Understanding the impacts of anthropogenic activities on groundwater is crucial for its management and utilization. However, predicting anthropogenic impacts on groundwater remains challenging due to their complexity. As any anthropogenic activity generates carbon emissions, we employed carbon emissions to characterize the intensity of anthropogenic activities to predict groundwater storage variations. Carbon emission–groundwater machine learning models indicate that groundwater storage will increase in Rhine Valley (7.3% ± 1.9%), the Great Lakes Basin (6.7% ± 4.3%), and Pearl River catchments (1.8% ± 1.5%) in the next 3 decades, but it will continue to decline in Yangtze River catchments (−13.7% ± 3.4%), with R² ranging from 0.916 to 0.995. Furthermore, the existing groundwater protection measures of Yangtze River catchments will not be sufficient to compensate for future declines in groundwater storage caused by anthropogenic activities (5.9% ± 4% decrease in 2050), indicating the necessity of more effective measures. This study developed a method to predict the impacts of anthropogenic activities on groundwater, thus overcoming an important obstacle in predicting groundwater behavior, which is crucial for the utilization and management of groundwater resources. The methodology developed in this study for predicting the impacts of anthropogenic activities on groundwater will raise awareness of the link between anthropogenic activities and groundwater and lead to in-depth research on anthropogenically driven groundwater prediction studies. This will overcome substantial barriers to predicting groundwater behavior, which is critical for groundwater resource use and management.

As a critical global public health concern, food safety has prompted substantial strategic advancements in detection technologies to safeguard human health. Integrated intelligent sensing systems, incorporating advanced information perception and computational intelligence, have emerged as rapid, user-friendly, and cost-effective solutions through the synergy of multisource sensors and smart computing. This review systematically examines the fundamental principles of intelligent sensing technologies, including optical, electrochemical, machine olfaction, and machine gustatory systems, along with their practical applications in detecting microbial, chemical, and physical hazards in food products. The review analyzes the current state and future development trends of intelligent perception from 3 core aspects: sensing technology, signal processing, and modeling algorithms. Driven by technologies such as machine learning and blockchain, intelligent sensing technology can ensure food safety throughout all stages of food processing, storage, and transportation, and provide support for the traceability and authenticity identification of food. It also presents current challenges and development trends associated with intelligent sensing technologies in food safety, including novel sensing materials, edge-cloud computing frameworks, and the co-design of energy-efficient algorithms with hardware architectures. Overall, by addressing current limitations and harnessing emerging innovations, intelligent sensing technologies are poised to establish a more resilient, transparent, and proactive framework for safeguarding food safety across global supply chains.

Advanced haptic feedback interfaces are essential for human–machine interaction, particularly in assistive technologies that offer versatile commands, simplify navigation, and enhance emotional interactions for individuals with visual and hearing impairments. Current systems, primarily reliant on Braille and mechanical announcements, fall short of addressing these needs. Existing haptic interfaces, while providing various haptic feedback modes, still face challenges including rigid, strong current, or high-voltage stimulation, limiting their applicability and long-term safety for widespread use. Here, the work demonstrates a flexible, integrable, and programmable haptic interface based on elastomer actuators that utilize a unique forming process to create customized local stiffness in a multilayer elastomer by varying the cross-linking density of elastomers. Complemented by tailored software, the system delivers a 4-dimensional haptic experience within a safe voltage of less than 50 V and a frequency range of 50 to 450 Hz, enabling high-fidelity emotional and navigational feedback. Demonstrations of this system achieve an average accuracy rate of 64.6% in emotional interactions without prior training, improving to 95.8% with learning mode, along with an average accuracy rate of 94.2% for 9 directional commands in navigation interactions.

Mechanical metamaterials, by introducing porous structures into the materials, can achieve complex nonlinear responses through the large deformation of structures, which support a new generation of impact energy absorption and vibration damping systems, wearable electronics, and tactile simulation devices. However, arbitrarily customizable stress–strain curves have yet to be achieved by existing mechanical metamaterials, which are inherently multi-degree-of-freedom (multi-DOF) deformable systems, and their deformation sequence is influenced by the minimum energy gradient principle. Multi-DOF metamaterials behave like underactuated systems, where the number of degrees of freedom exceeds the number of actuators. As a result, their deformation is controlled by the material's elastic forces, inertial forces, and boundary constraints. Here, we propose a novel composition of elastic components integrated with one-degree-of-freedom (1-DOF) kinematic bases, forming a fully actuated system in which the number of actuators equals the number of degrees of freedom. The deformation of each elastic component is governed by its designed 1-DOF kinematic path. Consequently, the stress–strain profile can be arbitrarily prescribed, for instance, controlled multistage strain softening curve is achievable, as the principle of minimum energy gradient does not affect the deformation sequence dictated by the 1-DOF kinematic base. Furthermore, a class of shape memory alloys (SMAs) is introduced as active components to enable rapid in situ property change, providing versatility in switching between different target responses. The analytical inverse design method, numerical analysis, parametric study of different target responses, and experimental validation are carried out. Lastly, preliminary demonstrations of designable anisotropic nonlinear responses are presented.

