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3D bioprinting is currently widely used to build engineered mammalian tissue constructs with complex spatial structures. It has revolutionized tissue engineering and is a promising avenue for regenerative medicine. Recently, 3D bioprinting has also been used for the fabrication of living tissues that cultivate microorganisms including photosynthetic single-celled microalgae and bacterial cells. Here we review the principles and applications of biomimetic 3D living materials powered by microorganisms. We envision that there will be great potential for the application of microorganism-driven materials in biomedicine, biotechnology, and living device fabrication as well as for ecosystem restoration.

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.

The effect of light scattering is non-negligible in micro-scale DMD-based 3D printing. Light scattering results in unwanted exposure and polymerization, thus deteriorating the fabrication resolution and fidelity. We report using machine learning (ML) approach to mitigate the effect of light scattering. A neural network (NN) was designed to study the highly-sophisticated relationship between the input digital masks and their corresponding output 3D printed structures. After trained with 300 pairs of digital masks and printed structures, the neural network was able to optimize the 3D printing process by suggesting the optimal grayscale digital masks which are not necessarily identical to the desired structures. Verification results showed that using NN-generated digital masks yielded significant improvements in printing resolution and fidelity compared to using masks that are identical to the desired structures.

Glioblastoma multiforme (GBM) is the most lethal primary brain tumor characterized by high cellular and molecular heterogeneity, hyper-vascularization, and innate drug resistance. Current treatment options include a combination of surgical resection, radiotherapy, and chemotherapy primarily with temozolomide, but the prognosis is poor with an average life expectancy of 15 months. Despite significant research and drug development efforts, therapeutic advances to treat glioblastoma remain stagnant. Cellular components and extracellular matrix (ECM) are the two primary sources of heterogeneity in GBM. One of the major roadblocks in understanding the genetic basis of the cancer and developing new therapies is the lack of physiologically relevant and patient-specific GBM tumor models. Here, we develop biomimetic tri-regional GBM models with a tumor region, an acellular ECM region, and an endothelial region – with regional stiffnesses patterned corresponding to the GBM stroma, pathological or normal brain parenchyma, and brain capillaries. 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 3D bioprinting technology utilized in our study enables rapid, flexible, and reproducible 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.

When using light-based three-dimensional (3D) printing methods to fabricate functional micro-devices, unwanted light scattering during the printing process is a significant challenge to achieve high-resolution fabrication. We report the use of a deep neural network (NN)-based machine learning (ML) technique to mitigate the scattering effect, where our NN was employed to study the highly sophisticated relationship between the input digital masks and their corresponding output 3D printed structures. Furthermore, the NN was used to model an inverse 3D printing process, where it took desired printed structures as inputs and subsequently generated grayscale digital masks that optimized the light exposure dose according to the desired structures’ local features. Verification results showed that using NN-generated digital masks yielded significant improvements in printing fidelity when compared with using masks identical to the desired structures.

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.

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.

Polycarbonates are widely used in food packages, drink bottles, and various healthcare products such as dental sealants and tooth coatings. However, bisphenol A (BPA) and phosgene used in the production of commercial polycarbonates pose major concerns to public health safety. Here, we report a green pathway to prepare BPA-free polycarbonates (BFPs) by thermal ring-opening polymerization and photopolymerization. Polycarbonates prepared from two cyclic carbonates in different mole ratios demonstrated tunable mechanical stiffness, excellent thermal stability, and high optical transparency. Three-dimensional (3D) printing of the new BFPs was demonstrated using a two-photon laser direct writing system and a rapid 3D optical projection printer to produce structures possessing complex high-resolution geometries. Seeded C3H10T1/2 cells also showed over 95% viability with potential applications in biological studies. By combining biocompatible BFPs with 3D printing, novel safe and high-performance biomedical devices and healthcare products could be developed with broad long-term benefits to society.

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.

