Real-time monitoring of liver injury is essential for preserving physiological health. Alanine aminotransferase (ALT) detection is widely regarded as a fundamental approach for the early diagnosis of liver injury. However, existing detection methods often suffer from complex operation, high costs, and limited sensitivity. Here, we introduce a real-time biosensor based on functionalized liquid crystal microcavities with whispering gallery mode (WGM) laser for rapid and sensitive ALT detection. The microcavity functionalized with stearic acid exhibits distinct optical responses to ALT-catalyzed enzymatic reactions across varying concentrations. The high-quality factor of the microcavity obviously enhances its biosensing performance. Simulations reveal variations in the electric field behavior of WGM lasing as the liquid crystal microcavity transitions between radial and bipolar configurations. Further analysis was conducted using experimental WGM spectra and corresponding polarized optical microscopy images. Experimental results demonstrate a strong linear correlation between ALT concentration and reaction time within the range of 0 to 240 U/l. This biosensor exhibits a sensitivity of 0.67 s/(U/l), indicating its potential as a promising approach for early liver injury assays. In addition to in vitro verification, in vivo validation using mouse serum samples further confirms its practical applicability, yielding results consistent with those tested by using commercial assay kits. This method offers a simple, cost-effective, and efficient detection of ALT, underscoring the potential of liquid crystal microcavities for biosensing in liver injury monitoring.

Schwann cells (SCs) are indispensable for peripheral nerve regeneration, yet the mechanisms enabling their metabolic adaptation to meet the energetic demands of axonal repair remain elusive. Here, we identify N-methyl-D-aspartate (NMDA) receptors as central regulators of SC metabolic plasticity. In a mouse model of acute motor axonal neuropathy, nerve injury led to a marked decrease in NMDA receptor expression on SC. Functional studies revealed that NMDA receptors mediate calcium influx to drive glycolysis and oxidative phosphorylation via the phosphoinositide 3-kinase/protein kinase B/mammalian target of rapamycin and hypoxia-inducible factor-1α/c-Myc pathways, ensuring adenosine triphosphate production for axonal repair. Simultaneously, NMDA receptors orchestrate ataxia telangiectasia-mutated and Rad3-related protein–autophagy related 13-dependent mitophagy to clear reactive oxygen species-damaged mitochondria, maintaining metabolic efficiency during energy stress. Targeted metabolomics, Seahorse flux, and molecular pathological analysis revealed NMDA receptor-dependent remodeling of glucose metabolism, tricarboxylic acid cycle, nucleotide synthesis, and mitochondrial ultrastructure in SC. NMDA receptor deficiency disrupts energy metabolism and impairs axonal survival following sciatic nerve injury, resulting in aggravated neurological deficits and hindered nerve regeneration. Crucially, NMDA receptor activation rescued axonal integrity and motor function in mice with acute motor axonal neuropathy, underscoring their therapeutic potential. Our findings establish NMDA receptors as dual regulators of SC energy metabolism and mitochondrial quality control, providing a novel strategy to enhance glia-axonal metabolic coupling in peripheral neuropathies.

While parity transformation represents a fundamental symmetry operation in physics, its implications remain underexplored in metamaterial science. Here, we introduce a framework leveraging parity transformation to construct parity-inverted counterparts of arbitrary 3-dimensional meta-atoms, enabling the creation of parity-engineered metamaterial slabs. We demonstrate that the synergy between reciprocity and parity transformation, distinct from mirror operation, guarantees undistorted wave transmission across exceptional bandwidths, independent of structural configuration or meta-atom design specifics. Furthermore, these metamaterials exhibit dynamic acoustic mimicry capability, enabling adaptive blending of reflected signatures into surrounding environments while preserving transmitted wavefront integrity. Validated through numerical simulations and experimental prototypes, this breakthrough offers transformative potential for acoustic camouflage applications, particularly for sonar systems. Our findings reveal fundamental implications of parity transformation in artificial materials, establishing parity engineering as a paradigm for designing ultrabroadband functional materials with unprecedented operational versatility.

