Photopolymerization-based 3D printing has emerged as a promising technique to fabricate 3D structures. However, during the printing process, polymerized materials such as hydrogels often become highly light-scattering, thus perturbing incident light distribution and thereby deteriorating the final print resolution. To overcome this scattering-induced resolution deterioration, we developed a novel method termed flashing photopolymerization (FPP). Our FPP approach is informed by the fundamental kinetics of photopolymerization reactions, where light exposure is delivered in millisecond-scale flashes, as opposed to continuous light exposure. During the period of flash exposure, the prepolymer material negligibly scatters light. The material then polymerizes and opacifies in absence of light, therefore the exposure pattern is not perturbed by scattering. Compared to the conventional use of a continuous wave (CW) light source, the FPP fabrication resolution is improved. FPP also shows little dependency on the exposure, thus minimizing trial-and-error type optimization. Using FPP, we demonstrate its use in generating high-fidelity 3D printed constructs.

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.

The ability to noninvasively assess skeletal muscle microstructure, which predicts function and disease, would be of significant clinical value. One method that holds this promise is diffusion tensor magnetic resonance imaging (DT-MRI), which is sensitive to the microscopic diffusion of water within tissues and has become ubiquitous in neuroimaging as a way of assessing neuronal structure and damage. However, its application to the assessment of changes in muscle microstructure associated with injury, pathology, or age remains poorly defined, because it is difficult to precisely control muscle microstructural features in vivo. However, recent advances in additive manufacturing technologies allow precision-engineered diffusion phantoms with histology informed skeletal muscle geometry to be manufactured. Therefore, the goal of this study was to develop skeletal muscle phantoms at relevant size scales to relate microstructural features to MRI-based diffusion measurements. A digital light projection based rapid 3D printing method was used to fabricate polyethylene glycol diacrylate based diffusion phantoms with (1) idealized muscle geometry (no geometry; fiber sizes of 30, 50, or 70 μm or fiber size of 50 μm with 40% of walls randomly deleted) or (2) histology-based geometry (normal and after 30-days of denervation) containing 20% or 50% phosphate-buffered saline (PBS). Mean absolute percent error (8%) of the printed phantoms indicated high conformity to templates when "fibers" were >50 μm. A multiple spin-echo echo planar imaging diffusion sequence, capable of acquiring diffusion weighted data at several echo times, was used in an attempt to combine relaxometry and diffusion techniques with the goal of separating intracellular and extracellular diffusion signals. When fiber size increased (30-70 μm) in the 20% PBS phantom, fractional anisotropy (FA) decreased (0.32-0.26) and mean diffusivity (MD) increased (0.44 × 10^-3 mm²/s-0.70 × 10^-3 mm²/s). Similarly, when fiber size increased from 30 to 70 μm in the 50% PBS diffusion phantoms, a small change in FA was observed (0.18-0.22), but MD increased from 0.86 × 10^-3 mm²/s to 1.79 × 10^-3 mm²/s. This study demonstrates a novel application of tissue engineering to understand complex diffusion signals in skeletal muscle. Through this work, we have also demonstrated the feasibility of 3D printing for skeletal muscle with relevant matrix geometries and physiologically relevant tissue characteristics.

Since the advent of additive manufacturing, known commonly as 3D printing, this technology has revolutionized the biofabrication landscape and driven numerous pivotal advancements in tissue engineering and regenerative medicine. Many 3D printing methods were developed in short course after Charles Hull first introduced the power of stereolithography to the world. However, materials development was not met with the same enthusiasm and remained the bottleneck in the field for some time. Only in the past decade has there been deliberate development to expand the materials toolbox for 3D printing applications to meet the true potential of 3D printing technologies. Herein, we review the development of biomaterials suited for light-based 3D printing modalities with an emphasis on bioprinting applications. We discuss the chemical mechanisms that govern photopolymerization and highlight the application of natural, synthetic, and composite biomaterials as 3D printed hydrogels. Because the quality of a 3D printed construct is highly dependent on both the material properties and processing technique, we included a final section on the theoretical and practical aspects behind light-based 3D printing as well as ways to employ that knowledge to troubleshoot and standardize the optimization of printing parameters.

Recent advances in 3D bioprinting have transformed the tissue engineering landscape by enabling the controlled placement of cells, biomaterials, and bioactive agents for the biofabrication of living tissues and organs. However, the application of 3D bioprinting is limited by the availability of cytocompatible and printable biomaterials that recapitulate properties of native tissues. Here, we developed an integrated 3D projection bioprinting and orthogonal photoconjugation platform for precision tissue engineering of tailored microenvironments. By using a photoreactive thiol-ene gelatin bioink, soft hydrogels can be bioprinted into complex geometries and photopatterned with bioactive moieties in a rapid and scalable manner via digital light projection (DLP) technology. This enables localized modulation of biophysical properties such as stiffness and microarchitecture as well as precise control over spatial distribution and concentration of immobilized functional groups. As such, well-defined properties can be directly incorporated using a single platform to produce desired tissue-specific functions within bioprinted constructs. We demonstrated high viability of encapsulated endothelial cells and human cardiomyocytes using our dual process and fabricated tissue constructs functionalized with VEGF peptide mimics to induce guided endothelial cell growth for programmable vascularization. This work represents a pivotal step in engineering multifunctional constructs with unprecedented control, precision, and versatility for the rational design of biomimetic tissues.

