Chemotherapy-induced gastrointestinal toxicity, particularly intestinal barrier disruption and diarrhea, is a major dose-limiting adverse effect with unclear mechanisms. Here, we identify magnesium isoglycyrrhizinate (MIG) as a novel therapeutic agent that ameliorates 5-fluorouracil (5-FU)- and irinotecan-induced intestinal injury by enhancing epithelial barrier integrity. Using MIG as a molecular probe, we revealed a pathogenic mechanism underlying chemotherapy-induced barrier damage. Integrated chemoproteomics (limited proteolysis–mass spectrometry and thermal proteome profiling) analyses revealed direct binding of MIG to the RNA helicase DDX5 (DEAD-box helicase 5), whose expression is markedly increased upon 5-FU-induced injury. Mechanistically, DDX5 destabilizes the G-quadruplex (G4) structure in the CTNNB1 (β-catenin) 5′ untranslated region, suppressing β-catenin production and compromising barrier function. Crucially, MIG acts as a novel DDX5 inhibitor that blocks G4 unwinding, thereby restoring β-catenin expression and barrier integrity in a dose-dependent manner. In vivo, MIG outperforms the canonical DDX5 inhibitor supinoxin in mitigating intestinal damage. Taken together, the results of our study not only establish MIG as a promising therapeutic candidate but also delineate the DDX5/CTNNB1 axis as a targetable pathway for treating chemotherapy-induced barrier dysfunction.

Biomolecular self-assembly presents a convenient and promising approach for fabricating functional nanomaterials. The inherent structural and functional diversity of biomolecules facilitates the creation of a wide spectrum of biological nanomaterials through this intricate process. These versatile materials have demonstrated extensive utility in multidisciplinary domains, encompassing materials science, biomedical engineering, tissue engineering, nanotechnology, and analytical science. This review focuses on self-assembled biomolecular materials for energy harvesting applications, organized into 4 main aspects. Firstly, we introduce the self-assembly methods and key factors involved in biomolecular self-assembly mechanism, including hydrogen bonding, covalent bonds, π–π interactions, electrostatic interactions, and hydrophobic/hydrophilic interactions. Secondly, we discussed the structural characteristics of different types of self-assembled biomolecular materials and introduced their mechanical, piezoelectric, ferroelectric, semiconductor, and biocompatibility properties. Next, the application of self-assembled biomolecular materials in energy harvesting was studied, mainly focusing on piezoelectric nanogenerators, triboelectric nanogenerators, water-enabled electricity generation, and other types of energy harvesting devices. Finally, we emphasized challenges in the area encompassing not only the design of the materials and assembly regulation but also probable efforts in improving performance and application fields. We believe that this review will elucidate diverse functions of self-assembled biomaterials, paving the way for the innovative design of biomaterials not only for energy harvesting systems but also for biomaterial-based microelectronic devices.

The integration of wearable technology and smart textiles has substantially advanced the development of radio-frequency (RF) electronics embedded in textile substrates, opening new opportunities across health monitoring, environmental sensing, and wireless communication. Despite their established performance, conventional rigid RF systems face inherent limitations in conformability and seamless integration within wearable platforms. This review comprehensively summarizes recent progress in textile-based RF active devices, encompassing reconfigurable antennas, tunable metasurfaces, and multifunctional RF systems. We emphasize the transition from isolated components to fully integrated, intelligent platforms capable of energy harvesting, low-power communication, and distributed sensing while proposing solution strategies and future development directions for enriched and systematic performance. Critical technical challenges such as high-precision fabrication, tunable RF response, and architecture design for complex systems are thoroughly discussed. Ultimately, this review outlines promising pathways toward autonomous, adaptive, and intelligently networked textile RF systems, highlighting the convergence of wireless functionality and system-level co-design for the next generation of wearable electronics.

Clear cell renal cell carcinoma (ccRCC) is a lethal urologic malignancy with limited biomarkers for prognosis and therapeutic stratification. Interferon-induced protein 44 (IFI44) has been implicated in immune regulation, but its role in ccRCC is unclear. To address this gap, we comprehensively investigated the clinical significance, biological roles, and molecular mechanisms of IFI44 in ccRCC pathogenesis. Using integrative transcriptomic analysis of the Gene Expression Omnibus and the Cancer Genome Atlas-Kidney Clear Cell Carcinoma cohorts, we first identified IFI44 as a key candidate gene. Bioinformatic enrichment analyses and immune infiltration profiling were conducted to investigate potential mechanisms. In parallel, we established ccRCC cell lines with stable IFI44 knockdown and evaluated phenotypic changes using Cell Counting Kit-8, Transwell assays, wound-healing assays, and flow cytometry, thereby examining cell proliferation, apoptosis, migration, and invasion. We observed that IFI44 was markedly elevated in ccRCC tissues, and its increased level was closely associated with advanced tumor stage and poorer patient survival. Enrichment analyses indicated that IFI44 participates in pathways related to viral response, RNA splicing, and mRNA processing. Moreover, elevated IFI44 expression may be associated with an immunosuppressive tumor microenvironment, as suggested by increased infiltration of effector T cells and M1 macrophages, along with decreased infiltration of activated dendritic cells. In mechanistic studies, IFI44 knockdown markedly suppressed cell proliferation, triggered apoptosis, and reduced both migratory and invasive capacities, whereas PRDX1 overexpression rescued these phenotypes and PRDX1 was shown to interact with IFI44. In summary, the data show that IFI44 acts as an oncogene in ccRCC, promoting tumor progression through its interaction with PRDX1 while also shaping an immunosuppressive microenvironment, and suggest that IFI44 is a promising biomarker of prognosis and candidate therapeutic target for ccRCC.

Hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR⁺/HER2⁻) early breast cancer (EBC) patients face long-term recurrence risk despite standard treatment. Current prognostic tools relying on clinicopathological factors or multigene assays have limited accuracy or accessibility. In this study, we developed a multimodal recurrence risk prediction (MRRP) model integrating routinely available clinical data, including whole-slide images (WISs), ultrasound (US) imaging and diagnostic reports, and structured clinical parameters. The MRRP model employs a hierarchical transformer-based fusion framework with innovative intra- and intermodality cross-attention mechanisms to dynamically integrate diverse feature representations. Using a well-curated cohort of 768 HR⁺/HER2⁻ EBC patients with long-term follow-up, MRRP demonstrated superior prognostic performance (C-index = 0.840) compared to single-modality models, with robust time-dependent AUCs exceeding 0.85 at 3, 5, and 7 years. Ablation studies highlighted the central role of pathology features and the complementary value of US and clinical data. We further validated the optimal query selection strategies and evaluated different pretrained encoders, revealing complex modality interactions. To address real-world challenges of missing modality data, a learnable compensation mechanism was implemented, improving model robustness. Our study provides a clinically practical, AI-driven tool for precise risk stratification in HR⁺/HER2⁻ EBC patients, facilitating individualized treatment and surveillance decisions without reliance on costly multi-omics data.

The modulation of thermal radiation is essential for advanced photonic applications, offering a novel perspective for information carriers. However, current carriers are limited to a few discrete radiation states at isolated time points and cannot capture the entire dynamic process along the full temporal axis, resulting in substantial information loss. Here, we propose and experimentally validate a novel spatiotemporal modulation strategy that dynamically tailors emissivity across the entire temporal domain, where gentle and uniform modulation of atomic configurations enables the creation of entirely novel permittivity libraries. To realize flexible thermal radiation tailoring, we utilize an Ag–In₃SbTe₂ (IST) interface atomic rearrangement metamaterial (ARM). As a dynamic optical control platform, ARM exhibits continuous spectral modulation with remarkably high amplitudes (64.74% in the 3- to 5-μm band and 73.94% in the 8- to 14-μm band), together with rich variations across the temporal domain to realize tailored infrared emissivity and infrared information encryption. This work establishes a unified framework for continuous, atomic-scale spatiotemporal control of thermal radiation, opening new pathways for spectral modulation and photonic information regulation in the time domain.

