presented as a circulation, but a permanent rhythmic systolic-diastolic pulsation in all directions. Such movement also represents the main force of substance distribution inside the CSF system. ⋯ If a certain transport mechanism is not available at one site, the substance will be distributed by CSF movement along the CSF system and into the CNS region where that transport mechanism is available. Pharmacological manipulation suggests that the residence time and the substance travel distance along the CSF system depend on the capacity of transport mechanisms situated on CNS blood capillaries. Physiological absorption of the CSF into the venous sinuses and/or lymphatics, due to their small surface area, should be of minor importance in comparison with the huge absorptive surface area of the microvessel network.
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Subjective well-being (SWB) is closely related to our physical and mental health. Existing studies show that neural or genetic basis underpins individual difference in SWB. Moreover, researchers have found high enrichment of SWB-related mutations in the central nervous system, but the relationship between the genetic architecture of SWB and brain morphology has not been explored. ⋯ In whole-brain analyses, we found that a higher PGS was significantly associated with increased CT in the right superior temporal gyrus (STG) and GMV in the right insula, both of which are involved in social cognition and emotional processing. More importantly, these findings were repeatable at some different thresholds. The results may suggest that the brain morphology of right STG and insula is partly regulated by SWB-related genetic factors.
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GPR55, an atypical cannabinoid receptor activated by lysophosphatidylinositol (LPI) has been involved in various physiological and pathological processes. We examined the effect of GPR55 activation on rat brain microvascular endothelial cells (RBMVEC), an essential component of the blood-brain barrier (BBB). GPR55 was detected in RBMVEC by western blot and immunocytochemistry. ⋯ LPI decreased the electrical resistance of RBMVEC monolayer assessed with Electric Cell-Substrate Impedance Sensing (ECIS) in a dose-dependent manner. In vivo studies indicate that systemic administration of LPI increased the permeability of the BBB, assessed with Evans Blue method. Taken together, our results indicate that GPR55 activation modulates the function of endothelial cells of brain microvessels, produces a transient reduction in endothelial barrier function and increases BBB permeability.
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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.