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Cited by 680

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Separation of human breast cancer cells from blood by differential dielectric affinity.

Open access
Becker, F F, Wang, X B, Huang, Y, Pethig, R, Vykoukal, J, Gascoyne, P R·1995·Proceedings of the National Academy of Sciences

Abstract

Electrorotation measurements were used to demonstrate that the dielectric properties of the metastatic human breast cancer cell line MDA231 were significantly different from those of erythrocytes and T lymphocytes. These dielectric differences were exploited to separate the cancer cells from normal blood cells by appropriately balancing the hydrodynamic and dielectrophoretic forces acting on the cells within a dielectric affinity column containing a microelectrode array. The operational criteria for successful particle separation in such a column are analyzed and our findings indicate that the dielectric affinity technique may prove useful in a wide variety of cell separation and characterization applications.

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Crossref · 10.1073/pnas.92.3.860

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Metadata

Authors
Becker, F. F., Wang, X. B., Huang, Y., Pethig, R., Vykoukal, J., & Gascoyne, P. R.
Venue
Proceedings of the National Academy of Sciences
Published
1995-01-31
Volume
92
Issue
3
Pages
860-864
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2060040620
Cited by
680
References
1
FWCI
11.94
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Separation of human breast cancer cells from blood by differential dielectric affinity. https://app.cochat.ai/papers/10.1073/pnas.92.3.860
The paper
Becker, F. F., Wang, X. B., Huang, Y., Pethig, R., Vykoukal, J., & Gascoyne, P. R. (1995). Separation of human breast cancer cells from blood by differential dielectric affinity. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.92.3.860

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.