Methods. Based on TCMSP and CNKI, the components and action targets related to Prunella vulgaris L were screened. The OMIM(Online Mendelian Inheritance in Man) and GeneCards (The human gene database) were used to search for targets related to DH. The “gene - drug - disease” relationship map was drawn by Cytoscape_v3.7.2 plug-in. The target was amplified by the STRING platform, and the “protein - protein” interaction relationship (PPI) network of the interacting target was obtained by the STRING online analysis platform and the Cytoscape_v3.7.2 plug-in. Finally, GO enrichment analysis and KEGG pathway enrichment analysis were conducted on David and Metascape platform to study the co-acting targets. Results. 11 active components, 41 key targets and 16 significant signaling pathways were identified from Prunella vulgaris L. The main active components of Prunella vulgaris L against DH were quercetin and kaumferol, etc, and potential action targets were IL-6 and INS, etc and signaling pathways were AGE-RAGE signaling pathway, TNF signaling pathway, MAPK signaling pathway, PI3K-AKT signaling pathway, etc. It involves in biological processes such as cell proliferation, apoptosis and inflammatory response. Conclusions. The main molecular mechanism of Prunella vulgaris L against DH is that sterols and flavonoids play an active role by affecting TNF signaling pathway, AGE-RAGE signaling pathway, MAPK pathway, PI3K-Akt pathway related targets such as IL-6 and INS.The role of traditional Chinese medicine Prunella vulagaris L in the treatment of tumors and inflammation has been widely confirmed. We found that some signaling pathways of Prunella vulgaris L action can also regulate diabetes and hypertension, so we decided to study the active ingredients, potential targets and signaling pathway of Prunrlla vulgaris L, and explore the “multi-target, multi-pathway” molecular mechanism of Prunella vulgaris L on diabetes mellitus complicated with hypertension(DH).  The global prevalence of diabetes mellitus (The following abbreviations are diabetes) has continued to grow in recent years. According to the International Diabetes Alliance, the estimated number of diabetes patients worldwide in 2019 was 463 million, and is increasing year by year [In traditional Chinese medicine, diabetes and hypertension are attributed to vertigo, wasting-thirst, deficiency of liver-yin and kidney-yin is the common pathological basis of both , 6. ThirAs science advances, plant drugs are gaining more attention and many natural plant chemicals have shown great clinical prospects for combating complications of diabetes and diabetes. Through the examination of ancient books, it is found that Prunella vulgaris L was first contained in Sheng Nong's herbal classic, the main chemical components include triterpenes, sterols, flavonoids, organic acids, coumarin and other type compounds, whose functions include but not limited to blood pressure lowering, blood sugar lowering, etc. Many researchers have now used Prunella vulgaris L in the clinical treatment of diabetes and hypertension –10. But Network pharmacology is a new method and new theory developed on the basis of network biology and multi-directional pharmacology, and based on the construction and analysis technology of the network. Because diabetes is very easy to cause hypertension, and the high mortality rate after the combination, there are few studies on traditional Chinese medicine in treating diabetes associated with hypertension, so we choose to explore the molecular mechanism of Prunella vulgaris L on DH. For the complex diseases of DH, its multi-target and multi-pathway characteristics are suitable for exploring the molecular mechanism with network pharmacology. This paper aims to study the molecular mechanism and pathway prediction of diabetes complicated with hypertension through network pharmacology, and provide a theoretical basis for the further study of the treatment of DH. Its innovation lies in discussing not only one disease in diabetes or hypertension, but exploring the effect of Prunella vulgaris L on disease treatment when diabetes combines hypertension and its complications, and studying the role of the signaling pathway of Prunella vulgaris L in diabetes and hypertension. The molecular docking technology was used to make the results more accurate. The results can not only explore the effect of the traditional drug Prunella vulgaris L on to DH, but also through the study on other diseases.http://tcmspw.com/tcmspsearch.php) includes networks of chemicals, targets and drug targets for 499 Chinese herbal medicines, as well as associated drug target networks, Oral bioavailability (OB) is one of the most important pharmacokinetic parameters in drug absorption, distribution, metabolism, excretion (ADME), indicating the speed and extent to which the active ingredient or active base is absorbed into the body circulation and is absorbed, and the higher the OB value usually indicates the better drug-likeness(DL) of the bioactive molecule of the drug. Due to the poor bioavailability of some traditional Chinese medicine compounds. Therefore, according to the TCMSP database recommended screening indicators combined with pubmed, CNKI and other database reports, OB ≥30% and DL ≥0.18 were identified as screening criteria for active ingredients in Prunella vulgaris L, substances meeting active compounds.The TCMSP database (https://www.uniprot.org/)is the most informative protein sequence database to convert the protein ingredients of Prunella vulgaris L active compounds into gene targets in preparation for the next exploration of the relationship with disease.The Uniprot Protein Database (http://www.omim.org/), GeneCards database(http://www.genechttp://ards.org/) is recognized as a disease target database online retrieval tool that can provide a full range of genetic information. In the above database, “diabetic mellitus” “hypertension” was retrieved as the search word, and the intersection and obtained the action targets associated with DH.The OMIM database  to build a “DH-Prunella vuglaris L-compounds-key target” relationship network. The mechanism of Prunella vulgaris L improving DH was explored by the network.https://string-db.org) to expand the gene. The STRING data online analysis platform is a tool capable of analyzing protein interaction networks, able to visualize the relationship between proteins to obtain PPI network maps where high connectivity is called central genes.The key targets of “drug-disease” were imported into the STRING data online analysis platform (https://david.ncifcrf.gov/), Metascape (http://metascape.org/).The GO database classifies genes and gene products in three aspects: biological processes, molecular function, and cell components. The KEGG database is a database integrating information about genomic, chemical, and system functions that presents the signaling pathways in which the screened key genes are located. GO and KEGG analysis of the screened key targets using David (http://www.rcsb.org/) and the 2D structure of molecular ligands can be downloaded from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/), preprocessing and molecular docking of the target protein and active ingredients using Maestro11.5.Download the target protein structure from the PDB database , and Betweenness-Centrality(BC), Closeness-Centrality(CC). Set 135 points of DC>37.5, CC>2.5251,3881 lines, BC>73.85669, CC>0.7070175, select 41 core genes and obtain PPI network diagram of 41 points, 748 lines . PPI netGO enrichment analysis of 41 target genes through the David database. Making three partial bubble diagram of biological process and cellular component, molecular function at the top 10 enrichment, respectively . It can https://maayanlab.cloud/Enrichr/) and the top 11-bit bubble diagram  pathway, and has anti-oxidation and anti-inflammatory activity, improving glucose metabolism by enhancing insulin sensitivity and improving β cell function and quality[β-glusterol and Spinasterol can prevent and treat hypertension [α-glucossidase and α-amylase, angiotensin converting ase (ACE) and direct vascular relaxation or calcium channel regulation [β cells were immune from apoptosis caused by high glucose stress via the AMPK signaling pathway [This paper analyzes the effective components of Prunella vulgaris L, and creates new ideas for the treatment of DH. The results of this study show that the key compounds that Prunella vulgaris L plays are quercetin, morin, luteolin, kaempferol, beta-sitosterol, delphinidin, spinasterol, vulgaxanthin-I, etc. Studies show that quercetin is a flavonoid,Choi,S et al. confirmed that quercletin can acute enhance acetylcholine-induced 2K1C hypertensive rat vascular relaxation, suggesting that quercletin plays an anti-hypertensive role by reducing vascular elasticity . Meanwhidiabetes . WuYT etd quality, 16. Extrtension , 18. Thegulation . Lai Den pathway .α cells [We found that the top two gene target, IL6, is a multifunctional cytokine secreted by monocyte macrophages, functioning mainly in immunomodulation. According to research, diabetes, hypertension and other diseases can lead to higher IL6 levels in serum, while multiple reports say that genetic polymorphisms of IL6 are closely related to insulin levels and large blood vessels, and may regulate insulin secretion through pancreatic α cells . IL6 alsα cells . INS is α cells . Carmodyα cells . Many ofα cells . The resα cells .κ Bactivity to promote a variety of genes associated with atherosclerosis such as IL-6 [κB [κB binds to a specific DNA sequence, regulates transcription of corresponding genes and accelerates the occurrence of cardiovascular complications. It is conceivable that positive feedback cycles between downstream paths may produce a vicious cycle that promotes cardiovascular complications of diabetes.In the AGE/RAGE signaling pathway, AGE and its receptor RAGE interactions trigger oxidative stress, inflammatory response, and thrombosis, thus participating in vascular aging and damage, and may be an important cause of diabetes associated with hypertension . AGE/RAG as IL-6 . The resIL-6 [κB . As prevα levels increased significantly at the generation of oxidative stress [α, as one of the regulators, induces the production of cytokines like IL-1β, IL-6 involved in oxidative stress and inflammatory response processes.TNFR1 in the TNF signaling pathway mainly regulates cell regulation processes and is associated with insulin resistance and the pathogenesis of type 2 diabetes .The stude stress . TNF-α, α expression and apoptosis [The Insulin pathway activates the MAPK pathway that causes vasoconstriction through endothelial-dependent mechanisms . A largepoptosis .This paper analyzes the treatment of Prunella vulgaris L for DH, and verifies the docking activity of small molecular ligand and protein with molecular docking. The eleven active components of Prunella vulgaris L for diabetes combined with hypertension include steroids, flavonoids, etc., 41 key targets IL-6, NOS3, etc., and 21 significant signaling pathways, such as AGE-RAGE, HIF-1, etc., and analyzed the specific role of these targets and signaling pathways. It theoretically explains the potential mechanism of traditional Chinese medicine Prunella vulgaris L in treating diabetes with hypertension, and provides the direction for the subsequent effect of Prunella vulgaris L in the treatment of DH.


