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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Accumulating evidence suggests that neuroinflammation is the main mechanism in cognitive dysfunction and that brain-derived neurotrophic factor (BDNF) is involved in learning and memory by binding to tyrosine kinase B (TrkB) receptors. Herein, we tested the roles of the BDNF-TrkB signaling pathway and its downstream cascade in lipopolysaccharide (LPS) induced cognitive dysfunction in mice. Mice were treated with LPS (0.25 mg/kg) for 7 days, and learning and memory function was evaluated by the novel object recognition test (NORT). ⋯ In the entorhinal cortex, the protein levels of BDNF, p-TrkB, Bcl-2, p-CaMK2 and p-CREB were decreased, and the protein level of Bax was increased in LPS mice. Interestingly, 7,8-DHF alleviated these disorders in LPS mice and improved learning and memory function; however, the TrkB antagonist ANA12 effectively reversed effects of 7,8-DHF. Therefore, we conclude that the BDNF-TrkB signaling pathway and its downstream cascades disorders in different regions are main mechanisms of cognitive dysfunction, and 7,8-DHF maybe useful as a new treatment for preventing or treating cognitive dysfunction induced by neuroinflammation in neurodegenerative diseases.
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Cervical spinal cord injury (cSCI) impairs neural drive to the respiratory muscles, causing life- threatening complications such as respiratory insufficiency and diminished airway protection. Repetitive "low dose" acute intermittent hypoxia (AIH) is a promising strategy to restore motor function in people with chronic SCI. Conversely, "high dose" chronic intermittent hypoxia (CIH; ∼8 h/night), such as experienced during sleep apnea, causes pathology. ⋯ However, CIH exerted complex effects depending on injury status. Whereas CIH increased A1 receptor expression in intact (not injured) rats, it increased A2A receptor expression in spinally injured (not intact) rats. The differential impact of CIH reinforces the concept that the injured spinal cord behaves in distinct ways from intact spinal cords, and that these differences should be considered in the design of experiments and/or new treatments for chronic cSCI.
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Increased expression of alpha-synuclein (ASYN) and decreased expression of Nurr1 are associated with Parkinson's disease (PD) pathogenesis. These two proteins interact functionally and ASYN overexpression suppresses Nurr1 levels. ASYN pan-neuronal overexpression coupled with Nurr1 hemizygosity followed by Nurr1 repression in aging mice results in the manifestation of a typical PD-related phenotype and pathology. ⋯ However, they displayed increased energy expenditure, reduced striatal dopamine (DA) and prolonged hyperactivity to a novel environment indicating impaired habituation. This DA-ergic dysfunction was observed in young adult '2-hit-DA' mice, persisted throughout life and it was associated with ASYN and Nurr1 synergistic alterations of DAT levels and function. Our experiments indicate that the expression levels of ASYN and Nurr1 are critical in the dysregulation of the nigrostriatal DA system and may be involved in neuropsychiatric aspects of PD.
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The unpredictability of epileptic seizures is one of the most problematic aspects of the field of epilepsy. Methods or devices capable of detecting seizures minutes before they occur may help prevent injury or even death and significantly improve the quality of life. Machine learning (ML) is an emerging technology that can markedly enhance algorithm performance by interpreting data. ⋯ While ML has good prospects with regard to detecting epileptic seizures via EEG signals, many clinicians are still unfamiliar with this field. This work briefly summarizes the history and recent significant progress made in this field and clarifies the essential components of the automatic seizure detection system using ML methodologies for clinicians. This review also proposes how neurologists can actively contribute to ensure improvements in seizure prediction using EEG-based ML.