A pan-cancer single-cell transcriptional atlas of tumor infiltrating myeloid cells.

Tumor-infiltrating myeloid cells (TIMs) are key regulators in tumor progression, but the similarity and distinction of their fundamental properties across different tumors remain elusive. Here, by performing a pan-cancer analysis of single myeloid cells from 210 patients across 15 human cancer types, we identified distinct features of TIMs across cancer types. Mast cells in nasopharyngeal cancer were found to be associated with better prognosis and exhibited an anti-tumor phenotype with a high ratio of TNF+/VEGFA+ cells. Systematic comparison between cDC1- and cDC2-derived LAMP3+ cDCs revealed their differences in transcription factors and external stimulus. Additionally, pro-angiogenic tumor-associated macrophages (TAMs) were characterized with diverse markers across different cancer types, and the composition of TIMs appeared to be associated with certain features of somatic mutations and gene expressions. Our results provide a systematic view of the highly heterogeneous TIMs and suggest future avenues for rational, targeted immunotherapies.

Autonomous self-burying seed carriers for aerial seeding.

Aerial seeding can quickly cover large and physically inaccessible areas1 to improve soil quality and scavenge residual nitrogen in agriculture2, and for postfire reforestation3-5 and wildland restoration6,7. However, it suffers from low germination rates, due to the direct exposure of unburied seeds to harsh sunlight, wind and granivorous birds, as well as undesirable air humidity and temperature1,8,9. Here, inspired by Erodium seeds10-14, we design and fabricate self-drilling seed carriers, turning wood veneer into highly stiff (about 4.9 GPa when dry, and about 1.3 GPa when wet) and hygromorphic bending or coiling actuators with an extremely large bending curvature (1,854 m-1), 45 times larger than the values in the literature15-18. Our three-tailed carrier has an 80% drilling success rate on flat land after two triggering cycles, due to the beneficial resting angle (25°-30°) of its tail anchoring, whereas the natural Erodium seed's success rate is 0%. Our carriers can carry payloads of various sizes and contents including biofertilizers and plant seeds as large as those of whitebark pine, which are about 11 mm in length and about 72 mg. We compare data from experiments and numerical simulation to elucidate the curvature transformation and actuation mechanisms to guide the design and optimization of the seed carriers. Our system will improve the effectiveness of aerial seeding to relieve agricultural and environmental stresses, and has potential applications in energy harvesting, soft robotics and sustainable buildings.

Subtype-specific 3D genome alteration in acute myeloid leukaemia.

Acute myeloid leukaemia (AML) represents a set of heterogeneous myeloid malignancies, and hallmarks include mutations in epigenetic modifiers, transcription factors and kinases1-5. The extent to which mutations in AML drive alterations in chromatin 3D structure and contribute to myeloid transformation is unclear. Here we use Hi-C and whole-genome sequencing to analyse 25 samples from patients with AML and 7 samples from healthy donors. Recurrent and subtype-specific alterations in A/B compartments, topologically associating domains and chromatin loops were identified. RNA sequencing, ATAC with sequencing and CUT&Tag for CTCF, H3K27ac and H3K27me3 in the same AML samples also revealed extensive and recurrent AML-specific promoter-enhancer and promoter-silencer loops. We validated the role of repressive loops on their target genes by CRISPR deletion and interference. Structural variation-induced enhancer-hijacking and silencer-hijacking events were further identified in AML samples. Hijacked enhancers play a part in AML cell growth, as demonstrated by CRISPR screening, whereas hijacked silencers have a downregulating role, as evidenced by CRISPR-interference-mediated de-repression. Finally, whole-genome bisulfite sequencing of 20 AML and normal samples revealed the delicate relationship between DNA methylation, CTCF binding and 3D genome structure. Treatment of AML cells with a DNA hypomethylating agent and triple knockdown of DNMT1, DNMT3A and DNMT3B enabled the manipulation of DNA methylation to revert 3D genome organization and gene expression. Overall, this study provides a resource for leukaemia studies and highlights the role of repressive loops and hijacked cis elements in human diseases.

Non-KREEP origin for Chang'e-5 basalts in the Procellarum KREEP Terrane.

