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Tumor necrosis factor receptor-associated factor 6 (TRAF6) is crucial in flavivirus infections, modulating the host immune response through interactions with viral proteins. Despite its importance, the relationship between TRAF6 and Zika virus (ZIKV) remains poorly understood. Our prior proteomics analysis revealed reduced TRAF6 protein levels in ZIKV-infected human trophoblast cells compared to non-infected controls. Subsequent studies in cell models and murine tissues confirmed a significant reduction in both TRAF6 mRNA and protein levels post-ZIKV infection. Further investigations unveiled that ZIKV induces P62-mediated degradation of TRAF6, with NS1 identified as the primary contributor. Co-localization and interaction studies demonstrated that NS1 promotes the association of P62, a key autophagy mediator, with TRAF6. Notably, our findings revealed TRAF6 enhances ZIKV infection, NS1 ubiquitination, NS1 expression, and the production of inflammatory cytokines and chemokines. These insights highlight the intricate TRAF6-ZIKV relationship, offering potential for drug targeting NS1-TRAF6 interactions to manage ZIKV infections effectively.

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Ongoing warming will influence plant photosynthesis via thermal effects and by enhancing water deficit. As the primary limiting factor for the growth and development of plants in arid deserts, water may alter the potential warming effects on plant photosynthesis and lead to increased uncertainty in plant dynamics. Here, we used open-top chambers (OTCs) to evaluate the impacts of in situ warming (+0.5 and +1.5 °C) on the photosynthesis and growth of two representative desert plants, Artemisia ordosica and Grubovia dasyphylla, from wet to dry spells. The plant traits associated with photosynthetic diffusive and biochemical processes were also measured to explore the underlying mechanisms involved. We found that warming significantly increased the net photosynthetic rate (Anet) during wet spells under 1.5 °C warming in both plants, while only increased that of A. ordosica under 0.5 °C warming. During dry spells, Anet decreased both in A. ordosica and G. dasyphylla, with the rates of declining being 48 % and 41 %, respectively, higher than control under warming. Consequently, warming significantly amplified photosynthetic responses to drought events, which offset the positive warming effects during wet spells and led to unchanged plant biomass in both species. Besides, alterations in plant traits tended to be associated with positive warming effects during wet spells, and the negative effects of drought were mainly due to stomatal limitation. Our results emphasised that the potential benefits of warming during wet spells may be reversed during drought events. Thus, the adverse effects of ongoing warming on desert productivity may increase during dry spells in growing seasons and during dry years.

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Breast cancer is the most prevalent malignant tumor among women with high heterogeneity. Traditional techniques frequently struggle to comprehensively capture the intricacy and variety of cellular states and interactions within breast cancer. As global precision medicine rapidly advances, single-cell RNA sequencing (scRNA-seq) has become a highly effective technique, revolutionizing breast cancer research by offering unprecedented insights into the cellular heterogeneity and complexity of breast cancer. This cutting-edge technology facilitates the analysis of gene expression profiles at the single-cell level, uncovering diverse cell types and states within the tumor microenvironment. By dissecting the cellular composition and transcriptional signatures of breast cancer cells, scRNA-seq provides new perspectives for understanding the mechanisms behind tumor therapy, drug resistance and metastasis in breast cancer. In this review, we summarized the working principle and workflow of scRNA-seq and emphasized the major applications and discoveries of scRNA-seq in breast cancer research, highlighting its impact on our comprehension of breast cancer biology and its potential for guiding personalized treatment strategies.

