A camera-based light scattering approach coupled with a viscoelasticity-induced cell migration technique has been used to characterize the morphological properties of erythrocytes in microfluidic flows. We have obtained the light scattering profiles (LSPs) of individual living cells in microfluidic flows over a wide angular range and matched them with scattering simulations to characterize their morphological properties. The viscoelasticity-induced 3D cell alignment in microfluidic flows has been investigated by bright-field and holographic microscopy tracking, where the latter technique has been used to obtain precise cell alignment profiles in-flow. Such information allows variable cell probability control in microfluidic flows at very low viscoelastic polymer concentrations, obtaining cell measurements that are almost physiological. Our results confirm the possibility of precise, label-free analysis of individual living erythrocytes in microfluidic flows.

Optical signature of erythrocytes by light scattering in microfluidic flows

Rossi D.;
2015-01-01

Abstract

A camera-based light scattering approach coupled with a viscoelasticity-induced cell migration technique has been used to characterize the morphological properties of erythrocytes in microfluidic flows. We have obtained the light scattering profiles (LSPs) of individual living cells in microfluidic flows over a wide angular range and matched them with scattering simulations to characterize their morphological properties. The viscoelasticity-induced 3D cell alignment in microfluidic flows has been investigated by bright-field and holographic microscopy tracking, where the latter technique has been used to obtain precise cell alignment profiles in-flow. Such information allows variable cell probability control in microfluidic flows at very low viscoelastic polymer concentrations, obtaining cell measurements that are almost physiological. Our results confirm the possibility of precise, label-free analysis of individual living erythrocytes in microfluidic flows.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4823584
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