Nanocarrier design for pathogen-inspired innate immune agonist delivery.

In complex diseases such as cancer, modulating cytokine signatures of disease using innate immune agonists holds therapeutic promise. Novel multi-agonist treatments offer tunable control of the immune system because they are uniquely pathogen inspired, eliciting robust antitumor responses by promoting synergistic cytokine responses. However, the chief strategic hurdle is ensuring multi-agonist delivery to the same target cells, highlighting the importance of using nanomaterial-based carriers. Here, we place nanocarriers in center stage and review the delivery hurdles related to the varying extra- and intracellular localizations of innate immune receptors. We discuss a range of nanomaterials used for multi-agonist delivery, highlighting their respective benefits and drawbacks. Our overarching stance is that rational nanocarrier design is crucial for developing pathogen-inspired multi-agonist immunotherapies.

A neural algorithm for computing bipartite matchings.

Finding optimal bipartite matchings-e.g., matching medical students to hospitals for residency, items to buyers in an auction, or papers to reviewers for peer review-is a fundamental combinatorial optimization problem. We found a distributed algorithm for computing matchings by studying the development of the neuromuscular circuit. The neuromuscular circuit can be viewed as a bipartite graph formed between motor neurons and muscle fibers. In newborn animals, neurons and fibers are densely connected, but after development, each fiber is typically matched (i.e., connected) to exactly one neuron. We cast this synaptic pruning process as a distributed matching (or assignment) algorithm, where motor neurons "compete" with each other to "win" muscle fibers. We show that this algorithm is simple to implement, theoretically sound, and effective in practice when evaluated on real-world bipartite matching problems. Thus, insights from the development of neural circuits can inform the design of algorithms for fundamental computational problems.

Self-locking and stiffening deployable tubular structures.

Deployable tubular structures, designed for functional expansion, serve a wide range of applications, from flexible pipes to stiff structural elements. These structures, which transform from compact states, are crucial for creating adaptive solutions across engineering and scientific fields. A significant barrier to advancing their performance is balancing expandability with stiffness. Using compliant materials, these structures achieve more flexible transformations than those possible with rigid mechanisms. However, they typically exhibit reduced stiffness when subjected to external pressures (e.g., tube wall loading). Here, we utilize origami-inspired techniques and internal stiffeners to meet conflicting performance requirements. A self-locking mechanism is proposed, which combines the folding behavior observed in curved-crease origami and elastic shell buckling. This mechanism employs simple shell components, including internal diaphragms that undergo pseudofolding in a confined boundary condition to enable a snap-through transition. We reveal that the deployed tube is self-locked through geometrical interference, creating a braced tubular arrangement. This arrangement gives a direction-dependent structural performance, ranging from elastic response to crushing, thereby offering the potential for programmable structures. We demonstrate that our approach can advance existing deployment mechanisms (e.g., coiled and inflatable systems) and create diverse structural designs (e.g., metamaterials, adaptive structures, cantilevers, and lightweight panels).Weanticipate our design to be a starting point to drive technological advancement in real-world deployable tubular structures.

Multiple forces facilitate the aquatic acrobatics of grasshopper and bioinspired robot.

Aquatic locomotion is challenging for land-dwelling creatures because of the high degree of fluidity with which the water yields to loads. We surprisingly found that the Chinese rice grasshopper Oxya chinensis, known for its terrestrial acrobatics, could swiftly launch itself off the water's surface in around 25 ms and seamlessly transition into flight. Biological observations showed that jumping grasshoppers use their front and middle legs to tilt up bodies first and then lift off by propelling the water toward the lower back with hind legs at angular speeds of up to 18°/ms, whereas the swimming grasshoppers swing their front and middle legs in nearly horizontal planes and move hind legs less violently (~8°/ms). Force measurement and model analysis indicated that the weight support could be achieved by hydrostatics which are proportionate to the mass of the grasshoppers, while the propulsions for motion are derived from the controlled limb-water interactions (i.e., the hydrodynamics). After learning the structural and behavioral strategies of the grasshoppers, a robot was created and was capable of swimming and jumping on the water surface like the insects, further demonstrating the effectiveness of decoupling the challenges of aquatic locomotion by the combined use of the static and dynamic hydro forces. This work not only uncovered the combined mechanisms responsible for facilitating aquatic acrobatics in this species but also laid a foundation for developing bioinspired robots that can locomote across multiple media.

