Photothermal materials with high conversion efficiency offer a promising approach for preventing ice accretion on infrastructures like wind turbines. However, the conflict between weak-light inefficiency in winter and overheating hazards in summer remains a challenge for composites. Herein, we develop a robust thermochromic photothermal icephobic coating with switchable solar-driven anti-/deicing and anti-overheating modes for all-season demands. During freezing winter, a 0.05 W/cm² weak solar irradiation can raise the black coating (solar absorbance >97%) temperature from −10 to 7.6 °C and facilitate rapid ice shedding from rotating rotor. During summer, the thermochromic coating turns white with strong reflection and limits coating temperature below 51 °C, inhibiting composites oxidation above 60 °C. Strikingly, the interpenetrating elasticity and ultraslippage endow the coating with exceptional ice detachment properties, exhibiting an ultralow ice adhesion strength (<31 kPa) and sliding angle (<8.3°), which are maintained even after 200 Taber abrasion cycles. This study successfully addresses the critical challenge of regulating the all-season temperature of photothermal coatings, pioneering a new pathway for designing intelligent anti-icing coatings for wind turbines and low-altitude rotorcraft.

Continuous-variable quantum secure communication encoded by Gaussian mapping offers high-capacity and high transmission rates. For the theoretically secure encryption scheme of a 1-time pad, a highly reliable coherent-state quantum secure communication system has been established, and its security has been quantitatively evaluated using Wyner’s wiretap channel theory. We also propose an information reconstruction scheme based on multidimensional rotation to extract secret messages at low-to-medium signal-to-noise ratios. Meanwhile, to address the unbalanced optical path, we design a self-balanced homodyne detector based on a programmable gain amplifier, achieving an electronic noise variance of 1.624\times {10}^{-7} {\mathrm{V}}^2 and a bandwidth of 715 MHz. In 10-km optical fiber transmission, the system successfully achieved secure transmission of the dichroic image, processed 1,536 information blocks, each containing 2^{10} continuous variables, with a block error rate of approximately 8.78\times {10}^{-5}, and ultimately achieved the secrecy capacity of 2.44\times {10}^5 bits per second.

Nanozymes overcome key limitations of natural enzymes, including poor environmental tolerance, high production costs, and batch-to-batch variability, with their enhanced physicochemical stability and controllable catalytic performance, thus enabling applications in biocatalysis and disease theranostics. However, their practical applications remain limited by insufficient catalytic efficiency, inadequate target specificity, and restricted programmable dynamic adaptability. DNA nanotechnology offers a versatile and biocompatible framework for the precise regulation of nanozymes due to its sequence-defined programmability and precise molecular recognition capability. This approach improves catalytic performance while maintaining excellent biocompatibility and low immunogenicity. This review systematically summarizes the latest advances in DNA nanotechnology-mediated precise regulation of nanozymes, with particular emphasis on the mechanistic basis of 6 regulatory modes. We further examine the representative applications of these DNA–nanozyme hybrid systems in disease therapy, biomedical sensing, and environmental monitoring, and outline the key challenges and future directions toward clinical and industrial translation.

Endogenous bioelectric signals serve as pivotal physiological cues that govern cellular behavior and tissue regeneration. Conductive hydrogels have become a disruptive platform in the field of tissue engineering because they can promote tissue repair by utilizing endogenous electrical signals. Conventional conductive hydrogels often suffer from weak tissue adhesion and high contact impedance, which sever the continuity of endogenous bioelectric signals essential for regeneration. To bridge this gap, polyphenol-based adhesive-electrocoupling hydrogels have garnered increasing attention. The conductive network within adhesive-electrocoupling hydrogels facilitates electron transfer-mediated polyphenol redox cycling, preserving catechols for robust adhesion. This strong tissue interface integration maintains electrical signal transduction, constructing a conductive-adhesive synergistic circuit. This review first elucidates the biological effects of bioelectricity, establishing a theoretical foundation for conductive hydrogels to promote tissue repair using endogenous electrical signals. Subsequently, this review systematically summarizes the design strategies for adhesive-electrocoupling hydrogels mediated by polyphenol redox interactions, grounded in electron transfer mechanisms. Crucially, this review introduces the distinct biological mechanisms driving regeneration, highlighting the synergistic interplay among the intrinsic bioactivity of polyphenols, the modulation of cell behavior through endogenous electric field coupling, and cell adhesion. Furthermore, the versatile applications of adhesive-electrocoupling hydrogels in repairing electro-sensitive tissues are critically examined. Finally, this review discusses the current challenges and prospects.

Burn wounds are prone to infection, and traditional antibiotics cannot be used locally due to bacterial resistance. As a clinical first-line use of silver ion dressings, their use is often limited due to potential toxic side effects and high costs. To overcome these limitations, a bimetallic nanozyme with multiple antibacterial properties was proposed. CuO nanoflowers were first synthesized via a simple liquid-phase method, and then, Ag ions were doped to synthesize Ag-CuO nanozymes. In vitro/in vivo experiments/RNA sequencing revealed that it not only has a variety of enzyme activities, which can accumulate reactive oxygen species (ROS) for sterilization, but can also cooperate with the starvation-cuproptosis-like death cascade for sterilization. The genes regulating the phosphotransferase system were down-regulated by Ag-CuO nanozymes, which reduced the uptake of carbohydrates needed for energy synthesis by bacteria. The tricarboxylic acid cycle signaling pathway was inhibited, and adenosine triphosphate synthesis was reduced, thus inhibiting its own protection against external stimuli. Moreover, the down-regulation of the lpdA gene, coupled with bacterial starvation, synergistically led to an increase in Cu²⁺ influx and an increase in Cu⁺ accumulation, thereby amplifying bacterial cuproptosis-like death and biofilm inhibition. The unique ROS-starvation-cuproptosis-like death sterilization method overcomes the limitation that traditional antibiotics are easily tolerated by bacteria. Importantly, its efficacy was verified in a mouse New Zealand rabbit model, which strongly demonstrated its potential for clinical use in the treatment of drug-resistant bacterial infections, as it has excellent antibacterial activity and the ability to promote angiogenesis compared with those of commercial silver-based dressings with the same silver ion content.

