Metabolomic analysis o1f alizarin intervention on duck enteritis virus-infected duck fibroblast cells

Metabolomic analysis o1f alizarin intervention on duck enteritis virus-infected duck fibroblast cells | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Metabolomic analysis o 1 f alizarin intervention on duck enteritis virus-infected duck fibroblast cells Yan Wang, Wenwen Bi, Peng Wu, Yijun Chen, Zihan Jin, Jiaqi Chen, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7112922/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract (background）Alizarin is the main active component in traditional Chinese medicines such as Rubia cordifolia and Lonicera japonica, and it has anti-inflammatory and antiviral effects. It has been demonstrated that Rubia cordifolia can effectively prevent and treat duck enteritis virus (DEV) infection. This study aims to further clarify the mechanism by which rubiadin prevents DEV infection. (Method)Duck embryo fibroblast (DEF) cells were pretreated with alizarin before being infected with DEV. Cell samples were collected at different time points for metabolomics sequencing, and the proliferation of DEV was detected by qPCR simultaneously. (Result）Compared with the virus infection group, the alizarin intervention group exhibited a significantly reduced DEV load in DEF cells (P < 0.05). Transcriptome sequencing results revealed that alizarin inhibited DEV proliferation in DEF cells by modulating metabolic pathways such as those of tryptophan and arginine, thereby altering metabolites including indole and glutamate. (Conclusions）Alizarin effectively inhibits DEV proliferation in DEF cells and mitigates virus-induced cytopathic effects, thereby providing a theoretical foundation for the screening of targeted antiviral agents against DEV. alizarin duck enteritis virus duck embryo fibroblast cells metabonomics signal pathway Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Introduction Duck enteritis virus (DEV), officially designated as Anatid alphaherpesvirus 1 and commonly referred to as duck plague virus (DPV), is classified within the family Herpesviridae, subfamily Alphaherpesvirinae, and genus Mardivirus. [ 1 ] 。DEV, the causative agent of Duck virus enteritis (DVE), induces pathological alterations including circular hemorrhagic lesions in the digestive tract, longitudinal necrotic foci, and pinpoint hemorrhages in the liver in Muscovy ducks, mallards, Cherry Valley ducks, swans, and other waterfowl species within the order Anseriformes [ 2 ] , DEV, characterized by high transmissibility, a short disease course, and a high fatality rate, has emerged as a significant pathogen threatening the health of waterfowl populations in the poultry industry. It has caused substantial economic losses to the waterfowl breeding industry both in China and globally [ 3 ] . In the era of "reducing and replacing antibiotics," the prevention and control of DEV primarily rely on vaccination and antibiotic therapy. Therefore, there is a pressing need to identify and develop novel antiviral agents that are both safer and more environmentally sustainable [ 4 ] . The abundant resources of traditional Chinese medicine (TCM) components, combined with their low toxicity and minimal side effects, as well as the reduced likelihood of inducing drug resistance, have positioned the screening of effective bioactive compounds from TCM as a promising strategy for replacing antibiotics in antiviral therapy. This area has become one of the current focal points in antiviral drug research and development. [ 5 ] 。Rubia cordifolia L., a member of the Rubiaceae family, is commonly known as Xigan, Lala Teng, Huoxuecao, and Xuejianchou. This plant possesses a wide range of pharmacological activities, including hemostatic and blood-activating effects, anti-tumor properties, antioxidant capabilities, and immunomodulatory functions [ 6 ] .Rubia cordifolia is rich in diverse chemical constituents, including cyclohexapeptides, anthraquinones and their glycosides, naphthoquinones and their glycosides, terpenoids, polysaccharides, and trace elements. Additionally, the plant contains several phytosterols, such as β-sitosterol and daucosterol [ 7 ][ 8 ][ 9 ][ 10 ] .Alizarin, as a key bioactive constituent of Rubia cordifolia L., serves as a potential therapeutic target for analgesic and anti-inflammatory effects, and has been shown to ameliorate pathological changes in adjuvant-induced arthritis [ 11 ] .Furthermore, alizarin exhibits potential as a larvicide and insecticide [ 12 ] , and demonstrates promising applications in the prevention of protein misfolding diseases. These properties suggest its utility in the development of effective anti-amyloidogenic compounds [ 13 ] . Metabolomics, an analytical chemistry-based research approach, investigates endogenous small-molecule metabolites in organisms, their dynamic variations, and identifies specific biomarkers [ 14 ] . It has been extensively applied in drug discovery, the analysis of biological variation patterns, and the elucidation of disease mechanisms [ 15 ] .It facilitates the evaluation of how vaccines and drugs influence host metabolic profiles, thereby enabling researchers to optimize formulations and enhance safety assessments [ 16 ] .In metabolomics studies of the COVID-19 virus, it has been observed that the virus enhances its replication through alterations in lipid, amino acid, and carbohydrate metabolism [ 17 ] . It serves as a powerful analytical tool for elucidating the biochemical alterations associated with viral infection, including changes in amino acid metabolism, heightened energy requirements, and modifications in lipid metabolic pathways. Furthermore, it plays a critical role in identifying potential druggable metabolic proteins and/or regulatory factors through advanced flux analysis techniques, such as those involving the interpretation of metabolic networks [ 18 ] .Various metabolomics approaches have been employed in advancing the modernization of TCM and in the diagnosis and management of diverse pathological conditions, including cardiovascular diseases, renal disorders, hepatic diseases, and metabolic syndromes [ 19 ] .It offers a valuable opportunity to elucidate the mechanisms of action underlying TCM, TCM syndromes, and the physiological changes following TCM treatment.This study selected alizarin, an effective bioactive component of TCM, and DEF cells as the research subjects. Experimental procedures included the determination of the maximum safe drug concentration, CPE observation, and real-time fluorescence q-PCR analysis. Metabolomics technology was employed to investigate the potential molecular mechanisms through which alizarin influences the proliferation of DEV. The findings aim to provide reference data for the prevention and control of viral diseases in livestock and poultry, as well as a scientific foundation for future research on antiviral TCMs. 1 Materials and Methods 1.1 Viruses and Duck Embryos The viral suspension of the Guizhou isolate of DEV (DEV-GZ strain, TCID 50 3.98×10^-5/0.1 mL) was preserved in the Laboratory of Preventive Veterinary Medicine, College of Animal Science, Guizhou University. Specific-pathogen-free (SPF) duck eggs were obtained from He Run Poultry Company, Sansui County, Guizhou Province. The eggs were then incubated to reach 9–11-day-old embryos for subsequent experimental use.(In my research, I have obtained the informed consent of the owners for the use of these animals.) 1.2 Main reagents DMEM medium, DEPC-treated water, fetal bovine serum (FBS), penicillin-streptomycin solution, Hank's balanced salt solution, 0.25% trypsin-EDTA, and Cell Counting Kit-8 (CCK-8) reagents were obtained from Gibco (USA). Trizol reagent, TB Green Premix Ex Taq™ II, and Premix Ex Taq™ II were purchased from TaKaRa Biotechnology (Dalian) Co., Ltd. alizarin was acquired from Aladdin Reagent (Shanghai) Co., Ltd. 1.3 Experimental grouping and sample collection This experiment was designed with four treatment groups: a blank control group (Group A), a alizarin control group (Group B), a duck enteritis virus (DEV) infection group (Group D), and a alizarin intervention group (Group E). DEF cells were resuspended at a density of 1×10⁵ cells/mL and seeded into 6-well culture plates at a volume of 1 mL per well. The plates were incubated at 37°C under 5% CO₂ until the cells reached approximately 80% confluence.In Groups B and E, 1 mL of alizarin solution (0.05 mg/mL) was added to each well, followed by a 2-hour incubation at 37°C. Subsequently, the solution was removed, and the cells were rinsed three times with Hank’s balanced salt solution. In Group B, fresh cell maintenance medium was added after washing. In Group E, 100 TCID 50 of DEV-GZ strain viral suspension was inoculated and allowed to adsorb for 1.5 hours. Following adsorption, the viral solution was discarded, and the cells were washed three times with Hank’s balanced salt solution before the addition of maintenance medium.In Group D, 100 TCID 50 of DEV-GZ strain was inoculated directly and adsorbed for 1.5 hours. Afterward, the supernatant was removed, and the cells were washed three times with Hank’s solution prior to the addition of maintenance medium. Group A received no treatment and was maintained under standard culture conditions at 37°C and 5% CO₂ throughout the experimental period.The CPE in DEF cells across all groups were monitored visually during the incubation period. Cell samples from each group were collected at 24, 36, and 48 hours post-infection, with three biological replicates collected at each time point for subsequent analysis. 1.4 Sample preparation for metabolome sequencing Accurately weigh 25 mg of cell pellet (use the entire amount if less than 25 mg) and transfer it to a thick-walled centrifuge tube. Add two small magnetic beads to each tube. Subsequently, add 10 μL of the prepared internal standard solution to each sample. Next, introduce 800 μL of the protein precipitation reagent (comprising 320 μL methanol, 320 μL acetonitrile, and 160 μL water), and place the mixture in a bead mill homogenizer operating at 50 Hz for 5 minutes. Following homogenization, store the samples at -20°C for 2 hours to induce protein precipitation.Afterward, centrifuge the samples at 25,000 × g and 4°C for 15 minutes. Carefully collect 600 μL of the supernatant from each sample and transfer it into a new microcentrifuge tube. Freeze-dry the supernatant under vacuum. Reconstitute the dried residue with 120 μL of 50% methanol and vortex thoroughly until complete dissolution. Centrifuge again at 25,000 × g and 4°C for 15 minutes to remove any insoluble debris, and transfer the resulting supernatant into a fresh microcentrifuge tube.Finally, take 10 μL from each processed sample and pool them together to prepare a quality control (QC) sample, which will be used for subsequent instrumental analysis. 1.5 Metabolomic data processing and quality control The raw data acquired using the Waters UPLC I-Class Plus system (Waters, USA) coupled with a Q Exactive high-resolution mass spectrometer (Thermo Fisher Scientific, USA) were preprocessed and analyzed using the metaX software. Data quality was assessed based on the reproducibility of QC samples throughout the analytical sequence. Key evaluation criteria included the consistency of base peak chromatograms (BPC) across QC samples, principal component analysis (PCA), correlation analysis among QC samples, and the coefficient of variation (CV) of detected metabolites within QC samples. 1.6 Metabolomics data analysis 1.6.1 Compound Detection and Annotation To characterize the quantity, classification, and functional features of detected metabolites, samples from the blank control group, rhaponticin control group, DEV infection group, and rhaponticin intervention group were selected for BPC analysis. In both positive and negative ionization modes, the representative BPC profiles of each group provide a visual representation of the metabolic detection status across samples. The identified metabolites were categorized and annotated based on their biological functions by referencing the Human Metabolome Database (HMDB) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). 1.6.2 Screening and analysis of differential metabolites To evaluate the underlying distribution, separation patterns, and the presence of outlier samples among the blank control group, alizarin control group, DEV infection group, and alizarin intervention group, dimensionality reduction was applied to the original data from all four groups.FC and p-value for each comparison group were calculated using fold change analysis and independent t-tests, respectively. The p-value was used to assess the statistical significance of metabolite differences between paired groups. Differential metabolites were identified through a combination of PCA and univariate analysis, applying the following criteria: Fold Change ≥ 1.2 or ≤ 0.83; p-value < 0.05.To visualize these results, volcano plots were generated based on the FC and p-value distributions. Prior to clustering analysis, the data underwent log₂ transformation and z-score normalization (mean-centered normalization) using R software. Euclidean distances were then computed to reflect variations in differential metabolite profiles. Hierarchical clustering was subsequently performed across comparison groups, with the results displayed as a heat map to illustrate patterns of metabolic variation. 1.6.3 Analysis of related metabolic pathways The significantly differentially expressed metabolites were compared against KEGG database to perform metabolic pathway enrichment analysis. Bubble charts were generated to visually represent the enriched pathways. To assess the underlying distribution, separation patterns, and potential outlier samples among the blank control group, rhubarb pigment control group, DEV infection group, and alizarin intervention group, dimensionality reduction was applied to the original data from all four groups. Fold change analysis and independent t-tests were performed for each comparison group to calculate FC and p-value, respectively. The p-value was used to assess the statistical significance of metabolite differences between paired sample groups. Differential metabolites in each comparison group were identified through a combination of PCA and univariate analysis, applying the following criteria: FC ≥ 1.2 or ≤ 0.83; p-value < 0.05. The FC and p-value data were visualized using volcano plots to illustrate significant changes across metabolites. Prior to clustering analysis, the data underwent log₂ transformation and z-score normalization (mean-centered normalization) using R software. Euclidean distances were then calculated to reflect variations in differential metabolite profiles. Hierarchical clustering was conducted among different comparison groups, with results displayed as a heat map to demonstrate patterns of metabolic variation. 2 Result 2.1 The results of the effect of alizarin on DEV 2.1.1 The determination result of TC0 of alizarin Various concentrations of alizarin solution were administered to DEF cells and incubated in a 37℃ incubator for 24 hours. Concurrently, a blank cell control group and a medium control group were established. Cell viability was assessed using CCK-8 assay to determine cytotoxicity. The results are presented in Fig. 1 . As illustrated in the figure, the cytotoxic effect of alizarin on DEF cells increased in a concentration-dependent manner. Therefore, TC 0 of alizarin was determined to be 0.05 mg/mL. 2.1.2 The effect of alizarin on the proliferation of DEV To investigate the effect of alizarin on the replication of DEV in DEF cells, q-PCR was employed to monitor changes in viral copy numbers in cell samples from each group at 24, 36, and 48 hours post-treatment. The results were analyzed using the 2 ⁻ΔΔCt method and visualized with GraphPad Prism 8 software. As illustrated in Fig. 2, compared to the DEV infection group, the relative viral expression in the alizarin intervention group was significantly decreased at all three time points (24 h, 36 h, and 48 h) (P < 0.05). These findings suggest that alizarin effectively inhibits the proliferation of DEV in DEF cells. 2.2 The results of the study on the effect of alizarin on DEV proliferation based on metabolomics research. 2.2.1 The quality control results of the DEV proliferation metabolome are affected by alizarin. （ 1 ） The result of BPC of QC samples To evaluate the instrument stability and the analytical consistency of the comparison groups, BPC was employed. All QC samples in both positive and negative ionization modes were overlaid separately. The chroma to graphic peaks exhibited high abundance, a high degree of overlap, and minimal fluctuations in response intensity and retention time (Fig. 3). These results indicate stable instrument performance during the detection process, consistent sample status, and high-quality data output. (2) PCA results All original sample data were subjected to dimensionality reduction through principal component analysis (PCA), with results presented in Fig. 4. The QC samples are tightly clustered, indicating minimal systematic error, high experimental reproducibility, and excellent data quality. (4) The correlation analysis results of QC samples QC samples were selected from the total data set, and the Spear man correlation coefficient was calculated based on the quantitative values of these QC samples. The results are presented in Fig. 5. A higher correlation among QC samples (indicated by an R² value closer to 1) reflects lower systematic error, improved experimental repeatability, and enhanced data quality. 