Major psychiatric disorders are characterized by substantial clinical heterogeneity and high comorbidity, yet their underlying biological mechanisms are not fully uncovered. The microbiota–gut–brain axis (MGBA) offers a cross-system perspective for elucidating the pathophysiology of major psychiatric disorders. The Brain–Gut Health Initiative (BIGHI) was established as the first prospective longitudinal cohort in China dedicated to investigating major psychiatric disorders guided by the framework of MGBA, enabling large-scale, transdiagnostic, and longitudinal analyses of brain–gut interactions. To date, the BIGHI has enrolled over 1,200 participants with schizophrenia, major depressive disorder, bipolar disorder, and healthy controls, with multidimensional data collected including clinical symptomatology, neurocognitive performance, electroencephalography, magnetic resonance imaging, peripheral blood biomarkers, and gut microbiome profiles. The studies within the BIGHI reveal (a) brain–gut physiological alterations in psychiatric disorders; (b) systematic relationships among brain function, peripheral physiological markers, and gut microbiome; and (c) brain–gut network patterns with marked interindividual heterogeneity. In future studies, we will expand the BIGHI into a collaborative network and promote data harmonization and interdisciplinary collaboration to advance computational psychiatry as well as its clinical translation.

Understanding the variation of functional architecture across individuals and populations is fundamental to advancing our knowledge of human health and behavior. Yet, while functional organization differences related to ethnicity/race are consistently reported, their underlying mechanisms remain poorly understood. Here, we apply precision individualized functional mapping to systematically investigate ethnicity/race-related differences between African American (AA) and white American (WA) cohorts in the brain’s intrinsic organization and their associations with lifestyle and transcriptional signatures. We show that variations in network topography and functional connectivity across these ethnic/racial groups follow a hierarchical sensorimotor–association axis and are constrained by brain morphology. Importantly, we identify lifestyle factors—particularly education and substance use—that significantly mediate these associations between ethnicity/race and functional connectivity. Leveraging human brain gene expression data, we further demonstrate that cortical transcriptional patterns are spatially aligned with ethnicity/race-related variability in functional connectivity. Gene ontology analyses of associated genes reveal significant enrichment in biological processes such as synaptic signaling and neuronal system development. Together, these findings uncover a multi-layered framework linking ethnicity/race-related differences in brain function to structural constraints, lifestyle influences, and molecular signatures, and point to the need for a more comprehensive and equitable understanding of human brain diversity.

Conventional second near-infrared (NIR-II; 1,000 to 1,700 nm) fluorescence imaging cannot simultaneously achieve a high signal-to-noise ratio and motion-artifact-free capture of rapid physiological dynamics. Here, we introduce NIR-II compressive fluorescence imaging (COFI), a high-speed, pixel-super-resolved compressive imaging technique that encodes dynamics into single frames using a high-speed spatial light modulator and a low-frame-rate NIR-II camera. A hybrid reconstruction algorithm integrating a denoising convolutional neural network with an enhanced super-resolution generative adversarial network subsequently restores high-fidelity videos. The system achieves 3.3 kiloframes per second with a space–bandwidth–time product of 4.22 × 10⁸ pixels/s without compromising intrinsic sensitivity. Compared to conventional short-exposure imaging with the same duration of 500 μs, NIR-II COFI achieves a 36% improvement in signal-to-noise ratio. Furthermore, using bright 1,525-nm nanoparticle probes, we demonstrate multicomponent phosphorescence lifetime imaging, high-speed motion tracking, and real-time visualization of murine intestinal peristalsis in both awake and anesthetized states. This work facilitates deep-tissue, high-speed in vivo imaging of fast biological processes.

Photoresponsive materials offer unique opportunities for advanced technologies by enabling their precise, noncontact remote control and converting light energy into well-defined changes in structure and function. Among them, multigated photochromic systems have emerged as a transformative frontier, overcoming constraints of conventional single-stimulus systems. Here, “gated” refers to the deliberate use of an additional external input (e.g., pH, voltage, mechanical force, or temperature) to regulate or modulate the photoisomerization process. Such multi-input control enables sophisticated, programmable behaviors, including Boolean logic operations, environmental adaptation, and high-security information encryption, thereby marked expanding their application potential. In this review, we present a comprehensive and systematic analysis of multigated photochromic materials. We first introduce a unified design strategy and classification framework based on gating mechanisms. The core sections critically evaluate recent advances in proton-, electro-, mechano-, thermal-, and wavelength-gated systems, with particular emphasis on the underlying principles that connect molecular design to tailored performance. Furthermore, we discuss emerging and unconventional gating modes, including ion-, liquid-, gas-, and intensity-gated photochromism. Finally, we present a comparative analysis of all gating modalities, identify persistent conceptual and practical challenges, and outline future directions toward intelligent, adaptive material platforms. This review aims to establish a foundational framework that guides the rational design of next-generation multigated photochromic materials for applications in sensing, anticounterfeiting, information technology, and adaptive devices.

Momentum conservation in the nucleon is examined in terms of continuous flow of the momentum current density (or, in short, momentum flow), which receives contributions from both kinetic motion and interacting forces involving quarks and gluons. While quarks conduct momentum flow through their kinetic motion and the gluon scalar (anomaly) contributes via pure interactions, the gluon stress tensor has both effects. The quarks momentum flow encodes the information of the color-Lorentz force density on them, and the momentum conservation allows to trace its origin to the gluon tensor and anomaly (a “negative pressure” potential). From the state-of-the-art lattice calculations and experimental fits on the form factors of the quantum chromodynamics energy-momentum tensor, we exhibit pictures of the momentum flow and the color-Lorentz forces on the quarks in the nucleon. In particular, the anomaly contributes a critical attractive force with a strength similar to that of a heavy-quark confinement potential.

Aqueous ammonium-ion (NH₄⁺) batteries/capacitors, recognized for inherent high safety and fast diffusion kinetics, are a promising alternative for sustainable energy storage. However, the development of ammonium-ion energy storage devices has been hindered by the poor compatibility between the distinctive solvation structure of NH₄⁺ ions and conventional organic electrode materials, especially under low-temperature conditions. Here, a redox-active conjugated polymer with self-selective coordination mechanism is designed for achieving high-rate and low-temperature performance. The electron delocalization induced by the conjugated backbone facilitates rapid electronic transport in electrodes, delivering an ultrahigh-rate capacity of 107 mAh g⁻¹ at 20 A g⁻¹ under 25 °C and stable cycling performance with 99% capacity retention under −50 °C. Theoretical calculations and experimental investigations reveal that the inherent structural self-selectivity renders symmetrically arranged carbonyl groups as active binding sites for NH₄⁺ storage, leading to a reversible 4-electron coordination process. Hence, the assembled all-organic hybrid ammonium-ion capacitor enables a long cycle life for over 3,000 cycles at −50 °C, which surpasses the lowest operating temperature reported for ammonium-ion devices, thus propelling the advancement of ammonium-ion energy storage technologies at low temperatures.

Zirconia (ZrO₂) has become a promising alternative to titanium (Ti) for bone implants due to its excellent biocompatibility. Despite this, the osseointegration of ZrO₂ remains lower than that of Ti implants. However, the underlying biological mechanisms, particularly the osteoimmune response, remain not fully elucidated. Herein, we employed single-cell RNA sequencing to profile the immune-inflammatory niches of ZrO₂ and Ti-based implants, to elucidate mechanisms that could guide the osteogenic functionalization of ZrO₂ implants. The analysis provides a high-resolution atlas of immune–stromal cell dynamics at the bone–implant interface, identifying distinct cellular subsets and ligand–receptor axes activated by each material. Ti implants preferentially enriched stem-cell niches and up-regulated collagen organization through fibroblast-specific collagen type I alpha 1 chain/syndecan 1 signaling, promoting regenerative extracellular matrix remodeling and early osteogenic microenvironment. In contrast, ZrO₂ implants triggered lymphoid-dominated responses, characterized by collagen type VI alpha 2 chain/cluster of differentiation 44-mediated macrophage activation, and pro-inflammatory pathway activation. In vivo validation via bulk RNA sequencing confirmed these material-specific immunomodulatory programs, with Ti favoring osteogenic microenvironments and ZrO₂ inducing fibro-inflammatory niches. These findings provide mechanistic targets for designing immunomodulatory biointerfaces to enhance the osseointegration of ZrO₂ implants.

