Additive manufacturing, otherwise known as three-dimensional (3D) printing, is driving major innovations in many areas, such as engineering, manufacturing, art, education and medicine. Recent advances have enabled 3D printing of biocompatible materials, cells and supporting components into complex 3D functional living tissues. 3D bioprinting is being applied to regenerative medicine to address the need for tissues and organs suitable for transplantation. Compared with non-biological printing, 3D bioprinting involves additional complexities, such as the choice of materials, cell types, growth and differentiation factors, and technical challenges related to the sensitivities of living cells and the construction of tissues. Addressing these complexities requires the integration of technologies from the fields of engineering, biomaterials science, cell biology, physics and medicine. 3D bioprinting has already been used for the generation and transplantation of several tissues, including multilayered skin, bone, vascular grafts, tracheal splints, heart tissue and cartilaginous structures. Other applications include developing high-throughput 3D-bioprinted tissue models for research, drug discovery and toxicology.

3D bioprinting of tissues and organs

Additive manufacturing (AM) alias 3D printing translates computer-aided design (CAD) virtual 3D models into physical objects. By digital slicing of CAD, 3D scan, or tomography data, AM builds objects layer by layer without the need for molds or machining. AM enables decentralized fabrication of customized objects on demand by exploiting digital information storage and retrieval via the Internet. The ongoing transition from rapid prototyping to rapid manufacturing prompts new challenges for mechanical engineers and materials scientists alike. Because polymers are by far the most utilized class of materials for AM, this Review focuses on polymer processing and the development of polymers and advanced polymer systems specifically for AM. AM techniques covered include vat photopolymerization (stereolithography), powder bed fusion (SLS), material and binder jetting (inkjet and aerosol 3D printing), sheet lamination (LOM), extrusion (FDM, 3D dispensing, 3D fiber deposition, and 3D plotting), and 3D bioprinting....

Polymers for 3D Printing and Customized Additive Manufacturing

A challenge for tissue engineering is producing three-dimensional (3D), vascularized cellular constructs of clinically relevant size, shape and structural integrity. We present an integrated tissue-organ printer (ITOP) that can fabricate stable, human-scale tissue constructs of any shape. Mechanical stability is achieved by printing cell-laden hydrogels together with biodegradable polymers in integrated patterns and anchored on sacrificial hydrogels. The correct shape of the tissue construct is achieved by representing clinical imaging data as a computer model of the anatomical defect and translating the model into a program that controls the motions of the printer nozzles, which dispense cells to discrete locations. The incorporation of microchannels into the tissue constructs facilitates diffusion of nutrients to printed cells, thereby overcoming the diffusion limit of 100-200 μm for cell survival in engineered tissues. We demonstrate capabilities of the ITOP by fabricating mandible and calvarial bone, cartilage and skeletal muscle. Future development of the ITOP is being directed to the production of tissues for human applications and to the building of more complex tissues and solid organs.

A 3D bioprinting system to produce human-scale tissue constructs with structural integrity

http://www.tissueeng.net/lab/papers/1-s2.0-S014296121500719X-main.pdf

Synthesis, properties, and biomedical applications of gelatin methacryloyl (GelMA) hydrogels

We demonstrate the additive manufacturing of complex three-dimensional (3D) biological structures using soft protein and polysaccharide hydrogels that are challenging or impossible to create using traditional fabrication approaches. These structures are built by embedding the printed hydrogel within a secondary hydrogel that serves as a temporary, thermoreversible, and biocompatible support. This process, termed freeform reversible embedding of suspended hydrogels, enables 3D printing of hydrated materials with an elastic modulus <500 kPa including alginate, collagen, and fibrin. Computer-aided design models of 3D optical, computed tomography, and magnetic resonance imaging data were 3D printed at a resolution of ~200 μm and at low cost by leveraging open-source hardware and software tools. Proof-of-concept structures based on femurs, branched coronary arteries, trabeculated embryonic hearts, and human brains were mechanically robust and recreated complex 3D internal and external anatomical architectures.

Three-dimensional printing of complex biological structures by freeform reversible embedding of suspended hydrogels.

High-throughput, cost-effective, and portable devices can enhance the performance of point-of-care tests. Such devices are able to acquire images from samples at a high rate in combination with microfluidic chips in point-of-care applications. However, interpreting and analyzing the large amount of acquired data is not only a labor-intensive and time-consuming process, but also prone to the bias of the user and low accuracy. Integrating machine learning (ML) with the image acquisition capability of smartphones as well as increasing computing power could address the need for high-throughput, accurate, and automatized detection, data processing, and quantification of results. Here, ML-supported diagnostic technologies are presented. These technologies include quantification of colorimetric tests, classification of biological samples (cells and sperms), soft sensors, assay type detection, and recognition of the fluid properties. Challenges regarding the implementation of ML methods, including the required number of data points, image acquisition prerequisites, and execution of data-limited experiments are also discussed.

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Machine learning-enabled multiplexed microfluidic sensors.

