Head, D (2016) Biomechanical Analysis of Infectious Biofilms. Advances in Experimental Medicine and Biology, 915. pp. 99-114. ISSN 0065-2598
Abstract
The removal of infectious biofilms from tissues or implanted devices and their transmission through fluid transport systems depends in part of the mechanical properties of their polymeric matrix. Linking the various physical and chemical microscopic interactions to macroscopic deformation and failure modes promises to unveil design principles for novel therapeutic strategies targeting biofilm eradication, and provide a predictive capability to accelerate the development of devices, water lines, etc, that minimise microbial dispersal. Here, our current understanding of biofilm mechanics is appraised from the perspective of biophysics , with an emphasis on constitutive modelling that has been highly successful in soft matter. Fitting rheometric data to viscoelastic models has quantified linear and nonlinear stress relaxation mechanisms, how they vary between species and environments, and how candidate chemical treatments alter the mechanical response. The rich interplay between growth, mechanics and hydrodynamics is just becoming amenable to computational modelling and promises to provide unprecedented characterisation of infectious biofilms in their native state.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016, Springer International Publishing Switzerland. This is an author produced version of a paper published in Biophysics of Infection, Advances in Experimental Medicine and Biology. Uploaded in accordance with the publisher's self-archiving policy. The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-32189-9_8 |
Keywords: | Biomechanics; Biofilm viscoelasticity; Constitutive modelling |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) > Institute for Computational and Systems Science (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 02 Jun 2016 11:41 |
Last Modified: | 16 Jan 2018 07:17 |
Published Version: | http://dx.doi.org/10.1007/978-3-319-32189-9_8 |
Status: | Published |
Publisher: | Springer |
Identification Number: | 10.1007/978-3-319-32189-9_8 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:100188 |