Background: Suxiao Xintong dropping pills (SXXTDP), a traditional Chinese medicine, is widely applied for treating myocardial infarction (MI). However, its therapy mechanisms are still unclear. Therefore, this research is designed to explore the molecular mechanisms of SXXTDP in treating MI.Methods: The active ingredients of SXXTDP and their corresponding genes of the active ingredients were retrieved from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. MI-related genes were identified via analyzing the expression profiling data (accession number: GSE97320). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed to study the shared genes of drug and disease. Through protein–protein interaction (PPI) network and the Cytoscape plugin cytoHubba, the hub genes were screened out. The compounds and hub targets binding were simulated through molecular docking method.Results: We obtained 21 active compounds and 253 corresponding target genes from TCMSP database. 1833 MI-related genes were identified according to P<0.05 and |log2FC| ≥ 0.5. 27 overlapping genes between drug and disease were acquired. GO analysis indicated that overlapping genes were mainly enriched in MAP kinase activity and antioxidant activity. KEGG analysis indicated that overlapping genes were mainly enriched in IL-17 signaling pathway and TNF signaling pathway. We obtained 10 hub genes via cytoHubba plugin. Six of the 10 hub genes, including PTGS2, MAPK14, MMP9, MAPK1, NFKBIA, and CASP8, were acted on molecular docking verification with their corresponding compounds of SXXTDP.Conclusion: SXXTDP may exert cardioprotection effect through regulating multiple targets and multiple pathways in MI. Myocardial infarction (MI) is a class of cardiovascular diseases that possess high mortality all over the world . PercutaSome Traditional Chinese Medicine (TCM) can improve blood circulation. Therefore, TCM has been employed to treat ischemia cardiovascular diseases in China for a long time. SXXTDP comprising Chuanxiong (Rhizoma Chuanxiong), Mudanpi (Cortex Moutan), and Bingpian (Borneolum Syntheticum). SXXTDP has broad pharmacological activities, including anti-inflammation, anti-oxidant, anti-arrhythmic activity, and so on ,3. As isNetwork pharmacology is an effective method to discover novel drugs and mechanisms. So far, this method has been successfully used to clarify the multi-target regulation of TCM in treating diseases. For example, Li et al. explored the potential mechanisms of Tongxinluo capsule in the treatment of coronary heart disease . Yu et aIn the present study, we find the active ingredients and potential molecular mechanisms of SXXTDP in treating MI by utilizing network pharmacology method. These findings indicate that SXXTDP is effective in anti-inflammation, anti-oxidant, anti-arrhythmic activity, and anti-apoptosis, and thus can be applied to the treatment of MI.https://tcmspw.com/tcmsp.php) [https://www.uniprot.org/) [All chemical constituents of SXXTDP were retrieved from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database (msp.php) . We selemsp.php) ,8. The tot.org/)  to searcot.org/) .https://www.ncbi.nlm.nih.gov/geo/), including 3 samples from healthy individuals and 3 MI samples. On the basis of the annotation information of platform GPL570, probe IDs were converted to the corresponding genes. According to P<0.05 and |log2FC| ≥ 0.5, differential expression genes (DEGs) between healthy individuals and MI were obtained by using the package limma of R language [The expression profiling data of GSE97320 and annotation information of microarray platform GPL570 (Affymetrix Human Genome U133 Plus 2.0 Array) were acquired from the GEO database  [The overlapping genes of drug and disease were imported into the STRING database (db.org/)  and a prdb.org/) , the keyP<0.05.Gene Ontology (GO) analysis is an important method that describes the features of candidate targets. By using Clusterprofiler package , a biocoP<0.05.Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis is an important method that describes enrichment of signal pathways of candidate targets. By using Clusterprofiler package, the shared target genes of drug and disease were analyzed with the KEGG pathways analysis tool. The screening criteria was https://pubchem.ncbi.nlm.gov/) [http://www.rcsb.org/) [https://pymol.org.) [According to the results of GO analysis and KEGG pathway, we selected the key protein receptor and ligand associated with protein receptor. The 2D chemical structure of small molecular ligands were acquired from PubChem (lm.gov/) . The 3D lm.gov/) . The 3D sb.org/) . PyMol 2ol.org.)  was usedol.org.) , the forol.org.) . Based oAccording to the screening criteria of the OB≥30% and DL≥0.18, 21 active compounds of SXXTDP were obtained from the TCMSP database, including 3 ingredients of Bingpian, 7 ingredients of Chuanxiong, and 11 ingredients of Mudanpi, as shown in 2FC| ≥ 0.5 and P<0.05, 1833 DEGs, including 1117 up-regulated genes and 716 down-regulated genes, were identified by analyzing the expression profiling data (accession number: GSE97320). A volcano plot of DEGs was shown in According to the criteria of |LogPTGS2, NCOA2, PTGS1, MAPK14, NR3C2, CALM1, STAT1, ALOX5, SLPI, CAT, AKR1B1, CCND1, BCL2L1, MMP9, MAPK1, NFKBIA, CASP8, HSPA5, PRKCB, MGAM, THBD, COL1A1, IFNGR1, TOP2A, NFE2L2, RUNX2, and E2F2. Next, the network of ‘drug-compounds-targets’ was constructed by utilizing Cytoscape 3.8.0 software, as shown in About 27 overlapping genes related with MI and SXXTDP were obtained through the Perl language, including MAPK1, MAPK14, CCND1, CASP8, BCL2L1, MMP9, PTGS2, STAT1, NFKBIA, and CAT, as shown in About 27 overlapping genes associated with disease and drug were inputted into STRING database. We obtained a PPI network after selecting “Homo sapiens” and the medium confidence>0.4, as shown in P<0.05) were presented in In order to further analyze the function of 27 overlapping genes, GO enrichment analysis was conducted by the clusterProfiler package in R language. The top 20 GO enrichment terms  were presented in KEGG enrichment analysis was conducted by the clusterProfiler package in R language. The top 20 KEGG enrichment terms -catechin, and PTGS2-wallichilide were verified by molecular docking, as shown in Using molecular docking approach, we verified the binding sites of the target genes and their corresponding compounds of SXXTDP. According to IL-17 signaling pathway and TNF signaling pathway from the results of KEGG pathway enrichment analysis, we determined six key genes, including The leading causes of death in rural and urban residents were cardiovascular diseases according to China Cardiovascular Diseases Report 2017. Despite advances in medical technology in recent years, myocardial infarction (MI) continues to be regarded as a pivotal risk factor of death . TCM hasMAPK1, MAPK14, CCND1, CASP8, BCL2L1, MMP9, PTGS2, STAT1, NFKBIA, and CAT. SXXTDP is comprised of Chuanxiong, Mudanpi, and Bingpian. Those ingredients have broad pharmacological activities, including anti-inflammation, anti-oxidant, anti-arrhythmic activity, and so on [P<0.05 and |log2FC| ≥ 0.5. A total of 27 overlapping genes between drug and disease were acquired. GO analysis indicated that overlapping genes were mainly enriched in MAP kinase activity, antioxidant activity. KEGG analysis indicated that overlapping genes were mainly enriched in IL-17 signaling pathway and TNF signaling pathway. We obtained 10 hub genes via cytoHubba plugin. Six of the 10 hub genes, including PTGS2, MAPK14, MMP9, MAPK1, NFKBIA, and CASP8, were acted on molecular docking verification with their corresponding compounds of SXXTDP. Study finds that IL-17 signaling pathway is involved in immune responses [The present study used network pharmacology and molecular docking simulation to research the molecular mechanisms of SXXTDP in the treatment of MI. It was found that SXXTDP exerted a potential role in treating MI through regulating multiple target genes, including nd so on . The actesponses . Inhibitesponses . MIR-324esponses . Study fesponses .Mitogen-activated protein kinase 1  and mitogen-activated protein kinase 14  are two members of MAP kinase family. MAP kinases are involved in many cellular processes such as transcription regulation and proliferation. Cardiomyocyte-specific deletion of the Mapk14 and Mapk11 genes reduce myocardial cells apoptosis and increase cardiomyocytes proliferation via inactivation of p38 activity . Matrix Quercetin, a flavonoid, has special biological functions, including antioxidant, anti-inflammatory, anti-platelet aggregation, and so on . A studySimvastatin, HMG-CoA reductase inhibitor, is effective in antioxidant activity , anti-apThe results of this research showed that the active ingredients of SXXTDP played an active role in anti-apoptosis, anti-oxidation, anti-inflammation, and improvement of cardiac remodeling roles. According to the molecular docking simulation, we found that MAPK1-quercetin, MMP9-quercetin, NFKBIA-quercetin, CASP8-quercetin, MAPK14-Myricanone, PTGS2-Perlolyrine, PTGS2-Myricanone, PTGS2-kaempferol, and PTGS2-catechin might exert important roles in treating MI.The present study reveals that SXXTDP exert cardioprotection effect via regulating multiple targets and multiple pathways in MI. SXXTDP may be a promising drug in treating MI. Meanwhile, our study will provide a scientific basis for the further lab studies.Click here for additional data file.