DMD-based 3D printing is a powerful tool for making high-resolution biomimetic functional tissues and organs with various biomaterials for tissue engineering and regenerative medicine. A plethora of tissues have been fabricated using this technology including liver, heart, lung, kidney, blood vessels, cartilage, and placenta. In this article, we show prevascularization of the artificial tissue constructs using DMD-based 3D printing, which is essential to maintain the long term viability and function of a thick tissue. We also show a 3D printed biomimetic hepatic model that recapitulates the microarchitecture as well as the heterogeneous cell population of various cell types in the native liver tissue. It is important for the biomaterials to mimic the native microenvironment. Finally, we demonstrate that 3D printed tissue-specific decellularized extracellular matrix can improve cell response and behavior.

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 the 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.

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.

Limbal stem cell deficiency (LSCD) and corneal disorders are among the top global threats for human vision. Emerging therapies that integrate stem cell transplantation with engineered hydrogel scaffolds for biological and mechanical support are becoming a rising trend in the field. However, methods for high-throughput fabrication of hydrogel scaffolds, as well as knowledge of the interaction between limbal stem/progenitor cells (LSCs) and the surrounding extracellular matrix (ECM) are still much needed. Here, we employed digital light processing (DLP)-based bioprinting to fabricate hydrogel scaffolds encapsulating primary LSCs and studied the ECM-dependent LSC phenotypes. The DLP-based bioprinting with gelatin methacrylate (GelMA) or hyaluronic acid glycidyl methacrylate (HAGM) generated microscale hydrogel scaffolds that could support the viability of the encapsulated primary rabbit LSCs (rbLSCs) in culture. Immunocytochemistry and transcriptional analysis showed that the encapsulated rbLSCs remained active in GelMA-based scaffolds while exhibited quiescence in the HAGM-based scaffolds. The primary human LSCs (hLSCs) encapsulated within bioprinted scaffolds showed consistent ECM-dependent active/quiescent statuses. Based on these results, we have developed a novel bioprinted dual ECM ‘Yin-Yang’ model encapsulating LSCs to support both active and quiescent statues. Our findings provide valuable insights towards stem cell therapies and regenerative medicine for corneal reconstruction.

Microstereolithography is a light-assisted three-dimensional (3D) fabrication technology providing free-form fabrication capability with fine resolution and high speed. There is a wide range of material choice for this technology, including biomaterials such as hydrogels and proteins. It realizes 3D fabrication by spatially controlling light exposure so that the liquid state material solidifies at the predefined location and forms a solid structure as design. The prevailing polymerization mechanism is free-radical photopolymerization, which can be induced in a solution comprising the proper monomers and photoinitiators. Microstereolithography outstrips inkjet-based and extrusion-based micro 3D printing on fabrication resolution, fabrication speed, and structural integrity. While scanning-based microstereolithography is able to print a structure with a ∼100 nm resolution at a slow speed, projection-based microstereolithography offers a much faster fabrication speed (e.g., in seconds) at a microscale printing resolution.

In 4Pi microscopy, the intensity and polarization distributions of the focal spot directly determine the system resolution, influencing its extended applications. This paper illustrates how the focal spot is affected by the polarization and phase modulation of the incident beams. Various combinations of polarization states and phase modulations are considered and their effects on the focal spot are investigated. The optimal configurations for generating a solid spot and a doughnut-shaped spot are proposed. This paper provides the theoretical basis and reference for extended applications, such as super-resolution confocal microscopy, 4Pi microscopy or 4Pi-STED microscopy.

Hydrogel scaffolds that mimic the native extracellular matrix (ECM) environment play a crucial role in tissue engineering. It has been demonstrated that cell behaviors can be affected by not only the hydrogel's physical and chemical properties, but also its three dimensional (3D) geometrical structures. In order to study the influence of 3D geometrical cues on cell behaviors as well as the maturation and function of engineered tissues, it is imperative to develop 3D fabrication techniques for creating micro and nanoscale hydrogel constructs. Among existing techniques that can effectively pattern hydrogels, two-photon polymerization (2PP)-based femtosecond laser 3D printing technology allows one to produce hydrogel structures with a resolution of 100 nm. This article reviews the basics of this technique and some of its applications in tissue engineering.

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.

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.

