Regulating Interfacial Microenvironment in Aqueous Electrolyte via a N2 Filtering Membrane for Efficient Electrochemical Ammonia Synthesis.

Electrochemical synthesis of ammonia (NH3) in aqueous electrolyte has long been suffered from poor nitrogen (N2) supply owing to its low solubility and sluggish diffusion kinetics. Therefore, creating a N2 rich microenvironment around catalyst surface may potentially improve the efficiency of nitrogen reduction reaction (NRR). Herein, a delicately designed N2 filtering membrane consisted of polydimethylsiloxane is covered on catalyst surface via superspreading. Because this membrane let the dissolved N2 molecules be accessible to the catalyst but block excess water, the designed N2 rich microenvironment over catalyst leads to an optimized Faradaic efficiency of 39.4% and an NH3 yield rate of 109.2 µg h-1 mg-1, which is superior to those of the most report metal-based catalysts for electrochemical NRR. This study offers alternative strategy for enhancing NRR performance.

A Highly Sensitive and Selective Fluorescent Sensor for Folic Acid Detection Based on D-penicillamine Stabilized Ag/Cu Alloy Nanoclusters.

In this work, a highly sensitive and selective method for detecting folic acid (FA) was developed using D-penicillamine (DPA) stabilized Ag/Cu alloy nanoclusters (DPA@Ag/Cu NCs). The yellow emission of DPA@Ag/Cu NCs was found to be quenched upon the addition of FA to the system. The fluorescence intensity quenching value demonstrated a linear relationship with FA concentrations ranging from 0.01 to 1200 µM, with a limit of detection (LOD) of 5.3 nM. Furthermore, the detection mechanism was investigated through various characterization analyses, including high resolution transmission electron microscopy, fluorescence spectra, ultraviolet-visible absorption spectra, and fluorescence lifetime. The results indicated that the fluorescence quenching induced by FA was a result of electron transfer from FA to the ligands of DPA@Ag/Cu NCs. The selectivity of the FA sensor was also evaluated, showing that common amino acids and inorganic ions had minimal impact on the detection of FA. Moreover, the standard addition method was successfully applied to detect FA in human serum, chewable tablets and FA tablets with promising results. The use of DPA@Ag/Cu NCs demonstrates significant potential for detecting FA in complex biological samples.

Effects of improved amino acid balance diet on lysine mammary utilization, whole body protein turnover and muscle protein breakdown on lactating sows.

BACKGROUND: The study objective was to test the hypothesis that low crude protein (CP) diet with crystalline amino acids (CAA) supplementation improves Lys utilization efficiency for milk production and reduces protein turnover and muscle protein breakdown. Eighteen lactating multiparous Yorkshire sows were allotted to 1 of 2 isocaloric diets (10.80 MJ/kg net energy): control (CON; 19.24% CP) and reduced CP with "optimal" AA profile (OPT; 14.00% CP). Sow body weight and backfat were recorded on d 1 and 21 of lactation and piglets were weighed on d 1, 14, 18, and 21 of lactation. Between d 14 and 18, a subset of 9 sows (CON = 4, OPT = 5) was infused with a mixed solution of 3-[methyl-2H3]histidine (bolus injection) and [13C]bicarbonate (priming dose) first, then a constant 2-h [13C]bicarbonate infusion followed by a 6-h primed constant [1-13C]lysine infusion. Serial blood and milk sampling were performed to determine plasma and milk Lys enrichment, Lys oxidation rate, whole body protein turnover, and muscle protein breakdown. RESULTS: Over the 21-d lactation period, compared to CON, sows fed OPT had greater litter growth rate (P < 0.05). Compared to CON, sows fed OPT had greater efficiency of Lys (P < 0.05), Lys mammary flux (P < 0.01) and whole-body protein turnover efficiency (P < 0.05). Compared to CON, sows fed OPT tended to have lower whole body protein breakdown rate (P = 0.069). Muscle protein breakdown rate did not differ between OPT and CON (P = 0.197). CONCLUSION: Feeding an improved AA balance diet increased efficiency of Lys and reduced whole-body protein turnover and protein breakdown. These results imply that the lower maternal N retention observed in lactating sows fed improved AA balance diets in previous studies may be a result of greater partitioning of AA towards milk rather than greater body protein breakdown.

