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Biotarget
Article
License: CC BY NC ND
Data sources: UnpayWall
Biotarget
Article . 2017 . Peer-reviewed
Data sources: Crossref
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Biotargets in neural regeneration

Authors: Qingqing Fang; Tongtong Xu; Changyue Wu; Songlin Zhou; Hualin Sun;

Biotargets in neural regeneration

Abstract

The peripheral nervous system (PNS) exhibits a much larger capacity for regeneration than the central nervous system (CNS). The main reason is that the neurons in PNS still have certain intrinsic capacity for regeneration and the Schwann cells in PNS provide a suitable regeneration microenvironment. Factors that enhance the intrinsic growth potential of adult neurons are key players in the successful repair and regeneration of neurons following injury. Therefore, the full understanding of the mechanism of peripheral nerve regeneration will help us to solve the problems encountered in CNS regeneration. In this review, a number of intrinsic regeneration-promoting mechanisms have been described, including the role of transcription factors [signal transducers and activators of transcription 3 (STAT3), activating transcription factor 3 (ATF3), c-Jun, cyclic AMP response element binding protein (CREB) and Sox] in neuronal regeneration, the regulating factors [the phosphatase and tensin homolog (PTEN)-mTOR, PI3K-glycogen synthesis kinase 3 (GSK3), suppressor of cytokine signaling 3 (SOCS 3), histone deacetylases 5 (HDAC5) and reactive oxygen species (ROS)] for neuronal regeneration, the regulation of non-coding RNA [microRNAs (miRNAs), long-chain non-coding RNAs (lncRNAs) and circular RNAs (circRNAs)] in neuronal regeneration, the regulation of regeneration pathway in neural regeneration and the exosomes in neural regeneration. Finally, the prospect of neural regeneration was discussed, which contributes to greatly broaden the way to study the ability of nerve regeneration, identify more key biotarget molecules in neuronal regeneration, and provide innovative strategies to trigger and enhance the nerve regeneration.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Average
Average
Top 10%
hybrid