Abstract
Exercise and physical activity exert mechanical loading on the bones which induces bone formation. However, the relationship between the osteocyte lacunar-canalicular morphology and mechanical stress experienced locally by osteocytes transducing signals for bone formation is not fully understood. In this study, we used computational modeling to predict the effect of canalicular density, the number of fluid inlets, and load direction on fluid flow shear stress (FFSS) and bone strains and how these might change following the microstructural deterioration of the lacunar-canalicular network that occurs with aging. Four distinct computational models were initially generated of osteocytes with either ten or eighteen dendrites using a fluid–structure interaction method with idealized geometries. Next, a young and a simulated aged osteocyte were developed from confocal images after FITC staining of the femur of a 4-month-old C57BL/6 mouse to estimate FFSS using a computational fluid dynamics approach. The models predicted higher fluid velocities in the canaliculi versus the lacunae. Comparison of idealized models with five versus one fluid inlet indicated that with four more inlets, one-half of the dendrites experienced FFSS greater than 0.8 Pa, which has been associated with osteogenic responses. Confocal image-based models of real osteocytes indicated a six times higher ratio of canalicular to lacunar surface area in the young osteocyte model than the simulated aged model and the average FFSS in the young model (FFSS = 0.46 Pa) was three times greater than the aged model (FFSS = 0.15 Pa). Interestingly, the surface area with FFSS values above 0.8 Pa was 23 times greater in the young versus the simulated aged model. These findings may explain the impaired mechano-responsiveness of osteocytes with aging.
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Acknowledgements
The authors would like to acknowledge the National Science Foundation (NSF, award number NSF-CMMI-1662284 PI: T Ganesh), National Institute of Health (NIH-NIA P01 AG039355 PI: LF Bonewald) and (NIH/SIG S10OD021665, S10RR027668 and R21 AR054449, PI: SL Dallas), and the University of Missouri-Kansas City School of Graduate Studies Research Grant Program.
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MN developed the FSI models from the images, developed and ran the FSI models, wrote several parts of the paper and helped with editing the final manuscript. LEL helped in developing the images for the model developed by MN. SLD runs the imaging laboratory where the images were taken and helped to train the students to do this work. She also helped in providing feedback and editing the manuscript. MLJ run the mice laboratory and all the mice used for the project were from his lab. He also helped to provide guidance and edited the manuscript. TG guided the dissertation work of MN of which this work is a part of. He provided overall guidance to MN and the project in the engineering aspects. He also helped in the development and editing of the manuscript.
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Niroobakhsh, M., Laughrey, L.E., Dallas, S.L. et al. Computational modeling based on confocal imaging predicts changes in osteocyte and dendrite shear stress due to canalicular loss with aging. Biomech Model Mechanobiol 23, 129–143 (2024). https://doi.org/10.1007/s10237-023-01763-w
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DOI: https://doi.org/10.1007/s10237-023-01763-w