Advances in 3-dimensional (3D) cardiac constructs have provided powerful preclinical models for investigating the pathological mechanisms underlying human cardiovascular diseases and facilitating drug discovery. In this review, we focused on recent advancements in 3D cardiac constructs technology and explored its potential applications in drug development. We summarized the main types of disease models built on 3D cardiac constructs, the key parameters used for assessing pathology and drug efficacy, and their role in drug discovery. We also discussed the application of novel biomaterials in 3D cardiac constructs, the latest research progress in 3D cardiac constructs-based drug screening, and the transformative potential of artificial intelligence-assisted research on 3D cardiac constructs. Finally, we addressed the existing technical limitations and outline future directions for the development of 3D cardiac constructs.

Enhancing the efficiency of photocatalytic H₂ evolution and H₂O₂ production through heterojunction engineering is crucial for addressing energy sustainability and environmental challenges. In this context, constructing S-scheme heterojunctions has emerged as a promising strategy. Here, we report an inorganic/organic S-scheme Bi₂WO₆/zinc(II) tetrakis(4-carboxy-phenyl)porphyrin (BWO/ZTP) heterojunction with a strong built-in electric field, constructed via an interface induction strategy. The optimal BWO/ZTP-1 achieves exceptional H₂ evolution and H₂O₂ production activity, achieving 2,343.3 and 236.1 μmol·g⁻¹·h⁻¹. These represent remarkable enhancements of 14.9 and 3.44 times for H₂ and 2.33 and 2.27 times for H₂O₂ over pristine BWO and Zn-TCPP. By using femtosecond transient absorption spectroscopy, Kelvin probe force microscopy, in situ x-ray photoelectron spectroscopy and density functional theory, we demonstrate that built-in electric field is pivotal for the exceptional performance, which leads to the proposal of a photocatalytic mechanism. This work provided feasible insights and references for the design of novel and superior inorganic/organic S-scheme heterojunction photocatalysts with tight contact and synergistic interaction for photocatalytic applications.

The sustained growth in global road mileage, combined with rising public expectations for improved travel safety and comfort, has created an urgent demand for sensing technologies in road systems. Nevertheless, conventional monitoring methods are increasingly insufficient for modern intelligent roads (IRs), which represent next-generation infrastructure requiring efficient and sustainable sensing solutions. Existing sensor systems that rely on traditional power sources or cabled power supply suffer from inherent limitations, including short operational lifespans and high maintenance costs. At the same time, current road micro-energy harvesting technologies struggle to meet the demands of large-scale distributed sensor networks in IR, underscoring the critical need for self-powered sensing solutions designed for IR. This review identifies the power supply bottleneck inherent in distributed sensor networks of IR, provides a critical comparison of potential solutions with a focus on micro-energy harvesting technologies, and offers a comprehensive review of the practical applications of self-powered sensors (mainly piezoelectric nanogenerators and triboelectric nanogenerators) within road systems. Furthermore, it proposes forward-looking recommendations and developmental prospects for the field, thereby offering theoretical support to advance the large-scale implementation of self-powered sensing in IR systems.

Soft robots and stretchable electronics, typically composed of stretchable elastomers and embedded conductive coils, have been widely investigated for applications in actuation, sensing, and communication. However, their fabrication still relies heavily on multistep and labor-intensive conventional methods. Here, we present a multimaterial 3-dimensional (3D) printing strategy based on direct ink writing technology, which enables the one-step fabrication of stretchable elastomers embedded with high-conductivity multilayer coils. This is achieved by alternately printing elastomer and nickel-particle-modified liquid metal (NLM) coil layers in a program-controlled sequence, with vertically printed NLM cones connecting adjacent NLM layers. With this strategy, we achieved one-step fabrication of a 4-layer-coil soft electromagnetic actuator (SEMA) and a self-sensing SEMA integrating sensing and driving modules, without the need for manual bonding or post-processing. We further built 3 functional devices to show the potential applications of this integrated 3D printing strategy: a sensor-integrated soft gripper capable of perceiving its own grasping state, a bio-inspired manta-like soft electromagnetic robot that achieves a swimming speed of 29 mm/s, and a SEMA integrated with a Hall sensor and a red light-emitting diode, which exhibits strong mechanical robustness. Overall, the integrated 3D printing strategy not only simplifies the fabrication but also enables the multifunctional and miniaturized design of soft robots and electronics.

Rapid infrastructure expansion in emerging economies is increasing construction-related carbon emissions. Using a probabilistic assessment of 52 planned bridges on Pakistan’s M-13 Motorway, the average carbon emission intensity (CEI) is 1,430 kg CO₂eq per square meter, 1.15 to 1.50 times higher per m² of deck area than international benchmarks. The raw material (extraction and production) phase dominates the footprint (94.4%), with reinforcement (48.9%) and concrete (39.4%) as the principal material contributors; both display high variability (coefficients of variation 67% to 130%), signaling substantial uncertainty. Evidence points to systemic inefficiencies, including conservative overdesign, reliance on foreign codes, and the absence of standardized local emission data. Targeted measures, structural optimization using digital tools, wider adoption of recycling and low-carbon mixes, and development of context-specific emission factor databases offer a scalable pathway to lower-carbon bridge infrastructure in Pakistan and comparable settings.

It is crucial to monitor the real-time and accurate status of an electric drive system and understand its interaction with driving behavior in order to meet the higher requirements for vehicle safety and reliability in the era of autonomous driving. Traditional wired sensors have limitations in system integration and energy autonomy. This study proposes a triboelectric nanogenerator (TENG) based on the centrifugal-force-enhanced contact mechanism, which can be directly integrated into the transmission shaft of electric vehicles to construct an intelligent self-powered monitoring system. This design effectively overcomes the bottleneck of unstable signals and insufficient durability of traditional rotating TENGs at high speeds by coupling centrifugal force and spring pre-tension and outputs stable and high signal-to-noise ratio sensing signals. On this basis, this study not only achieved high-precision real-time perception of the driving system speed but also further explored the rich information embedded in the centrifugal-force-enhanced contact TENG signal and extended it to the intelligent recognition of driving behavior and road conditions. Based on signal processing and the convolutional neural network and bidirectional long short-term memory model, the system has achieved fault diagnosis of key transmission component bearings in the transmission system with an accuracy rate of up to 96.1%. At the same time, the system can effectively recognize driving behaviors such as sudden acceleration and deceleration (recognition accuracy of 84%), as well as typical road conditions such as flat, slippery, and speed bumps (recognition accuracy of 89.9%), providing key information for automatic driving algorithm calibration and driving safety improvement. The self-powered embedded sensing technology developed in this study provides a new technological path for the efficient energy management and predictive maintenance system of intelligent connected vehicles and is a key sensing node for building future autonomous transportation systems.

Liver fibrosis shows limited treatment efficacy, driven by metabolic reprogramming and epigenetics, while the role of lactate-mediated lactylation in hepatic microenvironment remains unclear. Here, through integrative analysis of public databases and human cirrhotic liver tissues, we identified a pathogenic FSP1⁺ (fibroblast specific protein 1) macrophage subset as a key therapeutic target. We uncovered a novel FSP1–glycolysis–lactylation axis that drives fibrotic progression through metabolic–immune crosstalk. Expanded FSP1⁺ macrophage infiltration was observed in human cirrhotic liver tissues and myeloid-specific Fsp1 knockout markedly attenuates inflammation and fibrosis. Mechanistic investigations reveal that FSP1 physically interacts with pyruvate kinase M2 (PKM2) in macrophages, inhibiting its ubiquitin–proteasome degradation to stabilize the enzyme. This FSP1–PKM2 interaction enhances glycolytic flux and lactate production, which in turn promotes KAT2B-dependent lactylation of phosphoglycerate kinase 1 (PGK1) at lysine 353 (K353). The posttranslational modification creates a positive feedback loop by concurrently activating PGK1 and pyruvate dehydrogenase kinase 1, which blocks mitochondrial pyruvate metabolism, thereby amplifying glycolysis and PGK1 lactylation. Notably, we developed a cell-penetrating peptide targeting PGK1-K353 lactylation that effectively attenuates the progression of liver fibrosis. Our findings establish lactate-mediated lactylation of PGK1 as a critical node in fibrotic metabolism and reveal a previously unrecognized FSP1–glycolysis axis that sustains the pro-fibrotic microenvironment. Targeting PGK1-K353 lactylation represents a promising therapeutic strategy for chronic liver diseases.

