Paper
31 January 2012 Raman spectra of single cells with autofluorescence suppression by modulated wavelength excitation
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Abstract
Raman spectroscopy is a non-invasive technique offering great potential in the biomedical field for label-free discrimination between normal and tumor cells based on their biochemical composition. First, this contribution describes Raman spectra of lymphocytes after drying, in laser tweezers, and trapped in a microfluidic environment. Second, spectral differences between lymphocytes and acute myeloid leukemia cells (OCI-AML3) are compared for these three experimental conditions. Significant similarities of difference spectra are consistent with the biological relevance of the spectral features. Third, modulated wavelength Raman spectroscopy has been applied to this model system to demonstrate background suppression. Here, the laser excitation wavelength of 785 nm was modulated with a frequency of 40 mHz by 0.6 nm. 40 spectra were accumulated with an exposure time of 5 seconds each. These data were subjected to principal component analysis to calculate modulated Raman signatures. The loading of the principal component shows characteristics of first derivatives with derivative like band shapes. The derivative of this loading corresponds to a pseudo-second derivative spectrum and enables to determine band positions.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Christoph Krafft, Sebastian Dochow, Norbert Bergner, Joachim H. Clement, Bavishna B. Praveen, Michael Mazilu, Rob Marchington, Kishan Dholakia, and Jürgen Popp "Raman spectra of single cells with autofluorescence suppression by modulated wavelength excitation", Proc. SPIE 8219, Biomedical Vibrational Spectroscopy V: Advances in Research and Industry, 82190F (31 January 2012); https://doi.org/10.1117/12.908564
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Cited by 1 scholarly publication.
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KEYWORDS
Raman spectroscopy

Modulation

Optical tweezers

Microfluidics

Tumors

Principal component analysis

Proteins

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