Exploring the effect of laser excitation wavelength on signal recovery with deep tissue transmission Raman spectroscopy.

PublishedJOURNAL ARTICLEThe aim of this research was to find the optimal Raman excitation wavelength to attain the largest possible sensitivity in deep Raman spectroscopy of breast tissue. This involved careful consideration of factors such as tissue absorption, scattering, fluorescence and instrument response function. The study examined the tissue absorption profile combined with Raman scattering and detection sensitivity at seven different, laser excitation wavelengths in the near infrared region of the spectrum. Several key scenarios in regards to the sample position within the tissue were examined. The highest Raman band visibility over the background ratio in respect to biological tissue provides the necessary information for determining the optimum laser excitation wavelength for deep tissue analysis using transmission Raman spectroscopy, including detection of breast calcifications. For thick tissues with a mix of protein and fat, such as breast tissue, 790-810 nm is concluded to be the optimum excitation wavelength for deep Raman measurements.An EPSRC grant (EP/K020374/1) funded the work presented here

Sensitivity of Transmission Raman Spectroscopy Signals to Temperature of Biological Tissues

This is the final version of the article. Available from Springer Nature via the DOI in this record.Optical properties of biological tissues can be influenced by their temperature, thus affecting light transport inside the sample. This could potentially be exploited to deliver more photons inside large biological samples, when compared with experiments at room temperature, overcoming some of difficulties due to highly scattering nature of the tissue. Here we report a change in light transmitted inside biological tissue with temperature elevation from 20 to 40 °C, indicating a considerable enhancement of photons collected by the detector in transmission geometry. The measurement of Raman signals in porcine tissue samples, as large as 40 mm in thickness, indicates a considerable increase in signal ranging from 1.3 to 2 fold, subject to biological variability. The enhancements observed are ascribed to phase transitions of lipids in biological samples. This indicates that: 1) experiments performed on tissue at room temperature can lead to an underestimation of signals that would be obtained at depth in the body in vivo and 2) that experiments at room temperature could be modified to increase detection limits by elevating the temperature of the material of interest.The work was supported by a grant from the Engineering and Physical research council (EP/P012442/1)

Fluorescence suppression using micro-scale spatially offset Raman spectroscopy

We present a new concept of fluorescence suppression in Raman microscopy based on micro-spatially offset Raman spectroscopy which is applicable to thin stratified turbid (diffusely scattering) matrices permitting the retrieval of the Raman signals of sublayers below intensely fluorescing turbid over-layers. The method is demonstrated to yield good quality Raman spectra with dramatically suppressed fluorescence backgrounds enabling the retrieval of Raman sublayer signals even in situations where conventional Raman microscopy spectra are fully overwhelmed by intense fluorescence. The concept performance was studied theoretically using Monte Carlo simulations indicating the potential of up to an order or two of magnitude suppression of overlayer fluorescence backgrounds relative to the Raman sublayer signals. The technique applicability was conceptually demonstrated on layered samples involving paints, polymers and stones yielding fluorescence suppression factors between 12 to above 430. The technique has potential applications in a number of analytical areas including cultural heritage, archaeology, polymers, food, pharmaceutical, biological, biomedical, forensics and catalytic sciences and quality control in manufacture

Inductive queries for a drug designing robot scientist

It is increasingly clear that machine learning algorithms need to be integrated in an iterative scientific discovery loop, in which data is queried repeatedly by means of inductive queries and where the computer provides guidance to the experiments that are being performed. In this chapter, we summarise several key challenges in achieving this integration of machine learning and data mining algorithms in methods for the discovery of Quantitative Structure Activity Relationships (QSARs). We introduce the concept of a robot scientist, in which all steps of the discovery process are automated; we discuss the representation of molecular data such that knowledge discovery tools can analyse it, and we discuss the adaptation of machine learning and data mining algorithms to guide QSAR experiments

Effect of particle properties of powders on the generation and transmission of raman scattering

Transmission Raman measurements of a 1 mm thick sulfur-containing disk were made at different positions as it was moved through 4 mm of aspirin (150-212 mu m) or microcrystalline cellulose (Avicel) of different size ranges (<38, 53-106, and 150-212 mu m). The transmission Raman intensity of the sulfur interlayer at 218 cm(-1) was lower when the disk was placed at the top or bottom of the powder bed, compared to positions within the bed and the difference between the sulfur intensity at the outer and inner positions increased with Avicel particle size. Also, the positional intensity difference was smaller for needle-shaped aspirin than for granular Avicel of the same size. The attenuation coefficients for the propagation of the exciting laser and transmitted Raman photons through the individual powders were the same but decreased as the particle size of Avicel increased; also, the attenuation coefficients for propagation through 150-212 mu m aspirin were almost half of those through similar sized Avicel particles. The study has demonstrated that particulate size and type affect transmitted Raman intensities and, consequently, such factors need to be considered in the analysis of powders, especially if particle properties vary between the samples

Transversity distributions from difference asymmetries in semi-inclusive DIS

In recent years information on the transversity distribution h1 has been obtained by combining the Collins asymmetry results from semi-inclusive deep inelastic scattering (SIDIS) data on transversely polarized nucleon targets with the information on the fragmentation function of a transversely polarized quark from the asymmetries measured in e\ufee 12 annihilation into hadrons. An alternative method was proposed a long time ago, which does not require the e\ufee 12 data but allows one to get ratios of the u and d quark transversity distributions from the SIDIS data alone. The method utilizes the ratio of the difference of the Collins asymmetries of positively and negatively charged hadrons produced on transversely polarized proton and deuteron targets. We have applied this method to the COMPASS proton and deuteron data and extracted the ratio hdv 1 =huv 1 . The results are compared to those obtained in a previous point-by-point extraction based both on SIDIS and e\ufee 12 data

Analytical capability of defocused μ-SORS in the chemical interrogation of thin turbid painted layers

© The Author(s) 2015. A recently developed micrometer-scale spatially offset Raman spectroscopy (m-SORS) method provides a new analytical capability for investigating non-destructively the chemical composition of sub-surface, micrometer-scale thickness, diffusely scattering layers at depths beyond the reach of conventional confocal Raman microscopy. Here, we demonstrate experimentally, for the first time, the capability of μ-SORS to determine whether two detected chemical components originate from two separate layers or whether the two components are mixed together in a single layer. Such information is important in a number of areas, including conservation of cultural heritage objects, and is not available, for highly turbid media, from conventional Raman microscopy, where axial (confocal) scanning is not possible due to an inability to facilitate direct imaging within the highly scattering sample. This application constitutes an additional capability for μ-SORS in addition to its basic capacity to determine the overall chemical make-up of layers in a turbid system

Algorithms for Colourful Simplicial Depth and Medians in the Plane

The colourful simplicial depth of a point x in the plane relative to a configuration of n points in k colour classes is exactly the number of closed simplices (triangles) with vertices from 3 different colour classes that contain x in their convex hull. We consider the problems of efficiently computing the colourful simplicial depth of a point x, and of finding a point, called a median, that maximizes colourful simplicial depth. For computing the colourful simplicial depth of x, our algorithm runs in time O(n log(n) + k n) in general, and O(kn) if the points are sorted around x. For finding the colourful median, we get a time of O(n^4). For comparison, the running times of the best known algorithm for the monochrome version of these problems are O(n log(n)) in general, improving to O(n) if the points are sorted around x for monochrome depth, and O(n^4) for finding a monochrome median.Comment: 17 pages, 8 figure