Zuojin Pill (ZJP), a classic prescription, has the potential to prevent ulcerative colitis (UC). However, the active components and mechanisms of ZJP are still arcane. This study aimed to use a network pharmacology approach to find the bioactive compounds and potential action mechanisms of ZJP in the treatment of UC.  Firstly, the components and putative targets of ZJP were collected based on herbal medicine target databases, and a network containing the interaction between the targets of ZJP and the potential therapeutic targets of UC was established. Then, topological parameters were calculated to identify the key targets in the network and, in turn, to import them into the David database to perform path enrichment analysis.  14 potential therapeutic components of ZJP and 26 key targets were obtained. These targets were related to signal transduction, MAPK cascade, inflammatory response, immune response, and the apoptotic process of UC. Moreover, the PI3K-Akt signaling pathway, MAPK signaling pathway, toll-like receptor signaling pathway, and Prolactin signaling pathway were predicted to participate in ZJP treating UC. Among them, 14 active components of ZJP directly regulate these pathways.  ZJP could alleviate UC through the predicted components and mechanisms. The 14 predicted active components of ZJP may mainly play a therapeutic role for UC through synergistic regulation of the PI3K-Akt signaling pathway and MAPK signaling pathway. Ulcerative colitis (UC) is a chronic nonspecific inflammatory disease. It was listed as a modern refractory disease by the World Health Organization because of its unclear etiology, high clinical recurrence rate, and association with colon cancer . In receCoptis chinensis Franch.  and Evodia rutaecarpa (Juss.) Benth.  .Zuojin Pill (ZJP), a classic prescription for gastrointestinal diseases, has been widely used in the clinical treatment of gastrointestinal diseases since ancient times in China because of its safety and effectiveness. It composes of In recent years, ZJP has been reported to have beneficial evidence on UC . HoweverTherefore, this study aimed to use a comprehensive network pharmacology-based approach to investigate the potential effective components and molecular mechanisms of ZJP in treating UC. The flowchart of the experimental procedures of our study is shown in https://old.tcmsp-e.com/tcmsp.php, updated on May 31, 2014), Chinese Academy of Sciences Chemistry database , and related literatures to collect the chemical components of the two herbs contained in ZJP using “Coptidis Rhizoma” and “Fructus Evodiae” as the queries. The TCMSP is a unique systematic pharmacology database of Chinese herbal medicines, chemicals, targets, and drug-target networks. The CASC is one of the most comprehensive chemical databases in the world, which can provide chemical information of Chinese herbal medicine and natural products.We searched the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform .The targets of chemical components in ZJP were mainly obtained from the TCMSP database. If the targets of chemical constituents reported in the literature were not included in the database, they were obtained through SwissTargetPrediction (https://www.disgenet.org/) and Online Mendelian Inheritance in Man database . After screening the target (score ≥ 0.01) and removing the duplicate value, they were collected and used for data analysis serving as a target database for treating UC.The known therapeutic targets of UC were acquired from the DisGeNET database (https://string-db.org/), and the interactions with a probabilistic association confidence score ≥ 0.9 were selected in this study. All networks were constructed and analyzed by using Cytoscape v3.7.1. Three topological parameters were used as the screening criteria to obtain a hub network and key targets .The protein-protein interactions (PPIs) of each target were generated from the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database (https://david.ncifcrf.gov/). GO terms and KEGG pathways with p value < 0.05 were considered statistically significant.Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID)  and drug-likeness (DL) .http://admet.scbdd.com) is a free tool database for the prediction of absorption, distribution, metabolism, and excretion and various toxicities (ADMET) properties and has been widely used in chemical and pharmaceutical fields. Each SMILES of molecule was input to obtain organ toxicity and other toxic properties.ADMETlab  were predicted online by SwissTargetPrediction, and the targets of remaining compounds were from the TCMSP. Finally, 249 direct acting targets of Rhizoma Coptidis and 357 direct acting targets of Fructus Evodiae were obtained. After removing repeated targets, 386 targets were obtained for subsequent analysis. Also, there were 220 overlapping targets between the two herbs , which s1458 targets of UC were obtained from the DisGeNET database, and 180 targets of UC were obtained from the OMIM database. A total of 1527 targets of UC were obtained after removing the repeats for subsequent analysis . By compThe PPI network was constructed by STRING (confidence score ≥ 0.9), with 125 nodes and 645 edges . Based oTo investigate the biological functions and pathway of the key targets of ZJP, the gene ontology (GO), biological process (BP), and KEGG were performed through the functional annotation tool of DAVID and Cytoscape3.7.1. The top 10 GO terms and pathways were significantly enriched, respectively Figures  and 6 .In UC, the BPs mainly regulated by ZJP were signal transduction, response to drug, cellular response to lipopolysaccharide, MAPK cascade, inflammatory response, immune response, transcription from RNA polymerase II promoter, apoptotic process, regulation of sequence-specific DNA binding transcription factor activity, and lipopolysaccharide-mediated signaling pathway .The pathways mainly regulated by ZJP were pathways in cancer, Chagas disease, hepatitis B, the Toll-like receptor signaling pathway, influenza A, proteoglycans in cancer, the MAPK signaling pathway, HTLV-I infection, the PI3K-Akt signaling pathway, and the prolactin signaling pathway . Many ofThe key targets of ZJP enriched to four signaling pathways are shown in The pathogenesis of UC is sophisticated, including genetic, environmental, psychological stress, and other factors . In viewIn this study, we successfully identified 14 active molecules and 3 important pathways related to UC through network pharmacology and bioinformatics. This method can more clearly identify the targets and specific mechanisms of TCM in the treatment of diseases and obtain the key active molecules, which is of great significance for the development of natural drugs and the treatment of diseases.GO-BP enrichment analysis showed that ZJP may play an anti-UC role by regulating inflammatory response, immune response, apoptosis, MAPK cascade, signal transduction, and other biological functions. Pathway enrichment analysis results showed that many other diseases were enriched in addition to UC, which may be because the same molecular targets exist in different pathological processes of diseases. This is not only the limitation of network pharmacology but also the divergence points of the research direction. Therefore, we selected the enrichment pathway closely related to UC in our research. Finally, based on the two aspects of network construction and central network evaluation, 26 key targets of the ZJP potential target network were selected which were significantly enriched in three UC-related signaling pathways, including the PI3K-Akt signaling pathway, MAPK signaling pathway, and toll-like receptor signaling pathway. Studies have shown that the PI3K-Akt signaling pathway could regulate the inflammation and oxidative stress of UC , 13; the8α, and IL-6 in UC [κB signaling cascades, and improving disrupted epithelial barriers [β-Sitosterol could improve experimental colitis in mice by increasing the expression of antimicrobial peptides in intestinal epithelial cells [κB signaling [Among the 14 predicted active components, 9 compounds such as berberine, obacunone, quercetin, coptisine derivatives, berberrubine, palmatine, beta sitosterol, isorhamnetin, and rutaecarpine have been proved to be effective in the treatment of UC, and the related mechanism of some compounds was consistent with the predicted pathway in this study. Studies have shown that berberine could inhibit the p38 MAPK signaling pathway and decrease the levels of inflammatory biomarkers IL-1, TNF--6 in UC ; obacunobarriers ; quercetbarriers ; coptisibarriers ; berberrbarriers ; palmatibarriers ; β-Sitosal cells ; isorhamignaling ; rutaecaignaling . In geneα [In addition to the abovementioned active ingredients with the research basis related to UC, five potential active ingredients including worenine, epiberberine, palmidin A, moupinamide, and rutalinidine have not been reported in UC. Recent studies have shown that worenine could reverse the Warburg effect and inhibit colon cancer cell growth by negatively regulating HIF-1α ; epiberbα ; moupinaα . FurtherIn short, researching ZJP on UC by use of the network pharmacological approach reflected the multicomponent, multitarget, and integrated regulation of TCM prescriptions. This study predicted the potential active ingredients, molecular targets, and mechanisms of ZJP in the treatment of UC, which provided a prospective scientific reference for the future systematic study of the effects and mechanisms of ZJP and its material basis on UC.


