Calcium diffusion and gelling front migration determination in hydrogels blend for computational 3D modelling in 3D bioprinting applications

PALMA J.; BERTUOLA M.; HERMIDA E.B.

Dresden

Congreso; 7th International Conference on Cellular Materials - CellMAT 2022; 2022

German Materials Society (DGM)

Natural hydrogels are widely used for 3D-bioprinting of scaffolds thatemulate the extracellular matrixof different human tissues; Alginatebased gels are among the most broadly used. Crosslinking by Ca2+ionsis a key issue for achieving the proper mechanical response; thedynamics of this process has beenreported for alginate andalginate-gelatine systems [1,2] however, 3D modelling of scaffolds ofanyshape, with calculated diffusion parameters is not alreadyimplemented.The aim of this work was study the kinetics of the gellingfront and the diffusion of Calcium ions withinthe matrix of theAlginate-Gelatine-Hyaluronic acid (Alg-Gel-HA) tripartite ink (4.5%w/v of eachpolymer in PBS1X) using a simple and low-cost method (videorecord and image analysis by ImageJ®).Experimental data could be wellfitted by a numerical model (Python script) that predicts the timeformaximum cross-linking, according to the dimension and shape of thescaffolds.Samples were prepared by placing a drop of Alg-Gel-HA inkonto a glass slide, and pressing with acoverslip until the ink reachesthe edge of the coverslip. Each sample was mounted above a blackbaseand a USB camera with red light was used to enhance contrast inthe video. Once the video recordingwas started, 0.5M of Ca2+ wasinjected at one edge of the coverslip; the ink becomes opaque asthethe Ca2+ diffuses. The diffusion front was followed and recordedfor 40min at 22°C; the advance of thecrosslinking front (x) at thetime (t) was determined using the software image J®. These data couldbefitted by the equation: x = A*t1/2, where A is a constant, followingthe typical relation for a diffusionprocess. This A value was includedin a numerical code in Phyton, developed to model how thecrosslinkingproceeds in an any shape sample, just using the .STL file as the inputof the code. Thismodel was validated using circular samples as shownin the Fig 1.Processing the time evolution of the crosslinking front(border of the opaque outer area) shown in Fig1,A=(0.039±0.004)mm/s1/2 arises. Introducing this value in the Pythoncode we programmed we couldsimulate the advance of the crosslinkingfront and validate the results using circle shaped scaffold (Fig.1).Therefore, the experimental device and the image analysis have becomeproper to predict how thecrosslinking process takes place even incomplex structures. However, the numerical model fits verywell thebeginning of the diffusion process, but changes in the boundaryconditions deviate theprediction when more than 50% of the samples hasbeen crosslinked. For instance, the time neededto fully crosslink thesample of Fig 1 cylinder was t=(2700 ± 300)s while the simulationpredictt=(4400±700)s.References[1] A. Posbeyikian, et al.,Carbohydrate Polymers, 2021, 269, 1-10.[2] M.S. Chavez, et al.,Journal of food science, 1994, 59, 1108-1110.