000015105 001__ 15105
000015105 005__ 20161115100211.0
000015105 04107 $$aeng
000015105 046__ $$k2016-08-21
000015105 100__ $$aFranck, Christian
000015105 24500 $$aMean deformation metrics for quantifying 3D cell-matrix interactions

000015105 24630 $$n24.$$p24th International Congress of Theoretical and Applied Mechanics - Book of Papers
000015105 260__ $$bInternational Union of Theoretical and Applied Mechanics, 2016
000015105 506__ $$arestricted
000015105 520__ $$2eng$$aInvestigations in mechanobiology rely in large part on correlation of cellular processes with mechanical signals, such as matrix stiffness and cell tractions. Almost all cell traction and force quantification methodologies require knowledge of the underlying mechanical properties of the extracellular matrix to convert displacement data into corresponding traction data. This restricts the use of these techniques to material systems for which the user can accurately determine material properties. To overcome this hurdle, we present a new approach that does not require any knowledge of the underlying matrix properties but rather makes use of the intrinsically recorded kinematic displacement data. We show through rigorous validation and an application to a neutrophil disease model that such an approach produces both accurate and biologically significant information similar to traditional force-focused approaches.

000015105 540__ $$aText je chráněný podle autorského zákona č. 121/2000 Sb.
000015105 653__ $$a

000015105 7112_ $$a24th International Congress of Theoretical and Applied Mechanics$$cMontreal (CA)$$d2016-08-21 / 2016-08-26$$gICTAM2016
000015105 720__ $$aFranck, Christian
000015105 8560_ $$ffischerc@itam.cas.cz
000015105 8564_ $$s204275$$uhttps://invenio.itam.cas.cz/record/15105/files/TS.SM01-4.05.pdf$$yOriginal version of the author's contribution as presented on CD,  page 1695, code TS.SM01-4.05
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000015105 962__ $$r13812
000015105 980__ $$aPAPER