Anti-atherosclerotic effects of naringenin and quercetin from Folium Artemisiae argyi by attenuating Interleukin-1 beta (IL-1B)/ matrix metalloproteinase 9 (MMP9): network pharmacology-based analysis and validation

Anti-atherosclerotic effects of naringenin and quercetin from Folium Artemisiae argyi by attenuating Interleukin-1 beta (IL-1B)/ matrix metalloproteinase 9 (MMP9): network pharmacology-based analysis and validation | 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 Anti-atherosclerotic effects of naringenin and quercetin from Folium Artemisiae argyi by attenuating Interleukin-1 beta (IL-1B)/ matrix metalloproteinase 9 (MMP9): network pharmacology-based analysis and validation Lei Zhang, Zhihui Yang, Xinyi Li, Yunqing Hua, Guanwei Fan, Feng He This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2383711/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Effective components and related target genes of Folium Artemisiae argyi were screened from Traditional Chinese Medicines for Systems Pharmacology Database and Analysis Platform. The therapeutic targets of atherosclerosis were searched in the MalaCards and OMIM databases. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed in WebGestalt online and verified according to ClueGo and Pedia apps in Cytoscape. Then, the protein-protein interaction network was analyzed using the STRING database and constructed using Cytoscape. Differential expression of target genes was identified in GSE9128 and GSE71226 by GEO2R. And then, molecular docking was performed using the Molecular Operating Environment. Finally, we validated the protein expression of Interleukin-6 (IL-6)/IL-1B /MMP9 by qRT-PCR and Western blot in Raw264.7 which was induced by LPS. A total of 232 potential target genes and 8 ingredients of Folium Artemisiae argyi were identified. Quercetin, naringenin, and ethyl linoleate are potential candidate bioactive agents in treating atherosclerosis. Vascular endothelial growth factor (VEGFA), MMP9 and IL-1Β could be potential target genes. KEGG analysis demonstrated that the fluid shear stress and atherosclerosis pathway play a crucial role in the anti-atherosclerosis effect of Folium Artemisiae argyi. Gene Expression Omnibus (GEO) validation demonstrated that VEGFA was downregulated, while MMP9 and IL-1B were upregulated in patients with atherosclerosis. Molecular docking suggested that only MMP9 had a good combination with quercetin. The cell experiment results suggested that naringenin and quercetin have strong anti-inflammation effects, and significantly inhibit the expression of MMP9. Practical Applications Artemisiae argyi is a traditional Chinese herbal medicine that has been widely used for its antibacterial and anti-inflammatory effects. This research demonstrated the bioactive ingredients, potential targets, and molecular mechanism of Folium Artemisiae argyi in treating atherosclerosis. It also suggests a reliable approach in investigating the therapeutic effect of traditional Chinese herbal medicine in treating Atherosclerotic cardiovascular disease (ASCVD). Folium Artemisiae argyi atherosclerotic cardiovascular disease network pharmacology anti-inflammation quercetin naringenin Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Background ASCVD is a kind of disease arising from the obstruction of coronary vessels due to atherosclerosis or thrombosis. Cardiovascular diseases (CVDs) were the leading cause of death in non-communicable diseases according to the World Health Organization over the past decades [ 1 ] . CVD and stroke have become the two greatest causes of burden of disease in high-income countries. The risk factors of CVD vary and include sex, smoking, alcohol intake, and deficiencies in social relationships [ 2 ] . The causes of utmost concern in the general population are dyslipidemia and inflammation. Thus, statins and other drugs are widely used to reduce lipid levels and inflammation in hypercholesterolemia and other CVDs [ 3 ] . Although the effect is obvious, the side effects in some patients are also unavoidable [ 4 ] . The use of Traditional Chinese Medicine combination might be a potential supplementary treatment. Artemisiae argyi is a Chinese herbal medicine containing many bioactive compounds, such as flavonoids, glycosides, sterols, and essential oils [ 5 ] . It has been widely used for the treatment of infections, cancers, and other inflammatory diseases [ 6 ] . Inflammation is also a major cause of CVDs [ 7 ] . Therefore, we explored the possible treatment of ASCVD using Artemisia argyi according to a pharmacology-based network analysis method [ 8 ] . The traditional medicine pharmacology network prediction analysis is a method involving the pharmacogenomics and therapeutic mechanism of traditional Chinese medicinal herbs and/or formulae and the potential target genes and/or drugs [ 9 ] . The comprehensive investigation of the relationships among drugs, target genes, and diseases are possible because of the rapid development of bioinformatics and pharmacology [ 10 ] . Methods Compounding ingredients of Folium Artemisiae argyi Compounds from Folium Artemisiae argyi were determined using the public databases Traditional Chinese Medicines for Systems Pharmacology Database and Analysis Platform (TCMSP, https://tcmspw.com/tcmsp.php) [11] and Integrative Pharmacology-based Research Platform of Traditional Chinese Medicine (TCMIP, http://www.tcmip.cn/TCMIP) [12] . Pharmacokinetic absorption, distribution, metabolism, and excretion ( ADME) screen The ADME criteria of Folium Artemisiae argyi were extracted from the TCMSP database. Drug-likeness (DL) and oral bioavailability (OB) were selected to identify the bioactive ingredients of Folium Artemisiae argyi. OB is the percentage of an oral dose capable of producing pharmacological activity [13] . DL is an indicator for determining the similarity or likeness of a compound that can help in determining whether a compound has a therapeutic effect or not [14] . Targets of Compounds searching Information on the compounded ingredient target genes was obtained from the TCMSP database, and the Drug Bank (https://go.drugbank.com/) database was also used for determining the comprehensive drug targets of all ingredients. The related target genes of atherosclerosis were searched from the Mala Cards (https://www.malacards.org/) and OMIM (https://omim.org/) databases. The target genes of compounds were collected according to the Similarity ensemble approach (SEA) online database (http://sea.bkslab.org/). Protein-protein interaction (PPI) network The overlapping genes of AS and the compounds were selected as the hub genes and analyzed using the database STRING (https://string-db.org), which could provide the PPI network results. The Cytoscape (https://cytoscape.org/) software is widely applied to pharmacology studies in network construct and visualization. KEGG analysis and enrichment KEGG database was established by the Kanehisa Laboratory in 1995 and is typically used in pathway analysis and annotation in network pharmacology. We used WebGestalt [15] (WEB-based Gene Set Analysis Toolkit, http://www.webgestalt.org/) for KEGG pathway analysis, which is a functional enrichment analysis web tool. Then, the interactions between genes and pathways were validated by ClueGo and Pedia apps in Cytoscape. GEO Validation Candidate target genes were identified in the GEO database (GSE9128, GSE71226). GEO2R was used to identify the differentially expressed genes (DEGs), p £ 0.05, and ½log FC½ > 1 were the screening limitations. Molecular Docking Molecular docking is a crucial technology of network pharmacology analysis in proteins and small compounds. It is performed using the Molecular Operating Environment (MOE, v2019.0102) software to validate interactions between compounds and target proteins. The 3D structure of target proteins were obtained from the Protein Data Bank (PDB, http://www.rcsb.org) and imported into MOE to perform molecular docking after protein structure preparation. The structure of participant compounds was obtained from PubChem (https://pubchem.ncbi.nlm.nih.gov). Cell culture and treatment Raw264.7 was provided by Tianjin University of Traditional Chinese Medicine, and cultured by Dulbecco's modified Eagle medium (DMEM) containing 10% fetal bovine serum and 1% penicillin/streptomycin in an incubator (5% CO2, 37 o C). The cells were stimulated with lipopolysaccharide (LPS) (10 mg/ml) in the presence or absence of quercetin (10, 20, 50 mM), naringenin (10, 20, 50 mM) Real-Time Quantitative Reverse Transcription PCR and Western blot analysis The total RNA of Raw264.7 was isolated using an RNA extraction kit (Vazyme Biotech Co., Ltd), according to the manufacturer's instructions. The concentration of extracted RNA was detected using NanoDrop (Thermo), and complementary DNA (cDNA) was synthesized according to the manufacturer's instructions of RNA reverse transcription kit (Thermo). The messenger RNA (mRNA) expression levels of Interleukin-6 (IL-6), Interleukin-1 beta (IL-1B), matrix metallopeptidase 9 (MMP9) were analyzed using quantitative real-time polymerase chain reaction (qRT-PCR) on the LightCycler 96 (Roche) with SYBR Green (Thermo). Relative expression was calculated as 2 - △△ Ct using glyceraldehyde 3-phosphate dehydrogenase (GAPDH) as a reference gene. Primers were purchased from Sangon Biotech (Shanghai, China), sequences were listed in Table 4. Protein expression of IL-6/ IL-1β/ MMP9 were determined by Western blot. Rabbit anti-IL-6 (21865-1-AP) Polyclonal antibody was purchased from Proteintech; Mouse anti- IL-1 β (SC-52012), MMP-9 (SC-393859) monoclonal antibody were purchased from Santa Cruz