To explore the molecular mechanism of Simiao powder in the treatment of knee osteoarthritis.  Based on oral bioavailability and drug-likeness, the main active components of Simiao powder were screened using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). GeneCard, OMIM, DisGeNET, DrugBank, PharmGkb, and the Therapeutic Target Database were used to establish target databases for knee osteoarthritis. Cytoscape software was used to construct a visual interactive network diagram of “active ingredient - action target – disease.” The STRING database was used to construct a protein interaction network and analyze related protein interaction relationships. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) biological process enrichment analysis were performed on the core targets. Additionally, Discovery Studio software was used for molecular docking verification of active pharmaceutical ingredients and disease targets.  Thirty-seven active components of Simiao powder were screened, including 106 common targets. The results of network analysis showed that the targets were mainly involved in regulating biological processes such as cell metabolism and apoptosis. Simiao powder components were predicted to exert their therapeutic effect on the AGE-RAGE signaling pathway in diabetic complications, IL-17 signaling pathway, TNF signaling pathway, Toll-like receptor signaling pathway, and HIF-1 signaling pathway. The molecular docking results showed that the active components of Simiao powder had a good match with the targets of IL1B, MMP9, CXCL8, MAPK8, JUN, IL6, MAPK1, EGF, VEGFA, AKT1, and PTGS2.  Simiao powder has multisystem, multicomponent, and multitarget characteristics in treating knee osteoarthritis. Its possible mechanism of action includes inhibiting the inflammatory response, regulating immune function, and resisting oxidative stress to control the occurrence and development of the disease. Quercetin, wogonin, kaempferol, beta-sitosterol, and other active ingredients may be the material basis for the treatment of knee osteoarthritis. Knee osteoarthritis (KOA) is a common disease in middle-aged and elderly populations. The main clinical manifestations are knee pain, stiffness, and limited joint activity, and severe patients may even have disability . KOA hasAtractylodes chinensis rhizome (Rhizoma aractylodis), Cortex phellodendri, Radix achyranthis bidentatae, and Coicis Semen (Coix seed).Chinese herbal medicines (CHMs) have been used in China for thousands of years. Simiao powder use in treatment of KOA was first recorded in the book Cheng Fang Bian Du written by Bingcheng Zhang in the Qing Dynasty of China. Simiao powder is composed of four herbs: Atractylodes chinensis rhizome is derived from the dry rhizome of the compositae Atractylodes lancea (Thunb.) DC or Atractylodes chinensis (DC.) Koidz. It eliminates dampness, strengthens the spleen, eliminates wind, and disperses cold. Modern pharmacological studies have found that the main active components of Atractylodes chinensis rhizome include atractylenolide I, atractylenolide II, atractylenolide III, atractylone, hinesol, β-eudesmol, atractylodin, stigmasterol, and β-sitosterol [α, IL-1β, IL-6, VEGF, and PlGF in chronic inflammation [Atractylodes chinensis rhizome has antitumor effects. Bladder cancer is a critical urological disease. Modern studies have confirmed that ATL-1 has therapeutic effects on bladder cancer in vivo and in vitro by increasing the level of P21 and decreasing the levels of cyclin B1, CDK1, and Cdc25c [Atractylodes chinensis rhizome are also effective against leukemia and allergic diseases [The rhizome of tosterol . Modern tosterol , 6. ATL-ammation . At the ammation . Additiod Cdc25c . Melanomd Cdc25c . Notablydiseases .Phellodendron chinense Schneid or Phellodendron amurense Rupr. It contains many active components, such as alkaloid, sterol, lactone, and mucinous substance [Cortex phellodendri is the dry bark of the rutaceae plants ubstance . Cortex ubstance . Alkaloiubstance . Other substance .β- (IL-1β-) induced chondrocyte inflammation and apoptosis and may be a potential drug for the treatment of osteoarthritis [β-catenin signaling pathway [The source of Radix Achyranthis bidentatae is the root and rhizome of Achyranthes aspera L. The main active ingredients of Radix Achyranthis bidentatae include saponins, sterones, flavonoids, sugar, alkaloids, and organic acids. Among them, saponins and sterones are the main chemical components of Radix Achyranthis bidentatae . Previourthritis . Achyranrthritis . ABPS carthritis . Additio pathway .κB.Coicis Semen is a dried and mature seed of Coix lacryma-jobi L.var.mayuen (Roman.) Stapf. Coicis Semen is not only a traditional Chinese medicine but also a kind of food. The main active components of Coicis Semen include fatty acids, lipids, sugars, sterols, alkaloids, and triterpenes. Modern pharmacological studies have shown that Coicis Semen has anti-inflammatory, analgesic, antitumor, and immune-enhancing properties among other pharmacological activities . Adlay sSimiao powder has been used to treat arthritis for hundreds of years. During this period, although some of its mechanisms have characterized, those underlying its role in KOA are lacking. CHMs have complex characteristics of multicomponent, multitarget, and multichannel activity. A single herb contains multiple medicinal active substances, which is further complicated by the use of multiple herbs in combination. The therapeutic effect of CHMs is established on the basis of the theory of synergy, and CHM compounds play an important role in the treatment of various diseases. However, the active components, targets, and mechanisms of CHM compounds in the treatment of diseases are not yet clear.In 2007, Yildirim et al. conducted an analysis based on drug-gene and drug-protein interaction data sets and found that the drug and target tended to form an enriched network rather than an isolated corresponding relationship . MoreoveTherefore, in this study, the mechanism of action of Simiao powder in the treatment of KOA was characterized by using network pharmacology and molecular docking technology, and the scientific basis was provided. This paper attempts to elucidate the specific targets and molecular signaling pathways in KOA influenced by Simiao powder and provide new strategies for new drug development and clinical use. The flow chart of this work is shown in https://www.UniProt.org/UniProt/) was used to determine the human gene abbreviation of each target and obtain the possible target proteins of Simiao powder.The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) is a unique tool for systematic pharmacology research of traditional Chinese medicines (TCMs) . In TCMShttps://www.OMIM.org/), GeneCard database (https://www.genecards.org/), DisGeNET database (https://www.disgenet.org), DrugBank database (https://www.DrugBank.ca), PharmGkb database (https://www.PharmGkb.org/), and Therapeutic Target Database (http://bidd.nus.edu.sg/bidd-databases/TTD/TTD.asp). The database search results were merged, and duplicate targets were deleted to obtain all targets of KOA. The intersection of the targeted prediction results of the active components of Simiao powder and the retrieval results of KOA-related targets was determined, and the common target was selected as the potential therapeutic target of Simiao powder in the treatment of KOA. The Venny 2.1 (http://bioinfogp.cnb.csic.es/tools/venny/index.html) online tool was used to map the active ingredient target and the disease target of Simiao powder and to draw Venn diagrams. Then, the cross targets of Simiao powder and KOA were collected as the common genes of RAB in KOA treatment, which may be the potential target sets of Simiao powder in KOA treatment.“Knee osteoarthritis” was used as the search term in the OMIM database  is the number of connections between a node and other nodes in a network, and it is the most direct metric to depict the centrality of nodes in network analysis. The larger the degree, the more important the node . Betweenhttps://STRING-db.org/) is a database for searching known protein interactions and predicting protein interactions. By collecting, evaluating, and integrating all common “protein-protein” interaction resources, it complements the results predicted by the computer. On this basis, the common gene targets of Simiao powder and KOA were imported into the STRING database. A confidence level of 0.7 was selected, and the node on which the network was interrupted was hidden to analyze the protein-interaction network. The analysis results are saved in TSV format and imported into Cytoscape for topology attribute analysis. A node with high DC, BC, and CC values plays a very important role in the network. According to the analysis results of the topological properties of PPI mentioned above, the target with a median value above is selected as the core target, and the target is screened twice. Based on the results of the methods described above, we identify the hub gene of the network.PPI is the basis of cell function of the body and plays an important role in regulating physiological and pathological states of the body. A protein-interaction network (PIN) is a network constructed with protein-interaction information. PIN uses network nodes to represent proteins, network connecting lines to represent protein interactions, and node size, color, connection length, and thickness to represent topology parameters of node network. PPI and access networks are important in most biological functions and processes. The STRING database  for signaling pathway enrichment analysis; its visual function features are powerful. On the one hand, GO functional enrichment analysis includes categorization of molecular function (MF), biological process (BP), and cellular components (CC). On the other hand, KEGG enrichment analysis is used to screen the KEGG pathways. Using the above tools, we set the p value cutoff to 0.05 and q value cutoff to 0.05, selected the top 20 items with the highest enrichment, and displayed them in a bar chart. We downloaded 20 access maps and selected the possibly related ones after screening.Bioconductor is a common open-source toolkit for analyzing and understanding high-throughput genomic data. Based on the R software, the tool provides a variety of analysis and visualization methods for high-throughput genomic data, as well as GO annotation information of 19 species including human. In this study, the target name of Simiao powder intervention in KOA was transformed into an Entrez ID using Perl language tools. Then, we used the GO annotation information provided by Bioconductor and KEGG pathway database . The protein crystal structure of KOA-related target proteins was obtained from the RCSB PDB database (https://www.rcsb.org/).Through construction of the network of active components and disease targets, the drug-like components and KOA targets of Simiao powder were obtained. The mol2 structure of the pharmaceutical active ingredient