Abstract

Cartilages of the nasal septum, knee joint, rib, and nucleus pulposus of the intervertebral disc, as well as trypsinized and defective cartilage samples, were examined as samples. The IR spectra of the cartilage samples, as well as calibration mixtures of collagen and chondroitin sulfate, were obtained. The IR spectra were collected using the attenuated total reflectance techniques, and their processing was performed using the TQ Analyst software and the principal component regression calibration technique. Based on calibration dependence, the Ksp coefficient was determined as the ratio of the mass fractions of collagen and chondroitin sulfate. Its value was compared with the value of Kchem, equal to the ratio of the mass fractions of collagen and chondroitin sulfate, obtained using the classical chemical analysis of these substances. The IR spectra of cartilage tissues are a superposition of the IR spectra of collagen and chondroitin sulfate and qualitatively reflect their composition. A change in the ratio between the relative intensities of the characteristic bands of compounds in the IR spectrum is obvious only with a significant change in the content of these compounds in cartilage. This change occurs after trypsinization, when Ksp increases from 0.88±0.05 (Kchem~0.8) to 4.55. The use of a calibration model with a complete analysis of the cartilage IR spectrum made it possible to determine the difference in the ratio of the main components in the matrix of different samples in the absence of obvious changes in the IR spectra. Thus, a statistically significant decrease in the content of chondroitin sulfate in degraded articular cartilage (Ksp=4.4±1.8; Kchem~5.5) was shown compared with intact samples (Ksp=2.8±1.1; Kchem~2.6). IR spectrometric express analysis of cartilage tissue employing the principal component regression method allows a correct determination of the ratio of the main components in the cartilage matrix, those of collagen and glycosaminoglycans. The proposed technique includes one measurement, does not require prolonged and laborious sample preparation, does not require long, multi-stage and laborious chemical manipulations to determine each of the components, and makes it possible to determine the features and changes in the composition for a large set of samples of cartilage tissue of different types. In future, this approach can be used for non-invasive diagnostics of cartilage tissue.

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