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Abstract This article presents the development and testing of a low‐cost (<$60), portable, electrical impedance‐based microflow cytometer for single‐cell analysis under a controlled oxygen microenvironment. The system is based on an AD5933 impedance analyzer chip, a microfluidic chip, and an Arduino microcontroller operated by a custom Android application. A representative case study on human red blood cells (RBCs) affected by sickle cell disease is conducted to demonstrate the capability of the cytometry system. Impedance values of sickle blood samples exhibit remarkable deviations from the common reference line obtained from two normal blood samples. Such deviation is quantified by a conformity score, which allows for the measurement of intrapatient and interpatient variations of sickle cell disease. A low conformity score under oxygenated conditions or drastically different conformity scores between oxygenated and deoxygenated conditions can be used to differentiate a sickle blood sample from normal. Furthermore, an equivalent circuit model of a suspended biological cell is used to interpret the electrical impedance of single flowing RBCs. In response to hypoxia treatment, all samples, regardless of disease state, exhibit significant changes in at least one single‐cell electrical property, that is, cytoplasmic resistance and membrane capacitance. The overall response to hypoxia is less in normal cells than those affected by sickle cell disease, where the change in membrane capacitance varies from −23% to seven times as compared with −17% in normal cells. The results reported in this article suggest that the developed method of testing demonstrates the potential application for a low‐cost screening technique for sickle cell disease and other diseases in the field and low‐resource settings. The developed system and methodology can be extended to analyze cellular response to hypoxia in other cell types.
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Neural Network‐Enabled Multiparametric Impedance Signal Templating for High throughput Single‐Cell Deformability Cytometry Under Viscoelastic Extensional Flows
Abstract Cellular biophysical metrics exhibit systematic alterations during processes, such as metastasis and immune cell activation, which can be used to identify and separate live cell subpopulations for targeting drug screening. Image‐based biophysical cytometry under extensional flows can accurately quantify cell deformability based on cell shape alterations but needs extensive image reconstruction, which limits its inline utilization to activate cell sorting. Impedance cytometry can measure these cell shape alterations based on electric field screening, while its frequency response offers functional information on cell viability and interior structure, which are difficult to discern by imaging. Furthermore, 1‐D temporal impedance signal trains exhibit characteristic shapes that can be rapidly templated in near real‐time to extract single‐cell biophysical metrics to activate sorting. We present a multilayer perceptron neural network signal templating approach that utilizes raw impedance signals from cells under extensional flow, alongside its training with image metrics from corresponding cells to derive net electrical anisotropy metrics that quantify cell deformability over wide anisotropy ranges and with minimal errors from cell size distributions. Deformability and electrical physiology metrics are applied in conjunction on the same cell for multiparametric classification of live pancreatic cancer cells versus cancer associated fibroblasts using the support vector machine model.
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- Award ID(s):
- 2222933
- PAR ID:
- 10571471
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Small
- Volume:
- 21
- Issue:
- 5
- ISSN:
- 1613-6810
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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