was obtained from the Chemical Book database , molecular function (MF), and cellular component (CC). The results showed that the targets of Simiao powder for KOA were enriched for 123 GO terms. We screened the top 20 GO analysis results with hreshold . KEGG enThe KEGG Mapper tool was used to obtain the pathway map of Simiao powder for the treatment of KOA, as shown in The results of molecular docking show that the active ingredients of Simiao powder match well with the hub genes. The mechanism of Simiao powder's treatment of KOA was partially explained by the regulation of the targets of IL1B, MMP9, CXCL8, MAPK8, JUN, IL6, MAPK1, EGF, VEGFA, AKT1, and PTGS2. This indicates that the molecular docking results are consistent with the results of network pharmacology screening, and the reliability of network pharmacology is verified by molecular docking. The docking results for Simiao powder's active ligand and KOA target protein receptor are shown in Supplementary Table β and TNF-α, inhibit the inflammatory reaction effectively, downregulate the expression of IL-6, and upregulate the expression of basic fibroblast growth factor (bFGF), to reduce the degradation of cartilage matrix [Some previous studies have shown that Simiao powder inhibits inflammation. Simiao powder can inhibit the production of proinflammatory cytokines and reduce cartilage and bone injury by regulating the ATX-LPA and MAPK pathways . A rabbie matrix , 38. Adde matrix . AlthougBased on the network pharmacology approach, 37 active ingredients and 106 potential targets of Simiao powder were screened by using the target database of traditional Chinese medicine compounds and a human disease gene database. The enrichment of GO and KEGG terms in the targets of Simiao powder acting on KOA was analyzed with several biological function databases. Quercetin, wogonin, kaempferol, beta-sitosterol, and other active ingredients play an important role in the treatment of KOA with Simiao powder. The degree value of quercetin is 174, which is much higher than that of other compounds.β-induced inflammation of rat OA chondrocytes by inhibiting NF-κB, thereby protecting OA rat chondrocytes [β-stimulated inflammation by inhibiting the MAPK pathway [κB, and significantly inhibits NLRP3 inflammatory bodies. Additionally, beta-sitosterol also regulates bone metabolism balance and antioxidation [Quercetin is a flavonol compound with many biological activities; it is widely distributed in the plant kingdom and has many functions such as antioxidation, antiviral, and anti-inflammatory effects. Quercetin can inhibit the apoptosis of chondrocytes in the knee joint, reduce the production of proinflammatory cytokines, weaken the oxidative stress response, inhibit the degradation of cartilage extracellular matrix, protect articular cartilage, and delay the progression of OA . Wogonindrocytes . Another pathway . Beta-sixidation .Through topology analysis of the PPI network, 11 hub genes were identified including IL1B, MMP9, CXCL8, MAPK8, JUN, IL6, MAPK1, EGF, VEGFA, AKT1, and PTGS2.β can also activate AP-1-mediated transcription in articular chondrocytes. IL-1β induces MMP13 and inhibits bone and joint by inhibiting BATF/JUN transcription activity and inflammation of cartilage [IL6 is a mediator of inflammation and immune response, can be detected in synovial fluid, and is expressed in osteoarthritis cartilage, making IL-6 inhibition a potential target for the treatment of KOA , 46. Actartilage –50. AKT artilage . VEGFA partilage . It can artilage . Chemokiartilage . Matrix artilage . A genetartilage . Howeverartilage . PTGS2 iartilage . Epidermartilage .The enrichment analysis showed that Simiao powder may play a role in the prevention and treatment of KOA by regulating the AGE-RAGE in diabetic complications, IL-17, TNF, Toll-like receptor, and HIF-1 signaling pathways. In the process of aging, advanced glycation end products (AGEs) accumulate in articular cartilage.κB and MAPKs in various cell types, including chondrocytes [α and p38 MAP kinases and the activation of NF-κB, which in turn increases COX-2 expression and PGE2 production [The biological activity of AGEs is believed to be mediated by the age-specific receptor (RAGE), and activation of RAGE is involved in key signaling pathways related to activation of the proinflammatory response and various inflammatory genes . On the drocytes . On the drocytes . Additiooduction . IL-17 ioduction . Additiooduction .α, is known to play an important role in the pathological progress of OA. TNF-α can bind to two kinds of membrane receptors: TNF-R1 and TNF-R2. TNF-R1 can be activated in its soluble and membrane form, while TNF-R2 is mainly bound as its membrane form [κB and the MAPK signaling pathway. The activation of various signaling pathways can induce the production of matrix metalloproteinases, including MMP1, MMP3, and MMP13, which can enhance inflammation and further aggravate the destruction of OA cartilage [The TNF signaling pathway, especially TNF-ane form . Compareane form . The binartilage .Toll-like receptors (TLRs) are transmembrane signal transduction receptors. As a type I transmembrane protein, TLRs can be divided into three parts: extracellular, cytoplasmic, and transmembrane regions . TLRs arκB stimulate the release of IFN regulatory factors and the MAPK signaling pathway, leading to the release of chemokines, proinflammatory factors, and IFN. The TLR2/TLR4 signaling pathway induces expression of IL-1 and MMPs, increases the production of NO and PGE2, accelerates the degradation of proteoglycan and type II collagen, leads to the destruction of articular cartilage, and promotes the formation of KOA [TLR1-7 and TLR9 are upregulated in the synovium of patients with OA, and TLR4 is related to the severity of OA . Activatn of KOA . Addition of KOA .α protein family have been described: HIF-1α, HIF-2α, and HIF-3α [α and HIF-1β. One study shows that HIF-1α plays an important role in preventing OA. HIF-1α downregulates MMP13 by inhibiting β-catenin transcriptional activity in chondrocytes, thus alleviating the development of OA; lack of HIF-1α intensifies cartilage catabolism [Hypoxia inducible factors (HIFs) are key regulators of transcription factors and cell responses to hypoxia. So far, three members of the human HIF-d HIF-3α . HIF-1 id HIF-3α . HIF-1 itabolism . Additiotabolism .Using network pharmacology, 37 active components and 1070 potential therapeutic targets of Simiao powder were explored in this study. There were 1952 KOA-related targets, 106 of which are shared between Simiao powder and KOA.The GO biological process and KEGG signaling pathway enrichment analysis preliminarily predicted that Simiao powder regulates IL1B, MMP9, CXCL8, MAPK8, Jun, IL6, MAPK1, EGF, VEGFA, AKT1, PTGS2, and other targets through quercetin, wogonin, kaempferol, beta-sitosterol, and other effective active components; it regulates the AGE-RAGE signaling pathway in diabetic complications, IL-17 signaling pathway, TNF signaling pathway, Toll-like receptor signaling pathway, and HIF-1 signaling pathway and can inhibit inflammatory reaction, regulate immune function, and treat KOA.Unfortunately, this study provided only preliminary predictions, and the results have not been verified in clinical and animal experiments. Limited by the deficiencies of systems biology, multidirectional pharmacology, computational biology, and network analysis, the conclusions still need to be verified with subsequent experiments. Although there are some limitations, the network pharmacology analysis results show that there are many and complex factors that cause KOA. The analysis also intuitively shows the characteristics of Simiao powder in the treatment of KOA. Such research will undoubtedly increase our understanding of the pathogenesis of KOA and lead to new treatment strategies in the prevention and treatment of KOA.


To study the risk factors involved in the occurrence and progression of cervical intraepithelial neoplasia (CIN) and to establish predictive models.Genemania was used to build a gene network. Then, the core gene-related pathways associated with the occurrence and progression of CIN were screened in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) experiments were performed to verify the differential expression of the identified genes in different tissues. R language was used for predictive model establishment.A total of 10 genes were investigated in this study. A total of 30 cases of cervical squamous cell cancer (SCC), 52 cases of CIN and 38 cases of normal cervix were enrolled. Compared to CIN cases, the age of patients in the SCC group was older, the number of parities was greater, and the percentage of patients diagnosed with CINII+ by TCT was higher. The expression of TGFBR2, CSKN1A1, PRKCI and CTBP2 was significantly higher in the SCC groups. Compared to patients with normal cervix tissue, the percentage of patients who were HPV positive and were diagnosed with CINII+ by TCT was significantly higher. FOXO1 expression was significantly higher in CIN tissue, but TGFBR2 and CTBP2 expression was significantly lower in CIN tissue. The significantly different genes and clinical factors were included in the models.Combination of clinical and significant genes to establish the random forest models can provide references to predict the occurrence and progression of CIN. Cervical cancer is a female malignant tumor, and it has the second highest morbidity rate and the third highest mortality rate in the world . CervicaThe occurrence and progression of CIN is a very complex and multifactorial process. Cervical cytology analyses, HPV tests, colposcopies and cervical biopsy histopathology analyses are widely used in the clinic to screen for cervical intraepithelial neoplasia (CIN). However, the cytological diagnosis, HPV-DNA detection, pathology and single gene analysis are not capable of predicting the outcome of CIN. A large number of women every year may receive unnecessary treatment or may delay treatment. Therefore, combining the clinical features and significantly differentially expressed genes in CIN patients, a multifactor predictive model can be produced to more accurately predict the occurrence and progression of CIN, enabling the shunting of CIN patients according to risk factors for progression and the development of individualized treatment plans for different patients.Vibrio cholerae infection pathway. Among the genes of these pathways, CCND2, CDKN2A, CADM1, CCL2, CTNNB1, ERBB2, PHGDH, TP53BP1, TP63, TGFBR2, EGFR, PRKCB, SH3KBP1, KDELR1, NFATC1, PPP2R5D, HSPA6, PIKFYVE, RABEP1, TJP2, PIK3CA, PRKCI, PTGS2, STK11, FOXO1, TP53, MYC, IMP3 and MAPK1 are known to interact, and these genes may also be related to the occurrence and progression of CIN [The progression of CIN is related to signaling pathways such as the Wnt signaling pathway, the endocytosis signaling pathway and the n of CIN . GenemanSample protector for DNA/RNA (Takara 9750), RNA iso Plus (Takara 9109), PrimeScript™ RT reagent Kit with gDNA Eraser (Takara RR047A),SYBR®Premix Ex Taq™II (Takara RR820A) and primers were obtained from the Takara (Japan). A QuanStudio5 thermal cycler was purchased from Thermo Fisher (America). All experiments were performed according to the manufacturer’s instructions.A total of 120 cases were used, and specimens were obtained from the Gynecology Oncology Department of Guangxi Medical University Affiliated Cancer Hospital. The clinical features included age, gravity, parity, and HPV status. Normal cervical tissues were taken from patients who underwent a hysterectomy for uterine leiomyoma. CIN tissues were taken from postoperative cervical specimens obtained after cervical cold knife conization, and SCC tissues were collected from the tumor specimens of radical hysterectomies. Specimens were put in a sample protector solution immediately and then were frozen and stored at − 80 °C as soon as possible. A total of 38 normal cervical tissues, 52 CIN tissues and 30 cervical squamous carcinoma tissues were collected. The status of all specimens included in the study was confirmed by pathology diagnosis.Total RNA was extracted from tissues by TRIzol. The RNA concentration was 800–1500 ng/μl, and the optical density value (OD) was 1.7–2.0. One hundred nanograms of total RNA was reverse transcribed to generate cDNA. RT-qPCR was performed using a SYBR Green dye method. RT-qPCR reaction conditions were as follows: 95 °C 30 s for 1 cycle, 95 °C 5 s, 60 °C 30 s for 10 cycles, 95 °C 30 s for 1 cycle, and 95 °C 5 s, 60 ° 30 s for 40 cycles. The experiments were repeated 3 times. An absolute quantitative method was used for the experiments. The following formula was used to calculate expression: copies of target genes/copies of reference genes. β-actin served as the reference gene. The sequences of primers were showed in Table 1.P-value less than 0.05 was considered to be significantly different.SPSS 22.0 software was used to perform statistical analysis. The data are expressed as the mean ± standard deviation, and the group rank sum test was used for comparisons between groups. Chi-square tests were used for comparisons between classification data groups. Multivariate analysis uses binary logistic regression. A The randomForest package of Rstudio software was used to establish random forest models. The random numbers were generated by the seed.set function. Of the cases, 50% (60 cases) were randomly selected as the training set, and 50% (60 cases) were used as the test set. Using importance to evaluate the weight of each variable in the model, the mean decreased accuracy indicated a decrease in accuracy after variable substitution, and the mean decreased Gini indicated a decrease in the Gini coefficient after variable substitution. The larger the value was, the more important the variable was. The overall error of the model was evaluated by out-of-bag error (OOB error). The diagnostic effect of the model was evaluated by AUC and accuracy.Genemania was used to build a gene network and explore the interactions between genes Fig. . In the A total of 120 cases were used in this study: 38 normal cervix cases, 52 cases of CIN and 30 cases of SCC. The clinical characteristics of the cases were as follows.P = 0.000) and had more parity (P = 0.017), and the percentage of premenopausal cases (P = 0.000) were significantly higher. The expression levels of TGFBR2, FOXO1, CSKN1A1, PRKCI, and CTBP2 in CIN and SCC tissue samples were significantly different. The expression levels of TGFBR2, CSKN1A1, PRKCI, and CTBP2 were significantly upregulated in the SCC group, while FOXO1 was expressed at significantly lower levels in the SCC group  and TCT-diagnosed CINII+ (P = 0.000) was significantly higher than that of the normal group. FOXO1 expression levels were significantly higher in the CIN group, while TGFBR2 and CTBP2 were significantly lower in the CIN group  Table  and 6. TModels were assessed according to the accuracy rate, AUC and OOB error value of each. Among the 7 models predicting CIN progression, model 3 had the highest accuracy rate and the largest AUC, while the OOB error value was relatively small; therefore, model 3 was selected as the model for CIN progression Fig. . Model 1Currently, there are a large number of studies from across the world studying genes and biomarkers related to CIN progression and occurrence. However, the majority of studies report on single genes or single biomarkers that are associated with CIN, and only a few studies have combined multiple factors to predict CIN progression and occurrence. Mei Sze Tan et al.  screenedThe HPV infection pathway summarizes the mechanism of HPV infection and the carcinogenic process. The HPV infection pathway includes 11 subpathways: the Wnt signaling pathway, mTOR signaling pathway, apoptosis pathway, NFKB signaling pathway, P53 signaling pathway, JAK/STAT signaling pathway, Notch signaling pathway, PI3K/Akt signaling pathway, Toll-like receptor signaling pathway, focal adhesion pathway and antigen processing and presentation pathway. In this study, FOXO1, CSKN1A1 and CTBP2 were significantly differentially expressed genes located in the HPV infection pathway. Among them, the significant genes CSKN1A1 and CTBP2 were located in the Wnt signaling pathway. HPV E6 can activate the Wnt signaling pathway, thereby causing immortalization of cervical epithelial cells . In addiThe main function of the Hippo signaling pathway is to control the normal size of organs. In the process of cervical carcinogenesis, the expression of the core gene of this pathway, YAP, is upregulated with the progression of cervical lesions . ExcessiIn this study, the proportion of premenopausal cases of CIN was significantly higher than that of SCC cases, and logistic analysis found that premenopause was one of the independent risk factors for the progression of CIN. Chen et al.  studied Compared to CIN patients, the average age of SCC patients was greater, and the parity was significantly more than that of the CIN cases. For women younger than 25 years old, regardless of the level of cervical lesions, the rate of spontaneous regression was 1.4 times higher than that of women older than 50 years old . ChristiCompared to patients in the normal cervical group, the proportions of HPV positivity and CINII+ TCT results in CIN cases were significantly higher than they were in the normal cervical group. In model 12, the TCT results had a large impact on the results. This shows that TCT examination played an important role in the diagnosis of CIN. HPV and TCT play an important role in diagnosing CIN and identifying CIN and SCC. Although the results of TCT will cause false negatives due to the different methods of the operators, the accuracy of TCT in the diagnosis of cervical diseases has been significantly improved compared to traditional cervical smears . Among HThe random forest model consists of multiple decision trees, and there is no correlation between decision trees. When a new input sample enters, it will be judged by each decision tree. The random forest model is capable of preventing fitting, has low requirements of the data set, and has strong adaptability, making it suitable for nonlinear data. In this study, a random forest algorithm was used to build random forest models. Then, we choose the best models according to the accuracy, AUC value and OOB error value.Regarding the random forest models of CIN progression, model 3 had the highest accuracy and AUC value, and the OOB error value was relatively small. Therefore, model 3 was chosen as the predictive model for CIN progression. In model 3, CSNK1A1 and PRKCI had a great impact on the result. Moreover, these two genes were also significantly differentially expressed genes during the progression of CIN. In the HPV infection signaling pathway, CSNK1A1 can cause cell polarity loss through the action of HPVE6. However, there is no research on the expression of CSNK1A1 and cervical diseases. Most of the research on CSNK1A1 focuses on hematological malignancies. Overexpression of CSNK1A1 can promote the proliferation and survival of tumor cells by downregulating the expression of CTNNB1 in myeloma ; CSNK1A1For the random forest model of CIN occurrence, the accuracy rate and AUC value of model 12 are the largest, and the OOB error value is the smallest. Therefore, model 12 was chosen as a predictive model for the occurrence of CIN. CTBP2 has the largest impact on the model 12. CTBP2 is in the classic Wnt/β-catenin signaling pathway, which is one of the subpathways of the HPV infection signaling pathway; however, the role of CTBP2 in the HPV infection signaling pathway is unknown. In this study, the expression of CTBP2 in normal cervical tissue was higher than it was in CIN tissue. Surprisingly, compared with normal cervical tissue, SCC tissue expresses CTBP2 at much higher levels. Overexpression of CTBP2 might be linked to the progression of CIN. CTBP2 has not yet been reported in cervical diseases, but some studies have found that CTBP2 is associated with a variety of solid tumors. CTBP2 is overexpressed in non-small cell lung cancer and promotes tumor cell invasion and proliferation through the classic Wnt/β-catenin signaling pathway . AdditioTGFBR2 and FOXO1 were two other significant genes that might be related to the occurrence and progression of CIN. Among the tested models, model 3 incorporates TGFBR2 and FOXO1, and model 12 incorporates FOXO1. These two genes influence the progression and occurrence of CIN. There are few reports on the correlation between TGFBR2 and cervical diseases. Cai et al.  pointed FOXO1 plays an important role in the occurrence and progression of CIN. FOXO1 is considered to be a tumor suppressor gene. Overexpression of FOXO1 in vitro can inhibit the growth and proliferation of cervical cancer cells. Moreover, the prognosis of cervical cancer with FOXO1 overexpression is more satisfactory . In contThis study has some limitations. First, this is a single-center retrospective analysis with a small sample size. Second, there are some errors in the experimental results. In the future, it will be necessary to expand the sample size and improve the experimental methods to fully assess risk factors related to the occurrence and progression of CIN.In summary, the high expression of PRKCI and CSKN1A1 and premenopause are independent risk factors for the progression of CIN to SCC. Meanwhile, a random forest method combining clinical features and significantly differentially expressed genes predicted the occurrence and progression:n of CIN. For patients who are premenopausal, are older, have CINII+ results from TCT, have high parity, have high expression of TGFBR2, CSKN1A1, PRKCI, and CTBP2, and exhibit low expression of FOXO1, more attention should be paid to CIN progression. For women with HPV infection, CINII+ results from TCT, high FOXO1 expression and low CTBP2 expression, it is necessary to be vigilant regarding the occurrence of CIN.Additional file 1: Table S1. Sequences of primers. Additional file 2.Additional file 3.


