Micro-porous PLGA/ β -TCP/TPU scaffolds prepared by solvent-based 3D printing for bone tissue engineering purposes.
Luan P HattSylvie WirthAapo RistaniemiDaniel J CiricKeith ThompsonDavid EglinMartin James StoddartAngela R ArmientoPublished in: Regenerative biomaterials (2023)
The 3D printing process of fused deposition modelling is an attractive fabrication approach to create tissue-engineered bone substitutes to regenerate large mandibular bone defects, but often lacks desired surface porosity for enhanced protein adsorption and cell adhesion. Solvent-based printing leads to the spontaneous formation of micropores on the scaffold's surface upon solvent removal, without the need for further post processing. Our aim is to create and characterize porous scaffolds using a new formulation composed of mechanically stable poly(lactic-co-glycol acid) and osteoconductive β-tricalcium phosphate with and without the addition of elastic thermoplastic polyurethane prepared by solvent-based 3D-printing technique. Large-scale regenerative scaffolds can be 3D-printed with adequate fidelity and show porosity at multiple levels analysed via micro-computer tomography, scanning electron microscopy and N 2 sorption. Superior mechanical properties compared to a commercially available calcium phosphate ink are demonstrated in compression and screw pull out tests. Biological assessments including cell activity assay and live-dead staining prove the scaffold's cytocompatibility. Osteoconductive properties are demonstrated by performing an osteogenic differentiation assay with primary human bone marrow mesenchymal stromal cells. We propose a versatile fabrication process to create porous 3D-printed scaffolds with adequate mechanical stability and osteoconductivity, both important characteristics for segmental mandibular bone reconstruction.
Keyphrases
- tissue engineering
- bone marrow
- electron microscopy
- bone regeneration
- bone mineral density
- ionic liquid
- mesenchymal stem cells
- soft tissue
- bone loss
- drug delivery
- cell adhesion
- high throughput
- endothelial cells
- machine learning
- body composition
- solar cells
- risk assessment
- deep learning
- small molecule
- heavy metals
- binding protein
- protein protein