Biotechnology, Inc. (Santa Cruz, CA); Mouse anti-β-actin monoclonal antibody were purchased from Cell Signaling Technology, Inc. (Danvers, MA, USA). Quercetin and naringenin were purchased from Yuanye (Shanghai, China). Data analysis All data analysis were proceeding according online database (https://tcmspw.com/tcmsp.php, https://go.drugbank.com/, https://www.malacards.org/, https://omim.org/, http://sea.bkslab.org/, https://string-db.org, http://www.webgestalt.org/, https://www.ncbi.nlm.nih.gov/geo/geo2r/) and MOE software (v2019.0102). Statistical analysis was performed by GraphPad (PRISM 7.0.a), statistical significance was considered as p < 0.05, the differences among groups were analyzed with one-way ANVOA . Results Compounding ingredients of Folium Artemisiae argyi We input “Folium Artemisiae Argyi” as an “herb name” to search the ingredients of the compound. A total of 135 items were obtained, and only 9 ingredients were included after screening by OB ≥ 30% and DL ≥ 0.18 in this study (Table 1). The target genes of the nine ingredients were collected from the SEA (Similarity ensemble approach, http://sea.bkslab.org/) database, which is a database that can be searched for chemical formulas according to their ingredients. After selecting genes from humans and eliminating the duplicate genes, 8 ingredients and 232 genes were included. The network of compounds to target genes was constructed using Cytoscape (Figure 1) Atherosclerosis-related target genes We searched the Mala Cards database online using the keyword “atherosclerosis” and 81 target genes were selected. We searched the Online Mendelian Inheritance in Man (OMIM) database with the same keywords, and 269 genes were collected. The overlapping genes among “atherosclerosis-related genes” from Mala genes and OMIM database and the “compound ingredients target genes”; finally, eight hub genes were obtained (Figure 2). Network construction of protein-protein interaction (PPI) The eight hub genes were input into the online tool “STRING”, and the PPI network was constructed by the limitation: “minimum required interaction score, (confidence = 0.500); max number of interactors, (1st shell ≤ 20 interactors, 2nd shell ≤ 20 interactors)”; in total, 48 interactors were collected. KEGG pathway analysis of the 48 genes was performed using the online web tools WebGestalt. The top 20 pathways are listed in Table 2 and Figure 3. The results were validated using ClueGo + Pedia apps, and the “Fluid shear stress and atherosclerosis” pathway (Figure 4), including the three genes ( IL-1Β, MMP9, VEGFA ), were the target genes in the eight hub genes. GEO Validation Analysis of GSE71226 and GSE9128 expression data of atherosclerosis group revealed that VEGFA was downregulated, while MMP9 and IL-1Β were upregulated (Table 3, Supplementary Tables 1 and 2). Thus, the three genes might be the candidate therapeutic targets of Folium Artemisiae argyi in the clinical treatment of atherosclerosis. MOE docking Molecular docking was performed to validate the interaction of the target protein (IL-1Β, MMP9, and VEGFA) and the related participant compounds (MOL005735, MOL001494, MOL000098, and MOL001040). The IL-1Β and VEGFA docking results were not promising, and only MMP9 has a good docking result with MOL000098 (Figure 5). The molecular docking results predicted that quercetin from Folium Artemisiae argyi could be effective in atherosclerosis therapy by targeting MMP9. Quercetin and naringenin suppressed LPS-induced pro-inflammatory cytokines To investigate the effects of quercetin and naringenin on anti-inflammation, Raw264.7 were stimulated with LPS in the presence or absence of quercetin (10, 20, 50 mM) and naringenin (10, 20, 50 mM) for 24h. As shown in Figures 6 and 7, the mRNA and protein expression of IL-6 and IL-1B were significantly increased with the LPS treatment (P < 0.0001), which were inhibited by quercetin (10, 20, 50 mM) and naringenin (10, 20, 50 mM). These results provided evidence that quercetin and naringenin have a strong inhibitory effect on pro-inflammatory cytokines. MMP9 might be a therapeutic target of Folium Artemisiae argyi in ASCVD The mRNA and protein expression level of MMP9 had a significant increase after treatment with LPS in the Raw264.7, quercetin and naringenin could significantly decrease the mRNA and protein expression level of MMP9 (Figures 6 C, D and figure 7), suggesting that lowering the expression of MMP9 might be the therapeutic effect of quercetin and naringenin in the treatment of ASCVD . Discussion Multiple factors are associated with cardiovascular diseases [ 16 ] ; a high low-density lipoprotein cholesterol (LDL-C) concentration of plasma and inflammation are the major factors that cause atherosclerosis. Although statin treatment in lowering LDL-C has achieved a relatively optimistic result, its benefits are limited by adverse effects to the liver and others, and further effective drugs for treating ASCVD should be sought. In the present work, we constructed a network of bioactive compounds and the molecular targets of Folium Artemisiae argyi that overlapped the target genes between atherosclerosis and related ingredients of Folium Artemisiae argyi. Finally, eight hub genes were identified, and IL-1Β , VEGFA , and MMP9 genes in the fluid shear stress and atherosclerosis pathway are the most likely target genes in treating atherosclerosis. The results of the GEO database (GSE71226, GSE9128) validation revealed that IL-1Β and MMP9 expression was upregulated, and VEGFA was downregulated significantly compared with controls. The expression values of VEGFA from GSE9128 in the control group were higher compared to the Ischemic cardiomyopathy (ICM) group, coincident with early research that increased the expression of VEGFA might be a potential therapeutic method for ICM [ 17 ] . MMP9 involved in the matrix-metalloproteinases family has been implicated in regulating matrikines. Given their ability to alter cellular migration and mitogenesis, matrikines have been implicated in inflammation, wound repair, and atherosclerosis [ 18 ] . MMP9 plays a role in inflammation and is upregulated in a lipopolysaccharide (LPS) model of corneal inflammation [ 19 ] . And the molecular docking results also suggested that MMP9 has better interactivity with quercetin, the experiment results in Raw264.7 were also providing evidence that quercetin and naringenin could decrease the expression of MMP9 and suppressed the expression of pro-inflammation cytokines IL-6 and IL-1Β. In our study, the LPS induced inflammation in Raw264.7 also elevated the mRNA and protein expression level of MMP9, as while treated with quercetin (10, 20, 50 µM) and naringenin (10, 20, 50 µM) could significantly decrease its expression (Figs. 6 C, D and Fig. 7 ). And these results suggested quercetin might have the effect of steady atherosclerotic plaque stability by inhibiting MMP9 expression. IL-1Β is a member of the IL-1 family cytokines; it is an immunomodulatory signaling molecule and thus acts as a central mediator [ 20 ] . The Canakinumab Anti-Inflammatory Thrombosis Outcome Study trial also provided proof for the inflammation hypothesis of atherosclerosis [ 21 ] , and IL-1Β inhibition highlighted the potential of anti-inflammatory therapies to improve the clinical outcomes of CVDs. The results of our research also presented the suppression of quercetin and naringenin to pro-inflammation cytokines in IL-1Β and IL6 (Figs. 6 A, B and Fig. 7 ). The MMP9 and IL-1Β-related major ingredients of Folium Artemisiae argyi were quercetin and naringenin. Quercetin, one of the ingredients of Folium Artemisiae argyi, has shown a wide range of biological actions in anti-inflammatory and antiviral activities in vitro and in some animal models [ 22 ] . The ability of inflammation to promote atherosclerosis has been elucidated in molecular and cellular pathways by numerous experimental works [ 23 ] . Quercetin is a kind of flavonoid, and a prominent dietary antioxidant present in fruits, vegetables, and herbal medicines, it plays a role in attenuating atherosclerosis by alleviating inflammation and improving NO bioavailability [ 24 ] . Naringenin is also one of the natural flavanones in Folium Artemisiae argyi, and animal models have demonstrated its therapeutic potentials in treating inflammation-related diseases, such as atherosclerosis [ 25 ] . Naringenin suppresses inflammatory cytokine production during transcription and post-transcription; it not only inhibits cytokine mRNA expression but also promotes lysosome-dependent cytokine protein degradation [ 26 ] . Thus, the anti-atherosclerotic activity of naringenin is due to its high anti-inflammatory effects [ 27 ] . Ethyl linoleate is an unsaturated fatty acid used in many fields for its antibacterial and anti-inflammatory effects [ 28 ] . It is also widely used in preventing and treating atherosclerosis. Inflammation is an important driver of atherosclerosis, and cellular inflammatory changes actively contribute to atherosclerosis progression [ 29 , 30 ] . The therapeutic effect of the inflammatory pathway targets helped improve the outcomes of patients with cardiovascular diseases. The anti-inflammatory effects of the ingredients from Folium Artemisiae argyi were obvious. Consequently, Folium Artemisiae argyi has potential beneficial effects in atherosclerosis therapy through its anti-inflammatory activities. However, our research has limitations in investigating the mechanism of Folium Artemisiae argyi used in treating atherosclerosis. And its application to clinical medicine in the future should be determined through extensive experiments in vivo and in vitro. Conclusions In the present study, we performed network pharmacology-based prediction, molecular docking, and GEO database validation to verify the potential targets of Folium Artemisiae argyi through related bioactive ingredients in treating atherosclerosis. And the validation in the LPS-induced inflammation model of Raw264.7 also offered evidence that quercetin and naringenin have the anti-inflammation effect and suppressed the expression of MMP9. We demonstrated that the anti-inflammatory and keeping the atherosclerotic plaque stable ability of Folium Artemisiae argyi may be the main direction in atherosclerosis therapy in the future, which also provided a practicable application for the analysis of traditional Chinese medicine in the clinical treatment of diseases. Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. The data that support the findings of this study are openly available in [“figshare "] at 10.6084/m9.figshare.21916380. Competing interests The authors declare that they have no competing interests. Funding This research was supported by the Scientific Research Program (B2021234) from Hubei Provincial Department of Education; and Scientific Research Foundation for Advanced Talents (2042021040) from Huanggang Normal University and comprehensive utilization of characteristic biological resources in the Dabie Mountains. Authors' Contributions Lei Zhang and Feng He designed the manuscript. Lei Zhang completed the data download and analysis and wrote the manuscript. Zhihui Yang and Xinyi Li conduct the cell culture and western blot experiments; Yunqing Hua finished the qRT-PCR works. Guanwei Fan designed the experiments and offered advices. All the authors approved the final manuscript. Acknowledgements Not applicable. References Zhu, K.-F., Wang Y.-M., Zhu J.-Z., et al., National prevalence of coronary heart disease and its relationship with human development index: A systematic review. European journal of preventive cardiology, 2016. 23(5): p. 530-543. Valtorta, N.K., Kanaan M., Gilbody S., et al., Loneliness and social isolation as risk factors for coronary heart disease and stroke: systematic review and meta-analysis of longitudinal observational studies. Heart (British Cardiac Society), 2016. 102(13): p. 1009-1016. Wang, C.-Y., Liu P.-Y. and Liao J.K., Pleiotropic effects of statin therapy: molecular mechanisms and clinical results. Trends in Molecular Medicine, 2008. 14(1): p. 37-44. Schmitz, G. and Langmann T., Pharmacogenomics of cholesterol-lowering therapy. Vascular Pharmacology, 2006. 44(2): p. 75-89. 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Tables Table 1 Compounding ingredients of Folium Artemisiae argyi (TCMSP) Mol ID Molecule Name OB (%) DL MOL002883 ethyl oleate (NF) 32.4 0.19 MOL000358 beta-sitosterol 36.91 0.75 MOL005741 cycloartenol acetate 41.11 0.8 MOL005720 24-methylenecyloartanone 41.11 0.79 MOL001494 mandenol 42 0.19 MOL001040 (2R)-5,7-dihydroxy-2-(4-hydroxyphenyl)chroman-4-one 42.36 0.21 MOL000449 stigmasterol 43.83 0.76 MOL005735 dammaradienyl acetate 44.83 0.83 MOL000098 quercetin 46.43 0.28 Table 2 KEGG pathway analysis in WebGestalt (Top 20) GeneSet Description P Value FDR hsa04010 MAPK signaling pathway 2.37E-12 7.73E-10 hsa05133 Pertussis 3.07E-10 5.01E-08 hsa05200 Pathways in cancer 1.51E-09 1.64E-07 hsa05152 Tuberculosis 3.25E-09 2.65E-07 hsa05140 Leishmaniasis 6.93E-09 4.52E-07 hsa05418 Fluid shear stress and atherosclerosis 6.81E-08 3.57E-06 hsa04066 HIF-1 signaling pathway 7.67E-08 3.57E-06 hsa05145 Toxoplasmosis 2.00E-07 8.14E-06 hsa05162 Measles 6.63E-07 2.40E-05 hsa04064 NF-kappa B signaling pathway 9.56E-07 3.12E-05 hsa05215 Prostate cancer 1.10E-06 3.26E-05 hsa05142 Chagas disease (American trypanosomiasis) 1.55E-06 4.21E-05 hsa04919 Thyroid hormone signaling pathway 3.69E-06 9.25E-05 hsa04380 Osteoclast differentiation 7.11E-06 1.65E-04 hsa05202 Transcriptional misregulation in cancer 8.75E-06 1.90E-04 hsa04933 AGE-RAGE signaling pathway in diabetic complications 1.91E-05 3.89E-04 hsa04151 PI3K-Akt signaling pathway 2.38E-05 4.56E-04 hsa04620 Toll-like receptor signaling pathway 2.53E-05 4.58E-04 hsa04659 Th17 cell differentiation 2.98E-05 5.11E-04 hsa05211 Renal cell carcinoma 4.26E-05 6.94E-04 Table 3 GEO validation using GEO2R Expression Gene symbol Gene title P Value log FC upregulated genes IL-1Β interleukin 1 beta 0.00933762 1.20182753 MMP9 matrix metallopeptidase 9 0.0187166 2.267172 downregulated gene VEGFA vascular endothelial growth factor A 0.0011307 -1.6941442 Table 4 Primers of RT-PCR Gene name Sequence MMP9-F CTGGACAGCCAGACACTAAAG MMP9-R CTCGCGGCAAGTCTTCAGAG IL-1Β-F GAAATGCCACCTTTTGACAGTG IL-1Β-R TGGATGCTCTCATCAGGACAG IL-6 -F CTGCAAGAGACTTCCATCCAG IL-6 -R AGTGGTATAGACAGGTCTGTTGG GAPDH- F TGACCTCAACTACATGGTCTACA GAPDH-R CTTCCCATTCTCGGCCTTG Additional Declarations No competing interests reported. Supplementary Files figure7Aoriginalblot.zip figure7Boriginalblot.zip originaldataofGSE9128fromTCGAdatabasesupplementarytable1.xlsx originaldataofGSE71226fromTCGAdatabasesupplementarytable2.xlsx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 06 Mar, 2023 Reviews received at journal 14 Feb, 2023 Reviewers agreed at journal 14 Feb, 2023 Reviewers agreed at journal 06 Feb, 2023 Reviewers agreed at journal 06 Feb, 2023 Reviewers invited by journal 03 Feb, 2023 Editor assigned by journal 03 Feb, 2023 Editor invited by journal 19 Jan, 2023 Submission checks completed at journal 19 Jan, 2023 First submitted to journal 15 Dec, 2022 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. 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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-2383711","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":169188622,"identity":"6e15f957-1a55-422a-b986-55f6b1c90854","order_by":0,"name":"Lei Zhang","email":"","orcid":"","institution":"Huanggang Normal University","correspondingAuthor":false,"prefix":"","firstName":"Lei","middleName":"","lastName":"Zhang","suffix":""},{"id":169188624,"identity":"713c132f-16a1-434e-aa1f-eee9cf942aa6","order_by":1,"name":"Zhihui Yang","email":"","orcid":"","institution":"First Teaching Hospital of Tianjin University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Zhihui","middleName":"","lastName":"Yang","suffix":""},{"id":169188625,"identity":"3282b9b0-ed08-44d3-8c79-db3e0dd54e8b","order_by":2,"name":"Xinyi Li","email":"","orcid":"","institution":"Huanggang Normal University","correspondingAuthor":false,"prefix":"","firstName":"Xinyi","middleName":"","lastName":"Li","suffix":""},{"id":169188627,"identity":"8911e8a6-0582-40b5-8849-f6bc4cf3a451","order_by":3,"name":"Yunqing Hua","email":"","orcid":"","institution":"First Teaching Hospital of Tianjin University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yunqing","middleName":"","lastName":"Hua","suffix":""},{"id":169188629,"identity":"1434d9fe-c223-4764-9231-9d1a3ebd7792","order_by":4,"name":"Guanwei Fan","email":"","orcid":"","institution":"First Teaching Hospital of Tianjin University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Guanwei","middleName":"","lastName":"Fan","suffix":""},{"id":169188631,"identity":"7eb5dcf1-a479-4b07-a364-914fc5989289","order_by":5,"name":"Feng He","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzklEQVRIiWNgGAWjYBACA+YDQLLiAITHQ5QWtgQgeQaohY0kLYxtpGgxZ2M+9vDrvDuJ8+c3MD5428Ygb05Ii2UbW7qx7LZniRuOMTAbzm1jMNzZQMhh93vMpCW3HU7cwMbAJs3bxpBgcICQlmP836Ql5xxOnN/GwP6bSC08bJIfGw4nNhxjYGMmUgubmTTDscPGG44lNkvOOSdhuIGwFuZnkj9qDsvObz588MObMht5graAADMkOhgbgIQEEepBan8Qp24UjIJRMApGKgAAHQ5Bc8R8lfMAAAAASUVORK5CYII=","orcid":"","institution":"Huanggang Normal University","correspondingAuthor":true,"prefix":"","firstName":"Feng","middleName":"","lastName":"He","suffix":""}],"badges":[],"createdAt":"2022-12-16 02:59:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2383711/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2383711/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":31949828,"identity":"31e5c24b-3947-4945-b129-afef0ac15397","added_by":"auto","created_at":"2023-01-23 15:13:12","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":880263,"visible":true,"origin":"","legend":"\u003cp\u003eNetwork of compounds for targeting genes. Red circle: Folium Artemisiae argyi; Purple hexagon: ingredients of Folium Artemisiae argyi after screening by OB ≥30% and DL ≥0.18; green diamonds: target genes (human) of the ingredients; blue diamonds: eight hub genes overlapped among “atherosclerosis-related genes” from the Malagenes and OMIM databases and “compounding ingredients target genes.”\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-2383711/v1/4d909676cd9742b7c1e0ef9b.png"},{"id":31949826,"identity":"4f0e9ff2-1586-4654-8240-faf78507e8b0","added_by":"auto","created_at":"2023-01-23 15:13:12","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":122503,"visible":true,"origin":"","legend":"\u003cp\u003eTarget genes overlapping; gray circle: “atherosclerosis-related genes” from the Mala genes database; orange circle: “atherosclerosis-related genes” from the OMIM database; and blue circle: “ compounding ingredients target genes” from the SEA database\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-2383711/v1/d063491234ca3f83f25e8606.png"},{"id":31949827,"identity":"4ed1d0e5-6d6e-4582-92ae-60a79f396e50","added_by":"auto","created_at":"2023-01-23 15:13:12","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":101115,"visible":true,"origin":"","legend":"\u003cp\u003eTop 20 pathways analyzed in WebGestalt. arranged by the enrichment raito from high to low.