Language model (LM), a foundational algorithm in the development of capable artificial intelligence, has been widely explored, achieving remarkable attainment. As research advances, large language models (LLMs) have emerged by pretraining transformer-based models on large-scale corpora. These models showed great zero-shot and few-shot learning capabilities across a variety of tasks, attracting widespread attention from both academia and industry. Despite impressive performance, LLMs still tackle challenges in addressing complex real-world scenarios. Recently, the advent of DeepSeek has reignited intense interest among researchers. In this paper, we provide a concise development history of LLM and discuss current challenges and future perspective. In practice, we focus on 4 crucial aspects of LLMs, including emergent abilities, human alignment, retrieval augmented generation, and applications in specific domains.

Vascular disease is the leading cause of death worldwide. Predicting the burden of vascular disease and identifying modifiable key risk factors are critical for developing effective prevention strategies. This study aimed to project the global and regional burden of peripheral artery disease (PAD) from 2021 to 2050, with a specific focus on the impact of modifiable key risk factors and the potential benefits of their management. Compared to the 2021 Global Burden of Disease Study (GBD 2021), the number of PAD cases worldwide is projected to increase by 220% by 2050, reaching a staggering 360 million (95% uncertainty interval, 270 to 450). Age-standardized mortality is expected to double, while disability-adjusted life years (DALYs) are forecasted to rise from 19.7 to 33.1 per 100,000. Among individuals aged ≥65 years, PAD prevalence is projected to surge to 21.7% in women and 14.8% in men. Moreover, over 50% of PAD cases are expected to occur in low- and middle-income countries (LMICs). Metabolic diseases are anticipated to be the primary drivers of the rising PAD burden, with diabetes playing a key role in increasing PAD prevalence and severity. By effectively managing metabolic risk factors, age-standardized prevalence could be reduced by 36%, mortality by 17%, and DALYs by 10%. As metabolic risks, particularly diabetes, continue to rise alongside population aging, the global PAD burden is expected to increase substantially, especially in LMICs. Importantly, proactive metabolic risk management strategies have the potential to markedly alleviate the burden of vascular disease and reduce the growing geographic health disparities.

Multimodal sentiment analysis (MSA) aims to assess emotional states by integrating information from text, audio, and video. However, the heterogeneous nature of these modalities presents substantial challenges for accurate sentiment prediction. Existing approaches typically align pairs of modalities using attention mechanisms or contrastive learning, which are computationally expensive. Additionally, they often rely on a single granularity of alignment, either by averaging features over all time steps or aligning features at each individual time step. These approaches overlook the fact that emotional expression can vary across individuals and contexts, requiring multiple granularities to capture emotion effectively. To address these challenges, we propose a novel framework, Retrieve, Rank, and Reconstruction with Different Granularities (R3DG). R3DG segments the audio and video modalities into multiple representations at varying granularities based on their temporal durations. It then selects the most relevant representations that align closely with the text modality. To preserve the original information, R3DG reconstructs the audio and video data using the selected representations. Finally, the fused audio, video, and text features are aligned and combined for sentiment prediction, reducing the need for multiple alignment steps. Extensive experiments on 5 benchmark MSA datasets demonstrate that R3DG outperforms existing methods and achieves substantial reductions in computational time. Code is available at https://github.com/YetZzzzzz/R3DG.

Magnetic microrobots with noncontact and real-time control capabilities have garnered marked attention for targeted drug delivery in narrow, enclosed pathways within the human body. The manufacturing method of these magnetic robots plays a crucial role in determining their functionality. In this study, a photocuring 3-dimensional (3D) printing technique with in situ pixel-scale magnetic programming was developed, enabled by a 3D large-scale uniform magnetic field generator with a high strength of approximately 50 mT. Magnetic particles were rotated and aligned on demand to print intelligent structures with a spatial resolution of 50 μm. A novel key-node splicing magnetization method was introduced to control multicurved deformations in 1D strips and 2D membrane magnetic robots, enabling various modes of locomotion, such as rolling, creeping, swimming, and patch-based drug release. To support additional functions, 3D spatial magnetization was implemented for customized spiral capsule robots, allowing precise multidirectional swimming and multitarget droplet-based drug delivery. These multimode and multifunctional magnetic actuators were validated through in vivo operations in confined environments such as the gastrointestinal tract and bladder.

Lupus nephritis is recognized as a common and severe complication of systemic lupus erythematosus, without an optimal therapeutic strategy currently available. While mesenchymal stem cells (MSCs) hold therapeutic promise, their efficacy varies substantially, likely due to their plasticity and capacity to adopt pro-inflammatory (MSC1) or anti-inflammatory (MSC2) functional states in response to different microenvironments. Here, we report for the first time that IL-27, via JAK1–STAT1 signaling, up-regulates indoleamine 2,3-dioxygenase (IDO) in MSCs, driving MSC differentiation toward an IDO-positive MSC2 phenotype with low immunogenicity. These IDO-positive MSC2 cells produce kynurenine and kynurenic acid, the metabolites of tryptophan, which bind to the intracellular aryl hydrocarbon receptor. This interaction stimulates an increase in the anti-inflammatory factor TSG-6 and induces the differentiation of regulatory T cells. Notably, IL-27-conditioned MSC2 demonstrated superior therapeutic efficacy compared to conventional MSCs in a murine lupus nephritis model. In conclusion, this study revealed that IL-27 is a critical modulator of MSC immune plasticity and presented a novel therapeutic strategy utilizing IL-27-enhanced MSC2 for autoimmune diseases.

Glucocorticoid resistance increases the frequency of acute exacerbations and the risk of death in chronic obstructive pulmonary disease (COPD) patients with a history of long-term heavy smoking. In this study we aimed to investigate the role of neutrophil ferroptosis resistance and the formation of neutrophil extracellular traps (NETs) in cigarette smoke (CS)-induced glucocorticoid resistance in COPD. We collected clinical specimens from COPD patients and healthy subjects. A mouse model of COPD induced by CS exposure was established in vivo. Neutrophils were isolated from the peripheral blood of human donors and exposed to CS extract in vitro. We found extensive NET formation was observed in COPD patients with a history of long-term heavy smoking and was closely related to glucocorticoid resistance. In vivo, we found that prolonged CS exposure promoted NET formation and that rendered dexamethasone (Dex) treatment ineffective at alleviating lung inflammation in COPD model mice. However, the NET degrading agent deoxyribonuclease I could increase sensitivity to Dex in COPD model mice. In vitro experiments demonstrated that CS extract increased neutrophil cell viability by activating the Nrf2/SLC7A11/GPX4 pathway and inducing ferroptosis resistance in neutrophils. And we found that neutrophil specific GPX4 knockout inhibited CS-induced NET formation, increased sensitivity to Dex, and alleviated CS-induced glucocorticoid resistance in vivo and in vitro. In conclusion CS promotes glucocorticoid resistance in COPD by inducing ferroptosis resistance in neutrophils, further resulting in NET formation.