In vivo and in vitro experiments confirmed that antidiabetic effects of GQL were associated with a modulation of the TNF and PI3K–AKT–MTOR pathways.Type-2 diabetes mellitus (T2DM) and therapy options have been studied increasingly due to their rising incidence and prevalence. The trend of applying traditional Chinese medicine (TCM) to treat T2DM is increasing as a crucial medical care for metabolic dysfunctions. Gegen Qinlian decoction (GQL), a well-known classical TCM formula used in China, has been clinically applied to treat various types of chronic metabolic diseases. However, antidiabetic effects of GQL administration during T2DM have never been studied systematically. We assessed physiological and molecular targets associated with therapeutic effects of GQL by evaluating network topological characteristics. The GQL-related biological pathways are closely associated with antidiabetic effects, including the TNF and PI3K–AKT signaling pathways. Associated primary biological processes such as RNA polymerase II promoter transcription participate in the inflammatory response, oxidative stress reduction, and glucose metabolic process, thereby exerting multiple biological effects on the antidiabetic mechanism. Furthermore, our results showed that GQL can affect blood glycemic levels and ameliorate inflammatory symptoms, and liver and pancreas tissue injury in high-fat diet plus streptozotocin-induced diabetic mice.  Type-2 diabetes mellitus (T2DM) is a chronic metabolic disease which constitutes a severe threat to global public health . T2DM isPueraria lobata (Wild.) Ohwi), 9 g Scutellariae Radix , 9 g Coptidis Rhizoma , and 6 g Glycyrrhizae Radix et Rhizoma . Modern clinical research has shown that GQL can normalize hyperglycemia and hyperlipidemia in T2DM patients  was commercially purchased from PuraPharm , and its constituents were identified using UHPLC analysis. GQL powder (1 g) was extracted using methanol (10 ml) in a 15-ml centrifuge tube, and the methanol solution was sonicated and centrifuged at 35,000 rpm. The supernatant solution was then filtered through a 0.45-μm membrane before UHPLC analysis. Chromatographic analysis was performed using a reverse-phase ACE Excel C18 column (100 mm × 2.1 mm) at a flow rate of 0.379 ml/min at 35 C. The elution media with 0.15% trifluoroacetic acid (B) and methanol (A) were used with a gradient protocol as follows: 77–70% B for 0–4.4 min, 70%–65% B for 4.4–4.576 min, 65%–42% B for 4.576–6.864 min, 42%–45% B for 6.864–7.040 min, 45%–45% B for 7.04–9.68 min, 45%–30% B for 9.68–12 min, and 30–30% B for 12–15 min.Radix, 14 compounds from Scutellariae Radix, seven compounds from Coptidis Rhizoma, and 13 compounds from Glycyrrhizae Radix et Rhizoma. Some chemical compounds of GQL show some properties of absorption, distribution, metabolism, and excretion (ADME) and the standard of drug-likeness (DL), and potentially druggable compounds were selected as active constituents for further target prediction of GQL. Information on oral bioavailability (OB) and DL index of the 42 compounds is shown in http://tcmspw.com/) (http://db.idrblab.net/ttd/), KEGG (http://www.kegg.jp/), and CTD (http://ctdbase.org/) databases to identify corresponding T2DM-associated protein targets (http://string-db.org). We used a high confidence threshold (>0.9) to ensure reliability, and protein–protein interaction data with high node degrees obtained from STRING were selected for establishing a protein–protein interaction network.We collected information on the GQL chemical constituents from previous studies . Forty-tpw.com/) . Next, T targets . The com targets . To illuTo identify potential target proteins affected by GQL, GO biological function and KEGG pathway enrichment searches were carried out using the annotation database of DAVID biological information  to detern = 5, each). Following the best practice in pharmacological research  to induce obesity. After four weeks, HFD-fed mice were intraperitoneally injected with streptozotocin solution  at 50 mg/kg on two consecutive days . Next, mresearch , we usedresearch , to calcresearch  and animresearch , we oral2. To assess antidiabetic effects of GQL, we cultured AML12 cells in a palmitate plus high-glucose (33 mM) medium at 37 C for 24 h and treated the cells without or without GQL (100 μg/ml).AML12 hepatocytes  were cultured in DMEM/F12 medium (10% FBS plus 100 mg/ml streptomycin and 100 U/mL penicillin) and were incubated at 37 C in an incubator continuously supplying 5% COProtein was extracted by adding RIPA solution, and supernatant containing proteins was collected after centrifugation. After protein quantification using a Bio-Rad Protein Assay Kit II (5000002), protein separation was performed by SDS-PAGE gel electrophoresis, and separated proteins were transferred to a membrane and blocked using 5% BSA solution to prevent nonspecific protein binding. After blocking, the immunoblot membrane was incubated with primary antibodies against the target proteins such as GAPDH, iNOS, P-65, SOCS 2, P-ERK, P-AKT, P-MTOR, and P-JNK. After washing three times, the membrane was incubated with secondary antibody . Protein expression was visualized using the ECL system and was analyzed using the Chemidoc chemiluminescent platform .Total RNA was isolated by using an RNeasy Mini Kit , and concentration was measured at a 260 /280-nm ratio. First-strand cDNA was transcribed from total RNA using a First Strand Synthesis Kit . PCR was conducted using SYBR Green reagent, specific primers , and a LTissue samples of HFD + STZ mice were fixed in 4% paraformaldehyde buffer, and tissue sections (5 μm thickness) were stained using H&E and Oil Red O for general histology .t-test with Prism Software 8.3.1. Statistical significance is reported at p < 0.05.Statistical analysis was conducted using an ANOVA or Student's two-tailed TCM was administered orally to examine its efficacy after the ADME process, and OB of the 42 active ingredients in GQL has been indicated to determine potentially druggable active compounds . By screHighly connected subnetworks with 53 gene nodes were identified using the MCODE module analysis  Figure . The Venp < 0.05) to generate a target–pathway signaling network involving 33 target proteins , CC ontology (14 records), and MF ontology (19 records) consisted of 75.4, 14.2, and 10.4%, respectively . Target proteins . KEGG anCurative effects of the GQL formula on HFD + STZ-induced diabetic mice were evaluated, and GQL treatment showed promising hyperglycemic effects, as evidenced by the reduction in fasting blood glucose levels . ComparePI3K/AKT and TNF-α–related target proteins and signaling pathways were assessed in AML12 hepatocytes exposed to palmitate and high glucose levels. The TNF signaling pathway was examined by measuring TNFα, IKKα, IL-6, IL-1β, CASP 8, and CASP 3 mRNA , showingvia multiple targets and signaling pathways, which may aid in T2DM treatment. However, the complexity of TCMs may complicate in-depth research to elucidate the underlying mechanisms. Due to extensive clinical application of GQL to treat T2DM in China (T2DM is a heterogeneous disease with high morbidity and complex associated afflictions. Thus, development of diabetes is associated with multiple target proteins or pathways. TCMs composed of multiple indigents may exert various pharmacological effects in China , networkin vitro and in vivo to inhibit T2DM development.Our study explored the mechanisms of a multicomponent, multigene-targeting GQL formula by establishing a T2DM association network. This analysis was based on therapeutic effects of GQL formula relevant to 148 antidiabetic target genes, and GQL regulated binding kinase in plasma or cell membranes and modulated inflammatory responses, oxidative reduction, and glucose metabolic process by 38 significant proteins and signaling pathways, that is, the PI3–AKT , insulinRhizoma coptidis, which can have beneficial effects on diabetes and diabetic complications by modulating AKT/AMPK–NF-κB/MAPK/PI3K and oxidative stress signaling pathways (In the current study, GQL constituents with high OB and DL indices were selected as bioactive compounds with high pharmacokinetics because they may be absorbed and distributed in the patient’s body. Our compound–target network analysis showed 12 potential candidate compounds with high node degrees, that is, wogonin, oroxylin A, baicalein, baicalin, coptisine, epiberberine, berberine, palmatine, isoliquiritigenin, liquiritigenin, glycyrol, and formononetin, all of which may be associated with the marked antidiabetic effect of GQL on T2DM. These bioactive compounds exert antihyperlipidemic, anti-inflammatory, and anti-oxidative effects during diabetes and diabetic complications. Bioactive isoflavones from Puerariae Lobatae Radix, puerarin, and daidzin showed antidiabetic effects in animal studies, such as puerarin improving insulin resistance and islet damage by inhibiting inflammation and oxidative stress during diabetes and diabetic complications . Daidzinpathways . Specifipathways . Coptisipathways . Isoliqupathways . These ppathways . Our respathways  and multpathways . Moreovein vitro and in vivo should be further examined in clinical trials with T2DM patients. However, more evidence is needed to further validate antidiabetic bioactivities of the active compounds and to evaluate their respective contributions.In conclusion, a combination of pharmacology network analysis and experimental approaches may be a useful research tool to elucidate antidiabetic mechanisms of TCMs in detail. The development of T2DM is a complex pathological process involving multiple signaling pathways and multiple targets. Our results suggest that GQL can modulate multiple target proteins in multiple signaling pathways and can be used for T2DM therapy. The antidiabetic effects of GQL


