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Three-dimensional inertial focusing based impedance cytometer enabling high-accuracy characterization of electrical properties of tumor cells.

Authors :
Chen Ni
Mingqi Yang
Shuai Yang
Zhixian Zhu
Yao Chen
Lin Jiang
Nan Xiang
Source :
Lab on a Chip. 9/21/2024, Vol. 24 Issue 18, p4333-4343. 11p.
Publication Year :
2024

Abstract

The differences in the cross-sectional positions of cells in the detection area have a severe negative impact on achieving accurate characterization of the impedance spectra of cells. Herein, we proposed a threedimensional (3D) inertial focusing based impedance cytometer integrating sheath fluid compression and inertial focusing for the high-accuracy electrical characterization and identification of tumor cells. First, we studied the effects of the particle initial position and the sheath fluid compression on particle focusing. Then, the relationship of the particle height and the signal-to-noise ratio (SNR) of the impedance signal was explored. The results showed that efficient single-line focusing of 7–20 μm particles close to the electrodes was achieved and impedance signals with a high SNR and a low coefficient of variation (CV) were obtained. Finally, the electrical properties of three types of tumor cells (A549, MDA-MB-231, and UMUC-3 cells) were accurately characterized. Machine learning algorithms were implemented to accurately identify tumor cells based on the amplitude and phase opacities at multiple frequencies. Compared with traditional two-dimensional (2D) inertial focusing, the identification accuracy of A549, MDA-MB-231, and UM-UC-3 cells using our 3D inertial focusing increased by 57.5%, 36.4% and 36.6%, respectively. The impedance cytometer enables the detection of cells with a wide size range without causing clogging and obtains high SNR signals, improving applicability to different complex biological samples and cell identification accuracy. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14730197
Volume :
24
Issue :
18
Database :
Academic Search Index
Journal :
Lab on a Chip
Publication Type :
Academic Journal
Accession number :
179566068
Full Text :
https://doi.org/10.1039/d4lc00523f