Advanced drug delivery systems integrating immunomodulatory functions can improve cancer therapy. Herein, we develop a novel metal-phenolic capsule for synergistic drug delivery and immunomodulation. Specifically, a stable metal-phenolic network (MPN), formed by Fe (III), tannic acid, and catechol-modified hyaluronic acid, was assembled onto doxorubicin (DOX)-loaded mannose-glycated bovine serum albumin microbubbles to construct microcapsules with both drug loading and immunomodulatory functions simultaneously. The capsules release DOX in a pH-responsive manner and induce reactive oxygen species accumulation in tumor cells, thereby enhancing immunogenic cell death (ICD). This ICD effect, combined with the direct stimulation of dendritic cells (DCs) by the capsules and the paracrine signaling from capsule-activated M1 macrophages, synergistically promotes DC maturation. In vivo bilateral tumor models demonstrate that DmTFH substantially inhibits primary and distant tumor development and markedly delays metastasis to the lungs. Flow cytometry analysis confirms robust local and systemic immune responses, characterized by enhanced DC maturation within lymph nodes and increased infiltration of activated CD8⁺ and CD4⁺ T cells in tumors and spleens. Overall, the immunoactive MPN microcapsules constructed in this study enhance the immunotherapeutic efficacy of DOX through the synergistic action of carrier-inherent immunomodulation and chemotherapy, providing a promising approach for combinatorial cancer therapy.

Reliable detection of high-g shocks in extreme impact scenarios, such as automobile collisions, is essential for ensuring occupant safety. Conventional shock sensors based on piezoresistive or capacitive mechanisms often underperform in high-g environments due to their structural complexity, resulting in delayed or missed detection. Here, we present a self-powered high-g shock sensor that combines a triboelectric transducer with a prestressed structure to deliver large signal amplitude and minimal oscillation. The prestress mechanism enhances initial contact strength, achieving a 400% increase in signal amplitude and reduced oscillation. We further developed a self-powered, compact (<4.5 cm³) microsystem that integrates the shock sensor, a signal processing module, airbag triggering circuitry, and a high-g-resistant supercapacitor as a backup power source. The microsystem achieves ultra-fast shock detection and airbag activation with a delay of less than 0.2 ms. Furthermore, its power demand is 80% lower than that of commercial high-g sensors, while the pre-charged supercapacitor ensures operational stability. To further extend the functionality of the device, we designed a lightweight collision target classification algorithm using ensemble learning and feature importance analysis, which could accurately distinguish between automotive collisions with hard, brittle, and soft materials. This study advances triboelectric nanogenerators for high-g shock sensing, offering improved reliability, performance, and real-world adaptability.

Atherosclerotic plaques pose a substantial risk for life-threatening cardiovascular complications due to their propensity to trigger acute clinical events. Foam cell formation, resulting from dysregulated lipid homeostasis, serves as a pivotal pathological hallmark in the progression of atherosclerosis. In this study, we presented a precision therapeutic strategy targeting foam cells of multiple origins. The carrier-free nanomedicine Dlut based on luteolin was constructed, featuring CD44 active targeting and stimulus-driven traceless release. Dlut demonstrated active foam cell targeting capability and complete disintegration triggered by oxidative stress and acidic microenvironment, enabling a traceless release of luteolin. Transcriptomic profiling revealed that Dlut inhibited foam cell formation by accelerating lipid efflux. In vivo studies further demonstrated that Dlut significantly reduced plaque burden and improved plaque stability, highlighting a translational potential of atherosclerosis.

The development of terahertz science and technology has shown new application prospects in artificial intelligence. Terahertz stimulation can lead to information communication of cells. Terahertz unipolar picosecond pulse train stimulation can activate cell membrane hydrophilic pores and protein ion channels. However, the effect of the envelope of the terahertz unipolar stimulation remains unknown. This paper studies the effect of the envelope on membrane communication-related variables and the accompanying energy consumption by a cell model with considerations of hydrophilic pores and Na⁺, K⁺-ATPase. According to the results, terahertz unipolar picosecond pulse train stimulation can deliver the signal contained in its envelope into the variation rates of membrane potentials no matter whether the hydrophilic pores are activated or not and also into the variation rates of the ion flow via the pores after activation of the pores. In contrast, the ion flow via Na⁺, K⁺-ATPase seems irrelevant to the signal in the envelope. Moreover, the ion flows show a modulation effect on the variation rates of membrane potentials. The accompanying power dissipations in the cases of different envelopes are similar, as low as around the level of 10⁻¹¹ W. The results lay the foundations for application in artificial intelligence, like brain–machine communications.

Stem cells have important applications in both regenerative and reproductive medicine. The cohesin complex comprises 4 core subunits, namely, SMC1, SMC3, RAD21, and STAG, and notably, it plays pivotal roles in controlling the fate determinations of stem cells by facilitating the dynamic regulation of the 3-dimensional genome architecture. We have recently reported that RAD21 forms a complex with YAP1 and NEDD4 to promote the self-renewal of human spermatogonial stem cells and inhibit their apoptosis. In this review, we address the molecular properties of the cohesin complex and its multiple regulatory mechanisms in mediating the fate decisions of various kinds of stem cells, including hematopoietic stem cells, embryonic stem cells, spermatogonial stem cells, neural stem cells, and other types of stem cells. By maintaining the chromatin loop structure, the cohesin complex is involved in DNA repair and gene transcription, which in turn controls the pluripotency, self-renewal, and differentiation of stem cells. In addition, the cohesin complex ensures faithful DNA replication and sister chromatid cohesion, which indirectly supports genetic and epigenetic programs. Variants in the subunit components of the cohesin complex and proteins’ modifications further confer functional plasticity, and its mutations can lead to abnormal stem cell functions and are correlated with diseases including cancers. Future studies need to integrate multidisciplinary approaches including single-cell multi-omics and cryo-electronic microscopy to resolve the dynamic regulatory networks of the cohesin complex in stem cell fate regulation and further explore its potential applications in regenerative and reproductive medicine.

Artificial neural networks have long been studied to emulate the cognitive capabilities of the human brain for artificial intelligence (AI) computing. However, as computational demands intensify, conventional hardware based on transistor and complementary metal oxide semiconductor (CMOS) technology faces substantial limitations due to the separation of memory and processing, a challenge commonly known as the von Neumann bottleneck. In this review, we examine how memristors, which are novel nonvolatile memory devices that exhibit memory-dependent resistance, can be harnessed to build more efficient and scalable neural networks. We provide a comprehensive background on the evolution of neural network models and memristors, as well as introduce the principles of memristive devices, which mimic the dynamic behavior of biological synapses. Various neural network architectures, including convolutional, recurrent, and spiking models, are discussed, highlighting the advantages of integrating memristors for in-memory computing and parallel processing. Our review further examines key mechanisms such as synaptic plasticity, encompassing both long-term potentiation and depression, as well as emerging learning algorithms that leverage memristive behavior. Finally, we identify current challenges, such as achieving ultra-low power consumption, high device uniformity, and seamless system integration, and propose future directions in materials science, device engineering, system integration, and industrialization. These advances suggest that memristor-based neural networks may pave the way for next-generation AI systems that combine low power consumption with high computational performance, ultimately bridging the gap between biological and electronic information processing.