Mesangial proliferative glomerulonephritis (MsPGN) is the most common glomerulonephritis pathological type, including IgA nephropathy (IgAN), in which regional immune injury leads to disease progression without targeted treatment approaches. The mechanism of regional immune injury in MsPGN is unclear. We previously performed single-cell RNA sequencing (scRNA-seq) of IgAN and identified that the CX3CR1 gene increased in kidney. In this study, further scRNA-seq analysis and cellchat analysis revealed that CX3CL1 and CX3CR1 expression was increased in mesangial cells and monocytes/macrophages, respectively, in IgAN, mediating stronger crosstalk. This result and its association with regional immune injury were validated in clinical specimens and MsPGN animal model. Deficiency of CX3CR1⁺ monocytes/macrophages in the MsPGN animal model attenuated proteinuria, cell proliferation, and inflammation in glomerulus. Mechanistically, CX3CL1 in activated mesangial cells induced CX3CR1⁺ monocyte/macrophage migration and activation, and RNA-seq, Luminex multiplex immunoassay, and molecular analysis revealed that CX3CR1⁺ monocytes/macrophages induced mesangial cell injury via the MIF–CD74 interaction and activated the phosphatidylinositol 3-kinase (PI3K)/proteinserine-threonine kinase (AKT) pathway. Lastly, the therapeutic effect of the CX3CL1 monoclonal antibody quetmolimab was validated for inhibiting the progression of MsPGN. These findings demonstrate that activated mesangial cells interact with CX3CR1⁺ monocytes/macrophages promoting glomerulus regional immune injury in MsPGN, providing evidence into the CX3CL1–CX3CR1 axis as a novel target of treatment for MsPGN.

Ferroptosis plays a role in wound healing during the maturation of senescent endothelial cells. This study explores the modulation of ferroptosis in senescent human umbilical vein endothelial cells (HUVECs) and wound-healing processes by Piezo1 activation at the molecular, cellular, and tissue levels. Elevated Piezo1 expression was observed in HUVECs treated with the senescence inducer doxorubicin (Doxo) and the ferroptosis inducer erastin and in aged wound tissue. Pharmacological inhibition or knockdown of Piezo1 protected senescent HUVECs and aged wound tissue from ferroptosis. Additionally, Piezo1 channel activity was found to promote ferroptosis in senescent HUVECs by increasing intracellular Ca²⁺ levels. The calmodulin-dependent kinase II (CaMKII)/activating transcription factor 3 (ATF3)/SLC7A11 signaling axis was activated upon stimulation with erastin and Doxo, driving Piezo1-induced ferroptosis. CaMKII directly interacted with ATF3, which could be modulated through Piezo1 channel regulation. Notably, Piezo1 knockout mice or adeno-associated virus 9-mediated silencing of ATF3 attenuated ferroptosis in senescent cells and accelerated wound repair. Mechanistically, both genetic and pharmacological inhibition of Piezo1 promoted wound healing in aged tissues and regulated ferroptosis in senescent HUVECs through the CaMKII/ATF3/SLC7A11 pathway. In conclusion, these findings suggest that targeting Piezo1-mediated ferroptosis in senescent HUVECs offers a promising therapeutic approach for improving wound healing in the elderly.

The explosive growth of data has intensified challenges to information security, spurring a critical need for advanced encryption technologies, and relying solely on digital encryption still leaves information vulnerable to interception and leakage during transmission. Therefore, encryption technologies that combine digital algorithms with physical keys to further enhance information security are widely studied. In this work, we present an angle- and polarization-selective dual-wavelength long-wavelength infrared narrowband thermal emitter for infrared encryption–decryption applications. The thermal emitter is composed of an epsilon-near-zero material upon a metallic layer, designed to enable the excitation of the Berreman mode and asymmetric Fabry–Pérot resonance simultaneously. Numerical simulations combined with the transfer matrix method are employed to analytically investigate the optical responses, demonstrating good agreement with experimental results. Moreover, a robust multilevel cryptographic communication system is developed, utilizing the thermal emitter's imaging results as the physical-layer key to enable highly efficient information encryption and decryption. We anticipate that the proposed thermal emitters will pave the way for realizing relevant applications in various information encryption devices.

Limited research has investigated the connection between long COVID (LC) and the respiratory microbiome, particularly in older adults. This study aimed to characterize the respiratory microbiome of older LC patients (with an average age of 65 years old), through meta-transcriptomic sequencing of 201 individual samples. Marked differences in microbial diversity were observed between LC and non-LC patients, including disruptions in both pathogenic bacteria and fungi. Importantly, viral taxa, such as Herpes simplex virus type 1 and Human coronavirus 229E, were more frequently detected in LC patients, indicating the vulnerability of LC patients to viral infections. Functional annotation at the expression level revealed notable differences in microbial metabolism with alterations observed in pathways related to tryptophan–serotonin metabolism in LC patients. These findings underscore the altered microbial landscape, especially in older adults who developed LC, and fill the gap for the potentially clinical roles played by the respiratory microbiome.

