Biochip with multi-planar electrodes geometry for differentiation of non-spherical bioparticles in a microchannel

Investigation of geometry-dependent sensing characteristics of microfluidic for single-cell 3D localization

Flow cytometry-based measurement techniques have been widely used for single-cell characterizations, such as impedance, size, and dielectric properties. However, in the measurement process, the reliability of the output measurement signal directly affects the ability of the microsystem to judge the characteristics of single cells. Here, we designed a multiple nonparallel electrode structure for single-cell 3D localization. The performance of the structures was studied by analyzing the changes in electric field strength and the output differential current. The effects of microchannel height, sensing electrode distance, electrode inclination angle, and electrode width on output signals are investigated by analyzing the current change and electric field strength of single cells passing from the center of the microchannel. The numerical simulation results indicate that, when the microchannel height is 20 µm, the distance of the sensing electrodes is 100 µm, the inclination angle is 30°, the electrode width is 20 µm, and the optimal signal quality can be obtained. Reducing the height of the flow channel and shortening the sensing electrode spacing can significantly improve the signal amplitude. When the channel height is 20 µm, the signal intensity increases by 80% than that of 30 µm. The signal intensity of induced current with the sensing electrode spacing of 100 µm is 42% higher than that with the spacing of 120 µm. We analyzed the presence of multiple independent cells and adherent cells in the detection area and demonstrated through simulation that the signal changes caused by multi-cells can be superimposed by multiple single-cell signals. The induced current signal intensity of the same volume of cells with an ellipticity of 1 is 49% lower than that of cells with an ellipticity of 4. Based on the numerical investigation, we expect that the optimal geometry structure design will aid in the development of better performance signal cell impedance cytometry microsystems.

A review on intelligent impedance cytometry systems: Development, applications and advances

Impedance cytometry is a well-established technique for counting and analyzing single cells, with several advantages, such as convenience, high throughput, and no labeling required. A typical experiment consists of the following steps: single-cell measurement, signal processing, data calibration, and particle subtype identification. At the beginning of this article, we compared commercial and self-developed options extensively and provided references for developing reliable detection systems, which are necessary for cell measurement. Then, a number of typical impedance metrics and their relationships to biophysical properties of cells were analyzed with respect to the impedance signal analysis. Given the rapid advances of intelligent impedance cytometry in the past decade, this article also discussed the development of representative machine learning-based approaches and systems, and their applications in data calibration and particle identification. Finally, the remaining challenges facing the field were summarized, and potential future directions for each step of impedance detection were discussed.

Floating-Electrode-Enabled Impedance Cytometry for Single-Cell 3D Localization

As a label-free, low-cost, and noninvasive tool, impedance measurement has been widely used in single-cell characterization analysis. However, due to the tiny volume of cells, the uncertainty of the spatial position in the microchannel will bring measurement errors in single-cell electrical parameters. To overcome the issue, we designed a novel microdevice configured with a coplanar differential electrode structure to accurately resolve the spatial position of single cells without constraining techniques such as additional sheath fluids or narrow microchannels. The device precisely localizes single cells by measuring the induced current generated by the combined action of the floating electrode and the differential electrodes when single cells flow through the electrode-sensing area. The device was experimentally validated by measuring 6 μm yeast cells and 10 μm particles, achieving spatial localization with a resolution down to 2.1 μm (about 5.3% of the channel width) in lateral direction and 1.2 μm (about 5.9% of the channel height) in the vertical direction at a flow rate of 1.2 μL/min. In addition, by comparing measurement of yeast cells and particles, it was demonstrated that the device not only localizes the single cells or particles but also simultaneously characterizes their status properties such as velocity and size. The device offers a competitive electrode configuration in impedance cytometry with the advantages of simple structure, low cost, and high throughput, promising cell localization and thus electrical characterization.

Bioelectronic Sensor with Magnetic Modulation to Quantify Phagocytic Activity of Blood Cells Employing Machine Learning

Microbial infections result in activating an immune response in the human body, which triggers inflammatory pathways resulting in recognition and subsequent killing of the pathogens. Quantifying the blood cells' natural ability to kill pathogens, i.e., phagocytosis, is critical to demonstrating the effectiveness of an individual's response in combating pathogens. Current laboratory processes and equipment that can be used to monitor phagocytic activity are costly and time-consuming and require significant technical expertise to run such assays. Here, we design and develop a novel biosensing platform capable of quantifying the phagocytic ability of blood cells. The sensor design is composed of electronic sensing and magnetic modulation sub-systems that work in conjunction to monitor phagocytic activity in microfluidic channels. The phagocytes internalize the IgG-coated magnetic beads, and when infused into the sensor, their speed will be modulated using the quadrupole magnetic field configuration as they pass through microfluidic channels where microfabricated electrodes are placed. The electronic sensor will generate the voltage pulse for each passage of the phagocyte, whose distinct features are correlative to the phagocytic activity. We experimentally tested this device using 17 blood samples collected from patients at Robert Wood Johnson Medical Hospital. Further, we developed artificial neural networks (ANN) to improve the accuracy of the phagocytic activity detection. ANN model detected the phagocytic activity with 88.2% accuracy. This novel sensing platform can potentially be used to triage high risk patients and develop personalized theranostics for the septic patients in the future.

Microscopic impedance cytometry for quantifying single cell shape

In this work, we investigated the ability of impedance flow cytometry to measure the shape of single cells/particles. We found that the impedance pulses triggered by micro-objects that are asymmetric in morphology show a tilting trend, and there is no such a tilting trend for symmetric ones. Therefore, we proposed a new metric, tilt index, to quantify the tilt level of the impedance pulses. Through simulation, we found that the value of tilt index tends to be zero for perfectly symmetrical objects, while the value is greater than zero for asymmetrical ones. Also, this metric was found to be independent on the trajectories (i.e., lateral, and z-direction shift) of the target micro-object. In experiments, we adopted a home-made lock-in amplifier and performed experiments on 10 μm polystyrene beads and Euglena gracilis (E. gracilis) cells with varying shapes. The experimental results coincided with the simulation results and demonstrated that the new metric (tilt index) enables the impedance cytometry to characterize the shape single cells/particles without microscopy or other optical setups.