Biomedical applications, perspectives and tag design concepts in the cell - silent Raman window.

Spectroscopic studies increasingly employ Raman tags exhibiting a signal in the cell - silent region of the Raman spectrum (1800-2800 cm), where bands arising from biological molecules are inherently absent. Raman tags bearing functional groups which contain a triple bond, such as alkyne and nitrile or a carbon-deuterium bond, have a distinct vibrational frequency in this region. Due to the lack of spectral background and cell-associated bands in the specific area, the implementation of those tags can help overcome the inherently poor signal-to-noise ratio and presence of overlapping Raman bands in measurements of biological samples.

Towards non-invasive monitoring of non-melanoma skin cancer using spatially offset Raman spectroscopy.

BCC (basal cell carcinoma) and SCC (squamous cell carcinoma) account for the vast majority of cases of non-melanoma skin cancer (NMSC). The gold standard for the diagnosis remains biopsy, which, however, is an invasive and time-consuming procedure. In this study, we employed spatially offset Raman spectroscopy (SORS), a non-invasive approach, allowing the assessment of deeper skin tissue levels and collection of Raman photons with a bias towards the different layers of epidermis, where the non-melanoma cancers are initially formed and expand.

Rapid Vector-Based Peak Fitting and Resolution Enhancement for Correlation Analyses of Raman Hyperspectra.

Spectroscopic peak parameters are important since they provide information about the analyte under study. Besides obtaining these parameters, peak fitting also resolves overlapped peaks. Thus, the obtained parameters should permit the construction of a higher-resolution version of the original spectrum.

Saline dry fixation for improved cell composition analysis using Raman spectroscopy.

Raman spectroscopy enables the label-free assessment of cellular composition. While live cell analysis is the most accurate approach for cellular Raman spectroscopy, the analysis of fixed cells has proved to be very useful, particularly in collaborative projects where samples need to be serially examined by different laboratories or stored and reanalyzed at a later date. However, many chemicals that are widely used for cell fixation directly affect cellular biomolecules, yielding Raman spectra with missing or altered information.

Two-Dimensional Clustering of Spectral Changes for the Interpretation of Raman Hyperspectra.

Two-dimensional correlation spectroscopy (2D-COS) is a technique that permits the examination of synchronous and asynchronous changes present in hyperspectral data. It produces two-dimensional correlation coefficient maps that represent the mutually correlated changes occurring at all Raman wavenumbers during an implemented perturbation. To focus our analysis on clusters of wavenumbers that tend to change together, we apply a -means clustering to the wavenumber profiles in the perturbation domain decomposition of the two-dimensional correlation coefficient map.

Assessing the quality of stored red blood cells using handheld Spatially Offset Raman spectroscopy with multisource correlation analysis.

In this work we employ Spatially Offset Raman Spectroscopy (SORS) to non-invasively identify storage-related changes in red blood cell concentrate (RCC) in-situ within standard plastic transfusion bags. To validate the measurements, we set up a parallel study comparing both bioanalytical data (obtained by blood-gas analysis, hematology analysis and spectrophotometric assays), and Raman spectrometry data from the same blood samples. We then employ Multisource Correlation Analysis (MuSCA) to correlate the different types of data in RCC.

Critical Evaluation of Spectral Resolution Enhancement Methods for Raman Hyperspectra.

Overlapping peaks in Raman spectra complicate the presentation, interpretation, and analyses of complex samples. This is particularly problematic for methods dependent on sparsity such as multivariate curve resolution and other spectral demixing as well as for two-dimensional correlation spectroscopy (2D-COS), multisource correlation analysis, and principal component analysis. Though software-based resolution enhancement methods can be used to counter such problems, their performances often differ, thereby rendering some more suitable than others for specific tasks.

Multiphoton imaging and Raman spectroscopy of the bovine vertebral endplate.

The interface between the intervertebral disc and the vertebral body is important to the discs' biomechanics and physiology, and is widely implicated in its pathology. This study aimed to explore biochemically and structurally the bony endplate, cartilage endplate and intervertebral disc, below the nucleus and below the annulus in healthy bovine tails. Multiphoton imaging and spontaneous Raman spectroscopy were employed.

Non-invasive monitoring of red blood cells during cold storage using handheld Raman spectroscopy.

Background: The current best practices allow for the red blood cells (RBCs) to be stored for prolonged periods in blood banks worldwide. However, due to the individual-related variability in donated blood and RBCs continual degradation within transfusion bags, the quality of stored blood varies considerably. There is currently no method for assessing the blood product quality without compromising the sterility of the unit.

Augmented Two-Dimensional Correlation Spectroscopy for the Joint Analysis of Correlated Changes in Spectroscopic and Disparate Sources.