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GM1 gangliosidosis is a lysosomal storage disorder characterized by the accumulation of GM1 ganglioside, leading to severe neurodegeneration and early mortality. The disease primarily affects the central nervous system, causing progressive neurodegeneration, including widespread neuronal loss and gliosis. To gain a deeper understanding of the neuropathology associated with GM1 gangliosidosis, we employed single-nucleus RNA sequencing to analyze brain tissues from both GM1 gangliosidosis model mice and control mice. No significant changes in cell proportions were detected between the two groups of animals. Differential expression analysis revealed cell type-specific changes in gene expression in neuronal and glial cells. Functional analysis highlighted the neurodegenerative processes, oxidative phosphorylation, and neuroactive ligand-receptor interactions as the significantly affected pathways. The contribution of the impairment of neurotransmitter system disruption and neuronal circuitry disruption was more important than neuroinflammatory responses to GM1 pathology. In 16-week-old GM1 gangliosidosis mice, no microglial or astrocyte activation or increased expression of innate immunity genes was detected. This suggested that nerve degeneration did not induce the inflammatory response but rather promoted glial cell clearance. Our findings provide a crucial foundation for understanding the cellular and molecular mechanisms of GM1 gangliosidosis, potentially guiding future therapeutic strategies.

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BACKGROUND: Understanding the impact of environmental factors on physical activity (PA) and physical fitness (PF) is crucial for promoting a healthy lifestyle among children and adolescents. This study examines how awareness of sports policies, school, family, and community environments influence PA and PF in Chinese youth. METHODS: A cross-sectional study was conducted with 2747 children and adolescents (mean age 12.90 ± 2.49; 48.2% male) from 17 schools across five Chinese cities. Environmental factors were assessed via questionnaires, and PA levels were measured using the International Physical Activity Questionnaire-Short Form (IPAQ-SF). PF metrics, including BMI, waist-to-height ratio, grip strength, vertical jump, and 20-m shuttle run test (20-mSRT), were measured onsite. Structural Equation Modeling (SEM) was used to explore relationships between environmental factors and PA/PF outcomes. RESULTS: The school environment scored highest (78.0 ± 9.5), while the community environment scored lowest (38.7 ± 18.0). Family environment positively influenced low-intensity PA (LPA) (ß = 0.102, P < 0.001) but negatively affected moderate-to-vigorous PA (MVPA) (ß = -0.055, P = 0.035). Community environment and awareness of sports policies positively impacted MVPA (ß = 0.216, P < 0.001; ß = 0.072, P = 0.009, respectively). Family environment positively influenced BMI reduction (ß = -0.103, P < 0.001) but negatively affected grip strength (ß = -0.063, P = 0.018). Community environment improved grip strength and 20-mSRT performance (ß = 0.088, P = 0.002; ß = 0.065, P = 0.027). CONCLUSIONS: School environments, despite high scores, do not significantly impact PA and PF. Community environments, though scoring lower, positively affect MVPA, grip strength, and 20-mSRT. Awareness of sports policies boosts MVPA, while family environments support LPA and BMI but are inversely related to MVPA and grip strength. Integrated strategies involving community infrastructure, family support, and policy awareness are essential for promoting active lifestyles among children and adolescents.

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The goal of few-shot segmentation (FSS) is to segment unlabeled images belonging to previously unseen classes using only a limited number of labeled images. The main objective is to transfer label information effectively from support images to query images. In this study, we introduce a novel meta-learning framework called layer-wise mutual information (LayerMI), which enhances the propagation of label information by maximizing the mutual information (MI) between support and query features at each layer. Our approach involves the utilization of a LayerMI Block based on information-theoretic co-clustering. This block performs online co-clustering on the joint probability distribution obtained from each layer, generating a target-specific attention map. The LayerMI Block can be seamlessly integrated into the meta-learning framework and applied to all convolutional neural network (CNN) layers without altering the training objectives. Notably, the LayerMI Block not only maximizes MI between support and query features but also facilitates internal clustering within the image. Extensive experiments demonstrate that LayerMI significantly enhances the performance of baseline and achieves competitive performance compared to state-of-the-art methods on three challenging benchmarks: PASCAL-5 i , COCO-20 i , and FSS-1000.