Intervertebral disc degeneration (IVDD) is the most significant cause of low back pain, the sixth-largest disease burden globally, and the leading cause of disability. This study is aimed at investigating the molecular biological mechanism of Danggui-Sini formula (DSF) mediated IVDD treatment.  A potential gene set for DSF treatment of IVDD was identified through TCMSP, UniProt, and five disease gene databases. A protein interaction network of common targets between DSF and IVDD was established by using the STRING database. GO and KEGG enrichment analyses were performed using the R platform to discover the potential mechanism. Moreover, AutoDock Vina was used to verify molecular docking and calculate the binding energy.  A total of 119 active ingredients and 136 common genes were identified, including 10 core genes . Enrichment analysis results showed that the therapeutic targets of DSF for diseases mainly focused on the AGE-RAGE signaling pathway involved in diabetic complications, IL-17 signaling pathway, TNF signaling pathway, Toll-like receptor signaling pathway, apoptosis, cellular senescence, PI3K-Akt signaling pathway, and FoxO signaling pathway. These biological processes are induced mainly in response to oxidative stress and reactive oxygen species and the regulation of apoptotic signaling pathways. Molecular docking showed that there was a stable affinity between the core genes and the key components.  The combination of network pharmacology and molecular docking provides a practical way to analyze the molecular biological mechanism of DSF-mediated IVDD treatment, which confirms the “multicomponent, multitarget and multipathway” characteristics of DSF and provides an essential theoretical basis for clinical practice. Low back pain is the sixth largest disease burden globally and is the leading cause of disability, which has become a global health concern . A previThe initial clinical treatment for IVDD has focused on symptom relief, mainly with nonsteroidal anti-inflammatory drugs (NSAIDs) , 6. HoweNetwork pharmacology is a strategy for elucidating the synergistic effects and potential mechanism of multicompound and multitarget drugs based on various complex “drug-ingredient-target gene” networks . It may Angelica sinensis , Cinnamomum cassia Presl , Cynanchum otophyllum Schneid , Asarum sieboldii Miq , Glycyrrhiza uralensis Fisch , Tetrapanax papyriferus , and Ziziphus jujuba Mill . In recent years, pharmacological studies have shown that this decoction has positive anti-inflammatory and antioxidative effects, especially in the treatment of osteoarthritis [The Danggui-Sini formula (DSF) is a classic prescription in the Treatise on Febrile Diseases and is mainly composed of seven herbs : Angelicrthritis , 13. Altrthritis .This study integrated network pharmacology and molecular docking to explore the potentially effective mechanism and targets of DSF acting on IVDD. The research process is shown in https://tcmsp-e.com/) [https://go.drugbank.com/) [https://www.UniProt.org) [By searching the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database (-e.com/) , with thnk.com/) , and therot.org) .https://omim.org/) [https://www.genecards.org/) [http://ctdbase.org/) [https://go.drugbank.com/) [https://www.disgenet.org/) [To obtain the targets of IVDD, we searched a total of five databases, namely, Online Mendelian Inheritance in Man (OMIM) (im.org/) , Genecards.org/) , Comparase.org/) , DrugBannk.com/) , and Diset.org/) . In addiet.org/) . A commo“Active ingredients - potential targets” network and another related network for disease-core genes–active ingredients–herbs were established using the Cytoscape software . To obtahttps://www.string-db.org/) [We imported the common genes into the STRING database (db.org/)  to obtaihttps://www.rcsb.org/) and used the PyMol 2.4.0 software to remove water and natural ligands from the protein. Second, the 2D structures of active components  were downloaded from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/). Then, we used the ChemBio3D software to convert the molecular ligand into a 3D structure and performed energy minimization by the MM2 calculation method. Hydrogenation of proteins and small molecular ligands was prepared with the Autodock tool. Finally, Autodock Vina was used for molecular docking and calculating the binding energy [Molecular docking analysis focused on the proteins encoded by the 10 core genes and their corresponding active components. First, we downloaded the 3D structure of the protein from the RCSB PDB database , we obtained common genes that intersect between drug-target and disease-related genes. One hundred thirty-six genes were identified as potential genes for DSF in the treatment of IVDD, and the Venn diagram is shown in With the keyword “intervertebral disc degeneration,” we searched the five databases mentioned above and obtained a total of 2166 genes after deduplication. Using an online web service  plays a crucial role in the pathological process of IVDD, which is mainly mediated by inflammation and oxidative stress . IL6, TNα, IGF1 or low energy, low oxygen, and other factors. Then, mTOR activates downstream 4E-BP1 and p70S6K, which play a vital role in regulating the proliferation, apoptosis, and nutritional status of interdisc cells [β-estradiol prevents ECM degradation by downregulating MMP3 expression via the PI3K/Akt/FOXO3 pathway [GO and KEGG enrichment analysis results showed that the therapeutic targets of DSF for diseases mainly focused on the AGE-RAGE signaling pathway involved in diabetic complications, IL-17 signaling pathway, TNF signaling pathway, Toll-like receptor signaling pathway, apoptosis, cellular senescence, PI3K-Akt signaling pathway, and FoxO signaling pathway. The biological processes are mainly induced in response to oxidative stress and reactive oxygen species and the regulation of apoptotic signaling pathways. Studies have shown that all of these factors play crucial roles in the progression of IVDD. The TNF and IL-17 pathways play a synergistic role in the progression of IVDD, mainly by promoting the release of inflammatory factors, the apoptosis of NPCs, and the degradation of extracellular matrix (ECM) –44. mTORsc cells . Furthersc cells , 47. Recsc cells . In addi pathway . At pres pathway .However, our study also has some limitations. For example, the results of this study lacked in vitro validation, and further external validation with animals should be performed. Moreover, the screening of active ingredients and related genes through databases may not be sufficiently comprehensive.The combination of network pharmacology and molecular docking provides a practical way to analyze the molecular biological mechanisms of DSF-mediated IVDD treatment. AKT1, IL6, ALB, TNF, VEGFA, TP53, MAPK3, CASP3, JUN, and EGF may be potential targets of DSF in treating IVDD, and enrichment analysis results showed that the therapeutic targets of DSF for diseases mainly focused on the AGE-RAGE signaling pathway in diabetic complications, IL-17 signaling pathway, TNF signaling pathway, Toll-like receptor signaling pathway, apoptosis, cellular senescence, PI3K-Akt signaling pathway, and FoxO signaling pathway, which confirms the multicomponent, multipathway, and multitarget characteristics of DSF and provides an essential theoretical basis for clinical practice.


Background and Aims: Zhi Gan prescription (ZGP) has been clinically proven to exert a favorable therapeutic effect on nonalcoholic steatohepatitis (NASH). This study purpose to reveal the underlying molecular mechanisms of ZGP action in NASH.Methods: Systematic network pharmacology was used to identify bioactive components, potential targets, and the underlying mechanism of ZGP action in NASH. High fat (HF)-induced NASH model rats were used to assess the effect of ZGP against NASH, and to verify the possible molecular mechanisms as predicted by network pharmacology.Results: A total of 138 active components and 366 potential targets were acquired in ZGP. In addition, 823 targets of NASH were also screened. In vivo experiments showed that ZGP significantly improved the symptoms in HF-induced NASH rats. qRT-PCR and western blot analyses showed that ZGP could regulate the hub genes, PTEN, IL-6 and TNF in NASH model rats. In addition, ZGP suppressed mitochondrial autophagy through mitochondrial fusion and fission via the PINK/Parkin pathway.Conclusion: ZGP exerts its effects on NASH through mitochondrial autophagy. These findings provide novel insights into the mechanisms of ZGP in NASH. Non-alcoholic fatty liver disease (NAFLD) is a metabolic disorder caused by obesity, diabetes, and other factors that lead to fatty degeneration of the liver . Based oThe pathogenesis of NASH is complicated and has yet to be fully clarified. In recent years, the “multiple-hit” theory has highlighted the critical role of endoplasmic reticulum stress (ERS) in NAFLD, particularly in NASH. Hypoxia, oxidative stress, exogenous substances and the accumulation of unfolded proteins in the endoplasmic reticulum can disrupt endoplasmic reticulum homeostasis, leading to ERS, disturbances in hepatic lipid metabolism, inflammatory necrosis and apoptosis of hepatocytes, and ultimately the development of NASH . It has Zhi Gan prescription (ZGP) is composed of six herbal medicines . ZGP is an experiential prescription of Professor Fusheng Zhou for the treatment of NASH, which can tonify qi and strengthen the spleen, and dissipate blood stasis and phlegm . Clinicavia diverse bioactive components, which act on multiple targets  is characterized by its multi-component and multi-target nature. In the therapy of disease, TCM exerts its effects on multiple biological processes  targets . The eme targets . Network targets .In vivo experiments were performed to validate the potential molecular mechanisms. The result of this study provides novel insights into the mechanisms underlying the efficacy of herbal TCM in NASH and provide a reference for preparing ZGP for treating NASH.In this study, we sought to identify the active ingredients, therapeutic targets, and the mechanism of action of ZGP. Potential therapeutic targets were identified by network pharmacology analysis, followed by the construction an herbal-chemical-protein-disease network and the identification of hub genes identification. https://tcmspw.com/tcmsp.php) (http://lifecenter.sgst.cn/hit) (http://www.megabionet.org/tcmid) (http://stitch.embl.de) was used to retrieve compound targets  , Herbal .cn/hit)  and Tradg/tcmid) . In addi targets . After rin vivo  in vivo . Poor AD, describes the probability of a target interacting with more than k compounds of n compounds in the profile by the random choice method and the value is adjusted by the false discovery rate method. These statistics contribute to evaluate the likelihood of the stochastic result. p ≤ 0.01 means that the actual quantity of compounds that the target interacts with is significantly greater than the expected, therefore, this target can be considered as a core target for the formula.The core targets of ZGP can be verified by analyzing the target profile of ZGP ingredients. The target that interacts with the majority of compounds can be considered the core target for the pharmacological action of the formulation. In the meantime, the probability of a target was calculated by using a binomial statistical model  as follohttps://omim.org) (http://www.disgenet.org/) (https://www.genecards.org/) (https://www.uniprot.org/)  , DisGeNEet.org/) , and Gends.org/) . DisGeNEot.org/) . The netNASH-related targets and ZGP corresponding targets were input into Venn 2.1 software to draw Venn diagrams and screen the common targets of both. Then, the resulting target information was input into STRING database to construct the PPI network. Next, we used CytoNCA (v2.1.6), a plug-in of