A kinetic model for solving a combination optimization problem in ab-initio Cryo-EM 3D reconstruction.

Cryo-Electron Microscopy (cryo-EM) is a widely used and effective method for determining the three-dimensional (3D) structure of biological molecules. For ab-initio Cryo-EM 3D reconstruction using single particle analysis (SPA), estimating the projection direction of the projection image is a crucial step. However, the existing SPA methods based on common lines are sensitive to noise. The error in common line detection will lead to a poor estimation of the projection directions and thus may greatly affect the final reconstruction results. To improve the reconstruction results, multiple candidate common lines are estimated for each pair of projection images. The key problem then becomes a combination optimization problem of selecting consistent common lines from multiple candidates. To solve the problem efficiently, a physics-inspired method based on a kinetic model is proposed in this work. More specifically, hypothetical attractive forces between each pair of candidate common lines are used to calculate a hypothetical torque exerted on each projection image in the 3D reconstruction space, and the rotation under the hypothetical torque is used to optimize the projection direction estimation of the projection image. This way, the consistent common lines along with the projection directions can be found directly without enumeration of all the combinations of the multiple candidate common lines. Compared with the traditional methods, the proposed method is shown to be able to produce more accurate 3D reconstruction results from high noise projection images. Besides the practical value, the proposed method also serves as a good reference for solving similar combinatorial optimization problems.

Brain-inspired neural circuit evolution for spiking neural networks.

In biological neural systems, different neurons are capable of self-organizing to form different neural circuits for achieving a variety of cognitive functions. However, the current design paradigm of spiking neural networks is based on structures derived from deep learning. Such structures are dominated by feedforward connections without taking into account different types of neurons, which significantly prevent spiking neural networks from realizing their potential on complex tasks. It remains an open challenge to apply the rich dynamical properties of biological neural circuits to model the structure of current spiking neural networks. This paper provides a more biologically plausible evolutionary space by combining feedforward and feedback connections with excitatory and inhibitory neurons. We exploit the local spiking behavior of neurons to adaptively evolve neural circuits such as forward excitation, forward inhibition, feedback inhibition, and lateral inhibition by the local law of spike-timing-dependent plasticity and update the synaptic weights in combination with the global error signals. By using the evolved neural circuits, we construct spiking neural networks for image classification and reinforcement learning tasks. Using the brain-inspired Neural circuit Evolution strategy (NeuEvo) with rich neural circuit types, the evolved spiking neural network greatly enhances capability on perception and reinforcement learning tasks. NeuEvo achieves state-of-the-art performance on CIFAR10, DVS-CIFAR10, DVS-Gesture, and N-Caltech101 datasets and achieves advanced performance on ImageNet. Combined with on-policy and off-policy deep reinforcement learning algorithms, it achieves comparable performance with artificial neural networks. The evolved spiking neural circuits lay the foundation for the evolution of complex networks with functions.

Single-shot time-folded fluorescence lifetime imaging.

Fluorescence lifetime imaging is an important tool in bioimaging that allows one to detect subtle changes in cell dynamics and their environment. Most time-domain approaches currently involve scanning a single illumination point across the sample, which can make imaging dynamic scenes challenging, while single-shot "rapid lifetime determination" can suffer from large uncertainties when the lifetime is not appropriately sampled. Here, we propose a time-folded fluorescence lifetime imaging microscopy (TFFLIM) approach, whereby a time-folding cavity provides multiple spatially sheared replicas of the lifetime, each shifted temporally with respect to a fixed time gate. This provides a robust, single-shot FLIM approach that we experimentally validate across a broad lifetime range on fluorescent beads and Convallaria samples.

Platelet-Mimicking Nanosponges for Functional Reversal of Antiplatelet Agents.

