Discrimination of normal skin fibroblast and malignant melanocytes using dielectrophoretic force and fluid-induced shear force

Shogo Miyata, Yuta Ojima

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Cell analysis is an important technology that is widely used for medical diagnosis in hospitals and cell engineering research. Among cell analysis technology, dielectrophoresis (DEP) is one of the most promising approaches for discriminating biological particles because this phenomena requires no labeling procedure with a fluorescent dye or magnetic beads. In this study, we developed a precise cell analysis system by evaluating the DEP force with a liquid flow system. The DEP forces acting on a cell was characterized using a microfluidic chamber containing an electrode-array and fluid-induced shear forces. On the basis of this characterization, the discrimination between healthy skin cells and cancer cells was performed using our novel DEP cell sorting system. As a result, the healthy cells and cancer cells could be distinguished even if the dielectrophoretic properties of those cells were similar.

Original languageEnglish
Title of host publicationWorld Automation Congress Proceedings
PublisherIEEE Computer Society
Pages109-113
Number of pages5
ISBN (Electronic)9781889335490
DOIs
Publication statusPublished - 2014 Oct 24
Event2014 World Automation Congress, WAC 2014 - Waikoloa, United States
Duration: 2014 Aug 32014 Aug 7

Publication series

NameWorld Automation Congress Proceedings
ISSN (Print)2154-4824
ISSN (Electronic)2154-4832

Other

Other2014 World Automation Congress, WAC 2014
CountryUnited States
CityWaikoloa
Period14/8/314/8/7

Keywords

  • formatting
  • insert
  • style
  • styling

ASJC Scopus subject areas

  • Control and Systems Engineering

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    Miyata, S., & Ojima, Y. (2014). Discrimination of normal skin fibroblast and malignant melanocytes using dielectrophoretic force and fluid-induced shear force. In World Automation Congress Proceedings (pp. 109-113). [6935706] (World Automation Congress Proceedings). IEEE Computer Society. https://doi.org/10.1109/WAC.2014.6935706