4.7 Article

A novel mechanobiological model can predict how physiologically relevant dynamic loading causes proteoglycan loss in mechanically injured articular cartilage

期刊

SCIENTIFIC REPORTS
卷 8, 期 -, 页码 -

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NATURE PUBLISHING GROUP
DOI: 10.1038/s41598-018-33759-3

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资金

  1. University of Eastern Finland
  2. Massachusetts Institute of Technology
  3. Doctoral Programme in Science, Technology and Computing (SCITECO)
  4. European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant [713645, 702586]
  5. Academy of Finland [286526, 305138]
  6. Sigrid Juselius Foundation
  7. European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme [755037]
  8. National Institutes of Health (NIH) [UG3/UH3 TR002186]
  9. CSC-IT Center for Science Ltd, Finland
  10. Marie Curie Actions (MSCA) [702586] Funding Source: Marie Curie Actions (MSCA)
  11. European Research Council (ERC) [755037] Funding Source: European Research Council (ERC)

向作者/读者索取更多资源

Cartilage provides low-friction properties and plays an essential role in diarthrodial joints. A hydrated ground substance composed mainly of proteoglycans (PGs) and a fibrillar collagen network are the main constituents of cartilage. Unfortunately, traumatic joint loading can destroy this complex structure and produce lesions in tissue, leading later to changes in tissue composition and, ultimately, to post-traumatic osteoarthritis (PTOA). Consequently, the fixed charge density (FCD) of PGs may decrease near the lesion. However, the underlying mechanisms leading to these tissue changes are unknown. Here, knee cartilage disks from bovine calves were injuriously compressed, followed by a physiologically relevant dynamic compression for twelve days. FCD content at different follow-up time points was assessed using digital densitometry. A novel cartilage degeneration model was developed by implementing deviatoric and maximum shear strain, as well as fluid velocity controlled algorithms to simulate the FCD loss as a function of time. Predicted loss of FCD was quite uniform around the cartilage lesions when the degeneration algorithm was driven by the fluid velocity, while the deviatoric and shear strain driven mechanisms exhibited slightly discontinuous FCD loss around cracks. Our degeneration algorithm predictions fitted well with the FCD content measured from the experiments. The developed model could subsequently be applied for prediction of FCD depletion around different cartilage lesions and for suggesting optimal rehabilitation protocols.

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