BACKGROUND: During long-term antiplatelet agents (APAs) administration, patients with thrombotic diseases take a fairly high risk of life-threatening bleeding, especially when in need of urgent surgery. Rapid functional reversal of APAs remains an issue yet to be efficiently resolved by far due to the lack of any specific reversal agent in the clinic, which greatly restricts the use of APAs. METHODS: Flow cytometry analysis was first applied to assess the dose-dependent reversal activity of platelet-mimicking perfluorocarbon-based nanosponges (PLT-PFCs) toward ticagrelor. The tail bleeding time of mice treated with APAs followed by PLT-PFCs was recorded at different time points, along with corresponding pharmacokinetic analysis of ticagrelor and tirofiban. A hemorrhagic transformation model was established in experimental stroke mice with thrombolytic/antiplatelet therapy. Magnetic resonance imaging was subsequently applied to observe hemorrhage and thrombosis in vivo. Further evaluation of the spontaneous clot formation activity of PLT-PFCs was achieved by clot retraction assay in vitro. RESULTS: PLT-PFCs potently reversed the antiplatelet effect of APAs by competitively binding with APAs. PLT-PFCs showed high binding affinity comparable to fresh platelets in vitro with first-line APAs, ticagrelor and tirofiban, and efficiently reversed their function in both tail bleeding and postischemic-reperfusion models. Moreover, the deficiency of platelet intrinsic thrombotic activity diminished the risk of thrombogenesis. CONCLUSIONS: This study demonstrated the safety and effectiveness of platelet-mimicking nanosponges in ameliorating the bleeding risk of different APAs, which offers a promising strategy for the management of bleeding complications induced by antiplatelet therapy.

Nacre-like composites with superior specific damping performance.

Biological materials such as nacre have evolved microstructural design principles that result in outstanding mechanical properties. While nacre's design concepts have led to bio-inspired materials with enhanced fracture toughness, the microstructural features underlying the remarkable damping properties of this biological material have not yet been fully explored in synthetic composites. Here, we study the damping behavior of nacre-like composites containing mineral bridges and platelet asperities as nanoscale structural features within its brick-and-mortar architecture. Dynamic mechanical analysis was performed to experimentally elucidate the role of these features on the damping response of the nacre-like composites. By enhancing stress transfer between platelets and at the brick/mortar interface, mineral bridges and nano-asperities were found to improve the damping performance of the composite to levels that surpass many biological and man-made materials. Surprisingly, the improved properties are achieved without reaching the perfect organization of the biological counterparts. Our nacre-like composites display a loss modulus 2.4-fold higher than natural nacre and 1.4-fold more than highly dissipative natural fiber composites. These findings shed light on the role of nanoscale structural features on the dynamic mechanical properties of nacre and offer design concepts for the manufacturing of bio-inspired composites for high-performance damping applications.

Symbiosis-inspired de novo synthesis of ultrahigh MOF growth mixed matrix membranes for sustainable carbon capture.

Mixed matrix membranes (MMMs) are one of the most promising solutions for energy-efficient gas separation. However, conventional MMM synthesis methods inevitably lead to poor filler-polymer interfacial compatibility, filler agglomeration, and limited loading. Herein, inspired by symbiotic relationships in nature, we designed a universal bottom-up method for in situ nanosized metal organic framework (MOF) assembly within polymer matrices. Consequently, our method eliminating the traditional postsynthetic step significantly enhanced MOF dispersion, interfacial compatibility, and loading to an unprecedented 67.2 wt % in synthesized MMMs. Utilizing experimental techniques and complementary density functional theory (DFT) simulation, we validated that these enhancements synergistically ameliorated CO2 solubility, which was significantly different from other works where MOF typically promoted gas diffusion. Our approach simultaneously improves CO2 permeability and selectivity, and superior carbon capture performance is maintained even during long-term tests; the mechanical strength is retained even with ultrahigh MOF loadings. This symbiosis-inspired de novo strategy can potentially pave the way for next-generation MMMs that can fully exploit the unique characteristics of both MOFs and matrices.

Biomimetic Electronic Skin for Robots Aiming at Superior Dynamic-Static Perception and Material Cognition Based on Triboelectric-Piezoresistive Effects.