In adult mammals, programmed cell death (PCD) facilitates tissue remodeling and regeneration in spinal cord injury (SCI), but excessive activation impedes SCI repair. However, no comprehensive pan-PCD atlas exists that encompasses diverse cell death patterns to fully elucidate PCD in adult SCI and develop strategies for modulating the excessive PCD response. Here, we identified neonatal mice with balanced PCD post-SCI as an ideal model for adult SCI. Accordingly, we developed “Thanatoset”, an SCI-specific gene panel to map tissue and cellular pan-PCD dynamics across neonatal and adult mice. Microglia were identified as pivotal mediators of pan-PCD, showing greater vulnerability in adults than in neonates. According to computational drug screening, withaferin A can revert microglial pan-PCD in adults to a neonatal-like regenerative state. Histological, functional, and molecular analyses corroborated that withaferin A enhances SCI recovery in adults by modulating microglial pan-PCD. These findings highlight the therapeutic potential of the pan-PCD framework for developing strategies to restore regeneration and improve SCI outcomes.

Temperature measurement in confined environments has long been a substantial challenge. Due to poor accessibility to constrained space, and low visibility, conventional thermometry and existing nanoscale thermometers struggle to achieve efficient and accurate temperature detection. As an emerging technology, microrobots offer great potential for temperature sensing in such challenging conditions. Here, we propose a temperature-responsive microrobot (TRM) that integrates artificial neural networks into microscale thermal sensing, enabling quantitative temperature measurement in complex and constrained environments. The TRM undergoes irreversible color changes in a high-temperature range of 160 to 240 °C. It features a Janus structure composed of a Cu(NH₃)₄SO₄-based thermochromic material and a nickel-coated magnetic actuation layer, allowing reliable operation in nontransparent and geometrically confined environments such as porous geological structures and constrained microspaces. The thermochromic mechanism and motion dynamics of the TRM under elevated temperatures were systematically investigated. The microrobot exhibits distinct chromatic responses at different temperatures. Based on the correlation between chromaticity and temperature, a multilayer perceptron neural network was developed. By inputting the observed color features into the trained model, the surrounding temperature can be quantitatively determined. Experimental results in a simulated porous microchannel model confirmed the feasibility and effectiveness of the TRM for localized high-temperature detection. This work provides a new solution for temperature sensing in restricted environments and lays a solid foundation for the application of microrobots in industrial high-temperature monitoring, highlighting their potential for real-world deployment in complex conditions.

Safe and effective veterinary vaccines prevent infectious diseases and reduce morbidity. In this field, nanovaccines based on nanomaterials are emerging, showing great potential as innovative alternatives to conventional vaccines. This paper highlights the advantages, disadvantages, and mechanisms of nanomaterials, including biomimetic, polymeric, lipid nanoparticles, self-assembling proteins, and other materials used in veterinary vaccine development. We also describe the progress of their research in developing vaccines against common and serious veterinary infectious diseases, such as foot-and-mouth illness, porcine epidemic diarrhea, pseudorabies, and bordetellosis. We aim to provide a scientific basis and practical guidance for the research and development of new veterinary vaccines, thereby contributing to scientific and technological progress in the field of veterinary medicine and the protection of animal health.

Polymetallic nanomaterials have important development potential by integrating the properties and advantages of their components. However, their preparation paradigm urgently needs to be updated to make full use of their characteristics to realize their multifaceted applications. In this study, multifunctional trimetallic gold–silver–chromium nanocomposites (Au–Ag–Cr NCs) were successfully synthesized, and their polymetallic plasmonic absorption properties were used in a variety of applications, from multimode and multianalyte sensing, advanced arithmetic, and reversible logic to long-text information protection. Au–Ag–Cr NCs with Au or Ag nanoparticles anchored on Cr nanobelts were synthesized using Au–Cr nanoseeds, Ag⁺, ascorbic acid as the reductant, and sodium dodecylbenzenesulfonate as the stabilizer. The resulting Au–Ag–Cr NCs exhibited multichannel sensing ability for 2 analytes (Hg²⁺ and hypochlorite), with remarkably improved selectivity and sensitivity when analyzing combined channels. Multiresponsiveness of Au–Ag–Cr NCs to diverse substance combinations underpins input–output mapping relationships, enabling advanced molecular logic computations (such as arithmetic and reversible logic). By digitizing its intrinsic sensing and response mechanisms, advanced molecular information protection (including encoding, encryption, and information concealment) for extended text were successfully implemented. This work not only offers novel insights into the design and multifunctionality of multicomponent nanocomposites but also paves the way for a new paradigm in molecular information technology that integrates sensing, logic processing, and information security.

A promising therapeutic approach in oncology involves immune checkpoint blockade (ICB), which stimulates anti-tumor immune responses. Nevertheless, the effectiveness of this treatment in clinical settings remains limited, underscoring the need for complementary strategies. Recent studies highlight the potential of type I interferon (IFN-I) inducers to reprogram the tumor microenvironment and enhance ICB outcomes. Herein, through high-content screening of a natural compound library, we identified daurisoline (DS), a bioactive alkaloid extracted from the Chinese herbal medicine Rhizoma Menispermi, as a potent inducer of IFN-I signaling. Our findings indicated that DS up-regulates interferon responses and pro-inflammatory cytokine expression in a TANK-binding kinase 1 (TBK1)-dependent manner. In vivo, DS exhibited marked tumor growth inhibition by activating dendritic cells, macrophages, and CD8⁺ T cells, thereby enhancing anti-tumor immunity. Utilizing the LiP-SMap approach, we identified low-density lipoprotein receptor-related protein 1 (LRP1) as the direct target of DS. Mechanistically, the binding of DS to LRP1 substantially disrupted lysosomal function, which subsequently triggered 5′-azacytidine-induced protein 2-mediated TBK1 activation and IFN-I production. Furthermore, DS demonstrated synergistic effects with anti-programmed death 1 therapy and a stimulator of interferon genes agonist by remodeling the immunosuppressive microenvironment. Collectively, our findings establish LRP1 as a novel therapeutic target for cancer immunotherapy and highlight DS-driven immune reprogramming as a translatable strategy to potentiate ICB efficacy.

