Liang, Hongyan and Zhang, Yi and Chen, Deyong and Li, Yueying and Wang, Yixiang and Wang, Junbo and Chen, Jian (2022) Development of microfluidic flow cytometry capable of characterization of single-cell intrinsic structural and electrical parameters. Journal of Micromechanics and Microengineering, 32 (3). 035007. ISSN 0960-1317
Liang_2022_J._Micromech._Microeng._32_035007.pdf - Published Version
Download (18MB)
Abstract
Although single-cell intrinsic structural and electrical parameters (e.g. Dc of cell diameter, Dn of nuclear diameter, σcy of cytoplasmic conductivity and Csm of specific membrane capacitance) are promising for cell-type classification, they cannot be obtained simultaneously due to structural limitations of previously reported flow cytometry. This paper presented a microfluidic flow cytometry made of a double T-type constriction channel plus a predefined fluorescence detection domain, capable of high-throughput characterizing single-cell Dc, Dn, σcy and Csm leveraging a home-developed impedance-fluorescence model. As a demonstration, the microfluidic platform quantified Dc, Dn, σcy and Csm from ∼10 000 individual cells of three well-established tumor cell lines of A549, SW620 and HeLa where successful rates of cell-type classification were estimated as 54.5 ± 1.3% (Dc), 68.9 ± 6.8% (Dc + Dn) and 84.8 ± 4.4% (Dc, Dn, σcy + Csm) based on neural pattern recognition. Then Dc, Dn, σcy and Csm derived from ∼10 000 single cells of K562 vs Jurkat of leukemia and SACC-LM vs CAL 27 of oral tumor were quantified and compared, where successful rates of cell-type classification were estimated as 87.3% (K562 vs Jurkat) and 79.5% (SACC-LM vs CAL 27), respectively. In summary, the microfluidic platform reported in this study could quantify single-cell intrinsic structural and electrical parameters simultaneously, leading to significant increases in successful rates of cell-type classification.
Item Type: | Article |
---|---|
Subjects: | OA Library Press > Multidisciplinary |
Depositing User: | Unnamed user with email support@oalibrarypress.com |
Date Deposited: | 09 Jun 2023 05:53 |
Last Modified: | 18 Jun 2024 07:13 |
URI: | http://archive.submissionwrite.com/id/eprint/1140 |