2.2.2 Metabolomic data analysis results regarding the effect of alizarin on DEV replication （ 1 ） The statistics of the number of detected and identified compounds are presented in Table 1 . Table 1 Statistics of compound detection and identification numbers totalofnuber Num.ofCV≤30% RatioofCV≤30% 2603 2121 0.81 As shown in Fig. 6 and Fig. 7,a total of 2121 metabolites with CV values below 30% were identified, of which 631 metabolites were structurally annotated. The annotated metabolites primarily included 98 lipids (23.96%), 48 amino acids (11.7%), 34 organic acids (8.31%), and 26 benzene derivatives (6.34%), among others. The distribution of identified metabolites was further categorized based on the major Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways they participated in. The results indicated that the majority were involved in amino acid metabolism (32.57%), followed by lipid metabolism (15.43%), and xenobiotic biodegradation and metabolism (13.14%). （ 2 ） The screening and analysis results of differential metabolites affected by alizarin on the proliferation of DEV ①PCA A comprehensive analysis of PCA plots across different comparison groups reveals the presence of both shared and distinct ion compounds between the alizarin intervention groups and DEV infection groups at various time points, as well as among the alizarin intervention groups themselves across time.The results are shown in Fig. 8. ②Univariate analysis of metabolites and screening of differential metabolites A comprehensive analysis of PCA plots across different comparison groups indicates that metabolites exhibiting significant differences between the alizarin intervention groups and DEV infection groups, as well as among the alizarin intervention groups at various time points, demonstrate an increasing trend. The distribution and aggregation of these differentially expressed metabolites are predominantly confined to a narrow density range.The x-axis represents the log₂-transformed fold change, while the y-axis denotes the -log 10 transformed p-value. Blue dots indicate significantly downregulated differential metabolites, red dots represent significantly upregulated differential metabolites, and gray dots correspond to non-significant metabolites.The results are shown in Fig. 9. The differential metabolites in DEV infection groups and the alizarin intervention groups at various time points were identified based on fold change and p-value criteria. The screening thresholds were defined as FC ≥ 1.2 or ≤ 0.83, with a p-value < 0.05. The results indicated that the number of differentially expressed metabolites across comparison groups at different time points was substantial (Table 2). Compared to the DEV infection groups, the alizarin intervention groups at 24 h, 36 h, and 48 h identified 8, 18, and 30 differential metabolites, respectively, of which 1, 5, and 17 were upregulated, and 7, 13, and 13 were downregulated. Detailed information can be found in Table 3 Table 4 Table 5. When comparing among the alizarin intervention groups at different time points (24 h, 36 h, and 48 h), 59, 157, and 156 differential metabolites were identified, respectively, including 16, 65, and 48 upregulated metabolites, and 43, 92, and 108 downregulated metabolites. Overall, a considerable number of differential metabolites were observed. Table 2 Statistics of Differential Metabolites Group Total differential metabolites Up Down D-24/E-24 8 1 7 D-36/E-36 18 5 13 D-48/E-48 30 17 13 E-24/E-36 59 16 43 E-24/E-48 157 65 92 E-36/E-48 156 48 108 Table 3 Difference metabolites between DEV control group and alizarin intervention group for 24h No FC P-value Mode Name Formula 1 0.2769 0.0236 ＋ octopamine C 8 H 11 NO 2 2 0.0275 0.0163 ＋ 2-Mercaptobenzothiazole C 7 H 5 NS 2 3 8.2688 0.0262 ＋ 2,3-Butynyl prostaglandin E1 C 18 H 30 O 5 4 0.0070 0.0011 ＋ Hydroquinone trimethyl ether C 9 H 12 O 3 5 0.0252 0.0212 ＋ Maltol isobutyrate C 10 H 12 O 4 6 0.2944 0.0386 ＋ Methyl 2-methoxyvinyl-2-oxosulfate C 13 H 12 O 7 S 7 0.6526 0.0317 ＋ 4,5,7-Trihydroxy coumarin C 9 H 6 O 5 8 0.6836 0.0261 － methylprednisolone C 22 H 30 O 5 Table 4 Difference metabolites between DEV control group and alizarin intervention group for 36 h No FC p-value Mode Name Formula 1 1.4163 0.0421 ＋ pantothenic acid C 9 H 17 NO 5 2 0.3792 0.0296 ＋ 1-Stearoyl glycerol C 21 H 42 O 4 3 0.5342 0.0143 ＋ muscone C 16 H 30 O 4 1.5826 0.0416 ＋ DL-carnitine C 7 H 15 NO 3 5 1.2800 0.0233 ＋ N-Vinylformamide C 3 H 5 NO 6 1.5884 0.0188 ＋ Citric acid derivative of 1,3-dimethylbutylamine C 12 H 23 NO 7 7 0.1916 0.0254 － 4-Heptylphenyl 4-heptylbenzoic acid C 27 H 38 O 2 8 1.7324 0.0156 ＋ acetylcarnitine C 9 H 17 NO 4 9 0.3657 0.0434 ＋ N-Docosadienoyl ethanolamine C 22 H 41 NO 2 10 0.6526 0.0347 ＋ Undecanamide C 37 H 73 NO 5 11 0.4904 0.0045 ＋ 2,6,10-Trimethyl-2,6,10-tritriacontene C 16 H 28 12 0.5561 0.0180 ＋ Mono-hydroxylated rapeseed oil glycerol fatty acid ester C 19 H 38 O 4 13 0.4343 0.0122 ＋ 1 - Monoglyceride of palmitic acid C 16 H 32 O 2 14 0.4910 0.0309 ＋ bortezomib C 19 H 25 BN 4 O 4 15 0.6204 0.0443 ＋ Palovarotene C 27 H 30 N 2 O 2 16 0.3572 0.0014 ＋ 4-Hydroxy-3-octylphenyl benzoate C 47 H 70 O 3 17 0.4784 0.0438 ＋ Glyceryl Monostearate C 20 H 40 O 4 18 0.3298 0.0150 ＋ 3-Sulfodeoxycholic acid C 23 H 38 O 7 S Table 5 Difference metabolites between DEV control group and alizarin intervention group for 48 h No FC p-value Mode Name Formula 1 1.2558 0.0387 － L-glutamic acid C 5 H 9 NO 4 2 0.6110 0.0378 ＋ Indole-3-acrylic acid C 11 H 9 NO 2 3 1.5163 0.0047 ＋ Alkenylsuccinic anhydrides C 16 H 26 O 3 4 2.0516 0.0242 ＋ citral C 10 H 16 O 5 2.0841 0.0225 ＋ γ-Linolenic acid C 18 H 30 O 2 6 1.3992 0.0290 － oxalic acid C 2 H 2 O 4 7 1.2469 0.0299 － saccharopine C 11 H 20 N 2 O 6 8 0.7092 0.0293 ＋ 1,3,5(10)-Trien-3-yl sulfate C 18 H 24 O 4 S 9 0.5549 0.0239 － lactic acid C 3 H 6 O 3 10 0.8002 0.0092 ＋ S-(2,5-Dimethyl-3-furyl) 2-furan sulfic acid ester C 11 H 10 O 3 S 11 0.3838 0.0104 ＋ meprobamate C 9 H 18 N 2 O 4 12 0.5794 0.0300 ＋ Cyclic nylon dimer C 12 H 22 N 2 O 2 13 0.5825 0.0355 ＋ Tetraacetylethylenediamine C 10 H 16 N 2 O 4 14 0.5800 0.0012 ＋ N-Methyl-1H-indole-3-propanamide C 12 H 14 N 2 O 15 1.6402 0.0017 ＋ xanthopterin C 6 H 5 N 5 O 2 16 1.2432 0.0205 ＋ 7-(3-Chloro-2-hydroxy-3-methylbutoxy)-8-(3-methyl-2-oxobutyl)coumarin C 19 H 23 ClO 5 17 0.4103 0.0129 ＋ Amiloride C 15 H 20 O 3 18 0.4086 0.0040 ＋ cumyl hydroperoxide C 9 H 12 O 2 19 1.4604 0.0286 － Methylprednisolone Hemisuccinate C 25 H 32 O 8 20 1.5532 0.0027 ＋ butyrate C 16 H 28 O 2 21 1.3784 0.0277 ＋ N,N-Bis(2-hydroxyethyl) dodecanamide C 16 H 33 NO 3 22 1.5287 0.0007 ＋ 2,4-Dihydroxyheptanedioic acid 16-ethynyl ester C 19 H 34 O 4 23 2.2792 0.0305 － Lauric acid sulfate C 12 H 26 O 4 S 24 2.0535 0.0251 － Acetylhexacycline C 15 H 20 N 2 O 4 S 25 2.2689 0.0066 － pimobendan C 19 H 18 N 4 O 2 26 1.2728 0.0184 ＋ 4,6-Cholestadien-3-one C 27 H 42 O 27 0.8177 0.0059 ＋ octadecylamine C 18 H 39 N 28 0.6825 0.0184 ＋ estrane C 18 H 30 29 0.7493 0.0046 ＋ 1-Stearoyl-2-hydroxy-sn-glycerol-3-polyethylene glycol C 23 H 48 NO 7 P ③Cluster analysis of differentially expressed metabolites Differential metabolite clustering analysis was performed on the expression levels of differentially expressed metabolites in the DEV infection group and the alizarin intervention group at various time points. As shown in Fig. 10,the results indicated that, compared with the alizarin intervention group, the expression levels of differentially expressed metabolites in the DEV infection group exhibited significant variation across time points (24 h, 36 h, and 48 h). Specifically, the expression levels in the DEV infection group increased over time, whereas those in the alizarin intervention group decreased. Furthermore, when comparing the alizarin intervention groups across time points, notable differences were observed in metabolite expression levels, with the E-24 group showing the highest expression and the E-48 group exhibiting the lowest. Each row represents a differentially expressed metabolite, each column represents a sample, and the color intensity reflects the expression level, with blue indicating low expression and red indicating high expression. （ 3 ） Analysis of the effects of alizarin on metabolic pathways associated with DEV proliferation As illustrated in Fig. 11,analysis of metabolic pathways associated with the 24 h alizarin intervention group and the DEV infection group revealed that differentially expressed metabolites were predominantly enriched in pathways including alanine, aspartate, and glutamate metabolism; β-alanine metabolism; butyric acid metabolism; neuroactive ligand-receptor interaction; nicotinate and nicotinamide metabolism; and arginine and proline metabolism. Comparative analysis of metabolic pathways between the 36 h alizarin intervention group and the DEV infection group indicated significant enrichment of differentially expressed metabolites in pantothenate and CoA biosynthesis; β-alanine metabolism; fatty acid elongation, degradation, and biosynthesis; biosynthesis of unsaturated fatty acids; biosynthesis of terpenoids including ubiquinone; and overall fatty acid metabolism. Analysis of metabolic pathways linked to the 48 h alizarin intervention group and the DEV infection group demonstrated enrichment of differentially expressed metabolites in 2-oxocarboxylic acid metabolism; FoxO signaling pathway; D-glutamine and D-glutamate metabolism; nitrogen metabolism; taurine and hypotaurine metabolism; arginine biosynthesis; alanine, aspartate, and glutamate metabolism; and sulfur metabolism. Analysis of metabolic pathways associated with the 24 h and 36 h alizarin intervention groups revealed that differentially expressed metabolites were predominantly enriched in pathways including ABC transporters; aminoacyl-tRNA biosynthesis; amino acid biosynthesis; arginine and proline metabolism; β-alanine metabolism; glycine, serine, and threonine metabolism; tryptophan metabolism; and the pentose phosphate pathway. Comparative analysis of metabolic pathways between the 24 h and 48 h alizarin intervention groups indicated significant enrichment of differentially expressed metabolites in ABC transporters; β-alanine metabolism; amino acid biosynthesis; arginine and proline metabolism; glycine, serine, and threonine metabolism; purine metabolism; the pentose phosphate pathway; and phenylalanine metabolism. Analysis of metabolic pathways linked to the 36 h and 48 h alizarin intervention groups demonstrated enrichment of differentially expressed metabolites in pantothenate and CoA biosynthesis; unsaturated fatty acid biosynthesis; ABC transporters; linoleic acid metabolism; arginine and proline metabolism; tyrosine metabolism; and purine metabolism. 3 Discussion 3.1 Analysis of the effect of alizarin on the proliferation of DEV in DEF cells Duck viral enteritis, commonly referred to as duck plague, is caused by a virus belonging to the family Herpesviridae, subfamily Alphaherpesvirinae, and genus Meleagrid herpesvirus. This disease can induce acute, febrile, and highly contagious infections in ducks, geese, and other species of waterfowl [20] .The characteristic pathological changes associated with duck viral enteritis include vascular damage and hemorrhage in the intestine, lesions in lymphoid organs, and degenerative alterations in parenchymal organs [21] . The disease spreads rapidly, affects a wide range of waterfowl species, and is marked by high incidence and mortality rates. It represents one of the major diseases currently threatening the global duck industry, resulting in substantial economic losses. Currently, due to the absence of effective anti-DEV therapeutic options in the market, the prevention and control of duck viral enteritis primarily depend on vaccination [22] .However, the incidence and mortality rates of DVE remain elevated. Given the increasing prevalence of antibiotic resistance associated with the misuse and overuse of antibiotics [23] [24] , the development of novel "antibiotic-free" or "reduced-antibiotic" therapeutic agents against DEV is of critical importance for the effective prevention and treatment of DVE. Rubia cordifolia, commonly referred to as madder or dyeweed, was historically utilized as a natural dye [25] . However, recent studies have demonstrated that it also exhibits pharmacological activities, including hemostatic, anti-inflammatory, antiviral, and broad-spectrum antibacterial effects. alizarin is the key bioactive constituent of Rubia cordifolia. To date, extensive research has documented the anticancer properties of alizarin; however, investigations into its potential antiviral activity against DEV remain scarce. Therefore, this study selected alizarin to evaluate its inhibitory effect on DEV proliferation in vitro.The TCID 50 of DEV was calculated as 3.98 × 10⁻⁵/0.1 mL using the Reed-Muench method based on CPE observation. Concurrently, the maximum non-toxic concentration of alizarin was determined to be 0.05 mg/mL through the CCK-8 assay. Based on these results, the effect of alizarin on DEV proliferation in DEF cells was examined and validated using q-PCR technology. 3.2 Analysis of the Molecular Mechanism Underlying alizarin-Mediated Regulation of DEV Proliferation Based on Metabolomics Research With the rapid advancement of big data technologies, metabolomics has been extensively applied in various fields, including the elucidation of drug mechanisms of action, evaluation of therapeutic efficacy, identification of relevant metabolic biomarkers, and development of diagnostic models. Notably, research focusing on the detection of active components in traditional Chinese medicine using metabolomics-based sequencing techniques has seen a significant increase [25] .Metabolomic analysis of rats infected with respiratory syncytial virus (RSV) and administered Dingchuan Decoction revealed that the decoction could normalize the altered levels of bile acids, amino acids, and organic acids induced by RSV infection, as well as modulate the dysbiosis of the intestinal microbiota and immune system. Additionally, it demonstrated a regulatory effect on abnormal lipid metabolites [26] .Treatment with forsythoside (PHI) and baicalin (Bai) compounds may modulate key metabolic pathways such as amino acid biosynthesis, carbon metabolism, phenylalanine metabolism, alanine, aspartate, and glutamate metabolism, 2-oxocarboxylic acid metabolism, and β-alanine metabolism, thereby exerting regulatory effects on the respiratory tract microbiota and metabolic disturbances in chickens infected with infectious bronchitis virus (IBV) [27] .Metabolomics integrated with network pharmacology analysis of RD cells infected with enterovirus 71 (EV71) and treated with AST-IV revealed that AST-IV may activate cAMP signaling and antioxidant stress responses by targeting eight key metabolites—hypoxanthine, 2-ketobutyric acid, adenine, nicotinamide mononucleotide, prostaglandin H₂, 6-hydroxy-1H-indole-3-acetamide, hypoxanthine, and phosphocholine (PC)—thereby stimulating the PI3K-AKT signaling pathway and inhibiting EV71-induced apoptosis and viral replication [28] .In the metabolite profiling results, 8, 18, and 30 differential metabolites were identified when comparing the DEV infection group with the alizarin intervention group at 24 h, 36 h, and 48 h, respectively. Furthermore, 59, 157, and 156 differential metabolites were detected when comparing the alizarin intervention groups across different time points (24 h, 36 h, and 48 h). Among these, immune-related metabolites included indole-3-acrylic acid, L-glutamic acid, and DL-carnitine. Compared with the DEV infection group, the alizarin intervention group exhibited 6, 8, and 10 significantly enriched metabolic pathways at 24 h, 36 h, and 48 h, respectively. When comparing the alizarin intervention groups across time points (24 h vs. 36 h, 24 h vs. 48 h, 36 h vs. 48 h), a total of 10 major enriched metabolic pathways were consistently observed, including those associated with immunity such as D-glutamine and D-glutamic acid metabolism, tryptophan metabolism, and arginine and proline metabolism.It is evident that as time progresses, the number of differential metabolites increases, a trend that aligns generally with the overall variation pattern of differentially expressed genes observed in duodenal transcriptomic analysis at 72 h, 96 h, and 120 h post-DEV infection [29] .The primary explanation may be that following the invasion of pathogenic microorganisms into the host, the duodenal mucosa progressively activates an immune response. After a certain time interval, the defensive capacity is enhanced, leading to a gradual reduction in the number of differential metabolites and differentially expressed genes. Among the top five metabolites with the smallest p-values identified through comparisons between the DEV infection group and the alizarin intervention group at different time points, indole-3-propionic acid, L-glutamic acid, and acetylcarnitine are all associated with immune-inflammatory responses. Notably, indole-3-propionic acid is a metabolite derived from tryptophan, and the tryptophan metabolic pathway has been implicated in the regulation of inflammation. L-tryptophan, indole-3-propionic acid, and their endogenous metabolites involved in tryptophan metabolism represent an essential class of nutrients in mammals, which are closely associated with intestinal immune homeostasis and the pathogenesis of various immune-mediated diseases [30] .Abnormal metabolism of the intestinal microbiota and dysregulated levels of indole-3-lactic acid (ILA) have been observed in patients with colorectal cancer (CRC). Indole-3-lactic acid (ILA) has been shown to inhibit tumor cell proliferation, migration, and anti-apoptotic activity through metabolic reprogramming [31] . Sinomenine (SIN) demonstrates potent immunosuppressive and anti-inflammatory properties in the treatment of rheumatoid arthritis through the upregulation of microbial-derived tryptophan metabolites, including indole-3-acrylic acid (IA), indole-3-propionic acid (IPA), and indole-3-acetic acid (IAA) [32] .In this study, the alizarin intervention group suppressed virus-induced immunosuppressive pathways through down-regulation of immunosuppressive metabolites such as indole-3-acrylic acid and citral. Furthermore, the intervention enhanced the immune response by up-regulating key metabolites including glutamate, aspartate, and asparagine within the glutamine metabolic pathway. 