000070333 001__ 70333
000070333 005__ 20231129152507.0
000070333 0247_ $$2doi$$a10.1371/journal.pone.0195820
000070333 0248_ $$2sideral$$a105918
000070333 037__ $$aART-2018-105918
000070333 041__ $$aeng
000070333 100__ $$0(orcid)0000-0001-9318-7107$$aValero, C.
000070333 245__ $$aCombined experimental and computational characterization of crosslinked collagen-based hydrogels
000070333 260__ $$c2018
000070333 5060_ $$aAccess copy available to the general public$$fUnrestricted
000070333 5203_ $$aCollagen hydrogels are widely used for in-vitro experiments and tissue engineering applications. Their use has been extended due to their biocompatibility with cells and their capacity to mimic biological tissues; nevertheless their mechanical properties are not always optimal for these purposes. Hydrogels are formed by a network of polymer filaments embedded on an aqueous substrate and their mechanical properties are mainly defined by the filament network architecture and the individual filament properties. To increase properties of native collagen, such as stiffness or strain-stiffening, these networks can be modified by adding crosslinking agents that alter the network architecture, increasing the unions between filaments. In this work, we have investigated the effect of one crosslinking agent, transglutaminase, in collagen hydrogels with varying collagen concentration. We have observed a linear dependency of the gel rigidity on the collagen concentration. Moreover, the addition of transglutaminase has induced an earlier strain-stiffening of the collagen gels. In addition, to better understand the mechanical implications of collagen concentration and crosslinkers inclusion, we have adapted an existing computational model, based on the worm-like chain model (WLC), to reproduce the mechanical behavior of the collagen gels. With this model we can estimate the parameters of the biopolymer networks without more sophisticated techniques, such as image processing or network reconstruction, or, inversely, predict the mechanical properties of a defined collagen network.
000070333 536__ $$9info:eu-repo/grantAgreement/ES/MINECO/ENE2014-52105-R$$9info:eu-repo/grantAgreement/ES/MINECO/DPI2015-64221-C2-1-R$$9info:eu-repo/grantAgreement/EC/FP7/306571/EU/Predictive modelling and simulation in mechano-chemo-biology: a computer multi-approach/INSILICO-CELL$$9info:eu-repo/grantAgreement/ES/DGA/T86$$9info:eu-repo/grantAgreement/ES/DGA/T12
000070333 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000070333 590__ $$a2.776$$b2018
000070333 591__ $$aMULTIDISCIPLINARY SCIENCES$$b23 / 69 = 0.333$$c2018$$dQ2$$eT2
000070333 592__ $$a1.1$$b2018
000070333 593__ $$aAgricultural and Biological Sciences (miscellaneous)$$c2018$$dQ1
000070333 593__ $$aMedicine (miscellaneous)$$c2018$$dQ1
000070333 593__ $$aBiochemistry, Genetics and Molecular Biology (miscellaneous)$$c2018$$dQ1
000070333 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000070333 700__ $$0(orcid)0000-0003-2212-447X$$aAmaveda, H.$$uUniversidad de Zaragoza
000070333 700__ $$0(orcid)0000-0003-4747-7327$$aMora, M.$$uUniversidad de Zaragoza
000070333 700__ $$0(orcid)0000-0002-9864-7683$$aGarcía-Aznar, J.M.$$uUniversidad de Zaragoza
000070333 7102_ $$15004$$2605$$aUniversidad de Zaragoza$$bDpto. Ingeniería Mecánica$$cÁrea Mec.Med.Cont. y Teor.Est.
000070333 7102_ $$15001$$2065$$aUniversidad de Zaragoza$$bDpto. Ciencia Tecnol.Mater.Fl.$$cÁrea Cienc.Mater. Ingen.Metal.
000070333 773__ $$g13, 4 (2018), e0195820[16 pp]$$pPLoS One$$tPLoS ONE$$x1932-6203
000070333 8564_ $$s629417$$uhttps://zaguan.unizar.es/record/70333/files/texto_completo.pdf$$yVersión publicada
000070333 8564_ $$s105121$$uhttps://zaguan.unizar.es/record/70333/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
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000070333 951__ $$a2023-11-29-15:04:30
000070333 980__ $$aARTICLE