1. Toward stronger robocast calcium phosphate scaffolds for bone tissue engineering: A mini-review and meta-analysis.
- Author
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Liu Q, Lu WF, and Zhai W
- Subjects
- Bone and Bones, Compressive Strength, Tissue Scaffolds chemistry, Calcium Phosphates chemistry, Tissue Engineering methods
- Abstract
Among different treatments of critical-sized bone defects, bone tissue engineering (BTE) is a fast-developing strategy centering around the fabrication of scaffolds that can stimulate tissue regeneration and provide mechanical support at the same time. This area has seen an extensive application of bioceramics, such as calcium phosphate, for their bioactivity and resemblance to the composition of natural bones. Moreover, recent advances in additive manufacturing (AM) have unleashed enormous potential in the fabrication of BTE scaffolds with tailored porous structures as well as desired biological and mechanical properties. Robocasting is an AM technique that has been widely applied to fabricate calcium phosphate scaffolds, but most of these scaffolds do not meet the mechanical requirements for load-bearing BTE scaffolds. In light of this challenge, various approaches have been utilized to mechanically strengthen the scaffolds. In this review, the current state of knowledge and existing research on robocasting of calcium phosphate scaffolds are presented. Applying the Gibson-Ashby model, this review provides a meta-analysis from the published literature of the compressive strength of robocast calcium phosphate scaffolds. Furthermore, this review evaluates different approaches to the mechanical strengthening of robocast calcium phosphate scaffolds. The aim of this review is to provide insightful data and analysis for future research on mechanical strengthening of robocast calcium phosphate scaffolds and ultimately for their clinical applications., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not reflect the views of the A*STAR., (Copyright © 2021 Elsevier B.V. All rights reserved.)
- Published
- 2022
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