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谷氨酸诱导的兴奋性毒性导致帕金森病多巴胺能神经元丧失的计算模型。

A Computational Model of Loss of Dopaminergic Cells in Parkinson's Disease Due to Glutamate-Induced Excitotoxicity.

机构信息

Computational Neuroscience Lab, Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, IIT-Madras, Chennai, India.

Department of Psychiatry, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, United Kingdom.

出版信息

Front Neural Circuits. 2019 Feb 25;13:11. doi: 10.3389/fncir.2019.00011. eCollection 2019.

Abstract

Parkinson's disease (PD) is a neurodegenerative disease associated with progressive and inexorable loss of dopaminergic cells in Substantia Nigra pars compacta (SNc). Although many mechanisms have been suggested, a decisive root cause of this cell loss is unknown. A couple of the proposed mechanisms, however, show potential for the development of a novel line of PD therapeutics. One of these mechanisms is the peculiar metabolic vulnerability of SNc cells compared to other dopaminergic clusters; the other is the SubThalamic Nucleus (STN)-induced excitotoxicity in SNc. To investigate the latter hypothesis computationally, we developed a spiking neuron network-model of SNc-STN-GPe system. In the model, prolonged stimulation of SNc cells by an overactive STN leads to an increase in 'stress' variable; when the stress in a SNc neuron exceeds a stress threshold, the neuron dies. The model shows that the interaction between SNc and STN involves a positive-feedback due to which, an initial loss of SNc cells that crosses a threshold causes a runaway-effect, leading to an inexorable loss of SNc cells, strongly resembling the process of neurodegeneration. The model further suggests a link between the two aforementioned mechanisms of SNc cell loss. Our simulation results show that the excitotoxic cause of SNc cell loss might initiate by weak-excitotoxicity mediated by energy deficit, followed by strong-excitotoxicity, mediated by a disinhibited STN. A variety of conventional therapies were simulated to test their efficacy in slowing down SNc cell loss. Among them, glutamate inhibition, dopamine restoration, subthalamotomy and deep brain stimulation showed superior neuroprotective-effects in the proposed model.

摘要

帕金森病(PD)是一种与黑质致密部(SNc)多巴胺能细胞进行性和不可逆转丧失相关的神经退行性疾病。尽管已经提出了许多机制,但这种细胞丧失的决定性根本原因尚不清楚。然而,一些提出的机制显示出开发新的 PD 治疗方法的潜力。其中一个机制是与其他多巴胺能簇相比,SNc 细胞的特殊代谢脆弱性;另一个是丘脑下核(STN)对 SNc 的兴奋性毒性。为了在计算上研究后者的假设,我们开发了一个涉及 SNc-STN-GPe 系统的放电神经元网络模型。在该模型中,过度活跃的 STN 对 SNc 细胞的长期刺激会导致“应激”变量增加;当 SNc 神经元中的应激超过应激阈值时,神经元就会死亡。该模型表明,SNc 和 STN 之间的相互作用涉及正反馈,由于这种正反馈,初始的 SNc 细胞丧失超过阈值会导致失控效应,导致 SNc 细胞不可避免地丧失,这与神经退行性过程非常相似。该模型进一步表明了 SNc 细胞丧失的两种上述机制之间的联系。我们的模拟结果表明,SNc 细胞丧失的兴奋性毒性原因可能由能量不足介导的弱兴奋性毒性引发,随后是由去抑制的 STN 介导的强兴奋性毒性。模拟了各种常规疗法来测试它们减缓 SNc 细胞丧失的疗效。其中,谷氨酸抑制、多巴胺恢复、丘脑下核切开术和深部脑刺激在提出的模型中显示出更好的神经保护作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f14e/6397878/13c7e36e408f/fncir-13-00011-g0001.jpg

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