Background: Emerging evidence suggests that autoantibodies targeting podocytes are potential contributors to idiopathic nephrotic syndrome (INS); however, the specific mechanisms remain unclear. This study aims to explore the pathogenic role and underlying mechanisms of anti-vinculin autoantibodies in INS. Methods: Serum anti-vinculin autoantibody levels detected by protein microarray and clinical data were compared among INS patients (n = 147), healthy individuals (n = 84), and patients with other kidney or immune diseases (n = 100 of each disease). Immune-mediated mouse models were established to verify the pathogenicity of anti-vinculin autoantibodies. Mouse urine was monitored for urine protein levels, while immunofluorescence, pathological staining, and electron microscopy assessed kidney pathological and ultrastructural changes. Transcriptome sequencing of mouse kidney tissues was performed to investigate the key molecular mechanisms and signaling pathways involved in kidney injury post-immunization. Results: Anti-vinculin autoantibody levels were specifically elevated in INS patients, with a 54.42% positivity rate, correlating with urinary albumin, serum albumin, cholesterol, and CD19 levels. The average anti-vinculin autoantibody levels dropped markedly in pediatric INS patients during remission. Mouse experiments revealed that injecting anti-vinculin antibodies or recombinant vinculin protein induced proteinuria and podocyte injury in the immunized mice, and the renal phenotype closely resembled the pathological characteristics of minimal change disease. Transcriptome sequencing of renal tissues revealed up-regulation of inflammation, immune responses, cytokine activities, and B cell activation pathways in the immunized mice, while cytoskeleton-related functions were down-regulated. Conclusions: Autoantibodies targeting vinculin act as pathogenic autoantibodies in INS and hold potential value for diagnosing and monitoring INS progression.

Natural killer (NK) cells, serving as pivotal mediators of innate immunity, play an important role in antitumor immunity. Immune checkpoint can be expressed on the surface of NK cells and meticulously regulates their activation states and effector functions through complex signaling networks. In recent years, tumor immunotherapy strategies focusing on NK cell immune checkpoints have demonstrated remarkable advancements. This review systematically elucidates the expression profiles, signaling pathways, and the immune checkpoint molecule regulatory mechanisms localized on the NK cell membrane (e.g., NKG2A, KIRs, and TIGIT) or intracellularly (e.g., BIM, Cbl-b, and EZH2) during tumor immune evasion. Particular attention is devoted to dissecting the regulatory mechanisms through which these immune checkpoint molecules influence NK cell-mediated cytotoxicity, cytokine secretion, proliferative capacity, and tunable modulation of NK cell immune checkpoint expression by diverse factors within the tumor microenvironment. Furthermore, this review comprehensively summarizes preclinical advancements in NK cell immune checkpoint blockade strategies, including single checkpoint blockade, combinatorial checkpoint approaches, and their integration with conventional therapeutic modalities. Additionally, emerging therapeutic advancements, such as gene-editing technologies and chimeric antigen receptor-NK (CAR-NK) cell therapy, are evaluated for their prospective applications in immunotherapy based on NK cells. By thoroughly elucidating the molecular regulatory networks underlying NK cell immune checkpoints and their mechanisms of action within the complex tumor microenvironment, this review aims to provide critical theoretical insights and translational foundations to foster the development of innovative tumor immunotherapy strategies, improvement of combination therapies, and realization of personalized precision medicine.

Ultrasound localization microscopy (ULM) is a novel imaging technique that overcomes the diffraction limit to achieve super-resolution imaging at the 10-μm scale. Despite its remarkable progress, challenges persist in enhancing the precision of microbubble tracking and fulfilling the requirements for high frame rates in practical circumstances, especially in moving organs. To address these issues, an enhanced ULM approach (shorten as vc-Kalman) integrating rapid motion compensation was developed to achieve excellent image quality. Unlike traditional methods relying on observed bubble positions, the proposed algorithm combined statistical information derived from historical data with Kalman-filter-predicted positions to enable more accurate bubble localization. Meanwhile, microbubble brightness in adjacent frames was incorporated as multidimensional feature to further improve the matching efficacy. Furthermore, velocity constraint was applied to minimize possible erroneous traces and enhance the contrast-to-noise ratio of ULM images, while ensuring the continuity of vascular reconstruction and the accuracy of the blood flow analysis to generate a reduced normalized root mean square error in velocity estimation, even at a relatively low frame rate of 146 Hz. More important, to effectively suppress the impact of physiological movements in moving organs like kidneys, this algorithm fulfilled subpixel displacement vector identification through parabolic fitting and expedited motion compensation via dynamic programming-based cross-correlation search. The results indicated that this advanced vc-Kalman method substantially boosted both the robustness and accuracy of ULM imaging, thereby opening more opportunities for clinical applications of super-resolution ULM technology.

