Optimization techniques in microfluidic impedance cytometry toward bacteria and submicron particles analysis-A review

Area of Science:

• Biophysics
• Biotechnology
• Analytical Chemistry

Background:

• Single-cell analysis is crucial for understanding cellular heterogeneity in biomedical research.
• Microfluidic impedance cytometry (MIC) is a powerful technique for single-cell analysis, clinical diagnostics, and at-home testing.
• Current MIC applications include detecting cancer cells, blood cells, and bacteria, but submicron particle detection needs improvement.

Purpose of the Study:

• To review and examine optimization techniques for microfluidic impedance cytometry (MIC) systems.
• To provide feasible strategies for enhancing MIC's capability in detecting and classifying bacteria and submicron particles.
• To guide future development of MIC for improved single-cell and submicron particle analysis.

Main Methods:

• Review of current optimization techniques for MIC systems.
• Analysis of electrode layout, channel design, data processing algorithms, and excitation signals.
• Comparison of advantages and limitations of various optimization methods.

Main Results:

• Identified key aspects for MIC system optimization, including electrode layout, channel design, data processing, and excitation signals.
• Summarized and compared the strengths and weaknesses of different optimization approaches.
• Proposed strategies for effective bacteria and submicron particle detection and classification using MIC.

Conclusions:

• This review offers comprehensive insights for researchers in single-cell analysis, aiding in the development of MIC strategies for bacterial and submicron particle detection.
• It promotes the advancement of MIC systems and their analytical capabilities for submicron/nano-particles.
• The findings will benefit researchers studying bacteria, viruses, exosomes, and biological macromolecules through biophysical analysis.