Glioblastoma (GBM), the most prevalent and lethal primary brain malignancy in adults, currently lacks treatment effective options. Repurposing existing pharmaceutical agents as novel therapeutic modalities represents a viable strategy for efficiently utilizing resources. Here, we demonstrated that Isovalerylspiramycin I (ISP-I), the active component of a novel macrolide antibiotic, exerts a synergistic effect with temozolomide (TMZ) to enhance anti-GBM efficacy. ISP-I potently induced cytotoxicity and apoptosis through the induction of DNA double-strand breaks. The synergistic activity (combination index < 1) was confirmed for ISP-I in combination with TMZ against GBM. Additionally, ISP-I was found to induce immunogenic cell death, as evidenced by increased adenosine triphosphate release and calreticulin exposure. In murine models, ISP-I increased tumor-infiltrating CD8⁺ T cells, enhanced effector subsets, and reduced exhausted subsets. Mechanistically, ISP-I targeted the Frizzled-5 (FZD5)/Wnt/β-catenin signaling pathway, resulting in suppression of GSK-3β phosphorylation. This event subsequently increased β-catenin phosphorylation, reducing its translocation into the nucleus. Consequently, the binding of transcription factors (T-cell factor 1/lymphoid enhancer factor 1) to promoters of CD274 and O⁶-methylguanine-DNA methyltransferase (MGMT) was impeded, thereby enhancing GBM cell susceptibility to TMZ. These findings elucidate the mechanisms underlying ISP-I’s therapeutic efficacy in GBM and provide essential evidence for its clinical translation and combinatorial therapeutic strategies.

This perspective critically examines the paradigm-shifting findings regarding cellular senescence’s dual role in tissue biology, particularly focusing on its unexpected regenerative potential in hair growth. While cellular senescence has traditionally been viewed as a detrimental process associated with aging and tissue dysfunction, research has revealed its surprising beneficial effects on tissue regeneration. We analyze the groundbreaking discovery that senescent melanocytes can stimulate hair follicle stem cells through the osteopontin–CD44 signaling pathway, challenging the conventional understanding of senescence. This perspective also evaluates the implications of this finding for both basic research and therapeutic applications, suggesting that cellular senescence represents a complex, context-dependent phenomenon rather than a uniformly detrimental process. We discuss how this new perspective necessitates a more nuanced approach to senescence-targeted therapies and opens novel therapeutic possibilities for hair loss treatment. This analysis underscores the importance of understanding senescent cell heterogeneity and their diverse functions in tissue homeostasis, which could lead to more precise therapeutic strategies in regenerative medicine.

As the Internet of Things (IoT) continues to evolve, a growing number of wireless sensors have been integrated into daily life, posing new challenges to energy supply and communication. Point-to-point dynamic wireless power transfer and communication, enabled by user-based positioning and tracking services, hold great potential in the IoT. Here, we propose a speech-controlled reconfigurable intelligent metasurface (RIS) that translates natural-language commands into dynamically shaped electromagnetic beams by combining speech interaction, low-power RIS control, and a template matching algorithm, supporting real-time data communication and wireless power transfer for both static and moving targets. Unlike conventional RISs that rely on pre-defined control and external processing units, our approach provides the metasurface with visual and linguistic perception capabilities, enabling a paradigm shift from passive reconfiguration to active multimodal intelligence. The experimental results confirm the effectiveness of the speech-controlled RIS, while the measured results demonstrate that the RIS can provide a stable dc output that exceeds 4.61 V on dynamic targets. By enabling intuitive human–device interaction and effectively meeting the power supply requirements of small sensors, the proposed concept demonstrates strong application potential in IoT scenarios.

Growth differentiation factor 15 (GDF15), a TGF-β superfamily member and stress-responsive cytokine, plays a critical role in metabolism and regulation of inflammation. This review summarizes the expression, distribution, structure, processing, and secretion of GDF15. We also discuss multilayered regulatory networks governing GDF15 expression, including ATF4/CHOP, AMPK, EGR1, EZH2, PPARγ, NRF2, ERRγ, and p53, as well as posttranscriptional regulator CNOT6L. The GFRAL receptor is central to its function, mediating the anorexigenic and metabolic effects of GDF15. This review synthesizes evidence linking GDF15 to obesity, diabetes, cardiovascular diseases, metabolic liver disorders, cachexia, sarcopenia, and aging while exploring its interactions with key metabolic factors including FGF21, GLP-1, leptin, and glucocorticoids. Lifestyle interventions such as ketogenic, high-fat diets, and exercise modulate GDF15 levels, underscoring its role in pan-metabolic health. Pharmacologically, various agents—including anti-hyperglycemic agents and natural compounds—induce GDF15 expression, implicating their therapeutic potential in cardiometabolic diseases. We comprehensively evaluate current advances in GDF15-targeted drug development, including monoclonal antibodies, fusion proteins, and small-molecule drugs, to provide a scientific foundation for innovative therapies. Finally, we outline unresolved issues in GDF15 biology and therapeutics, such as the exploration of peripheral receptors, contradictory findings in studies of cardiometabolic diseases, and the persistent challenges in developing GDF15-targeted therapeutics.