Recent studies have revealed that polyclonality—where multiple distinct subclones cooperate during early tumor development—is a critical feature of tumor evolution, as demonstrated by Sadien et al. and Lu et al. in Nature (October 2024). These findings show that early polyclonal interactions can overcome fitness barriers, ultimately transitioning to monoclonality as dominant clones emerge. Understanding and targeting these interclonal dynamics offers new therapeutic opportunities. In this perspective, we outline how computational modeling and artificial intelligence (AI) tools can provide deeper insights into tumor polyclonality and identify actionable therapeutic strategies. By applying ligand–receptor interaction analysis, clonal trajectory reconstruction, network and pathway modeling, and spatial analysis, researchers can prioritize communication hubs, evolutionary bottlenecks, and microenvironmental niches that sustain tumor progression. These approaches, when integrated with experimental validation, offer a translational pathway from foundational discoveries to personalized cancer treatments aimed at disrupting cooperative subclonal ecosystems and preventing malignant progression.We commend the recent Nature publications, “Polyclonality overcomes fitness barriers in Apc-driven tumorigenesis” by Sadien et al. [1] and “Polyclonal-to-monoclonal transition in colorectal precancerous evolution” by Lu et al. [2], both featured on 2024 October 30. These groundbreaking studies employed distinct lineage tracing methods to investigate the origins and evolutionary dynamics of colorectal and intestinal tumorigenesis. Despite their different approaches, both studies reached convergent conclusions: Polyclonality plays a pivotal role in the early stages of tumor development, providing critical insights into how diverse cellular populations collaborate to overcome fitness barriers and drive tumor progression.

G protein-coupled receptor 120 (GPR120) plays a pivotal role in regulating lactation, yet its underlying mechanisms remain unclear. In mouse models, GPR120 expression in the mammary gland increases markedly during lactation. Under inflammatory conditions, both n-3 polyunsaturated fatty acids (n-3 PUFAs) and GPR120 agonists markedly reduced inflammatory responses and enhanced lipogenesis and migration in HC11 mammary epithelial cells. These benefits were also observed under non-inflammatory conditions and were diminished when GPR120 was knocked down. Furthermore, the regulatory function of GPR120 under non-inflammatory conditions in in vivo and in vitro models is explored. We discovered that the GPR120–Gα_s–cyclic adenosine monophosphate (cAMP)–exchange protein directly activated by cAMP (EPAC) signaling axis is critical for lipogenesis and migration in mammary epithelial cells. Through transcriptomic analyses, the EPAC–CCCTC-binding factor (CTCF)–peroxisome proliferator-activated receptor γ (PPARγ)/CCAAT enhancer-binding protein α (C/EBPα) pathway was identified to primarily govern lipogenesis, while the EPAC–C-X-C motif chemokine ligand 14 (CXCL14)/C-X-C chemokine receptor type 4 (CXCR4) autocrine loop regulates migration of mammary epithelial cells. Overall, these findings suggest that GPR120, which can be activated by n-3 PUFAs, improves mammary gland performance by alleviating inflammation and directly modulating mammary lipogenesis and mammary gland development through the CTCF–PPARγ/C/EBPα and CXCL14–CXCR4 pathways. Thus, GPR120 and its downstream signaling targets may represent an important clinical target for enhancing maternal lactation.

Neurogenic bone regeneration is essential for the effective restoration of bone tissue functionality, with exosomes derived from Schwann cells regionalized in bone injury tissue playing a crucial role in this process. However, precisely regulating the secretion of Schwann cells localized in bone injury tissue to enhance neurogenic bone regeneration remains a considerable challenge. In this study, an injectable, ultrasound-responsive piezoelectric conductive short fiber network (US@SFG) was innovatively developed using uniform short fiber homogenization techniques and multifunctional chemical modifications, enabling precise acoustic–electrical conversion that regionally activated the secretion of miRNAs from Schwann cell-derived exosomes, thereby promoting neurogenic bone regeneration. The incorporation of the piezoelectric polymer glycine imparts superior piezoelectric characteristics to the fiber network, while the conjugated π-electron motion within the conductive graphene network enhances internal electron transfer efficiency, thereby facilitating electrical conductivity. Compared with traditional piezoelectric fiber networks, acousto-electric conversion fiber networks demonstrated a 1.7-fold increase in piezoelectric performance and a 30-fold increase in conductivity, facilitating precise electrochemical regulation under ultrasound stimulation. In vitro studies revealed that acousto-electric conversion fiber networks precisely modulate the secretion of localized Schwann cell exosomal miRNAs (miRNA-494-3p, miRNA-381-3p, and miRNA-369-3p), activating the phosphatidylinositol 3-kinase/protein kinase B and Wnt signaling pathways in bone marrow mesenchymal stem cells, and thereby promoting osteogenic differentiation. Furthermore, in vivo experiments confirmed that under ultrasound imaging guidance, acousto–electric conversion fiber networks could be directed precisely to bone defects, where precise control of ultrasound parameters facilitated acoustic–electrical conversion and electrical signal modulation, markedly promoting the formation of neural networks and bone tissue regeneration. In this study, for the first time, an injectable acousto-electric conversion fiber network was constructed to activate Schwann cell exosomes in bone injury tissue regionally, providing a novel therapeutic strategy and potential molecular targets for neurogenic bone regeneration.

Recently developed base editing (BE), prime editing (PE), and click editing (CE) technologies enable precise and efficient genome editing with minimal risk of double-strand breaks and associated toxicity. However, their effectiveness in correcting real disease-causing mutations has not been systematically compared. Here, we aim to evaluate the potential of BE, PE, and CE technologies in rescuing the retinal degeneration-causing Pde6b (c.1976T>C, p.L659P) mutation. This site is prone to bystander effects, making it an ideal model for comparing the editing outcomes of these 3 novel technologies, particularly their editing precision. We optimized BE, PE, and CE systems in vitro using Pde6b-L659P cell models and compared their editing via deep sequencing. BE and PE had similar efficiency, but PE was the most precise, minimizing bystander edits. CE had lower efficiency and higher indel rates, needing further optimization. Using the optimal PE system for in vivo electroporation in Pde6b-L659P mice, we achieved 12.4% targeted repair with high precision, partially rescuing retinal degeneration. This study demonstrates proof of concept for the precise correction of the Pde6b-L659P mutation causing retinal degeneration using BE, PE, and CE tools. The findings offer valuable insights into the future optimization of precision gene editing techniques and their potential translational applications.

