A Comparison of the Histochemical and Image-Derived Proteoglycan Content of Articular CartilageAfara I1, Singh S2, Moody H 1 and Oloyede A1*
1School of Chemistry, Physics, and Mechanical Engineering, Science and Engineering Faculty, Institute of Health and Biomedical Innovation (IHBI), Queensland University of Technology, Brisbane, Australia
- *Corresponding Author:
- Adekunle Oloyede
School of Chemistry, Physics and Mechanical Engineering
Science and Engineering Faculty
Queensland University of Technology
2 George St, GPO. Box 2434 Brisbane, Australia
Tel: +61 7 3138 2158
Fax: +61 7 3864 1516
E-mail: [email protected]
Received date August 26, 2013; Accepted date October 04, 2013; Published date October 06, 2013
Citation: Afara I, Singh S, Moody H, Oloyede A (2013) A Comparison of the Histochemical and Image-Derived Proteoglycan Content of Articular Cartilage. Anatom Physiol 3:120. doi:10.4172/2161-0940.1000120
Copyright: © 2013 Afara I, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
There are several methods for determining the proteoglycan content of cartilage in biomechanics experiments. Many of these include assay-based methods and the histochemistry or spectrophotometry protocol where quantification is biochemically determined. More recently a method based on extracting data to quantify proteoglycan content has emerged using the image processing algorithms, e.g., in ImageJ, to process histological micrographs, with advantages including time saving and low cost. However, it is unknown whether or not this image analysis method produces results that are comparable to those obtained from the biochemical methodology. This paper compares the results of a well-established chemical method to those obtained using image analysis to determine the proteoglycan content of visually normal (n=33) and their progressively degraded counterparts with the protocols. The results reveal a strong linear relationship with a regression coefficient (R2) = 0.9928, leading to the conclusion that the image analysis methodology is a viable alternative to the spectrophotometry.