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.

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.

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.

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).

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.

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.

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.

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.

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.