Abstract: Post-traumatic osteoarthritis (PTOA) is a debilitating disease that presents in more than 50% of patients within 10-20 years of joint injury (i.e., ACL tear). During traumatic injuries our joints experience loads that vastly exceed the loads seen during normal physiological loading (i.e., walking).  These excessive loads, combined with loss of normal joint mechanics lead to cartilage swelling, cell death, and drastic bone loss within the first week after injury. However, the root cause of these changes and their role in the progression from injury to PTOA remains elusive. A potential mechanism for these changes is joint fluid transport. Joint fluid transport influences joint mechanics and is directly tied to the strain response of cartilage. The focus to date in musculoskeletal research has been on fluid transport within cartilage alone. Recently, studies have shown that musculoskeletal researchers may be ignoring a key player in joint mechanics and mass flux – bone to cartilage fluid transport. Bone to cartilage fluid transport may be a critical component of joint mechanics and provide cartilage with an additional source of nutrients. In addition, bone to cartilage fluid transport changes after traumatic injury may drive early joint changes, and the associated progression from injury to PTOA. Therefore, understanding the role of bone to cartilage fluid transport in health and disease is a logical next step toward understanding the progression from injury to PTOA.

Biography:  Brady Hislop is originally from Polson, MT, a small town in northwest Montana. He received his Bachelors of Science in Mechanical Engineering from the University of Idaho in 2019, and started his PhD in Mechanical Engineering at Montana State University in the fall of 2019. As a PhD candidate,  his research has focused on applying computational and experimental methods to better understand orthopedic systems. Furthermore, he was responsible for the conceptualization, design, development,  and utilization of a novel pipeline for untargeted metabolomics data – ensemble clustering de novo.