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BACKGROUND: In patients with schizophrenia, Diankuang Mengxing Decoction with antipsychotics is one of the treatments for it. However, little information is available regarding the difference between the therapeutic effect of Diankuang Mengxing Decoction with antipsychotics and other treatments. Systematic evaluation is conducted to assess the efficacy and safety of Diankuang Mengxing Decoction and other antipsychotics, which are used to treat schizophrenia. METHODS: We performed a systematic review (PROSPERO ID: CRD42023414603). This entailed a computerized search of several research databases from their respective dates of establishment until April 11, 2023, which collected clinical randomized controlled trials of Diankuang Mengxing Decoction combined with antipsychotics. The databases that contributed to this study were PubMed, Web of Science, Embase, EBSCOhost, Cochrane, Scopus, and Google Scholar. Each publication was screened according to defined inclusion and exclusion criteria, and appropriate literature was extracted and evaluated for quality, for which meta-analysis was performed using RevMan 5.4. RESULTS: A literature review of 456 publications resulted in the inclusion of 18 randomized controlled trials with data collected from a total of 1636 patients. Meta-analytical results showed combination with risperidone, olanzapine, chlorpromazine, clozapine, ziprasidone, or aripiprazole increased the overall effectiveness of Diankuang Mengxing Decoction when treating schizophrenia (P < . 00001), among whom olanzapine demonstrated the greatest enhancement (Z = 3.65, odds ratio = 4.26, 95% CI: 1.96-9.28, P = .0003). The 4-week/30-day treatment (P = .0003) and a dosage of 400 mL/d of Diankuang Mengxing Decoction (P = .0004) were more effective. Also, there were widespread reductions to the Positive And Negative Syndrome Scale (PANSS) total scores, PANSS-positive symptom scores, PANSS-negative symptom scores, general psychopathology scores (P < .05 for all), as well as the incidence of adverse effects (Z = 2.79, odds ratio = 0.34, 95% CI: 0.16-0.73, P = .005) in patients with schizophrenia. CONCLUSION: The combination of Diankuang Mengxing Decoction with different antipsychotics can improve the overall prognosis of patients with schizophrenia; Diankuang Mengxing Decoction combined olanzapine, a dosage of 400 mL/d and a duration of 4 weeks/30 days being the best in this regard, by alleviating the symptoms and diminishing the disorder's adverse effects. To build on this work, more large-sample, multi-center, and high-quality clinical studies in the future would help to further validate our findings.

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BACKGROUND: Influenza viruses pose a persistent threat to global public health, necessitating the development of innovative and broadly effective vaccines. METHODS: This study focuses on a multiepitope vaccine (MEV) designed to provide broad-spectrum protection against different influenza viruses. The MEV, containing 19 B-cell linear epitopes, 7 CD4+ T cells, and 11 CD8+ T cells epitopes identified through enzyme-linked immunospot assay (ELISPOT) in influenza viruses infected mice, was administered through a regimen of two doses of DNA vaccine followed by one dose of a protein vaccine in C57BL/6 female mice. FINDINGS: Upon lethal challenge with both seasonal circulating strains (H1N1, H3N2, BV, and BY) and historical strains (H1N1-PR8 and H3N2-X31), MEV demonstrated substantial protection against different influenza seasonal strains, with partial efficacy against historical strains. Notably, the increased germinal centre B cells and antibody-secreting cells, along with robust T cell immune responses, highlighted the comprehensive immune defence elicited by MEV. Elevated hemagglutinin inhibition antibody was also observed against seasonal circulating and historical strains. Additionally, mice vaccinated with MEV exhibited significantly lower counts of inflammatory cells in the lungs compared to negative control groups. INTERPRETATION: Our results demonstrated the efficacy of a broad-spectrum MEV against influenza viruses in mice. Conducting long-term studies to evaluate the durability of MEV-induced immune responses and explore its potential application in diverse populations will offer valuable insights for the continued advancement of this promising vaccine. FUNDING: Funding bodies are described in the Acknowledgments section.