Cytoscape, to evaluate the intersection.N is the total number of genes in the reference list, M denotes the number of genes annotated by GO or KEGG pathway, n represents the count of number of query genes, and k is the number of common genes between query genes and reference genes. According to the false discovery rate method, p < 0.01 demonstrates the significant association between annotated genes and query genes. In this study, GO enrichment analysis and KEGG pathway analysis was carried out for obtaining molecular function (MF), cellular component (CC), biological process (BP), and a functional pathway.In order to identify the functions of the formula targets and NASH-related genes, gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed. A hypergeometric test was preferable conducted to assess the relationship between annotation terms and the query genes, and the probability can be calculated as follows:A total of 120 Sprague-Dawley rats (180–220 g) were provided by the laboratory animal center of Zhejiang Chinese Medical University. This animal research protocol was ratified by the Institutional Animal Care and Use Committee of the Zhejiang Chinese Medical University. All the Sprague-Dawley rats were bred in a lab room with a 12 h light:12 h dark cycle and controlled temperature at 24 ± 2°C and allowed ad libitum acquire to rodent chow and water.n = 20), model (n = 20), positive medicine (n = 20), high-dose ZGP (n = 20), medium-dose ZGP (n = 20) and low-dose ZGP (n = 20) groups. Rats in the normal group were allowed free acquire to a standard diet. Animals in the model and treatment groups accepted a high-fat (HF) diet (2% cholesterol + 10% lard + 88% standard diet) for 8 weeks. After 8 weeks, rats in the high-dose ZGP, medium-dose ZGP, and low-dose ZGP groups were given a ZGP decoction at 22.88, 15.29, and 7.59 g/kg, respectively. Rats in the positive medicine control group received atorvastatin calcium tablets  by gavage for 4 weeks. Rats in the normal and model groups were given distilled water equivalent to the ZGP.The rats were randomly divided into six groups, including normal (The right liver lobe was removed and cut a piece of liver tissue (no more than 2 mm thick) with a blade and plotting plane flat. The liver tissue was immersed in 10% neutral formalin solution for fixation , and theEach blood specimen (3–5 ml) was centrifuged for 10 min , the upper layer of which was then collected in a 1.5 ml EP tube. An automatic biochemical analyzer was utilized to determine changes in serum lipid levels and hepatic functions . MDA and 4-HNE contents were measured using an ELISA kit following manufacturer instructions .Experimental manipulations were performed as previously reported .For Western blot analysis, the experiments were proceed as previously described .en bloc slices with 2% uranyl acetate at 4°C overnight. Stained slices were dehydrated with graded ethanol solutions, and then embedded in Durcupan ACM resin (Sigma). Ultrathin 80 nm liver sections were obtained using a Leica Ultracut UCT ultramicrotome, and poststained with uranyl acetate and lead salts. Subsequently, the digital images of slices were analyzed using a HITACHI H-7650 TEM under an 80 kV setting .The removed cells and liver tissue were fixed by circulating with a fixation buffer on ice for 2 h, followed by six washing steps using 0.1 M sodium cacodylate and 3 mM calcium chloride on ice. The cells and liver slices approximately 80 μm were dissected using a Leica VT 1,000 s vibratome and then were postfixed with 1% osmium tetroxide, 0.8% potassium ferrocyanide, and 3 mM calcium chloride in 0.1 M sodium cacodylate for 1 h. Slices were washed three times with ice-cold distilled water and stained Immunohistochemistry was performed according to the manufacturer’s instructions of the kits . Each slice was observed five visual regions randomly under high magnification (×200), and the Image-Pro Plus 6.0 was utilized to measure the integrated optical density (IOD) of each slice. The relative expressions of target proteins were represented by the average-optical density IOD/Area.p < 0.05 were indicated statistically significant between groups.The data were presented as the means ± standard error. Statistical analysis was conducted by one-way ANOVA and followed by the Student’s t-test (for two groups) or Tukey’s test (for more than two groups). A total of 142 components of ZGP were obtained from the TCMSP , TCM-ID (2021.4) and HIT (2021.4) databases. These components were screened using the criteria of QED ≥0.2. In total, 138 bioactive components of ZGP were included; 46 of Codonopsis Radix, 24 of Atractylodes Macrocephala Koidz., seven of Crataegus pinnatifida Bge., 24 of Polygoni Cuspidati Rhizoma Et Radix, 19 of Cassiae Semen, and 22 of Curcumaelongae Rhizoma. Consequently, the compounds and their corresponding targets remained for subsequent analysis.p ≤ 0.01 were selected as the formula targets. Information on the compounds with >10 targets, namely the main active components of ZGP, are listed in A total of 4,131 targets for ZGP were obtained from the STITCH database  with a DC ≥ 0.2. Then, each gene was scored by Materials and Methods 2.2, and 366 protein targets with a GO and KEGG pathway enrichment analyses were executed clarify the characteristics of targets for the key active components of ZGP . These tNASH occurrence and development are correlated to the regulation of multiple genes. Research on the relationship between the gene and gene-environment interactions can help to elucidate the pathogenesis of NASH. In this study, 1,551 NASH-related targets were collected from the OMIM (2021.4), DisGeNET , and GeneCards  database. The network of NASH-related genes containing 711 nodes and 17,280 edges is shown in A Venn diagram was constructed to acquire the common targets of the ZGP bioactive component targets and the NASH-related targets . The acqp < 0.01), respectively. By comparing with the results of disease genes, we found that 1,158 and 61 GO were terms significantly associated with the disease targets for MF and BP, respectively. We selected the common GO terms shown in Go enrichment analysis was performed to identify common features of the formula targets and disease genes in terms of GO annotation, respectively. The number of GO terms that are significantly associated with the formula targets for MF, BP, and CC was 2,424, 178, and 119 (p < 0.05). The top pathways (count number ≥10) included African trypanosomiasis, the adipocytokine signaling pathway, NAFLD, insulin resistance, the FoxO signaling pathway, the AMPK signaling pathway, the PPAR signaling pathway, type II diabetes mellitus, the longevity regulating pathway, and the mTOR signaling pathway , interleukin 6 (IL6), and tumor necrosis factor-α (TNF-α). The qRT-PCR results showed that PTEN mRNA expression was down-regulated while IL6 and TNF-α mRNA expression was up-regulated in model rats. After 4 weeks of treatment with ZGP, PTEN mRNA expression increased, while IL6 and TNF-α mRNA expression decreased . WesternWe observed GO terms for ZGP targets related to oxidative stress and reactive oxygen species. Hepatic mitochondrial ROS has a pivotal role in the development of NASH [18]. Oxidative stress can cause hepatocellular damage and death. The occurrence and development of liver injury can be induced by ROS, which promotes lipid peroxidation . Hence, The levels of HNE and MDA, products of lipid peroxidation, were quantified in the liver. We also evaluated the expression of HNE and MDA. The results showed that HNE and MDA expression were significantly increased compared to the control . HNE andTransmission electron microscopy was used to analyze the morphology of liver cells and lipid accumulation. In the control group, there were fewer lipid vacuoles with normal mitochondria and endoplasmic reticulum morphology compared with the other group. Abundant lipid droplets can be seen in the model tissues, the ultrastructure of liver cells has changed significantly, chromatin condenses on the edges, the endoplasmic reticulum expands, and mitochondria contract. Additionally, we found a significantly high level of autophagic vacuoles in tissue from the model group. Cellular integrity was maintained and lipid vacuoles were decreased in the treatment groups. ZGP significantly inhibited lipid accumulation and the structure in the liver appeared normal, especially in animals from the high-dose group . We alsoWe determined the level of autophagy in mice by assessing the conversion of LC3 from cytosolic LC3-I to LC3-II, as well as the levels of Beclin1 and p62. The results of qRT-PCR revealed that Beclin1 and LC3 expressions was increased, while the expression of p62 was reduced in the model group, compared with the control , indicatWe examined the expression of Mfn1, Mfn2, Opa1, Fis, and Drp1 by immunohistochemistry and qRT-PCR. The results showed that the expression of Mfn1, Mfn2, and Opa1 was down-regulated, while that of Fis and Drp1 was up-regulated in the model group, compared with the control . TreatmeWe also found that PINK1 and Parkin expression was increased in animal in the model group, compared with those in the control . Thus, ZChinese medicine is currently the most widely used form of complementary and alternative medicine. It is holistic in its effects and works on multiple targets, through multiple channels. ZGP is a Chinese herbal medicine that has been proven to improve NASH liver damage. In recent years, network pharmacology research on disease treatment has attracted widespread attention. Based on modern computer simulation technologies, this method is an effective method for screening and predicting drug targets. In the present study, network pharmacology was used to explore the material basis and mechanism of ZGP in the treatment of NASH. TCM monomers were selected based on the common signal pathway, and the PPI network and transcription factor prediction networks were constructed. In addition, we performed animal experiments to confirm that ZGP could improve NASH.In vivo studies were performed using a rat model of HF-induced NASH, which has been widely used in researched related to NASH , which in turn aggravates mitochondrial damage and apoptosis . We retrvia the expression of related proteins.Autophagy is a basic catabolic process that degrades abnormal or unnecessary cell components through lysosomal activity, thereby improving cell survival . During In conclusion, using network pharmacology, we show that ZGP acts on NASH through multi-compounds, multi-targets and multi-pathways. Furthermore, ZGP decreased the serum levels of TG, TC, LDL, ALT, and AST in NASH rats, and suppressed the levels oxidative stress. ZGP inhibited autophagy by mitochondrial fusion and fission. These findings provide novel insights into the mechanisms underlying the effects of ZGP in NASH.