In heavy-ion collisions at relativistic energies, the incident nuclei travel at nearly the speed of light. These collisions deposit kinetic energy into the overlap region and create a high-temperature environment where hadrons “melt” into deconfined quarks and gluons. The spectator nucleons, which do not undergo scatterings, generate an ultraintense electromagnetic field—on the order of 10¹⁸ G at the Relativistic Heavy Ion Collider and 10¹⁹ G at the Large Hadron Collider. These powerful electromagnetic fields have a substantial impact on the produced particles, not only complicating the study of particle interactions but also inducing novel physical phenomena. To explore the nature of these fields and their interactions with deconfined quarks, we provide a detailed overview, encompassing theoretical estimations of their generation and evolution, as well as experimental efforts to detect them. We also provide physical interpretations of the discovered results and discuss potential directions for future investigations.

Thermoelectric (TE) materials have garnered widespread research interest owing to their capability for direct heat-to-electricity conversion. Binary indium-based chalcogenides (In–X, X = Te, Se, S) stand out in inorganic materials by virtue of their relatively low thermal conductivity. For example, In₄Se_2.35 shows a low thermal conductivity of 0.74 W m⁻¹ K⁻¹ and an impressive zT value of 1.48 along the b–c plane at 705 K, as a result of structural anisotropy. Here, we review the structural features and recent research progress in the TE field for In–X materials. It begins by presenting the characteristics of crystal structure, electronic band structure, and phonon dispersion, aiming to microscopically understand the similarity/dissimilarity among these In–X compounds, notably the role of unconventional bonds (such as In–In) in modulating the band structures and lattice vibrations. Furthermore, TE optimization strategies of such materials were classified and discussed, including defect engineering, crystal orientation engineering, nanostructuring, and grain size engineering. The final section provides an overview of recent progress in optimizing TE properties of indium tellurides, indium selenides, and indium sulfides. An outlook is also presented on the major challenges and opportunities associated with these material systems for future TE applications. This Review is expected to provide critical insights into the development of new strategies to design binary indium-based chalcogenides as promising TE materials in the future.

Tryptophan (Trp), an essential amino acid, performs as a precursor for synthesizing various bioactive molecules primarily metabolized through the kynurenine (Kyn), serotonin, and indole pathways. The diverse metabolites were deeply implicated in multiple physiological processes. Emerging research has revealed the multifaceted contribution of Trp in skeletal health and pathophysiology of bone-related disease with the involvement of specific receptors including aryl hydrocarbon receptor (AhR), which modulated the downstream signaling pathways to manage the expression of pivotal genes and thereby altered cellular biological processes, such as proliferation and differentiation. Accompanied by distinct alterations in immune function, inflammatory responses, endocrine balance, and other physiological aspects, their impact and efficacy in osteochondrogenic disorders have also been well documented. Nevertheless, a thorough understanding of Trp metabolism within bone biology is currently lacking. In this review, we elucidate the complexities of Trp metabolic pathway and several metabolites, delineating their versatile modulatory roles in the physiology and pathology of osteoblasts (OBs), osteoclasts (OCs), chondrocytes, and intercellular coupling effects, as well as in the progression of osteochondral disorder. Moreover, we comprehensively delineate the regulatory mechanisms by which gut microbiota-generated indole derivatives mediate bidirectional crosstalk along the gut–bone axis. The establishment of an elaborate governing network about bone homeostasis provides a novel insight on therapeutic interventions.

The first challenge in building a living robotic system inspired by life evolution is how to replicate the original form of life—the cell. However, current microrobots mimic cell motion control but fail to replicate the functional biological activities of cellular systems. Here, we propose a strategy that programs microparticle swarms encapsulated in droplets at an air/liquid interface to create cell-mimetic droplet microrobots with vitality by employing alternating magnetic fields. Through the design of algorithms and spontaneous interface waves, our collective system embodies reversible transitions between gas, chain, array, and disk-like collective modes, and emulates various complex activities of living cells in nature, including division and exocytosis. Based on these 2 capabilities learned from living cells, the cell-mimetic microrobots navigate the bile duct to the gallbladder under the guidance and control of magnetic fields, completing the drug release task. This cell-mimetic microrobots may provide a fundamental understanding of cellular life and pave the way for the construction of artificial living systems. Furthermore, they hold substantial potential for medical and environmental applications.

Developing low-cost plastic recycling technologies is crucial for ecological sustainability and the circular economy. The recent publication in Science by Conk et al. introduces an innovative method employing base-metal catalysts, specifically WO₃/SiO₂ and Na/γ-Al₂O₃, to efficiently convert polyethylene, polypropylene, or their mixtures into valuable products, representing a marked advancement in the field of base-metal catalysis and plastic recycling.

