Discovery of the correlation between the suspended membrane capacitance and adherent morphology of single cells enriching from clinical pleural effusion revealed by a microfluidic impedance flow cytometry

Luan, Xiaofeng; Li, Yuang; Zhao, Haiping; Sun, Shuhui; Yang, Fan; Zhang, Wenchang; Zhang, Lingqian; Li, Mingxiao; Wang, Jinghui; Zhi, Tian; Zhang, Lina; Zhao, Yang; Huang, Chengjun

doi:10.1016/j.snb.2022.132487

Cited by 5 publications

(3 citation statements)

References 35 publications

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“…After two hours of cerebral ischemia and 24 hours of reperfusion, neutrophils were collected and separated from the peripheral blood of the rats using gradient density centrifugation ( Supplementary data ). The separated neutrophils from MCAO and sham-operated rats were further utilized to characterize C sm and σ cyto using a high-throughput single-cell electrical property characterization method [ 7 ]. Single cells were driven to pass continuously through the cross-shaped constriction microchannel of the microfluidic impedance flow cytometer accompanied by impedance monitoring.…”

Section: Characterization Of C Sm and σ ...mentioning

confidence: 99%

“…However, this method has limited clinical application for the prognosis of acute ischemic stroke due to the time-consuming labeling procedure. Recently, single cells' inherent electrical properties [ 5 ] (e.g., specific membrane capacitance (C sm ) and cytoplasmic resistance (σ cyto )) have been used to classify peripheral blood immune cells [ 6 ] and monitor changes in the tumor cell status [ 7 ] in a label-free manner.…”

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confidence: 99%

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Dynamic Detection of Specific Membrane Capacitance and Cytoplasmic Resistance of Neutrophils After Ischemic Stroke

Zhao¹,

Luan²,

Wang³

et al. 2023

Aging and disease

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Peripheral blood is the most readily available resource for stroke patient prognosis, but there is a lack of methods to detect dynamic changes of neutrophils in peripheral blood that can be used in the clinic. Herein, we developed a procedure to characterize dynamic changes of neutrophils based on their electrical properties in rats after transient middle cerebral artery occlusion (MCAO). We characterized the specific membrane capacitance (Csm) and cytoplasmic resistance (σcyto) of approximately 27,600 neutrophils from MCAO rats 24 h after ischemia/reperfusion. We found that the Csm and σcyto of neutrophils in the MCAO group were significantly higher compared to the sham group. Furthermore, we observed a monotonically upward shift in neutrophil Csm in the MCAO group during the four 5-minute test cycles. Our findings suggest that the dynamic changes of cellular electrical properties could reflect neutrophil activity and serve as a prognostic indicator for ischemic stroke in the clinical setting.

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Section: Characterization Of C Sm and σ ...mentioning

confidence: 99%

mentioning

confidence: 99%

Dynamic Detection of Specific Membrane Capacitance and Cytoplasmic Resistance of Neutrophils After Ischemic Stroke

Zhao¹,

Luan²,

Wang³

et al. 2023

Aging and disease

Self Cite

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“…12 By optimizing the excitation frequency, cell viability investigation, 13 cell status monitoring, 14 and stem cell differentiation monitoring 15 were achieved. Moreover, IFC measurement under multifrequency excitation can eliminate the influence of cell size and be applied to cell differentiation on different types of cells 16 (e.g., tumor cell analysis 17 ). Multifrequency measurements provide a prospective direction for the miniaturized total analysis of biological samples based on electrical characteristics (e.g., identification of tumor cell subtypes, 18 detection in blood samples, 19 and research on cell heterogeneity 20 ).…”

Section: ■ Introductionmentioning

confidence: 99%

Convolutional Neural Network-Driven Impedance Flow Cytometry for Accurate Bacterial Differentiation

Zhang,

Han,

et al. 2024

Anal. Chem.

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Impedance flow cytometry (IFC) has been demonstrated to be an efficient tool for label-free bacterial investigation to obtain the electrical properties in real time. However, the accurate differentiation of different species of bacteria by IFC technology remains a challenge owing to the insignificant differences in data. Here, we developed a convolutional neural networks (ConvNet) deep learning approach to enhance the accuracy and efficiency of the IFC toward distinguishing various species of bacteria. First, more than 1 million sets of impedance data (comprising 42 characteristic features for each set) of various groups of bacteria were trained by the ConvNet model. To improve the efficiency for data analysis, the Spearman correlation coefficient and the mean decrease accuracy of the random forest algorithm were introduced to eliminate feature interaction and extract the opacity of impedance related to the bacterial wall and membrane structure as the predominant features in bacterial differentiation. Moreover, the 25 optimized features were selected with differentiation accuracies of >96% for three groups of bacteria (bacilli, cocci, and vibrio) and >95% for two species of bacilli (Escherichia coli and Salmonella enteritidis), compared to machine learning algorithms (complex tree, linear discriminant, and K-nearest neighbor algorithms) with a maximum accuracy of 76.4%. Furthermore, bacterial differentiation was achieved on spiked samples of different species with different mixing ratios. The proposed ConvNet deep learning-assisted data analysis method of IFC exhibits advantages in analyzing a huge number of data sets with capacity for extracting predominant features within multicomponent information and will bring about progress and advances in the fields of both biosensing and data analysis.

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A review on intelligent impedance cytometry systems: Development, applications and advances

Tang,

Julian,

et al. 2023

Analytica Chimica Acta

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Discovery of the correlation between the suspended membrane capacitance and adherent morphology of single cells enriching from clinical pleural effusion revealed by a microfluidic impedance flow cytometry

Cited by 5 publications

References 35 publications

Dynamic Detection of Specific Membrane Capacitance and Cytoplasmic Resistance of Neutrophils After Ischemic Stroke

Dynamic Detection of Specific Membrane Capacitance and Cytoplasmic Resistance of Neutrophils After Ischemic Stroke

Convolutional Neural Network-Driven Impedance Flow Cytometry for Accurate Bacterial Differentiation

A review on intelligent impedance cytometry systems: Development, applications and advances

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