Raman spectroscopy provides molecular specificity through spectrally-resolved measurement of the inelastic scattering under monochromatic excitation. In the context of microscopy, it may serve as label-free cell imaging, providing structural information.
However, the very low cross-section of Raman scattering requires long time exposures, which preclude imaging of cellular components with low concentrations. Surface-enhanced Raman spectroscopy (SERS), which relies on the local electromagnetic field enhancement produced by metallic nanostructures, is an approach to drastically increase the sensitivity of the Raman detection while retaining large amounts of spectral information.
In cellular imaging, the measurement is usually performed on endocytosed nanostructures. However, the measured SERS signals vary strongly as they depend on excitation beam profile, local particle presence or aggregation and local molecular environment. Identifying and extracting spectra corresponding to molecules of interest within a SERS data set is very difficult.
Conventional data analysis methods look for global patterns in the data, whereas the singlemolecule sensitivity of SERS can detect independent molecules in each pixel with little correlation between pixels. Nicolas Pavillon and his colleagues from Osaka University now explored different algorithmic methods to automatically discriminate spectra of interest in the measured field of view, without imposing assumptions on the self-similarity of the data.
The proposed method relies on the indexing of the positions of relevant spectra, which are selected by the computation of a quality map. The scientists proposed various criteria to compute spectra extraction, such as the spectral energy, the peak count per spectra, or the projection coefficients on SVD vectors. They assessed each criteria with simulated data and applied this approach to different types of measurements, such as dried Rhodamine 6G adsorbed on gold nanoparticles deposited on a glass substrate, and HeLa cells with endocytosed gold nanoparticles.
The tests with simulated data showed that various criteria can provide satisfactory results. The computation time could be tremendously decreased by discarding irrelevant pixels through a simple criterion based on the spectral energy, reducing the processing time to typically less than 10 seconds for a field of view on the order of 100 X 100 pixels. The tests performed on Rhodamine 6G measurements demonstrated the validity of the proposed approach, where its known spectrum could be extracted automatically.
The peak count criterion was the most suitable for most cases, as it detects various patterns without filtering out any curve which may only appear a single instance in the data set. Such single spectra may be critical important in a given SERS detection experiment. One main feature of the proposed approach is that its output is a localization map of the most relevant spectra in a measurement. The spatial information is retained, making it possible to trace back the positions of several spectra with identical properties, for instance. The optimized method was utilized to extract and classify the complex SERS response behavior of gold nanoparticles taken in live cells. (Text contributed by K. Maedefessel-Herrmann)
N. Pavillon, K. Bando, K. Fujita, N. I. Smith, Feature-based recognition of Surface-enhanced Raman spectra for biological targets, J. Biophotonics 6(8),587-597 (2013); doi: http://dx.doi.org/10.1002/jbio.201200181
For more information about the Journal of Biophotonics visit the journal homepage.Regina Hagen
Regina Hagen | Wiley-VCH
Magic number colloidal clusters
13.12.2018 | Friedrich-Alexander-Universität Erlangen-Nürnberg
Record levels of mercury released by thawing permafrost in Canadian Arctic
13.12.2018 | University of Alberta
What if, instead of turning up the thermostat, you could warm up with high-tech, flexible patches sewn into your clothes - while significantly reducing your...
A widely used diabetes medication combined with an antihypertensive drug specifically inhibits tumor growth – this was discovered by researchers from the University of Basel’s Biozentrum two years ago. In a follow-up study, recently published in “Cell Reports”, the scientists report that this drug cocktail induces cancer cell death by switching off their energy supply.
The widely used anti-diabetes drug metformin not only reduces blood sugar but also has an anti-cancer effect. However, the metformin dose commonly used in the...
A research team from the University of Zurich has developed a new drone that can retract its propeller arms in flight and make itself small to fit through narrow gaps and holes. This is particularly useful when searching for victims of natural disasters.
Inspecting a damaged building after an earthquake or during a fire is exactly the kind of job that human rescuers would like drones to do for them. A flying...
Over the last decade, there has been much excitement about the discovery, recognised by the Nobel Prize in Physics only two years ago, that there are two types...
What if a sensor sensing a thing could be part of the thing itself? Rice University engineers believe they have a two-dimensional solution to do just that.
Rice engineers led by materials scientists Pulickel Ajayan and Jun Lou have developed a method to make atom-flat sensors that seamlessly integrate with devices...
12.12.2018 | Event News
10.12.2018 | Event News
06.12.2018 | Event News
13.12.2018 | Life Sciences
13.12.2018 | Physics and Astronomy
13.12.2018 | Earth Sciences