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Non-destructive detection of matrix stabilization correlates with enhanced mechanical properties of self-assembled articular cartilage.
Haudenschild, Anne K; Sherlock, Benjamin E; Zhou, Xiangnan; Hu, Jerry C; Leach, J Kent; Marcu, Laura; Athanasiou, Kyriacos A.
Afiliação
  • Haudenschild AK; Department of Biomedical Engineering, University of California Davis, Davis, CA, USA.
  • Sherlock BE; Department of Biomedical Engineering, University of California Davis, Davis, CA, USA.
  • Zhou X; Department of Biomedical Engineering, University of California Davis, Davis, CA, USA.
  • Hu JC; Department of Biomedical Engineering, University of California Irvine, Irvine, CA, USA.
  • Leach JK; Department of Biomedical Engineering, University of California Davis, Davis, CA, USA.
  • Marcu L; Department of Orthopaedic Surgery, University of California Davis Medical Center, Sacramento, CA, USA.
  • Athanasiou KA; Department of Biomedical Engineering, University of California Davis, Davis, CA, USA.
J Tissue Eng Regen Med ; 13(4): 637-648, 2019 04.
Article em En | MEDLINE | ID: mdl-30770656
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 (R2  = 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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Cartilagem Articular / Matriz Extracelular Tipo de estudo: Diagnostic_studies Limite: Animals / Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Cartilagem Articular / Matriz Extracelular Tipo de estudo: Diagnostic_studies Limite: Animals / Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article