Determination of intrinsic cellular electrical and mechanical properties using micro/nano manipulation techniques

Abstract

Single-mode biophysical fingerprints have specific overlap when cell heterogeneity is analyzed. The cross-sensitivity between these parameters results in significant fuzzy intervals in cell phenotype classification based on one-dimensional features, making it difficult to accurately separate cell clusters with similar biophysical characteristics but different functional subgroups. Therefore, developing cross-scale multi-modal synchronous detection technology for live cell parameters and building a machine learning-based multi-dimensional parameter coupling analysis model will be a key path to breaking through the bottleneck in the accurate analysis of cell heterogeneity. Hence, this review presents five micro/nano manipulation methods for determining intrinsic cellular electrical and mechanical properties. The working principles of these methods are thoroughly explained, together with their applications for extracting the intrinsic cellular electrical and mechanical properties of cells. Recently emerged artificial intelligence-facilitated methods are also discussed. This review finishes with a discussion of the future prospects of these five methods. Our conclusion is that understanding the multi-modal spectrum of intrinsic cellular electrical and mechanical properties will be a major breakthrough in uncovering the heterogeneity of diseases and building personalized diagnosis and treatment systems.