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MEF2C Enhances Dopaminergic Neuron Differentiation of Human Embryonic Stem Cells in a Parkinsonian Rat Model

Overview of attention for article published in PLOS ONE, August 2011
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Title
MEF2C Enhances Dopaminergic Neuron Differentiation of Human Embryonic Stem Cells in a Parkinsonian Rat Model
Published in
PLOS ONE, August 2011
DOI 10.1371/journal.pone.0024027
Pubmed ID
Authors

Eun-Gyung Cho, Jeffrey D. Zaremba, Scott R. McKercher, Maria Talantova, Shichun Tu, Eliezer Masliah, Shing Fai Chan, Nobuki Nakanishi, Alexey Terskikh, Stuart A. Lipton

Abstract

Human embryonic stem cells (hESCs) can potentially differentiate into any cell type, including dopaminergic neurons to treat Parkinson's disease (PD), but hyperproliferation and tumor formation must be avoided. Accordingly, we use myocyte enhancer factor 2C (MEF2C) as a neurogenic and anti-apoptotic transcription factor to generate neurons from hESC-derived neural stem/progenitor cells (NPCs), thus avoiding hyperproliferation. Here, we report that forced expression of constitutively active MEF2C (MEF2CA) generates significantly greater numbers of neurons with dopaminergic properties in vitro. Conversely, RNAi knockdown of MEF2C in NPCs decreases neuronal differentiation and dendritic length. When we inject MEF2CA-programmed NPCs into 6-hydroxydopamine-lesioned parkinsonian rats in vivo, the transplanted cells survive well, differentiate into tyrosine hydroxylase-positive neurons, and improve behavioral deficits to a significantly greater degree than non-programmed cells. The enriched generation of dopaminergic neuronal lineages from hESCs by forced expression of MEF2CA in the proper context may prove valuable in cell-based therapy for CNS disorders such as PD.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 95 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 2%
United States 1 1%
Australia 1 1%
Unknown 91 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 24%
Researcher 20 21%
Student > Master 10 11%
Student > Bachelor 8 8%
Professor 4 4%
Other 17 18%
Unknown 13 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 35 37%
Neuroscience 17 18%
Biochemistry, Genetics and Molecular Biology 12 13%
Medicine and Dentistry 7 7%
Unspecified 3 3%
Other 7 7%
Unknown 14 15%