Here we show that a mathematical model of the human sleep cycle can be used to obtain a detailed description of electroencephalogram (EEG) sleep stages, and we discuss how this analysis may aid in the prediction and prevention of seizures during sleep. The association between EEG data and the cortical model is found via locally linear embedding (LLE), a method of dimensionality reduction. We first show that LLE can distinguish between traditional sleep stages when applied to EEG data. It reliably separates REM and non-REM sleep and maps the EEG data to a low-dimensional output space where the sleep state changes smoothly over time. We also incorporate the concept of strongly connected components and use this as a method of automatic outlier rejection for EEG data. Then, by using LLE on a hybrid data set containing both sleep EEG and signals generated from the mesoscale cortical model, we quantify the relationship between the data and the mathematical model. This enables us to take any sample of sleep EEG data and associate it with a position among the continuous range of sleep states provided by the model; we can thus infer a trajectory of states as the subject sleeps. Lastly, we show that this method gives consistent results for various subjects over a full night of sleep and can be done in real time.

/pdf/a-continuous-mapping-of-sleep-states-through-association-of-2ryk9248pa.pdf

A continuous mapping of sleep states through association of EEG with a mesoscale cortical model

For decades, diabetes mellitus has been of wide concern with its high global prevalence, resulting in increasing social and financial burdens for individuals, clinical systems and governments. Continuous glucose monitoring (CGM) has become a popular alternative to the portable finger-prick glucometers available in the market for the convenience of diabetic patients. Hence, it has attracted much interest in various glucose sensing technologies to develop novel glucose sensors with better performance and longer lifetime, especially non-invasive or minimally invasive glucose sensing. Effort has also been put into finding biocompatible materials for implantable applications to achieve effective in vivo CGM. Here, we review the state-of-the-art researches in the field of CGM. The currently commercially available CGM technologies have been analyzed and a summary is provided of the potential types of recently researched non-invasive glucose monitors. Furthermore, the challenges and advances towards implantable applications have also been introduced and discussed, especially the novel biocompatible hydrogel aimed at minimizing the adverse impact from foreign-body response. In addition, a large variety of promising glucose-sensing technologies under research have been reviewed, from traditional electrochemical-based glucose sensors to novel optical and other electrical glucose sensors. The recent development and achievement of the reviewed glucose sensing technologies are discussed, together with the market analysis in terms of the statistical data for the newly published patents in the related field. Thus, the promising direction for future work in this field could be concluded.

https://iopscience.iop.org/article/10.1088/2516-1091/abe6f8/pdf

Optical sensors for continuous glucose monitoring

A wide range of platforms has been developed for 3D culture of cells in vitro to aggregate and align cells to resemble in vivo conditions in order to enhance communication between cells and promote differentiation. The cellulose skeleton of plant tissue can serve as an attainable scaffold for mammalian cells after decellularization, which is advantageous when compared to synthetic polymers or animal-derived scaffolds. Adjustable variables to modify the physical and biochemical properties of the resulting scaffolds include the protocol for the sodium dodecyl sulfate (SDS)-based decellularization procedure, surface coatings for cell attachment, plant type for decellularization, differentiation media, and integrity and shape of the substrate. These tunable cellulose platforms can host a wide range of mammalian cell types from muscle to bone cells, as well as malignancies. Here, fundamentals and applications of decellularized plant-based scaffolds are discussed. These biocompatible, naturally perfused, tunable, and easily prepared decellularized scaffolds may allow eco-friendly manufacturing frameworks for application in tissue engineering and organs-on-a-chip.

Plant-Based Scaffolds in Tissue Engineering.

Abstract Microrobots have attracted the attention of scientists owing to their unique features to accomplish tasks in hard-to-reach sites in the human body. Microrobots can be precisely actuated and maneuvered individually or in a swarm for cargo delivery, sampling, surgery, and imaging applications. In addition, microrobots have found applications in the environmental sector (e.g., water treatment). Besides, recent advancements of three-dimensional (3D) printers have enabled the high-resolution fabrication of microrobots with a faster design-production turnaround time for users with limited micromanufacturing skills. Here, the latest end applications of 3D printed microrobots are reviewed (ranging from environmental to biomedical applications) along with a brief discussion over the feasible actuation methods (e.g., on- and off-board), and practical 3D printing technologies for microrobot fabrication. In addition, as a future perspective, we discussed the potential advantages of integration of microrobots with smart materials, and conceivable benefits of implementation of artificial intelligence (AI), as well as physical intelligence (PI). Moreover, in order to facilitate bench-to-bedside translation of microrobots, current challenges impeding clinical translation of microrobots are elaborated, including entry obstacles (e.g., immune system attacks) and cumbersome standard test procedures to ensure biocompatibility. 

/pdf/3d-printed-microrobots-from-design-to-translation-2k8vh23z.pdf

Savas Tasoglu

Papers

Machine learning-enabled multiplexed microfluidic sensors.

A continuous mapping of sleep states through association of EEG with a mesoscale cortical model

Optical sensors for continuous glucose monitoring

Plant-Based Scaffolds in Tissue Engineering.

3D-printed microrobots from design to translation