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-2383711/v1/cd2415c7c2f277b10e6e0e07.png"},{"id":31949832,"identity":"6289c6ed-320a-4fb0-92d8-b218f37fa858","added_by":"auto","created_at":"2023-01-23 15:13:12","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":233588,"visible":true,"origin":"","legend":"\u003cp\u003e\"Fluid shear stress and atherosclerosis\" pathway and related genes. in the center of the circle were the genes related \"Fluid shear stress and atherosclerosis\" (linked with red lines)\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-2383711/v1/0c0e3a7e7260a26197f49ae1.png"},{"id":31949829,"identity":"cb6d6294-0115-40e9-bc35-78ac912c5ebb","added_by":"auto","created_at":"2023-01-23 15:13:12","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":92626,"visible":true,"origin":"","legend":"\u003cp\u003eMMP9 interacted action mode with quercetin. green structure represdent quercetin in the Figure A, and other parts was the structure of MMP9; in the central part of Figure B was the chemical structure of quercetin, other small circle with different colors were the proteins might be have interaction with it.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-2383711/v1/bec95dd376c240c3c7e5889d.png"},{"id":31949836,"identity":"d1533523-61ea-4368-91f4-57b8c4e96bfa","added_by":"auto","created_at":"2023-01-23 15:13:13","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":311487,"visible":true,"origin":"","legend":"\u003cp\u003eanti-inflammation effect of quercetin and naringenin, MMP9 might be the potential target. LPS: lipopolysaccharide. * P\u0026lt;0.05,** P\u0026lt;0.01,*** P\u0026lt;0.001，**** P\u0026lt;0.0001.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-2383711/v1/debb6a1957dc23267a11046f.png"},{"id":31949830,"identity":"d5c65091-76ff-4950-b3b7-65c1ef4a64fa","added_by":"auto","created_at":"2023-01-23 15:13:12","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":416282,"visible":true,"origin":"","legend":"\u003cp\u003eExpression of IL6, IL-1βand MMP9 in macrophage (RAW264.7) in each groups treated with quercetin (A) and naringenin (B), determined by western blot. * P\u0026lt;0.05,** P\u0026lt;0.01,*** P\u0026lt;0.001，**** P\u0026lt;0.0001. (Original blot were included in the “Supplementary material file”）\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-2383711/v1/5ec08f6199865c41980202d3.png"},{"id":31953481,"identity":"7d5af8c7-0a72-4176-9b43-b8f85c8bca87","added_by":"auto","created_at":"2023-01-23 15:29:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2358495,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2383711/v1/5af36ffc-ae0f-432d-a793-9dcaad6844e4.pdf"},{"id":31951966,"identity":"0fad649c-2256-4154-97e3-3f05c279e77b","added_by":"auto","created_at":"2023-01-23 15:21:12","extension":"zip","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":98528,"visible":true,"origin":"","legend":"","description":"","filename":"figure7Aoriginalblot.zip","url":"https://assets-eu.researchsquare.com/files/rs-2383711/v1/b3998d546e1cd148135e351b.zip"},{"id":31951965,"identity":"6284b966-9f79-4516-b75c-7eaa19cb2d09","added_by":"auto","created_at":"2023-01-23 15:21:12","extension":"zip","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":97471,"visible":true,"origin":"","legend":"","description":"","filename":"figure7Boriginalblot.zip","url":"https://assets-eu.researchsquare.com/files/rs-2383711/v1/7bdeeed841b57e0dad44a9ee.zip"},{"id":31953409,"identity":"db9f4f11-c7d1-405a-9653-f98bfd0d6bc5","added_by":"auto","created_at":"2023-01-23 15:29:12","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":25231,"visible":true,"origin":"","legend":"","description":"","filename":"originaldataofGSE9128fromTCGAdatabasesupplementarytable1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-2383711/v1/5fd19aa86a7f9516e7d93b5c.xlsx"},{"id":31953408,"identity":"b68ee87f-0115-4b3a-8d67-2ceb1a8ff722","added_by":"auto","created_at":"2023-01-23 15:29:12","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":184074,"visible":true,"origin":"","legend":"","description":"","filename":"originaldataofGSE71226fromTCGAdatabasesupplementarytable2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-2383711/v1/1408480c527e813e7301c317.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Anti-atherosclerotic effects of naringenin and quercetin from Folium Artemisiae argyi by attenuating Interleukin-1 beta (IL-1B)/ matrix metalloproteinase 9 (MMP9): network pharmacology-based analysis and validation","fulltext":[{"header":"Background","content":"\u003cp\u003eASCVD is a kind of disease arising from the obstruction of coronary vessels due to atherosclerosis or thrombosis. Cardiovascular diseases (CVDs) were the leading cause of death in non-communicable diseases according to the World Health Organization over the past decades\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. CVD and stroke have become the two greatest causes of burden of disease in high-income countries. The risk factors of CVD vary and include sex, smoking, alcohol intake, and deficiencies in social relationships\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. The causes of utmost concern in the general population are dyslipidemia and inflammation. Thus, statins and other drugs are widely used to reduce lipid levels and inflammation in hypercholesterolemia and other CVDs\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. Although the effect is obvious, the side effects in some patients are also unavoidable\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. The use of Traditional Chinese Medicine combination might be a potential supplementary treatment.\u003c/p\u003e \u003cp\u003eArtemisiae argyi is a Chinese herbal medicine containing many bioactive compounds, such as flavonoids, glycosides, sterols, and essential oils\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. It has been widely used for the treatment of infections, cancers, and other inflammatory diseases\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Inflammation is also a major cause of CVDs\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Therefore, we explored the possible treatment of ASCVD using Artemisia argyi according to a pharmacology-based network analysis method\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe traditional medicine pharmacology network prediction analysis is a method involving the pharmacogenomics and therapeutic mechanism of traditional Chinese medicinal herbs and/or formulae and the potential target genes and/or drugs\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. The comprehensive investigation of the relationships among drugs, target genes, and diseases are possible because of the rapid development of bioinformatics and pharmacology\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eCompounding ingredients of Folium Artemisiae argyi\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCompounds from Folium Artemisiae argyi were determined using the public databases Traditional Chinese Medicines for Systems Pharmacology Database and Analysis Platform (TCMSP, https://tcmspw.com/tcmsp.php)\u003csup\u003e[11]\u003c/sup\u003e and Integrative Pharmacology-based Research Platform of Traditional Chinese Medicine (TCMIP, http://www.tcmip.cn/TCMIP)\u003csup\u003e[12]\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePharmacokinetic absorption, distribution, metabolism, and excretion\u003c/strong\u003e (\u003cstrong\u003eADME) screen\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe ADME criteria of Folium Artemisiae argyi were extracted from the TCMSP database. Drug-likeness (DL) and oral bioavailability (OB) were selected to identify the bioactive ingredients of Folium Artemisiae argyi. OB is the percentage of an oral dose capable of producing pharmacological activity\u003csup\u003e[13]\u003c/sup\u003e. DL is an indicator for determining the similarity or likeness of a compound that can help in determining whether a compound has a therapeutic effect or not\u003csup\u003e[14]\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTargets of Compounds searching\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformation on the compounded ingredient target genes was obtained from the TCMSP database, and the Drug Bank (https://go.drugbank.com/) database was also used for determining the comprehensive drug targets of all ingredients. The related target genes of atherosclerosis were searched from the Mala Cards (https://www.malacards.org/) and OMIM (https://omim.org/) databases. The target genes of compounds were collected according to the Similarity ensemble approach (SEA) online database (http://sea.bkslab.org/).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProtein-protein interaction (PPI) network\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe overlapping genes of AS and the compounds were selected as the hub genes and analyzed using the database STRING (https://string-db.org), which could provide the PPI network results. The Cytoscape (https://cytoscape.org/) software is widely applied to pharmacology studies in network construct and visualization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKEGG analysis and enrichment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKEGG database was established by the Kanehisa Laboratory in 1995 and is typically used in pathway analysis and annotation in network pharmacology. We used WebGestalt\u003csup\u003e[15]\u003c/sup\u003e (WEB-based Gene Set Analysis Toolkit, http://www.webgestalt.org/) for KEGG pathway analysis, which is a functional enrichment analysis web tool. Then, the interactions between genes and pathways were validated by ClueGo and Pedia apps in Cytoscape.