Due to their simplicity and label-free nature, electrical sensing techniques are tremendously attractive for single-cell analysis. We have integrated multiple electrical sensing architectures within a single microchannel, so that high throughput measurements (300 cells/s) based on multiple parameters of interest (trajectory, velocity, size, opacity, shape/orientation) can be used to assess single cells. This novel platform is coupled to a neural network approach for impedance pattern recognition and can serve as a stepping-stone to real time single-cell analysis and sorting. Rapid determination of cell properties and trajectory can be used to predict cell position in flow and enable for accurate sorting based on cellular/sub-cellular intrinsic properties.
Mcgrath, J., Reale, R., Honrado, C., Bisegna, P., Swami, N., Caselli, F. (2019). Towards real-time multiparametric impedance cytometry. In 23rd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2019 (pp.1364-1365). Chemical and Biological Microsystems Society.
Towards real-time multiparametric impedance cytometry
Bisegna P.;Caselli F.
2019-01-01
Abstract
Due to their simplicity and label-free nature, electrical sensing techniques are tremendously attractive for single-cell analysis. We have integrated multiple electrical sensing architectures within a single microchannel, so that high throughput measurements (300 cells/s) based on multiple parameters of interest (trajectory, velocity, size, opacity, shape/orientation) can be used to assess single cells. This novel platform is coupled to a neural network approach for impedance pattern recognition and can serve as a stepping-stone to real time single-cell analysis and sorting. Rapid determination of cell properties and trajectory can be used to predict cell position in flow and enable for accurate sorting based on cellular/sub-cellular intrinsic properties.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
