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- Eliasson, Charlotte, 1973, et al.
(author)
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Multivariate methodology for surface enhanced Raman chemical imaging of lymphocytes
- 2006
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In: Chemometrics and Intelligent Laboratory Systems. - : Elsevier BV. - 0169-7439 .- 1873-3239. ; 81:1, s. 13-20
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Journal article (peer-reviewed)abstract
- Surface enhanced Raman spectroscopy (SERS) was used to study the uptake of rhodamine 6G in human lymphocytes. In total four Raman images of lymphocytes were used. The aim was to find a multivariate methodology capable of separating spectra with chemical information from those that mainly contained the surface enhanced background, in order to create chemical images. The standard PCA procedure was compared with PCA of standard normal variate (SNV) corrected spectra, spectra baseline corrected in the wavelet domain, and variable trimming before PCA, to isolate unique spectra. It was not straightforward to perform a standard PCA for overview, since the small background variation in many variables dominated over the Raman band variation that only occur in few variables. It was shown that wavelet filtering could remove background variations and that variable trimming followed by PCA modelling left the unique Raman spectra as outliers, which facilitated interpretation of the Raman score images.
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| 2. |
- Eliasson, Charlotte, 1973, et al.
(author)
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Surface-enhanced Raman scattering imaging of single living lymphocytes with multivariate evaluation
- 2005
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In: Spectrochimica Acta Part A-Molecular and Biomolecular Spectroscopy. - : Elsevier BV. - 1386-1425. ; 61:4, s. 755-760
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Journal article (peer-reviewed)abstract
- This paper is aimed to show the possibility to determine individual organic compounds introduced into single living cells with surface-enhanced Raman spectroscopy (SERS). Surface enhancement was achieved with gold colloids that were allowed to diffuse into lymphocytes. An introduced analyte, rhodamine 6G, could be imaged together with for example nucleotides and amino acids of the cell. Multivariate evaluation of surface-enhanced Raman images proved to be a powerful tool for the separation of spectral information of various intracellular components. The principal component analysis (PCA) enabled identification of spectra containing different chemical information and separation of the spectral contribution of rhodamine 6G from the complex cellular matrix.
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