Droplet-based magnetically activated cell separation

Y. H. Kim, S. Hong, B. Kim, S. Yun, Y. R. Kang, K. K. Paek, J. W. Lee, S. H. Lee, B. K. Ju

Research output: Contribution to journalConference article

3 Citations (Scopus)

Abstract

In this study, we developed a method that target cells in suspension can be separated by combining magnetic force and gravitation force. Since the newly developed method involves a separating process of a droplet containing non-target cells in suspension by applying magnetic force to separate target cells, we called it droplet-based magnetic activated cell sorting (dMACS). To demonstrate the efficiency of the dMACS system, Ter119 (+) cells from mouse bone marrow cells were separated by both conventional MACS and our dMACS systems. Effects of three parameters on separation efficiency were examined in the dMACS system. As a result, both volume of droplet of cell suspension, and magnetic force did not affect the efficiency of cell separation markedly. However, the time for cell settlement in the droplet showed a critical role in the efficiency of cell separation according to increasing time. Therefore, we tried to verify that the saturation time affected increase of its efficiency and that flow rate injected to get rid of the negative cell resulted in the decrease of its efficiency. Using this dMACS system, we were able to pinpoint that the flow rate of cell suspension injected into a magnetic platform results in disturbance in the droplet, leading to turbulence in the cell suspension.

Original languageEnglish
Pages (from-to)2575-2578
Number of pages4
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume26 IV
Publication statusPublished - 2004
EventConference Proceedings - 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2004 - San Francisco, CA, United States
Duration: 2004 Sep 12004 Sep 5

Keywords

  • Cell separation
  • Droplet
  • MACS
  • Magnet

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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