| 光谱学与光谱分析 |
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| Study of Spectrum Processing Method for Raman Microscopy on Single Living Cell |
| KANG Li-li1, HUANG Yao-xiong2*, WU Zheng-jie2 |
1. Department of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China
2. Department of Biomedical Engineering, Jinan University, Guangzhou 510632, China |
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Abstract To study the spectrum processing methods for Raman microscopy on single living cell and develop the pre-process techniques for Raman spectrum of single living cell to enhance the signal to noise ratio, sensitivity, and decrease the fluorescence influence, wiping off the cosmic rays was used to improve the spectrum. The spectra classification, spectra average and filtration were applied to enhance signal to noise ratio. The fluorescence was depressed for quantity analysis or utilized for analysis by comparing the background and the spectra. Results show that (1) comparing the spectra with short exposure time and more scans can wipe off the cosmic rays effectively. (2) the spectra classification, spectra average and filtration can improve the quality of spectra and can show some weak and sensitive bands. (3)sometimes the fluorescence has useful information. It is concluded that the proposed techniques for Raman spectrum of single cell in this paper can show the sensitive and weak intensity peaks and reflect the information of molecules structures very well.
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Received: 2010-04-23
Accepted: 2010-09-08
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Corresponding Authors:
HUANG Yao-xiong
E-mail: tyxhuang@jnu.edu.cn
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[1] Graselli J G，Bulkin B. Analytical Raman Spectroscopy. New York: Wiley and Sons, 1991.
[2] Puppels G J, Garritsen H S P, Seger-Nolten G M J, et al. J. Biophys.，1991, 60(5): 1046.
[3] Puppels G J, Bakker Schut T C, Sijtsema N M, et al. J. Mol. Struct., 1995, 347: 477.
[4] Wood B R，McNaughton D. J. Raman Spectrosc., 2002, 33: 517.
[5] Wood B R, McNaughton D. Biospectroscopy, 2002, 67: 259.
[6] Wood B R, Hammer L, Davis L, et al. Biomed. Opt.，2005, 10(1): 014005.
[7] Cary P R. Biochemical Application of Raman and Resonance Raman Spectroscopies. New York: Academic Press, 1982.
[8] KANG Li-li, HUANG Yao-xiong, LUO Man, et al(康立丽, 黄耀熊, 罗 曼, 等). Journal of Fourth Military Medical University(第四军医大学学报)，2007, 28(20): 1862.
[9] Kang Li-li, Huang Yao-xiong, Liu Wen-jing, et al. Bioploymers, 2008, 89(11): 951.
[10] Wu Yue, Huang Yao-xiong, Kang Li-li, et al. Bioploymers, 2009, pressed on web.
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