Mare volcanics on the Moon are the key record of thermo-chemical evolution throughout most of lunar history1-3. Young mare basalts-mainly distributed in a region rich in potassium, rare-earth elements and phosphorus (KREEP) in Oceanus Procellarum, called the Procellarum KREEP Terrane (PKT)4-were thought to be formed from KREEP-rich sources at depth5-7. However, this hypothesis has not been tested with young basalts from the PKT. Here we present a petrological and geochemical study of the basalt clasts from the PKT returned by the Chang'e-5 mission8. These two-billion-year-old basalts are the youngest lunar samples reported so far9. Bulk rock compositions have moderate titanium and high iron contents  with KREEP-like rare-earth-element and high thorium concentrations. However, strontium-neodymium isotopes indicate that these basalts were derived from a non-KREEP mantle source. To produce the high abundances of rare-earth elements and thorium, low-degree partial melting and extensive fractional crystallization are required. Our results indicate that the KREEP association may not be a prerequisite for young mare volcanism. Absolving the need to invoke heat-producing elements in their source implies a more sustained cooling history of the lunar interior to generate the Moon's youngest melts.

A genomic and epigenomic atlas of prostate cancer in Asian populations.

Prostate cancer is the second most common cancer in men worldwide1. Over the past decade, large-scale integrative genomics efforts have enhanced our understanding of this disease by characterizing its genetic and epigenetic landscape in thousands of patients2,3. However, most tumours profiled in these studies were obtained from patients from Western populations. Here we produced and analysed whole-genome, whole-transcriptome and DNA methylation data for 208 pairs of tumour tissue samples and matched healthy control tissue from Chinese patients with primary prostate cancer. Systematic comparison with published data from 2,554 prostate tumours revealed that the genomic alteration signatures in Chinese patients were markedly distinct from those of Western cohorts: specifically, 41% of tumours contained mutations in FOXA1 and 18% each had deletions in ZNF292 and CHD1. Alterations of the genome and epigenome were correlated and were predictive of disease phenotype and progression. Coding and noncoding mutations, as well as epimutations, converged on pathways that are important for prostate cancer, providing insights into this devastating disease. These discoveries underscore the importance of including population context in constructing comprehensive genomic maps for disease.

Dux activates metabolism-lactylation-MET network during early iPSC reprogramming with Brg1 as the histone lactylation reader.

The process of induced pluripotent stem cells (iPSCs) reprogramming involves several crucial events, including the mesenchymal-epithelial transition (MET), activation of pluripotent genes, metabolic reprogramming, and epigenetic rewiring. Although these events intricately interact and influence each other, the specific element that regulates the reprogramming network remains unclear. Dux, a factor known to promote totipotency during the transition from embryonic stem cells (ESC) to 2C-like ESC (2CLC), has not been extensively studied in the context of iPSC reprogramming. In this study, we demonstrate that the modification of H3K18la induced by Dux overexpression controls the metabolism-H3K18la-MET network, enhancing the efficiency of iPSC reprogramming through a metabolic switch and the recruitment of p300 via its C-terminal domain. Furthermore, our proteomic analysis of H3K18la immunoprecipitation experiment uncovers the specific recruitment of Brg1 during reprogramming, with both H3K18la and Brg1 being enriched on the promoters of genes associated with pluripotency and epithelial junction. In summary, our study has demonstrated the significant role of Dux-induced H3K18la in the early reprogramming process, highlighting its function as a potent trigger. Additionally, our research has revealed, for the first time, the binding of Brg1 to H3K18la, indicating its role as a reader of histone lactylation.

Revealing the mechanism of action of a first-in-class covalent inhibitor of KRASG12C (ON) and other functional properties of oncogenic KRAS by 31P NMR.

Individual oncogenic KRAS mutants confer distinct differences in biochemical properties and signaling for reasons that are not well understood. KRAS activity is closely coupled to protein dynamics and is regulated through two interconverting conformations: state 1 (inactive, effector binding deficient) and state 2 (active, effector binding enabled). Here, we use 31P NMR to delineate the differences in state 1 and state 2 populations present in WT and common KRAS oncogenic mutants (G12C, G12D, G12V, G13D, and Q61L) bound to its natural substrate GTP or a commonly used nonhydrolyzable analog GppNHp (guanosine-5'-[(ß,γ)-imido] triphosphate). Our results show that GppNHp-bound proteins exhibit significant state 1 population, whereas GTP-bound KRAS is primarily (90% or more) in state 2 conformation. This observation suggests that the predominance of state 1 shown here and in other studies is related to GppNHp and is most likely nonexistent in cells. We characterize the impact of this differential conformational equilibrium of oncogenic KRAS on RAF1 kinase effector RAS-binding domain and intrinsic hydrolysis. Through a KRAS G12C drug discovery, we have identified a novel small-molecule inhibitor, BBO-8956, which is effective against both GDP- and GTP-bound KRAS G12C. We show that binding of this inhibitor significantly perturbs state 1-state 2 equilibrium and induces an inactive state 1 conformation in GTP-bound KRAS G12C. In the presence of BBO-8956, RAF1-RAS-binding domain is unable to induce a signaling competent state 2 conformation within the ternary complex, demonstrating the mechanism of action for this novel and active-conformation inhibitor.

