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Membrane Potential Controls Adipogenic and Osteogenic Differentiation of Mesenchymal Stem Cells

Overview of attention for article published in PLOS ONE, November 2008
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Title
Membrane Potential Controls Adipogenic and Osteogenic Differentiation of Mesenchymal Stem Cells
Published in
PLOS ONE, November 2008
DOI 10.1371/journal.pone.0003737
Pubmed ID
Authors

Sarah Sundelacruz, Michael Levin, David L. Kaplan

Abstract

Control of stem cell behavior is a crucial aspect of developmental biology and regenerative medicine. While the functional role of electrophysiology in stem cell biology is poorly understood, it has become clear that endogenous ion flows represent a powerful set of signals by means of which cell proliferation, differentiation, and migration can be controlled in regeneration and embryonic morphogenesis. We examined the membrane potential (V(mem)) changes exhibited by human mesenchymal stem cells (hMSCs) undergoing adipogenic (AD) and osteogenic (OS) differentiation, and uncovered a characteristic hyperpolarization of differentiated cells versus undifferentiated cells. Reversal of the progressive polarization via pharmacological modulation of transmembrane potential revealed that depolarization of hMSCs prevents differentiation. In contrast, treatment with hyperpolarizing reagents upregulated osteogenic markers. Taken together, these data suggest that the endogenous hyperpolarization is a functional determinant of hMSC differentiation and is a tractable control point for modulating stem cell function.

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The data shown below were compiled from readership statistics for 201 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 <1%
Netherlands 1 <1%
Germany 1 <1%
Peru 1 <1%
United States 1 <1%
Unknown 195 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 57 28%
Researcher 33 16%
Student > Master 25 12%
Student > Bachelor 15 7%
Student > Doctoral Student 13 6%
Other 37 18%
Unknown 21 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 55 27%
Engineering 30 15%
Biochemistry, Genetics and Molecular Biology 26 13%
Medicine and Dentistry 20 10%
Physics and Astronomy 8 4%
Other 32 16%
Unknown 30 15%