Mechanical force, being so ubiquitous that it is often taken for granted and overlooked, is now gaining the spotlight for reams of evidence corroborating their crucial roles in the living body. The bone, particularly, experiences manifold extraneous force like strain and compression, as well as intrinsic cues like fluid shear stress and physical properties of the microenvironment. Though sparkled in diversified background, long noncoding RNAs (lncRNAs) concerning the mechanotransduction process that bone undergoes are not yet detailed in a systematic way. Our principal goal in this research is to highlight the potential lncRNA-focused mechanical signaling systems which may be adapted by bone-related cells for biophysical environment response. Based on credible lists of force-sensitive mRNAs and miRNAs, we constructed a force-responsive competing endogenous RNA network for lncRNA identification. To elucidate the underlying mechanism, we then illustrated the possible crosstalk between lncRNAs and mRNAs as well as transcriptional factors and mapped lncRNAs to known signaling pathways involved in bone remodeling and mechanotransduction. Last, we developed combinative analysis between predicted and established lncRNAs, constructing a pathway–lncRNA network which suggests interactive relationships and new roles of known factors such as H19. In conclusion, our work provided a systematic quartet network analysis, uncovered candidate force-related lncRNAs, and highlighted both the upstream and downstream processes that are possibly involved. A new mode of bioinformatic analysis integrating sequencing data, literature retrieval, and computational algorithm was also introduced. Hopefully, our work would provide a moment of clarity against the multiplicity and complexity of the lncRNA world confronting mechanical input. Mechanic force is recognized as a crucial factor regulating cellular physiological properties and directing cell fate . Particu2+)-permeable channels, was proven to be another mechanosensor essential for bone homeostasis. Via the critical intracellular Ca2+ sensor Ppp3ca, Piezo1/2 would contribute to the dephosphorylation and formation of the NFAT-Yap1-Ctnnb1 transcription factor (TF) network. The TFs were then activated and showed nuclear translocation for downstream gene regulation  and cytoskeleton, as well as membrane channels which contribute to force sensing, are mostly explored. FAs play as the crucial initiator in detecting and transducing extracellular matrix (ECM)-related biomechanical properties. The FA complex functions by having the integrin heterodimer at the cell surface to interact with the extracellular information and subsequently putting docking proteins to connect F-actin bundles . Hence, gulation .via multiple function modes  have gained the limelight for their potent regulation effects. NcRNAs hold a share of almost 98% of all genomic outputs in humans, contributing to an extensive manipulation of the transcriptional activities. MicroRNAs (miRNAs), as the most extensively studied type of ncRNAs, have gained wide recognition for their mechanosensitive roles, which were detailed before . Nonetheon modes . Signifion modes . Alongsion modes . Thus, non modes .Moreover, there are well-documented compelling proofs that lncRNAs participate in the chondrogenic and osteogenic differentiation of MSCs and beyond, indicating the significance of lncRNAs in biophysical processes of bones . Emerginhttp://www.ncbi.nlm.nih.gov/geo/) for inclusion of FS mRNA. GSE112122 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE112122) was finally chosen based on its ideal cell type, experimental strategy, and data quality. Raw data of the gene expression profiles of GSE112122 were downloaded for analysis, and several grouping strategies were developed. Namely, intermittent force group analysis applied differentiated expression comparison based on data from control (GSM3058133-3058135) vs. intermittent force (GSM3058136-3058138). Similarly, static force group analysis utilized strategy as control (GSM3058139-3058141) vs. static force (GSM3058142-3058144). To explore the deviation of mRNA profiles caused by force types, intermittent force (GSM3058136-3058138) and static force (GSM3058142-3058144) are set as grouping modes. The Empirical Analysis of Digital Gene Expression Data in R (edgeR) package (http://www.bioconductor.org/packages/release/bioc/html/edgeR.html) was used to screen out differentially expressed mRNAs (DE mRNAs). Gene ID was converted to gene name and noted for gene type based on the Ensembl database (http://asia.ensembl.org/index.html). Only genes with type annotation as “protein coding” were selected for further analysis, which ruled out several noncoding RNA expression profiles with low confidence. The p-value was calculated with t-test and adjusted for multiple testing using the false discovery rate (FDR) method. A threshold was set as FDR < 0.05 and |log2foldChange (FC)| > 1 for DE mRNA identification. The Pretty Heatmaps (pheatmap) package was exploited to visualize the differences. Top 50 genes with the highest values of |log2foldChange (FC)| were chosen for heatmap creation. All analyses were performed with the R 3.5.0 framework. Intersection of DE mRNAs from intermittent force group and static force group analyses contributed to the list of FS mRNA. DE mRNAs gained from the comparison between profiles of intermittent force and static force were named as force-type-sensitive mRNAs (FTS mRNAs). VENNY 2.1 (https://bioinfogp.cnb.csic.es/tools/venny/index.html) was explored for visualization. Functional annotation for DE mRNAs was conducted based on GO analyses. All functional clustering was assessed by the clusterProfiler package (http://www.bioconductor.org/packages/release/bioc/html/clusterProfiler.html). The Enrichplot package (http://www.bioconductor.org/packages/release/bioc/html/enrichplot.html) and ggplot2 package were implemented to visualize the enrichment results. Significant GO terms were identified with a cutoff of p < 0.05.Systematic searching of datasets concerning mechanical conditions was carried out in the GEO database  for validation of their conservation among species, especially the similarity of sequences compared to their counterpart hsa-miRNAs. CFS miRNAs were uploaded into DIANA-mirPath v3.0 (http://snf-515788.vm.okeanos.grnet.gr/) for KEGG analysis.To identify reliable miRNAs which are sensitive to force among bone cells, we explored and collected the miRNAs which were verified to act in a mechanosensitive way via functional experiments or displayed certified different expression profiles in a force-related situation by qPCR. Cell types included in our work are confined to MSCs and their derivations in bone tissues. Research made before 2010 was excluded, as well as those without highly reliable evidence. CFS miRNAs identified in species other than  miRBase  (http://ath v3.0  (http://http://starbase.sysu.edu.cn/) for prediction. The analysis was based on human genome and hg19 assembly, and the cutoff value was set as CLIP Data ≥ 3 (high stringency). Then, CFS-miRNA-targeting mRNAs were also predicted based on the intersection of datasets from miRTarBase (http://mirtarbase.mbc.nctu.edu.tw), miRDB (http://www.mirdb.org/), and TargetScan (http://www.targetscan.org/mamm_31/). MiRNA–mRNA pairs that gained validation from all three datasets were included. The predicted pairs were then intersected with the FS mRNA. Only mRNAs which were both force sensitive and predicted as miRNA targets were included to get CFS miRNA–FS mRNA pairs. Finally, the lncRNA–CFS miRNA pairs and CFS miRNA–FS mRNA pairs were imported and analyzed in Cytoscape 3.8.1 (https://cytoscape.org/). Pairs which could not form an lncRNA–miRNA–mRNA triplet were excluded. Alongside that, lncRNAs with a degree lower than three were also deleted. The ceRNA network was finally visualized by Cytoscape 3.8.1.Aiming at constructing the potential FR ceRNA network, we first screened out the lncRNA targets of CFS miRNAs, utilizing ENCORI (the Encyclopedia of RNA Interactomes)  (http://RTarBase  (http://), miRDB  . Then, 1 µg of RNA was transcribed to cDNA using a HiScript® III RT SuperMix for qPCR (+gDNA wiper)  according to the manufacturer’s protocol. The qRT-PCR assay was carried out on an ABI QuantStudio 6 system using Taq Pro universal SYBR qPCR Master Mix  according to the manufacturer’s protocol. GAPDH was used as endogenous references. The 2−ΔΔCt method was used to determine the relative quantification of gene expression levels. Primers for all the genes are listed in C3H/10T1/2 cells were purchased from Procell Life Science and Technology Co., Ltd. and were then cultured at 37°C under 5% carbon dioxide using modified Eagle’s medium  supplemented with 10% fetal bovine serum , 100 U/ml penicillin, and 100 μg/ml streptomycin (Invitrogen). The Flexcell FX-5000TM Tension System  was used to apply mechanical cyclical stretch. A total of 5 × 10p-value of <0.05.Interaction relationships between FS mRNA and FR lncRNA were screened out based on the database of ENCORI, which recorded the pairing relationship supported by at least one experiment. Loop relationships were extracted from the ceRNA network and a Ce-loop network was constructed. For co-expression network construction, the expression profile of GSE112122 was first normalized to TPM (transcripts per kilobase million) value, and the Pearson correlation coefficient was then calculated among FS mRNAs and FR lncRNAs. A threshold was set as a COR of >0.8 and a http://www.bioconductor.org/packages/release/bioc/html/TFBSTools.html) as well as JASPAR2016 package (http://www.bioconductor.org/packages/release/data/experiment/html/JASPAR2016.html) were used for calculation, and the cutoff score was set as 95%. The TF–FR lncRNA regulation was later analyzed and visualized by Cytoscape 3.8.1. For possible bidirectional regulation between TFs and lncRNAs, we intersected the FR ceRNA as well as FTR ceRNA network with the TF list gained by TFBS prediction. TF–FR lncRNA pairs predicted to have a ceRNA relationship via miRNAs were then chosen. Triplets which could form the circle as TF–FR lncRNA–CFS miRNA–TF were finally included and visualized.Transcription activity is tightly regulated by TFs via their sequence-specific binding with the TFBSs on genome. We managed to map out the possible regulation of TFs on our FR lncRNAs for elucidation of the potential upstream mechanism. The prediction strategy was based on the position weight matrix (PWM) method . The ups package  . Furthermore, we built the pathway–lncRNA network integrating prediction results of FR lncRNA with verified data of FS lncRNA, which was then visualized by Cytoscape.As for the intermittent force group, 1,989 DE mRNAs were screened out, including 886 upregulated and 1,103 downregulated mRNAs. Additionally, 451 DE mRNAs were validated in the static force group, with 281 and 170 DE mRNAs found to be upregulated and downregulated, respectively. The discrepancy of the DE mRNA volumes between two force types conformed to the conclusion of the original study . The intp < 0.05, 396 GO terms were screened out, with 359 in the biological process (BP), 21 in the cellular component (CC), and 13 in the molecular function (MF) based on the FS mRNAs. As for the FTS mRNA group, total terms of GO are counted as 582 with 535, 32, 15 for BP, CC, and MF, respectively. BP terms enriched in FS mRNAs are most related to development processes like cellular developments, bone mineralization, and ossification, verifying that the cellular differentiation processes were impacted by applying force. As for CC terms, extracellular matrix, contractile fibers, and communication elements are most enriched among FS mRNAs, suggesting that the force would significantly induce the reaction modes of cells. The mechanically responsive cellular activity could also be indicated by the MF terms enriched in stimulus reception and communication such as receptor ligand activity. Interestingly, when it comes to FTS mRNAs, the GO terms are largely connected with nuclear and chromosome activity, implying the possibility for transcriptional differences when reacting to different force types  to be enriched in our analysis, considering cancer represents the most common model in miRNA studies. Overall, KEGG results of CFS miRNAs highly conform to the established data, ensuring the confidence of the following analysis.In total, research carried out in MSCs, bone marrow stem cells (BMSCs), adipose-derived stem cells (ADSCs), PDLSCs, PDLCs, tendon-derived stem cells (TDSCs), alveolar bone cells (ABCs), primary rat osteoblasts (prOB), osteoblasts, MC3T3-E1 cells, MLO-Y4 osteocytes, and C2C12 cells was included and is listed in ynthesis . Notablyin vitro validation of our prediction, expression changes of 10 FR lncRNAs were checked by qPCR , which further verified the credibility of our prediction. For a BP-based explanation, we screened out several force-responsive pathways which were highly enriched among these pairs (p < 0.05), such as the PI3K-Akt signaling pathway, focal adhesion, regulation of actin cytoskeleton, calcium signaling pathway, and Wnt and Hippo signaling pathways. Connecting the co-expression network with a pathway could further suggest the potential roles of FR lncRNAs  was verified , and it H3K27me3 . In the H3K27me3 . Meanwhiin vitro . Thus, Nin vitro , a deepein vitro . H19 is  pathway . During  pathway . Another pathway . Our wor pathway  and acti pathway  while in pathway . Signifi pathway . Further pathway . Taken t pathway . Besidesargeting . LINC006argeting . SNHG1, argeting  as well argeting . Though in vitro and in vivo , a common bone disorder when patients are in a long-term-immobilization condition like fracture, therapeutic bed rest, and space flight. H19 was found to be downregulated in the MG condition and responsible for disuse-induced bone loss . Its ove in vivo . While m in vivo . Inspiriin vitro . Other tin vitro . Depleti in vivo . Upregul in vivo . However in vivo . Nonethe in vivo . Upregul in vivo . Extrinsin silico analysis could pale in comparison with biological experiments, its strength in data processing and network analysis is impeccable. Meanwhile, growing evidences showed that predicted data of lncRNAs concerning mechanobiology could be observed in biological systems. For instance, based on the expression profile of mouse cementoblasts under static compressive force gained from sequencing, H. Liu et al. (Bioinformatics has gained popularity in recent years. Though u et al.  selectedu et al. , where Ru et al. . Howeveru et al. . A limitu et al. . MoreoveUnequivocally, identification of lncRNAs needs a case-by-case basis, yet a systematic illustration is just as important, if not more so, as to provide a stepping stone to uncovering the panoramic view of this specific type of ncRNA. Though a question mark still hangs over the world of lncRNAs against mechanic cues, our work, hopefully, would produce a moment of clarity to break this impasse.


