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.