Osteoporosis is a systemic skeletal disorder characterized by reduced bone mass, impaired microarchitecture, and increased fracture risk, primarily resulting from dysregulated bone remodeling. Increasing evidence highlights a close interaction between bone metabolism and the gut microbiota. Alterations in bone mineral density can influence gut microbial composition. Conversely, microbial dysbiosis disrupts bone homeostasis through multiple pathways, including microbial metabolites, immune regulation, and neuroendocrine signaling. Short-chain fatty acids suppress osteoclast differentiation and enhance intestinal calcium absorption, while gut dysbiosis promotes bone loss by impairing intestinal barrier integrity and increasing proinflammatory cytokines such as tumor necrosis factor-α and interleukin-6. The gut–brain–bone axis represents an important regulatory network linking the central nervous system, gut-derived signals, and skeletal remodeling. Chronic stress and neurodegenerative conditions activate the hypothalamic–pituitary–adrenal axis and bone-derived extracellular vesicle signaling, thereby favoring bone resorption. Estrogen deficiency further disrupts the receptor activator of nuclear factor κΒ ligand/osteoprotegerin signaling pathway and alters gut microbial composition, contributing to postmenopausal bone loss. Therapeutic strategies targeting this axis, including probiotics, prebiotics, fecal microbiota transplantation, dietary fiber supplementation, and pharmacological or natural compounds, show potential in restoring microbial balance and improving bone metabolism. Future studies integrating multiomics approaches and well-designed clinical trials are needed to clarify microbiome–bone interactions and support the development of targeted interventions for osteoporosis.

As silicon anodes approach their theoretical capacity limits in lithium-ion batteries, the exploration of materials with even higher energy storage potential becomes imperative. Here, we demonstrate that silicon–carbon composites can deliver ultrahigh capacities exceeding 6,500 mAh g⁻¹, benefiting from the abundant internal defects within the composite. At a charge–discharge rate of 0.1 C (0.42 A g⁻¹), the initial discharge specific capacity reaches 6,694.21 mAh g⁻¹, with a Coulombic efficiency (CE) of 74.71%, markedly exceeding the theoretical capacity limit of silicon. By further optimizing lithium battery electrolyte, the initial discharge specific capacity is 5,294.88 mAh g⁻¹ and CE is increased to 90.96%. Moreover, an artificial intelligence-assisted framework combining a multilayer perceptron with a constrained genetic algorithm predicts a theoretical maximum initial discharge capacity of 7,789.55 mAh g⁻¹. These results provide compelling evidence that silicon–carbon composites hold great promise for substantially enhancing the energy density of next-generation lithium-ion batteries.

Non-small-cell lung cancer (NSCLC) with brain metastases poses formidable therapeutic challenges due to acquired resistance and the inherent pharmacokinetic defects of traditional delivery. We developed an innovative lipoic acid-based self-assembled nanodrug (dabrafenib, trametinib, and lipoic acid self-assembly [DTL]) system, whose rational design was guided by a novel machine learning platform to overcome high-cost, empirical screening bottlenecks. Multifunctional lipoic acid, serving as a universal self-assembling molecule, enabled DTL’s robust assembly and enhanced penetration across mucosal and solid tumor barriers via its unique thiol-mediated exchange mechanism while simultaneously exerting distinct antitumor efficacy. Intranasal administration of DTL achieved efficient dual-targeted delivery to both primary NSCLC and established intracranial metastases. Furthermore, compared to conventional targeted combination therapies, DTL induced diverse, multimodal tumor cell death (apoptosis, pyroptosis, and ferroptosis) and profoundly remodeled the immune microenvironment. In vivo, DTL markedly inhibited tumor growth with reduced toxicity, offering a clinically translatable strategy for advanced NSCLC.

Large momentum effective theory (LaMET) provides a general framework for computing the multi-dimensional partonic structure of the proton from first principles using lattice quantum chromodynamics (QCD). In this effective field theory approach, LaMET predicts parton distributions through a power expansion and perturbative matching of a class of Euclidean observables—quasi-distributions—evaluated at large proton momenta. Recent advances in lattice renormalization, such as the hybrid scheme with leading renormalon resummation, together with improved matching kernel that incorporates higher-loop corrections and resummations, have enhanced both the perturbative and power accuracy of LaMET, enabling a reliable quantification of theoretical uncertainties. Moreover, the Coulomb-gauge correlator approach further simplifies lattice analyses and improves the precision of transverse-momentum-dependent structures, particularly in the non-perturbative region. State-of-the-art LaMET calculations have already yielded certain parton observables with important phenomenological impact. In addition, the recently proposed kinematically enhanced lattice interpolation operators promise access to unprecedented proton momenta with greatly improved signal-to-noise ratios, which will extend the range of LaMET prediction and further suppress the power corrections. The remaining challenges, such as controlling excited-state contamination in lattice matrix elements and extracting gluonic distributions, are expected to benefit from emerging lattice techniques for ground-state isolation and noise reduction. Thus, lattice QCD studies of parton physics have entered an exciting stage of precision control and systematic improvement, which will have a broader impact for nuclear and particle experiments.

Vascular scaffolds are fundamental devices in treating vascular occlusions, aneurysms, and hemodialysis access. However, their long-term efficacy is often compromised by 2 major pathophysiological responses: acute thrombosis and intimal hyperplasia, underscoring the need for effective antithrombotic treatment and intensive surveillance. This review highlights the emerging approaches used to address such challenges in vascular scaffolds: surface biofunctionalization and intelligent monitoring systems. We first introduce the leading biodegradable elastic polymers for vascular scaffolds, followed by a comprehensive overview of surface biofunctionalization techniques for preventing thrombosis and promoting endothelialization. The review further explores the cutting-edge advances in integrating flexible bioelectronics with cardiovascular implants for intelligent real-time monitoring of hemodynamics, thrombosis, and restenosis. It concludes with a discussion of the remaining challenges and future perspectives, thereby promoting the development of more effective cardiovascular therapies and their clinical applications.

The tumor microenvironment is a central determinant of cancer progression, metastatic spread, and therapeutic resistance. Once considered passive scaffolds, stromal cells are now recognized as heterogeneous, active regulators of tumor behavior. Recent single-cell and spatial multiomics studies have resolved functionally distinct stromal subtypes, each defined by characteristic molecular programs and spatial niches, with specialized roles in extracellular matrix remodeling, immune evasion, and angiogenesis. This review synthesizes evidence for bidirectional stromal–tumor cross-talk in which cytokine networks (e.g., transforming growth factor-beta, interleukin-6, and C-X-C motif chemokine ligand 12/C-X-C chemokine receptor 4) coordinate epithelial–mesenchymal transition, stemness, chemotaxis, and vascular remodeling. Building on these insights, this review also argues for subtype-specific biomarkers and multimodal therapeutic strategies to overcome stromal-mediated resistance. Integrating stromal heterogeneity into precision-oncology workflows through standardized, lineage-resolved profiling and real-time biomarker guidance will be essential for diagnostic refinement and personalized treatment.