Glioblastoma multiforme (GBM) is the most lethal primary brain tumor characterized by high cellular and molecular heterogeneity, hypervascularization, and innate drug resistance. Cellular components and extracellular matrix (ECM) are the two primary sources of heterogeneity in GBM. Here, biomimetic tri-regional GBM models with tumor regions, acellular ECM regions, and an endothelial region with regional stiffnesses patterned corresponding to the GBM stroma, pathological or normal brain parenchyma, and brain capillaries, are developed. Patient-derived GBM cells, human endothelial cells, and hyaluronic acid derivatives are used to generate a species-matched and biochemically relevant microenvironment. This in vitro study demonstrates that biophysical cues are involved in various tumor cell behaviors and angiogenic potentials and promote different molecular subtypes of GBM. The stiff models are enriched in the mesenchymal subtype, exhibit diffuse invasion of tumor cells, and induce protruding angiogenesis and higher drug resistance to temozolomide. Meanwhile, the soft models demonstrate enrichment in the classical subtype and support expansive cell growth. The three-dimensional bioprinting technology utilized in this study enables rapid, flexible, and reproducible patient-specific GBM modeling with biophysical heterogeneity that can be employed by future studies as a tunable system to interrogate GBM disease mechanisms and screen drug compounds.

Three-dimensional (3D) bioprinting techniques have emerged as the most popular methods to fabricate 3D-engineered tissues; however, there are challenges in simultaneously satisfying the requirements of high cell density (HCD), high cell viability, and fine fabrication resolution. In particular, bioprinting resolution of digital light processing-based 3D bioprinting suffers with increasing bioink cell density due to light scattering. We developed a novel approach to mitigate this scattering-induced deterioration of bioprinting resolution. The inclusion of iodixanol in the bioink enables a 10-fold reduction in light scattering and a substantial improvement in fabrication resolution for bioinks with an HCD. Fifty-micrometer fabrication resolution was achieved for a bioink with 0.1 billion per milliliter cell density. To showcase the potential application in tissue/organ 3D bioprinting, HCD thick tissues with fine vascular networks were fabricated. The tissues were viable in a perfusion culture system, with endothelialization and angiogenesis observed after 14 days of culture.

Engineered nerve guidance conduits (NGCs) have been demonstrated for repairing peripheral nerve injuries. However, there remains a need for an advanced biofabrication system to build NGCs with complex architectures, tunable material properties, and customizable geometrical control. Here, a rapid continuous 3D-printing platform was developed to print customizable NGCs with unprecedented resolution, speed, flexibility, and scalability. A variety of NGC designs varying in complexity and size were created including a life-size biomimetic branched human facial NGC. In vivo implantation of NGCs with microchannels into complete sciatic nerve transections of mouse models demonstrated the effective directional guidance of regenerating sciatic nerves via branching into the microchannels and extending toward the distal end of the injury site. Histological staining and immunostaining further confirmed the progressive directional nerve regeneration and branching behavior across the entire NGC length. Observational and functional tests, including the von Frey threshold test and thermal test, showed promising recovery of motor function and sensation in the ipsilateral limbs grafted with the 3D-printed NGCs.

Pterygium is an ocular surface disorder with high prevalence that can lead to vision impairment. As a pathological outgrowth of conjunctiva, pterygium involves neovascularization and chronic inflammation. Here, we developed a 3D multicellular in vitro pterygium model using a digital light processing (DLP)-based 3D bioprinting platform with human conjunctival stem cells (hCjSCs). A novel feeder-free culture system was adopted and efficiently expanded the primary hCjSCs with homogeneity, stemness and differentiation potency. The DLP-based 3D bioprinting method was able to fabricate hydrogel scaffolds that support the viability and biological integrity of the encapsulated hCjSCs. The bioprinted 3D pterygium model consisted of hCjSCs, immune cells, and vascular cells to recapitulate the disease microenvironment. Transcriptomic analysis using RNA sequencing (RNA-seq) identified a distinct profile correlated to inflammation response, angiogenesis, and epithelial mesenchymal transition in the bioprinted 3D pterygium model. In addition, the pterygium signatures and disease relevance of the bioprinted model were validated with the public RNA-seq data from patient-derived pterygium tissues. By integrating the stem cell technology with 3D bioprinting, this is the first reported 3D in vitro disease model for pterygium that can be utilized for future studies towards personalized medicine and drug screening.