We propose to employ NN-enhanced IFC to achieve both real-time single-cell intrinsic characterization and intrinsic metric-based cell classification at high throughput.

Successful single-cell isolation is a pivotal technique for subsequent biological and chemical analysis of single cells. Although significant advances have been made in single-cell isolation and analysis techniques, most passive...

and isotopes), requiring tedious sample preparation, invasive operation, and prior knowledge of cell specificity. [3] In contrast, biophysical methods measure the mechanical, electrical, and optical properties to perform quick, label-free, and non-invasive single-cell characterization, [4] so as to facilitate subsequent operations on cells such as sorting, [5] culturing, [6] and omics analysis. [7] Cellular biophysical properties have been proven as effective biomarkers for diagnosing diseases and widely used in cell biology, dynamics, and pathology research. [8] As one of the biophysical properties, mechanical properties of cells reflect the characteristics of cell membranes, and cytoskeletal networks, which influence cellular and subcellular functions, [9] including cell adhesion, migration, polarization, and differentiation, as well as organelle organization and trafficking inside the cytoplasm. [10] At present, there are many classic methods for characterizing the mechanical properties of single cells, such as atomic force microscopy (AFM), micropipette aspiration, parallel-plate rheometry, and optical stretching. [11] These methods evaluate time-resolved cellular responses to external stresses, and offer effective means to obtain the single-cell intrinsic mechanical properties (e.g., Young's modulus and viscosity). However, they suffer from inherent problems with technically demanding and time-consuming procedures, which lead to difficulty in operation and low throughput (<1 cell min −1 ). [11] As an attractive alternative, microfluidics approaches allow detecting cell deformability at high throughput but low complexity for single-cell analysis. [12] However, the characterization relies on expensive and complex high-speed imaging systems with time-consuming image processing algorithms to obtain the dynamic deformation process of the cells, which limits the real-time capability desired for downstream cell manipulation and analysis such as deformability-based sorting.Exploiting electronic means or impedance cytometry for cellular mechanical characterization presents a new alternative approach. [13] Based on direct-current (DC) Coulter-counter, the visco-node-pore sensing system [14] is proposed to characterize the cellular mechanics solely by the current signal. It employs elegant design of straight [14] or sinusoidal [15] constriction channels to correlate the current signal to the mechanical viscoelastic properties, and is applied in biological applications. [16] But the footprint for the series of node-pore structure may limit Mechanical properties of single cells are important label-free biomarkers normally measured by expensive and complex imaging systems. To unlock this limit and allow mechanical properties comparable across different measurement platforms, camera-free intrinsic mechanical cytometry (CFIMC) is proposed for on-the-fly measurement of two major intrinsic mechanical parameters, that is, Young's modulus E and fluidity β, of single cells. CFIMC adopts a framework that couples the impedance ele...

Reflecting various physiological states and phenotypes of single cells, intrinsic biophysical characteristics (e.g., mechanical and electrical properties) are reliable and important, label‐free biomarkers for characterizing single cells. However, single‐modal mechanical or electrical properties alone are not specific enough to characterize single cells accurately, and it has been long and challenging to couple the conventionally image‐based mechanical characterization and impedance‐based electrical characterization. In this work, the spatial‐temporal characteristics of impedance sensing signal are leveraged, and an impedance‐based multimodal electrical‐mechanical flow cytometry framework for on‐the‐fly high‐dimensional intrinsic measurement is proposed, that is, Young's modulus E, fluidity β, radius r, cytoplasm conductivity σi, and specific membrane capacitance Csm, of single cells. With multimodal high‐dimensional characterization, the electrical‐mechanical flow cytometry can better reveal the difference in cell types, demonstrated by the experimental results with three types of cancer cells (HepG2, MCF‐7, and MDA‐MB‐468) with 93.4% classification accuracy and pharmacological perturbations of the cytoskeleton (fixed and Cytochalasin B treated cells) with 95.1% classification accuracy. It is envisioned that multimodal electrical‐mechanical flow cytometry provides a new perspective for accurate label‐free single‐cell intrinsic characterization.

As label-free and high-throughput single cell analysis platform, impedance flow cytometry (IFC) suffers from clogging caused by narrow microchannel as mechanical constriction (MC). Current sheath constriction (SC) solutions lack systematic...