Polyamines are ancient metabolites that serve critical functions in maintaining epithelial integrity, regulating immune response, and supporting healthy aging. The gut microbiota actively synthesizes and converts polyamines, while host factors such as inflammation, barrier function, and nutritional status dynamically modulate this metabolic network. Disruption of this host–microbiota axis reduces polyamine availability, impairs barrier function, and exacerbates inflammation. In contrast, polyamines exert protective effects by promoting epithelial repair, modulating macrophage and T-cell responses, and enhancing autophagy-mediated tissue renewal and longevity. Recent advances in engineered probiotics, microbial small RNAs, and postbiotics further highlight the therapeutic potential of precisely modulating polyamine metabolism in clinical contexts such as inflammatory bowel disease, metabolic syndrome, and neurodegenerative conditions associated with aging.

Electroactive microbes are uniquely capable of aggressively corroding metals like stainless steel that were once thought immune to microbial attack. This activity has been attributed to microbial destruction of the protective chromium oxide passive film on the stainless steel surface that protects the underlying Fe⁰ from corrosive agents, allowing the microbes to establish direct electrical contact with the Fe⁰ and extract electrons to support anaerobic respiration. We show here that the electroactive microbe Geobacter sulfurreducens, despite its high corrosive activity, is unable to physically breach the passive film. Instead, it enables biologically mediated electron transfer across an intact chromium oxide-rich layer that remains sufficiently insulating to block abiotic proton reduction. These findings challenge the prevailing assumption that electroactive microbes must directly contact Fe⁰ for corrosion and provide new guidance for the design of corrosion-resistant metals.

Steroid-induced osteonecrosis of the femoral head (SONFH) is a rapidly progressing and disabling complication of long-term glucocorticoid therapy, lacking effective early-stage intervention mechanisms. Its early manifestation involves a fate shift in bone marrow mesenchymal stem cells (BMSCs) characterized by decreased osteogenic differentiation (OGD) and increased adipogenic differentiation (AGD), yet the upstream regulatory mechanisms remain unclear. Herein, we integrated AGD-related microRNA (miRNA) microarray data with exosomal miRNA sequencing data and identified miR-199a-3p as a crucial candidate driver of this lineage imbalance. Our results revealed the up-regulation of miR-199a-3p in SONFH tissues and in glucocorticoid-treated cellular models, and indicated that its overexpression suppresses the OGD of BMSCs while markedly promoting the AGD. Further integrating mRNA-sequencing profiling during AGD with target prediction, protein–protein interaction network analysis, and dual-luciferase reporter assays, we confirmed integrin β8 (ITGB8) as a direct target of miR-199a-3p, which is consistently decreased in SONFH tissues and during adipogenic induction. We further revealed that miR-199a-3p suppressed the OGD of BMSCs by repressing ITGB8 expression, thereby inactivating the focal adhesion kinase (FAK)–extracellular signal-regulated kinase (ERK)–runt-related transcription factor 2 (RUNX2) signaling cascade. Conversely, silencing miR-199a-3p restores ITGB8 levels, reactivates this pathway, and corrects the OGD/AGD bias. In vivo, local administration of antagomiR-199a-3p in a SONFH rat model markedly improved trabecular bone architecture, increased bone mass, and up-regulated RUNX2 expression. These findings reveal for the first time that the miR-199a-3p/ITGB8–FAK–ERK–RUNX2 axis represents an unrecognized pathogenic pathway in SONFH, and support the local suppression of miR-199a-3p as a translatable early intervention strategy.

Parity–time and anti-parity–time symmetries, originally formulated in the context of non-Hermitian quantum mechanics, have now been experimentally realized across diverse physical platforms, including photonic, wave-guiding, acoustic, and mechanical systems, as well as systems operating near exceptional points. While the active manipulation of these symmetries has been well explored in wave-based systems, their implementations in diffusive physics have long remained predominantly confined to static phases, where systems are locked in a fixed symmetric or symmetry-broken configuration due to their invariant structural parameters. Bridging this gap, recent work has introduced and verified the concept of temporal anti-parity–time symmetry, demonstrating that energy transport in diffusive media can be actively programmed in the time domain.

Lanthanide nanocrystals hold exceptional promise for electroluminescence applications due to their unique optical properties. However, their intrinsic insulating character and localized 4f orbitals severely restrict carrier injection, thereby hindering direct electrical excitation. In a recent study published in Nature, Tan and colleagues circumvented this fundamental bottleneck via molecular engineering of the nanocrystal surface. They developed a series of functionalized ligands (e.g., carbazole-phosphine oxide) to establish an electroactive interface, facilitating efficient transfer of electro-generated triplet excitons to lanthanide ions. Notably, a wide-ranging multicolor electroluminescence from lanthanide nanocrystals was achieved for the first time, exhibiting high power efficiency and external quantum efficiency. These findings provide new opportunities for electrically driven luminescence in lanthanide nanocrystals or other insulating systems.

As a fundamental imaging task, All-in-One Image Restoration (AiOIR) aims to achieve image restoration caused by multiple degradation patterns via a single model with unified parameters. However, existing methods typically rely on sample-wise supervision, which tends to entangle degradation features with image content. Furthermore, the inevitable distribution shift between training data (source domain) and real-world samples (target domain) weakens degradation awareness, severely limiting the generalization capability of models in real-world scenarios. To address this, a Unified Domain-Adaptive Image Restoration (UDAIR) computer vision model is proposed by achieving the transition from learning unstable local features to learning robust universal prototypes. To decouple degradation from content, a Cross-Sample Contrastive Learning mechanism is implemented by a codebook-based module. By contrasting samples with shared degradations but diverse content, the proposed model learns discrete embeddings as degradation prototypes. Furthermore, to actively bridge the distribution gap during inference, a correlation alignment-based test-time adaptation mechanism is designed to dynamically pull drifting target features toward their corresponding degradation cluster centers to effectively eliminate residual alignment discrepancies. Experimental results on 10 open-source datasets demonstrate that UDAIR achieves new state-of-the-art performance for the AiOIR task, in which each technical module contributes to the desired performance improvement. Most importantly, the feature cluster validates the degradation identification under multiple degradation patterns, and qualitative comparisons showcase robust generalization to real-world scenarios.

Wearable haptic systems enable natural and intuitive human–machine interaction, with growing relevance in immersive entertainment, physical rehabilitation, social communication, and personalized therapy. By delivering real-time tactile feedback via electrical, thermal, and mechanical stimulation, individually or in combination, these systems enhance user engagement and enable more dynamic and responsive digital interactions. This review presents a structured overview of the design principles, actuation mechanisms, and material architectures that define current wearable haptic technologies. We evaluate the strengths and limitations of major feedback modalities and highlight how system-level designs are tailored to specific use cases, from immersive gaming and training simulations to postoperative rehabilitation and emotion-sensitive communication. We also identify key challenges in miniaturization, multimodal integration, user comfort, and long-term wearability. The insights presented here aim to inform the development of next-generation haptic interfaces that are adaptive, scalable, and deployable in real-world applications.

In solid tumors, the immunosuppressive tumor microenvironment and antigenic heterogeneity pose important challenges for effective immunotherapy, often leading to limited T-cell infiltration and inadequate immune activation. To overcome these barriers in solid tumors, the development of next-generation vaccines capable of eliciting robust and durable anti-tumor immunity has constituted a major focus in the clinic. A promising strategy involves a bioinspired approach that functionalizes synthetic nanocarriers with native cell membranes. These engineered platforms are designed to preserve the surface properties of native cell membranes (immune cells, nonimmune cells, and hybrid cell membranes) to enhance antigen presentation, prolong systemic circulation, and improve biocompatibility. This study systematically examines the design principles and mechanisms of bioinspired vaccines with native cell membranes, highlighting their capability to integrate multiple antigenic and adjuvant signals for superior antigen presentation and T-cell activation. We further explore the synergistic therapeutic effects of the next-generation vaccines when combined with common anti-tumor therapies. Moreover, the primary challenges for their clinical translation in solid tumors are critically discussed. These bioinspired nanoplatforms represent a transformative direction for developing more effective and personalized immunotherapies for solid tumors.