Semisynthesis and biological evaluation of novel honokiol thioethers against colon cancer cells HCT116 via inhibiting the transcription and expression of YAP protein.

Honokiol, derived from Magnolia officinalis (a traditional Chinese medicine), has been reported to have anticancer activity. Here, a series of novel honokiol thioethers bearing a 1,3,4-oxadiazole moiety were prepared and evaluated for their anticancer activities against three types of digestive system tumor cells. Biological evaluation showed that honokiol derivative 3k exhibited the best antiproliferative activity against HCT116 cells with an IC50 value of 6.1 µmol/L, superior to the reference drug 5-fluorouracil (IC50: 9.63 ± 0.27 µmol/L). The structure-activity relationships (SARs) indicated that the introduction of -(4-NO2)Ph, 3-pyridyl, -(2-F)Ph, -(4-F)Ph, -(3-F)Ph, -(4-Cl)Ph, and -(3-Cl)Ph groups was favorable for enhancing the anticancer activity of the title honokiol thioethers. Further study revealed that honokiol thioether 3k can well inhibit the proliferation of colon cancer cells HCT116, arresting the cells in G1 phase and inducing cell death. Moreover, a preliminary mechanism study indicated that 3k directly inhibits the transcription and expression of YAP protein without activating the Hippo signaling pathway. Thus, honokiol thioether 3k could be deeply developed for the development of honokiol-based anticancer candidates.

Dopamine promotes osteogenic differentiation of PDLSCs by activating DRD1 and DRD2 during orthodontic tooth movement via ERK1/2 signaling pathway.

Introduction: Orthodontic tooth movement (OTM) involves complex interactions between mechanical forces and periodontal tissue adaptation, mainly mediated by periodontal ligament cells, including periodontal ligament stem cells (PDLSCs), osteoblasts, and osteoclasts. Dopamine (DA), a neurotransmitter known for its critical role in bone metabolism, is investigated in this study for its potential to enhance osteogenic differentiation in PDLSCs, which are pivotal in OTM. This study examined the potential of DA to facilitate OTM by binding to DA receptors (D1R and D2R) and activating the ERK1/2 signaling pathway. We propose that DA's interaction with these receptors on PDLSCs could enhance osteogenic differentiation, thereby accelerating bone remodeling and reducing the duration of orthodontic treatments, which offering a novel approach to improve clinical outcomes in orthodontic care. Methods: This study utilized a rat OTM model, micro-CT, histological analyses, and in vitro assays to investigate dopamine's effect on osteogenesis. PDLSCs were cultured and treated with DA, and cytotoxicity, osteogenic differentiation, gene and protein expression assessed. Results: Dopamine administration significantly increased trabecular bone density and osteogenic marker expression in an OTM rat model. In vitro, DA at 10 nM optimally promoted human PDLSCs osteogenesis without affecting proliferation. Blocking DA receptors or inhibiting the ERK1/2 pathway attenuated these effects, underscoring the importance of dopaminergic signaling in tension-induced osteogenesis during OTM. Conclusion: Taken together, our study reveals that local dopamine administration at a concentration of 10 nM not only enhances tension-induced osteogenesis in vivo but also significantly promotes osteogenic differentiation of PDLSCs in vitro through D1 and D2 receptor-mediated ERK1/2 signaling pathway activation.

Finite-Time Consensus Adaptive Neural Network Control for Nonlinear Multiagent Systems Under PDE Models.

In this article, a novel adaptive control method based on neural networks is proposed for a class of multiagent systems (MASs) with nonlinear functions and external disturbances. First, the approximation properties of neural networks are used to approximate the MAS partial differential equation (PDE) model with nonlinear terms containing two variables, time t, and spatial variable x. Second, an adaptive controller is constructed to actuate the parabolic MAS to reach consensus under external disturbances. Based on this, the finite-time theorem and special inequalities are applied to prove the stability of the closed-loop system. Thus, MAS that have nonlinear functions and external disturbances are enabled with finite-time consensus. Finally, the effectiveness of the proposed control method is demonstrated by numerical simulations.

Deep learning modeling of rare noncoding genetic variants in human motor neurons defines CCDC146 as a therapeutic target for ALS.