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGEO Validation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCandidate target genes were identified in the GEO database (GSE9128, GSE71226). GEO2R was used to identify the differentially expressed genes (DEGs), p\u0026nbsp;\u0026pound;\u0026nbsp;0.05, and\u0026nbsp;\u0026frac12;log FC\u0026frac12;\u0026nbsp;\u0026gt;\u0026nbsp;1 were the screening limitations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMolecular Docking\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMolecular docking is a crucial technology of network pharmacology analysis in proteins and small compounds. It is performed using the Molecular Operating Environment (MOE, v2019.0102) software to validate interactions between compounds and target proteins. The 3D structure of target proteins were obtained from the Protein Data Bank (PDB, http://www.rcsb.org) and imported into MOE to perform molecular docking after protein structure preparation. The structure of participant compounds was obtained from PubChem (https://pubchem.ncbi.nlm.nih.gov).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell culture and treatment\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRaw264.7 was provided by Tianjin University of Traditional Chinese Medicine, and cultured by Dulbecco\u0026apos;s modified Eagle medium (DMEM) containing 10% fetal bovine serum and 1% penicillin/streptomycin in an incubator (5% CO2, 37\u003csup\u003eo\u003c/sup\u003eC). The cells were stimulated with lipopolysaccharide (LPS) (10\u0026nbsp;mg/ml) in the presence or absence of quercetin (10, 20, 50\u0026nbsp;mM), naringenin (10, 20, 50\u0026nbsp;mM)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReal-Time Quantitative Reverse Transcription PCR and Western blot analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe total RNA of Raw264.7 was isolated using an RNA extraction kit (Vazyme Biotech Co., Ltd), according to the manufacturer\u0026apos;s instructions. The concentration of extracted RNA was detected using NanoDrop (Thermo), and complementary DNA (cDNA) was synthesized according to the manufacturer\u0026apos;s instructions of RNA reverse transcription kit (Thermo). The messenger RNA (mRNA) expression levels of Interleukin-6 (IL-6), Interleukin-1 beta (IL-1B), matrix metallopeptidase 9 (MMP9) were analyzed using quantitative real-time polymerase chain reaction (qRT-PCR) on the LightCycler 96 (Roche) with SYBR Green (Thermo). Relative expression was calculated as 2\u003csup\u003e-\u003c/sup\u003e\u003csup\u003e△△\u003c/sup\u003e\u003csup\u003eCt\u003c/sup\u003e using glyceraldehyde 3-phosphate dehydrogenase (GAPDH) as a reference gene. Primers were purchased from Sangon Biotech (Shanghai, China), sequences were listed in Table 4. Protein expression of IL-6/ IL-1\u0026beta;/ MMP9 were determined by Western blot. Rabbit anti-IL-6 (21865-1-AP) Polyclonal antibody was purchased from Proteintech; Mouse anti- IL-1\u0026nbsp;\u0026beta;\u0026nbsp;(SC-52012), MMP-9 (SC-393859) monoclonal antibody were purchased from Santa Cruz Biotechnology, Inc. (Santa Cruz, CA); Mouse anti-\u0026beta;-actin monoclonal antibody were purchased from Cell Signaling Technology, Inc. (Danvers, MA, USA). Quercetin and naringenin were purchased from Yuanye (Shanghai, China).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data analysis were proceeding according online database (https://tcmspw.com/tcmsp.php, https://go.drugbank.com/, https://www.malacards.org/, https://omim.org/, http://sea.bkslab.org/, https://string-db.org, http://www.webgestalt.org/, https://www.ncbi.nlm.nih.gov/geo/geo2r/) and MOE software (v2019.0102). Statistical analysis was performed by GraphPad (PRISM 7.0.a), statistical significance was considered as p \u0026lt; 0.05, the differences among groups were analyzed with one-way ANVOA .\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eCompounding ingredients of Folium Artemisiae argyi\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe input \u0026ldquo;Folium Artemisiae Argyi\u0026rdquo; as an \u0026ldquo;herb name\u0026rdquo; to search the ingredients of the compound. A total of 135 items were obtained, and only 9 ingredients were included after screening by OB \u0026ge; 30% and DL \u0026ge; 0.18 in this study (Table 1). The target genes of the nine ingredients were collected from the SEA (Similarity ensemble approach, http://sea.bkslab.org/) database, which is a database that can be searched for chemical formulas according to their ingredients. After selecting genes from humans and eliminating the duplicate genes, 8 ingredients and 232 genes were included. The network of compounds to target genes was constructed using Cytoscape (Figure 1)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAtherosclerosis-related target genes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe searched the Mala Cards database online using the keyword \u0026ldquo;atherosclerosis\u0026rdquo; and 81 target genes were selected. We searched the Online Mendelian Inheritance in Man (OMIM) database with the same keywords, and 269 genes were collected. The overlapping genes among \u0026ldquo;atherosclerosis-related genes\u0026rdquo; from Mala genes and OMIM database and the \u0026ldquo;compound ingredients target genes\u0026rdquo;; finally, eight hub genes were obtained (Figure 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNetwork construction of protein-protein interaction (PPI)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe eight hub genes were input into the online tool \u0026ldquo;STRING\u0026rdquo;, and the PPI network was constructed by the limitation: \u0026ldquo;minimum required interaction score, (confidence = 0.500); max number of interactors, (1st shell \u0026le; 20 interactors, 2nd shell \u0026le; 20 interactors)\u0026rdquo;; in total, 48 interactors were collected. KEGG pathway analysis of the 48 genes was performed using the online web tools WebGestalt. The top 20 pathways are listed in Table 2 and Figure 3. The results were validated using ClueGo + Pedia apps, and the \u0026ldquo;Fluid shear stress and atherosclerosis\u0026rdquo; pathway (Figure 4), including the three genes (\u003cem\u003eIL-1\u0026Beta;, MMP9, VEGFA\u003c/em\u003e), were the target genes in the eight hub genes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGEO Validation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnalysis of GSE71226 and GSE9128 expression data of atherosclerosis group revealed that \u003cem\u003eVEGFA\u003c/em\u003e was downregulated, while \u003cem\u003eMMP9\u003c/em\u003e and \u003cem\u003eIL-1\u0026Beta;\u003c/em\u003e were upregulated (Table 3, Supplementary Tables 1 and 2). Thus, the three genes might be the candidate therapeutic targets of Folium Artemisiae argyi in the clinical treatment of atherosclerosis.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMOE docking\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMolecular docking was performed to validate the interaction of the target protein (IL-1\u0026Beta;, MMP9, and VEGFA) and the related participant compounds (MOL005735, MOL001494, MOL000098, and MOL001040). The IL-1\u0026Beta; and VEGFA docking results were not promising, and only MMP9 has a good docking result with MOL000098 (Figure 5). The molecular docking results predicted that quercetin from Folium Artemisiae argyi could be effective in atherosclerosis therapy by targeting MMP9.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuercetin and naringenin\u0026nbsp;suppressed LPS-induced pro-inflammatory cytokines\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo investigate the effects of quercetin and naringenin on anti-inflammation, Raw264.7 were stimulated with LPS in the presence or absence of quercetin (10, 20, 50\u0026nbsp;mM) and naringenin (10, 20, 50\u0026nbsp;mM) for 24h. As shown in Figures 6 and 7, the mRNA and protein expression of IL-6 and IL-1B were significantly increased with the LPS treatment (P \u0026lt; 0.0001), which were inhibited by quercetin (10, 20, 50\u0026nbsp;mM) and naringenin (10, 20, 50\u0026nbsp;mM). These results provided evidence that quercetin and naringenin have a strong inhibitory effect on pro-inflammatory cytokines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMMP9 might be a therapeutic target of Folium Artemisiae argyi in ASCVD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe mRNA and protein expression level of MMP9 had a significant increase after treatment with LPS in the Raw264.7, quercetin and naringenin could significantly decrease the mRNA and protein expression level of MMP9 (Figures 6 C, D and figure 7), suggesting that lowering the expression of MMP9 might be the therapeutic effect of quercetin and naringenin in the treatment of ASCVD .\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eMultiple factors are associated with cardiovascular diseases\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e; a high low-density lipoprotein cholesterol (LDL-C) concentration of plasma and inflammation are the major factors that cause atherosclerosis. Although statin treatment in lowering LDL-C has achieved a relatively optimistic result, its benefits are limited by adverse effects to the liver and others, and further effective drugs for treating ASCVD should be sought.