We aimed to develop a voiding cystourethrography (VCUG) diagnostic artificial intelligence model (VCUG-DAM), which relies on a novel architecture to automatically segment and diagnose the bladder, urethra, and ureters using a single VCUG image, while dynamically assessing the relative importance of each image. A total of 7,899 VCUG images from 1,660 patients across 15 Chinese hospitals were collected between 2021 and 2023. In stage 1, we assessed the performances of the VCUG-DAM model. The patient-level area under the curve (AUC) of VCUG-DAM was 0.8772, 0.7752, 0.9443, and 0.9342 for bladder, urethral, left, and right vesicoureteral reflux (VUR), respectively. In stage 2, we explored whether the VCUG-DAM model could improve the diagnostic ability of clinicians. VCUG-DAM improved the clinician’s diagnostic performance, with mean AUCs increasing from 0.8185 to 0.9456 for the bladder, 0.6507 to 0.7943 for the urethra, 0.6288 to 0.9641 for the left VUR, and 0.7305 to 0.9506 for the right VUR (all P < 0.0001). In stage 3, the consistency of the VCUG-DAM for VUR grading was validated. VCUG-DAM improved inter-clinician agreement for VUR grading. The fully automated VCUG-DAM demonstrated high accuracy, reliability, and robustness in multitask diagnoses of urinary tract abnormalities across multiple VCUG images, while improving the diagnostic ability of clinicians as an auxiliary tool.

Protein interactions with molecules, such as other proteins, peptides, or small ligands, play a critical role in biological processes, and the identification of protein binding sites is crucial for understanding the mechanisms underlying diseases such as cancer. Traditional protein binding site prediction models usually extract residue features manually and then employ a graph or point-cloud-based architecture borrowed from other fields. Therefore, substantial information loss and limited learning ability cause them to fail to capture residue binding patterns. To solve these challenges, we introduce a general network that predicts the binding residues of proteins, peptides, and metal ions on proteins. SpatConv extracts sequence features from a pretrained large protein language model and structure features from a local coordinate framework. SpatConv learns residue binding patterns through a specially designed, graph-free bio-spatial convolution, which characterizes the complex spatial environments around the residues. After training and testing, SpatConv demonstrates great improvements over the state-of-the-art predictors and reveals novel biological insights into the relationship between binding sites and physicochemical properties. Notably, SpatConv exhibits robust performance across predicted and experimental structures, enhancing its reliability. Additionally, when applying it to the spike protein structure of severe acute respiratory syndrome coronavirus 2, SpatConv successfully identifies antibody binding sites and predicts potential binding regions, providing strong evidence supporting new drug development. A user-friendly online server for SpatConv is freely available at http://liulab.top/SpatConv/server.

T lymphocytes consist of αβ and γδ T cells, which mature and differentiate from the same progenitor cells in the thymus. Cullin-RING ligases (CRLs), the largest family of ubiquitin ligases, require neddylation on the scaffold protein Cullins for their ligase activity. The role of neddylation–CRL system in thymus development and fate determination of αβ/γδ T cells remains elusive. Here, we generated conditional knockout mouse models with thymus individual deletion of Ube2m or Ube2f, 2 neddylation E2-conjugating enzymes, and Rbx1 or Sag, 2 dual neddylation and ubiquitylation E3 ligases. We found that only Rbx1, but not Ube2m/Ube2f, nor Sag, plays an essential role in thymus development and fate determination of αβ/γδ T cells. Specifically, Rbx1 loss causes shrinkage of the thymus, delayed T cell development, increased γδ T cells in the thymus, increased the ratio of immature Gzma⁺ γδ T cells, and decreased the ratio of the proliferative subpopulation. Some of these phenotypes were moderately rescued by simultaneous Bim deletion. Mechanistically, Rbx1 loss alters the Akt, NF-κB, and metabolic pathways in progenitor γδ T cells/DN3a cells. Finally, Rbx1 loss altered the γδ T1/T17 cell population in the thymus, suggesting that Rbx1 controls the fate of γδ T cells.

In orthopedic minimally invasive surgeries (MIS) such as percutaneous vertebroplasty (PVP) and percutaneous kyphoplasty (PKP), calcium phosphate cements (CPCs) are an attractive alternative to bioinert polymethyl methacrylate (PMMA) due to their superior biocompatibility and osteoconductivity. However, the mechanical strength and injectability of CPCs often remain insufficient for load-bearing applications, limiting their broader use in these critical procedures. To address this challenge, we introduce a machine learning-assisted approach to enhance both the mechanical strength and injectability of CPCs by identifying specific polymers as superplasticizers. By optimizing its concentration and the liquid-to-powder (L/P) ratio, we developed an injectable brushite-based cement with an exceptional compressive strength of 79.5 ± 4.3 MPa, surpassing both traditional CPCs and PMMA in orthopedic applications. Zeta potential and adsorption studies reveal that these superplasticizers enhance cement paste dispersion via electrostatic repulsion. In vitro assays demonstrate excellent biocompatibility and osteogenic properties, while in vivo experiments further confirm the cement’s superior osteoinductive capability. The brushite cement regulates cellular metabolism and stem cell differentiation by enhancing energy metabolism and activating key signaling pathways such as phosphatidylinositol 3-kinase–AKT and mitogen-activated protein kinase–extracellular signal–regulated kinase. These findings offer a novel approach to fabricating CPCs with enhanced mechanical strength and osteogenic potential, addressing long-standing challenges in orthopedic MIS.

Chronic mechanical vibrations and endoplasmic reticulum (ER) stress are major contributors to osteoarthritis (OA) progression. This study proposes a novel “cellular shock absorption” approach by developing viscoelastic hydrogel microspheres with tunable stress relaxation properties. By modulating the chemical bonds in the hydrogel network through oxidation and hydrazine coupling reaction, hydrogel microspheres capable of absorbing shock and reducing mechanical stimulus-induced ER stress in chondrocytes are created. Cationic liposomes, modified with the cartilage-targeting peptide Wyrgrl and loaded with tauroursodeoxycholic acid (TUDCA), are encapsulated within these hydrogel microspheres. The microspheres not only dissipate intra-articular impact forces, reducing vibration and pressure transmission, but also provide sustained release of TUDCA, alleviating ER stress and slowing OA progression. In vitro studies showed that the stress relaxation time constant (τ) of the microspheres was tuned to 23.81 s, closely resembling the mechanical properties of the cartilage matrix. This property, combined with targeted TUDCA delivery, reduced Grp78 and CHOP expression, alleviating ER stress and inhibiting chondrocyte apoptosis. In vivo, the microspheres preserved joint cartilage structure, suppressed ER stress responses, and substantially delayed OA progression. This strategy presents a promising approach to mitigating cartilage damage and delaying OA by reducing mechanical stress and alleviating ER stress.