Double-slit imaging is widely used for verifying the resolution of high-resolution and super-resolution microscopies. However, due to the fabrication limits, the slit width is generally non-negligible, which can affect the claimed resolution. In this paper we theoretically calculate the electromagnetic field distribution inside and near the metallic double slit using waveguide mode expansion method, and acquire the far-field image by vectorial Fourier optics. We find that the slit width has minimal influence when the illuminating light is polarized parallel to the slits. In this case, the claimed resolution should be based on the center-to-center distance of the double-slit. MOE (Min. of Education, S’pore) Published version

This Letter introduces an iterative phase-retrieval method based on the Gerchberg-Saxton (G-S) algorithm for generating any arbitrary 3D pattern in image space, while simultaneously controlling the polarization orientation at each pixel. For proof-of-principle, we generate a stereo focal spot array with distinct polarization orientation for each spot. This method is universal for controlling the output polarization; the only requirement is that the input polarization should be spatially inhomogeneous. This work has the potential to impact coherent imaging techniques and spectroscopy.

We propose a method for eliminating the deformations in fluorescence emission difference microscopy (FED). Due to excessive subtraction, negative values are inevitable in the original FED method, giving rise to deformations. We propose modulating the beam to generate an extended solid focal spot and a hollow focal spot. Negative image values can be avoided by using these two types of excitation spots in FED imaging. Hence, deformations are eliminated, and the signal-to-noise ratio is improved. In deformation-free imaging, the resolution is higher than that of confocal imaging by 32%. Compared to standard FED imaging with the same level of deformations, our method provides superior resolution.

We propose a method theoretically to break the diffraction limit and to improve the resolution in all three dimensions for fluorescence emission difference microscopy. We produce two kinds of hollow focal spot by phase modulation. By incoherent superposition, these two kinds of focal spot yield a 3D hollow focal spot. The optimal proportion of these two kinds of spot is given in the paper. By employing 3D hollow focal spot, super-resolution image can be yielded by means of fluorescence emission difference microscopy, with resolution enhanced both laterally and axially. According to computation result, size of point spread function of three-dimensional super-resolution imaging is reduced by about 40% in all three spatial directions with respect to confocal imaging.

We propose a novel method of generating a double-helix point spread function (DH-PSF) by focusing one vortex-phase-modulated, radially polarized, and annular Gaussian beam. The DH-PSF has two prominent lobes that rotate around the optical axis along the propagation direction of the light beam, which can be applied in displacement measurement with high resolution. Results of simulation based on the vectorial diffraction theory show that the displacement measurement method using the DH-PSF generated by the proposed method can achieve linearity with a correlation coefficient of 0.9999, a sensitivity of 51.837°/µm, and a measurement range of 3 µm. Further increase in displacement measurement precision can be achieved by introducing a special layer that is photosensitive only to the longitudinal component of the electric field.

A novel fluorescence emission difference technique is proposed for further enhancements of the lateral resolution in surface plasmon-coupled emission microscopy (SPCEM). In the proposed method, the difference between the image with phase modulation by using a 0-2π vortex phase plate (VPP) along with a diaphragm and the original image obtained from SPCEM is used to estimate the spatial distribution of the analyzed sample. By optimizing the size of the diaphragm and the subtractive factor, the lateral resolution can be enhanced by about 20% and 33%, compared with that in SPCEM with a single 0-2π VPP and conventional wide-field fluorescence microscopy, respectively. Related simulation results are presented to verify the capability of the proposed method for improving lateral resolution and reducing imaging distortion. It is believed that the proposed method has potentials to improve the performance of SPCEM, thus facilitating biological observation and research.

Fluorescence emission diffraction microscopy (FED) has proven to be an effective sub-diffraction-limited imaging method. In this paper, we theoretically propose a method to further enhance the resolving capability of FED. Using a coated mirror and only one objective lens, this method achieves not only the same axial resolution as 4Pi microscopy but also a higher lateral resolution. The point spread function (PSF) of our method is isotropic. According to calculations, the full width at half-maximum (FWHM) of the isotropic FED's PSF is 0.17λ along all three spatial directions. Compared with confocal microscopy, the lateral resolution is improved 0.7-fold, and the axial resolution is improved 3.1-fold. Simulation tests also demonstrate this method's advantage over traditional microscopy techniques.