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Diffusion-Based 3D Bioprinting Strategies.

Betty Cai1, David Kilian1, Daniel Ramos Mejia1

  • 1Department of Materials Science and Engineering, Stanford University, 476 Lomita Mall, Stanford, CA, 94305, USA.

Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|December 25, 2023
PubMed
Summary
This summary is machine-generated.

Controlled diffusion is a key strategy in 3D bioprinting for tailoring tissue constructs. This approach manipulates molecular movement to precisely control material properties and cell behavior in biofabrication.

Keywords:
bioprintingdiffusioninterfacial gelationmulti-material constructsperfusable structures

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Area of Science:

  • Biomaterials Engineering
  • Tissue Engineering
  • Biotechnology

Background:

  • 3D bioprinting allows fabrication of cell-laden, tissue-mimetic constructs with complex geometries.
  • Controlled diffusion is an emerging strategy to precisely engineer bioprinted construct properties.
  • Molecular diffusion influences microstructure, stiffness, and biochemistry, impacting cell phenotype.

Purpose of the Study:

  • To review recent advances in diffusion-based 3D bioprinting strategies.
  • To discuss methods for characterizing and predicting diffusion in bioprinting.
  • To highlight future directions for overcoming biofabrication limitations using diffusion.

Main Methods:

  • Categorization of diffusion-based strategies: inward, outward, and internal diffusion.
  • Review of applications including diffusion-induced gelation for multi-material constructs.
  • Discussion of characterization and prediction methods for diffusion processes.

Main Results:

  • Diffusion strategies enable tailoring of construct properties like stiffness and microstructure.
  • Inward, outward, and internal diffusion offer distinct control mechanisms.
  • Diffusion-induced gelation facilitates creation of complex geometries and dynamic properties.

Conclusions:

  • Diffusion-based strategies are crucial for advanced biofabrication.
  • Further research in diffusion characterization and prediction is needed.
  • Optimizing diffusion control will enhance capabilities in tissue engineering and regenerative medicine.