Robust Hydrogel Adhesion by Harnessing Bioinspired Interfacial Mineralization.

Hydrogels have gained intensive interest in biomedical and flexible electronics, and adhesion of hydrogels to substrates or devices is indispensable in these application scenarios. Although numerous hydrogel adhesion strategies have been developed, it is still challenging to achieve a hydrogel with robust adhesion interface through a universal yet simple method. Here, a strategy for establishing strong interfacial adhesion between various hydrogels and a wide variety of substrates (i.e., soft hydrogels and rigid solids, including glass, aluminum, PET, nylon and PDMS) even under wet conditions, is reported. This strong interfacial adhesion is realized by constructing a bioinspired mineralized transition layer through ion diffusion and subsequent mineral deposition. This strategy is not only generally applicable to a broad range of substrates and ionic pairs, but also compatible with various fabrication approaches without compromising their interfacial robustnesses. This strategy is further demonstrated in the application of single-electrode triboelectric nanogenerators (TENG), where a robust interface between the hydrogel and elastomer layers is enabled to ensure a reliable signal generation and output.

Advances in Piezoelectret Materials-Based Bidirectional Haptic Communication Devices.

Bidirectional haptic communication devices accelerate the revolution of virtual/augmented reality and flexible/wearable electronics. As an emerging kind of flexible piezoelectric materials, piezoelectret materials can effortlessly convert mechanical force into electrical signals and respond to electrical fields in a deformation manner, exhibiting enormous potential in the construction of bidirectional haptic communication devices. Existing reviews on piezoelectret materials primarily focus on flexible energy harvesters and sensors, and the recent development of piezoelectret-based bidirectional haptic communication devices has not been comprehensively reviewed. Herein, a comprehensive overview of the materials construction, along with the recent advances in bidirectional haptic communication devices, is provided. First, the development timeline, key characteristics, and various fabrication methods of piezoelectret materials are introduced. Subsequently, following the underlying mechanisms of bidirectional electromechanical signal conversion of piezoelectret, strategies to improve the d33 coefficients of materials are proposed. The principles of haptic perception and feedback are also highlighted, and representative works and progress in this area are summarized. Finally, the challenges and opportunities associated with improving the overall practicability of piezoelectret materials-based bidirectional haptic communication devices are discussed.

Modeling Structural Elements and Functional Responses to Lymphatic-Delivered Cues in a Murine Lymph Node on a Chip.

Lymph nodes (LNs) are organs of the immune system, critical for maintenance of homeostasis and initiation of immune responses, yet there are few models that accurately recapitulate LN functions in vitro. To tackle this issue, an engineered murine LN (eLN) has been developed, replicating key cellular components of the mouse LN; incorporating primary murine lymphocytes, fibroblastic reticular cells, and lymphatic endothelial cells. T and B cell compartments are incorporated within the eLN that mimic LN cortex and paracortex architectures. When challenged, the eLN elicits both robust inflammatory responses and antigen-specific immune activation, showing that the system can differentiate between non specific and antigen-specific stimulation and can be monitored in real time. Beyond immune responses, this model also enables interrogation of changes in stromal cells, thus permitting investigations of all LN cellular components in homeostasis and different disease settings, such as cancer. Here, how LN behavior can be influenced by murine melanoma-derived factors is presented. In conclusion, the eLN model presents a promising platform for in vitro study of LN biology that will enhance understanding of stromal and immune responses in the murine LN, and in doing so will enable development of novel therapeutic strategies to improve LN responses in disease.

Microcapillary cell extrusion deposition with picolitre dispensing resolution.

Extrusion-based cell deposition has become a prominent technique for expanding bioprinting applications. However, the associated print resolution in the order of nanolitre or above has been a limiting factor. The demand for improving print resolution towards the scale of a single cell has driven the development of precision nozzle extrusion, although the benefits gained remain ambiguous. Here, aided by in situ imaging, we investigated the dynamics of cell organisation through an extrusion-based microcapillary tip with picolitre precision through in-air or immersion deposition. The microcapillary extrusion setup, termed 'Picodis', was demonstrated by generating droplets of colouring inks immersed in an immiscible medium. Next, using 3T3 fibroblast cells as an experimental model, we demonstrated the deposition of cell suspension, and pre-aggregated cell pellets. Then, the dynamic organisation of cells within the microcapillary tip was described, along with cell ejection and deposition upon exiting the tip opening. The vision-assisted approach revealed that when dispersed in a culture medium, the movements of cells were distinctive based on the flow profiles and were purely driven by laminar fluid flow within a narrow tip. The primary process limitations were cell sedimentation, aggregation and compaction, along with trapped air bubbles. The use of picolitre-level resolution microcapillary extrusion, although it provides some level of control for a small number of cells, does not necessarily offer a reliable method when a specified number of cells are required. Our study provides insights into the process limitations of high-resolution cell ink extrusion, which may be useful for optimising biofabrication processes of cell-laden constructs for biomedical research. Supplementary information: The online version contains supplementary material available at 10.1007/s42242-022-00205-3.