\u003c/p\u003e \u003cp\u003eIn the present work, we constructed a network of bioactive compounds and the molecular targets of Folium Artemisiae argyi that overlapped the target genes between atherosclerosis and related ingredients of Folium Artemisiae argyi. Finally, eight hub genes were identified, and \u003cem\u003eIL-1Β\u003c/em\u003e, \u003cem\u003eVEGFA\u003c/em\u003e, and \u003cem\u003eMMP9\u003c/em\u003e genes in the fluid shear stress and atherosclerosis pathway are the most likely target genes in treating atherosclerosis. The results of the GEO database (GSE71226, GSE9128) validation revealed that IL-1Β and MMP9 expression was upregulated, and VEGFA was downregulated significantly compared with controls. The expression values of VEGFA from GSE9128 in the control group were higher compared to the Ischemic cardiomyopathy (ICM) group, coincident with early research that increased the expression of VEGFA might be a potential therapeutic method for ICM\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMMP9 involved in the matrix-metalloproteinases family has been implicated in regulating matrikines. Given their ability to alter cellular migration and mitogenesis, matrikines have been implicated in inflammation, wound repair, and atherosclerosis\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. MMP9 plays a role in inflammation and is upregulated in a lipopolysaccharide (LPS) model of corneal inflammation\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. And the molecular docking results also suggested that MMP9 has better interactivity with quercetin, the experiment results in Raw264.7 were also providing evidence that quercetin and naringenin could decrease the expression of MMP9 and suppressed the expression of pro-inflammation cytokines IL-6 and IL-1Β.\u003c/p\u003e \u003cp\u003eIn our study, the LPS induced inflammation in Raw264.7 also elevated the mRNA and protein expression level of MMP9, as while treated with quercetin (10, 20, 50 \u0026micro;M) and naringenin (10, 20, 50 \u0026micro;M) could significantly decrease its expression (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC, D and Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). And these results suggested quercetin might have the effect of steady atherosclerotic plaque stability by inhibiting MMP9 expression.\u003c/p\u003e \u003cp\u003eIL-1Β is a member of the IL-1 family cytokines; it is an immunomodulatory signaling molecule and thus acts as a central mediator\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. The Canakinumab Anti-Inflammatory Thrombosis Outcome Study trial also provided proof for the inflammation hypothesis of atherosclerosis\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e, and IL-1Β inhibition highlighted the potential of anti-inflammatory therapies to improve the clinical outcomes of CVDs. The results of our research also presented the suppression of quercetin and naringenin to pro-inflammation cytokines in IL-1Β and IL6 (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA, B and Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe MMP9 and IL-1Β-related major ingredients of Folium Artemisiae argyi were quercetin and naringenin. Quercetin, one of the ingredients of Folium Artemisiae argyi, has shown a wide range of biological actions in anti-inflammatory and antiviral activities in vitro and in some animal models\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. The ability of inflammation to promote atherosclerosis has been elucidated in molecular and cellular pathways by numerous experimental works\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. Quercetin is a kind of flavonoid, and a prominent dietary antioxidant present in fruits, vegetables, and herbal medicines, it plays a role in attenuating atherosclerosis by alleviating inflammation and improving NO bioavailability\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eNaringenin is also one of the natural flavanones in Folium Artemisiae argyi, and animal models have demonstrated its therapeutic potentials in treating inflammation-related diseases, such as atherosclerosis\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. Naringenin suppresses inflammatory cytokine production during transcription and post-transcription; it not only inhibits cytokine mRNA expression but also promotes lysosome-dependent cytokine protein degradation\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. Thus, the anti-atherosclerotic activity of naringenin is due to its high anti-inflammatory effects\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eEthyl linoleate is an unsaturated fatty acid used in many fields for its antibacterial and anti-inflammatory effects\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. It is also widely used in preventing and treating atherosclerosis.\u003c/p\u003e \u003cp\u003eInflammation is an important driver of atherosclerosis, and cellular inflammatory changes actively contribute to atherosclerosis progression\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e. The therapeutic effect of the inflammatory pathway targets helped improve the outcomes of patients with cardiovascular diseases. The anti-inflammatory effects of the ingredients from Folium Artemisiae argyi were obvious. Consequently, Folium Artemisiae argyi has potential beneficial effects in atherosclerosis therapy through its anti-inflammatory activities. However, our research has limitations in investigating the mechanism of Folium Artemisiae argyi used in treating atherosclerosis. And its application to clinical medicine in the future should be determined through extensive experiments in vivo and in vitro.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn the present study, we performed network pharmacology-based prediction, molecular docking, and GEO database validation to verify the potential targets of Folium Artemisiae argyi through related bioactive ingredients in treating atherosclerosis. And the validation in the LPS-induced inflammation model of Raw264.7 also offered evidence that quercetin and naringenin have the anti-inflammation effect and suppressed the expression of MMP9. We demonstrated that the anti-inflammatory and keeping the atherosclerotic plaque stable ability of Folium Artemisiae argyi may be the main direction in atherosclerosis therapy in the future, which also provided a practicable application for the analysis of traditional Chinese medicine in the clinical treatment of diseases.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. The data that support the findings of this study are openly available in [\u0026ldquo;figshare \u0026quot;] at 10.6084/m9.figshare.21916380.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the Scientific Research Program (B2021234) from Hubei Provincial Department of Education; and Scientific Research Foundation for Advanced Talents (2042021040) from Huanggang Normal University and comprehensive utilization of characteristic biological resources in the Dabie Mountains.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLei Zhang and Feng He designed the manuscript. Lei Zhang completed the data download and analysis and wrote the manuscript. Zhihui Yang and Xinyi Li conduct the cell culture and western blot experiments; Yunqing Hua finished the qRT-PCR works.\u0026nbsp;Guanwei Fan\u0026nbsp;designed the experiments and offered advices. All the authors approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eZhu, K.-F., Wang Y.-M., Zhu J.-Z., et al., National prevalence of coronary heart disease and its relationship with human development index: A systematic review. European journal of preventive cardiology, 2016. 23(5): p. 530-543.\u003c/li\u003e\n\u003cli\u003eValtorta, N.K., Kanaan M., Gilbody S., et al., Loneliness and social isolation as risk factors for coronary heart disease and stroke: systematic review and meta-analysis of longitudinal observational studies. Heart (British Cardiac Society), 2016. 102(13): p. 1009-1016.\u003c/li\u003e\n\u003cli\u003eWang, C.-Y., Liu P.-Y. and Liao J.K., Pleiotropic effects of statin therapy: molecular mechanisms and clinical results. Trends in Molecular Medicine, 2008. 14(1): p. 37-44.\u003c/li\u003e\n\u003cli\u003eSchmitz, G. and Langmann T., Pharmacogenomics of cholesterol-lowering therapy. Vascular Pharmacology, 2006. 44(2): p. 75-89.\u003c/li\u003e\n\u003cli\u003eZhang, L.B., Lv J.L., Chen H.L., et al., Chemical constituents from Artemisia argyi and their chemotaxonomic significance. Biochemical Systematics and Ecology, 2013. 50(10): p. 455-458.\u003c/li\u003e\n\u003cli\u003eAdams, M., Efferth T. and Bauer R., Activity-Guided Isolation of Scopoletin and Isoscopoletin, the Inhibitory Active Principles towards CCRF-CEM Leukaemia Cells and Multi-Drug Resistant CEM/ADR5000 Cells, from Artemisia argyi. 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W77-83.\u003c/li\u003e\n\u003cli\u003eYusuf, S., Hawken S., Ounpuu S., et al., Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet, 2004. 364(9438): p. 937-52.\u003c/li\u003e\n\u003cli\u003eHaniff, H.S., Knerr L., Liu X., et al., Design of a small molecule that stimulates vascular endothelial growth factor A enabled by screening RNA fold-small molecule interactions. Nat Chem, 2020. 12(10): p. 952-961.\u003c/li\u003e\n\u003cli\u003eVassiliadis, E., Barascuk N., Didangelos A., et al., Novel cardiac-specific biomarkers and the cardiovascular continuum. Biomark Insights, 2012. 7: p. 45-57.\u003c/li\u003e\n\u003cli\u003eLin, M., Jackson P., Tester A.M., et al., Matrix metalloproteinase-8 facilitates neutrophil migration through the corneal stromal matrix by collagen degradation and production of the chemotactic peptide Pro-Gly-Pro. 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Clin Sci (Lond), 2018. 132(12): p. 1243-1252.\u003c/li\u003e\n\u003cli\u003eLoke, W.M., Proudfoot J.M., Hodgson J.M., et al., Specific dietary polyphenols attenuate atherosclerosis in apolipoprotein E-knockout mice by alleviating inflammation and endothelial dysfunction. Arterioscler Thromb Vasc Biol, 2010. 30(4): p. 749-57.\u003c/li\u003e\n\u003cli\u003eMulvihill, E.E., Assini J.M., Sutherland B.G., et al., Naringenin decreases progression of atherosclerosis by improving dyslipidemia in high-fat-fed low-density lipoprotein receptor-null mice. Arterioscler Thromb Vasc Biol, 2010. 