Enzyme–photosensitizer (PS) conjugates hold great promise for clinical treatment of cancer and infectious diseases via catalysis-augmented photodynamic therapy (PDT). Compared to covalent coupling, physical binding utilizing noncovalent interactions provides a simple and nondestructive strategy to combine PS with enzymes. However, the mechanism of enzyme–PS physical combination remains largely unknown, and physically bonded enzyme–PS conjugates are rarely reported. Here, we systematically investigate the interacting behaviors of representative enzymes with one of the most popular PS of chlorin e6 (Ce6) and elucidate their binding dynamics and crucial determinants. Our results reveal that the positively charged and hydrophobic residues on the surface of enzymes are crucial determinants of Ce6 binding. In addition, we demonstrate that the positively charged surface area of enzymes can be employed as a reliable criterion for assessing and predicting the enzyme–Ce6 binding affinity. Guided by this criterion, we further construct catalase–Ce6 nanoconjugates (CAT–Ce6 NCs) with superior stability and robust photodynamic antimicrobial capability via physical binding. In a showcase treatment of methicillin-resistant Staphylococcus aureus (MRSA)-infected mouse model of subcutaneous abscess, CAT–Ce6 NCs enable hypoxia pathological microenvironment remodeling and bacteria elimination, realizing effective catalysis-augmented PDT. This study deciphers the physical binding mechanism of enzyme–PS and establishes a theoretical framework to facilitate the design and construction of outstanding enzyme–PS NCs for catalysis-augmented PDT.

Macrophages participate in the immune system by recognizing and engulfing foreign bodies inside phagosomes, which fuse with lysosomes in their cytoplasm to form mature phagolysosomes. Lysosomes have an acidic interior and generate and release reactive oxygen and nitrogen species (ROS/RNS) to destroy the endocytosed entities. It has been previously reported that intra-lysosomal pH plays an essential role in the regulation of ROS/RNS. However, the exact regulatory mechanism remains to be elucidated. Taking advantage of the large number of active lysosomes distributed along the phagocytic lumen during frustrated phagocytosis of glass fibers by macrophages, the intensity of 4 primary ROS/RNS released fluxes (ONOO⁻, H₂O₂, NO, and NO₂⁻) was monitored with platinum nanoelectrochemical sensors, thereby revealing the important role of intra-lysosomal pH on ROS/RNS fluxes after pharmacological modulations. Acidification (pH <5.0) does not alter the rate of production of ROS/RNS precursors (superoxide ions, O₂^•−, and parent NO) but promotes O₂^•− protonation, leading to an increase of H₂O₂ release. In contrast, the initial production of NO, which subsequently increased the release of ONOO⁻ and NO₂⁻, was enhanced by alkalinization (pH >6.0). The resulting increased oxidative stress was associated with massive proinflammatory cytokine release. Taken together, these results provide important information about the impact of lysosomal pH on ROS/RNS regulation.

Ferroptosis has promising potential for augmenting antitumor effects, but monotherapy with ferroptosis inducers in vivo has been reported to have limited efficacy in tumor management. The development of synergistic strategies with targeted capabilities is crucial for enhancing the antitumor efficacy of ferroptosis inducers. In this study, we designed and characterized a novel self-assembled nanomedicine by mixing ferrous ions (Fe²⁺) and epigallocatechin gallate (EGCG) in a controllable manner and encapsulating the ferroptosis inducer RSL3, named Fe-EGCG@RSL3. This multifunctional nanomedicine effectively induces ferroptosis and growth inhibition in bladder cancer cells and patient-derived organoids. In vivo, Fe-EGCG@RSL3 was enriched in the subcutaneous tumors of allogenic and xenograft mouse models, thereby substantially overcoming RSL3 resistance. Intravesical instillation of Fe-EGCG@RSL3 controls orthotopic bladder tumor progression. Furthermore, nanomedicine potentiates the therapeutic effect of anti-programmed cell death protein 1 (PD1) immunotherapy by increasing the cytotoxicity of CD8⁺ T cells to cancer cells and modulating the proportions of both T-cell and myeloid cell subpopulations within the tumor immune microenvironment. Overall, Fe-EGCG@RSL3 has dual functions as a multifaceted nanomedicine that integrates ferroptosis induction with immunomodulation, offering a novel and clinically translatable strategy for bladder cancer therapy.

Ocean acidification is becoming more prevalent and may contribute to coral reef degradation, yet our understanding of its role in global reef decline remains limited. Therefore, there is an urgent need to study the impact of reduced pH levels on the growth patterns of major reef-building corals. Here, we studied the skeleton-forming strategies of 4 widely distributed coral species in a simulated acidified habitat with a pH of 7.6 to 7.8. We reconstructed and visualized the skeleton-forming process, quantified elemental calcium loss, and determined gene expression changes. The results suggest that different reef-building corals have diverse growing strategies in lower pH conditions. A unique “cavity-like” forming process starts from the inside of the skeletons of Acropora muricata, which sacrifices skeletal density to protect its polyp–canal system. The forming patterns in Pocillopora damicornis, Montipora capricornis, and Montipora foliosa were characterized by “osteoporosis”, exhibiting disordered skeletal structures, insufficient synthesis of adhesion proteins, and low bone mass, correspondingly. In addition, we found that damage from acidification particularly affects pre-existing skeletal structures in the colony. These results enhance our understanding of skeleton-forming strategies in major coral species under lower pH conditions, providing a foundation for coral reef protection and restoration amidst increasing ocean acidification.