Empowering robots with tactile perception and even thinking as well as judgment capabilities similar to those of humans is an inevitable path for the development of future robots. Here, we propose a biomimetic electronic skin (BES) that truly serves and applies to robots to achieve superior dynamic-static perception and material cognition functionalities. First, the microstructured triboelectric and piezoresistive layers are fabricated by a facile template method followed by selected self-polymerization treatment, enabling BES with high sensitivity and a wide detection range. Further, through laminated-independent triboelectric and piezoresistive parts for perceiving dynamic and static pressures simultaneously, the BES is capable of supporting the robot hand to monitor the entire process during object grasping. Most importantly, by further combining a neural network model, an intelligent cognition system is constructed for real-time cognition of the object material species via one touch of the robot hand under arbitrary pressures, which goes beyond the human cognition ability.

A Crayfish-Inspired Sensor Fusion Platform for Super Additive Integration of Visual, Chemical, and Tactile Information.

The concept of cross-sensor modulation, wherein one sensor modality can influence another's response, is often overlooked in traditional sensor fusion architectures, leading to missed opportunities for enhancing data accuracy and robustness. In contrast, biological systems, such as aquatic animals like crayfish, demonstrate superior sensor fusion through multisensory integration. These organisms adeptly integrate visual, tactile, and chemical cues to perform tasks such as evading predators and locating prey. Drawing inspiration from this, we propose a neuromorphic platform that integrates graphene-based chemitransistors, monolayer molybdenum disulfide (MoS2) based photosensitive memtransistors, and triboelectric tactile sensors to achieve "Super-Additive" responses to weak chemical, visual, and tactile cues and demonstrate contextual response modulation, also referred to as the "Inverse Effectiveness Effect." We hold the view that integrating bio-inspired sensor fusion principles across various modalities holds promise for a wide range of applications.

PASS-ALL study of paediatric-inspired versus adult chemotherapy regimens on survival of high-risk Philadelphia-negative B-cell acute lymphoblastic leukaemia with allogeneic haematopoietic stem cell transplantation.

This PASS-ALL study was designed to explore the effect of paediatric-inspired versus adult chemotherapy regimens on survival of adolescents and young adults (AYA) with high-risk Philadelphia chromosome-negative B-cell acute lymphoblastic leukaemia (HR PH-ve B-cell ALL) eligible for allogeneic haematopoietic stem cell transplantation (allo-HSCT). The PASS-ALL study is a multicentre, observational cohort study, and 143 patients with HR B-cell PH-ve ALL were enrolled from five centres-77 patients allocated in the paediatric-inspired cohort and 66 in the adult cohort with comparable baseline characteristics. Of the 143 patients, 128 cases underwent allo-HSCT. Three-year leukaemia-free survival (LFS) in the paediatric-inspired cohort was 72.2% (95% CI 60.8%-83.6%) compared with 44.6% (95% CI 31.9%-57.3%; p = 0.001). Furthermore, time-to-positive minimal residual disease (TTP-MRD) post-HSCT was marked different, 3-year cumulative incidence of relapse was 25.9% (95% CI 15.8%-37.2%) in paediatric cohort and 45.4% (95% CI 40.0%-57.9%) in adult cohort (p = 0.026). Finally, the 3-year OS rate was 75.3% (95% CI 64.9%-85.7%) for the paediatric-inspired cohort and 64.1% (95% CI 51.8%-76.4%) for the adult cohort (p = 0.074). On a multivariate analysis, paediatric-inspired regimen is a predictive factor for LFS (HR = 2.540, 95% CI 1.327-4.862, p = 0.005). Collectively, our data suggest that paediatric-inspired chemotherapy pre-HSCT results in deeper and durable MRD response reduces relapse post-HSCT and improves survival in HR B-cell PH-ve ALL patients with allo-HSCT.

Skin-Inspired Textile Electronics Enable Ultrasensitive Pressure Sensing.

