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Non‐destructive detection of matrix stabilization correlates with enhanced mechanical properties of self‐assembled articular cartilage
Author(s) -
Haudenschild Anne K.,
Sherlock Benjamin E.,
Zhou Xiangnan,
Hu Jerry C.,
Leach J. Kent,
Marcu Laura,
Athanasiou Kyriacos A.
Publication year - 2019
Publication title -
journal of tissue engineering and regenerative medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.835
H-Index - 72
eISSN - 1932-7005
pISSN - 1932-6254
DOI - 10.1002/term.2824
Subject(s) - ultimate tensile strength , biomedical engineering , cartilage , compressive strength , cartilage oligomeric matrix protein , tissue engineering , extracellular matrix , lysyl oxidase , matrix (chemical analysis) , articular cartilage , materials science , chemistry , biophysics , osteoarthritis , composite material , biochemistry , anatomy , pathology , biology , medicine , alternative medicine
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 ( R 2 = 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.