Literature DB >> 32914827

Positional dependence of particles and cells in microfluidic electrical impedance flow cytometry: origin, challenges and opportunities.

Hugo Daguerre1, Miguel Solsona, Jonathan Cottet, Michaël Gauthier, Philippe Renaud, Aude Bolopion.   

Abstract

Microfluidic electrical impedance flow cytometry is now a well-known and established method for single-cell analysis. Given the richness of the information provided by impedance measurements, this non-invasive and label-free approach can be used in a wide field of applications ranging from simple cell counting to disease diagnostics. One of its major limitations is the variation of the impedance signal with the position of the cell in the sensing area. Indeed, identical particles traveling along different trajectories do not result in the same data. The positional dependence can be considered as a challenge for the accuracy of microfluidic impedance cytometers. On the other hand, it has recently been regarded by several groups as an opportunity to estimate the position of particles in the microchannel and thus take a further step in the logic of integrating sensors in so-called "Lab-on-a-chip" devices. This review provides a comprehensive overview of the physical grounds of the positional dependence of impedance measurements. Then, both the developed strategies to reduce position influence in impedance-based assays and the recent reported technologies exploiting that dependence for the integration of position detection in microfluidic devices are reviewed.

Mesh:

Year:  2020        PMID: 32914827     DOI: 10.1039/d0lc00616e

Source DB:  PubMed          Journal:  Lab Chip        ISSN: 1473-0189            Impact factor:   6.799


  3 in total

1.  Investigating Cell-Particle Conjugate Orientations in a Microfluidic Channel to Ameliorate Impedance-based Signal Acquisition and Detection.

Authors:  Brandon K Ashley; Ishika Mukerji; Umer Hassan
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2021-11

2.  Single-cell microfluidic impedance cytometry: from raw signals to cell phenotypes using data analytics.

Authors:  Carlos Honrado; Paolo Bisegna; Nathan S Swami; Federica Caselli
Journal:  Lab Chip       Date:  2021-01-05       Impact factor: 6.799

Review 3.  Recent Advances in Electrical Impedance Sensing Technology for Single-Cell Analysis.

Authors:  Zhao Zhang; Xiaowen Huang; Ke Liu; Tiancong Lan; Zixin Wang; Zhen Zhu
Journal:  Biosensors (Basel)       Date:  2021-11-22
  3 in total

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