1. Non-destructive detection of matrix stabilization correlates with enhanced mechanical properties of self-assembled articular cartilage.
- Author
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Haudenschild AK, Sherlock BE, Zhou X, Hu JC, Leach JK, Marcu L, and Athanasiou KA
- Subjects
- Amino Acid Oxidoreductases pharmacology, Animals, Biomechanical Phenomena, Cartilage, Articular drug effects, Cattle, Collagen metabolism, Compressive Strength, Cross-Linking Reagents chemistry, Extracellular Matrix drug effects, Extracellular Matrix Proteins pharmacology, Humans, Proteoglycans pharmacology, Support Vector Machine, Tensile Strength, Tissue Engineering, Tissue Scaffolds chemistry, Cartilage, Articular physiology, Extracellular Matrix metabolism
- Abstract
Tissue engineers rely on expensive, time-consuming, and destructive techniques to monitor the composition, microstructure, and function of engineered tissue equivalents. A non-destructive solution to monitor tissue quality and maturation would greatly reduce costs and accelerate the development of tissue-engineered products. The objectives of this study were to (a) determine whether matrix stabilization with exogenous lysyl oxidase-like protein-2 (LOXL2) with recombinant hyaluronan and proteoglycan link protein-1 (LINK) would result in increased compressive and tensile properties in self-assembled articular cartilage constructs, (b) evaluate whether label-free, non-destructive fluorescence lifetime imaging (FLIm) could be used to infer changes in both biochemical composition and biomechanical properties, (c) form quantitative relationships between destructive and non-destructive measurements to determine whether the strength of these correlations is sufficient to replace destructive testing methods, and (d) determine whether support vector machine (SVM) learning can predict LOXL2-induced collagen crosslinking. The combination of exogenous LOXL2 and LINK proteins created a synergistic 4.9-fold increase in collagen crosslinking density and an 8.3-fold increase in tensile strength as compared with control (CTL). Compressive relaxation modulus was increased 5.9-fold with addition of LOXL2 and 3.4-fold with combined treatments over CTL. FLIm parameters had strong and significant correlations with tensile properties (R
2 = 0.82; p < 0.001) and compressive properties (R2 = 0.59; p < 0.001). SVM learning based on FLIm-derived parameters was capable of automating tissue maturation assessment with a discriminant ability of 98.4%. These results showed marked improvements in mechanical properties with matrix stabilization and suggest that FLIm-based tools have great potential for the non-destructive assessment of tissue-engineered cartilage., (© 2019 John Wiley & Sons, Ltd.)- Published
- 2019
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