Neuroscience
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Review
Lactate supply from astrocytes to neurons and its role in ischemic stroke-induced neurodegeneration.
Glucose transported to the brain is metabolized to lactate in astrocytes and supplied to neuronal cells via a monocarboxylic acid transporter (MCT). Lactate is used in neuronal cells for various functions, including learning and memory formation. Furthermore, lactate can block stroke-induced neurodegeneration. ⋯ These findings suggest that the lack of lactate supply may strongly contribute to hypoxia-induced neurodegeneration. Furthermore, diminished lactate supply from astrocytes could facilitate stroke-induced neurodegeneration. Therefore, astrocyte-derived lactate may contribute to stroke prevention.
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It is well known that neuroinflammation plays a key role in neurodegenerative diseases. Hypoxia-inducible factor (HIF) and its hydroxylases-Prolyl-4-hydroxyases (PHDs) have been found to modulate the inflammatory processes. Here, the effects of PHDs enzyme onlipopolysaccharide-induced neuroinflammation and neurocognitive deficits were investigated. ⋯ DMOG and PHD3knockout decreased expression of inflammatory cytokines and improved the metabolic reprogramming caused by LPS treatment. Furthermore, pretreatment of DMOG reversed learning and memory deficits in systemic LPS-exposed mice through anti-neuroinflammation, which is independent of DMOG angiogenesis. These findings suggested that PHD3 may mediate LPS-induced microglial activation and neuroinflammation-associated neurobehavioral deficits.
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Microglia serve as resident immune cells in the brain, responding to insults and pathological developments. They have also been implicated in shaping synaptic development and regulation. The present study examined microglial cell density in a number of brain regions across select postnatal (P) ages along with the effects of valproic acid (VPA) on microglia density. ⋯ Finally, animals treated with VPA at P60 exhibited decreased microglia density in the hippocampus only. These results suggest rapid VPA-induced increases in microglial cell density in a developmentally-regulated fashion which differs across distinct brain areas. Furthermore, in the context of prior reports that early VPA causes excitotoxic damage, the present findings suggest early VPA exposure may provide a model for studying altered microglial responses to early toxicant challenge.
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Electroencephalogram (EEG)-based quantitative pain measurement is valuable in the field of clinical pain treatment, providing objective pain intensity assessment especially for nonverbal patients who are unable to self-report. At present, a key challenge in modeling pain events from EEG is to find invariant representations for intra- and inter-subject variations, where current methods based on hand-crafted features cannot provide satisfactory results. Hence, we propose a novel method based on deep learning to learn such invariant representations from multi-channel EEG signals and demonstrate its great advantages in EEG-based pain classification tasks. ⋯ The proposed method aims to jointly preserve the spatial-spectral-temporal structures of EEG, for learning representations with high robustness against intra-subject and inter-subject variations, making it more conducive to multi-class and subject-independent scenarios. Empirical evaluation on 4-level pain intensity assessment within the subject-independent scenario demonstrated significant improvement over baseline and state-of-the-art methods in this field. Our approach applies deep neural networks (DNNs) to pain intensity assessment for the first time and demonstrates its potential advantages in modeling pain events from EEG.