Modeling the effect of blunt impact on mitochondrial function in cartilage: implications for development of osteoarthritis.

Autor:	Kapitanov GI; Department of Mathematics, University of Iowa, Iowa City, IA, United States of America., Ayati BP; Department of Mathematics, University of Iowa, Iowa City, IA, United States of America.; Program in Applied Mathematical & Computational Sciences, University of Iowa, Iowa City, IA, United States of America.; Department of Orthopedics & Rehabilitation, University of Iowa, Iowa City, IA, United States of America., Martin JA; Department of Orthopedics & Rehabilitation, University of Iowa, Iowa City, IA, United States of America.; Department of Biomedical Engineering, University of Iowa, Iowa City, IA, United States of America.
Jazyk:	angličtina
Zdroj:	PeerJ [PeerJ] 2017 Jul 17; Vol. 5, pp. e3468. Date of Electronic Publication: 2017 Jul 17 (Print Publication: 2017).
DOI:	10.7717/peerj.3468
Abstrakt:	Objective: Osteoarthritis (OA) is a disease characterized by degeneration of joint cartilage. It is associated with pain and disability and is the result of either age and activity related joint wear or an injury. Non-invasive treatment options are scarce and prevention and early intervention methods are practically non-existent. The modeling effort presented in this article is constructed based on an emerging biological hypothesis-post-impact oxidative stress leads to cartilage cell apoptosis and hence the degeneration observed with the disease. The objective is to quantitatively describe the loss of cell viability and function in cartilage after an injurious impact and identify the key parameters and variables that contribute to this phenomenon. Methods: We constructed a system of differential equations that tracks cell viability, mitochondrial function, and concentrations of reactive oxygen species (ROS), adenosine triphosphate (ATP), and glycosaminoglycans (GAG). The system was solved using MATLAB and the equations' parameters were fit to existing data using a particle swarm algorithm. Results: The model fits well the available data for cell viability, ATP production, and GAG content. Local sensitivity analysis shows that the initial amount of ROS is the most important parameter. Discussion: The model we constructed is a viable method for producing in silico studies and with a few modifications, and data calibration and validation, may be a powerful predictive tool in the search for a non-invasive treatment for post-traumatic osteoarthritis. Competing Interests: The authors declare there are no competing interests.
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu