Specificity of obtained targets with NAFLD was estimated and investigated in Tissue/Cells–gene associations  and Disease–gene association-based EnrichR algorithms . RESULTS: Two collections were constructed: 227 protein–curcumin interactions and 95 NAFLD-associated genes. By Venn diagram, 14 significant targets were identified, and their biological pathways evaluated. Based on gene ontology, most targets involved stress and lipid metabolism. KEGG revealed chemical carcinogenesis, the AGE-RAGE signaling pathway in diabetic complications and NAFLD as the most common significant pathways. Specificity to diseases database  revealed specificity for steatosis/steatohepatitis. CONCLUSION: Curcumin may improve, or inhibit, progression of NAFLD through activation/inhibition of NAFLD-related genes. BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is a prevalent metabolic disorder. Defects in function/expression of genes/proteins are critical in initiation/progression of NAFLD. Natural products may modulate these genes/proteins. Curcumin improves steatosis, inflammation, and fibrosis progression. Here, bioinformatic tools, gene–drug and gene-disease databases were utilized to explore targets, interactions, and pathways through which curcumin could impact NAFLD. METHODS: Significant curcumin–protein interaction was identified (high-confidence:0.7) in the STITCH database. Identified proteins were investigated to determine association with NAFLD. gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were analyzed for significantly involved targets ( In recent decades, non-alcoholic fatty liver disease (NAFLD) has attracted interest from researchers as a highly prevalent metabolic disorder. Metabolic dysfunction can be initiated when there is only 5% fat accumulation in the liver. Furthermore, while an increasing proportion of the population has been diagnosed with NAFLD, scientific studies suggest that many individuals are unaware of the presence of the disease, which complicates the therapy . NAFLD cCurcuma longa Linn, which is endowed with diverse pharmacological activities [Curcumin is a bioactive polyphenolic compound, isolated from tivities ,20,21,22tivities ,29,30,31Emerging from these studies, therefore, are data supporting the significant clinical effect of curcumin on NAFLD. Although extensive data exist on the benefits of curcumin in NAFLD, studies on the mechanism of action of curcumin and its interaction with various genes have not been evaluated in detail.Systems biology and bioinformatics, a branch of biology that combines molecular biology and computer science, have been an integral part of research investigations in recent decades. This science focuses on the entire biological process and system as compared to past years where there was a tendency to investigate only a single protein or gene .In this bioinformatics study, we aimed to identify important gene targets for NAFLD and high probability protein targets of interaction for curcumin. Moreover, we have tried to correlate these targets with NAFLD using published literature on curcumin. Using the bioinformatics approach explores critical genes associated with curcumin and NAFLD in the online databases, then investigates their relations as targets of curcumin for NAFLD.http://stitch.embl.de/ (accessed on 3 October 2021)) to explore essential protein targets. STITCH is a platform for diagnosing interactions between chemicals and proteins. This database currently contains more than 9,640,000 proteins from 2031 organisms [We first searched interactions of curcumin in the STITCH database ) and the DISEASES database (diseases.jensenlab.org (accessed on 3 October 2021)), to find their association with NAFLD. DisGeNET is a database that contains a collection of genes associated with specific diseases. These data are integrated from a variety of sources, such as expert-curated repositories, the scientific literature and GWAS catalogs. DisGeNET currently covers more than 1700 genes and 24,000 diseases and traits [Next, we investigated the proteins on curated targets in two databases, the DisGeNET database (d traits . For assd traits . We extrhttps://www.uniprot.org/uploadlists/ (accessed on 3 October 2021). For this purpose, we collected all genes and protein targets in different formats (gene symbols) and in the section “Retrieve/ID mapping” and converted to UniProtKB. We finally created a Venn diagram (http://bioinformatics.psb.ugent.be/webtools/Venn/ (accessed on 3 October 2021)) for these two sets of protein collections to find important targets of curcumin beyond the key recognized targets. A Venn diagram is a suitable method for identifying interesting overlaps between two or more sets.Before identification of common genes between two collections (curated genes-NAFLD and curcumin-STITCH), to eliminate the bias of different forms of gene names, all genes were first converted to UniProt by http://geneontology.org (accessed on 3 October 2021). Additionally, KEGG was analyzed using the Enrichr database with the web address: https://maayanlab.cloud/Enrichr/ (accessed on 3 October 2021). The KEGG pathway is a comprehensive database that maps pathways according to their metabolic inter-relationships [p-value < 0.01 was considered as the cut-off criterion. We also analyzed the enrichment pathways using the Wikipathway plugin in Cytoscape version 3.8.2. Cytoscape is a powerful software for integrating biomolecular interaction networks. It also has the practical capability to install multiple plugins to analyze high throughput data and different biological processes [p-value < 0.01 was considered as the cut-off criterion. In this plugin, we selected the Nonalcoholic fatty liver disease–Homo sapiens pathway and highlighted the curcumin protein interactions in this pathway based on their STITCH score. In addition, we estimated the specificity of obtained targets with NAFLD and investigated them in Tissue/Cells–gene associations (PanglaoDB Augmented 2021 and Mouse Gene Atlas) and the Disease–gene associations based EnrichR algorithm (Jensen DISEASES and DisGeNET). EnrichR is a free enrichment analysis website that possesses 180 184 annotated gene sets from 102 gene set libraries. It is a comprehensive online analyzer and engine searching machine to assemble biological knowledge [Gene ontology (GO) enrichment is a popular procedure used to interpret genes and stratify them into three major categories: those that contribute to molecular function (MF), biological process (BP) or cellular component (CC) . GO was ionships . In GO arocesses . A p-valnowledge . Panglaonowledge . Mouse Gnowledge .Screening curcumin in the STITCH database with high confidence (0.7) identified 227 protein targets. The Drug–Protein interaction was visualized on Cytoscape A. STITCHThe curated data DisGeNet plugin on Cytoscape and DISEASES database identified 95 genes associated with NAFLD. All the data were visualized with Cytoscape software A. In thiA Venn diagram of the two created datasets revealed 14 candidates, CYP1A2, NFE2L2, PPARA, GSTA1, IL1A, LEP, LDLR, CSF2, GSTP1, PRKCE, TGFB1, ABCC2, AHR, and PRKCD B, that mGO analysis of the 14 identified protein targets demonstrated major involvement in response to oxygen-containing compounds, cellular response to lipid and stress, and regulation of lipid metabolic process under biological process . This anp-value pathways included chemical carcinogenesis, the AGE-RAGE signaling pathway in diabetic complications, fluid shear stress and atherosclerosis, non-alcoholic fatty liver disease and cytokine–cytokine receptor interaction  . The scoMoreover, the specificity of 14 obtained targets with NAFLD was confirmed based on the EnrichR algorithm in two databases, including Jensen DISEASES and DisGeNET. The result showed that NAFLD, and its advanced form NASH, were ranked in the top three in these databases .Furthermore, we visualized all curcumin–protein targets with high confidence (0.7) in the NAFLD pathway in Wikipathway. The more intense color indicates greater interaction (based on the STITCH score) . The patAs a metabolic disorder, the importance of NAFLD has gained prominence in parallel with the accelerating prevalence of other metabolic syndromes . In addiIn the present study, we first searched significant predictions of protein interaction with high confidence for curcumin. Then, we probed protein interaction associated with fatty liver disease, determined its impact as an inhibitor, activator, binding, or transcription factor on these genes, and selected the most relevant targets. In doing so, we identified 14 significant targets: CYP1A2, NFE2L2, PPARA, GSTA1, IL1A, LEP, LDLR, CSF2, GSTP1, PRKCE, TGFB1, ABCC2, AHR, and PRKCD, and then evaluated their biological pathways. Most of the targets were involved in response to lipid and stress and lipid metabolism based on gene ontology. KEGG enrichment pathways showed chemical carcinogenesis, the AGE-RAGE signaling pathway in diabetic complications and NAFLD as the most common significant pathways. The targets we found among the authentic disease databases were more specific to fatty liver disease (steatosis and steatohepatitis) than other diseases in these databases. We also investigated the possible presence of these important protein targets in the liver. Those 14 protein targets that we identified were responsible for different stages of NAFLD, including steatosis, steatohepatitis, and fibrosis. We determined that curcumin could impact each of those stages through modulating essential protein targets.PPARA  is a ligand-activated transcription factor, richly expressed in the liver and modulates various genes implicated in the catabolism of fatty acids . ActivatN-terminal kinase) and the nuclear factor-kappa B (NF-κB) pathway in HFD diet mice.NFE2L2 (nuclear factor erythroid-derived 2-like 2) is a potent transcription factor in modulating xenobiotics and antioxidants in stress responses. However, oxidative stress causes the progression of NAFLD, and NFE2L2 could promote the reduction of reactive oxygen species (ROS) and amelioration of NAFLD . In NFE2Curcumin exerts its anti-diabetic, cardioprotective, hepatoprotective, neuroprotective, and antitumor effects via NFE2L2 signaling pathways . CurcumiIn our current study, curcumin demonstrated a robust interaction with NFE2L2 based upon the STITCH score, having the second-highest score after CYP1A2 (high confidence: 0.877), and its function was determined to be through activation of NFE2L2. Similarly, NFE2L2 had the highest score (0.4), together with leptin (LEP) and PPARA, in the gene-diseases association database , indicatLEP was shown to be important with regards to NAFLD in our study (gda score: 0.4). LEP is a polypeptide hormone that interacts with its receptor, lepRb . SeveralCurcumin reduces the expression and secretion of leptin ,73,74. ALow-density apolipoprotein receptor (LDLR) is a mediator for cholesterol uptake in cells and is crucial for the clearance of cholesterol by the liver . LDLR deCytochrome P450 isozyme 1A2 (CYP1A2) plays an important role in metabolizing drugs and carcinogens . ResearcIn our study, CYP1A2 was identified as one of the most important NAFLD genes inhibited by curcumin (STITCH score: 0.948). According to our dataset, this gene is specifically present in the liver (high confidence: 4.78). However, due to conflicting results in studies about the increase and decrease of CYP1A2 in NAFLD, curcumin administration may benefit or exacerbate the disease, an issue that requires further investigation.Several studies have shown that IL1α is increased in NASH/NAFLD patients ,94,95 anGlutathione s-transferases (GSTs) are catalyzing enzymes that catalase hydrophobic and electrophilic compounds through glutathione reduction. GSTA1 is a member of the alpha class of GSTs and is principally expressed in the liver . GSTA1 pGlutathione S transferase Pi 1 (GSTP1) is another GST enzyme that plays a vital role in antioxidant defense through detoxifying foreign substances and inactivating byproducts of oxidative stress ,108. ResTGF-β is a growth factor and cytokine with profibrotic properties and is the most abundant isoform in the liver. TGF-βis also a key inducer of reactive oxygen species (ROS) . A studyColony-stimulating factor 2 (CSF2) has a role in binding to extracellular proteoglycans and modulating biological function . CSF2 isPRKCE is a member of the protein kinase C family, and has a C2 conserved domain (non-Ca2+ binding) and C1A and C1B domains for binding diacylglycerol (DAG) . SeveralABCC2 is mainly expressed in significant physiological barriers such as the canalicular membrane in liver cells. It contains multiple binding sites and shows complex transport kinetics . ABCC2 vAryl hydrocarbon receptor (AHR) is a ligand-activated transcription factor with multifunctional activity and may benefit or adversely affect NAFLD . Activat2+ [2+ homeostasis [Protein kinase c delta (PRKCD) is a member of the lipid-activated PKC family, which can be activated with DAG but not Ca2+ . PRKCD h2+ . PRKCD m2+ . SERCA ieostasis . Triglyceostasis . Deletioeostasis ,147. Deleostasis . Variouseostasis ,149,150.In summary, we surveyed the important NAFLD genes and their potential in targeting curcumin, together with their biological pathways. In this study, we identified 14 genes in NAFLD that are likely to be the target of curcumin and observed that curcumin induces or inhibits them. According to our results, this activity of curcumin was in line with improving NAFLD based on literature. We believe that the ongoing clinical trials investigating the effect of curcumin on fatty liver could yield positive results in the future, enhancing the therapeutic status of curcumin in this metabolic disorder.


There are studies on the hypoxia adaptation in yak, but there are few studies on the regulation of ferroptosis by hypoxia. This study was the first time to explore ferroptosis-related genes about hypoxia in yak. In this study, the oviduct epithelial cells between yak and bovine are performed by integrative analysis for functions, regulating network and hub genes. The results showed 29 up-regulated ferroptosis genes and 67 down-regulated ferroptosis genes, and GO-KEGG analysis showed that up-regulated differentially expressed genes (DEGs) were significantly enriched in ribosome pathway and oxidative phosphorylation pathway. Down-regulated DEGs were significantly enriched in longevity regulating pathway-mammal pathway. Mitophagy-Animal Pathway was a significant enrichment pathway for the up-regulated differentially expressed ferroptosis genes (DE-FRGs). HIF-1 signaling pathway is a significant pathway for the down-regulated DE-FRGs. By constructing DE-FRGs protein-protein interaction (PPI) network, 10 hub DE-FRGs  were obtained. The bta-mir-21-5p, bta-mir-10a and bta-mir-17-5p related to STAT3 were predicted. The results of this study indicated the important genes and pathways of the hypoxia in yak, and it was the first time to study ferroptosis genes and pathways related to the hypoxia adaptation by bulk-seq in yak. This study provided sufficient transcriptome datas for hypoxia adaptation. Yaks are a hypoxia-tolerant species that live in a high-altitude environment , which cFerroptosis is a popular research topic, which is a new type of iron-dependent programmed cell death, which is different from apoptosis, cell necrosis and autophagy. Ferroptosis leads to smaller mitochondria, increased membrane density, decreased cristae, and no obvious morphological changes in nucleus. Hypoxia inhibits ferritinophagy, increases in mitochondrial ferritin, and protects from ferroptosis . HypoxiaAt present, we used Weighted Correlation Network Analysis (WGCNA) to identify hub genes of hypoxic adaptation on lung, muscle, and spleen , RNA-Seqhttps://ngdc.cncb.ac.cn/gsa/) with series Numbers CRA007411. We selected a dataset of isthmus epithelial cells and ampulla epithelial cells of the oviduct. The RNA expression data of bovine were downloaded from the GEO (http://www.ncbi.nlm.nih.gov/geo/) database with series numbers GSE124110 (http://www.zhounan.org/ferrdb/current/).Yak oviduct samples were collected from Xining city, Qinghai province, China, at an altitude of 3,800~4,500 m. We performed the sequencing analysis, storing dataset in the Genome Sequence Archive . These DE-FRGs were used for subsequent analysis.We compared the data sets of yak and bovine, selection criteria for adjusted-https://David.ncifcrf.gov/). GO contains molecular functions (MF), biological processes (BP), and cellular component (CC). KEGG database includes biological functions, diseases, chemicals and drugs. Adjusted P-value < 0.05 were defined as statistically significant.The above DEGs and DE-FRGs were extracted, and then they were used for GO  functional enrichment and KEGG  signal pathway enrichment analysis for reference genome Bos grunniens by DAVID online database (https://cn.string-db.org/). The obtained results were imported into Cytoscape software for visualization and a confidence score > 0.40 was set to screen PPI pairs and build a PPI network.To further explore differential protein-protein interactions, protein interaction networks were analyzed for DE-FRGs using online String 11.5 database , an online software, which can help people find miRNA-interactions in gene regulation networks. Using B. taurus (cow) as ID type, 10 hub genes were input to search for miRNA related to hub genes.In protein network regulation results, nodes represent proteins and lines represent interactions between proteins. The hub genes were screened and scored by Cytohubba 3.7.1 plug-in in Cytoscape software. NetworkAnalyst , changes in GO biological processes (BP) mainly included cellular process, metabolic process, biological regulation, regulation of biological process, response to stimulus, cellular component organization or biogenesis, localization, positive regulation of biological process, multicellular organismal process, negative regulation of biological process, signaling, developmental process, immune system process. Changes in cellular component (CC) mainly focus on cell, cell part, organelle, organelle part, protein-containing complex, membrane, membrane-enclosed lumen, membrane part, extracellular region. The molecular function (MF) includes binding, catalytic activity, structural molecule activity, molecular function regulator, transporter activity, transcription regulator activity, molecular transducer activity. In particular , changes in GO biological processes (BP) mainly included cellular process, biological regulation, metabolic process, regulation of biological process, response to stimulus, cellular component organization or biogenesis, localization, multicellular organismal process, positive regulation of biological process, signaling, developmental process, negative regulation of biological process. Changes in cellular component (CC) mainly focus on cell, cell part, organelle, organelle part, membrane, protein-containing complex, membrane part. In addition, in the molecular function (MF), the main changes are binding, catalytic activity, transcription regulator activity, transporter activity, molecular function regulator, membrane-enclosed lumen. KEGG pathway analysis was rich in longevity regulating pathway-mammal pathway, human papillomavirus infection, axon guidance, phospholipase D signaling pathway, Lysosome, viral carcinogenesis, thyroid hormone signaling pathway , 29 up-regulated DE-FRGs changes in GO biological processes (BP) mainly included cellular process, metabolic process, biological regulation, regulation of biological process, response to stimulus, negative regulation of biological process, positive regulation of biological process, cellular component organization or biogenesis, signaling, localization, developmental process, multicellular organismal process, multi-organism process. Changes in cellular component (CC) mainly focus on cell, cell part, organelle, organelle part, membrane, protein-containing complex, membrane-enclosed lumen, membrane part, In addition, In the molecular function (MF), binding, catalytic activity, molecular function regulator, transcription regulator activity. KEGG pathway analysis is rich in mitophagy-animal pathway, protein processing in endoplasmic reticulum pathway, prostate cancer pathway , 67 down-regulated DE-FRGs changes in GO biological processes (BP) mainly included cellular process, biological regulation, metabolic process, regulation of biological process, response to stimulus, localization, positive regulation of biological process, cellular component organization or biogenesis, negative regulation of biological process, signaling, multicellular organismal process, developmental process, immune system process, multi-organism process. Changes in cellular component (CC) mainly focus on cell, cell part, organelle, membrane, organelle part, protein-containing complex, membrane part, membrane-enclosed lumen. In the molecular function (MF), binding, catalytic activity, transcription regulator activity, transporter activity, In particular, KEGG pathway analysis is rich in central carbon metabolism in cancer pathway, HIF-1 signaling pathway, pathways in cancer, hepatitis B pathway, relaxin signaling pathway, Kaposi sarcoma-associated herpesvirus infection pathway (As shown in  pathway .https://cn.string-db.org/). We made the protein-protein interaction network  for the first 10 hub genes for relevant miRNA prediction. Then, bta-mir-21-5p, bta-mir-10a and bta-mir-17-5p associated with STAT3 , to store iron. The relationship between hypoxia and iron death has attracted the attention of scholars. There is no high-throughput study to explore the potential link between ferroptosis and hypoxia in yak, and the mechanism of ferroptosis in hypoxic adaptation. We obtained 96 DE-FRGs by intersecting the differential genes of hypoxia adaptation with FerrDb, including 29 up-regulated DE-FRGs and 67 down-regulated DE-FRGs. Then, the enrichment analysis of DE-FRGs with KEGG-GO showed that the up-regulated ferroptosis genes were mainly involved in Mitophagy-animal pathway, while the down-regulated ferroptosis genes were mainly involved in HIF-1 signaling pathway, which indicated that hypoxia might inhibit the oxygen metabolism pathway related to ferroptosis. Mitophagy-biological pathway is the enrichment pathway of DE-FRGs. In previous studies, hypoxia can activate the PINK1/Parkin-mediated mitophagy pathway , selecti2), but the synthesized HIF-1 protein degrades quickly in cells, and HIF-1 can be stably expressed only under hypoxia. The HIF target MAFF promotes tumor invasion and metastasis through IL11 and STAT3 signaling , the data under accession CRA007411 are publicly available.The authors acknowledge that the transcriptome data stored in a database of GSA .The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Lonicer japonica Thunb.) against Newcastle disease.  Newcastle disease causes huge economic losses in the global poultry industry. An efficient treatment is needed to deal with the variable immunogenicity of the Newcastle disease virus (NDV). This study utilized network pharmacology to study the potential therapeutic targets of Honeysuckle  functions and Kyoto Encyclopedia of Genes and Genomics (KEGG) pathway enrichment analysis using the DAVID online tool were performed on these targets.  Twenty-five overlapping targets were identified. The PPI network construction results included 23 nodes of 25 genes and 95 edges. It was found that the IL-6 node had the largest degree. STAT1 and IRF1, CASP9, and CASP3 had the same as well as strongest interaction strengths. GO functions, such as “cytokine activity,” had a regulatory effect on NDV. The “Toll-like receptor signaling Pathway” “Nod-like receptor signaling pathway,” “RIG-I-like receptor signaling pathway,” and “Apoptosis,” which were obtained using KEGG analysis, also indicated that these pathways can act on NDV to enhance immune function.  In this study, the potential targets and mechanisms of action of Honeysuckle against Newcastle disease were explored through network pharmacology, which provided a theoretical basis for the treatment of Newcastle disease and provided new ideas for the development of traditional Chinese medicine for the poultry industry. Newcastle disease is one of the most dangerous diseases affecting the poultry industry worldwide. It is caused by the Newcastle disease virus (NDV), which can be rapidly transmitted through contact , 2. It cLonicer japonica Thunb.), a TCM, is mainly distributed in the Guangdong, Shandong, Henan, Hebei, and Hainan provinces, as well as Himalayas in China. It is rich in organic acids, flavonoids, volatile oils, and iridoid glycosides and has antiviral and anti-inflammatory effects [Traditional Chinese medicine (TCM) has played an important role in preventing and treating diseases in China for more than 2,000 years . Recentl effects –15. Howe effects .Network pharmacology is based on the analysis of the “drug-target-gene-disease” interaction network, which can reveal the effect mechanism of the synergistic effect of multimolecular drugs on the human body. The development of network pharmacology technology has provided great convenience for the study of the multicomponent, multipoint, and multichannel effect mechanism of Chinese medicine and Chinese medicine compounds in the treatment of diseases. Based on the technology of network pharmacology, this study systematically analyzes the potential therapeutic targets and molecular mechanisms of Honeysuckle in the treatment of Newcastle disease and provides a theoretical basis for the clinical application of Honeysuckle.https://tcmspw.com/tcmsp.php). Thereafter, relevant parameters such as oral bioavailability (OB) ≥ 30% and drug-likeness (DL) ≥ 0.18 were set for the active ingredients of Honeysuckle.The Chinese pinyin name “Jinyinhua” was the key word input in the “Herb Name” column in the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database (https://www.uniprot.org/) database to obtain the gene names of Honeysuckle. The “Reviewed” option was selected as a constraint on the method used in the UniProt database.To obtain the target names of Honeysuckle, the Mol ID of the active ingredients in Honeysuckle was entered into the target information as a screening condition. The target names were input in the UniProt (https://www.genecards.org) database for retrieval. Thereafter, these gene symbols were imported into the UniProt database to obtain the gene names of Newcastle disease. The filter criteria were the same as those used for the UniProt database in The gene symbols of Newcastle disease were obtained by entering the keyword “Newcastle disease” into the GeneCards (https://bioinfogp.cnb.csic.es/tools/venny/index.html) to identify potential targets for therapy.From the gene names of Honeysuckle and ND, the overlapping gene names were obtained using Venny online analysis  home page “Search.” The species constraint was “Gallus gallus.” In addition, we set the confidence of protein interaction >0.4 for predicting protein-protein interactions. Last, we inserted the resulting PPI network into Cytoscape 3.8.2 using MCODE analysis and cytoHubba plug-ins to verify the top 10 hub genes.First, we selected the “Multiple Proteins” option in the left column and then entered the overlapping targets obtained in 2.4 in the “List of Names” box in the right column, completed in the STRING database (https://david.ncifcrf.gov) online tool was used to perform the Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Thereafter, “Official Gene Symbol” was selected and “chicken” was set as the species selection. The GO terms were divided into three categories, namely, the biological process (BP), molecular functional (MF), and cellular component (CC), and were displayed using a bar chart. P value <0.05 and FDR <0.05 were used as the screening standards.The DAVID 6.8   . By furt gallus) . Among t gallus) . Among t gallus) .P value of “positive regulation of transcription from RNA polymerase II promoter” was the smallest  were screened according to the overlapping genes  related abnormal glucose metabolism, researchers showed that the apoptosis-related enzyme Caspase-3 was significantly increased with upregulation of IL-6 expression . MMP9 reα, and IFN-β increased after IRF7 is induced by stimulation of CEF cells, suggesting that IRF7 may be involved in the TLR signaling pathway [Through GO and KEGG analyses of 25 targets, these potential targets were allocated to different enrichment functions and pathways. There is an induced signal cascade that promotes apoptosis and cytokine secretion, and these signals cascade to promote NDV proliferation . It indi pathway .Based on network pharmacology, this study explored the pharmacokinetic mechanism of Honeysuckle against Newcastle disease and provided a theoretical basis for the preliminary test of Honeysuckle against Newcastle disease by retrieving various effective components of TCM, acquiring multiple targets, and exploring multiple pathways.


In this study, we used network pharmacology to explore the possible therapeutic mechanism underlying the treatment of diabetic nephropathy with Yishen capsules.The active chemical constituents of Yishen capsules were acquired using the Traditional Chinese Medicine Systems Pharmacology platform and the Encyclopedia of Traditional Chinese Medicine. Component target proteins were then searched and screened in the BATMAN database. Target proteins were cross-validated using the Comparative Toxicogenomics Database, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of the target proteins were performed. Then, protein–protein interaction (PPI) analysis was performed using the STRING database. Finally, a pharmacological network was constructed to show the component-target-pathway relationships. Molecular docking was used to analyse the interaction between drug components and target proteins.A. membranaceus, A. sinensis, E. ferox, A. orientale, and R. rosea) and their corresponding 12 key components  were screened. Furthermore, the 12 key components were related to 24 target protein nodes  and enriched in 24 pathway nodes . Molecular docking revealed that hydrogen bond was formed between drug components and target proteins.In total, 285 active chemical components were found, including 85 intersection targets against DN. In the pharmacological network, 5 key herbs (In conclusion, the active constituents of Yishen capsules modulate targets or signaling pathways in DN pathogenesis. Diabetic nephropathy (DN), a common and severe complication of diabetes mellitus (particularly type 2 diabetes mellitus), can eventually develop into end-stage renal disease . Type 2 A. membranaceus, A. sinensis, E. ferox, A. orientale, and R. rosea medicinal herbs. It has been reported that Yishen capsule could reduce proteinuria, protect renal function, and delay progression of early diabetic nephropathy [Traditional Chinese medicine has been used to treat DN for several years . Yishen hropathy , 13. Addhropathy , and Huahropathy . Gaoshanhropathy . HoweverNetwork pharmacology, an emerging discipline, integrates systems biology and pharmacology to facilitate drug innovation and development and clarify drug treatment mechanisms . In parthttp://lsp.nwu.edu.cn/browse.php?qc=herbs) was used to acquire data on the chemical components of the five Chinese medicinal herbs found in Yishen capsules, including molecule name, drug half-life, oral bioavailability, molecular mass, and drug likeness. Yishen capsules was composed of A. membranaceus, A. sinensis, E. ferox, A. orientale, and R. rosea in a ratio of 3:2:3:2:1 [http://www.tcmip.cn/ETCM/index.php/Home/Index/index.html) was used to retrieve small drug molecule information that could not be found in the TCMSP database.The Traditional Chinese Medicine Systems Pharmacology (TCMSP) database , and then used as the input items of the Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese medicine (BATMAN) (http://bionet.ncpsb.org/batman-tcm/). Default parameters were selected. The target protein gene of each component and the corresponding score were calculated, and the component-target protein relationship pair with score ≥ 5 was screened for further analysis.After the ADME parameters screening in the last step, the obtained effective components were first converted into PubChem CIDs through the PubChem database (http://ctdbase.org/) provides information on the associations between chemicals/genes and diseases to help develop disease mechanisms. The phrase “Diabetic, nephropathies” was used as a keyword based on inference scores to identify genes associated with DN in the CTD database. Then, targets scoring >50 were combined with the targets predicted in the previous step. Following logarithmic transformation, inference scores were acquired to assess the functional relationships among targets in the protein-protein interaction (PPI) network.The Comparative Toxicogenomics Database (CTD)  [p adjusted to ≤0.05 and counts ≥2 being considered significant enrichment results. The most significantly associated top 20 signaling pathways were shown using the bar graph.Using The Database for Annotation, Visualization and Integrated Discovery online bioinformatics resource  , KEGG pahttp://chianti.ucsd.edu/cytoscape-3.4.0/) was used to construct the PPI network. Further, the Metascape tool performed module mining on the PPI network based on the Molecular Complex Detection (MCODE) algorithm [http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html) in R package [p < 0.05 was considered the threshold. The most significantly associated top 10 signaling pathways were selected for bubble chart display.Using the Metascape online tool (https://metascape.org/gp/index.html#/main/step1), the PPI network of genes that were both target proteins of effective components and disease-related genes were explored. Then, the BioGrid , InWeb_Ilgorithm . Finally package . The BenTo further explore the molecular action of Yishen capsules in DN treatment, herbal medicine–component–target proteins–pathway networks were created in Cytoscape. Briefly, drug-effective components, effective components-target protein, and target protein-pathway relationship pairs were input into Cytoscape for network construction. In addition, the module genes identified by the molecular complex detection algorithm in the PPI analysis were selected used to construct a pharmacological network. Nodes of different colors represented the compounds, proteins, or pathways in the pharmacological networks, respectively, and compound–target or target–pathway relationships were presented as edges.http://www.rcsb.org/) [https://pubchem.ncbi.nlm.nih.gov/) in SDF format and converted to PDB format by pymol for subsequent molecular docking. Then, based on Lamarckian GA algorithm, Autodock software (Version 4.2.6) [Four of the target protein nodes in the pharmacological network  and the small drug molecules beta sitosterol and Stigmasterol targeting them were randomly selected for molecular docking analysis. Information on complexes of target proteins bound to other ligands was downloaded from the Protein Data Bank (PDB) database (sb.org/)  and usedn 4.2.6)  was usedA. membranaceus (87), E. ferox (26), R. rosea (6), A. sinensis (126), and A. orientale (46). Then, after screening the chemical components of the five medicines through a pre-set threshold, 38 of the original 285 chemical components were finally identified as important chemical components and were used for subsequent analysis. The relationship pairs included 13 components and 1283 target proteins. Then, these targets were compared with the results for the 214 genes associated with DN with inference scores of more than 50 in the CTD database. Finally, 85 intersected targets of the 1283 targets and 214 genes were obtained .VCAM1, TNF, PTGS2, BCL2, IL1B, NFKB1, IKBKB, CXCL12, CHUK), was among the top 20 pathways.In total, 102 pathways, including 33 signaling pathways, were identified upon pathway analysis. Moreover, the 20 most significant pathways, such as the hsa04151:PI3K−Akt (23 genes), hsa04152:AMPK (23 genes), hsa04066:HIF−1 (18 genes), hsa04068:FoxO (16 genes), and hsa04668:TNF (15 genes) signaling pathways, are illustrated in As shown in A. membranaceus, E. ferox, R. rosea, A. sinensis, and A. orientale), 13 chemical component nodes , 53 target protein nodes , and 20 pathway nodes   .A. membranaceus, E. ferox, R. rosea, A. sinensis, and A. orientale), 12 chemical component nodes , 24 target protein nodes , and 24 pathway nodes   .The results of molecular docking showed that, in beta sitosterol, hydrogen bond was formed between the ligand and ARG-407 of AKT2 and LYS-292 of NFKB1 . There wA. membranaceus, A. sinensis, E. ferox, A. orientale, and R. rosea) and 12 key components  were identified in Yishen capsules. These 12 key components were associated with 24 target protein nodes  and 24 pathways.Diabetic nephropathy increases morbidity and mortality in both type 1 and type 2 diabetes mellitus  and is tNetwork pharmacology analyses indicated that beta-sitosterol, beta-carotene, stigmasterol, alisol B, mairin, quercetin, caffeic acid, 1-monolinolein, kaempferol, jaranol, formononetin, and calycosin play key roles in the progression of DN. Clinical and experimental studies have reported β-sitosterol (24-ethyl cholestene-3-ol) as a naturally occurring plant sterol that possesses antihyperlipidemic and antihyperglycemic properties , 33. FurIn the pharmacological network, AGT, AKT1, AKT2, BCL2, SIRT1, and NFKB1 were important target protein nodes. The production of AGT is involved in DN progression . The T23SIRT 1 regulates the Bax and Bcl-2 apoptotic proteins in DN , and a NMoreover, in total, 20 pathway nodes were found to be associated with DN in the target network of cross-validation targets. The AMPK signaling pathway improves DN by reducing uric acid, serum albumin, creatinine, and kidney damage . The AMPIn conclusion, beta-sitosterol, stigmasterol, quercetin, caffeic acid, and kaempferol were identified as key components of Yishen capsules in the treatment of DN. AGT, AKT1, AKT2, and BCL2 may be important target proteins in the pharmacological network. Moreover, SIRT1 and NFKB1 may interact to regulate DN via the NF-kappa B signaling pathway. Furthermore, the AMPK and Ras signaling pathways are highly important in DN. However, more research is required to further validate these results.


Diffuse large B-cell lymphoma (DLBCL) is an aggressive B-cell lymphoma with high heterogeneity. There is an unmet need to investigate valid indicators for the diagnosis and therapy of DLBCL. κB) signaling pathways. The KOBAS database was used to assist in the screening of miRNAs of interest and construct the regulatory network of miRNA-mRNA. Finally, the expression level and diagnostic performance of miRNAs were analyzed with GEO datasets, and DEGs were identified from the GEPIA database.  GEO database was utilized to screen for differentially expressed genes (DEGs) and differential miRNAs in DLBCL tissues. The Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were applied to analyse DEGs. Then multiple databases were searched for related miRNAs within DLBCL, TNF receptor-associated factor 5 (TRAF5) and NF-kappa B (NF-κB signaling pathway and cytokine-cytokine receptor interaction, and involved in the process of immune response and protein binding. MiR-15a-5p, miR-147a, miR-192-5p, miR-197-3p, miR-532-5p, and miR-650 were revealed to be targeting TRAF5 and participating in NF-κB signaling pathway and might impact the apoptosis and signal transduction of DLBCL. In the GEPIA database, TRAF5 was significantly overexpressed in DLBCL. The expression of miR-197-3p was upregulated within GEO datasets, while the rest of the miRNAs were downregulated in DLBCL.  DEGs were significantly concentrated in the NF-κB signaling pathway by co-targeting TRAF5 and could be prospective biomarkers exploring the pathogenesis of DLBCL. Subsets of miRNAs may participate in the NF- Diffuse large B-cell lymphoma (DLBCL) is a frequently occurring type of non-Hodgkin lymphoma (NHL) in adults . DLBCL pκB) signaling pathway was proposed to be one potential pathogenesis of DLBCL [κB was caused by mutations in multiple genes, one of which was TNF receptor-associated factor 5 (TRAF5), and the deregulation of TRAF5 may promote the malignant transformation of DLBCL [κB signaling pathway [κB signaling pathway were rarely reported in DLBCL. With the prevalence of microarray technology and the establishment of various bioinformatics databases, effective tools and novel approaches have been accessible for exploring biomarkers and revealing the mechanisms of tumorigenesis and disease progression [κB signaling pathway in DLBCL based on bioinformatics analysis.In recent years, abnormal stimulation of NF-kappa B  and differential miRNAs of DLBCL were screened out from the GEO database , and thehttps://www.ncbi.nlm.nih.gov/geo/) was performed to search for gene and miRNA datasets of DLBCL, with the search term of lymphoma. The inclusion criteria of microarray datasets were as follows: (1) the studies using tissue samples of primary DLBCL from the human species; (2) patients without immune diseases or other tumors, and no relevant treatments received; and (3) nontumor lymphoid tissues as negative controls. The deadline for retrieving the GEO database was June 30, 2021.The GEO database (http://www.ncbi.nlm.nih.gov/geo/geo2r) [P < 0.05. The DEGs repeated in more than five out of 15 microarrays were selected for subsequent analysis.In the GEO database, GEO2R (o/geo2r)  was carrhttps://david.abcc.ncifcrf.gov/) [P value < 0.05 was established as the threshold. The STRING database (https://string-db.org/) was utilized to construct protein-protein interaction (PPI) network of DEGs [In DAVID database (rf.gov/) , Gene On of DEGs .http://www.cuilab.cn/hmdd) [http://mirwalk.umm.uni-heidelberg.de/) [http://www.sysu.edu.cn/) [http://mirdb.org/) [http://diana.imis.athena-innovation.gr/DianaTools) [κB signaling pathway were predicted by miRPathDB (https://mpd.bioinf.uni-sb.de/) [κB signaling pathway.(1) The differential miRNAs between the DLBCL group and the control group were analyzed using the GEO2R function in the GEO database. In addition, HMDD (cn/hmdd)  and miRWerg.de/)  were appedu.cn/) , miRWalkdb.org/)  and DIANnaTools) ; and (3)-sb.de/) , miRWalkhttp://www.targetscan.org/) [http://kobas.cbi.pku.edu.cn/) [P < 0.05). If TRAF5 was concentrated in the NF-κB signaling pathway and involved in apoptosis and signal transduction, the corresponding miRNA was considered to be likely to target TRAF5 and participate in the NF-κB signaling pathway. And then the corresponding miRNA and its target genes involved in NF-κB signaling pathway were integrated. Finally, the miRNA-mRNA regulatory network involved in NF-κB signaling pathway was obtained, and Cytoscape was used for visualization [Targets of hub miRNAs were predicted by 10 databases in five online software program, including ENCORI, miRWalk, miRPathDB, miRDB, and TargetScan (an.org/) . To reduedu.cn/)  (P < 0.0lization .http://gepia.cancer-pku.cn/) [The relative expression quantity of miRNAs in the GEO database was extracted. Differential expression levels of miRNAs were identified between the DLBCL group and the control group, and receiver operating characteristic (ROC) curve was utilized to evaluate diagnostic performance of miRNAs. Meanwhile, differential expression of TRAF5 and other target genes between DLBCL and the control group was identified using the GEPIA database (pku.cn/) .t-test. P < 0.05 revealed statistical significance.SPSS 22.0 was applied for data analysis. Graphpad Prism 7.0 was used for plotting. Statistical significance of each two groups was calculated by the Student's A total of 15 gene expression profile datasets were screened out from GEO database  of the 243 DEGs was mainly focused on the chemokine-mediated signaling pathway, immune response, cell adhesion and inflammatory response. The cellular component (CC) was mainly existed in the extracellular region, external side of plasma membrane, cytosol, and cell surface. Molecular function (MF) was primarily involved in protein binding, chemokine activity, and protein homodimerization activity Figures . Further pathway . The PPIκB signaling pathway were selected from the DIANA, miRWalk, and miRPathDB databases. After the intersection of the above three miRNA data sets, 163 miRNAs that were concurrently related to the DLBCL, TRAF5, and NF-κB signaling pathway were obtained (the Venn diagram is shown in (1) A total of 541 differentially DLBCL-related miRNAs were obtained from GEO datasets (GSE29493 and GSE117063), HMDD, and miRWalk databases. All miRNAs with statistical significance from GEO datasets were shown in κB signaling pathway  of miR-15a-5p, miR-147a, miR-192-5p, miR-197-3p, miR-532-5p, and miR-650 were all simultaneously enriched in the NF-κB signaling pathway were constructed into a visualized miRNA-mRNA regulatory network , X-linked inhibitor of apoptosis (XIAP), B-cell lymphoma 2 (BCL2), and interleukin-1 receptor-associated kinase 1 (IRAK1).MiR-15a-5p, miR-147a, miR-192-5p, miR-197-3p, miR-532-5p, and miR-650 with corresponding target genes involved in the NF- network . In addiP < 0.001), 0.840 (P < 0.01), 0.912 (P < 0.001), 1.000 (P < 0.001), and 0.840 (P < 0.01), respectively , C-C motif chemokine ligand 21 (CCL21), interleukin 1 receptor type 1 (IL1R1), vascular cell adhesion molecule 1 (VCAM1), CCL4, ATM serine/threonine kinase (ATM), lymphotoxin beta (LTB), and TNF receptor superfamily member 1A (TNFRSF1A).The molecular mechanisms of DLBCL have been intensively studied, but the pathogenesis of DLBCL is intricacy, and the relationships among molecular markers, signaling pathways, and regulatory mechanisms are complicated , 2. BioiκB signaling pathway is one of the crucial regulatory mechanisms of apoptosis and participates in multiple stages of B lymphocytes development [κB can prevent cell differentiation, inhibit apoptosis, and promote proliferation of tumor cells, and meanwhile increase inflammatory response, tumor microvascular formation, and metastasis [κB signaling [κB signaling pathway in cancer. The abnormalities of MYD88, mucosa associated lymphoid tissue lymphoma translocation gene 1 (MALT1), B-cell lymphoma 10 (BCL10), and other functional driver genes may lead to the excitation of the NF-κB signaling pathway in DLBCL, promoting proliferation of tumor cells, and ultimately leading to tumorgenesis of DLBCL [κB in DLBCL was aroused by multiple genes, including TRAF5, NF-κB inhibitor alpha (NFKBIA) and TNF receptor-associated factor 3 (TRAF3). To a certain extent, this experimental research verified the reliability of our calculation results. The missing or activated genes may accelerate the occurrence of lymphoma via causing wrong stimulation of NF-κB signaling pathway [The NF-elopment . In lymptastasis –46. Moreignaling –49. Therof DLBCL . In CompκB signaling pathway and performs a variety of significant functions in regulating cell cycle, inhibiting apoptosis, participating in inflammatory response, and immune regulation [κB. The study of Sutherland et al. [κB signaling pathway, and then inhibit apoptosis in B lymphoma cells of mouse. The above studies indicated that TRAF5 was aberrantly overexpressed in lymphoma. In our current study with GEPIA data, the overexpression of TRAF5 was discovered in DLBCL tissues, indicating that TRAF5 may be a promising molecular target and play potential roles in DLBCL. However, further research is warranted to look into the mechanism of TRAF5 in DLBCL.Previous studies have demonstrated that TRAF5 could bind to cell membrane or intracellular receptors such as CD30, CD40, and latent membrane protein 1 (LMP1) and stimulate downstream related signal transduction pathways . The stigulation , 51, 52.gulation  found thgulation  proved td et al.  has clarκB signaling pathway by co-targeting TRAF5, thereby affecting apoptosis and signal transduction of DLBCL. However, the mechanism of each miRNA has not been thoroughly investigated in DLBCL. In the study of nucleus pulposus cells of mouse, Zhang et al. [κB pathway. Overexpression of miR-147a exhibited poor prognosis in hepatitis C virus-positive DLBCL patients [κB pathway to alleviate endothelial cell damage induced by high glucose. The higher expression of miR-532-5p was reported in previous research on the plasma of DLBCL patients [κB activity. MiR-650 was also found to be upregulated in glioma, inducing the activation of NF-κB pathway, and promoting migration, proliferation, and invasion of glioma cells [κB signaling pathway via stimulating the activation of multiple target genes. At last, miRNAs also presented to target other 38 genes, such as BCL2, XIAP, IRAK1, and MYD88, to participate in the NF-κB signaling pathway based on our analysis of the miRNA-mRNA network. This complex regulatory network may participate in the malignant transformation of B lymphocytes and ultimately lead to the occurrence and development of DLBCL.As we know, the abnormal expression of miRNAs can change the production of target mRNAs and the expression of downstream proteins, leading to defects in the cell cycle and apoptosis mechanisms . In thisg et al.  found thpatients . Li and patients  demonstrpatients . In addipatients  clarifiema cells . Hence, There are several limitations for current study. First, the GEO2R online tool of the GEO database was utilized for data analysis in order to minimize the heterogeneity of results during the integration of differentially expressed genes. Although GEO is the most comprehensive and commonly used database, which data is always shared with other databases, there are still some datasets not included due to distinct experimental platforms, designs, materials, sequencing methods, and data types. Second, the current bioinformatics analysis was conducted as a preliminary study without validation by clinical cohorts or experimental research. Clinical, in vivo, and in vitro research are needed to further support our findings.κB signaling pathway by co-targeting TRAF5 and affect the apoptosis and signal transduction of DLBCL. This study provides a theoretical basis for in-depth research on the molecular regulation mechanism of DLBCL and provides evidence to explore new diagnostic biomarkers and cancer-targeted therapeutic drugs. However, these results still need to be verified by extensive experiments.In conclusion, this study indicated that miR-15a-5p, miR-147a, miR-192-5p, miR-197-3p, miR-532-5p, and miR-650 might participate in NF-


To explore the material basis and pharmacological mechanism of Xiaochaihu Decoction (XCHD), the classic Traditional Chinese Medicine (TCM) formula in inhibiting hepatic fibrosis (HF).  The main components in XCHD were screened from the TCMSP database, ETCM database, and literature, and their potential targets were detected and predicted using the Swiss Target Prediction platform. The HF-related targets were retrieved and screened through GeneCard database and OMIM database, combined with GEO gene chips. The XCHD targets and HF targets were mapped to search common targets. The protein-protein interaction (PPI) network was acquired via the STRING11.0 database and analyzed visually using Cytoscape 3.8.0 software. The potential mechanisms of the common targets identified through GO and KEGG pathway enrichment analysis were analyzed by using Metascape database. The results were visualized through OmicShare Tools. The “XCHD compound-HF target” network was visually constructed by Cytoscape 3.8.0 software. AutoDockVina1.1.2 and PyMoL software were used to verify the molecular docking of XCHD main active compounds and HF key targets. β-sitosterol, and kaempferol may be candidate agents, which acted on multiple targets like PTGS2, HSP90AA1, and PTGS1 and regulate multiple key biological pathways like IL-17 signaling pathway, TNF signaling pathway and PI3K-Akt signaling pathway to relieve HF. Moreover, molecular docking suggested that quercetin and PTGS2 could statically bind and interact with each other through amino acid residues val-349, LEU-352, PHE-381, etc.  A total of 164 potential active compounds from XCHD were screened to act on 95 HF-related targets. Bioinformatics analysis revealed that quercetin,  This work provides a systems perspective to study the relationship between Chinese medicines and diseases. The therapeutic efficacy of XCHD on HF was the sum of multitarget and multi-approach effects from the bioactive ingredients. This study could be one of the cornerstones for further research. Hepatic fibrosis (HF) is a reversible liver damage before various chronic liver diseases develop into irreversible liver injuries such as cirrhosis or even liver cancer. It is a key stage to affect the prognosis of chronic liver diseases . The patTCM has almost 5000 years of history, which creates many treatments for disease. Xiaochaihu Decoction (XCHD) is a classic Chinese medicine formula pioneering by the medical sage Zhong-Jing Zhang , and it Network pharmacology is an emerging and promising interdisciplinary subject. It is the combination of classical pharmacology, molecular biology, bioinformatics, and computer technology. It can avoid problems of high cost and long cycle of experiments and drug research. Its concept of holism, systems, and interaction are consistent with the characteristics of TCM treatment. It can systematically explain the complex mechanism of TCM prescriptions on treating refractory diseases  and provhttps://www.ncbi.nlm.nih.gov/geo/), Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform  [http://www.tcmip.cn/ETCM/index.php/Home/), PubChem (https://pubchem.ncbi.nlm.nih.gov/), Online Mendelian Inheritance in Man , Swiss Target Prediction (http://www.swisstargetprediction.ch/) [http://www.uniprot.org/) [https://www.genecards.org/, Version:5.0) [https://bioinfogp.cnb.csic.es/tools/venny), STRING11.0 (https://string-db.org) [http://metascape.org/gp/index.html) [http://www.omicshare.com/), Protein Data Bank (PDB) (https://www.rcsb.org/), AutoDockVina 1.1.2, and PyMoL [Data were analyzed in R version 4.2.0. Cytoscape was used to visualize the PPI network (version 3.8.0) 3.8.0 . The resmsp.php) , The Encion.ch/) , Uniprotot.org/) , GeneCarion:5.0) , Venny 2-db.org) , Metascpex.html) , OmicShand PyMoL .The chemical constituents of XCHD were screened by TCMSP database, ETCM database, and literature mining. OB value  ≥30% and DL value  ≥0.18 were selected as screening criteria. With the help of PubChem, we plotted the two-dimensional structure of main components, which was inputted into Swiss Target Prediction to predict the targets of the main components based on the similarity of two-dimensional structure. All target proteins of each drug are inputted into the Uniprot database to search for corresponding genes. The search criterion was that " homosapens (Human)" was set as the background organism. These data were used to construct the compound-target protein-gene interaction network.P value < 0.005 and |log2 (fold change)| > 1 were visualized by volcano map and heat map. In addition, GeneCards database and OMIM database provided target information related to HF-related disease. Finally, through searching keywords based on MeSH/PubMed: Hepatic Cirrhosis?Cirrhosis, Hepatic?Cirrhosis, Liver?Fibrosis, Liver?Liver Fibrosis etc, the targets of HF-related disease were collected. We then combined those results with GEO analysis results to get HF-related genes.The gene expression profiles of HF (GSE197112) were downloaded from the Gene Expression Omnibus (GEO) database, and “GEOquery,” “Limma,” and “AFFy” packages of R4.2.0 language were used to convert the downloaded probes into corresponding gene names and obtain upregulated and downregulated differentially expressed genes (DEGs), which were saved in Excel. DEGs with the cut-off criteria of XCHD and HF targets were matched one by one, entered into Venny 2.1 software, and these two overlapping targets were uploaded to STRING11.0 database to construct the protein-protein interaction (PPI) network. The species was named as Homo sapiens. Set the minimum interaction threshold to “Maximum confidence” (>0.4) and the rest to default values. In Cytoscape 3.8.0, overlapping targets were visually constructed for active components-target network of XCHD and HF. The CytoNCA plugin in Cytoscape3.8.0 software was utilized to calculate topological parameters of nodes, including degree, obligatory, betweenness, and eigenvector, all of which can provide an in depth analysis of the attributes of nodes in the interactive network.P < 0.01, while the main biological processes and metabolic pathways were analyzed and enriched. The obtained information was processed and imported into OmicShare Tools for analyzing and visualizing the results.The intersection of XCHD and HF targets was recorded on Metascape platform and set up Based on the above results, the active components of the top three in degree were used as ligands, and the targets of the top three in degree were used as receptors for molecular docking. The target protein structure was received from the PDB database, and the three-dimensional structure of the active ingredients downloaded from PubChem CID were imported into AutoDockVina1.1.2 and PyMoL software, and search for the optimal conformation.We relied on TCMSP, ETCM database, and literatures to search for the chemical constituents of XCHD. A total of 17 species of Bupleurum, 13 species of Pinellia, 36 species of Baicalensis, 22 species of ginseng, 92 species of licorice, 29 species of jujube, and 5 species of ginger were obtained. All chemical compounds were screened, and the duplicated compounds without corresponding targets were deleted. Then, we obtained 164 potential active compounds from XCHD for further analysis. According to the OB value, the basic information of the top 20 active components in XCHD is listed in The gene expression profiles of HF (GSE197112) were consisted of 8 samples. A total of 41489 genes were obtained, including 3750 DEGs, 1848 upregulated genes, and 1902 downregulated genes. In the volcano map , DEGs inAccording to the selected XCHD active components and HF targets, Venny 2.1 online software was used to draw Venn diagram, and 95 overlapped genes of XCHD targets and HF targets are identified in β-sitosterol . These may be essential active components with the therapeutic potential in XCHD for HF. The three corresponding maximum targets were PTGS2 , HSP90AA1 , and PTGS1 . In addition, according to the topological parameters calculated by Cytoscape3.8.0 software, the average degree was 15.58 of XCHD active compound-target network in treating HF. The top 10 topological parameters of active components and targets in XCHD are sorted in We constructed a map of the main active components of XCHD and their corresponding targets . Among tP < 0.05), including 2026 BP, 134 CC, and 263 MF. KEGG pathway analysis obtained 46 pathways and the main components of XCHD in the treatment of HF were enriched in signaling pathways such as IL-17 signaling pathway, TNF signaling pathway, and PI3K-Akt signaling pathway. XCHD compounds may act on these pathways to against HF. The top 20 significant enrichment terms of BP, CC, and MF and the top 20 significant KEGG signaling pathways were imported into OmicShare Tools to visually analysis and showed in Figures Metascape website was used to conduct GO analysis and KEGG pathway analysis on the targets of XCHD in treating HF. The GO analysis consisted of biological processes (BP), cellular compound (CC), and molecular function (MF). The results showed that the 95 genes were enriched in 2423 GO entries  with the larger degree and the three compounds with more predicted targets in active components targets network of XCHD and HF were, respectively, molecularly docked. The molecular docking results showed that the lowest binding energy of the molecule and the target protein were less than 0, indicating that the ligand and the receptor could spontaneously bind. The docking binding energy of quercetin of PTGS2, HSP90AA1, and PTGS1 was all less than-5 kcal·mol-1. The binding energy was, respectively, − 8.5, − 7.6, and − 7.0 kcal·mol−1. The lowXCHD is a classic herbal formula with a long history of clinical application. Although the anti-HF role of XCHD has been studied through experiments, systematic research on the exact mechanism of action is lacking, which greatly restricted the modernization and the internationalization of XCHD. As for this concern, we made a combination of bioinformatics analysis, network pharmacology, and molecular docking might contribute to find the therapeutic mechanism of XCHD on HF. Based on data mining, data analysis, and virtual computing, network pharmacology presents the relationships between active ingredients, key targets, related pathways, and diseases in computational modeling analysis. Compared to traditional pharmacology research methods, network pharmacology has shifted the paradigm from a “one-target, one-drug” mode to a “network-target, multiple-component-therapeutics” mode. This approach makes it very powerful and comprehensive for the analysis of drug combinations. Molecular docking can accurately predict the conformation of small molecule ligands within the appropriate target binding site and to assess the binding affinity. In recent years, molecular docking is quickly becoming one of the key component of the drug discovery pipeline.β-sitosterol were the top three promising active ingredients, which could act on multiple targets like PTGS2, HSP90AA1, and PTGS1 and regulate multiple biological pathways like IL-17 signaling pathway, TNF signaling pathway, and PI3K-Akt signaling pathway to relieve HF.In this work, a total of 164 potential active compounds from XCHD were screened to act on 95 HF-related targets. Quercetin, kaempferol, and 4–) induced HF. Quercetin can also markedly reverse the histopathological changes in rats with CCL4-induced HF [κB (NF-κB). The inhibition of NF-κB phosphorylation can protect against hepatic injury, inflammation, and fibrosis [Quercetin is an effective liver protectant . It is tduced HF . Moreovefibrosis . Quercetfibrosis . In addifibrosis , 36. Quefibrosis . Quercetfibrosis –40. Querfibrosis . Furtherfibrosis .β-sitosterol, which widely exists in natural plants, is classed as phytosterol with multiple biological activities and known as the “key of life” [β-sitosterol realizes a downregulation of the mRNA, protein expression of collagen-1, and α-smooth muscle actin (α-SMA) in activated HSCs, prevents collagen accumulation, alleviates dimethylnitrosamine- (DMN-) induced liver injury in mice, and plays an anti-fibrosis role [β-sitosterol has a dose-dependent preventative effect of liver on CCL4-induced chronic liver disease, which can inhibit oxidative stress, reduce the expression of HSCs activation markers, alleviate pathological damage of liver, and inhibit fibrosis [β (TGF-β) is a key mediator of HSCs activation and extracellular matrix deposition, which could result in HF. It is a key inducer of fibrosis in many organs. The severity of HF is positively correlated with TGF-β level, and the TGF-β pathway is considered as a potential anti-HF target [of life” . β-sitossis role . It has fibrosis . TransfoF target .β expression and ECM deposition and relieve HF. Furthermore, intraperitoneal injection of kaempferol significantly reduces necrosis of liver tissues and collagen deposition. The levels of ALT, AST, LN, and HA in kaempferol treatment group were significantly lower than control group. Kaempferol can inhibit collagen synthesis and HSCs activation in vivo and in vitro [Kaempferol has been proved to significantly reduce TGF-in vitro . Investiin vitro . Kaempfein vitro .β, and tumor necrosis factor-α (TNF-α) and increases the expression of the main fibrotic cytokine TGF-β [β, and other cytokines to stimulate the activation of HSCs, induce the appearance of all kinds of fibrotic factors including itself, and form a signal network to jointly affect the initiation and occurrence of HF [KEGG pathway analysis shows that the XCHD mechanism of inhibiting HF is related to the IL-17 signaling pathway, TNF signaling pathway, PI3K-Akt signaling pathway, and others. The IL-17 signaling pathway promotes the production of interleukin (IL)-6, IL-1ne TGF-β . In addine TGF-β . Tumor nce of HF , 53. Thece of HF . Studiesce of HF –56.κB-dependent mechanism [β and IL-18 [Molecular docking results show that the active compounds of XCHD have good affinities with PTGS2, HSP90AA1, and PTGS1. Prostaglandin-endoperoxide synthase (PTGS/COX) is a key rate-limiting enzyme in the synthesis of prostaglandins from arachidonic acid. Two isoenzymes of this enzyme, PTGS1 (COX-1) and PTGS2 (COX-2), have been identified. PTGS1 (COX-1) mainly acts on endoplasmic reticulum and expresses in many tissues. It is a constituent enzyme involved in physiological processes. PTGS2 (COX-2) mainly acts on cell membranes, and its expression induced by a series of stimuli is a major compound of inflammation and HF , 58.Undeechanism . Inhibitnd IL-18  and mitind IL-18 .The occurrence and development of HF is a complex biological process involving multiple targets and multiple pathways. Without effective treatment, HF might transform into cirrhosis or even liver cancer, greatly affecting the patient's quality of life and life period. Hence, it is of great significance to intervene in the pathological progression of HF. This study preliminarily proved that the therapeutic efficacy of XCHD on HF was the sum of multitarget and multi-approach effects from the bioactive ingredients. The results also provide more references for XCHD' clinical application and development, whereas the results of this work also have limitations. The present research data from different online databases was based on the reviewed and predicted data. Thus, those unproven, undocumented, and unupdated compounds or targets may not be included in our analysis. In a next step, we will carry out in vivo and in vitro experiments focusing on the stability test, pharmacodynamic evaluation, omics techniques, and pathway validation to conduct in-depth observations on the mechanism of the XCHD in treating HF.


Xingnao Kaiqiao Pill in the treatment of perioperative neurocognitive disorder (PND) from the perspective of network pharmacology and molecular docking technology. Active ingredients of Xingnao Kaiqiao Pill were screened from the traditional Chinese medicine database and analysis platform, and the putative targets were predicted. The GeneCards database was searched to obtain PND-related targets. The genes corresponding to the targets were searched and annotated on the UniProt database. The VennDiagram package in R was employed to obtain common target genes. The overlap genes were introduced into STRING to obtain a protein-protein interaction (PPI) network; thus, key targets were screened. The target relationship network of “Xingnao Kaiqiao Pill–traditional Chinese medicine–compound–common target” was constructed by Cytoscape software. Using R language package Bioconductor, Gene Ontology (GO) and pathway enrichment analysis  were performed on the common target genes. A total of 45 active ingredients of Xingnao Kaiqiao Pill were screened, with 182 potential targets, and 1,579 PND-related targets were retrieved from the GeneCards databases (Score ≥ 1). Using VennDiagram, 132 overlap genes were gotten. Xingnao Kaiqiao Pill mainly acted on targets, such as MAPK and JUN. GO enrichment analysis displayed G protein-coupled amine receptor activity, nuclear receptor activity, ligand-activated transcription factor activity, G protein-coupled neurotransmitter receptor activity, steroid hormone receptor activity, and cytokine receptor activity. KEGG enrichment analysis exhibited 157 signaling pathways. The regulation of interleukin 17, tumor necrosis factor, hypoxia-inducible factor-1, and MAPK signaling pathways affected central nervous system (CNS) inflammatory response, cellular immunity, tumor-related signaling pathways, protected neurons, and inhibited PND. The active ingredients of Xingnao Kaiqiao Pill adjust interleukin 17, tumor necrosis factor, hypoxia-inducible factor-1, and MAPK signaling pathways by acting on cell targets, such as JUN, MAPK, AKT1, etc., and finally exert a therapeutic effect on PND.To investigate the molecular mechanism of  With the increased number of elderly surgical patients, brain dysfunction after general anesthesia has been paid more and more attention in clinical practice. Neurocognitive changes related to surgery and anesthesia are mainly composed of postoperative delirium (POD) and postoperative cognitive dysfunction (POCD) . Since 2Xingnao Kaiqiao Pill, Angong Niuhuang Pill, and Buyang Huanwu Decoction are utilized for intervention, and have certain clinical effects  was built based on the big data of traditional Chinese medicines. The molecular network of various complex components constructed by network pharmacology and the protein/gene interactions based on multilevel targets can explain the material basis and functions of traditional Chinese medicine. Network pharmacology analysis is becoming an important method for studying complex diseases caused by multiple genes and multiple factors, such as PND. This study investigated the mechanism of 1 was employed to search the active ingredients of the Xingnao Kaiqiao Pill formula  (The TCMSP databasee Radix) . Two parXingnao Kaiqiao Pill using the TCMSP platform and the DrugBank database. For compounds whose targets were not found in the TCMSP, the Pharmacopoeia was retrieved, and literature search was conducted, and then the Pharm Mapper database was used for target prediction. The sdf format of the active ingredients was uploaded to the Pharm Mapper platform, with the property of “homo sapiens” set, and the putative targets could be obtained.Chemoinformatics was employed to predict the targets of the Chinese medicine components in The full name of PND was entered as a search term, and the disease-related targets could be retrieved on the GeneCards database. The output results of GeneCards used a relevance score greater than 1 as the screening criteria. Considering that PND has used names, such as POD and POCD, in the past, “postoperative delirium” and “postoperative cognitive dysfunction” were also input as search terms to prevent omission; the search results were summarized, and the targets were merged.2 The UniProt ID and Gene Name were annotated for each target. The Hash function of the Perl script was employed for automatic annotation of the above targets so as to perform further analysis.The active ingredients of the above-mentioned medicines and the targets corresponding to the diseases were searched on the UniProt database.Xingnao Kaiqiao Pill and PND, and the intersection genes corresponding to the compound disease were screened out as common target genes to determine the potential targets of Xingnao Kaiqiao Pill acting on PND.The VennDiagram package in R software was employed to calculate the overlap between the targets of Xingnao Kaiqiao Pill—traditional Chinese medicine—compound—common target” relationship network for visual analysis  less than 0.05 . The GO Xingnao Kaiqiao Pill and key targets encoded by hub genes, The RCSB PDB database  was used to visualize the network, and the size of the nodes was proportional to the degree centrality obtained from topology analysis. As is shown in To shed light on the potential mechanisms through which Xingnao Kaiqiao Pill against PND. The results of the top 10 in the above three aspects are shown in GO analysis results demonstrated that 132 targets were enriched in 154 GO items; these targets primarily existed in the membrane raft, the membrane microdomain, the caveola, the plasma membrane raft, the postsynaptic membrane, the organelle outer membrane, the outer membrane, the integral component of the postsynaptic membrane, and other regions of the cells. Secondly, these targets were involved in metabolism, energy pathways, apoptosis, and other biological processes. Moreover, G protein-coupled amine receptor activity, DNA-binding transcription factor binding, nuclear receptor activity, and other functions are the principal molecular functions of P-value, the first 20 items were selected, as shown in Xingnao Kaiqiao Pill on PND seems to have a close association with immune response and metabolism of immune molecules. The details of the above three signaling pathways are displayed from The results of KEGG pathway analysis of common target genes exhibited that 125 targets were enriched in 157 signaling pathways or biological processes. According to the count value and Xingnao Kaiqiao Pill and key targets encoded by hub genes. According to Xingnao Kaiqiao Pill demonstrated good binding with the key targets. Beta-sitosterol had a strong binding ability with two hub genes, i.e., AKT1 and RELA. Stigmasterol showed good binding ability with MAPK1 and IL6. Kaempferol showed good binding ability with JUN.In this study, we used molecular docking stimulation to identify the binding ability between bioactive components of PND, a CNS complication, presents many clinical manifestations; the deterioration of cognitive function involves cognitive, memory, motor function, attention, and concentration. According to the universally recognized pathogenesis, PND can be considered as a neuroinflammation disease . It has There is no clear record of this disease in Chinese medicine. Some scholars believe that PND should be classified as “dementia,” “forgetfulness,” and “epilepsy” on the basis of its clinical manifestations , and claqi, and blood deficiency syndrome. Elderly people frequently experience liver and kidney deficiency, insufficient qi, and blood. Furthermore, surgical trauma can break qi, consume blood, damage the collaterals, cause deficiency of qi and blood circulation, stagnation of blood stasis, and result in cerebral collateral blockage and mental function failure. The treatment should invigorate qi, activate blood, dispel blood stasis, and dredge collaterals. If the patient suffers from heart and kidney deficiency, yin deficiency, blood insufficiency, and internal disturbance of deficiency and fire, the treatment should nourish yin, blood, the heart, and focus on tranquilization. Chinese medicine compound preparation Xingnao Kaiqiao pill can tranquilize the emotional distress, strengthen body resistance, eliminate pathogenic factors, suppress the hyperactive liver for calming endogenous wind, regulate qi, dispel stagnation, tonify the kidney, and invigorate the brain. Xingnao Kaiqiao pill has the characteristics of overall regulation, multiple targets, multiple pathways, and multiple mechanisms, and has advantages in improving cognition and perioperative quality of life. More than 50 patients with PND, who had been consulted at the Department of Traditional Chinese Medicine in our hospital since 2020, received the treatment with Xingnao Kaiqiao pill and achieved good results.Chinese medicine treatment of PND is generally based on pathophysiological characteristics and clinical manifestations of the elderly after surgery. In a study of PND, Chinese medicine syndrome in elderly patients with bowel cancer, clinical patients were roughly divided into five syndrome types, namely, kidney essence deficiency syndrome, phlegm turbidity blocking orifice syndrome, blood stasis blocking collaterals syndrome, viscera stagnation, and turbid retention syndrome, Numerous research results demonstrated that PND may be induced by various factors, and its pathogenesis is not yet fully clear. Animal experiments and clinical trials have shown that PND pathogenesis is associated with increased immune inflammatory response of the CNS, abnormal neurotransmitters or receptors, abnormal cholinergic nerve function, β-amyloid formation, noxious stimulation, and stress response . It is cMAPK is a class of intracellular serine/threonine protein kinases, an important signaling system that mediates extracellular signals to intracellular responses, and plays a key role in immunity, inflammation, apoptosis, and angiogenesis. The MAPK signaling pathway plays an important role in the pathophysiological process of cognitive impairment . IL-6 isThe GO analysis results confirmed that intersection genes mainly enriched in the G protein-coupled amine receptor activity, nuclear receptor activity, ligand-activated transcription factor activity, G protein-coupled neurotransmitter receptor activity, steroid hormone receptor activity, and cytokine receptor activity may be associated with abnormal neurotransmitter or receptor and abnormal cholinergic nerve function in the pathogenesis of PND .Xingnao Kaiqiao Pill. These signaling pathways above do not exist in isolation, but have many intersections and protein interactions. The interaction of multiple signaling pathways has a key impact on the activation of downstream signaling pathways, the activation of microglia, the release of neurotoxic substances, and the impairment of cognitive function (In the results of KEGG pathway enrichment, PND-related body immunity and inflammation signaling pathways include the AGE-RAGE signaling pathway, the TNF signaling pathway, and the IL-17 signaling pathway. Notably, we found the MAPK signaling pathway embedded in these pathways above. The significant indicators indicate a high correlation with the pathophysiological mechanism of PND and the pharmacological effects of function .IL-17 is an important member of the new inflammatory cytokine family, and a proinflammatory cytokine extensively present in various inflammatory pathways . The IL-Microglia are immune cells in the CNS, and their activation pathways include three states: classic activation, alternative activation, and acquired activation. The classic activation pathway is strongly associated with TNF. The results of the KEGG pathway enrichment in this study displayed that NF-κB, JNK1/2, and Akt sites in the compound-disease target are crucial receptors in TNF target cells. There are many types of inflammatory mediators, cytokines, and chemokines released by TNF-mediated target cells. Among them, 12 types, such as IL-1β, IL-6, Jun, etc., are clearly identified as compound-disease targets.Cellular hypoxia linked to cognitive impairment. HIF-1 is an important regulator of cells, adapting to hypoxic environment . HIF-1α Xingnao Kaiqiao Pill in the treatment of PND is mainly associated with the regulation of CNS inflammation, and the involved signaling pathways have many intersections and protein interactions. MAPK1, JUN, AKT1, IL6, and RELA are core targets of active ingredients acting on the main related signaling pathways. Due to the limitations of the database and the algorithm, further experimental investigations are needed to verify the results from this analysis.In summary, the mechanism of The original contributions presented in this study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.WZ and GS managed the literature searches, designed the study, interpreted the statistical analyses, and wrote the first draft of the manuscript. HW and MF contributed to the data administration. XG edited the language to improve the clarity of the manuscript. ZL instructed in the study approach and supervised the statistical analyses and their interpretation. All authors have contributed to and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.