4 Overall Conclusion alizarin demonstrates the ability to inhibit DEV proliferation in DEF cells. The underlying mechanism involves the suppression of viral replication through the modulation of multiple amino acid metabolic pathways, including those of tryptophan and arginine, leading to the differential expression of associated metabolites such as indole-3-acrylic acid, L-glutamic acid, and DL-carnitine. Abbreviations full name abbreviation DuckVirus Enteritis DVE Duck Enteritis Virus DEV Fetal Bovine Serum FBS Duck Embryo Fibroblast DEF Principal Component Analysis PCA Kyoto Encyclopedia of Genesand Genomes KEGG Polymerase Chain Reaction PCR Tissue Culture Infective Dose TCID 50 Quality Control QC Human Metabolome Database HMDB Specific-pathogen-free SPF Entero virus A71 EV-A71 Respiratory Syncytial Virus RSV Angiotensin Converting Enzyme2 ACE2 Noro virus-1 MNV-1 Porcine Reproductiveand Respiratory Syndrome Virus PRRSV Hour h Declarations ①Ethics approval and consent to participate:All experimental procedures were approved by the Institutional Animal Ethics Committee from The Guizhou University (EAE-GZU-2021-T005).The owner's informed consent has been obtained. ②Consent for publication:Not Applicable ③Availability of data and materials:Data is provided within the manuscript or supplementary information files. ④Competing interests:There are no conflicts of interest to declare. ⑤Funding:Open Access funding enabled and organized by National Natural Science Foundation of China " Analysis of the molecular mechanism of DEV regulating calcium channels to promote inflammatory response of duck intestinal mucosal epithelial cells" (700626231135). ⑥Authors' contributions:WangYan, wrote the main manuscript, prepared the figures and tables, analysed the data and reviewed the manuscript. Bi Wenwen and WenMing were involved in the interpretation of the results and reviewed the manuscript. All authors have read and agreed to the published version of the manuscript. ⑦Acknowledgements:The authors thank Ming Wen and Bi Wenwen for their assistance with the experiment and writing. References Fleury HJ, Babin M, Bonnici JF, et al. First simultaneous isolation of influenza A virus and duck enteritis virus from commercial ducks in France. Vet Rec . 1986;119(9):208-209. doi:10.1136/vr.119.9.208.https://doi.org/10.1136/vr.119.9.208 El-Tholoth M, Hamed MF, Matter AA, Abou El-Azm KI. Molecular and pathological characterization of duck enteritis virus in Egypt. Transbound Emerg Dis. 2019;66(1):217-224. doi:10.1111/tbed.13002.https://doi.org/10.1111/tbed.13002 Tang W, Yuan M, Mao M, et al. Pathogenicity studies and molecular characterization of DPV infection in ducklings. Poult Sci. 2024;103(9):103919. doi:10.1016/j.psj.2024.103919 Levy SB, Marshall B. Antibacterial resistance worldwide: causes, challenges and responses. Nat Med. 2004;10(12 Suppl):S122-S129. doi:10.1038/nm1145. https://doi.org/10.1038/nm1145 Li J, Feng S, Liu X, et al. Effects of Traditional Chinese Medicine and its Active Ingredients on Drug-Resistant Bacteria. Front Pharmacol. 2022;13:837907. Published 2022 Jun 2. doi:10.3389/fphar.2022.837907. https://doi.org/10.3389/fphar.2022.837907 Zeng W, Fang Y, Mo S, et al. The Underling Mechanisms Exploration of Rubia cordifolia L. Extract Against Rheumatoid Arthritis by Integrating Network Pharmacology and Metabolomics. Drug Des Devel Ther. 2023;17:439-457. Published 2023 Feb 11. doi:10.2147/DDDT.S388932. https://doi.org/10.2147/DDDT.S388932 Boldizsár I, Szucs Z, Füzfai Z, Molnár-Perl I. Identification and quantification of the constituents of madder root by gas chromatography and high-performance liquid chromatography. J Chromatogr A. 2006;1133(1-2):259-274. doi:10.1016/j.chroma.2006.08.021. https://doi.org/10.1016/j.chroma.2006.08.021 Paramasivam S, Perumal SS. Methanolic extract of O.umbellata L. exhibits anti-osteoporotic effect via promoting osteoblast proliferation in MG-63 cells and inhibiting osteoclastogenesis in RANKL-stimulated RAW 264.7 cells. J Ethnopharmacol. 2023;315:116641. doi:10.1016/j.jep.2023.116641. https://doi.org/10.1016/j.jep.2023.116641 Li C, Tian L, Wang Y, et al. M13, an anthraquinone compound isolated from Morinda officinalis promotes the osteogenic differentiation of MSCs by targeting Wnt/β-catenin signaling. Phytomedicine. 2023;108:154542. doi:10.1016/j.phymed.2022.154542. https://doi.org/10.1016/j.phymed.2022.154542 Tsuchiya T, Takagi Y, Yamada H. Preparation of 5-(2,6-dideoxy-2-fluoro-alpha-L-talopyranosyloxy)-6-hydroxynap htho[2,3- f]quinoline-7,12-dione (FT-Alz), a new-type, potentially antitumor substance with various biological activities. Bioorg Med Chem Lett. 2000;10(3):203-207. doi:10.1016/s0960-894x(99)00655-1. https://doi.org/10.1016/s0960-894x(99)00655-1 Shen CH, Liu CT, Song XJ, et al. Evaluation of analgesic and anti-inflammatory activities of Rubia cordifolia L. by spectrum-effect relationships. J Chromatogr B Analyt Technol Biomed Life Sci. 2018;1090:73-80. doi:10.1016/j.jchromb.2018.05.021. https://doi.org/10.1016/j.jchromb.2018.05.021 Gandhi MR, Reegan AD, Ganesan P, et al. Larvicidal and Pupicidal Activities of Alizarin Isolated from Roots of Rubia cordifolia Against Culex quinquefasciatus Say and Aedes aegypti (L.) (Diptera: Culicidae). Neotrop Entomol. 2016;45(4):441-448. doi:10.1007/s13744-016-0386-x. https://doi.org/10.1007/s13744-016-0386-x Wang W, Zhang J, Qi W, Su R, He Z, Peng X. Alizarin and Purpurin from Rubia tinctorum L. Suppress Insulin Fibrillation and Reduce the Amyloid-Induced Cytotoxicity. ACS Chem Neurosci. 2021;12(12):2182-2193. doi:10.1021/acschemneuro.1c00177. https://doi.org/10.1021/acschemneuro.1c00177 Giera M, Yanes O, Siuzdak G. Metabolite discovery: Biochemistry's scientific driver. Cell Metab. 2022;34(1):21-34. doi:10.1016/j.cmet.2021.11.005 Elrashedy A, Mousa W, Nayel M, et al. Advances in bioinformatics and multi-omics integration: transforming viral infectious disease research in veterinary medicine. Virol J. 2025;22(1):22. Published 2025 Jan 31. doi:10.1186/s12985-025-02640-x. https://doi.org/10.1186/s12985-025-02640-x Tounta V, Liu Y, Cheyne A, Larrouy-Maumus G. Metabolomics in infectious diseases and drug discovery. Mol Omics. 2021;17(3):376-393. doi:10.1039/d1mo00017a. https://doi.org/10.1039/d1mo00017a Shen B, Yi X, Sun Y, et al. Proteomic and Metabolomic Characterization of COVID-19 Patient Sera. Cell. 2020;182(1):59-72.e15. doi:10.1016/j.cell.2020.05.032. https://doi.org/10.1016/j.cell.2020.05.032 Elrashedy A, Mousa W, Nayel M, et al. Advances in bioinformatics and multi-omics integration: transforming viral infectious disease research in veterinary medicine. Virol J. 2025;22(1):22. Published 2025 Jan 31. doi:10.1186/s12985-025-02640-x. https://doi.org/10.1186/s12985-025-02640-x Wang M, Chen L, Liu D, Chen H, Tang DD, Zhao YY. Metabolomics highlights pharmacological bioactivity and biochemical mechanism of traditional Chinese medicine. Chem Biol Interact. 2017;273:133-141. doi:10.1016/j.cbi.2017.06.011. https://doi.org/10.1016/j.cbi.2017.06.011 Dhama K, Kumar N, Saminathan M, et al. Duck virus enteritis (duck plague) - a comprehensive update. Vet Q. 2017;37(1):57-80. doi:10.1080/01652176.2017.1298885. https://doi.org/10.1080/01652176.2017.1298885 Li N, Hong T, Li R, et al. Pathogenicity of duck plague and innate immune responses of the Cherry Valley ducks to duck plague virus. Sci Rep. 2016;6:32183. Published 2016 Aug 24. doi:10.1038/srep32183 Jia WF, Wang AP, Wu Z, Lei XN, Cheng YT, Zhu SY. Current status of recombinant duck enteritis virus vector vaccine research. Front Vet Sci. 2025;12:1453150. Published 2025 Feb 5. doi:10.3389/fvets.2025.1453150. https://doi.org/10.3389/fvets.2025.1453150 Allel K, Fernandez-Miyakawa M, Gaze W, et al. Opportunities and challenges in antimicrobial resistance policy including animal production systems and humans across stakeholders in Argentina: a context and qualitative analysis. BMJ Open. 2024;14(6):e082156. Published 2024 Jun 17. doi:10.1136/bmjopen-2023-082156. Ford L, Henderson RL, Rayner CM, Blackburn RS. Mild extraction methods using aqueous glucose solution for the analysis of natural dyes in textile artefacts dyed with Dyer's madder (Rubia tinctorum L.). J Chromatogr A. 2017;1487:36-46. doi:10.1016/j.chroma.2017.01.053. https://doi.org/10.1016/j.chroma.2017.01.053 Wang XJ, Ren JL, Zhang AH, et al. Novel applications of mass spectrometry-based metabolomics in herbal medicines and its active ingredients: Current evidence. Mass Spectrom Rev. 2019;38(4-5):380-402. doi:10.1002/mas.21589. https://doi.org/10.1002/mas.21589 Ouyang Y, Chi L, Xu C, Zhao X, Cui Z. Se Pu. 2021;39(3):281-290. doi:10.3724/SP.J.1123.2020.06013. https://doi.org/10.3724/SP.J.1123.2020.06013 Feng H, Zhang J, Zhang K, et al. Synergistic anti-infectious bronchitis virus activity of Phillygenin combined Baicalin by modulating respiratory microbiota and improving metabolic disorders. Poult Sci. 2024;103(2):103371. doi:10.1016/j.psj.2023.103371 Hao J, Zhang X, Hu R, et al. Metabolomics combined with network pharmacology reveals a role for astragaloside IV in inhibiting enterovirus 71 replication via PI3K-AKT signaling. J Transl Med. 2024;22(1):555. Published 2024 Jun 10. doi:10.1186/s12967-024-05355-9. https://doi.org/10.1186/s12967-024-05355-9 Cai H, Yang X, Yang Y, et al. Untargeted metabolomics of the intestinal tract of DEV-infected ducks. Virol J. 2023;20(1):305. Published 2023 Dec 19. doi:10.1186/s12985-023-02266-x. https://doi.org/10.1186/s12985-023-02266-x Shen R, Zhang Y. Relationship between amino acid metabolism and inflammation in coronary heart disease (Review). Int J Mol Med. 2025;56(2):120. doi:10.3892/ijmm.2025.5561. https://doi.org/10.3892/ijmm.2025.5561 Zhou S, Wang K, Huang J, et al. Indole-3-lactic acid suppresses colorectal cancer via metabolic reprogramming. Gut Microbes. 2025;17(1):2508949. doi:10.1080/19490976.2025.2508949. https://doi.org/10.1080/19490976.2025.2508949 Jiang ZM, Zeng SL, Huang TQ, et al. Sinomenine ameliorates rheumatoid arthritis by modulating tryptophan metabolism and activating aryl hydrocarbon receptor via gut microbiota regulation. Sci Bull (Beijing). 2023;68(14):1540-1555. doi:10.1016/j.scib.2023.06.027. https://doi.org/10.1016/j.scib.2023.06.027 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7112922","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":497653514,"identity":"66e2773d-2f9f-4ab0-b880-0e911141a1de","order_by":0,"name":"Yan Wang","email":"","orcid":"","institution":"Guizhou University","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Wang","suffix":""},{"id":497653515,"identity":"5c508a7f-be69-477d-bf75-a11cd8af78b3","order_by":1,"name":"Wenwen Bi","email":"","orcid":"","institution":"Guizhou University","correspondingAuthor":false,"prefix":"","firstName":"Wenwen","middleName":"","lastName":"Bi","suffix":""},{"id":497653516,"identity":"295755c2-f6a3-4f4e-9da1-9a282b84b877","order_by":2,"name":"Peng Wu","email":"","orcid":"","institution":"Guizhou University","correspondingAuthor":false,"prefix":"","firstName":"Peng","middleName":"","lastName":"Wu","suffix":""},{"id":497653517,"identity":"246fa56f-2f1a-4294-aa87-f66897a944d4","order_by":3,"name":"Yijun Chen","email":"","orcid":"","institution":"Guizhou University","correspondingAuthor":false,"prefix":"","firstName":"Yijun","middleName":"","lastName":"Chen","suffix":""},{"id":497653518,"identity":"75358e07-b093-4ea4-b170-804d5bae73eb","order_by":4,"name":"Zihan Jin","email":"","orcid":"","institution":"Guizhou University","correspondingAuthor":false,"prefix":"","firstName":"Zihan","middleName":"","lastName":"Jin","suffix":""},{"id":497653519,"identity":"69133d30-9e56-4bc1-8011-a3d32709f519","order_by":5,"name":"Jiaqi Chen","email":"","orcid":"","institution":"Guizhou University","correspondingAuthor":false,"prefix":"","firstName":"Jiaqi","middleName":"","lastName":"Chen","suffix":""},{"id":497653520,"identity":"ad84f892-bfc8-4625-bb9f-f93472480812","order_by":6,"name":"Ying Yang","email":"","orcid":"","institution":"Guizhou University","correspondingAuthor":false,"prefix":"","firstName":"Ying","middleName":"","lastName":"Yang","suffix":""},{"id":497653521,"identity":"d050df10-022d-4ed6-9d9c-f3a5eed128ab","order_by":7,"name":"Ming Wen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVRIiWNgGAWjYBADOQjFRoIWY9K1JDYQrYW//wDrZp6KO+nz/c8YMHwoO8zAP7sBvxaJGwlst3nOPMvdeOCMAeOMc4cZJO4cIGDNDQa227lth3M3NvYYMPO2HWYwkEjAr0P+/AGgln+H0w2beQyY/xKjxeAA0GG5DYcT5NmAWhiJ0WJ4I7Ht9p9jhw038LAVHOw5l84D9B1+LXLnDx+7OaPmsLx8/+GND36UWcvxzyCghYGBsQHqQgYGIGLgIaQeAeQbiFc7CkbBKBgFIwwAAJKRRO+jj6RJAAAAAElFTkSuQmCC","orcid":"","institution":"Guizhou University","correspondingAuthor":true,"prefix":"","firstName":"Ming","middleName":"","lastName":"Wen","suffix":""}],"badges":[],"createdAt":"2025-07-13 11:23:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7112922/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7112922/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88918713,"identity":"ebe8841e-2cb7-4c48-9772-918898ddee0b","added_by":"auto","created_at":"2025-08-12 16:52:21","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":51257,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003edrug concentration(mg/mL)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7112922/v1/8f26cb3ff584e148d9ebbe34.png"},{"id":88919551,"identity":"94a99e04-79ec-46c3-8594-faf0c94c560d","added_by":"auto","created_at":"2025-08-12 17:00:21","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":37511,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe changes in the relative expression levels of DEV at different time periods\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7112922/v1/b1b0b9553d3953a4f2f003da.png"},{"id":88918717,"identity":"c19e1e52-6987-4534-bf63-0f00fa599946","added_by":"auto","created_at":"2025-08-12 16:52:21","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":636245,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eQC sample BPC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote: + means positive ion mode, - means negative ion mode\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7112922/v1/ff0c3a36bcce8aa8c8bc9bbd.png"},{"id":88918715,"identity":"442ef045-8147-4be7-ad90-e54a098553b9","added_by":"auto","created_at":"2025-08-12 16:52:21","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":76626,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePCA of all samples\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote: PC1 represents the first principal component, while PC2 expresses the second principal component\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7112922/v1/a4ee6185daa9d0d05067d074.png"},{"id":88918721,"identity":"284d71f7-bf5f-4e7a-a099-a5cdc477e45f","added_by":"auto","created_at":"2025-08-12 16:52:21","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":39264,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDiagram of QC sample\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote: PC1 represents the first principal component, while PC2 expresses the second principal component\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7112922/v1/9f7a26963f977030edbf3f46.png"},{"id":88918726,"identity":"2de9839c-7be5-4afb-abfb-edc055d3ebb4","added_by":"auto","created_at":"2025-08-12 16:52:21","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":27708,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRing diagram of metabolite classification\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote: Different colors in the figure represent different metabolite classification entries, and percentage represents the percentage of this type of metabolite in the total number of metabolites with classification information\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7112922/v1/d891192859126734bc06136a.jpg"},{"id":88919552,"identity":"728693c2-97f7-4d59-b81e-727888f03dea","added_by":"auto","created_at":"2025-08-12 17:00:21","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":43879,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKEGG Pathway Donut Char.