Bistable structures, which leverage mechanical instability, have emerged as a promising paradigm in the development of robotic grippers, providing advantages including rapid response and low energy consumption. A critical limitation of existing bistable grippers, however, lies in their invariable energy barriers, which hinder the balance between compliant triggering and powerful grasping. In this study, we propose a bistable robotic gripper capable of in situ energy barrier modulation, inspired by the adaptive seed dispersal behavior of Impatiens pods. This robotic gripper features an elastic curved beam-based architecture integrated with a motor-driven mechanism, enabling dynamic regulation of its energy landscape. This approach allows the energy barrier to be tuned over an order of magnitude during manipulation. In the low-barrier state, the robotic gripper initiates object interaction with a triggering force as low as 0.66 N, allowing for delicate manipulation. Upon state transition, instant energy barrier modulation (~300 ms) enhances grasping stability, achieving failure forces up to 12.08 N. This adaptive modulation strategy enables our robotic gripper to implement rapid, compliant, and powerful interaction. When incorporated into an unmanned aerial vehicle, the robotic gripper showcases reliable perching across diverse scenarios, highlighting the potential of energy barrier modulation to advance the adaptability and functionality of robotic systems.

Acute kidney injury (AKI) is a clinical syndrome with high mortality, and its pathogenesis involves complex inflammatory regulatory mechanisms. As core components of the cytokine network, interleukins (ILs) exert pleiotropic effects in the development of AKI, participating in processes such as inflammation, fibrosis, tissue damage repair, and remote organ injury. Moreover, ILs influence the progression of AKI by mediating the crosstalk among renal resident cells, immune cells, and fibroblasts. Pro-inflammatory ILs primarily accelerate the progression of AKI by recruiting neutrophils and inducing renal cell apoptosis, whereas anti-inflammatory ILs alleviate AKI by inhibiting the release of inflammatory cytokines and enhancing regulatory T cell function. Dual-function ILs may either promote disease progression or facilitate tissue repair depending on their cellular origin or the specific pathological stage. In terms of therapeutic strategies, monoclonal antibodies targeting ILs and their receptors, as well as advancements in extracellular vesicle technology, have shown promising potential. Future research should focus on elucidating the specific signaling networks of ILs and their intercellular interactions in order to promote precision medicine approaches for AKI and to block the transition from AKI to chronic kidney disease (CKD).

Advancing targeted cancer immunotherapy is pivotal for overcoming distant metastasis and tumor relapse. The recent study in Nature Cancer by Sanlorenzo et al. demonstrates a breakthrough strategy combining systemic type I interferon with topical Toll-like receptor 7/8 agonists, where oral imiquimod primes plasmacytoid dendritic cells (DCs) to produce type I interferon, thereby sensitizing conventional DCs in tumors to local Toll-like receptor 7 activation. This approach triggers c-Jun-dependent IL-12 production and CCL2-mediated plasmacytoid DC recruitment, enabling localized and systemic tumor suppression. Importantly, the therapy synergizes with PD-1 blockade to prevent recurrence, representing a significant advance in DC-targeted cancer immunotherapy.

Opioid use disorders (OUDs) pose a substantial global health burden, with methadone maintenance treatment (MMT) widely adopted as an intervention; however, MMT is associated with immunosuppression, metabolic disturbances, and dysbiosis of the gut microbiota. Despite the potential of acupuncture in reducing methadone dosages and opioid addiction, the underlying biological mechanisms remain unclear. Therefore, we aimed to integrate clinical trial data with multi-omics analysis, including single-cell sequencing, transcriptomics, metabolomics, and metagenomics, to evaluate the effects of acupuncture in patients undergoing MMT. We collected peripheral blood mononuclear cells, plasma, and fecal samples from 48 MMT participants in a randomized, placebo-controlled trial. Participants were divided into acupuncture (n = 25) and sham-acupuncture (n = 23) groups. After 8 weeks of intervention, 84% of patients in the acupuncture group achieved ≥20% reduction in methadone dosage, compared to 39% in the sham-acupuncture group (P < 0.01). Our findings revealed that acupuncture may activate the defense response to viruses, with altered immune cell functions in classical monocytes correlating with clinical responses to reduced methadone doses. Acupuncture might ameliorate intestinal microbial disruptions caused by OUD by up-regulating Bilophila and modulating bile acid metabolism. Furthermore, acupuncture up-regulated galectin-9 (LGALS9)-mediated intercellular communication between classical monocytes and other immune subsets. To further validate the mechanistic link between bile acid metabolism and immune regulation, we conducted in vitro experiments using THP-1 monocytes treated with cholic acid. The results showed that bile acid exposure suppressed galectin-9 and IFN-γ expression, while low-dose bile acid (simulating acupuncture effects) partially reversed this effect. These findings support a bile acid–galectin–interferon axis that may be modulated by acupuncture in OUD. Collectively, our results provide clinical and mechanistic evidence supporting acupuncture as a potential adjunct therapy to mitigate the adverse effects of long-term opioid use.