During the designed service life, road infrastructures will bear repeated loading conditions from vehicle weights and environmental conditions, resulting in the inevitable occurrence of road distresses including cracks, potholes, etc. The traditional inspection methods by transportation engineers are normally costly and labor-intensive. In recent years, artificial intelligence (AI)-based road distress detection methods have been widely used as convenient and automated approaches, while the AI-based methods heavily depend on a large amount of high-quality images, limiting the real engineering applications. To address the issues, this study introduces RoadDiffBox, a novel framework employing controlled image generation and semi-supervised learning. The framework addresses dataset imbalances through class control and accelerates image generation by utilizing the denoising diffusion implicit model’s reverse process sampling method, while employing knowledge distillation techniques optimized for resource-constrained mobile devices. It generates diverse and high-quality road distress images with automatic bounding box annotations, substantially reducing manual labeling requirements. Test results show that RoadDiffBox demonstrates strong generalizability across geographic regions (Germany, China, and India) and shows cross-domain potential in medical imaging applications. Performance evaluations demonstrate RoadDiffBox’s effectiveness, with classification models achieving an F1-score of 0.95 and detection models reaching a mean average precision (mAP@50) of 0.95 and an F1-score of 0.91 in controlled settings, while maintaining robust performance (an F1-score of 0.86 and a mAP@50 of 0.91) during on-site testing in real-world conditions. On server-class hardware, the model achieves generation times as low as 0.18 s per image. It is discovered that RoadDiffBox can serve as a scalable and efficient solution for real-time road maintenance with limited datasets.

Afterglow imaging offers exceptional signal-to-background ratios (SBRs) by circumventing real-time excitation and autofluorescence, yet conventional systems rely on visible-light excitation, limiting tissue penetration and signal intensity. Here, we report near-infrared-excitable organic afterglow nanoparticles (NOANPs) that leverage singlet oxygen (¹O₂)-mediated energy transfer to achieve prolonged, high-intensity emission with minimal photobleaching. The nanoparticles integrate a near-infrared-photoactive sensitizer (NAM-0), which generates abundant ¹O₂ under 808-nm laser excitation, and a triplenet-anthracene derivative (TD) as the afterglow substrate, which converts ¹O₂ into sustained luminescence. Co-encapsulation via one-step nanocoprecipitation ensures proximity between NAM-0 and TD, enabling efficient energy transfer and yielding exceptional afterglow brightness (>10⁹ photons/s) at ultralow concentrations (10 μg/ml). NOANPs enable deep-tissue imaging (up to 3.0 cm ex vivo) by synergizing the superior penetration of near-infrared light with organic afterglow chemistry. The nanoparticles uniquely support three imaging modes: fluorescence, white light-activated afterglow, and near-infrared-triggered afterglow, which were validated in orthotopic murine models of pancreatic cancer and glioma. By synergizing near-infrared excitation with organic afterglow chemistry, this work overcomes longstanding limitations in penetration depth of excitation light, offering a versatile tool for precision imaging.

The lower limb motion capture technology has garnered significant attention as a pivotal enabler in extended reality, sports science, film production, and medical rehabilitation. However, existing mature systems face critical challenges, including restricted operational environments, interference with natural activities, and cumbersome wearability. Here, a flexible insole pressure sensor array with an ultra-wide sensing range is developed using dip coating, laser cutting, and hot pressing, enabling lower limb motion capture. The developed fabric-based flexible pressure sensor exhibited an ultra-wide pressure range (3,770.9 kPa), high sensitivity (2.68 kPa⁻¹), rapid response, recovery times (17.2 ms/3.5 ms), and high work life (>4 million loading/unloading cycles). The insole-shaped flexible pressure sensor array accurately measures pressure in different postures, achieving 95.5% classification accuracy across 10 dynamic and static poses. More importantly, the system achieved a joint position prediction accuracy of 7.8 pixels ~(3.6 cm) in lower limb pose estimation. This high-precision lower limb motion capture system represents an ideal terminal for future extended reality applications, offering seamless integration, comfortable use, easily wearable design, and broad accessibility.