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote: Different colors represent different metabolite pathway ，Percentage represents the percentage of metabolites in particular pathway over all metabolites with pathway categorial information.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7112922/v1/449fd3d7b5cce141f943823c.jpg"},{"id":88920908,"identity":"7da0b9d2-80fd-49a7-8b52-ef1827b26a91","added_by":"auto","created_at":"2025-08-12 17:16:21","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":178254,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePCA between different comparison groups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote:Ⅰ represents the comparison between the virus control group and the alizarin intervention group at 24 hours; Ⅱ represents the comparison between the virus control group and the alizarin intervention group at 36 hours; Ⅲ represents the comparison between the virus control group and the alizarin intervention group at 48 hours; Ⅳ represents the comparison between the alizarin intervention groups at 24 and 36 hours; Ⅴ represents the comparison between the alizarin intervention groups at 24 and 48 hours; Ⅵ represents the comparison between the alizarin intervention groups at 36 and 48 hours.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7112922/v1/0061ba13da00b6f36dc17c02.jpg"},{"id":88918722,"identity":"37ac0f8e-644c-4062-b3df-9059dd6a5a32","added_by":"auto","created_at":"2025-08-12 16:52:21","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":310048,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVolcanoplotofdifferentialmetabolitesindifferentcomparisongroups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote:Ⅰ represents the comparison between the virus control group and the alizarin intervention group at 24 hours; Ⅱ represents the comparison between the virus control group and the alizarin intervention group at 36 hours; Ⅲ represents the comparison between the virus control group and the alizarin intervention group at 48 hours; Ⅳ represents the comparison between the alizarin intervention groups at 24 and 36 hours; Ⅴ represents the comparison between the alizarin intervention groups at 24 and 48 hours; Ⅵ represents the comparison between the alizarin intervention groups at 36 and 48 hours.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7112922/v1/20aeb45d53e362c68a591de4.jpg"},{"id":88919572,"identity":"eae69a77-173e-4dfc-9ac4-544ab2733c52","added_by":"auto","created_at":"2025-08-12 17:00:21","extension":"jpg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":524692,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eClustering on differential Metabolites in different comparison groups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote:Ⅰ represents the comparison between the virus control group and the alizarin intervention group at 24 hours; Ⅱ represents the comparison between the virus control group and the alizarin intervention group at 36 hours; Ⅲ represents the comparison between the virus control group and the alizarin intervention group at 48 hours; Ⅳ represents the comparison between the alizarin intervention groups at 24 and 36 hours; Ⅴ represents the comparison between the alizarin intervention groups at 24 and 48 hours; Ⅵ represents the comparison between the alizarin intervention groups at 36 and 48 hours.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"10.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7112922/v1/65c8b0efc1a49f311092855b.jpg"},{"id":88918733,"identity":"97f45a2b-ea04-441a-9cc3-125d6586f18e","added_by":"auto","created_at":"2025-08-12 16:52:21","extension":"jpg","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":348543,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMetabolic Pathway Enrichment Analysis Bubble Chart in different comparison groups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote:Ⅰ represents the comparison between the virus control group and the alizarin intervention group at 24 hours; Ⅱ represents the comparison between the virus control group and the alizarin intervention group at 36 hours; Ⅲ represents the comparison between the virus control group and the alizarin intervention group at 48 hours; Ⅳ represents the comparison between the alizarin intervention groups at 24 and 36 hours; Ⅴ represents the comparison between the alizarin intervention groups at 24 and 48 hours; Ⅵ represents the comparison between the alizarin intervention groups at 36 and 48 hours.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"11.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7112922/v1/2eac1f91128088a87500a3f1.jpg"},{"id":96453476,"identity":"449ef7cc-f25b-477f-bd33-a6d610523a58","added_by":"auto","created_at":"2025-11-21 10:00:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5077235,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7112922/v1/9ae2390f-c156-4b19-83c7-8c4f672525dd.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eMetabolomic analysis o\u003csup\u003e1\u003c/sup\u003ef alizarin intervention on duck enteritis virus-infected duck fibroblast cells\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDuck enteritis virus (DEV), officially designated as Anatid alphaherpesvirus 1 and commonly referred to as duck plague virus (DPV), is classified within the family Herpesviridae, subfamily Alphaherpesvirinae, and genus Mardivirus.\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e。DEV, the causative agent of Duck virus enteritis (DVE), induces pathological alterations including circular hemorrhagic lesions in the digestive tract, longitudinal necrotic foci, and pinpoint hemorrhages in the liver in Muscovy ducks, mallards, Cherry Valley ducks, swans, and other waterfowl species within the order Anseriformes\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e, DEV, characterized by high transmissibility, a short disease course, and a high fatality rate, has emerged as a significant pathogen threatening the health of waterfowl populations in the poultry industry. It has caused substantial economic losses to the waterfowl breeding industry both in China and globally\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn the era of \"reducing and replacing antibiotics,\" the prevention and control of DEV primarily rely on vaccination and antibiotic therapy. Therefore, there is a pressing need to identify and develop novel antiviral agents that are both safer and more environmentally sustainable\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. The abundant resources of traditional Chinese medicine (TCM) components, combined with their low toxicity and minimal side effects, as well as the reduced likelihood of inducing drug resistance, have positioned the screening of effective bioactive compounds from TCM as a promising strategy for replacing antibiotics in antiviral therapy. This area has become one of the current focal points in antiviral drug research and development.\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e。Rubia cordifolia L., a member of the Rubiaceae family, is commonly known as Xigan, Lala Teng, Huoxuecao, and Xuejianchou. This plant possesses a wide range of pharmacological activities, including hemostatic and blood-activating effects, anti-tumor properties, antioxidant capabilities, and immunomodulatory functions\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e.Rubia cordifolia is rich in diverse chemical constituents, including cyclohexapeptides, anthraquinones and their glycosides, naphthoquinones and their glycosides, terpenoids, polysaccharides, and trace elements. Additionally, the plant contains several phytosterols, such as β-sitosterol and daucosterol\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e][\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e][\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e][\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e.Alizarin, as a key bioactive constituent of Rubia cordifolia L., serves as a potential therapeutic target for analgesic and anti-inflammatory effects, and has been shown to ameliorate pathological changes in adjuvant-induced arthritis\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e.Furthermore, alizarin exhibits potential as a larvicide and insecticide \u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e, and demonstrates promising applications in the prevention of protein misfolding diseases. These properties suggest its utility in the development of effective anti-amyloidogenic compounds \u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eMetabolomics, an analytical chemistry-based research approach, investigates endogenous small-molecule metabolites in organisms, their dynamic variations, and identifies specific biomarkers \u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. It has been extensively applied in drug discovery, the analysis of biological variation patterns, and the elucidation of disease mechanisms \u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e.It facilitates the evaluation of how vaccines and drugs influence host metabolic profiles, thereby enabling researchers to optimize formulations and enhance safety assessments\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e.In metabolomics studies of the COVID-19 virus, it has been observed that the virus enhances its replication through alterations in lipid, amino acid, and carbohydrate metabolism\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIt serves as a powerful analytical tool for elucidating the biochemical alterations associated with viral infection, including changes in amino acid metabolism, heightened energy requirements, and modifications in lipid metabolic pathways. Furthermore, it plays a critical role in identifying potential druggable metabolic proteins and/or regulatory factors through advanced flux analysis techniques, such as those involving the interpretation of metabolic networks\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e.Various metabolomics approaches have been employed in advancing the modernization of TCM and in the diagnosis and management of diverse pathological conditions, including cardiovascular diseases, renal disorders, hepatic diseases, and metabolic syndromes\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e.It offers a valuable opportunity to elucidate the mechanisms of action underlying TCM, TCM syndromes, and the physiological changes following TCM treatment.This study selected alizarin, an effective bioactive component of TCM, and DEF cells as the research subjects. Experimental procedures included the determination of the maximum safe drug concentration, CPE observation, and real-time fluorescence q-PCR analysis. Metabolomics technology was employed to investigate the potential molecular mechanisms through which alizarin influences the proliferation of DEV. The findings aim to provide reference data for the prevention and control of viral diseases in livestock and poultry, as well as a scientific foundation for future research on antiviral TCMs.\u003c/p\u003e"},{"header":"1 Materials and Methods","content":"\u003ch2\u003e1.1 Viruses and Duck Embryos\u003c/h2\u003e\n\u003cp\u003eThe viral suspension of the Guizhou isolate of DEV (DEV-GZ strain, TCID\u003csub\u003e50\u003c/sub\u003e 3.98\u0026times;10^-5/0.1 mL) was preserved in the Laboratory of Preventive Veterinary Medicine, College of Animal Science, Guizhou University. Specific-pathogen-free (SPF) duck eggs were obtained from He Run Poultry Company, Sansui County, Guizhou Province. The eggs were then incubated to reach 9\u0026ndash;11-day-old embryos for subsequent experimental use.(In my research, I have obtained the informed consent of the owners for the use of these animals.)\u003c/p\u003e\n\u003ch2\u003e1.2 Main reagents\u003c/h2\u003e\n\u003cp\u003eDMEM medium, DEPC-treated water, fetal bovine serum (FBS), penicillin-streptomycin solution, Hank\u0026apos;s balanced salt solution, 0.25% trypsin-EDTA, and Cell Counting Kit-8 (CCK-8) reagents were obtained from Gibco (USA). Trizol reagent, TB Green Premix Ex Taq\u0026trade; II, and Premix Ex Taq\u0026trade; II were purchased from TaKaRa Biotechnology (Dalian) Co., Ltd. alizarin was acquired from Aladdin Reagent (Shanghai) Co., Ltd.\u003c/p\u003e\n\u003ch2\u003e1.3 Experimental grouping and sample collection\u003c/h2\u003e\n\u003cp\u003eThis experiment was designed with four treatment groups: a blank control group (Group A), a alizarin control group (Group B), a duck enteritis virus (DEV) infection group (Group D), and a alizarin intervention group (Group E). DEF cells were resuspended at a density of 1\u0026times;10⁵ cells/mL and seeded into 6-well culture plates at a volume of 1 mL per well. The plates were incubated at 37\u0026deg;C under 5% CO₂ until the cells reached approximately 80% confluence.In Groups B and E, 1 mL of alizarin solution (0.05 mg/mL) was added to each well, followed by a 2-hour incubation at 37\u0026deg;C. Subsequently, the solution was removed, and the cells were rinsed three times with Hank\u0026rsquo;s balanced salt solution. In Group B, fresh cell maintenance medium was added after washing. In Group E, 100 TCID\u003csub\u003e50\u003c/sub\u003e of DEV-GZ strain viral suspension was inoculated and allowed to adsorb for 1.5 hours. Following adsorption, the viral solution was discarded, and the cells were washed three times with Hank\u0026rsquo;s balanced salt solution before the addition of maintenance medium.In Group D, 100 TCID\u003csub\u003e50\u003c/sub\u003e of DEV-GZ strain was inoculated directly and adsorbed for 1.5 hours. Afterward, the supernatant was removed, and the cells were washed three times with Hank\u0026rsquo;s solution prior to the addition of maintenance medium. Group A received no treatment and was maintained under standard culture conditions at 37\u0026deg;C and 5% CO₂ throughout the experimental period.The CPE in DEF cells across all groups were monitored visually during the incubation period. Cell samples from each group were collected at 24, 36, and 48 hours post-infection, with three biological replicates collected at each time point for subsequent analysis.\u003c/p\u003e\n\u003ch2\u003e1.4 Sample preparation for metabolome sequencing\u003c/h2\u003e\n\u003cp\u003eAccurately weigh 25 mg of cell pellet (use the entire amount if less than 25 mg) and transfer it to a thick-walled centrifuge tube. Add two small magnetic beads to each tube. Subsequently, add 10 \u0026mu;L of the prepared internal standard solution to each sample. Next, introduce 800 \u0026mu;L of the protein precipitation reagent (comprising 320 \u0026mu;L methanol, 320 \u0026mu;L acetonitrile, and 160 \u0026mu;L water), and place the mixture in a bead mill homogenizer operating at 50 Hz for 5 minutes. Following homogenization, store the samples at -20\u0026deg;C for 2 hours to induce protein precipitation.Afterward, centrifuge the samples at 25,000 \u0026times; g and 4\u0026deg;C for 15 minutes. Carefully collect 600 \u0026mu;L of the supernatant from each sample and transfer it into a new microcentrifuge tube. Freeze-dry the supernatant under vacuum. Reconstitute the dried residue with 120 \u0026mu;L of 50% methanol and vortex thoroughly until complete dissolution. Centrifuge again at 25,000 \u0026times; g and 4\u0026deg;C for 15 minutes to remove any insoluble debris, and transfer the resulting supernatant into a fresh microcentrifuge tube.Finally, take 10 \u0026mu;L from each processed sample and pool them together to prepare a quality control (QC) sample, which will be used for subsequent instrumental analysis.\u003c/p\u003e\n\u003ch2\u003e1.5 Metabolomic data processing and quality control\u003c/h2\u003e\n\u003cp\u003eThe raw data acquired using the Waters UPLC I-Class Plus system (Waters, USA) coupled with a Q Exactive high-resolution mass spectrometer (Thermo Fisher Scientific, USA) were preprocessed and analyzed using the metaX software. Data quality was assessed based on the reproducibility of QC samples throughout the analytical sequence. Key evaluation criteria included the consistency of base peak chromatograms (BPC) across QC samples, principal component analysis (PCA), correlation analysis among QC samples, and the coefficient of variation (CV) of detected metabolites within QC samples.