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A cell viability assessment method based on area-normalized impedance spectrum (ANIS).

Rongbiao Zhang1, Mingji Wei1, Shuohuan Chen1

  • 1School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, China.

Biosensors & Bioelectronics
|April 6, 2018
PubMed
Summary

The area-normalized impedance spectrum (ANIS) method offers a more stable and accurate way to assess cell viability compared to traditional electric cell-substrate impedance sensing (ECIS). ANIS reduces fluctuations and measurement noise, improving cell status assessment.

Keywords:
Area-normalized impedance spectrum (ANIS)Cell viability assessmentElectric cell-substrate impedance sensing (ECIS)Impedance sensing method

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Area of Science:

  • Cell biology
  • Biophysics
  • Biosensing technology

Background:

  • Electric cell-substrate impedance sensing (ECIS) is a standard technique for evaluating cell health.
  • ECIS is susceptible to frequency drifts influenced by culture conditions and circuit models.
  • Existing methods require improvements in stability and accuracy for reliable cell status assessment.

Purpose of the Study:

  • To introduce and validate the area-normalized impedance spectrum (ANIS) method for enhanced cell viability assessment.
  • To address the limitations of frequency drift and measurement noise in ECIS.
  • To demonstrate the superior stability and accuracy of ANIS over conventional impedance sensing.

Main Methods:

  • Developed the ANIS method, normalizing impedance spectrum area within a threshold (Zth) defined by a 2% impedance decline.
  • Compared the stability of ANIS and conventional impedance sensing by normalizing area and impedance.
  • Validated ANIS using Cell Count Kit-8 (CCK-8) assay and analyzed noise susceptibility.

Main Results:

  • ANIS exhibited smoother, less fluctuating normalized area compared to the wave-like normalized impedance.
  • ANIS showed a 2.4% increase in correlation index and a 4% decrease in maximum error versus the impedance sensing method.
  • ANIS demonstrated reduced sensitivity to random measurement noise compared to traditional ECIS.

Conclusions:

  • The ANIS method provides a more stable and accurate approach for assessing cell viability.
  • ANIS overcomes the limitations of frequency drift and measurement noise inherent in standard ECIS.
  • This novel method enhances the reliability of cell status monitoring in various biological applications.