journal article·2021-10-01Open access

Bio-3D printing iPSC-derived human chondrocytes for articular cartilage regeneration

Anna Nakamura, Daiki Murata, Ryota Fujimoto, Sakura Tamaki, Sanae Nagata, Makoto Ikeya, Junya Toguchida, Koichi Nakayama

Biofabrication· Volume 13· Issue 4

Abstract

Abstract Osteoarthritis is a leading cause of pain and joint immobility, the incidence of which is increasing worldwide. Currently, total joint replacement is the only treatment for end-stage disease. Scaffold-based tissue engineering is a promising alternative approach for joint repair but is subject to limitations such as poor cytocompatibility and degradation-associated toxicity. To overcome these limitations, a completely scaffold-free Kenzan method for bio-3D printing was used to fabricate cartilage constructs feasible for repairing large chondral defects. Human induced pluripotent stem cell (iPSC)-derived neural crest cells with high potential to undergo chondrogenesis through mesenchymal stem cell differentiation were used to fabricate the cartilage. Unified, self-sufficient, and functional cartilaginous constructs up to 6 cm2 in size were assembled by optimizing fabrication time during chondrogenic induction. Maturation for 3 weeks facilitated the self-organisation of the cells, which improved the construct’s mechanical strength (compressive and tensile properties) and induced changes in glycosaminoglycan and type II collagen expression, resulting in improved tissue function. The compressive modulus of the construct reached the native cartilage range of 0.88 MPa in the 5th week of maturation. This paper reports the fabrication of anatomically sized and shaped cartilage constructs, achieved by combining novel iPSCs and bio-3D printers using a Kenzan needle array technology, which may facilitate chondral resurfacing of articular cartilage defects.
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Research context

OpenAlex topics: Osteoarthritis Treatment and Mechanisms · 3D Printing in Biomedical Research · Total Knee Arthroplasty Outcomes

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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