Amyotrophic lateral sclerosis (ALS) is a fatal and incurable neurodegenerative disease caused by the selective and progressive death of motor neurons (MNs). Understanding the genetic and molecular factors influencing ALS survival is crucial for disease management and therapeutics. In this study, we introduce a deep learning-powered genetic analysis framework to link rare noncoding genetic variants to ALS survival. Using data from human induced pluripotent stem cell (iPSC)-derived MNs, this method prioritizes functional noncoding variants using deep learning, links cis-regulatory elements (CREs) to target genes using epigenomics data, and integrates these data through gene-level burden tests to identify survival-modifying variants, CREs, and genes. We apply this approach to analyze 6,715 ALS genomes, and pinpoint four novel rare noncoding variants associated with survival, including chr7:76,009,472:C>T linked to CCDC146. CRISPR-Cas9 editing of this variant increases CCDC146 expression in iPSC-derived MNs and exacerbates ALS-specific phenotypes, including TDP-43 mislocalization. Suppressing CCDC146 with an antisense oligonucleotide (ASO), showing no toxicity, completely rescues ALS-associated survival defects in neurons derived from sporadic ALS patients and from carriers of the ALS-associated G4C2-repeat expansion within C9ORF72. ASO targeting of CCDC146 may be a broadly effective therapeutic approach for ALS. Our framework provides a generic and powerful approach for studying noncoding genetics of complex human diseases.

New multiple-layered 3D polymers showing aggregation-induced emission and polarization.

An exceptional achiral and chiral multilayer 3D polymer has been created and controlled by uniform and distinct aromatic chromophore units that are multiply sandwiched by naphthyl berths. In order to put together this assembly, it was necessary to search for new catalytic Suzuki-Miyaura polycouplings among various catalytic systems, monomers, and catalysts. Gel Permeation Chromatography (GPC) was able to verify the presence of many framework layers. The resulting achiral and chiral polymers displayed notable optical characteristic.

KIF11 UFMylation Maintains Photoreceptor Cilium Integrity and Retinal Homeostasis.

The photoreceptor cilium is vital for maintaining the structure and function of the retina. However, the molecular mechanisms underlying the photoreceptor cilium integrity and retinal homeostasis are largely unknown. Herein, it is shown that kinesin family member 11 (KIF11) localizes at the transition zone (connecting cilium) of the photoreceptor and plays a crucial role in orchestrating the cilium integrity. KIF11 depletion causes malformations of both the photoreceptor ciliary axoneme and membranous discs, resulting in photoreceptor degeneration and the accumulation of drusen-like deposits throughout the retina. Mechanistic studies show that the stability of KIF11 is regulated by an interplay between its UFMylation and ubiquitination; UFMylation of KIF11 at lysine 953 inhibits its ubiquitination by synoviolin 1 and thereby prevents its proteasomal degradation. The lysine 953-to-arginine mutant of KIF11 is more stable than wild-type KIF11 and also more effective in reversing the ciliary and retinal defects induced by KIF11 depletion. These findings identify a critical role for KIF11 UFMylation in the maintenance of photoreceptor cilium integrity and retinal homeostasis.

Relation-Aware Heterogeneous Graph Network for Learning Intermodal Semantics in Textbook Question Answering.

Textbook question answering (TQA) task aims to infer answers for given questions from a multimodal context, including text and diagrams. The existing studies have aggregated intramodal semantics extracted from a single modality but have yet to capture the intermodal semantics between different modalities. A major challenge in learning intermodal semantics is maintaining lossless intramodal semantics while bridging the gap of semantics caused by heterogeneity. In this article, we propose an intermodal relation-aware heterogeneous graph network (IMR-HGN) to extract the intermodal semantics for TQA, which aggregates different modalities while learning features rather than representing them independently. First, we design a multidomain consistent representation (MDCR) to eliminate semantic gaps by capturing intermodal features while maintaining lossless intramodal semantics in multidomains. Furthermore, we present neighbor-based relation inpainting (NRI) to reduce semantic ambiguity via repairing fuzzy relations with correlations of relations. Finally, we propose hierarchical multisemantics aggregation (HMSA) to guarantee the completeness of semantics by aggregating features of nodes and relations with a reconstruction network (RN). Experimental results show that IMR-HGN could extract the intermodal semantics of answers, achieving a 2.16% improvement on the validation set of the TQA dataset and a 3.04% increase on the test set of the AI2D dataset.

A Comparative Study of Removal of Acid Red 27 by Adsorption on Four Different Chitosan Morphologies.

