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.

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.

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.

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.

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.

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.

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.