The MpNAC72/MpERF105-MpMYB10b module regulates anthocyanin biosynthesis in Malus 'Profusion' leaves infected with Gymnosporangium yamadae.

Apple rust is a serious fungal disease affecting Malus plants worldwide. Infection with the rust pathogen Gymnosporangium yamadae induces the accumulation of anthocyanins in Malus to resist rust disease. However, the mechanism of anthocyanin biosynthesis regulation in Malus against apple rust is still unclear. Here, we show that MpERF105 and MpNAC72 are key regulators of anthocyanin biosynthesis via the ethylene-dependent pathway in M. 'Profusion' leaves under rust disease stress. Exogenous ethephon treatment promoted high expression of MpERF105 and MpNAC72 and anthocyanin accumulation in G. yamadae-infected M. 'Profusion' leaves. Overexpression of MpERF105 increased the total anthocyanin content of Malus plant material and acted by positively regulating its target gene, MpMYB10b. MpNAC72 physically interacted with MpERF105 in vitro and in planta, and the two form a protein complex. Coexpression of the two leads to higher transcript levels of MpMYB10b and higher anthocyanin accumulation. In addition, overexpression of MpERF105 or MpNAC72 enhanced the resistance of M. 'Profusion' leaves to apple rust. In conclusion, our results elucidate the mechanism by which MpERF105 and MpNAC72 are induced by ethylene in G. yamadae-infected M. 'Profusion' leaves and promote anthocyanin accumulation by mediating the positive regulation of MpMYB10b expression.

Autocrine, Paracrine, and Endocrine Signals That Can Alter Alveolar Macrophages Function.

Alveolar macrophages (AMs) are extremely versatile cells with complex functions involved in health or diseases such as pneumonia, asthma, and pulmonary alveolar proteinosis. In recent years, it has been widely identified that the different functions and states of macrophages are the results from the complex interplay between microenvironmental signals and macrophage lineage. Diverse and complicated signals to which AMs respond are mentioned when they are described individually or in a particular state of AMs. In this review, the microenvironmental signals are divided into autocrine, paracrine, and endocrine signals based on their secreting characteristics. This new perspective on classification provides a more comprehensive and systematic introduction to the complex signals around AMs and is helpful for understanding the roles of AMs affected by physiological environment. The existing possible treatments of AMs are also mentioned in it. The thorough understanding of AMs signals modulation may be contributed to the development of more effective therapies for AMs-related lung diseases.

Incorporating higher order network structures to improve miRNA-disease association prediction based on functional modularity.

As microRNAs (miRNAs) are involved in many essential biological processes, their abnormal expressions can serve as biomarkers and prognostic indicators to prevent the development of complex diseases, thus providing accurate early detection and prognostic evaluation. Although a number of computational methods have been proposed to predict miRNA-disease associations (MDAs) for further experimental verification, their performance is limited primarily by the inadequacy of exploiting lower order patterns characterizing known MDAs to identify missing ones from MDA networks. Hence, in this work, we present a novel prediction model, namely HiSCMDA, by incorporating higher order network structures for improved performance of MDA prediction. To this end, HiSCMDA first integrates miRNA similarity network, disease similarity network and MDA network to preserve the advantages of all these networks. After that, it identifies overlapping functional modules from the integrated network by predefining several higher order connectivity patterns of interest. Last, a path-based scoring function is designed to infer potential MDAs based on network paths across related functional modules. HiSCMDA yields the best performance across all datasets and evaluation metrics in the cross-validation and independent validation experiments. Furthermore, in the case studies, 49 and 50 out of the top 50 miRNAs, respectively, predicted for colon neoplasms and lung neoplasms have been validated by well-established databases. Experimental results show that rich higher order organizational structures exposed in the MDA network gain new insight into the MDA prediction based on higher order connectivity patterns.