Wearable pressure sensors have attracted great interest due to their potential applications in healthcare monitoring and human-machine interaction. However, it is still a critical challenge to simultaneously achieve high sensitivity, low detection limit, fast response, and outstanding breathability for wearable electronics due to the difficulty in constructing microstructure on a porous substrate. Inspired by the spinosum microstructure of human skin for highly-sensitive tactile perception, a biomimetic flexible pressure sensor is designed and fabricated by assembling MXene-based sensing electrode and MXene-based interdigitated electrode. The product biomimetic sensor exhibits good flexibility and suitable air permeability (165.6 mm s-1), comparable to the typical air permeable garments. Benefiting from the two-stage amplification effect of the bionic intermittent structure, the product bionic sensor exhibits an ultrahigh sensitivity (1368.9 kPa-1), ultrafast response (20 ms), low detection limit (1 Pa), and high-linearity response (R2 = 0.997) across the entire sensing range. Moreover, the pressure sensor can detect a wide range of human motion in real-time through intimate skin contact, providing essential data for biomedical monitoring and personal medical diagnosis. This principle lays a foundation for the development of human skin-like high-sensitivity, fast-response tactile sensors.

Bio-Inspired Interlocking Structures for Enhancing Flexible Coatings Adhesion.

The flexible protective coatings and substrates frequently exhibit unstable bonding in industrial applications. For strong interfacial adhesion of heterogeneous materials and long-lasting adhesion of flexible protective coatings even in harsh corrosive environments. Inspired by the interdigitated structures in Phloeodes diabolicus elytra, a straightforward magnetic molding technique is employed to create an interlocking microarray for reinforced heterogeneous assembly. Benefiting from this bio-inspired microarrays, the interlocking polydimethylsiloxane (PDMS) coating recorded a 270% improvement in tensile adhesion and a 520% increase in shear resistance, approaching the tensile limitation of PDMS. The elastic polyurethane-polyamide (PUPI) coating equipped with interlocking structures demonstrated a robust adhesion strength exceeding 10.8 MPa and is nearly unaffected by the corrosion immersion. In sharp contrast, its unmodified counterpart exhibited low initial adhesion and maintain ≈20% of its adhesion strength after 30 d of immersion. PUPI coating integrated with microarrays exhibits superior resistance to corrosion (30 d, |Z|0.01HZ ≈1010 Ω cm2, Rct≈108 Ω cm2), cavitation and long-term adhesion retention. These interlocking designs can also be adapted to curved surfaces by 3D printing and enhances heterogeneous assembly of non-bonded materials like polyvinylidene fluoride (PTFE) and PDMS. This bio-inspired interlocking structures offers a solution for durably bonding incompatible interfaces across varied engineering applications.

Efficient Solar-Driven Interfacial Water Evaporator using Hydrogel Modified Carbon-Based Biomass with Abundant Microchannels.

The conventional sea water desalination technologies are not yet adopted worldwide, especially in the third world countries due to their high capital cost as well as large energy requirement. To solve this issue in a sustainable way an interfacial solar water evaporation device is designed and proposed in this article using the branches of Prunus serrulata (PB). The PB has abundant microchannels and shows excellent photothermal conversion capability after carbonization. Moreover, the easy access to raw materials and the facile fabrication process makes the solar water evaporating device very cost effective for seawater desalination application. Experiments show that in the presence of the fabricated evaporator the evaporation rate of water can reach 3.5 kg m-2 h-1 under 1 sun, which is superior to many similar experimental devices. In addition, its advantages, such as effective sewage purification capability, low cost, and environmental friendliness, make this evaporator highly competitive in the extensive promotion of this technology and can be considered as a new sustainable solution for seawater desalination with great application potential and prospects.

Synergistic Modulation of Mass Transfer and Parasitic Reactions of Zn Metal Anode via Bioinspired Artificial Protection Layer.

Rechargeable aqueous zinc-ion batteries are regarded as promising energy storage devices due to their attractive economic benefits and extraordinary electrochemical performance. However, the sluggish Zn2+ mass transfer behavior and water-induced parasitic reactions that occurred on the anode-electrode interface inevitably restrain their applications. Herein, inspired by the selective permeability and superior stability of plasma membrane, a thin UiO-66 metal-organic framework layer with smart aperture size is ex-situ decorated onto the Zn anode. Experimental characterizations in conjunction with theoretical calculations demonstrate that this bio-inspired layer promotes the de-solvation process of hydrated Zn2+ and reduces the effective contact between the anode and H2 O molecules, thereby boosting Zn2+ deposition kinetics and restraining interfacial parasitic reactions. Hence, the Zn||Zn cells could sustain a long lifespan of 1680 h and the Zn||Cu cells yielded a stable coulombic efficiency of over 99.3% throughout 600 cycles under the assistance of the bio-inspired layer. Moreover, pairing with δ-MnO2 cathode, the full cells also demonstrate prominent cycling stability and rate performance. From the bio-inspired design philosophy, this work provides a novel insight into the development of aqueous batteries.

