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用于识别癫痫新治疗靶点的网络科学

Network science for the identification of novel therapeutic targets in epilepsy.

作者信息

Scott Rod C

机构信息

Department of Neurological Sciences, University of Vermont, Burlington, VT, USA; Neurosciences Unit, UCL Institute of Child Health, London, UK.

出版信息

F1000Res. 2016 May 16;5. doi: 10.12688/f1000research.8214.1. eCollection 2016.

Abstract

The quality of life of children with epilepsy is a function of seizures and associated cognitive and behavioral comorbidities. Current treatments are not successful at stopping seizures in approximately 30% of patients despite the introduction of multiple new antiepileptic drugs over the last decade. In addition, modification of seizures has only a modest impact on the comorbidities. Therefore, novel approaches to identify therapeutic targets that improve seizures and comorbidities are urgently required. The potential of network science as applied to genetic, local neural network, and global brain data is reviewed. Several examples of possible new therapeutic approaches defined using novel network tools are highlighted. Further study to translate the findings into clinical practice is now required.

摘要

癫痫患儿的生活质量取决于癫痫发作以及相关的认知和行为共病情况。尽管在过去十年中引入了多种新型抗癫痫药物,但目前的治疗方法仍无法使约30%的患者停止癫痫发作。此外,癫痫发作的改善对共病的影响也较为有限。因此,迫切需要新的方法来确定能够改善癫痫发作和共病的治疗靶点。本文综述了网络科学应用于基因、局部神经网络和全脑数据的潜力。重点介绍了使用新型网络工具定义的几种可能的新治疗方法实例。现在需要进一步研究将这些发现转化为临床实践。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1871/4870991/39a4c2013ee9/f1000research-5-8835-g0000.jpg

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