Dynamic Liquid Surface Enhanced Raman Scattering Platform Based on Soft Tubular Microfluidics for Label-Free Cell Detection.

Abstract

Cell detection is of great significance for biomedical research. Surface enhanced Raman scattering (SERS) has been widely applied to the detection of cells. However, there is still a lack of a general, low-cost, rapid, and sensitive SERS method for cell detection. Herein, a dynamic liquid SERS platform, which combines label-free SERS technique with soft tubular microfluidics for cell detection, is proposed. Compared with common static solid and static liquid measurement, the dynamic liquid SERS platform can present dynamical mixing, precise control of the mixing time, and continuous spectra collection. By characterizing the model molecules, the proposed dynamic liquid SERS platform has successfully demonstrated good stability and repeatability with 1.90% and 4.98% relative standard deviation (RSD), respectively. Three cell lines including one normal breast cell line (MCF-10A) and two breast cancer cell lines (MCF-7 and MDA-MB-231) were investigated in this platform. 270 cell spectra were selected as the training set for the classification of the models based on the K-Nearest Neighbor (K-NN) algorithm. In three independent experiments, three types of cells were identified by a test set containing 180 cell spectra with sensitivities above 83.3% and specificities above 91.6%. The accuracy was 94.1 ± 1.14% among three independent cell identifications. The dynamic liquid SERS platform has shown higher signal intensity, better repeatability, less pretreatment, and obtainment of more spectra with less time consumption. It will be a powerful detection tool in the area of cell research, clinical diagnosis, and food safety.