PITX2 functions as a transcription factor for GPX4 and protects pancreatic cancer cells from ferroptosis.

Ferroptosis inhibits tumor progression in pancreatic cancer cells, while PITX2 is known to function as a pro-oncogenic factor in various tumor types, protecting them from ferroptosis and thereby promoting tumor progression. In this study, we sought to investigate the regulatory role of PITX2 in tumor cell ferroptosis within the context of pancreatic cancer. We conducted PITX2 knockdown experiments using lentiviral infection in two pancreatic cancer cell lines, namely PANC-1 and BxPC-3. We assessed protein expression through immunoblotting and mRNA expression through RT-PCR. To confirm PITX2 as a transcription factor for GPX4, we employed Chromatin Immunoprecipitation (ChIP) and Dual-luciferase assays. Furthermore, we used flow cytometry to measure reactive oxygen species (ROS), lipid peroxidation, and apoptosis and employed confocal microscopy to assess mitochondrial membrane potential. Additionally, electron microscopy was used to observe mitochondrial structural changes and evaluate PITX2's regulation of ferroptosis in pancreatic cancer cells. Our findings demonstrated that PITX2, functioning as a transcription factor for GPX4, promoted GPX4 expression, thereby exerting an inhibitory effect on ferroptosis in pancreatic cancer cells and consequently promoting tumor progression. Moreover, PITX2 enhanced the invasive and migratory capabilities of pancreatic cancer cells by activating the WNT signaling pathway. Knockdown of PITX2 increased ferroptosis and inhibited the proliferation of PANC-1 and BxPC-3 cells. Notably, the inhibitory effect on ferroptosis resulting from PITX2 overexpression in these cells could be countered using RSL3, an inhibitor of GPX4. Overall, our study established PITX2 as a transcriptional regulator of GPX4 that could promote tumor progression in pancreatic cancer by reducing ferroptosis. These findings suggest that PITX2 may serve as a potential therapeutic target for combating ferroptosis in pancreatic cancer.

Sensory experience remodels genome architecture in neural circuit to drive motor learning.

Neuronal-activity-dependent transcription couples sensory experience to adaptive responses of the brain including learning and memory. Mechanisms of activity-dependent gene expression including alterations of the epigenome have been characterized1-8. However, the fundamental question of whether sensory experience remodels chromatin architecture in the adult brain in vivo to induce neural code transformations and learning and memory remains to be addressed. Here we use in vivo calcium imaging, optogenetics and pharmacological approaches to show that granule neuron activation in the anterior dorsal cerebellar vermis has a crucial role in a delay tactile startle learning paradigm in mice. Of note, using large-scale transcriptome and chromatin profiling, we show that activation of the motor-learning-linked granule neuron circuit reorganizes neuronal chromatin including through long-distance enhancer-promoter and transcriptionally active compartment interactions to orchestrate distinct granule neuron gene expression modules. Conditional CRISPR knockout of the chromatin architecture regulator cohesin in anterior dorsal cerebellar vermis granule neurons in adult mice disrupts enhancer-promoter interactions, activity-dependent transcription and motor learning. These findings define how sensory experience patterns chromatin architecture and neural circuit coding in the brain to drive motor learning.

Publisher Correction: Sensory experience remodels genome architecture in neural circuit to drive motor learning.

In this Letter, '≥' should be '≤' in the sentence: "Intra-chromosomal reads were further split into short-range reads (≥1 kb) and long-range reads (>1 kb)". This error has been corrected online.An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Machine learning-driven multiscale modeling reveals lipid-dependent dynamics of RAS signaling proteins.

RAS is a signaling protein associated with the cell membrane that is mutated in up to 30% of human cancers. RAS signaling has been proposed to be regulated by dynamic heterogeneity of the cell membrane. Investigating such a mechanism requires near-atomistic detail at macroscopic temporal and spatial scales, which is not possible with conventional computational or experimental techniques. We demonstrate here a multiscale simulation infrastructure that uses machine learning to create a scale-bridging ensemble of over 100,000 simulations of active wild-type KRAS on a complex, asymmetric membrane. Initialized and validated with experimental data (including a new structure of active wild-type KRAS), these simulations represent a substantial advance in the ability to characterize RAS-membrane biology. We report distinctive patterns of local lipid composition that correlate with interfacially promiscuous RAS multimerization. These lipid fingerprints are coupled to RAS dynamics, predicted to influence effector binding, and therefore may be a mechanism for regulating cell signaling cascades.

