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Mathematical model for bone mineralization
Defective bone mineralization has serious clinical manifestations, including deformities and fractures, but the regulation of this extracellular process is not fully understood. We have developed a mathematical model consisting of ordinary differential equations that describe collagen maturation, pr...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4544393/ https://www.ncbi.nlm.nih.gov/pubmed/26347868 http://dx.doi.org/10.3389/fcell.2015.00051 |
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author | Komarova, Svetlana V. Safranek, Lee Gopalakrishnan, Jay Ou, Miao-jung Yvonne McKee, Marc D. Murshed, Monzur Rauch, Frank Zuhr, Erica |
author_facet | Komarova, Svetlana V. Safranek, Lee Gopalakrishnan, Jay Ou, Miao-jung Yvonne McKee, Marc D. Murshed, Monzur Rauch, Frank Zuhr, Erica |
author_sort | Komarova, Svetlana V. |
collection | PubMed |
description | Defective bone mineralization has serious clinical manifestations, including deformities and fractures, but the regulation of this extracellular process is not fully understood. We have developed a mathematical model consisting of ordinary differential equations that describe collagen maturation, production and degradation of inhibitors, and mineral nucleation and growth. We examined the roles of individual processes in generating normal and abnormal mineralization patterns characterized using two outcome measures: mineralization lag time and degree of mineralization. Model parameters describing the formation of hydroxyapatite mineral on the nucleating centers most potently affected the degree of mineralization, while the parameters describing inhibitor homeostasis most effectively changed the mineralization lag time. Of interest, a parameter describing the rate of matrix maturation emerged as being capable of counter-intuitively increasing both the mineralization lag time and the degree of mineralization. We validated the accuracy of model predictions using known diseases of bone mineralization such as osteogenesis imperfecta and X-linked hypophosphatemia. The model successfully describes the highly nonlinear mineralization dynamics, which includes an initial lag phase when osteoid is present but no mineralization is evident, then fast primary mineralization, followed by secondary mineralization characterized by a continuous slow increase in bone mineral content. The developed model can potentially predict the function for a mutated protein based on the histology of pathologic bone samples from mineralization disorders of unknown etiology. |
format | Online Article Text |
id | pubmed-4544393 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-45443932015-09-07 Mathematical model for bone mineralization Komarova, Svetlana V. Safranek, Lee Gopalakrishnan, Jay Ou, Miao-jung Yvonne McKee, Marc D. Murshed, Monzur Rauch, Frank Zuhr, Erica Front Cell Dev Biol Cell and Developmental Biology Defective bone mineralization has serious clinical manifestations, including deformities and fractures, but the regulation of this extracellular process is not fully understood. We have developed a mathematical model consisting of ordinary differential equations that describe collagen maturation, production and degradation of inhibitors, and mineral nucleation and growth. We examined the roles of individual processes in generating normal and abnormal mineralization patterns characterized using two outcome measures: mineralization lag time and degree of mineralization. Model parameters describing the formation of hydroxyapatite mineral on the nucleating centers most potently affected the degree of mineralization, while the parameters describing inhibitor homeostasis most effectively changed the mineralization lag time. Of interest, a parameter describing the rate of matrix maturation emerged as being capable of counter-intuitively increasing both the mineralization lag time and the degree of mineralization. We validated the accuracy of model predictions using known diseases of bone mineralization such as osteogenesis imperfecta and X-linked hypophosphatemia. The model successfully describes the highly nonlinear mineralization dynamics, which includes an initial lag phase when osteoid is present but no mineralization is evident, then fast primary mineralization, followed by secondary mineralization characterized by a continuous slow increase in bone mineral content. The developed model can potentially predict the function for a mutated protein based on the histology of pathologic bone samples from mineralization disorders of unknown etiology. Frontiers Media S.A. 2015-08-21 /pmc/articles/PMC4544393/ /pubmed/26347868 http://dx.doi.org/10.3389/fcell.2015.00051 Text en Copyright © 2015 Komarova, Safranek, Gopalakrishnan, Ou, McKee, Murshed, Rauch and Zuhr. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cell and Developmental Biology Komarova, Svetlana V. Safranek, Lee Gopalakrishnan, Jay Ou, Miao-jung Yvonne McKee, Marc D. Murshed, Monzur Rauch, Frank Zuhr, Erica Mathematical model for bone mineralization |
title | Mathematical model for bone mineralization |
title_full | Mathematical model for bone mineralization |
title_fullStr | Mathematical model for bone mineralization |
title_full_unstemmed | Mathematical model for bone mineralization |
title_short | Mathematical model for bone mineralization |
title_sort | mathematical model for bone mineralization |
topic | Cell and Developmental Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4544393/ https://www.ncbi.nlm.nih.gov/pubmed/26347868 http://dx.doi.org/10.3389/fcell.2015.00051 |
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