Textiles with intrinsic breathability and mechanical adaptability are revolutionizing wearable electronics by delivering outstanding comfort and integration potentials. However, the expanding functionalities and body coverage of textile electronics necessitate large-scale and distributed driving circuits, which typically compromise the flexibility and permeability of textiles. To overcome the limitations of traditional circuit boards, textile hybrid electronics (THE) have emerged as promising electronic platforms, where both flexible and rigid components are seamlessly integrated into textiles. This route offers a synergy of system-level performance and wearing comfort. The progress report presents a comprehensive overview of the fabrication strategies for fully integrated THE, mainly encompassing the cross-scale production of flexible components and the reliable integration of rigid components. First, typical materials classified in textile electronic components are summarized. Then, various methods for constructing flexible coatings and fibrous structures are elucidated with distinct mechanisms and advantages for textile substrates. Followed by that, the focus shifts to the heterogeneous integration of rigid components, including the layer-by-layer and in-fiber strategies. Both approaches show promise in realizing monolithic and untethered THE systems. Furthermore, representative paradigms of THE are presented for their applications in pervasive health management and human–machine interaction. Finally, future trends of THE toward distributed and intelligent systems are specially emphasized, with key challenges and potential solutions outlined. The combination of various forms of THE is expected to embed advanced electronic functionalities into everyday textiles, bridging the gap between wearable electronics and human life.

Androgenetic alopecia (AGA)—a condition characterized by hair loss due to aging, autoimmune responses, stress, and other factors—results in hair follicle (HF) shrinkage and dermal papilla cell apoptosis. So far, only minoxidil (MXD) and finasteride have been approved for AGA treatment. However, both drugs have serious side effects, including hypersensitivity and sexual dysfunction. Hence, novel treatment agents are required for AGA. Although metformin (Met) is primarily a diabetes drug, it is also known to promote hair growth. However, it shows low transdermal permeability, and the mechanisms underlying its therapeutic effects on AGA remain unclear. Two-dimensional black phosphorus nanosheets (BP NSs) have attracted attention as drug carriers due to their low cytotoxicity, good biocompatibility, and strong antioxidant capacity. However, they are unstable, prone to degradation, and unsuitable for transdermal drug delivery. Fortunately, this limitation can be addressed through modification strategies, such as polyethylene glycol (PEG) addition (PEGylation). Here, we PEGylated BP NSs to improve their stability and loaded them with Met to generate a transdermal system (BP-PEG-Met) for AGA treatment. Compared with topical MXD, BP-PEG-Met markedly promoted hair regeneration while inducing fewer side effects. BP-PEG-Met scavenged excessive reactive oxygen species in skin cells, reducing the oxidative stress around HFs. Moreover, it up-regulated the expression of vascular endothelial growth factor (VEGF) and platelet-endothelial cell adhesion molecule-1 (CD31) in dermal papillae, inducing angiogenesis around HFs and accelerating the hair cycle toward anagen. Overall, this BP-PEG-Met transdermal delivery system showed marked clinical potential as a multifunctional tool for treating alopecia and possibly managing other skin conditions.

Outbreaks and the widespread prevalence of porcine respiratory infectious diseases have led to substantial economic losses worldwide. In this study, epidemiological surveillance revealed lower viral detection in association with an increased abundance of Bacillaceae in pigs with outdoor access; thus, Bacillus subtilis NS12, a strain with enhanced mucosal colonization and superior broad-spectrum antiviral activity, was isolated from the nasal mucosa of these pigs for further investigation. This mechanistic study revealed that the antiviral efficacy of B. subtilis NS12 is primarily attributed to bioactive metabolites, including a novel surfactin with high safety and antiviral activity and piceatannol, a potent antioxidant molecule. These metabolites modify the structure and fluidity of phospholipids within the viral envelope, thereby inhibiting viral entry by impeding membrane fusion. Therefore, with its broad-spectrum antiviral activity, B. subtilis NS12 offers a probiotic-based, environmentally sustainable, and noninvasive antiviral strategy for preventing and controlling respiratory viral infections.

Nonsuicidal self-injury (NSSI) demonstrates escalating prevalence among adolescents as a maladaptive behavior characterized by deliberate self-harm, yet its neurobiological underpinnings remain elusive. Spontaneous self-injurious behavior (SIB) in nonhuman primates (NHPs) emerges as a clinically relevant animal model for investigating NSSI pathogenesis and therapeutic interventions. However, previous studies have yet to comprehensively evaluate the translational value of self-injury in NHPs through integrated behavioral and neuroimaging characterization. In this study, we identified spontaneously self-injurious macaques within our NHP colony and performed multimodal assessments encompassing ethological profiling, neuroendocrine assays, metabolomic analysis, and neuroimaging. Our results revealed that SIB macaques exhibited biological patterns and temporal onset sequences of self-harm, accompanied by a locomotor and social interaction decrease based on 3-dimensional deep-learning recognition, sensory processing deficits, and impairments in emotional and cognitive processing. Biochemical profiling demonstrated reduced plasma concentrations of cortisol, serotonin, and oxytocin, coupled with metabolomic disturbances including up-regulation of digestive-related pathways and down-regulation of dopaminergic synaptic signaling and phosphatidylinositol metabolism. Neuroimaging analyses identified structural abnormalities featuring volumetric enlargement in amygdala and midbrain regions alongside gray matter reduction in the frontal and parietal lobes. Enhanced structural and functional connectivity was observed. Network-based statistics highlighted increased functional connectivity primarily between the frontal and parietal lobes. These alterations demonstrated a partial correlation with observed behavioral deficits in the self-injury macaques. Notably, a series of administration of low-dose ketamine had no effect on SIB and the physical index. Our integrative multi-omic approach elucidates the neurobiological phenotype of spontaneous SIB in macaques, highlighting the value of the SIB model for pathogenetic investigation and therapeutic development in human NSSIs.

Optical microscopy contributes to the ever-increasing progress in biological and biomedical studies, as it allows the implementation of minimally invasive experimental pipelines to translate the data of measured samples into valuable knowledge. Within these pipelines, reliable quality assessment must be ensured to validate the generated results. Image quality assessment is often applied with full-reference methods to estimate the similarity between the ground truth and the output images. However, current methods often show poor agreement with visual perception and lead to the generation of various full-reference metrics tailored to specific applications. Additionally, they rely on pixel-wise comparisons, emphasizing local intensity similarity while often overlooking comprehensive and interpretable image quality assessment. To address these issues, we have developed a multi-marker similarity method that compares standard quality markers, such as resolution, signal-to-noise ratio, contrast, and high-frequency components. The method computes a similarity score between the image and the ground truth for each marker and then combines these scores into an overall similarity estimate. This provides a full-reference estimate of image quality while extracting global quality features and detecting experimental artifacts. Multi-marker similarity provides a reliable and interpretable method for image quality assessment and the generation of quality rankings. By focusing on the comparison of quality markers rather than direct image distances, the method enables reduced-reference implementations, where a single field of view is used as a benchmark for multiple measurements. This opens a way for reliable automatic evaluation of big datasets, typical of large biomedical studies, when manually assessing single images and defining the ground truth for each field of view is not feasible.

