Date of Award


Degree Type


Degree Name

Master of Science in Biomedical Engineering


Biomedical Engineering

Committee Chair

Eric A. Nauman

Committee Co-Chair

Russell P. Main

Committee Member 1

Sarah Calve


While the mechanotransductive capability of skeletal tissue has been acknowledged for decades, the exact mechanisms that enable bone to sense and respond to external stimuli have remained elusive. Numerous theories have evolved to explain this behavior, most notably those involving fluid movement through the tissue’s hierarchical structure. Within mineralized bone, osteocytes reside in micro and nanoporosities, known as lacunae and canaliculi, which house the cell body and their long cellular processes, respectively. Through this lacunar-canalicular system (LCS), osteocytes form an interconnected network, which allow signaling and communication with surrounding osteocytes via gap junctions and secreted factors. It has been theorized that external loading-induced interstitial fluid movement along the cell processes results in shear stresses and/or drag forces that elicit stimulatory responses from osteocytes. While length and mineralized tissue render direct measurements inaccessible, mathematical and computational modeling have been utilized to predict these potential stimulatory mechanisms. However, assumptions regarding the presence of a glycocalyx, which is a pericellular matrix within the interstitial fluid space, are typically made despite the inability to fully characterize its structure. Thus, to investigate the importance of the possible compositions of this glycocalyx, a mathematical model of interstitial fluid flow within a canaliculus was developed, utilizing mixture theory. Resulting sensitivity analyses show that assumptions regarding the glycocalyx greatly influence the profile within the LCS, therefore affecting potential mechanotransductive signals. Additionally, confocal microscopy and a custom, automated reconstruction algorithm, were used to generate three-dimensional renderings of confocal images to further characterize the LCS and improve computational models. Both the mathematical model and reconstruction of the LCS will enhance the development of accurate predictive models and increase understanding of bone’s mechanotransductive abilities.