Diagnostic potential of near-infrared Raman spectroscopy in the stomach: differentiating dysplasia from normal tissue

Raman spectroscopy is a molecular vibrational spectroscopic technique that is capable of optically probing the biomolecular changes associated with diseased transformation. The purpose of this study was to explore near-infrared (NIR) Raman spectroscopy for identifying dysplasia from normal gastric mucosa tissue. A rapid-acquisition dispersive-type NIR Raman system was utilised for tissue Raman spectroscopic measurements at 785 nm laser excitation. A total of 76 gastric tissue samples obtained from 44 patients who underwent endoscopy investigation or gastrectomy operation were used in this study. The histopathological examinations showed that 55 tissue specimens were normal and 21 were dysplasia. Both the empirical approach and multivariate statistical techniques, including principal components analysis (PCA), and linear discriminant analysis (LDA), together with the leave-one-sample-out cross-validation method, were employed to develop effective diagnostic algorithms for classification of Raman spectra between normal and dysplastic gastric tissues. High-quality Raman spectra in the range of 800–1800 cm−1 can be acquired from gastric tissue within 5 s. There are specific spectral differences in Raman spectra between normal and dysplasia tissue, particularly in the spectral ranges of 1200–1500 cm−1 and 1600–1800 cm−1, which contained signals related to amide III and amide I of proteins, CH3CH2 twisting of proteins/nucleic acids, and the C=C stretching mode of phospholipids, respectively. The empirical diagnostic algorithm based on the ratio of the Raman peak intensity at 875 cm−1 to the peak intensity at 1450 cm−1 gave the diagnostic sensitivity of 85.7% and specificity of 80.0%, whereas the diagnostic algorithms based on PCA-LDA yielded the diagnostic sensitivity of 95.2% and specificity 90.9% for separating dysplasia from normal gastric tissue. Receiver operating characteristic (ROC) curves further confirmed that the most effective diagnostic algorithm can be derived from the PCA-LDA technique. Therefore, NIR Raman spectroscopy in conjunction with multivariate statistical technique has potential for rapid diagnosis of dysplasia in the stomach based on the optical evaluation of spectral features of biomolecules

Defining Multiple Characteristic Raman Bands of α-Amino Acids as Biomarkers for Planetary Missions Using a Statistical Method

Biomarker molecules, such as amino acids, are key to discovering whether life exists elsewhere in the Solar System. Raman spectroscopy, a technique capable of detecting biomarkers, will be on board future planetary missions including the ExoMars rover. Generally, the position of the strongest band in the spectra of amino acids is reported as the identifying band. However, for an unknown sample, it is desirable to define multiple characteristic bands for molecules to avoid any ambiguous identification. To date, there has been no definition of multiple characteristic bands for amino acids of interest to astrobiology. This study examinedL-alanine, L-aspartic acid, L-cysteine, L-glutamine and glycine and defined several Raman bands per molecule for reference as characteristic identifiers. Per amino acid, 240 spectra were recorded and compared using established statistical tests including ANOVA. The number of characteristic bands defined were 10, 12, 12, 14 and 19 for L-alanine (strongest intensity band: 832 cm-1), L-aspartic acid (938 cm-1), L-cysteine (679 cm-1),L-glutamine (1090 cm−1) and glycine (875 cm-1), respectively. The intensity of bands differed by up to six times when several points on the crystal sample were rotated through 360 °; to reduce this effect when defining characteristic bands for other molecules, we find that spectra should be recorded at a statistically significant number of points per sample to remove the effect of sample rotation. It is crucial that sets of characteristic Raman bands are defined for biomarkers that are targets for future planetary missions to ensure a positive identification can be made

Surface modification of a polyhedral oligomeric silsesquioxane poly(carbonate-urea) urethane (POSS-PCU) nanocomposite polymer as a stent coating for enhanced capture of endothelial progenitor cells

An unmet need exists for the development of next-generation multifunctional nanocomposite materials for biomedical applications, particularly in the field of cardiovascular regenerative biology. Herein, we describe the preparation and characterization of a novel polyhedral oligomeric silsesquioxane poly(carbonate-urea) urethane (POSS-PCU) nanocomposite polymer with covalently attached anti-CD34 antibodies to enhance capture of circulating endothelial progenitor cells (EPC). This material may be used as a new coating for bare metal stents used after balloon angioplasty to improve re-endothelialization. Biophysical characterization techniques were used to assess POSS-PCU and its subsequent functionalization with anti-CD34 antibodies. Results indicated successful covalent attachment of anti-CD34 antibodies on the surface of POSS-PCU leading to an increased propensity for EPC capture, whilst maintaining in vitro biocompatibility and hemocompatibility. POSS-PCU has already been used in 3 first-in-man studies, as a bypass graft, lacrimal duct and a bioartificial trachea. We therefore postulate that its superior biocompatibility and unique biophysical properties would render it an ideal candidate for coating medical devices, with stents as a prime example. Taken together, anti-CD34 functionalized POSS-PCU could form the basis of a nano-inspired polymer platform for the next generation stent coatings