Vitamin C (ascorbic acid) is a nutrient used to treat cardiovascular disease (CVD). However, the pharmacological targets of vitamin C and the mechanisms underlying the therapeutic effects of vitamin C on CVD remain to be elucidated. In this study, we used network pharmacology approach to investigate the pharmacological mechanisms of vitamin C for the treatment of CVD. The core targets, major hubs, enriched biological processes, and key signaling pathways were identified. A protein-protein interaction network and an interaction diagram of core target-related pathways were constructed. Three core targets were identified, including phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform, signal transducer and activator of transcription-3 (STAT3), and prothrombin. The GO and KEGG analyses identified top 20 enriched biological processes and signaling pathways involved in the therapeutic effects of vitamin C on CVD. The JAK-STAT, STAT, PD1, EGFR, FoxO, and chemokines signaling pathways may be highly involved in the protective effects of vitamin C against CVD. In conclusion, our bioinformatics analyses provided evidence on the possible therapeutic mechanisms of vitamin C in CVD treatment, which may contribute to the development of novel drugs for CVD. Cardiovascular disease (CVD) is a leading cause of death worldwide, accounting for 205 deaths per 100,000 persons . It reprVitamin C (ascorbic acid) is a nutrient with radical scavenger activity and antioxidant effects . ObservaThe antioxidant property of vitamin C contributes to the prevention and treatment of cardiovascular disorders . HoweverIn the present study, we investigated the molecular mechanisms underlying the protective effects of vitamin C against CVD by using network pharmacology approach. Our bioinformatics data may contribute to the development of new treatments for CVD for both clinical and basic investigators.http://www.swisstargetprediction.ch), DrugBank (http://www.drugbank.ca/) database, and Traditional Chinese Medicine Systems Pharmacology  were used to obtain all known targets of vitamin C. The therapeutic targets for CVD were collected using DrugBank database, Online Mendelian Inheritance (OMIM) (http://www.omim.org/) database, and GeneCards (www.genecards.org/) database. Then the targets of vitamin C with therapeutic potential for CVD were identified after eliminating duplicates.Swiss Target Prediction  network and to obtain general data (tsv.). Protein interactions with a confidence score of >0.9 were selected. General data were imported into Cytoscape (v3.7.1) to rebuild a PPI network of vitamin C against CVD. The network analyzer in Cytoscape was used to analyze the topological parameters, including mean and maximum degrees of freedom in the PPI network. The upper limit of the screening range was the maximum degree value in the topological data, while the lower limit was twice the average degree of freedom . The corp < 0.05.The R packages of ClusterProfiler, enrichplot, and ggplot2 were used for Gene Ontology (GO) Biological Function (BP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the core targets. The cut-off value was set as Cytoscape (v3.7.1) software was used for network visualization of the targets of vitamin C against CVD. An interaction diagram of core target-related GO/KEGG enrichment was generated . The stuA total of 339 known target genes of vitamin C and 802 known therapeutic targets for CVD were obtained . The VenCytoscape was used to calculate the topological parameters of the interaction network of 66 identified targets . The minThe GO BP and KEGG pathway enrichment analyses of three core targets were performed using R language. The enriched biological functions included regulation of energy homeostasis, acute-phase response, regulation of multicellular organism growth, regulation of multicellular organism growth, astrocyte differentiation, negative regulation of autophagy, positive regulation of phosphatidylinositol 3-kinase signaling, positive regulation of receptor signaling pathway via JAK-STAT, positive regulation of receptor signaling pathway via STAT, acute inflammatory response, regulation of phosphatidylinositol 3-kinase signaling, regulation of receptor signaling pathway via JAK-STAT, multicellular organism growth, regulation of receptor signaling pathway via STAT, phosphatidylinositol 3-kinase signaling, platelet activation, regulation of generation of precursor metabolites and energy, receptor signaling pathway via JAK-STAT, receptor signaling pathway via STAT, phosphatidylinositol-mediated signaling, and inositol lipid-mediated signaling . The enrThe network of the core targets of vitamin C with therapeutic potential for CVD and the interaction diagram of the core target-related pathways were constructed .Oxidative stress and inflammation play a crucial role in the onset and progression of atherosclerosis and the development of cardiovascular events . InflammPrevious studies have extensively reported the beneficial effects of vitamin C on CVD. However, large RCTs did not identify any benefit of vitamin C (and E) intake on CVD . FurtherIn agreement with GO analysis, KEGG pathway enrichment analysis also showed that the therapeutic effects of vitamin C on CVD were mainly associated with the JAK-STAT signaling pathway, as well as the PD-1 pathway, EGFR tyrosine kinase inhibitor resistance, the FoxO signaling pathway, and the chemokines signaling pathway . There iKEGG pathway enrichment showed that the chemokines signaling pathway was implicated in the therapeutic effects of vitamin C against CVD. The secreted chemokines cause epidermal damage by attracting proinflammatory immunocytes . The rolIn summary, we identified three core targets  of vitamin C with therapeutic potential for CVD and showed that the protective effects of vitamin C on CVD were attributed to its anti-inflammation property. The most enriched pathways were the JAK-STAT, PD-1, EGFR, FoxO, and chemokines signaling pathways. Our findings may guide further pharmacological investigations on the therapeutic effects of vitamin C on CVD and the discovery of new drugs for CVD treatment.There are some limitations to the current study. First, the targets of vitamin C with therapeutic potential for CVD were collected using public databases, which may lead to inaccurate results. Second, the core targets identified in the current study need to be further validated. Third, as CVD is a complex process involving different types of diseases, the roles of these targets and pathways in specific pathological conditions need to be evaluated in both basic scientific and clinical studies.The original contributions presented in the study are included in the article/NZ: designed, drafted, and revised the manuscript. BWH: performed the research and wrote the manuscript. WBJ: collected and analyzed the data. All the authors read and approved the final manuscript.This research was supported by Natural Science Foundation of Zhejiang Province (No. LQ20H020011).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.


The variable mechanisms on additive and synergistic effects of jasminoidin (JA)-Baicalin (BA) combination and JA-ursodeoxycholic acid (UA) combination in treating cerebral ischemia are not completely understood. In this study, we explored the differential pure mechanisms of additive and synergistic effects based on pathway analysis that excluded ineffective interference.The MCAO mice were divided into eight groups: sham, vehicle, BA, JA, UA, Concha Margaritifera (CM), BA-JA combination (BJ), and JA-UA combination (JU). The additive and synergistic effects of combination groups were identified by cerebral infarct volume calculation. The differentially expressed genes based on a microarray chip containing 16,463 oligoclones were uploaded to GeneGo MetaCore software for pathway analyses and function catalogue. The comparison of specific pathways and functions crosstalk between different groups were analyzed to reveal the underlying additive and synergistic pharmacological variations.Additive BJ and synergistic JU were more effective than monotherapies of BA, JA, and UA, while CM was ineffective. Compared with monotherapies, 43 pathways and six functions were found uniquely in BJ group, with 33 pathways and three functions in JU group. We found six overlapping pathways and six overlapping functions between BJ and JU groups, which mainly involved central nervous system development. Thirty-seven specific pathways and 10 functions were activated by additive BJ, which were mainly related to cell adhesion and G-protein signaling; and 27 specific pathways and three functions of synergistic JU were associated with regulation of metabolism, DNA damage, and translation. The overlapping and distinct pathways and functions may contribute to different additive and synergistic effects.The divergence pathways of pure additive effect of BJ were mainly related to cell adhesion and G-protein signaling, while the pure synergistic mechanism of JU depended on metabolism, translation and DNA damage. Such a systematic analysis of pathways may provide an important paradigm to reveal the pharmacological mechanisms underlying drug combinations. Stroke, one of the main causes of permanent disability and death worldwide, increased the total disease burden . As ischAlthough several rigorous analysis methods for synergistic drug combinations have been proposed, such as chou-talalay combination index (CI) , and isoIn previous studies, combination of BA and JA (BJ) have been demonstrated to exert an additive effect, while combination of JA and UA (JU) acted synergistically in treating cerebral ischemia . The monAnimal use protocols were reviewed and approved by the Ethics Review Committee for Animal Experimentation, China Academy of Chinese Medical Sciences, and the animal experiments were conducted in accordance with the Prevention of Cruelty to Animals Act 1986 and the National Institute of Health guidelines on the care and use of laboratory animals for experimental procedures. A total of 248 healthy adult male mice from Kunming, 3 months old, weighing 38–48 g, were used in this experiment. A focal cerebral ischemia-reperfusion model was induced after mice were anesthetized with 2% pentobarbital . The middle cerebral artery was occluded with an intraluminal filament for 1.5 h, followed by 24 h of reperfusion. The mice in the sham group proceeded with the same process, but the filament was not inserted. During the experiment, a heating pad was used to maintain the rectal temperature at 370°C–37.5°C. Brain temperature (monitored by 29-gauge thermocouples in the right corpus striatum) was maintained at 36°C–37°C under a temperature-regulating lamp; monitor the blood pressure, blood gas and glucose levels; EGGs were also monitored to ensure isoelectric currents during ischemia. Nine mice from each group were used to calculate the infarct ratio after 24-h reperfusion and the calculation of cerebral infarct volume was as described in our previous studies .Animals were randomly divided into eight groups: Vehicle (0.9% NaCl), Sham (0.9% NaCl), CM , BA , JA , UA , BJ , JU . The herbal preparations were chemically standardized products provided by the China Natural Institute for the Control of Pharmaceutical and Biological Product or Beijing University of Traditional Chinese Medicine, and their composition was validated using fingerprint chromatographic methodologies. The herbal preparations were dissolved with 0.9% NaCl before use, and then injected into the tail vein 1.5 hs after Middle Cerebral Artery Occlusion (MCAO), at a dosage of 2 ml/kg based on body weight .The hippocampus of nine mice in each group was homogenized in TRIzol reagent . According to the single-step method, the total RNA was extracted . RNA wasP value less than 0.05 compared with CM group were identified for further analysis. Moreover, up-regulation or downregulation was indicated by the expression level of an increase >1.5-fold or a decrease <0.5-fold compared with CM group, respectively.Experimental data was uploaded to the ArrayTrack system (U.S. Food and Drug Administration) for analysis through a robust multi-array analysis and standardization process. The results were submitted to the Array Express database. Genes with a via MetaCore software  after the differentially expressed genes were identified. All differentially expressed genes were uploaded and mapped to the GeneGo database. P values were used to measure the significant genes and canonical pathways, which was calculated by Fisher's exact test. A lower p value indicated a higher correlation between the gene and the ontology category. The level of statistical significance was set at P < 0.05, which could screen out all the canonical pathways with a P < 0.05 and a fold change >1.5 for further analysis. We uploaded the list of significantly differentially expressed genes in the BA, JA, UA, BJ, and JU groups into the MetaCore software for functional PA. Pathway enrichment analyses were performed via the MetaCore software . All the enriched pathways were listed in PA was conducted p53 (Santa Cruz), and developed using enhanced chemiluminescence (Amersham). The band density was measured by a GS-700 densitometer (Bio-Rad).The hippocampus was removed from the brains of the nine mice in each group. Proteins (40 μg per lane) were separated by sodium dodecyl sulfate (SDS) polyacrylamide gel electrophoresis and transferred to nitrocellulose membranes  by electroblotting. Membranes were incubated in 5% nonfat milk for 1 h and incubated with antibodies to anti-P < 0.05, ANOVA). Thus, we considered the CM groups as a negative group, and the other groups as positive groups  with negative groups (CM).The combined effect produced by the action of two or more agents, being equal to the sum of their separate effects was referred to additive effect . In ordeBased on the functional annotations, we performed statistics on pathways with well-defined functional classification  plays a central role in the selective degradation of intracellular proteins. Among the key proteins regulated by the proteome include those involved in inflammatory process control, cell cycle regulation, and gene expression. There is now overwhelming data suggesting that UPS can cause cerebral ischemic damage . And yetAll the pathways of BJ and JU were primarily involved in development. For example, Endothelin-1(ET-1)  and DopaBeyond that, signal transduction , immunesInterestingly, we noted that although BJ and JU modulated the same pathways, the targets of the two groups were not completely the same. For example, the IL-8 in angiogenesis signaling, BJ regulated molecules related to cell proliferation and dynamic balance of blood lipids; JU regulated molecules associated with cell immunity. This may partially explain the difference between additive and synergistic effects.As for characteristic mechanisms, the representative pathways only in BJ group were mostly related to cell adhesion and G-protein signaling, and those pathways in JU group were related to regulation of metabolism and DNA damage. For instance, triiodothyronine and thyroxine signaling were only enriched in the JU group; it has been shown that low free thyroxine index is associated with an increased risk for ischemic stroke and low free triiodothyronine levels are related to poor prognosis in acute ischemic stroke, which expressed the importance of metabolism regulation to stroke . Gap junIn summary, after excluding the interference of the negative group, we obtained the pure mechanisms of BJ and JU combinations. Specifically, the difference between BJ and JU was embodied in three aspects: (i) diversity of targeting pathways: BJ mainly focused on cell adhesion and G-protein signaling; while JU mainly involved regulation of metabolism, DNA damage, and translation; (ii) activating different targets in the same pathway; (iii) variation of vertical converge of signaling pathways. Our method to systematic comparison of pathways for the pure mechanisms of different drug combinations may contribute substantially to the interpretation of the precise pharmacological actions of combination therapies.The data generated in this article can be found in Arrayexpress, using the accession number E-TABM-6622.Animal use agreements were reviewed and authorized by the Ethics Review Committee for Animal Experimentation, China Academy of Chinese Medical Sciences, and the animal experiments were conducted in accordance with the Prevention of Cruelty to Animals Act 1986 and the National Institute of Health guidelines for conducting experimental procedures for the care and use of laboratory animals.ZW and JL contributed to the conception or design of the work. PWe drafted the manuscript, and PWa with BL revised the manuscript. HG checked all aspects of this manuscript to ensure that we can contribute.The work was supported by the National Natural Science Foundation of China (Grant No. 81673833 and 81603401&81803966) and the Fundamental Research Funds for Central Public Welfare Research Institutes .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.


Introduction: Impulse control disorders (ICDs) frequently complicate dopamine agonist (DA) therapy in Parkinson's disease (PD). There is growing evidence of a high heritability for ICDs in the general population and in PD. Variants on genes belonging to the reward pathway have been shown to account for part of this heritability. We aimed to identify new pathways associated with ICDs in PD.Methods: Thirty-six Parkinsonian patients on DA therapy with (n = 18) and without ICDs (n = 18) matched on age at PD's onset, and gender was selected to represent the most extreme phenotypes of their category. Exome sequencing was performed, and variants with a strong functional impact in brain-expressed genes were selected. Allele frequencies and their distribution in genes and pathways were analyzed with single variant and SKAT-O tests. The 10 most associated variants, genes, and pathways were retained for replication in the Parkinson's progression markers initiative (PPMI) cohort.Results: None of markers tested passed the significance threshold adjusted for multiple comparisons. However, the “Adenylate cyclase activating” pathway, one of the top associated pathways in the discovery data set (p = 1.6 × 10−3) was replicated in the PPMI cohort and was significantly associated with ICDs in a post hoc pooled analysis . Two of the 10 most associated variants belonged to genes implicated in cAMP and ERK signaling  although non-significant after Bonferroni correction.Conclusion: Our results suggest that genes implicated in the signaling pathways linked to G protein-coupled receptors participate to genetic susceptibility to ICDs in PD. Impulse control disorders (ICDs) and related behaviors are defined by the failure to resist an impulse to perform a self-rewarding act that will cause longer-term harm to oneself or others. Their prevalence is estimated between 1 and 3% in the general population while it raised up to 17% in treated Parkinsonian patients . Common PRKN mutations  or without (n = 132) ICDs or related behaviors. Common inclusion criteria were diagnosis of PD according to the UK Parkinson's Disease Society brain bank  conducted in France between 2012 and 2015 in 13 centers of the clinical research network for Parkinson's disease (NS-PARK/FCRIN) . Three hain bank  and age ain bank . This scain bank . The stuLRRK2 gene and for pathogenic mutations on PRKN gene.For this ancillary study, we selected an extreme phenotype (EP) population corresponding to 36 cases: 18 PD patients with ICDs (cases) and 18 PD patients without ICDs (controls). Cases were selected in descending order of behavioral scale in PD's scores. The five following items were considered: eating behavior, creativity, compulsive shopping, pathological gambling, and hypersexuality. Controls were selected considering the same items if scoring 0 in all of them. Cases and controls were matched for gender and age at PD onset and had been treated with ropinirole or pramipexole, the two major dopamine agonists used in this cohort. When several controls were available for matching, the patient exposed to the highest dose of DA was selected. Finally, as mutations or risk genetic variants have been shown to be associated with neuropsychiatric symptoms in PD patients , 25, pathttps://www.michaeljfox.org/ppmi-clinical-study, data downloaded on April 20, 2016), selecting cases and controls with similar criteria than for the hypothesis-generation cohort. In this cohort, ICD behaviors were screened by using the Questionnaire for Impulsive-Compulsive Disorders in Parkinson's disease (QUIP)  during follow-up (n = 52) while treating with pramipexole or ropinirole (n = 45) with a QUIP = 0 at baseline (n = 30) and available exome sequencing data (n = 27). For controls, we selected patients with QUIP scores remaining null throughout the follow-up (n = 127) treated with ropinirole or pramipexole (n = 107) with a dose > 290 mg LEDD for more than 3 months (n = 29) and exome sequencing data available (n = 28). The 10 most associated genetic variants, genes, and pathways were selected for replication using the whole exome sequencing data.For replication, we used the Parkinson's progression markers initiative (PPMI) data set (e (QUIP)  at each Exomes from the 36 selected patients were sequenced on an Illumina NextSeq 500 with the MedExome kit, and the resulting reads were aligned to the hg19 reference genome with BWA applying duplicate removal with Picard Tools MarkedDuplicates. We performed GATK base quality score recalibration, indel realignment, and SNP and INDEL discovery and genotyping across all samples simultaneously using HaplotypeCaller, followed by variant quality score recalibration according to the GATK Best Practices recommendation: GATK-HaplotypeCaller primary QC was applied at the variant level, excluding any variants that were not flagged as “PASS” by the VQSR algorithm, thus excluding variants outside the 95% sensitivity tranches . Finally, variants were annotated using the SnpEff tool and GENome MINing software  .For all 36 samples, mean coverage on target was above 84, and 90% of targeted regions were covered at least at 30X.http://www.braineac.org). Variants with a CADD score ≥ 12.37 were kept for further analysis, according to published recommendations  software.Genetic variants were filtered to keep variants likely to have a functional impact based on the Combined Annotation Dependent Depletion (CADD) score  as made ndations , if also−6, 1 × 10−5, and 4.1 × 10−4, respectively.Association of single variants with the case/control status was tested using the likelihood ratio test as made available in the Efficient and Parallelizable Association Container Toolbox, version 3.2.6 (EPACTS). Group-wise tests were conducted using SKAT-O tests as made available in EPACTS on both genes and Reactome pathways , 31. Thep-values were obtained using the Fisher test when SKAT-O p-values were found to be nominally significant in both EP and PPMI cohorts. P-values were considered as significant when passing the Bonferroni-corrected significance threshold considering the number of tests run during the discovery and replication phases . Tests were adjusted on age at PD diagnosis and gender.For the replication stage, combined n = 18; controls, n = 18) are described in p = 5 × 10−3). DA doses were significantly higher in control subjects  due to the study design (controls were recruited based on the absence of ICD behaviors despite high doses of DA). Among the cases, all had at least two different ICDs, five patients had a maximum score of 4 for at least one item, and eight patients accumulated at least two types of ICDs with a score equal to 3. There was no difference in ropinirole/pramipexole or gender distributions regarding to the type of ICDs except for hypersexuality, which was exclusively present in males  were involved in intracellular signal transduction, related to ERK, and cAMP signaling pathways. Three variants were laid on genes belonging to the pathway of focal adhesion . No mutation was found in the LRRK2 or PRKN genes.After quality controls, 354,174 variants were available for further analyses. Among the 34,981 with a CADD-score ≥ 12.37, 26,418 satisfied the condition of a minimal occurrence of 4 in the cohort for the single test. After selection upon brain expression of genes, 6,953 variants remained for further analyses. The 10 most associated variants are shown in DOCK4, RasGRF2, ITGA6, and ITGA11, were linked to the ERK pathway. PDE2A belongs to cAMP signaling. For some genes, such as PDE2A and RasGRF2, association was led by only one frequent variant, which was strongly associated in the single test. For others, as for DOCK4 and MYH14, association resulted from different rare variants laying in this gene in different individuals of the cohort  was related to focal adhesions with a total of eight variants  tested. The second most associated pathway was the adenylate activating pathway  with a total of 29 (10 of which were unique) variants tested distributed on eight genes.Of the 1,816 pathways extracted from the Reactome database, 1,130 were represented by at least two variants with a CADD score ≥ 12.37. Among them, only 312 had more than 95% of their genes expressed in the brain's regions of interest, and the 123 that had more than 80% of their genes represented by at least one variant were considered for further analysis. The five most associated pathways using SKAT-O are shown in −6, 1 × 10−5, and 4.1 × 10−4 for a single test, SKAT-O on genes and pathways, respectively), in the discovery phase only.None of the variants, genes, or pathways tested passed the significance threshold adjusted with Bonferroni's method (significance threshold of 7.2 × 10p < 0.001).The replication data set consisted of 59 patients (27 cases and 28 controls). Mean age at PD diagnosis was 58 years old in both groups. There were seven women in the cases and seven in the controls. Pramipexole was the most frequent DA in each group: 60 and 76% in cases and controls, respectively. Doses of DA were significantly higher in controls than in cases . Twenty-nine variants were tested in the EP and PPMI cohorts , the effect was observed in the same direction in both cohorts.We applied the same analysis for the 10 most associated variants, genes, and pathways. Only the “adenylate cyclase activating pathway” replicated in the PPMI cohort , regulating adenylate cyclase activity. D2-like receptors inhibit adenylyl cyclase, whereas stimulation of D1-like receptors leads to its activation through Galpha(olf) in the striatum . Cyclic-Interestingly, although below the significance threshold, many of the most associated variants or genes tested were linked to the cAMP and ERK-dependent pathways.PDCD6IP gene, also named DRIP4 for dopamine receptor interacting protein 4. This gene encodes a protein that has been shown to upregulate D1 and D3 receptor expression (The most associated variant in our study was a missense variant (rs3203777) in the pression .rs1877652 variant, enriched in patients with ICDs, is an intronic variant of the PDE2A gene encoding the phosphodiesterase 2A controlling cAMP rates and is shown to play a key role in the modulation of the signal induced by dopamine in rodents (RasGRF2 (rs34193571), previously associated with alcohol addiction  while the rs3743398, a variant lying on the ACAN gene belonging to the aggrecan family, was found more frequently in controls, suggesting a protective role. The most associated pathway in the EP cohort was related to the integrin system although it was not replicated in the PPMI cohort.Several top associated variants, genes, and pathways were related to integrin systems, which also act on ERK signaling via downstream transducers, including the focal adhesion kinase, FAK. Integrin and its downstream effectors have been shown to be involved in structural changes that occurred in the dendritic tree within the addiction to alcohol  or cocaiNone of these variants was previously found to be associated with ICDs in PD or in the general population. However, most previous studies focused on candidate gene coding receptors, transporters, or metabolism enzymes of the reward pathway but did not investigate their downstream signaling effectors –14.p-values obtained were far from reaching the adjustment for the multiple comparison threshold of significance. The lack of replicated results might also be due to differences between the two cohorts in terms of exome sequencing coverage or phenotypic definition of ICDs in the two cohorts. The selection of extreme cases strongly associated with DA-induced ICDs might have biased our results toward genes directly interacting with these drugs, which was the purpose of the design of the study. Our results also suggest that genetic susceptibility to ICDs in PD would rather result from the combination of multigenic variations than unique rare variants with strong effects, which was already suggested for ICDs in the general population , and our results deserve further replication in larger cohorts. The underpowered analysis may explain that only one pathway was replicated and that most of the pulation .This study highlights the potential important role of enrichment of functional variants in genes coding proteins of intracellular signaling cascades beyond neurotransmitter receptors in the genetic susceptibility of ICDs. Subjects with stronger signal transduction of GPCRs might be at higher risk to develop ICDs when exposed to dopaminergic therapy in PD. How these pathways interfere with drugs or increase the individual susceptibility to ICDs remain to be explored. The combination of clinical, neuroimaging, and exome sequencing data focused on the study of the polymorphism of the different pathways could help in providing some predictability, in the future, for ICDs in PD patients.jean-christophe.corvol@aphp.fr).Data are available upon request to any interested researcher or for the purpose of replicating our results (direct requests to The studies involving human participants were reviewed and approved by CPP Paris VI. The patients/participants provided their written informed consent to participate in this study.J-CC, FD, and SP contributed to the design of the work, data acquisition, interpretation of the data, and draft the manuscript. AR, HB, JG, and YM participated to data analysis. All authors contributed to the interpretation of the data, revised the manuscript for important intellectual content, provide approval for the publication, and agree to be accountable for all aspects of the work.J-CC has served on advisory boards for Air Liquide, Biogen, Denali, Ever Pharma, Idorsia, Prevail Therapeutic, Theranexus; and received grants from Ipsen, the Michael J Fox Foundation, and Sanofi. MA received honoraria and travel grants from Johnson and Johnson, Actelion Pharmaceuticals, Teva, LVL, Aguettant, Orkyn, AbbVie. The remaining 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.


Polycystic ovary syndrome (PCOS) is the most common female endocrine disease. Cangfu Daotan Decoction (CDD) can effectively relieve the clinical symptoms of PCOS patients.  To explore the active ingredients and related pathways of CDD for treating PCOS, a network pharmacology-based analysis was carried out. The active ingredients of CDD and their potential targets were obtained from the TCM system pharmacology analysis platform. The obtained PCOS-related genes from OMIM and GeneCards were imported to establish protein-protein interaction networks in STRING. Finally, GO analysis and significant pathway analysis were conducted with the RStudio (Bioconductor) database.  A total of 111 active compounds were obtained from 1433 ingredients present in the CDD, related to 118 protein targets. In addition, 736 genes were found to be closely related to PCOS, of which 44 overlapped with CDD and were thus considered therapeutically relevant. Pathway enrichment analysis identified the AGE-RAGE signalling pathway in diabetic complications, endocrine resistance, the IL-17 signalling pathway, the prolactin signalling pathway, and the HIF-1 signalling pathway. Moreover, PI3K-Akt, insulin resistance, Toll-like receptor, MAPK, and AGE-RAGE were related to PCOS and treatment.  CDD can effectively improve the symptoms of PCOS, and our network pharmacological analysis lays the foundation for future clinical research. Polycystic ovary syndrome (PCOS) is the most common endocrine disease in women and is characterized by abnormal adrenal and ovarian androgen secretion, ovulatory dysfunction, menstrual irregularity, acne , and polIn the past few decades, oral contraceptive pills (OCPs) have been widely used in PCOS patients to regulate their menstrual cycles and reduce hyperandrogenism . ClomiphAtractylodes lancea (Thunb.) Dc (Cangzhu), Cyperi Rhizoma (Xiangfu), Arisaematis Rhizoma (Dannanxing), Arum ternatum Thunb (Banxia), Zingiber officinale Roscoe (Shengjiang), Citrus reticulata (Chenpi), Aurantii Fructus (Zhike), Poria cocos (Schw.) Wolf (Fuling), and Licorice (Gancao) and is one of the most common prescriptions for phlegm and dampness-type PCOS patients [There is no specific Chinese medical term referring to “PCOS” in the ancient books of Chinese medicine. According to the clinical characteristics of PCOS, it is attributed to the category of irregular menstruation, infertility, obesity, etc. For thousands of years, TCM has been used to treat menstrual disorders, infertility, and obesity. There are a number of herbal formulas in treating the above diseases. A study showed that herbal medicine administration significantly relieved some of the symptoms of PCOS . Specifipatients . Anotherpatients . AlthougTherefore, it is necessary to clarify the biological basis and molecular nature of the TCM decoction. Network pharmacology has recently been developed as a new strategy and technique for elucidating complex pharmacological problems for new drug discovery . In receTCM decoctions have complex ingredients and multiple targets, and network pharmacology can predict novel compound targets and the potential pathways of action based on existing TCM decoctions and has helped clarify the mechanism of several TCM decoctions so far –23.In this study, we used the network pharmacology approach to explore the potential mechanism of action of CDD in treating PCOS. We first filtered the TCMSP database for active compounds of CDD and identified the targets, followed by mining for disease-related genes and network analysis of those genes .http://tcmspw.com/tcmsp.php) [To screen the active ingredients of CDD, we used the TCMSP database (msp.php) . TCMSP imsp.php) .CDD active ingredients were filtered mainly on the basis of oral bioavailability (OB), Caco-2 permeability (Caco-2), and drug-likeness (DL). OB, Caco-2, and DL are the three most key indicators of pharmacology. Specifically, the ingredients contained in the CDD meeting the criteria of OB ≥ 30%, Caco-2 ≥ 0.4, and DL ≥ 0.18 were chosen as candidate ingredients for further analysis.OB refers to the percentage and rate of the release and absorption of active ingredients into the systemic blood circulation and is an important pharmacokinetic index of oral drugs . It is aIn this study, OB ≥ 30%, DL ≥ 0.18, and Caco-2 ≥ 0.4 were regarded as a threshold for filtering possible candidate drugs.http://www.uniprot.org).We chose the TCMSP database as the main source of component-target data and obtained the target protein names of each herb in CDD. Only the proteins that had interactions with the bioactive components in CDD we had already obtained were selected. Then, we converted the target protein names of the bioactive components of CDD into gene names with the species limited into “Homo sapiens” with the UniProt Knowledgebase , which is a searchable, integrative database that predicts human genes. The knowledgebase automatically integrates gene-centric data from ∼150 web sources, including genomic, transcriptomic, proteomic, genetic, clinical, and functional information [https://omim.org/, updated on November 15, 2019), which is a comprehensive, authoritative, and timely knowledgebase of human genes and genetic disorders in the human genome. We searched the OMIM database with the keyword “PCOS.”We collected PCOS targets from two sources. One is the GeneCards database . We set the organism type to “Homo sapiens” and left the default settings in place for the other parameters. Then, we exported the downloaded “string_interactions.tsv” file and imported it into Cytoscape 3.7.2 to obtain the PPI network and perform network analysis. In the network, nodes represent the target proteins, and edges represent the interaction between proteins.To illustrate the possible interaction between PCOS-related targets and the potential targets of CDD, we intersected the potential targets of CDD and PCOS-related drug targets and obtained the intersecting targets with RStudio 3.6.1 (Venn Diagram). The overlapping target proteins of PCOS and CDD were used to construct a protein-protein interaction (PPI) network with multiple protein patterns on the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) platform .Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis are important methods used to describe the characteristics of candidate targets. We selected the standard Atractylodes lancea (Thunb.) Dc, 104 ingredients in Cyperi Rhizoma, 123 ingredients in Arisaematis Rhizoma, 116 ingredients in Arum ternatum Thunb., 265 ingredients in Zingiber officinale Roscoe, 63 ingredients in Citrus reticulata, 17 ingredients in Aurantii Fructus, 34 ingredients in Poria cocos (Schw.) Wolf, and 280 ingredients in Licorice. 122 ingredients passed the filters of OB ≥ 30%, DL ≥ 0.18, and Caco-2 ≥ 0.4. The pharmacokinetic properties of the compounds are shown in A total of 1051 chemical ingredients of the nine herb medicines in CFDT were retrieved from TCMSP, including 49 ingredients in A total of 1433 potential targets from the 111 ingredients were retrieved from the TCMSP database . After ehttps://www.genecards.org/) and the OMIM database (https://omim.org/).Research has shown that PCOS is a genetic predisposing, complex polygenic, multifactorial disorder , 31. In Among the above 736 PCOS-related targets, CDD shared 44 common targets with PCOS . The 44 In our network, the degree of the greenness of the nodes is high, and the numbers of edges of the nodes are 37 for AKT1; 32 for IL-6; 29 for VEGFA; 28 for CCND1, STAT3, MAPK1, and MAPK8; 27 for ESR1; 26 for FN1; 25 for MMP9, CXCL8, and MAPK14; 23 for AR; and 22 for PPARG and HIF1A. These results demonstrate that these targets are closely related to others in the network and consequently may play key roles in PCOS.AKTs have been confirmed to play an important role in granulosa-lutein cell (GC) proliferation, and there is reciprocal feedback between AKT and androgen. This study showed that the high expression of AKT1 and AKT2 may cause GC dysfunction in PCOS patients through a possible relation with androgen . ElevateThe MAPK signalling pathway is one of the most important signal transduction pathways in organisms and mediates physiological and pathological processes, such as the growth, development, and differentiation of organisms. Studies have shown that the MAPK signalling pathway plays an important role in the proliferation of ovarian granulosa cells , 36.Research confirmed that PPARG rs709154 and ESR1 rs1999805 are significantly associated with PCOS risk in a Chinese population . MMP9 maThe Merge function of Cytoscape 3.7.2 software was used to combine the Drug-Mol-Gene target network and the PCOS-Drug-Gene interaction network. The results showed that 111 compounds all together play a role in treating PCOS in the composite . The tarTo further illuminate the biological effects involved in the treatment of PCOS with CDD, we performed GO analysis of the 44 PCOS-related putative potential therapeutic target genes. GO annotation and enrichment of the genes encoding CDD were conducted from three aspects: molecular function (MF), biological process (BP), and cellular composition (CC). The most enriched terms in GO analysis are shown in Figures 6In detail, the top 18 terms in the GO BP category were mainly enriched in the regulation of developmental growth, reproductive system development, response to steroid hormone, epithelial cell proliferation, gland development, regulation of epithelial cell proliferation, transcription initiation from RNA polymerase II promoter, female pregnancy, multi-multicellular organism process, DNA-templated transcription, initiation, muscle cell proliferation, ossification, regulation of DNA-binding transcription factor activity, response to radiation, ameboidal-type cell migration, autophagy, and process utilizing autophagic mechanism .The top 19 terms in the GO CC category were mainly enriched in nuclear chromatin, secretory granule lumen, cytoplasmic vesicle lumen, vesicle lumen, extracellular matrix, nuclear chromosome part, chromatin, glutamatergic synapse, platelet alpha granule lumen, platelet alpha granule, RNA polymerase II transcription factor complex, nuclear transcription factor complex, transcription factor complex, postsynaptic density, receptor complex, asymmetric synapse, neuron to neuron synapse, postsynaptic specialization, and basement membrane .The top 19 terms in the GO MF category were mainly enriched in RNA polymerase II proximal promoter sequence-specific DNA binding, proximal promoter sequence-specific DNA binding, nuclear receptor activity, transcription factor activity, direct ligand regulated sequence-specific DNA binding, steroid hormone receptor activity, protein heterodimerization activity, receptor regulator activity, nuclear hormone receptor binding, hormone receptor binding, phosphatase binding, cytokine receptor binding, receptor ligand activity, chromatin binding, steroid binding, protein phosphatase binding, growth factor activity, cytokine activity, protein serine/threonine kinase activity, DNA-binding transcription activator activity, RNA polymerase II-specific, transcription coregulator activity, and RNA polymerase II transcription factor binding .p value < 0.05 were considered significant.To clarify the biological actions of these targets, we performed KEGG analysis and pathway enrichment analysis with the RStudio (Bioconductor) database. We listed the genes of major PCOS putative therapeutic targets and imported them into RStudio to generate relevant pathways that might have an important influence on the biological process of CDD in treating PCOS. Pathways with an adjusted p values of the related genes. The colour from blue to red reflects the adjusted p values from large to small, and the node size and bar length indicate the number of related genes. The histogram and bubble chart were separately arranged according to the p value and the number of related genes. According to the p value, the AGE-RAGE signalling pathway in diabetic complications, Kaposi sarcoma-associated herpesvirus infection, proteoglycans in cancer, endocrine resistance, hepatitis B, the IL-17 signalling pathway, prostate cancer, the prolactin signalling pathway, human cytomegalovirus infection, pancreatic cancer, the HIF-1 signalling pathway, and EGFR tyrosine kinase inhibitor resistance were within the top 12 terms. According to the number of related genes, Kaposi sarcoma-associated herpesvirus infection, proteoglycans in cancer, the PI3K-Akt signalling pathway, the AGE-RAGE signalling pathway in diabetic complications, human cytomegalovirus infection, hepatitis B, endocrine resistance, the IL-17 signalling pathway, prostate cancer, the HIF-1 signalling pathway, Epstein–Barr virus infection, and the prolactin signalling pathway were in the top 12 terms. The overlapping terms of the above lists included the AGE-RAGE signalling pathway in diabetic complications, endocrine resistance, the IL-17 signalling pathway, the prolactin signalling pathway, and the HIF-1 signalling pathway.A total of 123 signalling pathways were significantly enriched through pathway enrichment analysis. In the histogram and bubble diagram , the colα, and a variety of inflammation-related genes, including VEGF, tissue factor, and RAGE [AGE-RAGE signalling may activate multiple intracellular signalling pathways involving protein kinase C and MAPKs and may influence NF-κB activity. Research has shown an association between PCOS and chronic inflammatory factors, proinflammatory cytokines such as interleukin-1, interleukin-6, interleukin-17 –43, and and RAGE , 45.Prolactin (PRL) is involved in a variety of biological functions, including osmotic regulation, reproduction, lactation, endocrinology and metabolism, growth and development, and immunomodulation. It is a polypeptide hormone secreted by the pituitary gland that regulates the female reproductive and endocrine system by activating pathways, including the MAPK and PI3K pathways . InsulinA previous study also revealed that hypoxia-inducible factor-1a (HIF-1a) mediated endothelin-2 (ET-2) signalling and plays an important role in ovulation in rats and indicated that HIF-1a signalling is inhibited in a PCOS rat model by increasing PHD activity .TCM plays a crucial role in the pharmaceutical industry, alternative medicine, and many other fields –50. HoweTCM gives priority to the concept of holism in diagnosis and pays more attention to the overall changes in function. The treatment is based on syndrome differentiation, emphasizing the recovery of overall function, which is similar to the network concept of network pharmacology .Traditional research methods on TCM mainly rely on pharmacochemical and pharmacological experiments, which have many problems, such as low data flux, low precision, long cycles, and high costs. The construction and development of a network pharmacology analysis platform, TCM database, and target prediction technology has brought new ideas and strategies for the study on the basis and mechanism of the pharmacodynamic substances of TCM to clarify characteristics such as the good curative effects, high safety profile, and multicomponents and multitargets of TCM . These dThe combination of bioinformatics, computer technology, and experiments in the study of the pharmacodynamic components and potential targets of TCM broke through the deficiency of traditional studies is more rapid, flexible, and accurate and has been widely used in research on the network pharmacology of TCM .TCM has a long history in treating menstrual diseases and infertility related to PCOS and has achieved good effects . In thisIn this study, the preliminary analysis based on network pharmacology provided a basis for subsequent studies on the pharmacodynamic ingredients and mechanisms of CDD. However, due to the limitations of the screening conditions and the TCM database, this study also has some shortcomings. Although a large number of targets and pathways were obtained through network pharmacology screening, these results must be verified by subsequent pharmacological experiments. In this study, the active components of CDD and their molecular mechanisms in PCOS were predicted overall, and a variety of potential therapeutic targets were explored. Thus, this study lays a good theoretical foundation for the next step of experimental verification and provides directions for further research on the molecular mechanism of PCOS.


Hua-Feng-Dan (HFD) is a Chinese medicine for stroke. This study is to predict and verify potential molecular targets and pathways of HFD against stroke using network pharmacology.  The TCMSP database and TCMID were used to search for the active ingredients of HFD, and GeneCards and DrugBank databases were used to search for stroke-related target genes to construct the “component-target-disease” by Cytoscape 3.7.1, which was further filtered by MCODE to build a core network. The STRING database was used to obtain interrelationships by topology and to construct a protein-protein interaction network. GO and KEGG were carried out through DAVID Bioinformatics. Autodock 4.2 was used for molecular docking. BaseSpace was used to correlate target genes with the GEO database.  Based on OB ≥ 30% and DL ≥ 0.18, 42 active ingredients were extracted from HFD, and 107 associated targets were obtained. PPI network and Cytoscape analysis identified 22 key targets. GO analysis suggested 51 cellular biological processes, and KEGG suggested that 60 pathways were related to the antistroke mechanism of HFD, with p53, PI3K-Akt, and apoptosis signaling pathways being most important for HFD effects. Molecular docking verified interactions between the core target  and the active ingredients . The identified gene targets were highly correlated with the GEO biosets, and the stroke-protection effects of Xuesaitong in the database were verified by identified targets.  HFD could regulate the symptoms of stroke through signaling pathways with core targets. This work provided a bioinformatic method to clarify the antistroke mechanism of HFD, and the identified core targets could be valuable to evaluate the antistroke effects of traditional Chinese medicines. Aconitum coreanum (Bai Fu Zi), Arum ternatum Thunb. (Ban Xia), Arisaema erubescens (Tian Nan Xing), Aconiti Radix (Chuan Wu), Curcumae Radix (Yu Jin), Gastrodia elata (Tian Ma), Nepeta cataria (Jing Jie), Atractylodes japonica (Cang Shu), Perilla frutescens (Zi Su), Crotonis fructus (Ba Dou), Moschus moschiferus (She Xiang), Borneolum syntheticum (Bing Pian), and Santalum album L. (Tan Xiang). HFD also contains cinnabar, realgar, and other minerals. As a famous traditional Chinese medicine, it has excellent therapeutic effects on stroke, hemiplegia, epilepsy, mouth-eye crookedness, and other head wind and encephalopathy. It is recorded in “Yi Fang Ju Lei,” “Ying Tong Bai Wen,” etc.Hua-Feng-Dan (HFD) is a classical Chinese medicine preparation for the treatment of neurological disorders since the Ming dynasty. After more than 370 years of historical inheritance, it is listed as the National Protection Heritage in 1950 and is still in clinical use today. HFD consists of Modern pharmacological studies have shown that HFD has a protective effect on a variety of central nervous system injury and neuroinflammation models. HFD protects mice from bacterial lipopolysaccharide (LPS) plus neurotoxin MPTP toxicity  and amelChinese herbal medicine preparations are composed of many different compounds with various structures and functions, and all components act together on multiple targets instead of a specific target to achieve therapeutic effects and to reduce toxicity. Some of the components act as the main medicine (JUN), some as secondary medicine (Zou), some as complementary medicine (Chen), and some as guide-drug (Shi) . HFD is In this work, the active molecules in HFD were identified that transcend the physiological barriers and interact with the network targets. We aim to use a comprehensive network pharmacology-based approach to investigate the mechanisms of how HFD exerts therapeutic effects on stroke, and the built network was further verified by correlating with the GEO database of antistroke Chinese medicine.https://tcmspw.com/tcmsp.php) [http://119.3.41.228:8000/tcmid/) [https://www.genecards.org/MyGenes/) and the DrugBank database (https://www.drugbank.ca/) using the keyword “Stroke.”Through the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database (msp.php)  and the /tcmid/) . Stroke-Candidate potential ingredients and herbals of HFD were retrieved and screened from TCMSP retrieved and TCMID database. All the ingredients and their quantitative targets were visualized analysis using Cytoscape 3.7.1 software .https://www.uniprot.org/). The “Draw Venn Diagram” online tool (http://bioinformatics.psb.ugent.be/webtools/Venn/) was used to input the previously collected HFD genes and stroke genes to achieve common genes [HFD targets and stroke targets were transferred to uniform generic names through the UniProt database , the species were selected as “Homo sapiens,” and the obtained “tsv” file was imported into Cytoscape 3.7.1 software for further analysis of the core network.The previously collected common targets were entered into the STRING online database  was used to perform gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to reflect the biological process, molecular function, cellular component, and pathway of HFD in the treatment of stroke. The results are displayed in a bar chart or bubble chart. The smaller the p value is, the higher the degree of enrichment is; the larger the count is, the more genes are enriched on it [DAVID online database  structure diagrams of these compounds were downloaded through the PubChem database and imported into the Chem3D software to draw three-dimensional structure diagrams and optimize energy and save them in mol2 format. Then, the files were imported into AutoDockTools-1.5.6 software to add the charge and display rotatable keys and then saved in pdbqt format. Next, the protein crystal structures corresponding to the core target genes were downloaded from the PDB database, imported into PyMOL software to remove water molecules and heteromolecules, imported into AutoDockTools-1.5.6 software to add hydrogen atoms, saved to pdbqt format, and imported into Discovery Studio 3.5 Client software to search for active pockets. Finally, the compound is used as a ligand, and the protein corresponding to the core target gene is used as a receptor for molecular docking. PyMOL software and Discovery Studio 3.5 Client were used to analyze and interpret the results.https://www.illumina.com/products/by-type/informatics-products/basespace-correlationengine.html; formerly NextBio) is an RNA sequencing and microarray database curated over 23,000 scientific studies to get data-driven answers for genes, experiments, drugs, and phenotypes for the research. The 26 key targets analyzed by the MCODE plug-in were individually input into BSCE for curated studies, followed by filtering with the keyword “stroke” and then combined as the “template.” Using “Chinese medicine” and “stroke” for curated studies, there is one study using Xuesaitong against MOCA-induced stroke in mice with two biosets and a summary p value by the Running Fisher test. The −log was calculated and VLOOKUP with the “template” to make a correlation. This method provides a correlation of the overlapping genes between DEGs and biosets curated in BSCE [p value), the higher the degree of similarity. Biosets that were negatively correlated with DEG were predicted to produce opposite effects. The Treeview 1.6 (https://download.cnet.com/TreeView/3000-2352_4-75666005.html) was used to visualize differences [BaseSpace Correlation Engine (BSCE)  Dc, 9 in Schizonepetae herba, 1 in Moschus moschiferus, 3 in Santalum album L., 4 in Gastrodia elata, 5 in Arisaematis rhizoma, and 11 in Perilla frutescens as shown in The 13 Chinese herbal medicines of HFD were searched through the TCMSP and TCMID databases, and there were 42 active ingredients that met the screening conditions , including 3 in According to the 42 active ingredients of HFD, 121 targets were retrieved in the TCMSP database. 7408 and 49 targets were achieved by searching for “Stroke” in GeneCards and DrugBank databases, respectively. The targets obtained above were entered into the Venn database to obtain a common target, as shown in The 42 active ingredients of HFD collected before and 107 intersection genes of HFD and stroke were imported into Cytoscape 3.7.1 software for visual analysis. As shown in The previously collected 107 common targets were entered into the STRING online database, the species were selected as “Homo sapiens,” and the obtained “tsv” file was imported into Cytoscape 3.7.1 software, as shown in p value is <1.0e − 16. Besides, in all the nodes in The 22 core targets selected by the MCODE plug-in were entered into the STRING database for PPI network analysis . There wR language was used for GO analysis and KEGG analysis. Based on the DAVID database, it was used to analyze the core intersection genes of HFD and stroke. Go analysis includes a biological process (BP), cell composition (CC), and molecular function (MF). Fifty-one significant changes in biological processes were screened, and the top 20 were displayed as bar graphs . KEGG paThrough in-depth analysis, the three most important signaling pathways, apoptosis, phosphatidylinositol-3 kinase (PI3K)/AKT, and P53 signaling pathway, were selected. The genes enriched in the abovementioned pathways include 14 genes in the core genes, in which the six genes were in two or more of the pathways . The topMolecular docking was used for verification of the interaction between active ingredients and target genes. The results obtained by the molecular docking software are shown in Supplementary Table 1. From the results, the lowest binding free energy of beta-sitosterol and caspase-8 was −8.64 kcal/mol. There are Alkyl/Pi-Alkyl hydrophobic interactions between Ile257, His317, Cys360, and beta-sitosterol. Among them, His317 and Cys360 belong to the active site of the caspase-8 protein. In addition, there were three hydrogen bonds: Lys253, Tyr324, Asp319, and beta-sitosterol; there was van der Waals force between Asp363, Gln358, Arg260, Arg413, Tyr412, and beta-sitosterol. On the other hand, the lowest binding free energy of beta-sitosterol and caspase-9 was -9.0 kcal/mol, and there are hydrophobic interactions between His237, Cys287, Arg178, Arg180, Phe351, Pro357, and beta-sitosterol. His237 and Cys287 are the key amino acid residues in the active site of the caspase-9 protein. There are van der Waals interactions between Thr179, Thr181, Lys358, Ser183, Ser361, Asp186, Gln285, Gly182, and beta-sitosterol . The lowp-values) >4 or <−4 with the 26 gene targets in 153 gene biosets (17 GSE studies) except for Igf2 (2.92) was provided as Supplementary Table 2D.In this study, the active ingredients and potential targets of HFD in the treatment of stroke were studied through network pharmacology. 42 active substances were identified by TCMSP and TCMID ; 107 targets were identified with GeneCards and DrugBank. MCODE screened out 22 target genes, STRING constructed 194 Edges in PPI, GO analyzed 51 biological processes, and KEGG enriched 60 significantly related pathways. Molecular docking of 6 targets with 4 active ingredients provided an in-depth analysis of network pharmacology. In addition, the 26 targets from Figures Since its creation in the Ming Dynasty, HFD has played an important role in the improvement of stroke and poststroke symptoms. The formulation of HFD has been continuously improved; for example, through the fermentation, the macromolecules could be degraded into small molecular substances by microorganisms to improve the bioavailability, and the processing by the “Shui-Fei method” is important to reduce the toxicity of heavy metals such as cinnabar and realgar. In recent years, studies have demonstrated that the safety of HFD is different from environmental mercury and arsenic compounds –21. HoweDue to the complexity of the components of traditional Chinese medicine, it is difficult to fully discuss the mechanism of HFD in the treatment of brain diseases through the point-to-point research model of “the animal model-signal pathway,” which requires a lot of tedious work and away from the theory of traditional medicine. Network pharmacology studies may provide a novel approach by constructing a drug-target-disease network from the perspective of the intersection of drugs and disease regulation, through the analysis of the action network, the representative active ingredients are screened, and the target genes are verified by molecular docking, to reveal the active ingredients and mechanism of HFD action in stroke prevention and treatment.In this study, the HFD recipe was first screened by TCMSP and TCMID database, and 13 herbs and 42 ingredients were obtained. Subsequently, 107 interactions with GenCard and DrugBank were found. The core network was obtained through Cytoscape analysis, which contained 22 genes. Typically, the core gene is considered a key role, so we have shown up core gene , STRING κB (NF-κB)/Rel families, plays an important role in inflammation and immune response, which may be a PI3K-AKT regulatory signal, which in turn regulates the apoptosis pathway [GO analyzed 51 biological processes, and KEGG enriched 60 significantly related pathways. In the KEGG analysis, the 3 most important signal pathways were selected through in-depth analysis: apoptosis, phosphatidylinositol-3 kinase (PI3K)/AKT, and P53 signaling pathway. Multiple studies have confirmed that apoptosis is initiated in stroke. Caspase-3, caspase-8, and caspase-9 are important members of the caspase family; upon receipt of specific stress, cytochrome c released by mitochondria will combine with procaspase-9/Apaf-1 to activate and cleave caspase-9 . The cle pathway . On the  pathway . Studies pathway . Under p pathway . The inc pathway . MDM2 is pathway . Phospho pathway .It can be seen that multiple pathways play an important role in stroke through their interactions. In order to further verify the interaction between the 6 core genes and the active ingredients, the HFD effective ingredients were docked with the target to molecular events against stroke. Normally, the binding free energy is lower than −5.0 kcal/mol, indicating good binding activity between the docking molecule and the target, and the values are lower than −7.0 kcal/mol indicating strong binding activity, which indicates a significant interaction. As shown by the results, except for luteolin and MDM2 , the lowest binding free energy between other small molecules and their targets is all lower than −7.0 kcal/mol.p value) was used to study the correlation of selected genes. The cutoff of −log is set at ± 4 [p values) were returned to the normal, or to the opposite direction, confirming the therapeutic effects of this Chinese medicine. It should be mentioned that when there is one type of “Chinese medicine” and “stroke,” only this study was curated in the database; and when there is one type of “cinnabar” and “stroke,” the same study appeared. Cinnabar is an active ingredient in Chinese medicines including HFD and An-Gong-Niu-Huang Wan for brain diseases [In order to study this core network in evaluating the general applicability of traditional Chinese medicine in the treatment of stroke, the 26 genes from Figures t at ± 4 . Under tt at ± 4 . In Figut at ± 4 , GSE3533t at ± 4 , GSE 515t at ± 4 , GSE2113t at ± 4 , GSE4145t at ± 4 , and GSEt at ± 4  and was t at ± 4 , and mordiseases , and theIn summary, this study predicted the active ingredients, targets, and signal pathways of HFD treatment stroke through network pharmacology and verified the core ingredients and targets, laying a foundation for elucidating the mechanism of action. It also provides a systematic evaluation of the degree of stroke and the effect of drug treatment. The selected 26 core targets could be valuable biomarkers to evaluate the efficacy of HFD and Chinese medicines against stroke.The mechanism of action of HFD in stroke involves multiple compounds, targets, and pathways. HFD could regulate the symptoms of stroke through signaling pathways with core targets. This work provided a bioinformatic method to clarify the antistroke mechanism of HFD, and the identified core targets could serve as a biomarker to study antistroke traditional Chinese medicines including mineral-containing remedies.