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Tumour cell identification by means of Raman spectroscopy in combination with optical traps and microfluidic environments

机译:通过拉曼光谱结合光阱和微流体环境识别肿瘤细胞

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Raman spectroscopy has been recognized to be a powerful tool for label-free discrimination of cells. Sampling methods are under development to utilize the unique capabilities to identify cells in body fluids such as saliva, urine or blood. The current study applied optical traps in combination with Raman spectroscopy to acquire spectra of single cells in microfluidic glass channels. Optical traps were realized by two 1070 nm single mode fibre lasers. Microflows were controlled by a syringe pump system. A novel microfluidic glass chip was designed to inject single cells, modify the flow speed, accommodate the laser fibres and sort cells after Raman based identification. Whereas the integrated microchip setup used 514 nm for excitation of Raman spectra, a quartz capillary setup excited spectra with 785 nm laser wavelength. Classification models were trained using linear discriminant analysis to differentiate erythrocytes, leukocytes, acute myeloid leukaemia cells (OCI-AML3), and breast tumour cells BT-20 and MCF-7 with accuracies that are comparable with previous Raman experiments of dried cells and fixed cells in a Petri dish. Implementation into microfluidic environments enables a high degree of automation that is required to improve the throughput of the approach for Raman activated cell sorting.
机译:拉曼光谱法已被认为是无标记区分细胞的有力工具。采样方法正在开发中,以利用独特的功能来识别唾液,尿液或血液等体液中的细胞。当前的研究将光阱与拉曼光谱结合使用,以获取微流玻璃通道中单细胞的光谱。光阱由两个1070 nm单模光纤激光器实现。通过注射泵系统控制微流。一种新型的微流控玻璃芯片被设计用于注射单个细胞,修改流速,容纳激光纤维并在基于拉曼的鉴定之后对细胞进行分选。集成微芯片设置使用514 nm激发拉曼光谱,而石英毛细管设置激发了785 nm激光波长的光谱。使用线性判别分析训练分类模型,以区分红细胞,白细胞,急性髓细胞性白血病细胞(OCI-AML3)以及乳腺肿瘤细胞BT-20和MCF-7,其准确性与之前的干细胞和固定细胞拉曼实验相当在培养皿中。在微流体环境中的实施实现了高度自动化,这是提高拉曼活化细胞分选方法的通量所必需的。

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