Multisite chronic pain (MCP) frequently co-occurs with immune and depressive disorders, yet whether it reflects coordinated cross-domain multi-omic dysregulation remains unknown. Using UK Biobank data (19,484 baseline participants; 32,870 to 399,476 for 15.9-year follow-up), we identified MCP-related multi-omic signatures spanning 59 biochemical measures, 168 metabolites, and 2,920 proteins. Notably, these signatures showed graded dysregulation [controls < depression < rheumatoid arthritis (RA) < comorbidity] with increasing disease burden, were associated with increased risk of incident RA and depression, and partially mediated their bidirectional association. We further identified HNMT as a depression risk factor, FGF21 as an RA risk factor, MME as a depression protective factor, and platelet count/FGF21/HNMT as shared factors using Mendelian randomization. Beyond disease outcomes, the signatures were associated with brain structural impairment and health-related behaviors (smoking/fish intake/physical activity), and aligned with polygenic liability for immune–metabolic–psychiatric traits. Together, these findings demonstrate that MCP reflects coordinated neuro–immune–metabolic dysregulation underlying RA–depression comorbidity and functions as a systems-level phenotype linking immune processes and depression.

Federated learning enables decentralized, privacy-preserving training but remains vulnerable to privacy leakage in the quantum era. Quantum federated learning (QFL) offers a promising path toward enhanced security and efficiency. However, a practical and experimentally validated QFL protocol utilizing near-term quantum techniques to address data privacy has been lacking. Here, we present QuNetQFL, a QFL protocol implemented on quantum networks, in which local model updates are masked with distributed quantum secret keys, offering information-theoretic security during aggregation. We experimentally validate the protocol on a 4-client quantum network and benchmark its performance using the generated keys on quantum and real-world datasets. Adding a single quantum client substantially improves global accuracy for classifying multipartite entangled and nonstabilizer quantum datasets. For language tasks, we apply QuNetQFL to sentiment analysis by federated fine-tuning of a hybrid classical-quantum language model, achieving comparable and robust performance in simulation and on real quantum hardware. Large-scale simulations further demonstrate scalability to 200 clients for handwritten-digit recognition, with rapid convergence and a 75% reduction in communication cost via model compression. Our work establishes a practical and scalable route to quantum-secure federated learning for the emerging quantum internet.

The selective activation of H₂O₂ into hydroxyl radicals (•OH) through the synergistic interplay between the nanozyme’s internal orbital interactions and external orbital coupling with intermediates presents an important scientific challenge. In this study, we demonstrate that PdBi aerogels with controllable tensile strain first enhance the Pd d orbital energy level through p–d orbital hybridization, and subsequently, the hybridized Pd d orbitals couple sequentially with the molecular orbitals of H₂O₂, forming a cascade of orbital hybridizations. High-performance liquid chromatography quantitative analysis reveals that the engineered PdBi aerogels remarkably improve •OH selectivity from 73.3% to 95.4%, importantly boosting both the activation efficiency and selectivity. Experimental studies and theoretical calculations have demonstrated that the hybridization of the d orbitals of Pd and the p orbitals of Bi in PdBi aerogels initially raises the d-band energy level of the Pd atoms. During the activation of H₂O₂, the high-energy 4d_xz/yz and 4d_z² orbitals of Pd further hybridize with the 2π* and 5σ orbitals of H₂O₂, thereby enhancing the orbital interaction with H₂O₂ and creating optimal conditions for O–O bond cleavage and consequently enhancing the efficiency of •OH generation. Capitalizing on the differential reactivity patterns of various pesticides with PdBi aerogels, we develop a colorimetric sensor array for the discrimination and simultaneous detection of pesticide residues. Taking chlorpyrifos as an example, the detection limit is 0.23 μM, demonstrating good detection sensitivity. This work presents an orbital-level design strategy for creating highly selective nanozymes in H₂O₂ activation systems.

This narrative review summarizes recent advances in the integration of artificial intelligence (AI)-driven rehabilitation robotics with metabolic regulation in critically ill pulmonary patients. AI-enabled robotic systems, combining multimodal physiological sensing with adaptive machine learning, allow continuous monitoring of cardiopulmonary and metabolic parameters and support individualized, dynamic interventions. Unlike conventional rehabilitation based on fixed protocols, these systems establish closed-loop feedback between metabolic signals and motor output, enabling sustained low-intensity muscle activation while optimizing oxygen utilization, glucose metabolism, and mitochondrial function. Such regulation may interrupt the pathological interplay among inflammation, metabolic imbalance, and muscle atrophy, thereby promoting respiratory and systemic recovery. Recent developments in metabolic monitoring, biofeedback control, and multi-omics integration have further extended these platforms toward comprehensive metabolic management. By integrating biomechanical support with computational and biochemical intelligence, this approach reframes rehabilitation as an active process of metabolic reprogramming. However, current evidence remains heterogeneous, and well-designed clinical studies are needed to validate the reproducibility and clinical efficacy of these strategies.