Stimulated Raman microscopy (CARS): From principles to applications |
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Authors: | Djaker Nadia Marguet Didier Rigneault Hervé |
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Affiliation: | Institut Fresnel, Equipe Mosaic, UMR CNRS 6133, Université Paul Cézanne Aix-Marseille III, Domaine Universitaire de Saint-Jér?me 13397 Marseille Cedex 20, France. |
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Abstract: | A new technique in microscopy is now available which permits to image specific molecular bonds of chemical species present in cells and tissues. The so called Coherent Anti-Stokes Raman Scattering (CARS) approach aims at maximizing the light matter interaction between two laser pulses and an intrinsic molecular vibrational level. This is possible through a non linear process which gives rise to a coherent radiation that is greatly enhanced when the frequency difference between the two laser pulses equals the Raman frequency of the aimed molecular bond. Similar to confocal microscopy, the technique permits to build an image of a molecular density within the sample but doesn't require any labelling or staining since the contrast uses the intrinsic vibrational levels present in the sample. Images of lipids in membranes and tissues have been reported together with their spectral analysis. In the case of very congested media, it is also possible to use a non invasive labelling such as deuterium which shifts the molecular vibration of the C-H bond down to the C-D bond range which falls in a silent region of the cell and tissue vibrational spectra. Such an approach has been used to study lipid phase in artificial membranes. Although the technique is still under development, CARS has now reach a maturity which will permit to bring the technology at a commercial stage in the near future. The last remaining bottleneck is the laser system which needs to be simplified but solutions are now under evaluation. When combined with others more conventional techniques, CARS should give its full potential in imaging unstained samples and like two photons techniques has the potential of performing deep tissues imaging. |
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