\u003c/p\u003e\n\u003ch2\u003e1.6 Metabolomics data analysis\u003c/h2\u003e\n\u003ch3\u003e1.6.1 Compound Detection and Annotation\u003c/h3\u003e\n\u003cp\u003eTo characterize the quantity, classification, and functional features of detected metabolites, samples from the blank control group, rhaponticin control group, DEV infection group, and rhaponticin intervention group were selected for BPC analysis. In both positive and negative ionization modes, the representative BPC profiles of each group provide a visual representation of the metabolic detection status across samples. The identified metabolites were categorized and annotated based on their biological functions by referencing the Human Metabolome Database (HMDB) and the Kyoto Encyclopedia of Genes and Genomes (KEGG).\u003c/p\u003e\n\u003ch3\u003e1.6.2 Screening and analysis of differential metabolites\u003c/h3\u003e\n\u003cp\u003eTo evaluate the underlying distribution, separation patterns, and the presence of outlier samples among the blank control group, alizarin control group, DEV infection group, and alizarin intervention group, dimensionality reduction was applied to the original data from all four groups.FC and p-value for each comparison group were calculated using fold change analysis and independent t-tests, respectively. The p-value was used to assess the statistical significance of metabolite differences between paired groups. Differential metabolites were identified through a combination of PCA and univariate analysis, applying the following criteria: Fold Change \u0026ge; 1.2 or \u0026le; 0.83; p-value \u0026lt; 0.05.To visualize these results, volcano plots were generated based on the FC and p-value distributions. Prior to clustering analysis, the data underwent log₂ transformation and z-score normalization (mean-centered normalization) using R software. Euclidean distances were then computed to reflect variations in differential metabolite profiles. Hierarchical clustering was subsequently performed across comparison groups, with the results displayed as a heat map to illustrate patterns of metabolic variation.\u003c/p\u003e\n\u003ch3\u003e1.6.3 Analysis of related metabolic pathways\u003c/h3\u003e\n\u003cp\u003eThe significantly differentially expressed metabolites were compared against KEGG database to perform metabolic pathway enrichment analysis. Bubble charts were generated to visually represent the enriched pathways. To assess the underlying distribution, separation patterns, and potential outlier samples among the blank control group, rhubarb pigment control group, DEV infection group, and alizarin intervention group, dimensionality reduction was applied to the original data from all four groups.\u003c/p\u003e\n\u003cp\u003eFold change analysis and independent t-tests were performed for each comparison group to calculate FC and p-value, respectively. The p-value was used to assess the statistical significance of metabolite differences between paired sample groups. Differential metabolites in each comparison group were identified through a combination of PCA and univariate analysis, applying the following criteria: FC \u0026ge; 1.2 or \u0026le; 0.83; p-value \u0026lt; 0.05. The FC and p-value data were visualized using volcano plots to illustrate significant changes across metabolites. Prior to clustering analysis, the data underwent log₂ transformation and z-score normalization (mean-centered normalization) using R software. Euclidean distances were then calculated to reflect variations in differential metabolite profiles. Hierarchical clustering was conducted among different comparison groups, with results displayed as a heat map to demonstrate patterns of metabolic variation.\u003c/p\u003e"},{"header":"2 Result","content":"\u003ch2\u003e2.1\u0026nbsp;The results of the effect of alizarin on DEV\u003c/h2\u003e\n\u003ch3 id=\"_Toc129857101\"\u003e2.1.1 The determination result of TC0 of alizarin\u003c/h3\u003e\n\u003cp\u003eVarious concentrations of alizarin solution were administered to DEF cells and incubated in a 37℃ incubator for 24 hours. Concurrently, a blank cell control group and a medium control group were established. Cell viability was assessed using CCK-8 assay to determine cytotoxicity. The results are presented in \u003cstrong\u003eFig. 1\u003c/strong\u003e. As illustrated in the figure, the cytotoxic effect of alizarin on DEF cells increased in a concentration-dependent manner. Therefore, TC\u003csub\u003e0\u003c/sub\u003e of alizarin was determined to be 0.05 mg/mL.\u003c/p\u003e\n\u003ch3\u003e2.1.2 The effect of alizarin on the proliferation of DEV\u003c/h3\u003e\n\u003cp\u003eTo investigate the effect of alizarin on the replication of DEV in DEF cells, q-PCR was employed to monitor changes in viral copy numbers in cell samples from each group at 24, 36, and 48 hours post-treatment. The results were analyzed using the 2\u003csup\u003e⁻\u0026Delta;\u0026Delta;Ct\u003c/sup\u003e method and visualized with GraphPad Prism 8 software. As illustrated in Fig. 2, compared to the DEV infection group, the relative viral expression in the alizarin intervention group was significantly decreased at all three time points (24 h, 36 h, and 48 h) (P \u0026lt; 0.05). These findings suggest that alizarin effectively inhibits the proliferation of DEV in DEF cells.\u003c/p\u003e\n\u003ch2\u003e2.2\u0026nbsp;The results of the study on the effect of alizarin on DEV proliferation based on metabolomics research.\u003c/h2\u003e\n\u003ch3 id=\"_Toc129857110\"\u003e2.2.1 The quality control results of the DEV proliferation metabolome are affected by alizarin.\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003cstrong\u003eThe result of BPC of QC samples\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo evaluate the instrument stability and the analytical consistency of the comparison groups, BPC was employed. All QC samples in both positive and negative ionization modes were overlaid separately. The chroma to graphic peaks exhibited high abundance, a high degree of overlap, and minimal fluctuations in response intensity and retention time (Fig. 3). These results indicate stable instrument performance during the detection process, consistent sample status, and high-quality data output.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(2) PCA results\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eAll original sample data were subjected to dimensionality reduction through principal component analysis (PCA), with results presented in Fig. 4. The QC samples are tightly clustered, indicating minimal systematic error, high experimental reproducibility, and excellent data quality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(4) The correlation analysis results of QC samples\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQC samples were selected from the total data set, and the Spear man correlation coefficient was calculated based on the quantitative values of these QC samples. The results are presented in Fig. 5. A higher correlation among QC samples (indicated by an R\u0026sup2; value closer to 1) reflects lower systematic error, improved experimental repeatability, and enhanced data quality.\u003c/p\u003e\n\u003ch3\u003e2.2.2 Metabolomic data analysis results regarding the effect of alizarin on DEV replication\u003c/h3\u003e\n\u003cp id=\"_Toc117439756\"\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003cstrong\u003eThe statistics of the number of detected and identified compounds are presented in\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Statistics of compound detection and identification numbers\u003c/strong\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30.8511%;\"\u003e\n \u003cp\u003etotalofnuber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.5106%;\"\u003e\n \u003cp\u003eNum.ofCV\u0026le;30%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.6383%;\"\u003e\n \u003cp\u003eRatioofCV\u0026le;30%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30.8511%;\"\u003e\n \u003cp\u003e2603\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.5106%;\"\u003e\n \u003cp\u003e2121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.6383%;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAs shown in Fig. 6 and Fig. 7,a total of 2121 metabolites with CV values below 30% were identified, of which 631 metabolites were structurally annotated. The annotated metabolites primarily included 98 lipids (23.96%), 48 amino acids (11.7%), 34 organic acids (8.31%), and 26 benzene derivatives (6.34%), among others. The distribution of identified metabolites was further categorized based on the major Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways they participated in. The results indicated that the majority were involved in amino acid metabolism (32.57%), followed by lipid metabolism (15.43%), and xenobiotic biodegradation and metabolism (13.14%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003cstrong\u003eThe screening and analysis results of differential metabolites affected by alizarin on the proliferation of DEV\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e①PCA\u0026nbsp;\u003c/strong\u003eA comprehensive analysis of PCA plots across different comparison groups reveals the presence of both shared and distinct ion compounds between the alizarin intervention groups and DEV infection groups at various time points, as well as among the alizarin intervention groups themselves across time.The results are shown in Fig. 8.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e②Univariate analysis of metabolites and screening of differential metabolites\u0026nbsp;\u003c/strong\u003eA comprehensive analysis of PCA plots across different comparison groups indicates that metabolites exhibiting significant differences between the alizarin intervention groups and DEV infection groups, as well as among the alizarin intervention groups at various time points, demonstrate an increasing trend. The distribution and aggregation of these differentially expressed metabolites are predominantly confined to a narrow density range.The x-axis represents the log₂-transformed fold change, while the y-axis denotes the -log\u003csub\u003e10\u003c/sub\u003e transformed p-value. Blue dots indicate significantly downregulated differential metabolites, red dots represent significantly upregulated differential metabolites, and gray dots correspond to non-significant metabolites.The results are shown in Fig. 9.\u003c/p\u003e\n\u003cp\u003eThe differential metabolites in DEV infection groups and the alizarin intervention groups at various time points were identified based on fold change and p-value criteria. The screening thresholds were defined as FC \u0026ge; 1.2 or \u0026le; 0.83, with a p-value \u0026lt; 0.05. The results indicated that the number of differentially expressed metabolites across comparison groups at different time points was substantial (Table 2). Compared to the DEV infection groups, the alizarin intervention groups at 24 h, 36 h, and 48 h identified 8, 18, and 30 differential metabolites, respectively, of which 1, 5, and 17 were upregulated, and 7, 13, and 13 were downregulated. Detailed information can be found in Table 3 Table 4 Table 5. When comparing among the alizarin intervention groups at different time points (24 h, 36 h, and 48 h), 59, 157, and 156 differential metabolites were identified, respectively, including 16, 65, and 48 upregulated metabolites, and 43, 92, and 108 downregulated metabolites. Overall, a considerable number of differential metabolites were observed.\u003c/p\u003e\n\u003cp\u003eTable 2\u003cstrong\u003e\u0026nbsp;Statistics of Differential Metabolites\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19.5423%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38.2042%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal differential metabolites\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.5352%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUp\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.7183%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDown\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19.5423%;\"\u003e\n \u003cp\u003eD-24/E-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38.2042%;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.5352%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.7183%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19.5423%;\"\u003e\n \u003cp\u003eD-36/E-36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38.2042%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.5352%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.7183%;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19.5423%;\"\u003e\n \u003cp\u003eD-48/E-48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38.2042%;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.5352%;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.7183%;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19.5423%;\"\u003e\n \u003cp\u003eE-24/E-36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38.2042%;\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.5352%;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.7183%;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19.5423%;\"\u003e\n \u003cp\u003eE-24/E-48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38.2042%;\"\u003e\n \u003cp\u003e157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.5352%;\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.7183%;\"\u003e\n \u003cp\u003e92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19.5423%;\"\u003e\n \u003cp\u003eE-36/E-48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38.2042%;\"\u003e\n \u003cp\u003e156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.5352%;\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.7183%;\"\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 3\u003cstrong\u003e\u0026nbsp;Difference metabolites between DEV control group and alizarin intervention group for 24h\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"537\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.0559%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.7114%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2905%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.0559%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMode\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 34.0782%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eName\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.8082%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFormula\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.0559%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.7114%;\"\u003e\n \u003cp\u003e0.2769\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2905%;\"\u003e\n \u003cp\u003e0.0236\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.0559%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 34.0782%;\"\u003e\n \u003cp\u003eoctopamine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.8082%;\"\u003e\n \u003cp\u003eC\u003csub\u003e8\u003c/sub\u003eH\u003csub\u003e11\u003c/sub\u003eNO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.0559%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.7114%;\"\u003e\n \u003cp\u003e0.0275\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2905%;\"\u003e\n \u003cp\u003e0.0163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.0559%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 34.0782%;\"\u003e\n \u003cp\u003e2-Mercaptobenzothiazole\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.8082%;\"\u003e\n \u003cp\u003eC\u003csub\u003e7\u003c/sub\u003eH\u003csub\u003e5\u003c/sub\u003eNS\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.0559%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.7114%;\"\u003e\n \u003cp\u003e8.2688\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2905%;\"\u003e\n \u003cp\u003e0.0262\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.0559%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 34.0782%;\"\u003e\n \u003cp\u003e2,3-Butynyl prostaglandin E1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.8082%;\"\u003e\n \u003cp\u003eC\u003csub\u003e18\u003c/sub\u003eH\u003csub\u003e30\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.0559%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.7114%;\"\u003e\n \u003cp\u003e0.0070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2905%;\"\u003e\n \u003cp\u003e0.0011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.0559%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 34.0782%;\"\u003e\n \u003cp\u003eHydroquinone trimethyl ether\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.8082%;\"\u003e\n \u003cp\u003eC\u003csub\u003e9\u003c/sub\u003eH\u003csub\u003e12\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.0559%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.7114%;\"\u003e\n \u003cp\u003e0.0252\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2905%;\"\u003e\n \u003cp\u003e0.0212\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.0559%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 34.0782%;\"\u003e\n \u003cp\u003eMaltol isobutyrate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.8082%;\"\u003e\n \u003cp\u003eC\u003csub\u003e10\u003c/sub\u003eH\u003csub\u003e12\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.0559%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.7114%;\"\u003e\n \u003cp\u003e0.2944\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2905%;\"\u003e\n \u003cp\u003e0.0386\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.0559%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 34.0782%;\"\u003e\n \u003cp\u003eMethyl 2-methoxyvinyl-2-oxosulfate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.8082%;\"\u003e\n \u003cp\u003eC\u003csub\u003e13\u003c/sub\u003eH\u003csub\u003e12\u003c/sub\u003eO\u003csub\u003e7\u003c/sub\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.0559%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.7114%;\"\u003e\n \u003cp\u003e0.6526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2905%;\"\u003e\n \u003cp\u003e0.0317\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.0559%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 34.0782%;\"\u003e\n \u003cp\u003e4,5,7-Trihydroxy coumarin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.8082%;\"\u003e\n \u003cp\u003eC\u003csub\u003e9\u003c/sub\u003eH\u003csub\u003e6\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.0559%;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.7114%;\"\u003e\n \u003cp\u003e0.6836\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.2905%;\"\u003e\n \u003cp\u003e0.0261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.0559%;\"\u003e\n \u003cp\u003e－\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 34.0782%;\"\u003e\n \u003cp\u003emethylprednisolone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.8082%;\"\u003e\n \u003cp\u003eC\u003csub\u003e22\u003c/sub\u003eH\u003csub\u003e30\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4\u003cstrong\u003e\u0026nbsp;Difference metabolites between DEV control group and alizarin intervention group for 36 h\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"540\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.1852%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.6296%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.4815%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMode\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32.4074%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eName\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.963%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFormula\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.1852%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.6296%;\"\u003e\n \u003cp\u003e1.4163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3333%;\"\u003e\n \u003cp\u003e0.0421\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.4815%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32.4074%;\"\u003e\n \u003cp\u003epantothenic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.963%;\"\u003e\n \u003cp\u003eC\u003csub\u003e9\u003c/sub\u003eH\u003csub\u003e17\u003c/sub\u003eNO\u003csub\u003e5\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.1852%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.6296%;\"\u003e\n \u003cp\u003e0.3792\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3333%;\"\u003e\n \u003cp\u003e0.0296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.4815%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32.4074%;\"\u003e\n \u003cp\u003e1-Stearoyl glycerol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.963%;\"\u003e\n \u003cp\u003eC\u003csub\u003e21\u003c/sub\u003eH\u003csub\u003e42\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.1852%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.6296%;\"\u003e\n \u003cp\u003e0.5342\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3333%;\"\u003e\n \u003cp\u003e0.0143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.4815%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32.4074%;\"\u003e\n \u003cp\u003emuscone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.963%;\"\u003e\n \u003cp\u003eC\u003csub\u003e16\u003c/sub\u003eH\u003csub\u003e30\u003c/sub\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.1852%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.6296%;\"\u003e\n \u003cp\u003e1.5826\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3333%;\"\u003e\n \u003cp\u003e0.0416\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.4815%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32.4074%;\"\u003e\n \u003cp\u003eDL-carnitine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.963%;\"\u003e\n \u003cp\u003eC\u003csub\u003e7\u003c/sub\u003eH\u003csub\u003e15\u003c/sub\u003eNO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.1852%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.6296%;\"\u003e\n \u003cp\u003e1.2800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3333%;\"\u003e\n \u003cp\u003e0.0233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.4815%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32.4074%;\"\u003e\n \u003cp\u003eN-Vinylformamide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.963%;\"\u003e\n \u003cp\u003eC\u003csub\u003e3\u003c/sub\u003eH\u003csub\u003e5\u003c/sub\u003eNO\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.1852%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.6296%;\"\u003e\n \u003cp\u003e1.5884\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3333%;\"\u003e\n \u003cp\u003e0.0188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.4815%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32.4074%;\"\u003e\n \u003cp\u003eCitric acid derivative of 1,3-dimethylbutylamine \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.963%;\"\u003e\n \u003cp\u003eC\u003csub\u003e12\u003c/sub\u003eH\u003csub\u003e23\u003c/sub\u003eNO\u003csub\u003e7\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.1852%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.6296%;\"\u003e\n \u003cp\u003e0.1916\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3333%;\"\u003e\n \u003cp\u003e0.0254\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.4815%;\"\u003e\n \u003cp\u003e－\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32.4074%;\"\u003e\n \u003cp\u003e4-Heptylphenyl 4-heptylbenzoic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.963%;\"\u003e\n \u003cp\u003eC\u003csub\u003e27\u003c/sub\u003eH\u003csub\u003e38\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.1852%;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.6296%;\"\u003e\n \u003cp\u003e1.7324\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3333%;\"\u003e\n \u003cp\u003e0.0156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.4815%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32.4074%;\"\u003e\n \u003cp\u003eacetylcarnitine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.963%;\"\u003e\n \u003cp\u003eC\u003csub\u003e9\u003c/sub\u003eH\u003csub\u003e17\u003c/sub\u003eNO\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.1852%;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.6296%;\"\u003e\n \u003cp\u003e0.3657\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3333%;\"\u003e\n \u003cp\u003e0.0434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.4815%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32.4074%;\"\u003e\n \u003cp\u003eN-Docosadienoyl ethanolamine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.963%;\"\u003e\n \u003cp\u003eC\u003csub\u003e22\u003c/sub\u003eH\u003csub\u003e41\u003c/sub\u003eNO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.1852%;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.6296%;\"\u003e\n \u003cp\u003e0.6526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3333%;\"\u003e\n \u003cp\u003e0.0347\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.4815%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32.4074%;\"\u003e\n \u003cp\u003eUndecanamide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.963%;\"\u003e\n \u003cp\u003eC\u003csub\u003e37\u003c/sub\u003eH\u003csub\u003e73\u003c/sub\u003eNO\u003csub\u003e5\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.1852%;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.6296%;\"\u003e\n \u003cp\u003e0.4904\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3333%;\"\u003e\n \u003cp\u003e0.0045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.4815%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32.4074%;\"\u003e\n \u003cp\u003e2,6,10-Trimethyl-2,6,10-tritriacontene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.963%;\"\u003e\n \u003cp\u003eC\u003csub\u003e16\u003c/sub\u003eH\u003csub\u003e28\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.1852%;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.6296%;\"\u003e\n \u003cp\u003e0.5561\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3333%;\"\u003e\n \u003cp\u003e0.0180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.4815%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32.4074%;\"\u003e\n \u003cp\u003eMono-hydroxylated rapeseed oil glycerol fatty acid ester\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.963%;\"\u003e\n \u003cp\u003eC\u003csub\u003e19\u003c/sub\u003eH\u003csub\u003e38\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.1852%;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.6296%;\"\u003e\n \u003cp\u003e0.4343\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3333%;\"\u003e\n \u003cp\u003e0.0122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.4815%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32.4074%;\"\u003e\n \u003cp\u003e1 - Monoglyceride of palmitic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.963%;\"\u003e\n \u003cp\u003eC\u003csub\u003e16\u003c/sub\u003eH\u003csub\u003e32\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.1852%;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.6296%;\"\u003e\n \u003cp\u003e0.4910\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3333%;\"\u003e\n \u003cp\u003e0.0309\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.4815%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32.4074%;\"\u003e\n \u003cp\u003ebortezomib\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.963%;\"\u003e\n \u003cp\u003eC\u003csub\u003e19\u003c/sub\u003eH\u003csub\u003e25\u003c/sub\u003eBN\u003csub\u003e4\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.1852%;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.6296%;\"\u003e\n \u003cp\u003e0.6204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3333%;\"\u003e\n \u003cp\u003e0.0443\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.4815%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32.4074%;\"\u003e\n \u003cp\u003ePalovarotene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.963%;\"\u003e\n \u003cp\u003eC\u003csub\u003e27\u003c/sub\u003eH\u003csub\u003e30\u003c/sub\u003eN\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.1852%;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.6296%;\"\u003e\n \u003cp\u003e0.3572\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3333%;\"\u003e\n \u003cp\u003e0.0014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.4815%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32.4074%;\"\u003e\n \u003cp\u003e4-Hydroxy-3-octylphenyl benzoate \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.963%;\"\u003e\n \u003cp\u003eC\u003csub\u003e47\u003c/sub\u003eH\u003csub\u003e70\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.1852%;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.6296%;\"\u003e\n \u003cp\u003e0.4784\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3333%;\"\u003e\n \u003cp\u003e0.0438\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.4815%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32.4074%;\"\u003e\n \u003cp\u003eGlyceryl Monostearate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.963%;\"\u003e\n \u003cp\u003eC\u003csub\u003e20\u003c/sub\u003eH\u003csub\u003e40\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.1852%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.6296%;\"\u003e\n \u003cp\u003e0.3298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3333%;\"\u003e\n \u003cp\u003e0.0150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.4815%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32.4074%;\"\u003e\n \u003cp\u003e3-Sulfodeoxycholic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.963%;\"\u003e\n \u003cp\u003eC\u003csub\u003e23\u003c/sub\u003eH\u003csub\u003e38\u003c/sub\u003eO\u003csub\u003e7\u003c/sub\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 5\u003cstrong\u003e\u0026nbsp;Difference metabolites between DEV control group and alizarin intervention group for 48 h\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"551\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMode\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eName\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFormula\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e1.2558\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0387\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e－\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003eL-glutamic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e5\u003c/sub\u003eH\u003csub\u003e9\u003c/sub\u003eNO\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e0.6110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0378\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003eIndole-3-acrylic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e11\u003c/sub\u003eH\u003csub\u003e9\u003c/sub\u003eNO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e1.5163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003eAlkenylsuccinic anhydrides\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e16\u003c/sub\u003eH\u003csub\u003e26\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e2.0516\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0242\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003ecitral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e10\u003c/sub\u003eH\u003csub\u003e16\u003c/sub\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e2.0841\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003e\u0026gamma;-Linolenic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e18\u003c/sub\u003eH\u003csub\u003e30\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e1.3992\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0290\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e－\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003eoxalic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e2\u003c/sub\u003eH\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e1.2469\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0299\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e－\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003esaccharopine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e11\u003c/sub\u003eH\u003csub\u003e20\u003c/sub\u003eN\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e6\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e0.7092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0293\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003e1,3,5(10)-Trien-3-yl sulfate \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e18\u003c/sub\u003eH\u003csub\u003e24\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e0.5549\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e－\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003elactic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e3\u003c/sub\u003eH\u003csub\u003e6\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e0.8002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003eS-(2,5-Dimethyl-3-furyl) 2-furan sulfic acid ester \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e11\u003c/sub\u003eH\u003csub\u003e10\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e0.3838\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003emeprobamate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e9\u003c/sub\u003eH\u003csub\u003e18\u003c/sub\u003eN\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e0.5794\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003eCyclic nylon dimer\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e12\u003c/sub\u003eH\u003csub\u003e22\u003c/sub\u003eN\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e0.5825\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0355\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003eTetraacetylethylenediamine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e10\u003c/sub\u003eH\u003csub\u003e16\u003c/sub\u003eN\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e0.5800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003eN-Methyl-1H-indole-3-propanamide \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e12\u003c/sub\u003eH\u003csub\u003e14\u003c/sub\u003eN\u003csub\u003e2\u003c/sub\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e1.6402\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003exanthopterin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e6\u003c/sub\u003eH\u003csub\u003e5\u003c/sub\u003eN\u003csub\u003e5\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e1.2432\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0205\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003e7-(3-Chloro-2-hydroxy-3-methylbutoxy)-8-(3-methyl-2-oxobutyl)coumarin \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e19\u003c/sub\u003eH\u003csub\u003e23\u003c/sub\u003eClO\u003csub\u003e5\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e0.4103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003eAmiloride\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e15\u003c/sub\u003eH\u003csub\u003e20\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e0.4086\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003ecumyl hydroperoxide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e9\u003c/sub\u003eH\u003csub\u003e12\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e1.4604\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0286\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e－\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003eMethylprednisolone Hemisuccinate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e25\u003c/sub\u003eH\u003csub\u003e32\u003c/sub\u003eO\u003csub\u003e8\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e1.5532\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003ebutyrate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e16\u003c/sub\u003eH\u003csub\u003e28\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e1.3784\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0277\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003eN,N-Bis(2-hydroxyethyl) dodecanamide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e16\u003c/sub\u003eH\u003csub\u003e33\u003c/sub\u003eNO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e1.5287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003e2,4-Dihydroxyheptanedioic acid 16-ethynyl ester \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e19\u003c/sub\u003eH\u003csub\u003e34\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e2.2792\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e－\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003eLauric acid sulfate \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e12\u003c/sub\u003eH\u003csub\u003e26\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e2.0535\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0251\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e－\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003eAcetylhexacycline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e15\u003c/sub\u003eH\u003csub\u003e20\u003c/sub\u003eN\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e2.2689\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e－\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003epimobendan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e19\u003c/sub\u003eH\u003csub\u003e18\u003c/sub\u003eN\u003csub\u003e4\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e1.2728\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003e4,6-Cholestadien-3-one\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e27\u003c/sub\u003eH\u003csub\u003e42\u003c/sub\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e0.8177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003eoctadecylamine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e18\u003c/sub\u003eH\u003csub\u003e39\u003c/sub\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e0.6825\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003eestrane\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e18\u003c/sub\u003eH\u003csub\u003e30\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8.89292%;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.245%;\"\u003e\n \u003cp\u003e0.7493\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.9782%;\"\u003e\n \u003cp\u003e0.0046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.3448%;\"\u003e\n \u003cp\u003e＋\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.2087%;\"\u003e\n \u003cp\u003e1-Stearoyl-2-hydroxy-sn-glycerol-3-polyethylene glycol \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.3303%;\"\u003e\n \u003cp\u003eC\u003csub\u003e23\u003c/sub\u003eH\u003csub\u003e48\u003c/sub\u003eNO\u003csub\u003e7\u003c/sub\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e③Cluster analysis of differentially expressed metabolites\u0026nbsp;\u003c/strong\u003eDifferential metabolite clustering analysis was performed on the expression levels of differentially expressed metabolites in the DEV infection group and the alizarin intervention group at various time points. As shown in Fig. 10,the results indicated that, compared with the alizarin intervention group, the expression levels of differentially expressed metabolites in the DEV infection group exhibited significant variation across time points (24 h, 36 h, and 48 h). Specifically, the expression levels in the DEV infection group increased over time, whereas those in the alizarin intervention group decreased. Furthermore, when comparing the alizarin intervention groups across time points, notable differences were observed in metabolite expression levels, with the E-24 group showing the highest expression and the E-48 group exhibiting the lowest.\u003c/p\u003e\n\u003cp\u003eEach row represents a differentially expressed metabolite, each column represents a sample, and the color intensity reflects the expression level, with blue indicating low expression and red indicating high expression.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003cstrong\u003eAnalysis of the effects of alizarin on metabolic pathways associated with DEV proliferation\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs illustrated in Fig. 11,analysis of metabolic pathways associated with the 24 h alizarin intervention group and the DEV infection group revealed that differentially expressed metabolites were predominantly enriched in pathways including alanine, aspartate, and glutamate metabolism; \u0026beta;-alanine metabolism; butyric acid metabolism; neuroactive ligand-receptor interaction; nicotinate and nicotinamide metabolism; and arginine and proline metabolism. Comparative analysis of metabolic pathways between the 36 h alizarin intervention group and the DEV infection group indicated significant enrichment of differentially expressed metabolites in pantothenate and CoA biosynthesis; \u0026beta;-alanine metabolism; fatty acid elongation, degradation, and biosynthesis; biosynthesis of unsaturated fatty acids; biosynthesis of terpenoids including ubiquinone; and overall fatty acid metabolism. Analysis of metabolic pathways linked to the 48 h alizarin intervention group and the DEV infection group demonstrated enrichment of differentially expressed metabolites in 2-oxocarboxylic acid metabolism; FoxO signaling pathway; D-glutamine and D-glutamate metabolism; nitrogen metabolism; taurine and hypotaurine metabolism; arginine biosynthesis; alanine, aspartate, and glutamate metabolism; and sulfur metabolism.\u003c/p\u003e\n\u003cp\u003eAnalysis of metabolic pathways associated with the 24 h and 36 h alizarin intervention groups revealed that differentially expressed metabolites were predominantly enriched in pathways including ABC transporters; aminoacyl-tRNA biosynthesis; amino acid biosynthesis; arginine and proline metabolism; \u0026beta;-alanine metabolism; glycine, serine, and threonine metabolism; tryptophan metabolism; and the pentose phosphate pathway. \u0026nbsp;Comparative analysis of metabolic pathways between the 24 h and 48 h alizarin intervention groups indicated significant enrichment of differentially expressed metabolites in ABC transporters; \u0026beta;-alanine metabolism; amino acid biosynthesis; arginine and proline metabolism; glycine, serine, and threonine metabolism; purine metabolism; the pentose phosphate pathway; and phenylalanine metabolism. Analysis of metabolic pathways linked to the 36 h and 48 h alizarin intervention groups demonstrated enrichment of differentially expressed metabolites in pantothenate and CoA biosynthesis; unsaturated fatty acid biosynthesis; ABC transporters; linoleic acid metabolism; arginine and proline metabolism; tyrosine metabolism; and purine metabolism.\u003c/p\u003e"},{"header":"3 Discussion","content":"\u003ch2\u003e3.1 Analysis of the effect of alizarin on the proliferation of DEV in DEF cells\u003c/h2\u003e\n\u003cp\u003eDuck viral enteritis, commonly referred to as duck plague, is caused by a virus belonging to the family Herpesviridae, subfamily Alphaherpesvirinae, and genus Meleagrid herpesvirus. This disease can induce acute, febrile, and highly contagious infections in ducks, geese, and other species of waterfowl\u003csup\u003e[20]\u003c/sup\u003e.The characteristic pathological changes associated with duck viral enteritis include vascular damage and hemorrhage in the intestine, lesions in lymphoid organs, and degenerative alterations in parenchymal organs\u003csup\u003e[21]\u003c/sup\u003e. The disease spreads rapidly, affects a wide range of waterfowl species, and is marked by high incidence and mortality rates. It represents one of the major diseases currently threatening the global duck industry, resulting in substantial economic losses.\u003c/p\u003e\n\u003cp\u003eCurrently, due to the absence of effective anti-DEV therapeutic options in the market, the prevention and control of duck viral enteritis primarily depend on vaccination\u003csup\u003e[22]\u003c/sup\u003e.However, the incidence and mortality rates of DVE remain elevated. Given the increasing prevalence of antibiotic resistance associated with the misuse and overuse of antibiotics\u003csup\u003e[23]\u003c/sup\u003e\u003csup\u003e[24]\u003c/sup\u003e, the development of novel \u0026quot;antibiotic-free\u0026quot; or \u0026quot;reduced-antibiotic\u0026quot; therapeutic agents against DEV is of critical importance for the effective prevention and treatment of DVE.\u003c/p\u003e\n\u003cp\u003eRubia cordifolia, commonly referred to as madder or dyeweed, was historically utilized as a natural dye\u0026nbsp;\u003csup\u003e[25]\u003c/sup\u003e. However, recent studies have demonstrated that it also exhibits pharmacological activities, including hemostatic, anti-inflammatory, antiviral, and broad-spectrum antibacterial effects. alizarin is the key bioactive constituent of Rubia cordifolia. To date, extensive research has documented the anticancer properties of alizarin; however, investigations into its potential antiviral activity against DEV remain scarce. Therefore, this study selected alizarin to evaluate its inhibitory effect on DEV proliferation in vitro.The TCID\u003csub\u003e50\u003c/sub\u003e of DEV was calculated as 3.98 \u0026times; 10⁻⁵/0.1 mL using the Reed-Muench method based on CPE observation. Concurrently, the maximum non-toxic concentration of alizarin was determined to be 0.05 mg/mL through the CCK-8 assay. Based on these results, the effect of alizarin on DEV proliferation in DEF cells was examined and validated using q-PCR technology.\u003c/p\u003e\n\u003ch2 id=\"_Toc129857119\"\u003e3.2 Analysis of the Molecular Mechanism Underlying alizarin-Mediated Regulation of DEV Proliferation Based on Metabolomics Research\u003c/h2\u003e\n\u003cp\u003eWith the rapid advancement of big data technologies, metabolomics has been extensively applied in various fields, including the elucidation of drug mechanisms of action, evaluation of therapeutic efficacy, identification of relevant metabolic biomarkers, and development of diagnostic models. Notably, research focusing on the detection of active components in traditional Chinese medicine using metabolomics-based sequencing techniques has seen a significant increase\u003csup\u003e[25]\u003c/sup\u003e.Metabolomic analysis of rats infected with respiratory syncytial virus (RSV) and administered Dingchuan Decoction revealed that the decoction could normalize the altered levels of bile acids, amino acids, and organic acids induced by RSV infection, as well as modulate the dysbiosis of the intestinal microbiota and immune system. Additionally, it demonstrated a regulatory effect on abnormal lipid metabolites\u003csup\u003e[26]\u003c/sup\u003e.Treatment with forsythoside (PHI) and baicalin (Bai) compounds may modulate key metabolic pathways such as amino acid biosynthesis, carbon metabolism, phenylalanine metabolism, alanine, aspartate, and glutamate metabolism, 2-oxocarboxylic acid metabolism, and \u0026beta;-alanine metabolism, thereby exerting regulatory effects on the respiratory tract microbiota and metabolic disturbances in chickens infected with infectious bronchitis virus (IBV)\u003csup\u003e[27]\u003c/sup\u003e.Metabolomics integrated with network pharmacology analysis of RD cells infected with enterovirus 71 (EV71) and treated with AST-IV revealed that AST-IV may activate cAMP signaling and antioxidant stress responses by targeting eight key metabolites\u0026mdash;hypoxanthine, 2-ketobutyric acid, adenine, nicotinamide mononucleotide, prostaglandin H₂, 6-hydroxy-1H-indole-3-acetamide, hypoxanthine, and phosphocholine (PC)\u0026mdash;thereby stimulating the PI3K-AKT signaling pathway and inhibiting EV71-induced apoptosis and viral replication\u003csup\u003e[28]\u003c/sup\u003e.In the metabolite profiling results, 8, 18, and 30 differential metabolites were identified when comparing the DEV infection group with the alizarin intervention group at 24 h, 36 h, and 48 h, respectively. Furthermore, 59, 157, and 156 differential metabolites were detected when comparing the alizarin intervention groups across different time points (24 h, 36 h, and 48 h). Among these, immune-related metabolites included indole-3-acrylic acid, L-glutamic acid, and DL-carnitine. Compared with the DEV infection group, the alizarin intervention group exhibited 6, 8, and 10 significantly enriched metabolic pathways at 24 h, 36 h, and 48 h, respectively. When comparing the alizarin intervention groups across time points (24 h vs. 36 h, 24 h vs. 48 h, 36 h vs. 48 h), a total of 10 major enriched metabolic pathways were consistently observed, including those associated with immunity such as D-glutamine and D-glutamic acid metabolism, tryptophan metabolism, and arginine and proline metabolism.It is evident that as time progresses, the number of differential metabolites increases, a trend that aligns generally with the overall variation pattern of differentially expressed genes observed in duodenal transcriptomic analysis at 72 h, 96 h, and 120 h post-DEV infection\u003csup\u003e[29]\u003c/sup\u003e.The primary explanation may be that following the invasion of pathogenic microorganisms into the host, the duodenal mucosa progressively activates an immune response. After a certain time interval, the defensive capacity is enhanced, leading to a gradual reduction in the number of differential metabolites and differentially expressed genes.\u003c/p\u003e\n\u003cp\u003eAmong the top five metabolites with the smallest p-values identified through comparisons between the DEV infection group and the alizarin intervention group at different time points, indole-3-propionic acid, L-glutamic acid, and acetylcarnitine are all associated with immune-inflammatory responses. Notably, indole-3-propionic acid is a metabolite derived from tryptophan, and the tryptophan metabolic pathway has been implicated in the regulation of inflammation.\u003c/p\u003e\n\u003cp\u003eL-tryptophan, indole-3-propionic acid, and their endogenous metabolites involved in tryptophan metabolism represent an essential class of nutrients in mammals, which are closely associated with intestinal immune homeostasis and the pathogenesis of various immune-mediated diseases\u003csup\u003e[30]\u003c/sup\u003e.Abnormal metabolism of the intestinal microbiota and dysregulated levels of indole-3-lactic acid (ILA) have been observed in patients with colorectal cancer (CRC). Indole-3-lactic acid (ILA) has been shown to inhibit tumor cell proliferation, migration, and anti-apoptotic activity through metabolic reprogramming\u003csup\u003e[31]\u003c/sup\u003e. Sinomenine (SIN) demonstrates potent immunosuppressive and anti-inflammatory properties in the treatment of rheumatoid arthritis through the upregulation of microbial-derived tryptophan metabolites, including indole-3-acrylic acid (IA), indole-3-propionic acid (IPA), and indole-3-acetic acid (IAA)\u003csup\u003e[32]\u003c/sup\u003e.In this study, the alizarin intervention group suppressed virus-induced immunosuppressive pathways through down-regulation of immunosuppressive metabolites such as indole-3-acrylic acid and citral. Furthermore, the intervention enhanced the immune response by up-regulating key metabolites including glutamate, aspartate, and asparagine within the glutamine metabolic pathway.