Previously, we demonstrated that the immediate administration of multitarget anxiolytic afobazole slows down the progression of neuronal damage in a 6-hydroxidodamine (6-OHDA) model of Parkinson's disease due to the activation of chaperone Sigma1R. The aim of the present study is to evaluate the therapeutic potential of deferred afobazole administration in this model. Male ICR mice received a unilateral 6-OHDA lesion of the striatum. Fourteen days after the surgery, mice were treated with afobazole, selective Sigma1R agonist PRE-084, selective Sigma1R antagonist BD-1047, and a combination of BD-1047 with afobazole or PRE-084 for another 14 days. The deferred administration of afobazole restored the intrastriatal dopamine content in the 6-OHDA-lesioned striatum and facilitated motor behavior in rotarod tests. The action of afobazole accorded with the effect of Sigma1R selective agonist PRE-084 and was blocked by Sigma1R selective antagonist BD-1047. The present study illustrates the Sigma1R-dependent effects of afobazole in a 6-OHDA model of Parkinson's disease and reveals the therapeutic potential of Sigma1R agonists in treatment of the condition.
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http://dx.doi.org/10.3390/ijms21207620 | DOI Listing |
Cell-type-specific activation of parvalbumin (PV)-expressing neurons in the external globus pallidus (GPe) through optogenetics has shown promise in facilitating long-lasting movement dysfunction recovery in mice with Parkinson's disease. However, its translational potential is hindered by adverse effects stemming from the invasive implantation of optical fibers into the brain. In this study, we have developed a non-invasive optogenetics approach, utilizing focused ultrasound-triggered mechanoluminescent nanotransducers to enable remote photon delivery deep in the brain for genetically targeted neuromodulation.
View Article and Find Full Text PDFKorean J Neurotrauma
December 2024
Department of Neurosurgery, Chungnam National University Hospital, Chungnam National University School of Medicine, Daejeon, Korea.
Front Med (Lausanne)
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Software Engineering Department, LUT University, Lahti, Finland.
Introduction: Neurodegenerative diseases, including Parkinson's, Alzheimer's, and epilepsy, pose significant diagnostic and treatment challenges due to their complexity and the gradual degeneration of central nervous system structures. This study introduces a deep learning framework designed to automate neuro-diagnostics, addressing the limitations of current manual interpretation methods, which are often time-consuming and prone to variability.
Methods: We propose a specialized deep convolutional neural network (DCNN) framework aimed at detecting and classifying neurological anomalies in MRI data.
Cogn Neurodyn
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Department of Physiology, School of Basic Medical Sciences, Chengdu Medical College, Sichuan, 610500 China.
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View Article and Find Full Text PDFBioinform Adv
December 2024
Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL 32611, United States.
Motivation: Network motif identification (MI) problem aims to find topological patterns in biological networks. Identifying disjoint motifs is a computationally challenging problem using classical computers. Quantum computers enable solving high complexity problems which do not scale using classical computers.
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