Label‐free monitoring of inflammatory tissue conditions using a carrageenan‐induced acute inflammation rat model. Issue 6 (23rd February 2018)

• Record Type: Journal Article
• Authors: Lee, Seung Ho; Lee, Sang Hwa; Shin, Jae‐Ho; Choi, Samjin
• Other Names: Bianchini Paolo specialEditor.
• Is Part Of: Microscopy research and technique. Volume 81:Issue 6(2018)
• Page Start: 544
• Page End: 550
• Publication Date: 2018-02-23
• Subjects: acute inflammation -- carrageenan -- principle component analysis -- Raman spectroscopy; Electron microscopy -- Technique -- Periodicals; Microscopy -- Periodicals; Microscopy -- Technique -- Periodicals; 502.825
• DOI: 10.1002/jemt.23010
• Languages: English
• ISSNs: 1059-910X

Abstract

Abstract: Although the confirmation of inflammatory changes within tissues at the onset of various diseases is critical for the early detection of disease and selection of appropriate treatment, most therapies are based on complex and time‐consuming diagnostic procedures. Raman spectroscopy has the ability to provide non‐invasive, real‐time, chemical bonding analysis through the inelastic scattering of photons. In this study, we evaluate the feasibility of Raman spectroscopy as a new, easy, fast, and accurate diagnostic method to support diagnostic decisions. The molecular changes in carrageenan‐induced acute inflammation rat tissues were assessed by Raman spectroscopy. Volumes of 0 (control), 100, 150, and 200 µL of 1% carrageenan were administered to rat hind paws to control the degree of inflammation. The prominent peaks at [1, 062, 1, 131] cm −1 and [2, 847, 2, 881] cm −1 were selected as characteristic measurements corresponding to the C–C stretching vibrational modes and the symmetric and asymmetric C–H (CH2 ) stretching vibrational modes, respectively. Principal component analysis of the inflammatory Raman spectra enabled graphical representation of the degree of inflammation through principal component loading profiles of inflammatory tissues on a two‐dimensional plot. Therefore, Raman spectroscopy with multivariate statistical analysis represents a promising method for detecting biomolecular responses based on different types of inflammatory tissues. Abstract : Multivariate statistical analysis of inflammatory Raman spectral data could be used as a potential diagnostic tool for analyzing various inflammatory diseases.