Deployable extrusion bioprinting of compartmental tumoroids with cancer associated fibroblasts for immune cell interactions.

Realizing the translational impacts of three-dimensional (3D) bioprinting for cancer research necessitates innovation in bioprinting workflows which integrate affordability, user-friendliness, and biological relevance. Herein, we demonstrate 'BioArm', a simple, yet highly effective extrusion bioprinting platform, which can be folded into a carry-on pack, and rapidly deployed between bio-facilities. BioArm enabled the reconstruction of compartmental tumoroids with cancer-associated fibroblasts (CAFs), forming the shell of each tumoroid. The 3D printed core-shell tumoroids showedde novosynthesized extracellular matrices, and enhanced cellular proliferation compared to the tumour alone 3D printed spheroid culture. Further, thein vivophenotypes of CAFs normally lost after conventional 2D co-culture re-emerged in the bioprinted model. Embedding the 3D printed tumoroids in an immune cell-laden collagen matrix permitted tracking of the interaction between immune cells and tumoroids, and subsequent simulated immunotherapy treatments. Our deployable extrusion bioprinting workflow could significantly widen the accessibility of 3D bioprinting for replicating multi-compartmental architectures of tumour microenvironment, and for developing strategies in cancer drug testing in the future.

Engineering Electrodes with Robust Conducting Hydrogel Coating for Neural Recording and Modulation.

Coating conventional metallic electrodes with conducting polymers has enabled the essential characteristics required for bioelectronics, such as biocompatibility, electrical conductivity, mechanical compliance, and the capacity for structural and chemical functionalization of the bioelectrodes. However, the fragile interface between the conducting polymer and the electrode in wet physiological environment greatly limits their utility and reliability. Here, a general yet reliable strategy to seamlessly interface conventional electrodes with conducting hydrogel coatings is established, featuring tissue-like modulus, highly-desirable electrochemical properties, robust interface, and long-term reliability. Numerical modeling reveals the role of toughening mechanism, synergy of covalent anchorage of long-chain polymers, and chemical cross-linking, in improving the long-term robustness of the interface. Through in vivo implantation in freely-moving mouse models, it is shown that stable electrophysiological recording can be achieved, while the conducting hydrogel-electrode interface remains robust during the long-term low-voltage electrical stimulation. This simple yet versatile design strategy addresses the long-standing technical challenges in functional bioelectrode engineering, and opens up new avenues for the next-generation diagnostic brain-machine interfaces.

A Flexible Self-Powered Noncontact Sensor with an Ultrawide Sensing Range for Human-Machine Interactions in Harsh Environments.

Noncontact human-machine interactions (HMIs) provide a hygienic and intelligent approach to communicate between humans and machines. However, current noncontact HMIs are generally hampered by the interaction distance, and they lack the adaptability to environmental interference such as high humidity conditions. Here, we explore a self-powered electret-based noncontact sensor (ENS) with moisture-resisting ability and ultrawide sensing range exceeding 2.5 m. A megascopic air-bubble structure is designed to enhance charge-storage stability and charge-recovery ability of the ENS based on the heterocharge-synergy effect in electrets. Besides, multilayer electret films are introduced to strengthen the electric field by utilizing the electrostatic field superposition effect. Thanks to the above improved performances of the ENS, we demonstrate various noncontact HMI applications in harsh environments, including noncontact appliances, a moving trajectory and accidental fall tracking system, and a real-time machine learning-assisted gesture recognition system with accuracy as high as 99.21%. This research expands the way for noncontact sensor design and may further broaden applications in noncontact HMIs.

Impact-Resistant Hydrogels by Harnessing 2D Hierarchical Structures.

With the strengthening capacity through harnessing multi-length-scale structural hierarchy, synthetic hydrogels hold tremendous promise as a low-cost and abundant material for applications demanding unprecedented mechanical robustness. However, integrating high impact resistance and high water content, yet superior softness, in a single hydrogel material still remains a grand challenge. Here, a simple, yet effective, strategy involving bidirectional freeze-casting and compression-annealing is reported, leading to a hierarchically structured hydrogel material. Rational engineering of the distinct 2D lamellar structures, well-defined nanocrystalline domains and robust interfacial interaction among the lamellae, synergistically contributes to a record-high ballistic energy absorption capability (i.e., 2.1 kJ m-1 ), without sacrificing their high water content (i.e., 85 wt%) and superior softness. Together with its low-cost and extraordinary energy dissipation capacity, the hydrogel materials present a durable alternative to conventional hydrogel materials for armor-like protection circumstances.

A hackable, multi-functional, and modular extrusion 3D printer for soft materials.