A persistently substantial energy demand and metabolic reprogramming endure throughout the entire course of osteoclastogenesis, accompanied by an intensified oxidative stress. Hence, balancing cellular energy metabolism and maintaining redox homeostasis offer potential for coordinating osteoclastogenesis and bone loss in pathological conditions. In the present study, we have discovered Visomitin, a novel antioxidant that specifically targets mitochondria, which efficiently decreases intracellular reactive oxygen species (ROS) levels, inhibits osteoclastogenesis, and impairs the function of bone resorption. Mechanistically, Visomitin directly targets signal transducer and activator of transcription 3 (STAT3), leading to the inhibition of its transcriptional activity and modulation of lactate dehydrogenase B (LDHB) expression levels, consequently triggering metabolic reprogramming and exerting antagonistic effects on osteoclasts. Furthermore, administration of Visomitin demonstrates marked protective effects against pathological bone loss in vivo. Given its established clinical safety profile in ophthalmologic applications, Visomitin emerges as a promising anti-resorptive agent for clinical translation. This study also unveils the STAT3/LDHB axis as a critical nexus linking mitochondrial redox regulation to osteoclast metabolism, providing a novel therapeutic strategy for osteoclast-driven bone diseases.

Self-powered sensing technologies have sparked a revolution in electric devices. Furthermore, ultrathin characteristics are highly desirable for on-skin and wearable devices to achieve superior conformability on complex 3-dimensional surfaces, which facilitates improved wearing comfort and detection accuracy. However, developing self-powered sensors with ultrathin and conformal features without complicated fabrication processes remains a formidable challenge. Herein, we present an ultrathin self-powered sensor with high conformability, fabricated by a liquid-phase transferring approach. The sandwich-like sensor is spin-coated layer by layer on a water-soluble substrate. Upon immersion in water and complete dissolution of the sacrificial layer, the sensor can be transferred to a variety of surfaces with diverse morphologies. The ultrathin sensor shows long-term stability. When the 45-μm-thick sensor is transferred to human skin, robotic hands, insole, flat plates with fine bevels, cylinders, undulating surfaces, and leaf textures, the fingerprint and surface details of the objects are vividly reflected on the sensor surface, attesting to its exceptional conformability. Driven by the triboelectric effect, the self-powered sensor and its array exhibit good sensitivity and rapid response time, enabling tactile sensing functions for pressure, material species, surface roughness detection, and motion state. The proposed design strategies for ultrathin self-powered sensors hold immense promises in wearable devices, robotics, and human–machine interfacing.

As an emerging frontier in biomimetic intelligent microsystems, insect-scale flapping-wing micro aerial vehicles (FWMAVs) demonstrate significant application potential due to their exceptional maneuverability and stealth capabilities. This study proposes a novel mechanical self-stabilization architecture validated through systematic engineering design to address the critical challenge of balancing dynamic instability with payload constraints in stable flight control. By integrating a piezoelectric direct-drive actuator to streamline transmission mechanisms with the optimized V-wing configuration, we developed a V-wing FWMAV prototype weighing 204 mg (wingspan: 68 mm) that demonstrates 41.5% enhanced lift performance and 40% reduction in structural asymmetry errors compared to previous iterations. To overcome the inherent limitations of conventional control methods in payload capacity and response latency, we engineered a cylindrically symmetric damping mechanism. Through the symmetrical aerodynamic design of the top layout, this innovation generates 3-dimensional restoring moments through optimized vortex distribution patterns, achieving isotropic damping effects in the vertical axis. Experimental results reveal that the 241-mg Tumbler FWMAV equipped with this damper exhibits breakthrough stabilization performance: Vertical stabilization duration shows 5- and 20-fold improvements over conventional cross-type dampers and undamped systems, respectively, enabling stable untethered hovering flight exceeding 15 s. The established integrated design paradigm combining structural optimization, aerodynamic enhancement, and passive stabilization control provides a new way to the longstanding technical bottleneck between payload capacity and dynamic stability in insect-scale FWMAVs.

Neuroendocrine prostate cancer (NEPC), an aggressive and highly malignant subtype of castration-resistant prostate cancer (CRPC), arises through drug resistance mechanisms involving genomic alterations, epigenetic remodeling, tumor microenvironment (TME) reprogramming, and lineage plasticity. A hallmark of NEPC is its independence from the androgen receptor (AR) pathway, evidenced by diminished or absent AR expression—a key barrier to effective clinical management. Therefore, a comprehensive understanding of NEPC pathogenesis and progression is essential, as it facilitates the identification of potential therapeutic targets and the development of more effective therapies. In this review, we summarize the typical characteristics of NEPC and describe its clinical diagnosis, relevant imaging modalities, current treatment strategies, and associated therapeutic difficulties. We also highlight the core events driving NEPC formation. Furthermore, we discuss potential therapeutic targets for the disease and review pharmacological agents that have demonstrated efficacy against NEPC, aiming to offer innovative perspectives and potential research directions for future NEPC treatment.

The limited energy density inherent in cathode materials remains a marked barrier to the widespread adoption of sodium-ion batteries. Despite considerable research efforts, the precise influence of atomic and crystalline configurations on energy density is not yet fully understood, creating a knowledge gap that hinders the rational design of advanced cathode materials. In this study, we propose a machine learning approach to systematically identify promising cathode materials with high energy densities. Our model highlights the critical roles of entropy and equivalent electronegativity, among other properties such as molecular mass, electron affinity, and average ionic radius. Based on these insights, we successfully synthesized Na₃Mn_0.5V_0.5Ti_0.5Zr_0.5(PO₄)₃ (NMVTZP) electrodes via a sol–gel method. The resulting electrodes exhibit an impressive reversible specific capacity of 148.27 mAh g⁻¹ at a 0.1-C rate, outperforming several previously reported cathode materials. Additionally, the NMVTZP electrodes demonstrate an average operating voltage of 3.14 V, an energy density of 465 Wh kg⁻¹, and exceptional rate performance, retaining 90.20 mAh g⁻¹ at a 5-C rate. We anticipate that our machine learning approach will accelerate the development of high-performance materials and greatly contribute to the advancement of sodium-ion battery technology.

