Neuroscience
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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.
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Presbycusis, or age-related hearing loss (ARHL), is primarily associated with sensory or transduction nerve cell degeneration in the peripheral and/or central auditory systems. During aging, the auditory system shows mitochondrial dysfunction and increased inflammatory responses. Mitochondrial dysfunction promotes leakage of mitochondrial DNA (mtDNA) into the cytosol, which activates the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway to induce type I interferon and inflammatory responses. ⋯ The results showed that cGAS-positive immunoreactive cells were observed in the cochlea, inferior colliculus, and auditory cortex. Levels of cytosolic mtDNA, cGAS, STING, phosphorylated interferon regulatory factor 3, and cytokines were significantly increased in the cochlea, inferior colliculus, and auditory cortex of 6-, 9-, and 12-month-old mice compared with 3-month-old mice. These findings suggested that cytosolic mtDNA may play an important role in the pathogenesis of ARHL by activating cGAS-STING-mediated type I interferon and inflammatory responses.
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The widespread application of ionizing radiation in industrial and medical fields leads to the increased brain exposure to X-rays. Radiation brain injury (RBI) seriously affects health of patients by causing cognitive dysfunction and neuroinflammation. However, the link between X-ray exposure and depressive symptoms and their detailed underlying mechanisms have not been well studied. ⋯ Moreover, X-ray exposure increased the expression of HMGB1, activated NLRP3 inflammasome signaling pathway and microglial cells, and then facilitated the release of pro-inflammatory cytokines, resulting in the pyroptosis and neuron loss both in vivo and in vitro. Additionally, glycyrrhizin (Gly), which is a HMGB1 inhibitor, reversed X-ray-induced behavioral changes and neuronal damage. Our findings indicated that HMGB1-mediated pyroptosis was involved in radiation-induced depression.
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Fragmentation of the daily sleep-wake rhythm with increased nighttime awakenings and more daytime naps is correlated with the risk of development of Alzheimer's disease (AD). To explore whether a causal relationship underlies this correlation, the present study tested the hypothesis that chronic fragmentation of the daily sleep-wake rhythm stimulates brain amyloid-beta (Aβ) levels and neuroinflammation in the 3xTg-AD mouse model of AD. Female 3xTg-AD mice were allowed to sleep undisturbed or were subjected to chronic sleep fragmentation consisting of four daily sessions of enforced wakefulness (one hour each) evenly distributed during the light phase, five days a week for four weeks. ⋯ Sleep fragmentation also stimulated neuroinflammation as shown by increased expression of markers of microglial activation and proinflammatory cytokines measured by q-RT-PCR analysis of hippocampal samples. No significant effects of sleep fragmentation on Aβ, tau, or neuroinflammation were observed in the cerebral cortex. These studies support the concept that improving sleep consolidation in individuals at risk for AD may be beneficial for slowing the onset or progression of this devastating neurodegenerative disease.