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Electrocatalytic H2 production from seawater, recognized as a promising technology utilizing offshore renewables, faces challenges from chloride-induced reactions and corrosion. Here, We introduce a catalytic surface where OH- dominates over Cl- in adsorption and activation, which is crucial for O2 production. Our NiFe-based anode, enhanced by nearby Cr sites, achieves low overpotentials and selective alkaline seawater oxidation. It outperforms the RuO2 counterpart in terms of lifespan in scaled-up stacks, maintaining stability for over 2500 h in three-electrode tests. Ex situ/in situ analyses reveal that Cr(III) sites enrich OH-, while Cl- is repelled by Cr(VI) sites, both of which are well-dispersed and close to NiFe, enhancing charge transfer and overall electrode performance. Such multiple effects fundamentally boost the activity, selectively, and chemical stability of the NiFe-based electrode. This development marks a significant advance in creating durable, noble-metal-free electrodes for alkaline seawater electrolysis, highlighting the importance of well-distributed catalytic sites.

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To explore the impacts of cytomegalovirus (CMV) infection and antiviral treatment (AVT) on native liver survival (NLS) in biliary atresia (BA) infants. This retrospective cohort study included infants diagnosed as BA between January 2015 and December 2021 at Hunan Children's Hospital. CMV infection was defined by DNA polymerase chain reaction alone (DNA data set) and combination of DNA and immunoglobulin M (CMV data set). In the DNA data set of 330 patients, 234 patients (70.9%) survived with their native liver in 2 years, with 113 (73.9%) in the DNA- cohort, 70 (65.4%) in the DNA+ and AVT- cohort and 51 (72.9%) in the DNA+ and AVT+ cohort, without significant differences by log-rank tests. In patients administrated between 2015 and March 2019, there were 206 evaluable patients in the DNA data set, with rates of 5-year NLS of 68.3% in the DNA- cohort, similar to that in the DNA+ and AVT+ cohort (62.2%, p = 0.546), but significantly higher than that in the DNA+ and AVT- cohort (51.4%, p = 0.031). Similar trends were also observed in the CMV data set, although statistically insignificant. CMV infection before or on the day of HPE can reduce the rate of 5-year NLS and AVT was recommended for CMV-infected BA infants.

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Chordin-like 1 (CHRDL1) is a secreted protein that serves as an endogenous antagonist of bone morphogenetic proteins (BMPs). In the developing retina, Bmp4 has been demonstrated to be essential for sustaining the proliferation of progenitor cells and facilitating the differentiation of glial cells. Despite these efforts, the precise effects of Bmp4 inhibition on the developing retina are yet to be fully understood. We sought to address this question by overexpressing Chrdl1 in the developing retina. In this study, we explored the impact of Bmp4 inhibition on the developing mouse retina by conditionally overexpressing the Bmp4 inhibitor Chrdl1. Initially, we characterized the expression patterns of Bmp4 and Chrdl1 in the developing mouse retina from E10.5 to P12.5. Additionally, we utilized various molecular markers to demonstrate that Bmp4 inhibition disrupts both neuronal and Müller glial differentiation in the developing mouse retina. Moreover, through the application of RNA-seq analysis, distinctively expressed retinal genes under the modulation of Bmp4 signaling were discerned, encompassing the upregulation of Id1/2/3/4 and Hes1/5, as well as the downregulation of Neurod1/2/4 and Bhlhe22/23. Lastly, electroretinogram (ERG) and optomotor response (OMR) assays were conducted to illustrate that Bmp4 inhibition impairs the functional connectivity of various cells in the retina and consequently affects visual function. Collectively, this study demonstrates that inhibiting Bmp4 promotes the differentiation of retinal neurons over Müller glia by activating the expression of genes associated with neuron specification. These findings offer molecular insights into the role of Bmp4 signaling in mammalian retinal development.