\u003c/p\u003e"},{"header":"4 Overall Conclusion","content":"\u003cp\u003ealizarin demonstrates the ability to inhibit DEV proliferation in DEF cells. The underlying mechanism involves the suppression of viral replication through the modulation of multiple amino acid metabolic pathways, including those of tryptophan and arginine, leading to the differential expression of associated metabolites such as indole-3-acrylic acid, L-glutamic acid, and DL-carnitine.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64.3059%;\"\u003e\n \u003cp\u003e\u0026nbsp;full name\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.6941%;\"\u003e\n \u003cp\u003eabbreviation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64.3059%;\"\u003e\n \u003cp\u003eDuckVirus Enteritis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.6941%;\"\u003e\n \u003cp\u003eDVE\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64.3059%;\"\u003e\n \u003cp\u003eDuck Enteritis Virus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.6941%;\"\u003e\n \u003cp\u003eDEV\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64.3059%;\"\u003e\n \u003cp\u003eFetal Bovine Serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.6941%;\"\u003e\n \u003cp\u003eFBS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64.3059%;\"\u003e\n \u003cp\u003eDuck Embryo Fibroblast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.6941%;\"\u003e\n \u003cp\u003eDEF\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64.3059%;\"\u003e\n \u003cp\u003ePrincipal Component Analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.6941%;\"\u003e\n \u003cp\u003ePCA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64.3059%;\"\u003e\n \u003cp\u003eKyoto Encyclopedia of Genesand Genomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.6941%;\"\u003e\n \u003cp\u003eKEGG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64.3059%;\"\u003e\n \u003cp\u003ePolymerase Chain Reaction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.6941%;\"\u003e\n \u003cp\u003ePCR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64.3059%;\"\u003e\n \u003cp\u003eTissue Culture Infective Dose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.6941%;\"\u003e\n \u003cp\u003eTCID\u003csub\u003e50\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64.3059%;\"\u003e\n \u003cp\u003eQuality Control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.6941%;\"\u003e\n \u003cp\u003eQC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64.3059%;\"\u003e\n \u003cp\u003eHuman Metabolome Database\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.6941%;\"\u003e\n \u003cp\u003eHMDB\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64.3059%;\"\u003e\n \u003cp\u003eSpecific-pathogen-free\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.6941%;\"\u003e\n \u003cp\u003e\u0026nbsp;SPF\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64.3059%;\"\u003e\n \u003cp\u003eEntero virus A71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.6941%;\"\u003e\n \u003cp\u003eEV-A71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64.3059%;\"\u003e\n \u003cp\u003eRespiratory Syncytial Virus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.6941%;\"\u003e\n \u003cp\u003eRSV\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64.3059%;\"\u003e\n \u003cp\u003eAngiotensin Converting Enzyme2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.6941%;\"\u003e\n \u003cp\u003eACE2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64.3059%;\"\u003e\n \u003cp\u003eNoro virus-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.6941%;\"\u003e\n \u003cp\u003eMNV-1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64.3059%;\"\u003e\n \u003cp\u003ePorcine Reproductiveand Respiratory Syndrome Virus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.6941%;\"\u003e\n \u003cp\u003ePRRSV\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64.3059%;\"\u003e\n \u003cp\u003eHour\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.6941%;\"\u003e\n \u003cp\u003eh\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e①Ethics approval and consent to participate:All experimental procedures were approved by the Institutional Animal Ethics Committee from The Guizhou University (EAE-GZU-2021-T005).The owner\u0026apos;s informed consent has been obtained.\u003c/p\u003e\n\u003cp\u003e②Consent for publication:Not Applicable\u003c/p\u003e\n\u003cp\u003e③Availability of data and materials:Data is provided within the manuscript or supplementary information files.\u003c/p\u003e\n\u003cp\u003e④Competing interests:There are no conflicts of interest to declare.\u003c/p\u003e\n\u003cp\u003e⑤Funding:Open Access funding enabled and organized by National Natural Science Foundation of China \u0026quot; Analysis of the molecular mechanism of DEV regulating calcium channels to promote inflammatory response of duck intestinal mucosal epithelial cells\u0026quot; (700626231135).\u003c/p\u003e\n\u003cp\u003e⑥Authors\u0026apos; contributions:WangYan, wrote the main manuscript, prepared the figures and tables, analysed the data and reviewed the manuscript. Bi Wenwen and WenMing were involved in the interpretation of the results and reviewed the manuscript. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e⑦Acknowledgements:The authors thank Ming Wen and Bi Wenwen for their assistance with the experiment and writing.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFleury HJ, Babin M, Bonnici JF, et al. First simultaneous isolation of influenza A virus and duck enteritis virus from commercial ducks in France. \u003cem\u003eVet Rec\u003c/em\u003e. 1986;119(9):208-209. doi:10.1136/vr.119.9.208.https://doi.org/10.1136/vr.119.9.208\u003c/li\u003e\n\u003cli\u003eEl-Tholoth M, Hamed MF, Matter AA, Abou El-Azm KI. Molecular and pathological characterization of duck enteritis virus in Egypt. Transbound Emerg Dis. 2019;66(1):217-224. doi:10.1111/tbed.13002.https://doi.org/10.1111/tbed.13002\u003c/li\u003e\n\u003cli\u003eTang W, Yuan M, Mao M, et al. Pathogenicity studies and molecular characterization of DPV infection in ducklings. Poult Sci. 2024;103(9):103919. doi:10.1016/j.psj.2024.103919\u003c/li\u003e\n\u003cli\u003eLevy SB, Marshall B. Antibacterial resistance worldwide: causes, challenges and responses. Nat Med. 2004;10(12 Suppl):S122-S129. doi:10.1038/nm1145. https://doi.org/10.1038/nm1145\u003c/li\u003e\n\u003cli\u003eLi J, Feng S, Liu X, et al. Effects of Traditional Chinese Medicine and its Active Ingredients on Drug-Resistant Bacteria. Front Pharmacol. 2022;13:837907. Published 2022 Jun 2. doi:10.3389/fphar.2022.837907. https://doi.org/10.3389/fphar.2022.837907\u003c/li\u003e\n\u003cli\u003eZeng W, Fang Y, Mo S, et al. The Underling Mechanisms Exploration of Rubia cordifolia L. Extract Against Rheumatoid Arthritis by Integrating Network Pharmacology and Metabolomics. Drug Des Devel Ther. 2023;17:439-457. Published 2023 Feb 11. doi:10.2147/DDDT.S388932. https://doi.org/10.2147/DDDT.S388932\u003c/li\u003e\n\u003cli\u003eBoldizs\u0026aacute;r I, Szucs Z, F\u0026uuml;zfai Z, Moln\u0026aacute;r-Perl I. Identification and quantification of the constituents of madder root by gas chromatography and high-performance liquid chromatography. J Chromatogr A. 2006;1133(1-2):259-274. doi:10.1016/j.chroma.2006.08.021. https://doi.org/10.1016/j.chroma.2006.08.021\u003c/li\u003e\n\u003cli\u003eParamasivam S, Perumal SS. Methanolic extract of O.umbellata L. exhibits anti-osteoporotic effect via promoting osteoblast proliferation in MG-63 cells and inhibiting osteoclastogenesis in RANKL-stimulated RAW 264.7 cells. J Ethnopharmacol. 2023;315:116641. doi:10.1016/j.jep.2023.116641. https://doi.org/10.1016/j.jep.2023.116641\u003c/li\u003e\n\u003cli\u003eLi C, Tian L, Wang Y, et al. M13, an anthraquinone compound isolated from Morinda officinalis promotes the osteogenic differentiation of MSCs by targeting Wnt/\u0026beta;-catenin signaling. Phytomedicine. 2023;108:154542. doi:10.1016/j.phymed.2022.154542. https://doi.org/10.1016/j.phymed.2022.154542\u003c/li\u003e\n\u003cli\u003eTsuchiya T, Takagi Y, Yamada H. Preparation of 5-(2,6-dideoxy-2-fluoro-alpha-L-talopyranosyloxy)-6-hydroxynap htho[2,3- f]quinoline-7,12-dione (FT-Alz), a new-type, potentially antitumor substance with various biological activities. Bioorg Med Chem Lett. 2000;10(3):203-207. doi:10.1016/s0960-894x(99)00655-1. https://doi.org/10.1016/s0960-894x(99)00655-1\u003c/li\u003e\n\u003cli\u003eShen CH, Liu CT, Song XJ, et al. Evaluation of analgesic and anti-inflammatory activities of Rubia cordifolia L. by spectrum-effect relationships. J Chromatogr B Analyt Technol Biomed Life Sci. 2018;1090:73-80. doi:10.1016/j.jchromb.2018.05.021. https://doi.org/10.1016/j.jchromb.2018.05.021\u003c/li\u003e\n\u003cli\u003eGandhi MR, Reegan AD, Ganesan P, et al. Larvicidal and Pupicidal Activities of Alizarin Isolated from Roots of Rubia cordifolia Against Culex quinquefasciatus Say and Aedes aegypti (L.) (Diptera: Culicidae). Neotrop Entomol. 2016;45(4):441-448. doi:10.1007/s13744-016-0386-x. https://doi.org/10.1007/s13744-016-0386-x\u003c/li\u003e\n\u003cli\u003eWang W, Zhang J, Qi W, Su R, He Z, Peng X. Alizarin and Purpurin from Rubia tinctorum L. Suppress Insulin Fibrillation and Reduce the Amyloid-Induced Cytotoxicity. ACS Chem Neurosci. 2021;12(12):2182-2193. doi:10.1021/acschemneuro.1c00177. https://doi.org/10.1021/acschemneuro.1c00177\u003c/li\u003e\n\u003cli\u003eGiera M, Yanes O, Siuzdak G. Metabolite discovery: Biochemistry\u0026apos;s scientific driver. Cell Metab. 2022;34(1):21-34. doi:10.1016/j.cmet.2021.11.005\u003c/li\u003e\n\u003cli\u003eElrashedy A, Mousa W, Nayel M, et al. Advances in bioinformatics and multi-omics integration: transforming viral infectious disease research in veterinary medicine. Virol J. 2025;22(1):22. Published 2025 Jan 31. doi:10.1186/s12985-025-02640-x. https://doi.org/10.1186/s12985-025-02640-x\u003c/li\u003e\n\u003cli\u003eTounta V, Liu Y, Cheyne A, Larrouy-Maumus G. Metabolomics in infectious diseases and drug discovery. Mol Omics. 2021;17(3):376-393. doi:10.1039/d1mo00017a. https://doi.org/10.1039/d1mo00017a\u003c/li\u003e\n\u003cli\u003eShen B, Yi X, Sun Y, et al. Proteomic and Metabolomic Characterization of COVID-19 Patient Sera. Cell. 2020;182(1):59-72.e15. doi:10.1016/j.cell.2020.05.032. https://doi.org/10.1016/j.cell.2020.05.032\u003c/li\u003e\n\u003cli\u003eElrashedy A, Mousa W, Nayel M, et al. Advances in bioinformatics and multi-omics integration: transforming viral infectious disease research in veterinary medicine. Virol J. 2025;22(1):22. Published 2025 Jan 31. doi:10.1186/s12985-025-02640-x. https://doi.org/10.1186/s12985-025-02640-x\u003c/li\u003e\n\u003cli\u003eWang M, Chen L, Liu D, Chen H, Tang DD, Zhao YY. Metabolomics highlights pharmacological bioactivity and biochemical mechanism of traditional Chinese medicine. Chem Biol Interact. 2017;273:133-141. doi:10.1016/j.cbi.2017.06.011. https://doi.org/10.1016/j.cbi.2017.06.011\u003c/li\u003e\n\u003cli\u003eDhama K, Kumar N, Saminathan M, et al. Duck virus enteritis (duck plague) - a comprehensive update. Vet Q. 2017;37(1):57-80. doi:10.1080/01652176.2017.1298885. https://doi.org/10.1080/01652176.2017.1298885\u003c/li\u003e\n\u003cli\u003eLi N, Hong T, Li R, et al. Pathogenicity of duck plague and innate immune responses of the Cherry Valley ducks to duck plague virus. Sci Rep. 2016;6:32183. Published 2016 Aug 24. doi:10.1038/srep32183\u003c/li\u003e\n\u003cli\u003eJia WF, Wang AP, Wu Z, Lei XN, Cheng YT, Zhu SY. Current status of recombinant duck enteritis virus vector vaccine research. Front Vet Sci. 2025;12:1453150. Published 2025 Feb 5. doi:10.3389/fvets.2025.1453150. https://doi.org/10.3389/fvets.2025.1453150\u003c/li\u003e\n\u003cli\u003eAllel K, Fernandez-Miyakawa M, Gaze W, et al. Opportunities and challenges in antimicrobial resistance policy including animal production systems and humans across stakeholders in Argentina: a context and qualitative analysis. BMJ Open. 2024;14(6):e082156. Published 2024 Jun 17. doi:10.1136/bmjopen-2023-082156.\u003c/li\u003e\n\u003cli\u003eFord L, Henderson RL, Rayner CM, Blackburn RS. Mild extraction methods using aqueous glucose solution for the analysis of natural dyes in textile artefacts dyed with Dyer\u0026apos;s madder (Rubia tinctorum L.). J Chromatogr A. 2017;1487:36-46. doi:10.1016/j.chroma.2017.01.053. https://doi.org/10.1016/j.chroma.2017.01.053\u003c/li\u003e\n\u003cli\u003eWang XJ, Ren JL, Zhang AH, et al. Novel applications of mass spectrometry-based metabolomics in herbal medicines and its active ingredients: Current evidence. Mass Spectrom Rev. 2019;38(4-5):380-402. doi:10.1002/mas.21589. https://doi.org/10.1002/mas.21589\u003c/li\u003e\n\u003cli\u003eOuyang Y, Chi L, Xu C, Zhao X, Cui Z. Se Pu. 2021;39(3):281-290. doi:10.3724/SP.J.1123.2020.06013. https://doi.org/10.3724/SP.J.1123.2020.06013\u003c/li\u003e\n\u003cli\u003eFeng H, Zhang J, Zhang K, et al. Synergistic anti-infectious bronchitis virus activity of Phillygenin combined Baicalin by modulating respiratory microbiota and improving metabolic disorders. Poult Sci. 2024;103(2):103371. doi:10.1016/j.psj.2023.103371\u003c/li\u003e\n\u003cli\u003eHao J, Zhang X, Hu R, et al. Metabolomics combined with network pharmacology reveals a role for astragaloside IV in inhibiting enterovirus 71 replication via PI3K-AKT signaling. J Transl Med. 2024;22(1):555. Published 2024 Jun 10. doi:10.1186/s12967-024-05355-9. https://doi.org/10.1186/s12967-024-05355-9\u003c/li\u003e\n\u003cli\u003eCai H, Yang X, Yang Y, et al. Untargeted metabolomics of the intestinal tract of DEV-infected ducks. Virol J. 2023;20(1):305. Published 2023 Dec 19. doi:10.1186/s12985-023-02266-x. https://doi.org/10.1186/s12985-023-02266-x\u003c/li\u003e\n\u003cli\u003eShen R, Zhang Y. Relationship between amino acid metabolism and inflammation in coronary heart disease (Review). Int J Mol Med. 2025;56(2):120. doi:10.3892/ijmm.2025.5561. https://doi.org/10.3892/ijmm.2025.5561\u003c/li\u003e\n\u003cli\u003eZhou S, Wang K, Huang J, et al. Indole-3-lactic acid suppresses colorectal cancer via metabolic reprogramming. Gut Microbes. 2025;17(1):2508949. doi:10.1080/19490976.2025.2508949. https://doi.org/10.1080/19490976.2025.2508949\u003c/li\u003e\n\u003cli\u003eJiang ZM, Zeng SL, Huang TQ, et al. Sinomenine ameliorates rheumatoid arthritis by modulating tryptophan metabolism and activating aryl hydrocarbon receptor via gut microbiota regulation. Sci Bull (Beijing). 2023;68(14):1540-1555. doi:10.1016/j.scib.2023.06.027. https://doi.org/10.1016/j.scib.2023.06.027\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"alizarin, duck enteritis virus, duck embryo fibroblast cells, metabonomics, signal pathway","lastPublishedDoi":"10.21203/rs.3.rs-7112922/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7112922/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e(background）Alizarin is the main active component in traditional Chinese medicines such as Rubia cordifolia and Lonicera japonica, and it has anti-inflammatory and antiviral effects. It has been demonstrated that Rubia cordifolia can effectively prevent and treat duck enteritis virus (DEV) infection. This study aims to further clarify the mechanism by which rubiadin prevents DEV infection.\u003c/p\u003e\n\u003cp\u003e(Method)Duck embryo fibroblast (DEF) cells were pretreated with alizarin before being infected with DEV. Cell samples were collected at different time points for metabolomics sequencing, and the proliferation of DEV was detected by qPCR simultaneously.\u003c/p\u003e\n\u003cp\u003e(Result）Compared with the virus infection group, the alizarin intervention group exhibited a significantly reduced DEV load in DEF cells (P \u0026lt; 0.05). Transcriptome sequencing results revealed that alizarin inhibited DEV proliferation in DEF cells by modulating metabolic pathways such as those of tryptophan and arginine, thereby altering metabolites including indole and glutamate.\u003c/p\u003e\n\u003cp\u003e(Conclusions）Alizarin effectively inhibits DEV proliferation in DEF cells and mitigates virus-induced cytopathic effects, thereby providing a theoretical foundation for the screening of targeted antiviral agents against DEV.\u003c/p\u003e","manuscriptTitle":"Metabolomic analysis o1f alizarin intervention on duck enteritis virus-infected duck fibroblast cells","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-12 16:52:16","doi":"10.21203/rs.3.rs-7112922/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1451c9ed-2084-4746-bc9e-b5ef20cd049a","owner":[],"postedDate":"August 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-19T18:38:32+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-12 16:52:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7112922","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7112922","identity":"rs-7112922","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}