3D bioprinting of a stem cell-laden, multi-material tubular composite: An approach for spinal cord repair

Hamid, Omar A.; Eltaher, Hoda M.; Sottile, Virginie; Yang, Jing

doi:10.1016/j.msec.2020.111707

Cited by 53 publications

(33 citation statements)

References 52 publications

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“…Pluronic F127) into a hydrogel construct, which is removed after printing, can provide perfusion channels, which can increase cell viability and survival in larger constructs 29 . Furthermore, combining bioinks in controlled ratios to reproducibly create experimental tissue culture environments, enables studies of cell responses in which the role of the surrounding matrix composition or specific treatments can be evaluated 30 – 33 . To demonstrate the multimaterial printing capacity of the open source bioprinter, we designed a square construct intersected by eight spokes originating from the constructs center, to be printed with cell-laden laminin bioink (Fig.…”

Section: Resultsmentioning

confidence: 99%

An open source extrusion bioprinter based on the E3D motion system and tool changer to enable FRESH and multimaterial bioprinting

Engberg

Stelzl

Eriksson

et al. 2021

Sci Rep

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Bioprinting is increasingly used to create complex tissue constructs for an array of research applications, and there are also increasing efforts to print tissues for transplantation. Bioprinting may also prove valuable in the context of drug screening for personalized medicine for treatment of diseases such as cancer. However, the rapidly expanding bioprinting research field is currently limited by access to bioprinters. To increase the availability of bioprinting technologies we present here an open source extrusion bioprinter based on the E3D motion system and tool changer to enable high-resolution multimaterial bioprinting. As proof of concept, the bioprinter is used to create collagen constructs using freeform reversible embedding of suspended hydrogels (FRESH) methodology, as well as multimaterial constructs composed of distinct sections of laminin and collagen. Data is presented demonstrating that the bioprinted constructs support growth of cells either seeded onto printed constructs or included in the bioink prior to bioprinting. This open source bioprinter is easily adapted for different bioprinting applications, and additional tools can be incorporated to increase the capabilities of the system.

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Section: Resultsmentioning

confidence: 99%

An open source extrusion bioprinter based on the E3D motion system and tool changer to enable FRESH and multimaterial bioprinting

Engberg

Stelzl

Eriksson

et al. 2021

Sci Rep

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show abstract

“…Finally, since the bioprinting process has a lot of complexities, a future goal could be the application of machine learning (ML) and a computational method collection, which contains mathematical functions of the real world based on historical data. In this sense, ML could overcome the complexity of representing biological tissue models from tissue images into a 3D tissue model with cellular resolution and tissue properties, and the compatibility of different materials used could be predicted [278,279]. In addition, the combination of ML with Big Data, related to modern clinical images, could help solve the multiscale and multiparameter complexities when the number of changing parameters is exceeded in the processing and post-processing process.…”

Section: Discussionmentioning

confidence: 99%

The 3D Bioprinted Scaffolds for Wound Healing

et al. 2022

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Skin tissue engineering and regeneration aim at repairing defective skin injuries and progress in wound healing. Until now, even though several developments are made in this field, it is still challenging to face the complexity of the tissue with current methods of fabrication. In this review, short, state-of-the-art on developments made in skin tissue engineering using 3D bioprinting as a new tool are described. The current bioprinting methods and a summary of bioink formulations, parameters, and properties are discussed. Finally, a representative number of examples and advances made in the field together with limitations and future needs are provided.

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“…ML is, therefore, needed because of multiscale complexities of representing biological tissue models. In addition, ML can also help predict the compatibility of dissimilar materials used in bioprinting[ 5 , 6 ]. In processing and post-processing, it is almost impossible to perform wet experiments when the number of changing parameters exceeds a certain number, for example, ten parameters.…”

Section: Complexities In Bioprintingmentioning

confidence: 99%

Application of Machine Learning in 3D Bioprinting: Focus on Development of Big Data and Digital Twin

An¹,

Chua²,

Mironov³

2024

IJB

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The application of machine learning (ML) in bioprinting has attracted considerable attention recently. Many have focused on the benefits and potential of ML, but a clear overview of how ML shapes the future of three-dimensional (3D) bioprinting is still lacking. Here, it is proposed that two missing links, Big Data and Digital Twin, are the key to articulate the vision of future 3D bioprinting. Creating training databases from Big Data curation and building digital twins of human organs with cellular resolution and properties are the most important and urgent challenges. With these missing links, it is envisioned that future 3D bioprinting will become more digital and in silico, and eventually strike a balance between virtual and physical experiments toward the most efficient utilization of bioprinting resources. Furthermore, the virtual component of bioprinting and biofabrication, namely, digital bioprinting, will become a new growth point for digital industry and information technology in future.

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3D bioprinting of a stem cell-laden, multi-material tubular composite: An approach for spinal cord repair

Cited by 53 publications

References 52 publications

An open source extrusion bioprinter based on the E3D motion system and tool changer to enable FRESH and multimaterial bioprinting

An open source extrusion bioprinter based on the E3D motion system and tool changer to enable FRESH and multimaterial bioprinting

The 3D Bioprinted Scaffolds for Wound Healing

Application of Machine Learning in 3D Bioprinting: Focus on Development of Big Data and Digital Twin

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