Progress of reprogramming astrocytes into neuron

IF 2.6 3区 医学 Q3 NEUROSCIENCES
Sitong Liu , Ximing Xu , Emmanuel Omari-Siaw , Jiangnan Yu , Wenwen Deng
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引用次数: 0

Abstract

As the main players in the central nervous system (CNS), neurons dominate most life activities. However, after accidental trauma or neurodegenerative diseases, neurons are unable to regenerate themselves. The loss of this important role can seriously affect the quality of life of patients, ranging from movement disorders to disability and even death. There is no suitable treatment to prevent or reverse this process. Therefore, the regeneration of neurons after loss has been a major clinical problem and the key to treatment. Replacing the lost neurons by transdifferentiation of other cells is the only viable approach. Although much progress has been made in stem cell therapy, ethical issues, immune rejection, and limited cell sources still hinder its clinical application. In recent years, somatic cell reprogramming technology has brought a new dawn. Among them, astrocytes, as endogenously abundant cells homologous to neurons, have good potential and application value for reprogramming into neurons, having been reprogrammed into neurons in vitro and in vivo in a variety of ways.

将星形胶质细胞重编程为神经元的进展。
作为中枢神经系统(CNS)的主要角色,神经元主导着大多数生命活动。然而,在遭受意外创伤或患上神经退行性疾病后,神经元无法自我再生。失去这一重要作用会严重影响患者的生活质量,包括运动障碍、残疾甚至死亡。目前还没有合适的治疗方法来预防或逆转这一过程。因此,神经元缺失后的再生一直是一个重大的临床问题,也是治疗的关键。通过其他细胞的转分化来替代失去的神经元是唯一可行的方法。虽然干细胞治疗取得了很大进展,但伦理问题、免疫排斥和有限的细胞来源仍阻碍着干细胞的临床应用。近年来,体细胞重编程技术带来了新的曙光。其中,星形胶质细胞作为与神经元同源的内源性丰富细胞,在体外和体内通过多种方式重编程为神经元,具有很好的潜力和应用价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.60
自引率
0.00%
发文量
65
审稿时长
37 days
期刊介绍: Molecular and Cellular Neuroscience publishes original research of high significance covering all aspects of neurosciences indicated by the broadest interpretation of the journal''s title. In particular, the journal focuses on synaptic maintenance, de- and re-organization, neuron-glia communication, and de-/regenerative neurobiology. In addition, studies using animal models of disease with translational prospects and experimental approaches with backward validation of disease signatures from human patients are welcome.
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