Abstract
Biofabrication commonly involves the use of liquid droplets to transport cells to the printed structure. However, the viability of the cells after impact is poorly controlled and understood, hampering applications including cell spraying, inkjet bioprinting, and laser-assisted cell transfer. Here, we present an analytical model describing the cell viability after impact as a function of the cell-surrounding droplet characteristics. The model connects (1) the cell survival as a function of cell membrane elongation, (2) the membrane elongation as a function of the cell-containing droplet size and velocity, and (3) the substrate properties. The model is validated by cell viability measurements in cell spraying, which is a method for biofabrication and used for the treatment of burn wounds. The results allow for rational optimization of any droplet-based cell deposition technology, and we include practical suggestions to improve the cell viability in cell spraying.
Highlights
The current work aims to understand the influence of the droplet impact on cell viability, which is applicable both to drop-on-demand and spray deposition technologies
We introduce a model describing the cell viability as a function of the cell-containing droplet size, the viscosity, and the impact velocity
The model is shown to accurately describe the viability measurements as a function of the input parameters. These results provide a powerful tool to rationally evaluate and improve clinical spray treatments and tissue engineering applications
Summary
Of the impact process alone (for other technologies this is not the case, as explained in supplementary section I). The current work aims to understand the influence of the droplet impact on cell viability, which is applicable both to drop-on-demand and spray deposition technologies. We introduce a model describing the cell viability as a function of the cell-containing droplet size, the viscosity, and the impact velocity. The droplet size and impact velocity are measured and used to obtain model predictions as described. The cell viability after spraying is measured as a function of the air pressure, the liquid viscosity, the nozzle-substrate distance, and the substrate stiffness. The model is shown to accurately describe the viability measurements as a function of the input parameters. These results provide a powerful tool to rationally evaluate and improve clinical spray treatments and tissue engineering applications
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