Three-dimensional (3D) printing has emerged as a powerful tool for material, food, and life science research and development, where the technology's democratization necessitates the advancement of open-source platforms. Herein, we developed a hackable, multi-functional, and modular extrusion 3D printer for soft materials, nicknamed Printer.HM. Multi-printhead modules are established based on a robotic arm for heterogeneous construct creation, where ink printability can be tuned by accessories such as heating and UV modules. Software associated with Printer.HM were designed to accept geometry inputs including computer-aided design models, coordinates, equations, and pictures, to create prints of distinct characteristics. Printer.HM could further perform versatile operations, such as liquid dispensing, non-planar printing, and pick-and-place of meso-objects. By 'mix-and-match' software and hardware settings, Printer.HM demonstrated printing of pH-responsive soft actuators, plant-based functional hydrogels, and organ macro-anatomical models. Integrating affordability and open design, Printer.HM is envisaged to democratize 3D printing for soft, biological, and sustainable material architectures.

Integrated 3D printing of flexible electroluminescent devices and soft robots.

Flexible and stretchable light emitting devices are driving innovation in myriad applications, such as wearable and functional electronics, displays and soft robotics. However, the development of flexible electroluminescent devices via conventional techniques remains laborious and cost-prohibitive. Here, we report a facile and easily-accessible route for fabricating a class of flexible electroluminescent devices and soft robotics via direct ink writing-based 3D printing. 3D printable ion conducting, electroluminescent and insulating dielectric inks were developed, enabling facile and on-demand creation of flexible and stretchable electroluminescent devices with good fidelity. Robust interfacial adhesion with the multilayer electroluminescent devices endowed the 3D printed devices with attractive electroluminescent performance. Integrated our 3D printed electroluminescent devices with a soft quadrupedal robot and sensing units, an artificial camouflage that can instantly self-adapt to the environment by displaying matching color was fabricated, laying an efficient framework for the next generation soft camouflages.

Cancer cell migration on straight, wavy, loop and grid microfibre patterns.

Cell migration plays an important role in physiological and pathological processes where the fibrillar morphology of extracellular matrices (ECM) could regulate the migration dynamics. To mimic the morphological characteristics of fibrillar matrix structures, low-voltage continuous electrospinning was adapted to construct straight, wavy, looped and gridded fibre patterns made of polystyrene (of fibre diameter ca. 3µm). Cells were free to explore their different shapes in response to the directly-adhered fibre, as well as to the neighbouring patterns. For all the patterns studied, analysing cellular migration dynamics of MDA-MB-231 (a highly migratory breast cancer cell line) demonstrated two interesting findings: first, although cells dynamically adjust their shapes and migration trajectories in response to different fibrillar environments, their average step speed is minimally affected by the fibre global pattern; secondly, a switch in behaviour was observed when the pattern features approach the upper limit of the cell body's minor axis, reflecting that cells' ability to divert from an existing fibre track is limited by the size along the cell body's minor axis. It is therefore concluded that the upper limit of cell body's minor axis might act as a guide for the design of microfibre patterns for different purposes of cell migration.

Biodegradable Smart Face Masks for Machine Learning-Assisted Chronic Respiratory Disease Diagnosis.

Utilizing smart face masks to monitor and analyze respiratory signals is a convenient and effective method to give an early warning for chronic respiratory diseases. In this work, a smart face mask is proposed with an air-permeable and biodegradable self-powered breath sensor as the key component. This smart face mask is easily fabricated, comfortable to use, eco-friendly, and has sensitive and stable output performances in real wearable conditions. To verify the practicability, we use smart face masks to record respiratory signals of patients with chronic respiratory diseases when the patients do not have obvious symptoms. With the assistance of the machine learning algorithm of the bagged decision tree, the accuracy for distinguishing the healthy group and three groups of chronic respiratory diseases (asthma, bronchitis, and chronic obstructive pulmonary disease) is up to 95.5%. These results indicate that the strategy of this work is feasible and may promote the development of wearable health monitoring systems.

3D printed biomimetic cochleae and machine learning co-modelling provides clinical informatics for cochlear implant patients.

Cochlear implants restore hearing in patients with severe to profound deafness by delivering electrical stimuli inside the cochlea. Understanding stimulus current spread, and how it correlates to patient-dependent factors, is hampered by the poor accessibility of the inner ear and by the lack of clinically-relevant in vitro, in vivo or in silico models. Here, we present 3D printing-neural network co-modelling for interpreting electric field imaging profiles of cochlear implant patients. With tuneable electro-anatomy, the 3D printed cochleae can replicate clinical scenarios of electric field imaging profiles at the off-stimuli positions. The co-modelling framework demonstrated autonomous and robust predictions of patient profiles or cochlear geometry, unfolded the electro-anatomical factors causing current spread, assisted on-demand printing for implant testing, and inferred patients' in vivo cochlear tissue resistivity (estimated mean = 6.6 kΩcm). We anticipate our framework will facilitate physical modelling and digital twin innovations for neuromodulation implants.