New models, reinforced by in vivo experimentation, show why 5-10% of bone fractures don't heal properly, and how these cases may be treated to restart the healing process. Results of the model, published September 2 in the open-access journal PLoS Computational Biology, may benefit the ageing population in which the occurrence of bone fractures is expected to rise substantially in the near future.
In 5 to 10% of bone fracture cases, the healing process does not succeed in repairing the bone, which leads to the formation of delayed unions or even non-unions - fractures that fail to heal. Using a combination of an animal model mimicking a clinical non-union situation and a mathematical model developed for studying normal fracture healing, researchers at the Katholieke Universiteit Leuven (Belgium), University of Liège (Belgium), Edinburgh University (United Kingdom) and Oxford University (United Kingdom) investigated this health problem.
For example, the authors investigated the potential to treat non-unions by transplanting cells from the bone marrow to the fracture site. This was also tested in a pilot animal experiment; both the simulations and the experiments showed the formation of a bony union between the fractured bone ends. In addition, the researchers used the mathematical model to explain some unexpected experimental observations.
The study demonstrates the added value of using a combination of mathematical modelling and experimental research, as well the potential of using cell transplantation for the treatment of non-unions.
PLEASE ADD THIS LINK TO THE PUBLISHED ARTICLE IN ONLINE VERSIONS OF YOUR REPORT: http://www.
CITATION: Geris L, Reed AAC, Vander Sloten J, Simpson AHRW, Van Oosterwyck H (2010) Occurrence and Treatment of Bone Atrophic Non-Unions Investigated by an Integrative Approach. PLoS Comput Biol 6(9): e1000915. doi:10.1371/journal.pcbi.1000915
Katholieke Universiteit Leuven
+32 16 327096
This press release refers to an upcoming article in PLoS Computational Biology. The release is provided by journal staff and by the article authors and their institutions. Any opinions expressed in this release or article are the personal views of the journal staff and/or article contributors, and do not necessarily represent the views or policies of PLoS. PLoS expressly disclaims any and all warranties and liability in connection with the information found in the releases and articles and your use of such information.
PLoS Journals publish under a Creative Commons Attribution License (http://creativecommons.
About PLoS Computational Biology
PLoS Computational Biology (www.ploscompbiol.org) features works of exceptional significance that further our understanding of living systems at all scales through the application of computational methods. All works published in PLoS Computational Biology are open access. Everything is immediately available subject only to the condition that the original authorship and source are properly attributed. Copyright is retained
About the Public Library of Science
The Public Library of Science (PLoS) is a non-profit organization of scientists and physicians committed to making the world's scientific and medical literature a freely available public resource. For more information, visit http://www.