## 4 Discussion
Moreover, the stem cells were assumed to originate from the periosteum, the outer cortical surface and medullary canal according to mechano-regulation tissue differentiation [12; 17; 18; 39]. The objective of the present study was to perform a robust test of this theory by applying it to a MSC implantation model in knee OA where different mechanical loadings were used to alter the cartilage regeneration response. One of the main strengths of this study is that the modeling technique used to test the mechano-regulation theory is dissimilar to those typically used to investigate the mechano-regulation of cartilage regeneration. Many previous computational studies examining the mechano-biology of cartilage regeneration only investigated the physiological axial load. Additionally, they described boundary and contact conditions that do not accurately reflect clinical situations using simple phenomenological computational models. Our knee joint model that was developed from real medical imaging could successfully predict the patterns of cellular differentiation in osteochondral defect regeneration. A previous study demonstrated regeneration through both endochondral and direct intramembranous ossification in the base of the defect, with cartilage formation occurring at the center of the defect and fibrous tissue formation superficially [40]. This pattern of repair was also found in the present model. We also found that gait cycle loading was better than vertical loading for cartilage regeneration. However, in the simple vertical loading model, increased bone formation was predicted to occur via endochondral ossification and particular regions of the cartilage began to differentiate into fibrous tissue, ultimately leading to a reduction in the amount of cartilage within the defect. Due to an increase in the magnitude of fluid flow within the defect, the stimulus for fibrous tissue formation is increased [41]. This increase in strain also promotes cell death at the articular surface [41]. Thus, preventing this fibrous tissue formation superficially and any subsequent cell death by an appropriate rehabilitation protocol would be beneficial in avoiding long-term failure of tissue repair. There are also several limitations to this study. First, we assumed that cell movement can be described using a diffusion equation of a non-linear relationship that exists between mitosis/cell death and the magnitude of strain experienced by cells; and that tissue differentiation is regulated by a combination of the magnitude of octahedral shear strain and fluid flow within the tissue, which may not be completely accurate. Second, we did not account for the rate at which cells differentiate and produce a matrix and we did not attempt to model the effects of growth factors, such as transforming growth factor-beta. Third, we did not model the scaffold. The MSCs are not actually injected directly but should rather be implanted in combination with a scaffold. Fourth, our model could not be validated using experimental data. It is very challenging to find experimental data with identical conditions. There are also advantages of using computational simulations to predict the results in this way. In addition, we validated it with previous computational results. Finally, the developed models did not consider cells that only migrate into the defect from the exposed cancellous bone and it was instead assumed that MSCs could only enter the defect through implantation. Developments of computational technology have now enabled researchers to perform simulations from a patient- or subject-specific perspective in the orthopedic field. Our results were obtained using a 3D model developed from real medical imaging and our results demonstrate that stance-phase loading was better than axial loading for cartilage regeneration. This is because simple vertical loading may cause excessive strain, while a stance-phase gait cycle prevents this strain at the cartilage defect due to the relationship with other loadings.