piRT-IFC: Physics-informed real-time impedance flow cytometry for the characterization of cellular intrinsic electrical properties

doi:10.1038/s41378-023-00545-9

	piRT-IFC: Physics-informed real-time impedance flow cytometry for the characterization of cellular intrinsic electrical properties
	Luan, Xiaofeng 1,2; Liu, Pengbin 1,2; Huang, Di 3; Zhao, Haiping 4; Li, Yuang 1,2; Sun, Sheng 1,2; Zhang, Wenchang 1; Zhang, Lingqian 1; Li, Mingxiao 1; Zhi, Tian 3; Zhao, Yang 1; Huang, Chengjun 1,2
	2023-06-08
发表期刊	MICROSYSTEMS & NANOENGINEERING
ISSN	2055-7434
卷号	9 期号:1 页码:10
摘要	Real-time transformation was important for the practical implementation of impedance flow cytometry. The major obstacle was the time-consuming step of translating raw data to cellular intrinsic electrical properties (e.g., specific membrane capacitance C-sm and cytoplasm conductivity s(cyto)). Although optimization strategies such as neural network-aided strategies were recently reported to provide an impressive boost to the translation process, simultaneously achieving high speed, accuracy, and generalization capability is still challenging. To this end, we proposed a fast parallel physical fitting solver that could characterize single cells' C-sm and s(cyto) within 0.62 ms/cell without any data preacquisition or pretraining requirements. We achieved the 27000-fold acceleration without loss of accuracy compared with the traditional solver. Based on the solver, we implemented physics-informed real-time impedance flow cytometry (piRT-IFC), which was able to characterize up to 100,902 cells' C-sm and s(cyto) within 50 min in a real-time manner. Compared to the fully connected neural network (FCNN) predictor, the proposed real-time solver showed comparable processing speed but higher accuracy. Furthermore, we used a neutrophil degranulation cell model to represent tasks to test unfamiliar samples without data for pretraining. After being treated with cytochalasin B and N-Formyl-Met-Leu-Phe, HL-60 cells underwent dynamic degranulation processes, and we characterized cell's C-sm and s(cyto) using piRT-IFC. Compared to the results from our solver, accuracy loss was observed in the results predicted by the FCNN, revealing the advantages of high speed, accuracy, and generalizability of the proposed piRT-IFC.
DOI	10.1038/s41378-023-00545-9
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China[2018YFC2001100] ; National Natural Science Foundation of China[62171441] ; State Key Laboratory of Computer Architecture (ICT, CAS)[CARCH202122]
WOS研究方向	Science & Technology - Other Topics ; Instruments & Instrumentation
WOS类目	Nanoscience & Nanotechnology ; Instruments & Instrumentation
WOS记录号	WOS:001003561700001
出版者	SPRINGERNATURE
引用统计	被引频次：2[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/21206
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Zhi, Tian; Zhao, Yang; Huang, Chengjun
作者单位	1.Chinese Acad Sci, Inst Microelect, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, Beijing, Peoples R China 4.Capital Med Univ, Xuanwu Hosp, Cerebrovasc Dis Res Inst, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Luan, Xiaofeng,Liu, Pengbin,Huang, Di,et al. piRT-IFC: Physics-informed real-time impedance flow cytometry for the characterization of cellular intrinsic electrical properties[J]. MICROSYSTEMS & NANOENGINEERING,2023,9(1):10.
APA	Luan, Xiaofeng.,Liu, Pengbin.,Huang, Di.,Zhao, Haiping.,Li, Yuang.,...&Huang, Chengjun.(2023).piRT-IFC: Physics-informed real-time impedance flow cytometry for the characterization of cellular intrinsic electrical properties.MICROSYSTEMS & NANOENGINEERING,9(1),10.
MLA	Luan, Xiaofeng,et al."piRT-IFC: Physics-informed real-time impedance flow cytometry for the characterization of cellular intrinsic electrical properties".MICROSYSTEMS & NANOENGINEERING 9.1(2023):10.