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Chromosome instability (CIN) and subsequent aneuploidy are prevalent in various human malignancies, influencing tumor progression such as metastases and relapses. Extensive studies demonstrate the development of chemoresistance in high-CIN tumors, which poses significant therapeutic challenges. Given the association of CIN with poorer prognosis and suppressed immune microenvironment observed in colorectal carcinoma (CRC), here we aimed to discover chemotherapeutic drugs exhibiting increased inhibition against high-CIN CRC cells. By using machine learning methods, we screened out two BCL-XL inhibitors Navitoclax and WEHI-539 as CIN-sensitive reagents in CRC. Subsequent analyses using a CIN-aneuploidy cell model confirmed the vulnerability of high-CIN CRC cells to these drugs. We further revealed the critical role of BCL-XL in the viability of high-CIN CRC cells. In addition, to ease the evaluation of CIN levels in clinic, we developed a three-gene signature as a CIN surrogate to predict prognosis, chemotherapeutic and immune responses in CRC samples. Our results demonstrate the potential value of CIN as a therapeutic target in CRC treatment and the importance of BCL-XL in regulating survival of high-CIN CRC cells, therefore representing a valuable attempt to translate a common trait of heterogeneous tumor cells into an effective therapeutic target.

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Artificial intelligence (AI) can acquire characteristics that are not yet known to humans through extensive learning, enabling to handle large amounts of pathology image data. Divided into machine learning and deep learning, AI has the advantage of handling large amounts of data and processing image analysis, consequently it also has a great potential in accurately assessing tumour microenvironment (TME) models. With the complex composition of the TME, in-depth study of TME contributes to new ideas for treatment, assessment of patient response to postoperative therapy and prognostic prediction. This leads to a review of the development of AI's application in TME assessment in this study, provides an overview of AI techniques applied to medicine, delves into the application of AI in analysing the quantitative and spatial location characteristics of various cells (tumour cells, immune and non-immune cells) in the TME, reveals the predictive prognostic value of TME and provides new ideas for tumour therapy, highlights the great potential for clinical applications. In addition, a discussion of its limitations and encouraging future directions for its practical clinical application is presented.

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Effectively regulating monomer and excimer emission in a singular supramolecular luminous platform is challenging due to high difficulty of precise control over its aggregation and dispersion behavior when subjected to external stimuli. Here, we show a metallo-cage (MTH) featuring a triple helical motif that displays a unique dual emission. It arises from both intramolecular monomer and intermolecular excimer, respectively. The distorted molecular conformation and the staggered stacking mode of MTH excimer are verified through single crystal X-ray diffraction analysis. These structural features facilitate the switch between monomer and excimer emission, which are induced by changes in concentration and temperature. Significantly, adjusting the equilibrium between these two states in MTH enables the production of vibrant white light emission in both solution and solid state. Moreover, when combined with a PMMA (polymethyl methacrylate) substrate, the resulting thin films can serve as straightforward fluorescence thermometer and thermally activated information encryption materials.

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Cell-cell interactions are essential components of coordinated cell function in lung homeostasis. Lung diseases involve altered cell-cell interactions and communication between different cell types, as well as between subsets of cells of the same type. The identification and understanding of intercellular signaling in lung fibrosis offer insights into the molecular mechanisms underlying these interactions and their implications in the development and progression of lung fibrosis. A comprehensive cell atlas of the human lung, established with the facilitation of single-cell RNA transcriptomic analysis, has enabled the inference of intercellular communications using ligand-receptor databases. In this review, we provide a comprehensive overview of the modified cell-cell communications in lung fibrosis. We highlight the intricate interactions among the major cell types within the lung and their contributions to fibrogenesis. The insights presented in this review will contribute to a better understanding of the molecular mechanisms underlying lung fibrosis and may guide future research efforts in developing targeted therapies for this debilitating disease.

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Being one of the pivotal adipocytokines, adiponectin binds to various receptors and exerts diverse biological functions, encompassing anti-fibrosis, anti-atherosclerosis, anti-ischemia-reperfusion, regulation of inflammation, and modulation of glucose and lipid metabolism. Alterations in adiponectin levels are observed in patients afflicted with diverse cardiovascular diseases. This paper comprehensively reviews the impact of adiponectin on the pathogenesis and progression of cardiovascular diseases, elucidating the underlying cellular and molecular mechanisms along with the associated cell signaling pathways. Furthermore, it deliberates on the diagnostic and predictive efficacy of adiponectin as a protein marker for cardiovascular diseases. Additionally, it outlines methods for manipulating adiponectin levels in vivo. A thorough understanding of these interconnections can potentially inform clinical strategies for the prevention and management of cardiovascular diseases.

