Brain and nerve = Shinkei kenkyū no shinpo
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Severe acute respiratory syndrome-correlated new coronavirus (SARS-Cov-2) continues to spread rapidly around the world. Reports regarding the neuropathy and myopathy associated with SARS-Cov-2 increase everyday. ⋯ When initiating clinical treatment for COVID-19, it is crutial to distinguish the peripheral neuropathy or myopathy caused directly or indirectly by SARS-Cov-2 from those caused by other conditions. In this review, we aimed to report the peripheral nerve and muscle disorders associated with SARS-Cov-2 and their possible underlying pathophysiological mechanisms.
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In patients with Alzheimer's disease, the brain interstitial space is an important place where amyloid-β oligomers and aggregates exist. Although tau aggregates are observed inside neurons, extracellular brain interstitial fluid tau has drawn attention because of increasing understanding of cell-to-cell propagation of tau aggregation. In this review, we summarize our current understanding of factors influencing brain interstitial fluid concentrations of amyloid-β and tau, mainly focusing on known epidemiological risk factors for Alzheimer's disease.
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Amyotrophic lateral sclerosis (ALS) is the most rapidly progressive motor neuron disease (MND) in adults, characterized by the selective death of motor neurons in the motor cortex, brainstem, and spinal cord. Riluzole and edaravone are the only approved drugs available in Japan to date. Approximately 10% of ALS cases are familial in rature, defined as the existence of disease-causing mutation. ⋯ This review article describes the clinical characteristics of familial ALS based on each disease-causing mutation. The pathomechanism of ALS including proteostasis, RNA metabolism, and axonal pathology are discussed in detail. We also reviewed the status of development of therapeutic strategies for familial ALS based on analysis of animal models and induced pluripotent stem cells.
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Artificial intelligence and brain science have kept a swinging relationship with opposing views: "Artificial realization of intelligence should be free from biological constraints" and "We should reverse-engineer the best existing implementation of intelligence." In this article, we first review today's achievements of artificial intelligence and its impacts on brain and life sciences. We then discuss how progresses in brain science can contribute to future developments in artificial intelligence.
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Half a century ago, cerebellar learning models based on a simple perceptron were proposed independently by Marr and Albus. Soon, these models were combined with Ito's flocculus hypothesis that the cerebellar flocculus controls the vestibulo-ocular reflex through teacher signal-dependent learning, and consequently integrated into the so-called Marr-Albus-Ito cerebellar learning hypothesis. Ten years later, Ito found the synaptic plasticity of long-term depression at cerebellar Purkinje cell synapses, which underlies cerebellar learning. ⋯ Artificial intelligence (AI) based on the neural network models originating from a simple perceptron, has now developed to deep learning. As the LSM model of the cerebellum is the counterpart of deep learning in the brain, the cerebellum is considered to be the origin of current AI. Finally, we discuss the impact of the evolution of AI on future clinical cerebellar neurology.