To investigate the relationship between structures and adsorption properties, four different morphologies of chitosan, with hydrogel (CSH), aerogel (CSA), powder (CSP), and electrospinning nanofiber (CSEN) characteristics, were employed as adsorbents for the removal of Acid Red 27. The structures and morphologies of the four chitosan adsorbents were characterized with SEM, XRD, ATR-FTIR, and BET methods. The adsorption behaviors and mechanisms of the four chitosan adsorbents were comparatively studied. All adsorption behaviors exhibited a good fit with the pseudo-second-order kinetic model (R2 > 0.99) and Langmuir isotherm model (R2 > 0.99). Comparing the adsorption rates and the maximum adsorption capacities, the order was CSH > CSA > CSP > CSEN. The maximum adsorption capacities of CSH, CSA, CSP, and CSEN were 2732.2 (4.523), 676.7 (1.119), 534.8 (0.885), and 215.5 (0.357) mg/g (mmol/g) at 20 °C, respectively. The crystallinities of CSH, CSA, CSP, and CSEN were calculated as 0.41%, 6.97%, 8.76%, and 39.77%, respectively. The crystallinity of the four chitosan adsorbents was the main factor impacting the adsorption rates and adsorption capacities, compared with the specific surface area. With the decrease in crystallinity, the adsorption rates and capacities of the four chitosan adsorbents increased gradually under the same experimental conditions. CSH with a low crystallinity and large specific surface area resulted in the highest adsorption rate and capacity.

Pyrrolic Nitrogen Boosted H2 Generation from an Aqueous Solution of HCHO at Room Temperature by Metal-Free Carbon Catalysts.

Hydrogen production from organic hydrides represents a promising strategy for the development of safe and sustainable technologies for H2 storage and transportation. Nonetheless, the majority of existing procedures rely on noble metal catalysts and emit greenhouse gases such as CO2/CO. Herein, we demonstrated an alternative N-doped carbon (CN) catalyst for highly efficient and robust H2 production from an aqueous solution of formaldehyde (HCHO). Importantly, this process generated formic acid as a valuable byproduct instead of CO2/CO, enabling a clean H2 generation process with 100% atom economy. Mechanism investigations revealed that the pyrrolic N in the CN catalysts played a critical role in promoting H2 generation via enhancing the transformation of O2 to generate •OO- free radicals. Consequently, the optimized CN catalysts achieved a remarkable H2 generation rate of 13.6 mmol g-1 h-1 at 30 °C. This finding is anticipated to facilitate the development of liquid H2 storage and its large-scale utilization.

Point Cloud Registration Method Based on Geometric Constraint and Transformation Evaluation.

Existing point-to-point registration methods often suffer from inaccuracies caused by erroneous matches and noisy correspondences, leading to significant decreases in registration accuracy and efficiency. To address these challenges, this paper presents a new coarse registration method based on a geometric constraint and a matrix evaluation. Compared to traditional registration methods that require a minimum of three correspondences to complete the registration, the proposed method only requires two correspondences to generate a transformation matrix. Additionally, by using geometric constraints to select out high-quality correspondences and evaluating the matrix, we greatly increase the likelihood of finding the optimal result. In the proposed method, we first employ a combination of descriptors and keypoint detection techniques to generate initial correspondences. Next, we utilize the nearest neighbor similarity ratio (NNSR) to select high-quality correspondences. Subsequently, we evaluate the quality of these correspondences using rigidity constraints and salient points' distance constraints, favoring higher-scoring correspondences. For each selected correspondence pair, we compute the rotation and translation matrix based on their centroids and local reference frames. With the transformation matrices of the source and target point clouds known, we deduce the transformation matrix of the source point cloud in reverse. To identify the best-transformed point cloud, we propose an evaluation method based on the overlap ratio and inliers points. Through parameter experiments, we investigate the performance of the proposed method under various parameter settings. By conducting comparative experiments, we verified that the proposed method's geometric constraints, evaluation methods, and transformation matrix computation consistently outperformed other methods in terms of root mean square error (RMSE) values. Additionally, we validated that our chosen combination for generating initial correspondences outperforms other descriptor and keypoint detection combinations in terms of the registration result accuracy. Furthermore, we compared our method with several feature-matching registration methods, and the results demonstrate the superior accuracy of our approach. Ultimately, by testing the proposed method on various types of point cloud datasets, we convincingly established its effectiveness. Based on the evaluation and selection of correspondences and the registration result's quality, our proposed method offers a solution with fewer iterations and higher accuracy.