Here, we present an augmented form of two-dimensional correlation spectroscopy, that integrates in a single format data from spectroscopic and multiple non-spectroscopic sources for analysis. The integration is affected by augmenting every spectrum in a hyperspectral data set with relevant non-spectroscopic data to permit two-dimensional correlation analysis of the ensemble of augmented spectra. A -means clustering is then applied to the results of the perturbation domain decomposition to determine which Raman peaks cluster with any of the non-spectroscopic data.

Tissue Phantoms for Biomedical Applications in Raman Spectroscopy: A Review.

Raman spectroscopy is a group of analytical techniques, currently applied in several research fields, including clinical diagnostics. Tissue-mimicking optical phantoms have been established as an essential intermediate stage for medical applications with their employment from spectroscopic techniques to be constantly growing. This review outlines the types of tissue phantoms currently employed in different biomedical applications of Raman spectroscopy, focusing on their composition and optical properties.

Correction: Applications of Raman spectroscopy in the development of cell therapies: state of the art and future perspectives.

Correction for 'Applications of Raman spectroscopy in the development of cell therapies: state of the art and future perspectives' by Shreyas Rangan et al., Analyst, 2020, DOI: 10.1039/c9an01811e.

Applications of Raman spectroscopy in the development of cell therapies: state of the art and future perspectives.

Therapies based on injecting living cells into patients offer a huge potential to cure many degenerative and deadly diseases, with hundreds of clinical trials ongoing. Due to their complex nature, a basic understanding of their biochemical and functional characteristics, how to manufacture them for safe and efficacious therapy, and how to effectively implement them in clinical settings are very challenging. Raman spectroscopy could provide an information-rich, non-invasive, non-destructive analytical method to complement the use of conventional sample-based, infrequent and destructive biochemical assays typically employed to analyze and validate the quality of therapeutic cells.

Defocused Spatially Offset Raman Spectroscopy in Media of Different Optical Properties for Biomedical Applications Using a Commercial Spatially Offset Raman Spectroscopy Device.

In this study, we show how defocused spatially offset Raman spectroscopy (SORS) can be employed to recover chemical information from media of biomedical significance within sealed plastic transfusion and culture bags using a commercial SORS instrument. We demonstrate a simple approach to recover subsurface spectral information through a transparent barrier by optimizing the spatial offset of the defocused beam. The efficiency of the measurements is assessed in terms of the SORS ratio and signal-to-noise ratio (S/N) through a simple manual approach and an ordinary least squares model.

Fourier transform infrared spectroscopic imaging of colon tissues: evaluating the significance of amide I and C-H stretching bands in diagnostic applications with machine learning.

Fourier transform infrared (FTIR) spectroscopic imaging of colon biopsy tissues in transmission combined with machine learning for the classification of different stages of colon malignancy was carried out in this study. Two different approaches, an optical and a computational one, were applied for the elimination of the scattering background during the measurements and compared with the results of the machine learning model without correction for the scattering. Several different data processing pathways were implemented in order to obtain a high accuracy of the prediction model.

Determination of Depth in Transmission Raman Spectroscopy in Turbid Media Using a Beam Enhancing Element.

This study demonstrates experimentally a method to enable prediction of depth of a chemical species buried in a turbid medium by using transmission Raman spectroscopy alone. The method allows the prediction of the depth of a single, chemically distinct layer within a turbid matrix by performing two measurements, with and without a beam enhancing element, or "photon diode." The samples employed consisted of two different polymers, of total thickness 3.

Subwavelength Terahertz Imaging of Graphene Photoconductivity.

Using a spatially structured, optical pump pulse with a terahertz (THz) probe pulse, we are able to determine spatial variations of the ultrafast THz photoconductivity with subwavelength resolution (75 μm ≈ λ/5 at 0.8 THz) in a planar graphene sample. We compare our results to Raman spectroscopy and correlate the existence of the spatial inhomogeneities between the two measurements.

Characterisation of signal enhancements achieved when utilizing a photon diode in deep Raman spectroscopy of tissue.

We characterise the performance of a beam enhancing element ('photon diode') for use in deep Raman spectroscopy (DRS) of biological tissues. The optical component enhances the number of laser photons coupled into a tissue sample by returning escaping photons back into it at the illumination zone. The method is compatible with transmission Raman spectroscopy, a deep Raman spectroscopy concept, and its implementation leads to considerable enhancement of detected Raman photon rates.

Studying the distribution of deep Raman spectroscopy signals using liquid tissue phantoms with varying optical properties.

In this study we employed large volume liquid tissue phantoms, consisting of a scattering agent (Intralipid), an absorption agent (Indian ink) and a synthesized calcification powder (calcium hydroxyapatite (HAP)) similar to that found in cancerous tissues (e.g. breast and prostate), to simulate human tissues.