Artificial intelligence-based radiomics in bone tumors: Technical advances and clinical application.

Radiomics is the extraction of predefined mathematic features from medical images for predicting variables of clinical interest. Recent research has demonstrated that radiomics can be processed by artificial intelligence algorithms to reveal complex patterns and trends for diagnosis, and prediction of prognosis and response to treatment modalities in various types of cancer. Artificial intelligence tools can utilize radiological images to solve next-generation issues in clinical decision making. Bone tumors can be classified as primary and secondary (metastatic) tumors. Osteosarcoma, Ewing sarcoma, and chondrosarcoma are the dominating primary tumors of bone. The development of bone tumor model systems and relevant research, and the assessment of novel treatment methods are ongoing to improve clinical outcomes, notably for patients with metastases. Artificial intelligence and radiomics have been utilized in almost full spectrum of clinical care of bone tumors. Radiomics models have achieved excellent performance in the diagnosis and grading of bone tumors. Furthermore, the models enable to predict overall survival, metastases, and recurrence. Radiomics features have exhibited promise in assisting therapeutic planning and evaluation, especially neoadjuvant chemotherapy. This review provides an overview of the evolution and opportunities for artificial intelligence in imaging, with a focus on hand-crafted features and deep learning-based radiomics approaches. We summarize the current application of artificial intelligence-based radiomics both in primary and metastatic bone tumors, and discuss the limitations and future opportunities of artificial intelligence-based radiomics in this field. In the era of personalized medicine, our in-depth understanding of emerging artificial intelligence-based radiomics approaches will bring innovative solutions to bone tumors and achieve clinical application.

The Arabidopsis pre-mRNA 3' end processing related protein FIP1 promotes seed dormancy via the DOG1 and ABA pathways.

Seed dormancy is an important adaptive trait to prevent germination occurring at an inappropriate time. The mechanisms governing seed dormancy and germination are complex. Here, we report that FACTOR INTERACTING WITH POLY(A) POLYMERASE 1 (FIP1), a component of the pre-mRNA 3' end processing machinery, is involved in seed dormancy and germination processes in Arabidopsis thaliana. FIP1 is mainly expressed in seeds and the knockout of FIP1 causes reduced seed dormancy, indicating that FIP1 positively influences seed dormancy. Meanwhile, fip1 mutants are insensitive to exogenous ABA during seed germination and early seedling establishment. The terms 'seed maturation' and 'response to ABA stimulus' are significantly enriched in a gene ontology analysis based on genes differentially expressed between fip1-1 and the wild type. Several of these genes, including ABI5, DOG1 and PYL12, show significantly decreased transcript levels in fip1. Genetic analysis showed that either cyp707a2 or dog1-5 partially, but in combination completely, represses the reduced seed dormancy of fip1, indicating that the double mutant cyp707a2 dog1-5 is epistatic to fip1. Moreover, FIP1 is required for CFIM59, another component of pre-mRNA 3' end processing machinery, to govern seed dormancy and germination. Overall, we identified FIP1 as a regulator of seed dormancy and germination that plays a crucial role in governing these processes through the DOG1 and ABA pathways.

Predicting neurodegeneration from sleep related biofluid changes.

Sleep-wake disturbances are common in neurodegenerative diseases and may occur years before the clinical diagnosis, potentially either representing an early stage of the disease itself or acting as a pathophysiological driver. Therefore, discovering biomarkers that identify individuals with sleep-wake disturbances who are at risk of developing neurodegenerative diseases will allow early diagnosis and intervention. Given the association between sleep and neurodegeneration, the most frequently analyzed fluid biomarkers in people with sleep-wake disturbances to date include those directly associated with neurodegeneration itself, such as neurofilament light chain, phosphorylated tau, amyloid-beta and alpha-synuclein. Abnormalities in these biomarkers in patients with sleep-wake disturbances are considered as evidence of an underlying neurodegenerative process. Levels of hormonal sleep-related biomarkers such as melatonin, cortisol and orexin are often abnormal in patients with clinical neurodegenerative diseases, but their relationships with the more standard neurodegenerative biomarkers remain unclear. Similarly, it is unclear whether other chronobiological/circadian biomarkers, such as disrupted clock gene expression, are causal factors or a consequence of neurodegeneration. Current data would suggest that a combination of fluid biomarkers may identify sleep-wake disturbances that are most predictive for the risk of developing neurodegenerative disease with more optimal sensitivity and specificity.