Design and Asymmetric Control of Orientational Chirality by Using the Combination of C(sp2)-C(sp) Levers and Achiral N-Protecting Group.

New chiral targets of orientational chirality have been designed and asymmetrically synthesized by taking advantage of N-sulfinyl imine-directed nucleophilic addition/oxidation, Suzuki-Miyaura, and Sonogashira cross-coupling reactions. Orientation of single isomers has been selectively controlled by using aryl/alkynyl levers [C(sp2)-C(sp) axis] and tBuSO2- protecting group on nitrogen as proven by X-ray diffraction analysis. The key structural characteristic of resulting orientational products is shown by remote through-space blocking manner. Seventeen examples of multi-step synthesis were obtained with modest to good chemical yields and complete orientational selectivity.

Preclinical evaluation of the SARS-CoV-2 Mpro inhibitor RAY1216 shows improved pharmacokinetics compared with nirmatrelvir.

Although vaccines are available for SARS-CoV-2, antiviral drugs such as nirmatrelvir are still needed, particularly for individuals in whom vaccines are less effective, such as the immunocompromised, to prevent severe COVID-19. Here we report an α-ketoamide-based peptidomimetic inhibitor of the SARS-CoV-2 main protease (Mpro), designated RAY1216. Enzyme inhibition kinetic analysis shows that RAY1216 has an inhibition constant of 8.4 nM and suggests that it dissociates about 12 times slower from Mpro compared with nirmatrelvir. The crystal structure of the SARS-CoV-2 Mpro:RAY1216 complex shows that RAY1216 covalently binds to the catalytic Cys145 through the α-ketoamide group. In vitro and using human ACE2 transgenic mouse models, RAY1216 shows antiviral activities against SARS-CoV-2 variants comparable to those of nirmatrelvir. It also shows improved pharmacokinetics in mice and rats, suggesting that RAY1216 could be used without ritonavir, which is co-administered with nirmatrelvir. RAY1216 has been approved as a single-component drug named 'leritrelvir' for COVID-19 treatment in China.

Inhalation bioaccessibility of imidacloprid in particulate matter: Implications for risk assessment during spraying.

Adverse health outcomes due to the inhalation of pesticide residues in atmospheric particulate matter (PM) are gaining global attention. Quantitative health risk assessments of pesticide inhalation exposure highlight the need to understand the bioaccessibility of pesticide residues. Herein, the inhalation bioaccessibility of imidacloprid in PM was determined using three commonly used in vitro lung modeling methods (Artificial Lysosomal Fluid, Gamble Solution, and Simulated Lung Fluid). To validate its feasibility and effectiveness, we evaluated the bioavailability of imidacloprid using a mouse nasal instillation assay. The in vitro inhalation bioaccessibility of imidacloprid was extracted using Gamble Solution with a solid-liquid ratio of 1/1000, an oscillation rate of 150 r/min, and an extraction time of 24 h, showed a strong linear correlation with its in vivo liver-based bioavailability (R2 =0.8928). Moreover, the margin of exposure was incorporated into the inhalation exposure risk assessment, considering both formulations and nozzles. The inhalation unit exposure of imidacloprid for residents was 0.95-4.09 ng/m3. The margin of exposure for imidacloprid was determined to be acceptable when considering inhalation bioaccessibility. Taken together, these results indicate that the inhalation bioaccessibility of pesticides should be incorporated into assessments of human health risks posed by PM particles.

Dissolution and regeneration of starch in hydroxyl-functionalized ionic liquid aqueous solution.