The protonation process of adsorbed *CO intermediates has been widely recognized as a critical determinant governing product selectivity in electrocatalytic carbon dioxide reduction reaction (eCO₂RR). However, the active hydrogen species and mechanism of *CO protonation in acid eCO₂RR remain ambiguous. Particularly, the involvement of H⁺ in *CO hydrogenation is still under debate. Here, we developed a CuCl-mediated synthesis strategy integrated with rare-earth doping electronic structure engineering, which enriches intermediates and promotes adsorbed hydrogen (*H) participation in reactions, respectively. For the first time, differential electrochemical mass spectrometry (DEMS) and nuclear magnetic resonance (NMR) were employed to clarify the participation of hydrogen species in liquid and gaseous eCO₂RR products, with isotope labeling utilized to distinguish the distribution of H⁺ and *H in the products. Experimental verification confirmed that in acidic electrolytes, the ethylene pathway was dominated by H⁺ hydrogenation, whereas the ethanol pathway incorporated contributions from both H⁺ and *H. Upon yttrium (Y) doping into Cu₂O/CuCl, interfacial water activation was markedly enhanced, thereby enabling the provision of supplementary *H for catalytic engagement. Notably, our Y-Cu₂O/CuCl catalyst achieves a remarkable 65.7% Faradaic efficiency for ethanol with exceptional 65-h stability at 200 mA cm⁻¹. This work provides new evidence for H⁺ participation in acid eCO₂RR, emphasizing the critical role of H₂O activation degree in selectivity regulation, and thus offering novel insights for designing efficient acid eCO₂RR catalysts.

Doxorubicin (DOX)-based chemotherapy is the basic treatment for triple-negative breast cancer (TNBC). However, chemoresistance is still one of the major causes of metastasis, recurrence, and poor outcomes. Recently, a close relationship between chemoresistance and endoplasmic reticulum (ER) stress has been found. In this study, ER-associated degradation (ERAD)-related protein EDEM1 (ER degradation enhancing α-mannosidase-like 1) plays a vital role in DOX-induced ER stress, which is up-regulated in tumor cells and tissues. In vitro and in vivo experiments reveal the promoting role of EDEM1 in the progression and chemoresistance of TNBC. Besides, EDEM1 attenuates autophagy and reduces ER stress-related apoptosis, indicating its inhibitory effect on ER stress. Furthermore, EDEM1 promotes ERAD and enhances the antioxidant capacity of tumor cells. Mechanistically, EDEM1 competitively binds Kelch-like ECH-associated protein 1 to prevent the ubiquitination and degradation of nuclear factor erythroid 2-related factor 2 (Nrf2), leading to increased Nrf2 nuclear translocation and antioxidant response element activation to bolster antioxidant defense and cell survival. Moreover, both the expression and function of EDEM1 are down-regulated by miR-32-5p. Clinically, high EDEM1 expression is correlated with poor patient outcomes in breast cancer, especially in TNBC patients treated with DOX-based chemotherapy. These findings reveal EDEM1 as a regulator of ER homeostasis during cancer progression and chemoresistance, and a potential target for breast cancer therapy.

Collagen is a major structural component of human tissues, and its spatial arrangement is critical for maintaining tissue mechanical integrity and regulating cell behavior. In atherosclerosis (AS), collagen fiber arrangement has been implicated in plaque stability and the regulation of vascular calcification, yet its evolution during disease progression and association with other pathological processes remain poorly understood. In this study, male ApoE^−/− mice were fed a high-fat diet to establish a model of AS. Histological staining was performed every 5 weeks to analyze the collagen fiber alignment in the aortic arch of mice, along with calcification-related cells, proteins, and growth factors. The experimental results indicate that collagen fiber arrangement underwent gradual disruption and randomization as the disease progressed. Randomized collagen fibers were found to colocalize with inflammatory infiltration, smooth muscle cell phenotypic switching, osteogenic gene expression, and calcification. Therefore, changes in collagen fiber arrangement can be used to determine the presence of AS lesions, delineate their location, monitor disease progression, and assess plaque stability, thereby providing a solid theoretical foundation for the diagnosis and treatment of AS.

Water extraction from lunar regolith is one of the critical techniques for in situ resource utilization on the Moon. Traditional conductive heating methods show low efficiencies for massive water production from lunar regolith due to the low heat conductivity of lunar regolith and the inherent harsh lunar environment. To enhance the effectiveness of massive water production and reduce energy cost, microwave heating method is used in this study to extract water from icy lunar regolith at an initial cryogenic temperature of −80 °C. Hydrated lunar regolith simulant (LRS) is prepared with the water content from 1.96% to 13.79%. The particles are compacted into large cylinder sample with a size of 70 mm (diameter) × 70 mm (height). An integrated microwave heating system is built by which the icy lunar regolith is heated by microwaves at 2.45 GHz. Water vapor is transmitted in a closed flow path, and liquid water is collected in a cold trap after condensation. Both a high-power heating pattern (800 W) and a low-power heating pattern (400 W) are studied. The results show that microwave heats the sample uniformly, and water content escapes from center to outside. At the high power of 800 W, the samples are dried almost completely at an energy cost of 1.9 to 10.0 W·h/g with the decrease of water content. The rate of water collection is up to 1.57 g/min. Reducing heating power to 400 W prolongs the initial heat input period. Once the liquid water begins to collect, the water collection rate is comparable to that at the high-power heating pattern. The results prove the effectiveness of microwave heating for massive water production from icy lunar regolith, and the technique can be used for future engineering applications.

Dysregulation of ferroptosis is linked to chemoresistance, and reprogramming of glucose metabolism is involved in this progress. However, the underlying mechanisms remain obscure. Herein, using metabolic profiling, we find that hexosamine biosynthetic pathway (HBP) metabolism and the byproduct, UDP-GlcNAc, are substantially up-regulated in chemoresistant tumor tissues and cells. UDP-GlcNAc-derived O-GlcNAcylation levels increase with the decreased ferroptosis and chemosensitivity in cancer cells. Knockout of the rate-limiting enzyme GFPT1 in HBP metabolism inhibits O-GlcNAcylation, induces ferroptosis, and mitigates chemoresistance of orthotopic bladder cancer in Gfpt1^−/− mice. The global O-GlcNAcylation omics mapped the O-GlcNAcylated sites and proteins in resistant and nonresistant tumor cells, showing that NR3C1 is highly O-GlcNAcylated at Thr²⁹⁹ in response to chemotherapy. The chromatin immunoprecipitation sequencing delineates that NR3C1 O-GlcNAcylation at Thr²⁹⁹ prominently enhances transcriptional activity of GPX4 by facilitating the binding of NR3C1 on GPX4 promoter, inhibiting ferroptosis. Higher O-GlcNAcylation of NR3C1 improves protein stability and reduces proteasome-dependent degradation by suppressing ubiquitination. Inhibition of NR3C1 O-GlcNAcylation via Thr²⁹⁹ mutant or knockout of NR3C1 facilitates ferroptosis and improves chemosensitivity of resistant cancer cells in vitro and in vivo. In addition, we propose a novel predicting model for chemoresistance based on the GFPT1 and NR3C1 levels in pre-chemotherapy biopsy tissues through a training set and a validation set. These findings exemplify how metabolic and epigenetic reprogramming regulates ferroptosis via the GFPT1/NR3C1/GPX4 axis, and implicate NR3C1 O-GlcNAcylation as a potential target for reversing chemoresistance.