000065613 001__ 65613
000065613 005__ 20201113085627.0
000065613 0247_ $$2doi$$a10.1016/j.compbiomed.2018.02.001
000065613 0248_ $$2sideral$$a104416
000065613 037__ $$aART-2018-104416
000065613 041__ $$aeng
000065613 100__ $$0(orcid)0000-0002-8656-7846$$aCóndor, Mar$$uUniversidad de Zaragoza
000065613 245__ $$aA web-based application for automated quantification of chemical gradients induced in microfluidic devices
000065613 260__ $$c2018
000065613 5060_ $$aAccess copy available to the general public$$fUnrestricted
000065613 5203_ $$aBackground and objective
Advances in microfabrication have allowed the development and popularization of microfluidic devices, which are powerful tools to recreate three-dimensional (3-D) biologically relevant in vitro models. These microenvironments are usually generated by using hydrogels and induced chemical gradients. Going further, computational models enable, after validation, the simulation of such conditions without the necessity of real experiments, thus saving costs and time. In this work we present a web-based application that allows, based on a previous numerical model, the assessment of different chemical gradients induced within a 3-D extracellular matrix.
Methods
This application enables the estimation of the spatio-temporal chemical distribution inside microfluidic devices, by defining a first set of parameters characterizing the chip geometry, and a second set characterizing the diffusion properties of the hydrogel-based matrix. The simulated chemical concentration profiles generated within a synthetic hydrogel are calculated remotely on a server and returned to the website in less than 3¿min, thus offering a quick automatic quantification to any user. To ensure the day-to-day applicability, user requirements were investigated prior to tool development, pre-selecting some of the most common geometries. The tool is freely available online, after user registration, on http://m2be.unizar.es/insilico_cell under the software tab.
Results
Four different microfluidic device geometries were defined to study the dependence of the geometrical parameters onto the gradient formation processes. The numerical predictions demonstrate that growth factor diffusion within 3-D matrices strongly depends not only on the physics of diffusion, but also on the geometrical parameters that characterizes these complex devices. Additionally, the effect of the combination of different hydrogels inside a microfluidic device was studied.
Conclusions
The automatization of microfluidic device geometries generation provide a powerful tool which facilitates to any user the possibility to automatically create its own microfluidic device, greatly reducing the experimental validation processes and advancing in the understanding of in-vitro 3-D cell responses without the necessity of using commercial software or performing real testing experiments.
000065613 536__ $$9info:eu-repo/grantAgreement/ES/MINECO/DPI2015-64221-C2-1-R$$9info:eu-repo/grantAgreement/EC/FP7/306571/EU/Predictive modelling and simulation in mechano-chemo-biology: a computer multi-approach/INSILICO-CELL$$9info:eu-repo/grantAgreement/ES/DGA/C126
000065613 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000065613 590__ $$a2.286$$b2018
000065613 591__ $$aBIOLOGY$$b27 / 87 = 0.31$$c2018$$dQ2$$eT1
000065613 591__ $$aMATHEMATICAL & COMPUTATIONAL BIOLOGY$$b15 / 59 = 0.254$$c2018$$dQ2$$eT1
000065613 591__ $$aENGINEERING, BIOMEDICAL$$b39 / 80 = 0.488$$c2018$$dQ2$$eT2
000065613 591__ $$aCOMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS$$b52 / 106 = 0.491$$c2018$$dQ2$$eT2
000065613 592__ $$a0.57$$b2018
000065613 593__ $$aHealth Informatics$$c2018$$dQ2
000065613 593__ $$aComputer Science Applications$$c2018$$dQ2
000065613 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/submittedVersion
000065613 700__ $$aRüberg, Thomas
000065613 700__ $$0(orcid)0000-0002-3784-1140$$aBorau Zamora, Carlos$$uUniversidad de Zaragoza
000065613 700__ $$aPiles, Joan
000065613 700__ $$0(orcid)0000-0002-9864-7683$$aGarcía-Aznar, José Manuel$$uUniversidad de Zaragoza
000065613 7102_ $$15004$$2605$$aUniversidad de Zaragoza$$bDpto. Ingeniería Mecánica$$cÁrea Mec.Med.Cont. y Teor.Est.
000065613 773__ $$g95 (2018), 118-128$$pComput. biol. med.$$tCOMPUTERS IN BIOLOGY AND MEDICINE$$x0010-4825
000065613 8564_ $$s576050$$uhttps://zaguan.unizar.es/record/65613/files/texto_completo.pdf$$yPreprint
000065613 8564_ $$s32945$$uhttps://zaguan.unizar.es/record/65613/files/texto_completo.jpg?subformat=icon$$xicon$$yPreprint
000065613 909CO $$ooai:zaguan.unizar.es:65613$$particulos$$pdriver
000065613 951__ $$a2020-11-13-08:47:01
000065613 980__ $$aARTICLE