(251o) Numerical Model of Streaming DEP for Stem Cell Sorting | AIChE

(251o) Numerical Model of Streaming DEP for Stem Cell Sorting

Authors 

Natu, R. - Presenter, Clemson University
Martinez-Duarte, R., Clemson University
Neural stem cells are of special interest due to their potential in neurogenesis to treat spinal cord injuries, in promoting brain repair and other nervous disorders.[1,2] Current common methods used to quantitatively characterize stem cells include fluorescence activated cell sorting, (FACS) [3], magnetic bead-coupled cell separation[4] and micropipette aspiration [5]. These are limited due to the lack of antigens and labels that are specific enough to stem cells of interest. Dielectrophoresis is a label free separation technique that has been recently demonstrated for the enrichment of neural stem/progenitor cells using the membrane capacitance of the cell as the distinguishing factor[6]. Here we use numerical simulation to investigate the use of streaming DEP for the continuous sorting of neural stem/progenitor cells. The aim is at understanding how select device and experimental variables affect the throughput and efficiency while continuously sorting SC27 stem cells, neurogenic progenitor, from SC23 cells, an astrogenic progenitor. The sorting is studied by characterizing the width of the stream obtained for these cells with a purity �98% for continuous separation. The variables studied here are electrode cross section shape (circle, lens and diamonds), height (10, 50 and 100% of the channel height), the flow rate (200-2000 µl/min) and the cell concentration (103 to 105 cells/ml). Based on the results of the simulation, a device is proposed to retrieve the streams.

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