2D and 3D Micropatterning of Mussel-Inspired Functional Materials by Direct Laser Writing.

This work addresses the critical need for multifunctional materials and substrate-independent high-precision surface modification techniques that are essential for advancing microdevices and sensing elements. To overcome existing limitations, the versatility of mussel-inspired materials (MIMs) is combined with state-of-the-art multiphoton direct laser writing (DLW) microfabrication. In this way, 2D and 3D MIM microstructures of complex designs are demonstrated with sub-micron to micron resolution and extensive post-functionalization capabilities. This study includes polydopamine (PDA), mussel-inspired linear, and dendritic polyglycerols (MI-lPG and MI-dPG), allowing their direct microstructure on the substrate of choice with the option to tailor the patterned topography and morphology in a controllable manner. The functionality potential of MIMs is demonstrated by successfully immobilizing and detecting single-stranded DNA on MIM micropattern and nanoarray surfaces. In addition, easy modification of MIM microstructure with silver nanoparticles without the need of any reducing agent is shown. The methodology developed here enables the integration of MIMs in advanced applications where precise surface functionalization is essential.

Catheter-Assisted Bioinspired Adhesive Magnetic Soft Millirobot for Drug Delivery.

Soft millirobots have evolved into various therapeutic applications in the medical field, including for vascular dredging, cell transportation, and drug delivery, owing to adaptability to their surroundings. However, most soft millirobots cannot quickly enter, retrieve, and maintain operations in their original locations after removing the external actuation field. This study introduces a soft magnetic millirobot for targeted medicine delivery that can be transported into the body through a catheter and anchored to the tissues. The millirobot has a bilayer adhesive body with a mussel-inspired hydrogel layer and an octopus-inspired magnetic structural layer. It completes entry and retrieval with the assistance of a medical catheter based on the difference between the adhesion of the hydrogel layer in air and water. The millirobot can operate in multiple modes of motion under external magnetic fields and underwater tissue adhesion after self-unfolding with the structural layer. The adaptability and recyclability of the millirobots are demonstrated using a stomach model. Combined with ultrasound (US) imaging, operational feasibility within organisms is shown in isolated small intestines. In addition, a highly efficient targeted drug delivery is confirmed using a fluorescence imaging system. Therefore, the proposed soft magnetic millirobots have significant potential for medical applications.

Bio-Inspired Organic Synaptor with In Situ Ion-Doped Ultrathin Polyelectrolyte Containing Acetylcholine-Like Cation.

An ion-based synaptic transistor (synaptor) is designed to emulate a biological synapse using controlled ion movements. However, developing a solid-state electrolyte that can facilitate ion movement while achieving large-scale integration remains challenging. Here, a bio-inspired organic synaptor (BioSyn) with an in situ ion-doped polyelectrolyte (i-IDOPE) is demonstrated. At the molecular scale, a polyelectrolyte containing the tert-amine cation, inspired by the neurotransmitter acetylcholine is synthesized using initiated chemical vapor deposition (iCVD) with in situ doping, a one-step vapor-phase deposition used to fabricate solid-state electrolytes. This method results in an ultrathin, but highly uniform and conformal solid-state electrolyte layer compatible with large-scale integration, a form that is not previously attainable. At a synapse scale, synapse functionality is replicated, including short-term and long-term synaptic plasticity (STSP and LTSP), along with a transformation from STSP to LTSP regulated by pre-synaptic voltage spikes. On a system scale, a reflex in a peripheral nervous system is mimicked by mounting the BioSyns on various substrates such as rigid glass, flexible polyethylene naphthalate, and stretchable poly(styrene-ethylene-butylene-styrene) for a decentralized processing unit. Finally, a classification accuracy of 90.6% is achieved through semi-empirical simulations of MNIST pattern recognition, incorporating the measured LTSP characteristics from the BioSyns.