Strain-stiffening hydrogels, which mimic the nonlinear mechanical behavior of biological tissues such as skin, arteries, and cartilage, hold transformative potential for biomedical applications. This study introduces immersion phase separation (IPS) 3-dimensional (3D) printing, an innovative technique that enables the one-step fabrication of strain-stiffening hydrogel scaffolds with intricate, hierarchical architectures. This technique addresses the long-standing challenge of balancing structural complexity and intrinsic mechanoresponsive behavior in traditional hydrogel fabrication methods. By leveraging dynamic hydrophobic interactions and solvent exchange kinetics, IPS 3D printing achieves multiscale control over pore architectures (5 to 200 μm) and anisotropic microchannels while preserving J-shaped stress–strain curves (fracture stress: ~0.7 MPa; elongation: >1,000%). The physically cross-linked network enables closed-loop recyclability (>95% material recovery) without performance degradation, while functional fillers (e.g., carbon nanotubes, copper, and hydroxyapatite) enhance properties such as electrical conductivity (2-orders-of-magnitude improvement) and real-time motion sensing capabilities. This platform facilitates the creation of patient-specific implants with tailored mechanical properties and paves the way for adaptive biohybrid devices that mimic the dynamic behavior of native tissues, holding promise for regenerative medicine, soft robotics, and advanced biomedical applications. IPS 3D printing uniquely resolves the trade-off between structural sophistication and functional biomimicry, establishing a paradigm for replicating dynamic biological tissues.

Cancer immunotherapy has greatly changed the therapeutic landscape for metastatic malignancies. Nevertheless, due to immune-related adverse events, drug resistance, and other factors, cancer immunotherapy remains largely untapped. Recent research has shown that the microbiota is crucial in shaping immune function and that its modulation can influence antitumor immunity. However, because of the intricate nature of the microbiome and immune system, a comprehensive mechanistic framework for understanding how the microbiota influences antitumor immune responses is still lacking. In this review, we summarize the mechanisms of the microbiota in antitumor immunity. We also comprehensively outline the methods for measuring the microbiota and their limitations. Additionally, we discuss the key challenges facing the targeting of the microbiota as a regulatory strategy for cancer immunotherapy.

There is remarkable demand for bio-based specialty resins such as benzoxazine thermosets, but they are brittle and difficult to process. This study reports the synthesis of a processable bio-based polybenzoxazine resin via the copolymerization of rigid and soft benzoxazine dimers synthesized from bio-based phenols. The polybenzoxazine copolymer demonstrated excellent thermoplasticity and a tunable toughness in the range of 9.0 to 24.1 MJ/m³. The incorporation of soft segments and dynamic ester bonds in the polybenzoxazine notably improved its thermoplasticity compared with traditional thermosetting benzoxazine resins. The polybenzoxazine copolymer also demonstrated a dielectric constant of 2.99 and a dielectric loss of 0.019 at 3 GHz, as well as a high breakdown voltage of 27.2 kV/mm. This research highlights the promising mechanical and thermal properties of the resulting bio-based resin, as well as its tunable dielectric properties, making it a competitive candidate for various high-performance applications in the polymer industry.

Apolipoprotein E (ApoE) has been implicated in neurodegenerative diseases; however, its function and underlying mechanisms in depression remain elusive. In this study, we employed chronic social defeat stress (CSDS) to establish a mouse model of depression and observed significantly reduced ApoE expression in the hippocampus. By leveraging ApoE knockout (ApoE^−/−) and knockdown (ApoE-KD) mouse models, we demonstrated that ApoE deficiency induced depression-like behaviors, which were closely associated with impaired GABAergic synaptic transmission and down-regulation of ApoE receptors and K⁺–Cl⁻ cotransporter 2 (KCC2). In addition, we found an interaction between KCC2 and the ApoE receptor low-density lipoprotein receptor (LDLR) through coimmunoprecipitation analysis. Moreover, overexpression of ApoE or targeted activation of GABAergic neurons in the hippocampus significantly reversed depression-like behaviors in both CSDS-exposed and ApoE-KD mice. Lastly, treatment with KCC2 activators, CLP290 and CLP257, restored the expression levels of KCC2 and the GABA_AR α1 subunit, significantly alleviating depression-like behaviors induced by CSDS or ApoE-KD. Together, our results elucidate the pivotal role of ApoE in the pathophysiology of depression and highlight the ApoE–KCC2 signaling pathway as a potential target for developing innovative antidepressant therapies.