Atmospheric water harvesting (AWH) has garnered widespread attention for the alleviation of freshwater scarcity. However, AWH still presents challenges in simultaneously achieving rapid adsorption–desorption, low-energy regeneration, and environmentally sustainable development. Herein, a biomimetic all-biomass double-layer sponge is prepared to spatially separate moisture capture from solar-driven desorption while integrating hydrovoltaic power generation (HG) for the co-production of water and electricity. Inspired by tree transpiration, the carboxylated wood scaffold loaded with LiCl mimics root-like moisture uptake, while the recycled demethylated lignin coated on the upper layer serves as a photothermal evaporation layer that drives efficient solar-induced desorption analogous to leaf-mediated sunlight absorption. The biomimetic double-layer structure enables efficient moisture absorption and desorption, with vertical humidity gradients guiding water through directional fiber microchannels and generating sustained flow potentials. Under 60% relative humidity (RH), 25 °C, and 1-sun illumination, the open-circuit voltage (V_oc) of the double-layer wood sponge is ~430 mV, with a short-circuit current (I_sc) of ~6.3 μA and water uptake capacity of ~1.45 g g⁻¹, maintaining stable properties over multiple adsorption–desorption cycles. Under simulated conditions outdoors, freshwater can be effectively harvested, while the generated electricity can power lighting or be stored in capacitors to supply commercial electronic devices. In this strategy, the natural cellulose–lignin structure within wood is restructured and repurposed into a low-cost, sustainable platform that supplies both freshwater and environmental energy, providing a scalable pathway for efficient collection of water resources in resource-constrained regions.

Halide perovskites are novel photovoltaic materials with soft ionic lattice that are continuously exposed to sunlight during operation. High-energy ultraviolet (UV) irradiation will cause halide ion oxidation within the perovskite layer, accelerating halide ion migration and component loss, which results in a marked degradation in the device’s photovoltaic performance. Here, we introduce a 2,3-bis(2,4,5-trimethyl-3-thienyl) maleimide (BTTM) molecule capable of interconversion between UV and visible light into the perovskite structure, intensifying the light stability of the perovskite layer via ion anchoring. Meanwhile, the incorporation of BTTM promotes the growth of perovskite crystals and efficiently passivates defects within the perovskite film, significantly boosting the open-circuit voltage of the perovskite solar cells. This results in a power conversion efficiency increase from 22.07% to 24.71%. Under UV irradiation (365 nm), BTTM molecules mitigate the degradation of perovskite by suppressing the ion migration of iodide ions. After cumulative exposure to 5 kWh/m² of continuous UV irradiation, BTTM-based devices retain over 90% of their initial power conversion efficiency, demonstrating significantly enhanced UV stability. This study offers a straightforward approach to UV protection, providing novel insights for the environmental application of perovskite solar cells under intense UV irradiation.

The long-standing trade-off between illumination performance (such as uniformity) and optical system complexity has hindered the development of compact lithographic tools. Here, we overcome this limitation by introducing a metasurface-enabled lensless illumination system that seamlessly combines light homogenization and monitoring capabilities. Using an asymmetric diffusion metasurface integrated with intelligent optimization algorithms, we achieve precise light field control and self-adaptive feedback without relying on conventional lens assemblies. When deployed on a self-developed large-field lithography platform, the system demonstrates uniform ultraviolet illumination with nonuniformity below 3% and successfully exposes patterns across a range of feature sizes. A gray-level to power-level mapping algorithm enables real-time assessment of light-emitting diode performance, providing diagnostic alerts and adaptively reconfigurable exposure configurations to circumvent defective emitters. This synergy between metasurface optics and algorithmic intelligence establishes a new paradigm for compact, low-cost, and scalable lithographic illumination, offering a pathway toward next-generation intelligent manufacturing systems.

Cellulose nanofibrils (CNFs) are strong, flexible biopolymers, whereas producing large-area (centimeter-scale) optical films with tunable, vivid interference colors with them remains difficult. The amorphous regions within the fibrils reduce birefringence and prevent uniform color formation. Here, we develop an integrated salt-assisted assembly (iSAA) strategy that combines metal-ion crosslinking with organic–inorganic coassembly to fabricate nanofibril–crystal composite films with tunable, vibrant colors. By adjusting the concentration of aluminum salt during assembly, we precisely control optical phase retardation from about 400 nm to over 2,500 nm, covering the full range of the interference colors. The resulting films appear naturally transparent while displaying intense colors across the visible spectrum when viewed under polarized light. We further demonstrate the universality of the iSAA strategy by fabricating films from different biopolymer fibrils (e.g., chemically modified CNFs and protein amyloid fibrils) on hydrophilic and hydrophobic substrates. Additionally, coupling the transmitted colors of these films and their intrinsic optical haze produces a novel spectrally selective polychromatic lighting effect. These results establish the iSAA strategy as a general platform for engineering nanofibril-based birefringent materials with programmable polarization optics, expanding their potential in advanced optical and energy-efficient applications.

Liquid biopsy strategies for glioma leveraging metabolic features remain inadequately investigated. Herein, we performed liquid chromatography-mass spectrometry-based metabolomic and proteomic analyses on 189 tissue samples from 122 adult glioma patients, and nuclear magnetic resonance-based targeted metabolomic profiling on plasma samples from 430 participants encompassing 82 adult glioma patients, 53 pediatric primary brain tumor patients, 80 pancreatic cancer patients, and 215 nontumor controls. The results demonstrate that aberrations in “Alanine, aspartate, and glutamate metabolism” and “tricarboxylic acid (TCA) cycle” pathways are ubiquitous across subtypes and progression of glioma. Notably, these signatures could be captured in plasma, thereby reflecting shared metabolic features between tumor tissues and circulation. Based on these findings, we developed a liquid biopsy model comprising 7 plasma metabolites (including creatine, lactic acid, succinic acid, N,N-dimethylglycine, 2-oxoglutaric acid, acetic acid, and glutamic acid). This model achieved high diagnostic accuracy in independent test sets (area under the curve = 0.964 for adult glioma set; and 0.925 for pediatric primary brain tumor set). Meanwhile, the model exhibited a higher sensitivity of 0.885 for glioma compared to 0.800 for pancreatic cancer, providing evidence to support the tumor selectivity of the model. Together, we present a plasma-based metabolomic classifier that faithfully mirrors the core metabolic reprogramming of glioma and can serve as a readily available liquid biopsy tool.

The pathophysiology of ischemic stroke is critically mediated by detrimental neuroinflammation. Tripartite motif-containing 21 (TRIM21) serves as an E3 ubiquitin ligase that regulates important biological functions. Nonetheless, the specific role of TRIM21 in neuroinflammation and ischemic brain injury remains unclear. In this study, we found that TRIM21 expression was up-regulated in astrocytes within the peri-infarct regions of mice subjected to transient middle cerebral artery occlusion (tMCAO) and in an in vitro oxygen–glucose deprivation and reoxygenation (OGD/R) model. TRIM21 deficiency alleviated cerebral ischemia/reperfusion (I/R) injury by attenuating the inflammatory responses and oxidative stress. Mechanistically, our findings demonstrated that TRIM21 interacts with MDA5 and sequentially promotes the K63-linked ubiquitination and stabilization of MDA5, ultimately activating the nuclear factor κB (NF-κB) pathway in astrocytes. Moreover, MDA5 overexpression effectively reversed protective effects of TRIM21 deficiency after cerebral ischemia. Consistently, brain-targeted TRIM21 silencing with nanoparticle delivery considerably ameliorated cerebral I/R injury. Collectively, our findings identify TRIM21 as a novel astrocyte-specific mediator of neuroinflammation in cerebral ischemic injury and highlight its potential as a therapeutic target for ischemic stroke.

