Abstract Recently, 3D bioprinting techniques have been broadly recognized as a promising tool to fabricate functional tissues and organs. The bioink used for 3D bioprinting consists of biological materials and cells. Because of the dominant gravitational force, the suspended cells in the bioink sediment resulting in the accumulation and aggregation of cells. This study primarily focuses on the quantification of cell sedimentation-induced cell aggregation during and after inkjet-based bioprinting. The major conclusions are summarized as follows: (1) as the printing time increases from 0 min to 60 min, the percentage of the cells forming cell aggregates at the bottom of the bioink reservoir increases significantly from 3.6% to 54.5%, indicating a severe cell aggregation challenge in 3D bioprinting, (2) during inkjet-based bioprinting, at the printing time of only 15 min, more than 80% of the cells within the nozzle have formed cell aggregates. Both the individual cells and cell aggregates tend to migrate to the vicinity of the nozzle centerline mainly due to the weak shear-thinning properties of the bioink, and (3) after the bioprinting process, the mean cell number per microsphere increases significantly from 0.38 to 1.05 as printing time increases from 0 min to 15 min. The maximum number of cells encapsulated within one microsphere is ten, and 29.8% of the microspheres with cells encapsulated have contained small or large cell aggregates at the printing time of 15 min.
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Laser-based bioprinting for multilayer cell patterning in tissue engineering and cancer research
Abstract 3D printing, or additive manufacturing, is a process for patterning functional materials based on the digital 3D model. A bioink that contains cells, growth factors, and biomaterials are utilized for assisting cells to develop into tissues and organs. As a promising technique in regenerative medicine, many kinds of bioprinting platforms have been utilized, including extrusion-based bioprinting, inkjet bioprinting, and laser-based bioprinting. Laser-based bioprinting, a kind of bioprinting technology using the laser as the energy source, has advantages over other methods. Compared with inkjet bioprinting and extrusion-based bioprinting, laser-based bioprinting is nozzle-free, which makes it a valid tool that can adapt to the viscosity of the bioink; the cell viability is also improved because of elimination of nozzle, which could cause cell damage when the bioinks flow through a nozzle. Accurate tuning of the laser source and bioink may provide a higher resolution for reconstruction of tissue that may be transplanted used as an in vitro disease model. Here, we introduce the mechanism of this technology and the essential factors in the process of laser-based bioprinting. Then, the most potential applications are listed, including tissue engineering and cancer models. Finally, we present the challenges and opportunities faced by laser-based bioprinting.
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- Award ID(s):
- 1762202
- NSF-PAR ID:
- 10321204
- Editor(s):
- Jang, Jinah
- Date Published:
- Journal Name:
- Essays in Biochemistry
- Volume:
- 65
- Issue:
- 3
- ISSN:
- 0071-1365
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Compensating the cell-induced light scattering effect in light-based bioprinting using deep learningAbstract Digital light processing (DLP)-based three-dimensional (3D) printing technology has the advantages of speed and precision comparing with other 3D printing technologies like extrusion-based 3D printing. Therefore, it is a promising biomaterial fabrication technique for tissue engineering and regenerative medicine. When printing cell-laden biomaterials, one challenge of DLP-based bioprinting is the light scattering effect of the cells in the bioink, and therefore induce unpredictable effects on the photopolymerization process. In consequence, the DLP-based bioprinting requires extra trial-and-error efforts for parameters optimization for each specific printable structure to compensate the scattering effects induced by cells, which is often difficult and time-consuming for a machine operator. Such trial-and-error style optimization for each different structure is also very wasteful for those expensive biomaterials and cell lines. Here, we use machine learning to learn from a few trial sample printings and automatically provide printer the optimal parameters to compensate the cell-induced scattering effects. We employ a deep learning method with a learning-based data augmentation which only requires a small amount of training data. After learning from the data, the algorithm can automatically generate the printer parameters to compensate the scattering effects. Our method shows strong improvement in the intra-layer printing resolution for bioprinting, which can be further extended to solve the light scattering problems in multilayer 3D bioprinting processes.more » « less
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Abstract 3D bioprinting is an emerging technology to fabricate tissues and organs by precisely positioning cells into 3D structures using printable cell‐laden formulations known as bioinks. Various bioinks are utilized in 3D bioprinting applications; however, developing the perfect bioink to fabricate constructs with biomimetic microenvironment and mechanical properties that are similar to native tissues is a challenging task. In recent years, decellularized extracellular matrix (dECM)‐based bioinks have received an increasing attention in 3D bioprinting applications, since they are derived from native tissues and possess unique, complex tissue‐specific biochemical properties. This review focuses on designing dECM‐based bioinks for tissue and organ bioprinting, including commonly used decellularization and decellularized tissue characterization methods, bioink formulation and characterization, applications of dECM‐based bioinks, and most recent advancements in dECM‐based bioink design.
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Abstract The encapsulation of cells within gel‐phase materials to form bioinks offers distinct advantages for next‐generation 3D bioprinting. 3D bioprinting has emerged as a promising tool for patterning cells, but the technology remains limited in its ability to produce biofunctional, tissue‐like constructs due to a dearth of materials suitable for bioinks. While early demonstrations commonly used viscous polymers optimized for printability, these materials often lacked cell compatibility and biological functionality. In response, advanced materials that exist in the gel phase during the entire printing process are being developed, since hydrogels are uniquely positioned to both protect cells during extrusion and provide biological signals to embedded cells as the construct matures during culture. Here, an overview of the design considerations for gel‐phase materials as bioinks is presented, with a focus on their mechanical, biochemical, and dynamic gel properties. Current challenges and opportunities that arise due to the fact that bioprinted constructs are active, living hydrogels composed of both acellular and cellular components are also evaluated. Engineering hydrogels with consideration of cells as an intrinsic component of the printed bioink will enable control over the evolution of the living construct after printing to achieve greater biofunctionality.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1042/EBC20200093