A novel iTreg-related signature for prognostic prediction in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer. Most patients are diagnosed at an advanced stage, therefore it is crucial to identify novel prognostic biomarkers for LUAD. As important regulatory cells, inducible regulatory T cells (iTregs) play a vital role in immune suppression and are important for the maintenance of immune homeostasis. This study explored the prognostic value and therapeutic effects of iTreg-related genes in LUAD. Data for LUAD patients, including immune infiltration data, RNA sequencing data, and clinical features, were acquired from The Cancer Genome Atlas, Gene Expression Omnibus, and Tumor Immune Single-cell Hub 2 databases. Immune-related subgroups with different infiltration patterns and iTreg-related genes were identified through univariate and multivariate Cox regression analyses and weighted correlation network analysis. Functional enrichment analyses were performed to explore the underlying mechanisms of iTreg-related genes. A prognostic risk signature was constructed using Cox regression analysis with the least absolute shrinkage and selection operator penalty. The ESTIMATE algorithm was applied to determine the immune status of LUAD patients. We applied the constructed signature to predict chemosensitivity and performed single-cell RNA sequencing analysis. The infiltration of iTregs was identified as an independent factor for predicting patient outcomes. We constructed a prognostic signature based on seven iTreg-related genes (GIMAP5, SLA, MS4A7, ZNF366, POU2AF1, MRPL12, and COL5A1), which was applied to subdivide patients into high- and low-risk subgroups. Our results revealed that patients in the iTreg-related low-risk subgroup had a better prognosis and possibly greater sensitivity to traditional chemotherapy. Our study provides a novel iTreg-related signature to elucidate the mechanisms underlying LUAD prognosis and promote individualized chemotherapy treatment.

A Dual-Modal, Label-Free Raman Imaging Method for Rapid Virtual Staining of Large-Area Breast Cancer Tissue Sections.

As one of the most common cancers, accurate, rapid, and simple histopathological diagnosis is very important for breast cancer. Raman imaging is a powerful technique for label-free analysis of tissue composition and histopathology, but it suffers from slow speed when applied to large-area tissue sections. In this study, we propose a dual-modal Raman imaging method that combines Raman mapping data with microscopy bright-field images to achieve virtual staining of breast cancer tissue sections. We validate our method on various breast tissue sections with different morphologies and biomarker expressions and compare it with the golden standard of histopathological methods. The results demonstrate that our method can effectively distinguish various types and components of tissues, and provide staining images comparable to stained tissue sections. Moreover, our method can improve imaging speed by up to 65 times compared to general spontaneous Raman imaging methods. It is simple, fast, and suitable for clinical applications.

Designing Urchin-Like S@SiO2 with Regulated Pores Toward Ultra-Fast Room Temperature Sodium-Sulfur Battery.

Captured by high theoretical capacity and low-cost, Sodium-Sulfur (Na-S) batteries have been deemed as promising energy-storage systems. However, their electrochemical properties, containing both cycling and rate properties, still suffer from the notorious "shuttle effect" of polysulfide. Herein, through the effective regulation of pore sizes, a series of S@SiO2 cathode materials are obtained. Benefitting from the abundant pore channels of SiO2 particles, the sulfur loading is as high as 76.3%. Importantly, a suitable pore size can lead to adequate reaction and rapid diffusion behaviors, resulting in excellent electrochemical performances. Specifically, at 2.0 A g-1, the initial capacity of the as-optimized sample can be up to 1370.6 mAh g-1. Surprisingly, even after 1050 cycles, it could achieve a high reversible capacity of 1280.8 mAh g-1 with an attenuation rate of 0.089%. At 5.0 A g-1, after 500 cycles, the capacity can still remain ≈ 1132.6 mAh g-1 (capacity retention rate, 97.5%). Given this, the work is anticipated to offer an effective strategy for advanced electrodes for Na-S batteries.