There have been continuous quests for suitable solvents for starch, given the importance of effective starch dissolution in its modification and subsequent materials production. In light of this, the potential of hydroxyl-functionalized ionic liquid (IL) as a promising solvent for starch was investigated. Within this study, a hydroxyl-functionalized IL 1-(2,3-dihydroxypropyl)-3-methylimidazole chloride ([Dhpmim][Cl]) was synthesized, and the dissolution of starch in this IL and its aqueous solutions was examined. Starch (5.35 wt%) was completely dissolved in [Dhpmim][Cl] within 2 h at 100 °C. The solubility of starch in [Dhpmim][Cl]-water mixtures initially increased and then decreased with rising water content. The optimal ratio was found to be 1:9 (wt/wt) water:[Dhpmim][Cl], achieving the highest solubility at 9.28 wt%. Density functional theory (DFT) simulations elucidated the possible interactions between starch and solvents. After dissolution and regeneration in the 1:9 water:[Dhpmim][Cl] mixture, starch showed no discernible change in the molecular structure, with no derivatization reaction observed. Regenerated starch exhibited a transformation in crystalline structure from A-type to V-type, and its relative crystallinity (12.4 %) was lower than that of native starch (25.2 %), resulting in decreased thermal stability. This study suggests that the hydroxyl-functionalized IL, [Dhpmim][Cl], and its aqueous solutions serve as effective solvents for starch dissolution.

Metagenomic insights into the response of soil microbial communities to pathogenic Ralstonia solanacearum.

Understanding the response of soil microbial communities to pathogenic Ralstonia solanacearum is crucial for preventing bacterial wilt outbreaks. In this study, we investigated the soil physicochemical and microbial community to assess their impact on the pathogenic R.solanacearum through metagenomics. Our results revealed that certain archaeal taxa were the main contributors influencing the health of plants. Additionally, the presence of the pathogen showed a strong negative correlation with soil phosphorus levels, while soil phosphorus was significantly correlated with bacterial and archaeal communities. We found that the network of microbial interactions in healthy plant rhizosphere soils was more complex compared to diseased soils. The diseased soil network had more linkages, particularly related to the pathogen occurrence. Within the network, the family Comamonadaceae, specifically Ramlibacter_tataouinensis, was enriched in healthy samples and showed a significantly negative correlation with the pathogen. In terms of archaea, Halorubrum, Halorussus_halophilus (family: Halobacteriaceae), and Natronomonas_pharaonis (family: Haloarculaceae) were enriched in healthy plant rhizosphere soils and showed negative correlations with R.solanacearum. These findings suggested that the presence of these archaea may potentially reduce the occurrence of bacterial wilt disease. On the other hand, Halostagnicola_larseniia and Haloterrigena_sp._BND6 (family: Natrialbaceae) had higher relative abundance in diseased plants and exhibited significantly positive correlations with R.solanacearum, indicating their potential contribution to the pathogen's occurrence. Moreover, we explored the possibility of functional gene sharing among the correlating bacterial pairs within the Molecular Ecological Network. Our analysis revealed 468 entries of horizontal gene transfer (HGT) events, emphasizing the significance of HGT in shaping the adaptive traits of plant-associated bacteria, particularly in relation to host colonization and pathogenicity. Overall, this work revealed key factors, patterns and response mechanisms underlying the rhizosphere soil microbial populations. The findings offer valuable guidance for effectively controlling soil-borne bacterial diseases and developing sustainable agriculture practices.

Identification of a lncRNA/circRNA-miRNA-mRNA network in Nasopharyngeal Carcinoma by deep sequencing and bioinformatics analysis.

Background: Accumulating evidence indicates that non-coding RNAs (ncRNA), including long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs), can function as competitive endogenous RNAs (ceRNAs) by binding to microRNAs (miRNAs) and regulating host gene expression at the transcriptional or post-transcriptional level. Dysregulation in ceRNA network regulation has been implicated in the occurrence and development of cancer. However, the lncRNA/circRNA-miRNA-mRNA regulatory network is still lacking in nasopharyngeal carcinoma (NPC). Methods: Differentially expressed genes (DEGs) were obtained from our previous sequencing data and Gene Expression Omnibus (GEO). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) were used to explore the biological functions of these common DEGs. Through a series of bioinformatic analyses, the lncRNA/circRNA-miRNA-mRNA network was established. In additional, the external data GSE102349 was used to test the prognostic value of the hub mRNAs through the Kaplan-Meier method. Results: We successfully constructed a lncRNA/circRNA-miRNA-mRNA network in NPC, consisting of 16 lncRNAs, 6 miRNAs, 3 circRNAs and 10 mRNAs and found that three genes (TOP2A, ZWINT, TTK) were significantly associated with overall survival time (OS) in patients. Conclusion: The regulatory network revealed in this study may help comprehensively elucidate the ceRNA mechanisms driving NPC, and provide novel candidate biomarkers for evaluating the prognosis of NPC.