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Identification of neural stem and progenitor cell subpopulations using DC insulator-based dielectrophoresis.
Liu, Yameng; Jiang, Alan; Kim, Estelle; Ro, Clarissa; Adams, Tayloria; Flanagan, Lisa A; Taylor, Thomas J; Hayes, Mark A.
Afiliação
  • Liu Y; School of Molecular Sciences, Arizona State University, Tempe, Arizona, USA. mhayes@asu.edu.
Analyst ; 144(13): 4066-4072, 2019 Jul 07.
Article em En | MEDLINE | ID: mdl-31165125
Neural stem and progenitor cells (NSPCs) are an extremely important group of cells that form the central nervous system during development and have the potential to repair damage in conditions such as stroke impairment, spinal cord injury and Parkinson's disease degradation. Current schemes for separation of NSPCs are inadequate due to the complexity and diversity of cells in the population and lack sufficient markers to distinguish diverse cell types. This study presents an unbiased high-resolution separation and characterization of NSPC subpopulations using direct current insulator-based dielectrophoresis (DC-iDEP). The properties of the cells were identified by the ratio of electrokinetic (EK) to dielectrophoretic (DEP) mobilities. The ratio factor of NSPCs showed more heterogeneity variance (SD = 3.4-3.9) than the controlled more homogeneous human embryonic kidney cells (SD = 1.1), supporting the presence of distinct subpopulations of cells in NSPC cultures. This measure reflected NSPC fate potential since the ratio factor distribution of more neurogenic populations of NSPCs was distinct from the distribution of astrogenic NSPC populations (confidence level >99.9%). The abundance of NSPCs captured with different ranges of ratio of EK to DEP mobilities also exhibit final fate trends consistent with established final fates of the chosen samples. DC-iDEP is a novel, label-free and non-destructive method for differentiating and characterizing, and potentially separating, neural stem cell subpopulations that differ in fate.

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Ano de publicação: 2019 Tipo de documento: Article