30(4): p. 742-8.\u003c/li\u003e\n\u003cli\u003eZeng, W., Jin L., Zhang F., et al., Naringenin as a potential immunomodulator in therapeutics. Pharmacol Res, 2018. 135: p. 122-126.\u003c/li\u003e\n\u003cli\u003eOrhan, I.E., Nabavi S.F., Daglia M., et al., Naringenin and atherosclerosis: a review of literature. Curr Pharm Biotechnol, 2015. 16(3): p. 245-51.\u003c/li\u003e\n\u003cli\u003eJelenko, C., Wheeler M.L., Anderson A.P., et al., Studies in burns: XIV, Heling in burn wounds treated with Ethyl Linoleate alone or in combination with selected topical antibacterial agents. Annals of surgery, 1975. 182(5): p. 562-566.\u003c/li\u003e\n\u003cli\u003eMayerl, C., Lukasser M., Sedivy R., et al., Atherosclerosis research from past to present\u0026mdash;on the track of two pathologists with opposing views, Carl von Rokitansky and Rudolf Virchow. Virchows Archiv, 2006. 449(1): p. 96-103.\u003c/li\u003e\n\u003cli\u003eGrebe, A., Hoss F. and Latz E., NLRP3 Inflammasome and the IL-1 Pathway in Atherosclerosis. Circ Res, 2018. 122(12): p. 1722-1740.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCompounding ingredients of Folium Artemisiae argyi\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(TCMSP)\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"652\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003eMol ID\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"62.26993865030675%\"\u003e\n \u003cp\u003eMolecule Name\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.122699386503067%\"\u003e\n \u003cp\u003eOB (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003eDL\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003eMOL002883\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"62.26993865030675%\"\u003e\n \u003cp\u003eethyl oleate (NF)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.122699386503067%\"\u003e\n \u003cp\u003e32.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003eMOL000358\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"62.26993865030675%\"\u003e\n \u003cp\u003ebeta-sitosterol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.122699386503067%\"\u003e\n \u003cp\u003e36.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003eMOL005741\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"62.26993865030675%\"\u003e\n \u003cp\u003ecycloartenol acetate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.122699386503067%\"\u003e\n \u003cp\u003e41.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003eMOL005720\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"62.26993865030675%\"\u003e\n \u003cp\u003e24-methylenecyloartanone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.122699386503067%\"\u003e\n \u003cp\u003e41.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003eMOL001494\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"62.26993865030675%\"\u003e\n \u003cp\u003emandenol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.122699386503067%\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003eMOL001040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"62.26993865030675%\"\u003e\n \u003cp\u003e(2R)-5,7-dihydroxy-2-(4-hydroxyphenyl)chroman-4-one\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.122699386503067%\"\u003e\n \u003cp\u003e42.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003eMOL000449\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"62.26993865030675%\"\u003e\n \u003cp\u003estigmasterol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.122699386503067%\"\u003e\n \u003cp\u003e43.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003eMOL005735\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"62.26993865030675%\"\u003e\n \u003cp\u003edammaradienyl acetate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.122699386503067%\"\u003e\n \u003cp\u003e44.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"15.950920245398773%\"\u003e\n \u003cp\u003eMOL000098\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"62.26993865030675%\"\u003e\n \u003cp\u003equercetin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.122699386503067%\"\u003e\n \u003cp\u003e46.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2 KEGG pathway analysis in WebGestalt (Top 20)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"633\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003eGeneSet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.03785488958991%\"\u003e\n \u003cp\u003eDescription\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003eP Value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003eFDR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003ehsa04010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.03785488958991%\"\u003e\n \u003cp\u003eMAPK signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e2.37E-12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e7.73E-10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003ehsa05133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.03785488958991%\"\u003e\n \u003cp\u003ePertussis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e3.07E-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e5.01E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003ehsa05200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.03785488958991%\"\u003e\n \u003cp\u003ePathways in cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e1.51E-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e1.64E-07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003ehsa05152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.03785488958991%\"\u003e\n \u003cp\u003eTuberculosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e3.25E-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e2.65E-07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003ehsa05140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.03785488958991%\"\u003e\n \u003cp\u003eLeishmaniasis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e6.93E-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e4.52E-07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003ehsa05418\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.03785488958991%\"\u003e\n \u003cp\u003eFluid shear stress and atherosclerosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e6.81E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e3.57E-06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003ehsa04066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.03785488958991%\"\u003e\n \u003cp\u003eHIF-1 signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e7.67E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e3.57E-06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003ehsa05145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.03785488958991%\"\u003e\n \u003cp\u003eToxoplasmosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e2.00E-07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e8.14E-06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003ehsa05162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.03785488958991%\"\u003e\n \u003cp\u003eMeasles\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e6.63E-07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e2.40E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003ehsa04064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.03785488958991%\"\u003e\n \u003cp\u003eNF-kappa B signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e9.56E-07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e3.12E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003ehsa05215\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.03785488958991%\"\u003e\n \u003cp\u003eProstate cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e1.10E-06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e3.26E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003ehsa05142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.03785488958991%\"\u003e\n \u003cp\u003eChagas disease (American trypanosomiasis)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e1.55E-06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e4.21E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003ehsa04919\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.03785488958991%\"\u003e\n \u003cp\u003eThyroid hormone signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e3.69E-06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e9.25E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003ehsa04380\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.03785488958991%\"\u003e\n \u003cp\u003eOsteoclast differentiation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e7.11E-06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e1.65E-04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003ehsa05202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.03785488958991%\"\u003e\n \u003cp\u003eTranscriptional misregulation in cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e8.75E-06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e1.90E-04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003ehsa04933\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.03785488958991%\"\u003e\n \u003cp\u003eAGE-RAGE signaling pathway in diabetic complications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e1.91E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e3.89E-04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003ehsa04151\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.03785488958991%\"\u003e\n \u003cp\u003ePI3K-Akt signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e2.38E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e4.56E-04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003ehsa04620\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.03785488958991%\"\u003e\n \u003cp\u003eToll-like receptor signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e2.53E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e4.58E-04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003ehsa04659\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.03785488958991%\"\u003e\n \u003cp\u003eTh17 cell differentiation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e2.98E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e5.11E-04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003ehsa05211\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.03785488958991%\"\u003e\n \u003cp\u003eRenal cell carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e4.26E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.987381703470032%\"\u003e\n \u003cp\u003e6.94E-04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3 GEO validation using GEO2R\u003c/strong\u003e\u003c/p\u003e\n\u003ctable align=\"left\" border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"671\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.029850746268657%\"\u003e\n \u003cp\u003eExpression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.776119402985074%\"\u003e\n \u003cp\u003eGene symbol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"32.38805970149254%\"\u003e\n \u003cp\u003eGene title\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.432835820895523%\"\u003e\n \u003cp\u003eP Value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.373134328358208%\"\u003e\n \u003cp\u003elog FC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"24.029850746268657%\"\u003e\n \u003cp\u003eupregulated genes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.776119402985074%\"\u003e\n \u003cp\u003eIL-1\u0026Beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"32.38805970149254%\"\u003e\n \u003cp\u003einterleukin 1 beta\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.432835820895523%\"\u003e\n \u003cp\u003e0.00933762\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.373134328358208%\"\u003e\n \u003cp\u003e1.20182753\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"19.44990176817289%\"\u003e\n \u003cp\u003eMMP9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"42.63261296660118%\"\u003e\n \u003cp\u003ematrix metallopeptidase 9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.68172888015717%\"\u003e\n \u003cp\u003e0.0187166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.23575638506876%\"\u003e\n \u003cp\u003e2.267172\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.029850746268657%\"\u003e\n \u003cp\u003edownregulated gene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.776119402985074%\"\u003e\n \u003cp\u003eVEGFA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"32.38805970149254%\"\u003e\n \u003cp\u003evascular endothelial growth factor A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.432835820895523%\"\u003e\n \u003cp\u003e0.0011307\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.373134328358208%\"\u003e\n \u003cp\u003e-1.6941442\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\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4 Primers of RT-PCR\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eGene name\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eSequence\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eMMP9-F \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eCTGGACAGCCAGACACTAAAG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eMMP9-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eCTCGCGGCAAGTCTTCAGAG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eIL-1\u0026Beta;-F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eGAAATGCCACCTTTTGACAGTG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eIL-1\u0026Beta;-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eTGGATGCTCTCATCAGGACAG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eIL-6 -F\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eCTGCAAGAGACTTCCATCCAG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eIL-6 -R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eAGTGGTATAGACAGGTCTGTTGG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eGAPDH- F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eTGACCTCAACTACATGGTCTACA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eGAPDH-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"50%\"\u003e\n \u003cp\u003eCTTCCCATTCTCGGCCTTG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-complementary-medicine-and-therapies","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcam","sideBox":"Learn more about [BMC Complementary Medicine and Therapies](https://bmccomplementmedtherapies.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Complementary Medicine and Therapies","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Folium Artemisiae argyi, atherosclerotic cardiovascular disease, network pharmacology, anti-inflammation, quercetin, naringenin","lastPublishedDoi":"10.21203/rs.3.rs-2383711/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2383711/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEffective components and related target genes of Folium Artemisiae argyi were screened from Traditional Chinese Medicines for Systems Pharmacology Database and Analysis Platform. The therapeutic targets of atherosclerosis were searched in the MalaCards and OMIM databases. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed in WebGestalt online and verified according to ClueGo and Pedia apps in Cytoscape. Then, the protein-protein interaction network was analyzed using the STRING database and constructed using Cytoscape. Differential expression of target genes was identified in GSE9128 and GSE71226 by GEO2R. And then, molecular docking was performed using the Molecular Operating Environment. Finally, we validated the protein expression of Interleukin-6 (IL-6)/IL-1B /MMP9 by qRT-PCR and Western blot in Raw264.7 which was induced by LPS.\u003c/p\u003e\n\u003cp\u003eA total of 232 potential target genes and 8 ingredients of Folium Artemisiae argyi were identified. Quercetin, naringenin, and ethyl linoleate are potential candidate bioactive agents in treating atherosclerosis. Vascular endothelial growth factor (VEGFA), MMP9 and IL-1Β could be potential target genes. KEGG analysis demonstrated that the fluid shear stress and atherosclerosis pathway play a crucial role in the anti-atherosclerosis effect of Folium Artemisiae argyi. Gene Expression Omnibus (GEO) validation demonstrated that VEGFA was downregulated, while MMP9 and IL-1B were upregulated in patients with atherosclerosis. Molecular docking suggested that only MMP9 had a good combination with quercetin. The cell experiment results suggested that naringenin and quercetin have strong anti-inflammation effects, and significantly inhibit the expression of MMP9.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePractical Applications\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eArtemisiae argyi is a traditional Chinese herbal medicine that has been widely used for its antibacterial and anti-inflammatory effects. This research demonstrated the bioactive ingredients, potential targets, and molecular mechanism of Folium Artemisiae argyi in treating atherosclerosis. It also suggests a reliable approach in investigating the therapeutic effect of traditional Chinese herbal medicine in treating \u0026nbsp;Atherosclerotic cardiovascular disease (ASCVD).\u003c/p\u003e","manuscriptTitle":"Anti-atherosclerotic effects of naringenin and quercetin from Folium Artemisiae argyi by attenuating Interleukin-1 beta (IL-1B)/ matrix metalloproteinase 9 (MMP9): network pharmacology-based analysis and validation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-01-23 15:13:07","doi":"10.21203/rs.3.rs-2383711/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2023-03-06T07:13:35+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-02-15T01:26:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"8a06592b-7a13-49a4-ba84-1957c8874588","date":"2023-02-15T00:53:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"1f9f15c8-0546-423e-a346-31fc8771ebe3","date":"2023-02-07T02:15:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"fd364bc8-6537-454e-8f68-4c82f24e7439","date":"2023-02-06T16:21:25+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-02-03T16:08:03+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-02-03T15:28:45+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2023-01-19T16:57:14+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-01-19T16:53:49+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Complementary Medicine and Therapies","date":"2022-12-16T02:55:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-complementary-medicine-and-therapies","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcam","sideBox":"Learn more about [BMC Complementary Medicine and Therapies](https://bmccomplementmedtherapies.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Complementary Medicine and Therapies","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a7d806d4-c5a5-4663-8ed0-028387635344","owner":[],"postedDate":"January 23rd, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2023-10-16T16:14:28+00:00","versionOfRecord":[],"versionCreatedAt":"2023-01-23 15:13:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2383711","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2383711","identity":"rs-2383711","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}