? Fitzpatrick Osteoarthritis (OA) is a degenerative joint condition affecting over one third of the US population over age 65. Analysts expect numbers to rise over the coming decades, given the increasingly aging and obese population. Knee OA is most prevalent, and can result in severe pain and debilitation. Since articular cartilage has little regenerative ability, no treatment offers a cure. Therefore, preventing OA initiation and limiting progression is critical to reducing incidence and severity. Historically, clinicians have seen OA as a ?wear-and-tear? condition driven by mechanical loads. However, it is becoming increasingly apparent that initiation and progression is multifaceted. Our goal is to enhance researcher and clinician understanding of OA and improve their ability to predict and then treat early onset and progression. Our objective is to develop the data-driven computational models needed to quantify interactions between the biomechanical, structural, and biological factors. Our hypothesis is that particular combinations of mechanical, structural, and biological factors effectively predict OA, and a computational model can help researchers and clinicians to quantify interactions and significantly improve their ability to apply effective early intervention strategies. Results would have an enormous functional, social, and economic impact across an aging population. Our proposed work focuses on three applications of computational modeling to understand OA: (1) longitudinal cartilage degeneration and relationship to baseline biological and bioimaging markers, (2) the adaptive response of cartilage structure to biological and mechanical inputs, and (3) evaluation of computational models as a potential guidance tool for surgical, rehabilitation, or musculoskeletal adaptation. Our long-term vision is to develop a computational platform that we can efficiently customize for individual subjects to represent their key biomechanical, structural, and biological parameters, enabling pre-clinical evaluation of surgical interventions or of therapies such as exercise/muscle training programs or gait adaptation strategies.
| King, Matthew D; Long, Thomas; Pfalmer, Daniel L et al. (2018) SPIDR: small-molecule peptide-influenced drug repurposing. BMC Bioinformatics 19:138 |
| LaFoya, Bryce; Munroe, Jordan A; Pu, Xinzhu et al. (2018) Src kinase phosphorylates Notch1 to inhibit MAML binding. Sci Rep 8:15515 |
| Anders, Catherine B; Eixenberger, Josh E; Franco, Nevil A et al. (2018) ZnO nanoparticle preparation route influences surface reactivity, dissolution and cytotoxicity. Environ Sci Nano 5:572-588 |
| LaFoya, Bryce; Munroe, Jordan A; Miyamoto, Alison et al. (2018) Beyond the Matrix: The Many Non-ECM Ligands for Integrins. Int J Mol Sci 19: |
| Stender, Christina J; Rust, Evan; Martin, Peter T et al. (2018) Modeling the effect of collagen fibril alignment on ligament mechanical behavior. Biomech Model Mechanobiol 17:543-557 |
| Rubin, Janet; Styner, Maya; Uzer, Gunes (2018) Physical Signals May Affect Mesenchymal Stem Cell Differentiation via Epigenetic Controls. Exerc Sport Sci Rev 46:42-47 |
| DePompeo, Christine M; Bond, Laura; George, Yelena E et al. (2018) Intra-abdominal complications following intestinal anastomoses by suture and staple techniques in dogs. J Am Vet Med Assoc 253:437-443 |
| Uzer, Gunes; Bas, Guniz; Sen, Buer et al. (2018) Sun-mediated mechanical LINC between nucleus and cytoskeleton regulates ?catenin nuclear access. J Biomech 74:32-40 |
| Warburton, Kevin J; Everingham, John B; Helms, Jillian L et al. (2018) Wear testing of a canine hip resurfacing implant that uses highly cross-linked polyethylene. J Orthop Res 36:1196-1205 |
| Beard Jr, Richard S; Hoettels, Brian A; Meegan, Jamie E et al. (2018) AKT2 maintains brain endothelial claudin-5 expression and selective activation of IR/AKT2/FOXO1-signaling reverses barrier dysfunction. J Cereb Blood Flow Metab :271678X18817512 |
Showing the most recent 10 out of 87 publications