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Polyethylene oxide (PEO)-based all solid-state lithium metal batteries (ASSLMBs) are strongly hindered by the fast dendrite growth at the Li metal/electrolyte interface, especially under large rates. The above issue stems from the suboptimal interfacial chemistry and poor Li+ transport kinetics during cycling. Herein, a SnF2-catalyzed lithiophilic-lithiophobic gradient solid electrolyte interphase (SCG-SEI) of LixSny/LiF-Li2O is in-situ formed. The superior ionic LiF-Li2O rich upper layer (17.1 nm) possesses high interfacial energy and fast Li+ diffusion channels, wherein lithiophilic LixSny alloy layer (8.4 nm) could highly reduce the nucleation overpotential with lower diffusion barrier and promote rapid electron transportation for reversible Li+ plating/stripping. Simultaneously, the insoluble SnF2-coordinated PEO promotes the rapid Li+ ion transport in the bulk phase. As a result, an over 46.7 and 3.5 times improvements for lifespan and critical current density of symmetrical cells are achieved, respectively. Furthermore, LiFePO4-based ASSLMBs deliver a recorded cycling performance at 5 C (over 1000 cycles with a capacity retention of 80.0%). More importantly, impressive electrochemical performances and safety tests with LiNi0.8Mn0.1Co0.1O2 and pouch cell with LiFePO4, even under extreme conditions (i.e., 100 ℃), are also demonstrated, reconfirmed the importance of lithiophilic-lithiophobic gradient interfacial chemistry in the design of high-rate ASSLMBs for safety applications.

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Sandification can degrade the strength and quality of dolomite, and to a certain extent, compromise the stability of a tunnel's surrounding rock as an unfavorable geological boundary. Sandification degree classification of sandy dolomite is one of the non-trivial challenges faced by geotechnical engineering projects such as tunneling in complex geographical environments. The traditional methods quantitatively measuring the physical parameters or analyzing some visual features are either time-consuming or inaccurate in practical use. To address these issues, we, for the first time, introduce the convolutional neural network (CNN)-based image classification methods into dolomite sandification degree classification task. In this study, we have made a significant contribution by establishing a large-scale dataset comprising 5729 images, classified into four distinct sandification degrees of sandy dolomite. These images were collected from the vicinity of a tunnel located in the Yuxi section of the CYWD Project in China. We conducted comprehensive classification experiments using this dataset. The results of these experiments demonstrate the groundbreaking achievement of CNN-based models, which achieved an impressive accuracy rate of up to 91.4%. This accomplishment underscores the pioneering role of our work in creating this dataset and its potential for applications in complex geographical analyses.

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Pullulanases are important starch-debranching enzymes that mainly hydrolyze the α-1,6-glycosidic linkages in pullulan, starch, and oligosaccharides. Nevertheless, their practical applications are constrained because of their poor activity and low thermostability. Moreover, the trade-off between activity and thermostability makes it challenging to simultaneously improve them. In this study, an engineered pullulanase was developed through reshaping the active-site tunnel and engineering the surface lysine residues using the pullulanase from Pyrococcus yayanosii CH1 (PulPY2). The specific activity of the engineered pullulanase was increased 3.1-fold, and thermostability was enhanced 1.8-fold. Moreover, the engineered pullulanase exhibited 11.4-fold improvement in catalytic efficiency (kcat/Km). Molecular dynamics simulations demonstrated an anti-correlated movement around the entrance of active-site tunnel and stronger interactions between the surface residues in the engineered pullulanase, which would be beneficial to the activity and thermostability improvement, respectively. The strategies used in this study and dynamic evidence for insight into enzyme performance improvement may provide guidance for the activity and thermostability engineering of other enzymes.

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