Protein kinases are key mediators of cellular signaling and control cell functions through the phosphorylation of target proteins. They have become major targets for therapeutic agents aimed at treating human diseases, particularly cancer. Protein kinase inhibitors (PKIs) have emerged at the forefront of drug development, and their investigations continue to be intense, with several candidates undergoing clinical trials and persistent endeavors to identify new chemical scaffolds. The main focus is still on developing isoform-selective compounds, which are inhibitors designed to target certain protein kinases, specifically isoforms, for more precise treatment. The identification and advancement of versatile inhibitor scaffolds that more effectively target individual kinases is essential for minimizing off-target effects and resistance. This review highlights important progress in PKI therapy, emphasizing the expansion of treatments for cancer, inflammatory diseases, and neurodegenerative diseases. Future efforts should focus on improving the specificity of inhibitors via mechanistic insights, developing combination therapies, establishing novel strategies, such as CRISPR-Cas9 integration with artificial intelligence-driven drug design, and overcoming resistance to enhance clinical treatment outcomes. Clinical case stories show the challenges and possible opportunities in this quickly evolving area.

Background: No robust biomarkers have been identified to predict the efficacy of programmed cell death protein 1 (PD-1) inhibitors in patients with locoregionally advanced nasopharyngeal carcinoma (LANPC). We aimed to develop radiomic models using pre-immunotherapy MRI to predict the response to PD-1 inhibitors and the patient prognosis. Methods: This study included 246 LANPC patients (training cohort, n = 117; external test cohort, n = 129) from 10 centers. The best-performing machine learning classifier was employed to create the radiomic models. A combined model was constructed by integrating clinical and radiomic data. A radiomic interpretability study was performed with whole slide images (WSIs) stained with hematoxylin and eosin (H&E) and immunohistochemistry (IHC). A total of 150 patient-level nuclear morphological features (NMFs) and 12 cell spatial distribution features (CSDFs) were extracted from WSIs. The correlation between the radiomic and pathological features was assessed using Spearman correlation analysis. Results: The radiomic model outperformed the clinical and combined models in predicting treatment response (area under the curve: 0.760 vs. 0.559 vs. 0.652). For overall survival estimation, the combined model performed comparably to the radiomic model but outperformed the clinical model (concordance index: 0.858 vs. 0.812 vs. 0.664). Six treatment response-related radiomic features correlated with 50 H&E-derived (146 pairs, |r|= 0.31 to 0.46) and 2 to 26 IHC-derived NMF, particularly for CD45RO (69 pairs, |r|= 0.31 to 0.48), CD8 (84, |r|= 0.30 to 0.59), PD-L1 (73, |r|= 0.32 to 0.48), and CD163 (53, |r| = 0.32 to 0.59). Eight prognostic radiomic features correlated with 11 H&E-derived (16 pairs, |r|= 0.48 to 0.61) and 2 to 31 IHC-derived NMF, particularly for PD-L1 (80 pairs, |r|= 0.44 to 0.64), CD45RO (65, |r|= 0.42 to 0.67), CD19 (35, |r|= 0.44 to 0.58), CD66b (61, |r| = 0.42 to 0.67), and FOXP3 (21, |r| = 0.41 to 0.71). In contrast, fewer CSDFs exhibited correlations with specific radiomic features. Conclusion: The radiomic model and combined model are feasible in predicting immunotherapy response and outcomes in LANPC patients. The radiology–pathology correlation suggests a potential biological basis for the predictive models.

Micro-electro-mechanical systems (MEMS) light detection and ranging (LiDAR) systems are widely employed in diverse applications for their precise ranging and high-resolution imaging capabilities. However, conventional Lissajous scanning patterns, despite their design flexibility, are increasingly limited in meeting the growing demands for image quality. In this study, we propose a novel programmable scanning method that enhances angular resolution within defined regions of interest (ROIs). By applying parameter modulation techniques, we establish a direct, analytical link between the scanning trajectory and ROI placement, enabling precise resolution control. The proposed method increases point cloud density by 2 to 6 times across any ROI within a Lissajous scan, achieving localized improvements of up to 650%, independent of frequency constraints. Moreover, it reduces the design complexity of MEMS scanning mirrors by half, while maintaining comparable high-resolution performance. Incorporating a gaze-inspired trajectory modulation strategy and random modulation continuous wave ranging, we develop a MEMS LiDAR prototype that greatly enhances point cloud fidelity and enables accurate 3-dimensional imaging within ROIs—achieving a ranging accuracy of 2.4 cm (3σ). This approach not only improves angular resolution in targeted regions but also extends the practical applicability of MEMS LiDAR to multitarget tracking and recognition scenarios. Furthermore, the study establishes a robust theoretical framework for ROI-based trajectory control, contributing to the advancement of next-generation high-resolution imaging systems.