Rapid urbanization intensifies hygiene and sustainability challenges in drainage systems, where conventional floor drains suffer from odor backflow, bacterial growth, and pathogen transmission. Existing disinfection methods depend on external power or chemicals, increasing energy consumption and environmental pollution. Herein, we develop an intelligent floor drain system that enables self-powered disinfection by recovering wastewater energy. By synergistically integrating a turbine blade drain valve, a magnetic levitation module, a contactless drive module, and an electromagnetic power generation (EMG) module, the intelligent floor drain system recovers energy from wastewater for power generation while maintaining its traditional functionality. The EMG module is able to produce a peak power output of 0.8 mW at a drainage rate of 4.15 l/min. A voltage-multiplying circuit boosts energy output by 55%. The system was able to achieve 98.2% sterilization efficiency after 50 min of operation. This work contributes to the global goals of sustainability and energy efficiency.

tRNA-derived small RNAs (tsRNAs) or tRNA-derived fragments (tRFs) are an important class of regulatory molecules whose role in cardiac hypertrophy remains largely unknown. Here, we identified a novel tRF contributing to the regulation of cardiac hypertrophy that we termed CHAtRF (cardiac hypertrophy-associated tRF). The CHAtRF level was increased in mice and in patients with cardiac hypertrophy. CHAtRF deficiency attenuated angiotensin II (AngII)-induced cardiac hypertrophy and restored the heart function, while CHAtRF overexpression enhanced hypertrophic responses. Mechanistically, CHAtRF directly interacts with SRSF5 and blocks SRSF5 to bind with Psmg4 pre-mRNA, which mediates alternative splicing of Psmg4 pre-mRNA and promotes exon 2 skipping of Psmg4. CHAtRF-dependent alternative splicing of Psmg4 inhibits the expression of Psmg4 full-length isoform, resulting in progression of pathological hypertrophy. The ability of CHAtRF to regulate hypertrophy was confirmed in hiPSC-CMs, and CHAtRF serum levels are higher in individuals with myocardial hypertrophy or heart failure. Our findings reveal new insights into the previously unrecognized role of tsRNAs during cardiac hypertrophy, which provide potential novel therapeutic targets for pathological hypertrophy and might serve as potential biomarkers for diagnosing cardiac hypertrophy and heart failure.

The trabecular meshwork (TM) plays a pivotal role in maintaining intraocular pressure (IOP) by regulating aqueous humor outflow. Nuclear factor erythroid 2-related factor 2 (NRF2) was identified as a key transcriptional controller of TM redox balance and mitochondrial function. Transcriptomic profiling of tert-butyl hydroperoxide (tBHP)-induced oxidative injury revealed NRF2 pathway involvement in TM cellular defense. NRF2 knockout (KO) mice exhibited impaired aqueous humor dynamics, elevated IOP, and TM oxidative damage. In vitro, NRF2 knockdown aggravated oxidative stress and mitochondrial dysfunction, whereas NRF2 overexpression mitigated tBHP-induced cytotoxicity. The results of the gene set enrichment analysis (GSEA) indicated enrichment of oxidative phosphorylation pathway in NRF2-deficient cells. Chromatin immunoprecipitation sequencing (ChIP-seq) confirmed NDUFS7 as a direct NRF2 target essential for mitochondrial complex I integrity. Restoration of NDUFS7 expression in NRF2-deficient TM cells or KO mice rescued mitochondrial impairment. Collectively, these findings establish the NRF2/NDUFS7 axis as a central defense mechanism protecting TM from oxidative injury and suggest potential therapeutic strategies for glaucoma-associated ocular hypertension.

Behavior plays a critical role in health and disease. Although molecular omics have advanced the understanding of biological mechanisms, they alone cannot explain the role of behavior in health, and traditional behavioral measurement technologies have struggled to capture the dynamic, multidimensional, and heterogeneous nature of real-world behaviors. With the development of digital technologies such as wearable devices, smartphone sensors, and ecological momentary assessment, behavioromics has emerged as a new research paradigm with a holistic systems perspective, integrating continuous, multimodal behavioral data with molecular, physiological, and environmental information. By organizing behavioral measurement, modeling, and interpretation within a unified analytical framework, behavioromics reveals dynamic behavioral patterns, supports mechanism-informed inference, and identifies actionable targets for early intervention. Despite ongoing challenges in data heterogeneity, causal interpretation, and ethical governance, behavioromics holds promise for reshaping disease prediction, early detection, and precision intervention, and for advancing proactive health through earlier, behavior-centered prevention.

Chemical alterations in metal oxides during manipulation greatly diminish their potential in artificial photosynthesis. Clarifying and overcoming these changes is crucial for realizing the sustainable generation of solar fuels and chemicals. Here, employing multimodal operando techniques, we elucidated the degradation mechanism of copper oxide (CuO_x) photocathodes under operational conditions, revealing an electron-mediated reductive photocorrosion pathway: Cu₂O/CuO → Cu₂O → Cu. These key findings led us to engineer an ultrathin carbon layer encapsulation strategy formed via electrodeposition-coupled self-assembly of carbon nanodots. This protective layer enables efficient photoelectron extraction and spatial isolation. The resulting CuO_x@C exhibits gratifying durability with unaltered phases and steady photocurrent throughout extended operation exceeding 24 h. To enhance activity and selectivity toward ethylene, Ag nanoparticles were integrated onto CuO_x@C. The Ag decoration enhances CO₂ adsorption, stabilizes *CO intermediate, and facilitates the crucial *CO–*CO coupling. The Faraday efficiency for CO₂-to-ethylene conversion on CuO_x@C/Ag reaches up to ~66.4% and retains ~95% of its initial performance after prolonged use. This synergistic strategy of carbon encapsulation and metal decoration exhibits broad applicability, as validated by CuO_x@C/Ru, CuO_x@C/Pd, and BiVO₄@C/Pt. Our work provides a universal design framework for efficient and durable photoelectrodes, accelerating their transition from laboratory prototypes to scalable technologies.

Liver metastasis remains a major challenge in cancer treatment, yet its cellular and molecular landscape remains poorly defined at the pan-cancer level. Here, we construct a single-cell transcriptomic atlas of liver metastases across multiple cancer types by analyzing 100 single-cell RNA sequencing samples, profiling over 460,000 cells, and identifying 121 distinct cellular subtypes. We define 4 representative cellular programs (CPs) associated with liver metastasis, revealing how cellular composition and intercellular interactions within the tumor microenvironment drive metastatic progression and immune modulation. These CPs recapitulate a dynamic transition from immunoactive states, marked by natural-killer-cell-mediated immune surveillance and macrophage-driven angiogenesis, to immunosuppressive environments dominated by regulatory T cell infiltration and immune exclusion. The shift is marked by progressive alterations in immune infiltration, stromal remodeling, and tumor-intrinsic adaptations, elucidating key mechanisms of immune evasion and metastatic niche formation. Our study provides a high-resolution framework for understanding the heterogeneity and evolution of liver metastasis and highlights the potential of CP-based stratification to inform therapeutic strategies targeting the metastatic tumor microenvironment.

The extreme climatic conditions of the Tibetan Plateau foster unique microbial communities, especially in the sediment ecosystem. A thorough understanding of these communities could facilitate revealing their microbial diversity, biological resources, and response to climate change. Here, we have constructed the Tibetan Plateau Microbial Catalog of Sediment (TPMC-S) based on 248 metagenomic sediment samples from the Tibetan Plateau. We identified 511,056,752 nonredundant genes and recovered 13,696 metagenome-assembled genomes with enormous phylogenetic novelty (over 90% novel species), far exceeding other contemporary Tibetan microbial catalogs and expanding the microbial functional diversity. We also revealed that similarities of sediment microbial communities followed the distance–decay relationship. Furthermore, sediments contained a high proportion of evolutionarily “possible ancient species (PAS)” compared with paired aquatic samples, especially ancient archaeal lineages, suggesting a microbial “sedimentary archive” in sediment. Finally and most importantly, Asgardarchaeota, including 2 potentially novel genera, were identified from the sediments, and their latest divergence predated the uplift of the Tibetan Plateau, while they still gained functions to adapt to extreme environments. Our findings positioned the Tibetan Plateau as both a genomic repository of microbial antiquity, especially Asgardarchaeota, and an active arena for modern extremophile innovation, providing insights for deciphering microbial resilience strategies in climate-sensitive ecosystems and informing novel bioprospecting efforts.

With the continuous advancement of micro-light-emitting diode (Micro-LED) manufacturing technology, Micro-LED displays are poised to emerge as the next-generation display technology, making important strides in areas such as near-eye displays, large-scale high-definition devices, and flexible screens. Among the various technical challenges associated with Micro-LED displays, detection plays a crucial role in identifying defective pixels, improving yield, and reducing overall production costs. Given that Micro-LED chip arrays often consist of millions of tiny chips (<50 μm), existing electrical detection methods face limitations such as low efficiency and high costs. As a result, enhancing detection efficiency, improving accuracy, and reducing costs have become the key trends in the development of Micro-LED detection technology. This review first outlines the key indicators to be monitored during Micro-LED chip detection. It then provides an in-depth analysis of the various detection methods available at different stages of the manufacturing process. Finally, it concludes with a summary of the current state of Micro-LED detection technology and offers a forward-looking perspective on future technological advancements.

Cuproptosis, a newly identified form of copper-dependent programmed cell death, has emerged as a potential therapeutic strategy for cancer treatment. However, its antitumor efficacy was strictly limited by dysregulated glycolytic metabolism of tumor cells. Herein, we proposed multifunctional copper-based nano-PROTACs (CHNDs) to degrade hexokinase 2 (HK-2) and amplify cuproptosis for cancer therapy via dual mitochondrial energy depletion. Our initial evaluation indicated that polyethyleneimine (PEI)-based nano-PROTACs (PHDs) triggered HK-2 degradation via the ubiquitin–proteasome system (UPS). PHDs reduced HK-2 expression to 43.7% in 4T1 cells and 42.1% in CT26 cells, which consequently impaired glycolysis in tumor cells. Furthermore, copper ion release from CHNDs in a controlled manner and the glucose metabolism homeostasis interference by PHDs orchestrally induced effective cuproptosis and glycolysis inhibition for suppressing development and metastasis of tumor cells. Notably, CHNDs markedly inhibited the growth of murine colon and breast tumors by simultaneously disrupting mitochondrial respiration and glycolysis, resulting in tumor inhibition rates of 76.6% and 55.3%, respectively, and extending the median survival of CT26 tumor-bearing mice from 21 to 29 d. Our designed multifunctional engineered nanoparticle-based targeted protein degraders facilitated a new paradigm for precise oncology and proteolysis-targeting chimera (PROTAC) development.

Determining platelet-derived growth factor receptor β (PDGFRβ) expression in biological specimens is pivotal for cancer diagnosis, drug development, and therapeutic monitoring. After tyrosine kinase inhibitor (TKI) therapy, altered PDGFRβ expression may correlate with treatment resistance mechanisms. Real-time, accurate detection of PDGFRβ levels pre- and post-TKI treatment holds substantial clinical value, as it enables therapeutic efficacy evaluation, resistance prediction, and timely regimen adjustment. However, the current repertoire of real-time technologies for precise PDGFRβ monitoring remains highly limited. Herein, we present a novel nanoprobe (Cy3-Gint4.T@BPNSs) for PDGFRβ detection based on a fluorescence quenching–recovery mechanism. Cy3-Gint4.T is a cyanine 3 (Cy3)-labeled aptamer with high specificity and strong selective binding affinity for PDGFRβ. Black phosphorus nanosheets (BPNSs) adsorb Cy3-Gint4.T via van der Waals forces to quench its fluorescence. Upon targeting PDGFRβ on cancer cells, the aptamer–receptor interaction outcompetes Cy3-Gint4.T’s binding to BPNSs, triggering its release and subsequent fluorescence restoration. Notably, the restored fluorescence intensity shows a direct correlation with cellular PDGFRβ expression, highlighting the nanoprobe’s potential for guiding tumor diagnosis and treatment. Critically, our data confirm that dynamic PDGFRβ expression changes induced by specific TKI therapies exhibit a proportional relationship with corresponding fluorescence intensity variations. This finding further supports an association between PDGFRβ expression dynamics and TKI resistance mechanisms, facilitating precise PDGFRβ monitoring and individualized therapeutic guidance.

In the tumor microenvironment, both tumor cells and tumor-associated macrophages (TAMs) frequently impede the effective treatment of glioblastoma (GBM). Herein, a co-extracellular vesicles (EVs) delivery system composed of M0 RAW264.7 macrophage-derived extracellular vesicles (MEVs) and doxorubicin (DOX)-loaded lemon-derived EVs (LEVDs) is demonstrated, enabling a significant enhancement of immunochemotherapy for GBM. This system facilitates the penetration of both EV types across the blood–brain barrier and blood–brain tumor barrier, enabling precise modulation of TAMs and tumor cells within the GBM microenvironment. During this process, MEVs exhibit a remarkable homing capacity toward TAMs, and meanwhile, they are enriched in microRNA let-7f-5p, which targets the 3′ untranslated region of A20 mRNA in M2 macrophages, leading to the activation of nuclear factor κB signaling pathway. This cascade drives the repolarization of M2 macrophages toward an M1 phenotype, effectively reversing the immunosuppressive tumor microenvironment. Concurrently, LEVDs exhibit exceptional targeting of GBM cells through receptor–ligand interactions, facilitating efficient chemotherapy. As expected, the co-EVs delivery system significantly enhances immunochemotherapy for GBM through MEVs-mediated TAM repolarization and LEVDs-driven chemotherapy.

The regeneration of large bone defects remains a major clinical challenge due to the lack of stable and effective osteoinductive signals. Although extracellular vesicles have shown promising potential for cell-free bone regeneration, their application is largely constrained by complex purification and embedding into scaffolds. Migrasomes, newly identified organelles with the extracellular matrix affinity, represent a promising yet underexplored avenue for cell-free tissue engineering. Here, we report a migrasome-enriched bioactive layer as a functional osteoinductive interface for cell-free bone regeneration. We demonstrated that osteoprogenitor stem cells (OPSCs) derived from human cortical bone exhibit robust osteogenic capacity and, upon osteogenic induction, promote the release and deposition of migrasomes together with calcium on culture surfaces. Utilizing these characteristics, we developed an in situ deposition strategy where OPSCs are preseeded on biphasic calcium phosphate (BCP) scaffolds, induced to mineralize, followed by decellularization. This process robustly preserves a native, osteogenic migrasome layer on the scaffold without the need for vesicle isolation or chemical conjugation. The resulting migrasome-functionalized scaffolds markedly up-regulated osteogenic gene expression and promoted bone regeneration in a murine calvarial defect model. Altogether, these findings validate migrasomes as a potent, endogenous signaling platform for bone tissue engineering. Moreover, our new paradigm for cell-free biomaterials employing cellular secretomes opens a new frontier in regenerative medicine, where the transient activity of cells is permanently captured to direct tissue repair.

Effective management of plant pathogenic bacteria faces major challenges, including rapidly evolving bacterial resistance, environmental risks associated with traditional copper-based agrochemicals, and the scarcity of new antibacterial targets. Recently, liquid–liquid phase separation (LLPS) has been extensively demonstrated to play crucial roles in microbial biology. However, the use of phase-separating proteins as targets for bactericide development remains unexplored. Herein, we report the first syringic acid derivative, C₃₁, that targets the alpha subunit of RNA polymerase (RpoA) in Xanthomonas oryzae pv. oryzae (Xoo). C₃₁ exhibits exceptional inhibitory activity against Xoo (EC₅₀ = 0.86 μg/ml, half maximal effective concentration) and maintains a low resistance risk throughout 12 successive passages. Pot experiments show that C₃₁ provides superior control efficacy (59.37%) against rice bacterial leaf blight compared with syringic acid (24.65%) and thiodiazole copper (42.41%), showing sustained efficacy and high crop safety. Mechanistic studies reveal that RpoA and σ⁷⁰ factor undergo LLPS to generate biomolecular condensates that function as “transcriptional hubs”, thereby regulating the expression efficiency of global virulence genes and consequently strengthening Xoo pathogenicity. C₃₁ binds to the C-terminal domain of RpoA and prevents LLPS initiation and subsequent condensate formation, resulting in antibacterial effects. This study establishes an LLPS-based strategy to control phytopathogenic bacteria.