The study aims to explore potential mechanisms of YiSui NongJian formula (YSNJF) in treating myelodysplastic syndromes (MDS) by network pharmacology-based strategy. Active compounds and corresponding potential therapeutic targets of YSNJF were harvested by utilizing the database of TCMSP  and BATMAN-TCM . MDS targets were adopted from GeneCard, KEGG (Kyoto Encyclopedia of Genes and Genomes), TTD (Therapeutic Target Database), DrugBank, and DisGeNet. Then a network of YSNJF- compounds-target-MDS network was harvested. The protein–protein interaction (PPI) network was then generated by the Sting database and subjected to Cytoscape software to harvest major and core targets network by topological analysis. Genes from the core targets network were further subjected to Gene Ontology (GO) and KEGG enrichment analysis to figure out potential targeting pathways. Finally, a compounds-targets-pathways network was generated by Cytoscape. A total of 210 active compounds and 768 corresponding potential therapeutic targets were harvested from ingredients of YSNJF. MDS was shown to have 772 potential treating targets with 98 intersected targets corresponding to 98 active compounds in YSNJF. Topological analysis revealed that 15 targets formed the core PPI network. Further, GO and KEGG enrichment analysis revealed that those core targets were mainly enriched on cell cycle- and immune-related pathways. The present study revealed that therapeutic effects of YSNJF on MDS might be achieved through regulating cell cycle- and immune-related pathways.  Myelodysplastic syndromes (MDS) are a group of clonal bone marrow neoplasms characterized by clonal proliferation of hematopoietic stem cells, ineffective hematopoiesis, myelodysplasia, peripheral blood cytopenia, recurrent genetic abnormalities, and a high risk of evolution to acute myeloid leukemia (AML), and manifested by morphologic dysplasia in hematopoietic cells and by peripheral cytopenia . For patRadix Astragali preparata), dangshen (Codonopsis pilosula), baizhu , fuling (Poria cocos), shuizhi (Hirudo), etc. From our previous clinical practice, we have found that YSNJF together with chemotherapy could significantly improve hemogram parameter and MDS symptoms, which could further promote the prognosis of MDS patients when compared with chemotherapy alone, especially in low-risk MDS patients [Traditional Chinese herbal medicine has been widely adopted for various disease treatments for more than 2,000 years. Currently, integrative medicine by combining traditional Chinese medicine with western medicine was shown promising therapeutic effects with properties of economical and practical . YiSui Npatients . Althougpatients . HoweverNetwork pharmacology for exploring mechanisms of traditional Chinese herbal medicine, as first proposed by Li et al. , was ablTherefore, the present study was designed to determine the potential mechanisms of ingredients in YSNJF in treating MDS by utilizing the method of network pharmacology. Our research may help in MDS drug screening, improve the formulation of YSNJF, and may provide a useful reference for the exploration the therapeutic mechanism of other traditional Chinese medicine.https://tcmspw.com/tcmsp.php) and BATMAN-TCM [http://bionet.ncpsb.org/batman-tcm/), were utilized for screening of active compounds and corresponding potential therapeutic targets of YSNJF. Herbal medicines in YSNJF were firstly subject to TCMSP, oral relative bioavailability (OB) ≥ 30%, and drug-likeness (DL) ≥ 0.18 were set as threshold for active compounds and corresponding potential therapeutic targets screening. And if herbal medicines in YSNJF were not included in TCMSP, those herbal medicines were then subject to BATMAN-TCM. The screening threshold in BATMAN-TCM was set as drug-target similarities score ≥ 20 and adjusted P-value < 0.05.Two online databases, TCMSP  (TraditiTMAN-TCM  (Bioinfohttps://www.genecards.org/), KEGG , TTD [http://bidd.nus.edu.sg/group/cjttd/), DrugBank (https://go.drugbank.com/), and DisGeNet (https://www.disgenet.org/) with the term of ‘Myelodysplastic Syndrome/myelodysplastic syndrome’. Duplicated targets were removed to harvest the final MDS target sets.MDS targets screening were performed by search several databases like GeneCard (p/), TTD   network construction and major and core targets network identificationhttps://string-db.org). Minimum required interaction score was set as ‘medium confidence = 0.4’ while other parameter remains as default. Then generated PPI network was loaded to Cytoscape. A build-in module of CytoCNA was further utilized to generate major targets network when Betweenness, Closeness, Degree/Connectivity, Eigenvector, Local Average Connectivity-based method, and Network of each node were all larger than the median. Core target networks were generated from major target networks by topological analysis.PPI network of intersected targets was generated by uploading intersected targets to the online database of String (http://metascape.org/). Cutoff values in this database were set as follows: Min Overlap = 3; Min Enrichment>1.5; P-Value Cutoff = 0.01. Top 20 enriched pathways of GO  and KEGG were made visualized in a bubble chart by utilizing an online bioinformatics tool . The size of the bubble represents the number of targets enriched in the indicated pathway and the color of the bubble represents the P-value of enrichment.To better interpret the function of those intersected targets, pathway enrichment analyzes by GO and KEGG were performed by using Metasacpe  to exclude invalid compound-target pairs. Finally, a total of 210 active compounds and 768 corresponding targets were generated. Some of the compounds were found to have to exist in many herbal medicines and to have multiple targets  and 768 corresponding targets were identified by using GeneCard, KEGG, TTD, DrugBank, and DisGeNet. 98 drug-related genes, which may be the targets of YSNJF in treating MDS, were harvested by using a Venn tool. PPI network of compounds-targets was then generated and core targets were identified by using Cytoscape together with String database. GO and KEGG enrichment analysis of 15 core targets revealed that PI3K/AKT-, MAPK/ERK-, and JAK/STAT3-mediated cell cycle- and immune related-signaling pathway were the most enriched ones. Therefore, genes in those signal pathways may be critical targets for MDS treatment.In the current study, network pharmacology methods were used to explore potential targets and mechanisms of YSNJF in the treatment of MDS. A total of 210 active compounds were identified by using TCMSP (OB ≥ 30% and DL ≥ 0.18) and BATMAN-TCM  has been widely adopted in China and surrounding countries for thousands of years . Of noteAs previously reported that natural products derived products were able to fight against cancer-like polysaccharides, proteins, and organelles from fungus could be utilized for anti-cancer drug screening , herbal Topological analysis harvested core targets network also revealed some clues which may help to understand the therapeutic action of YSNJF. TP53, a typical tumor-inhibiting gene, was reported to upregulating the expression of BAX while downregulating Bcl-2 so that it could promote target cell apoptosis. AKT serine/threonine kinase 1 (AKT1), also known as protein kinase B alpha , was demonstrated to be involved in process of cell survival, proliferation, and anti-apoptosis once phosphate by PI3K signal pathway. MAPKs could be activated by various cytokines and extracellular stimulus and MAPKs signal pathways were shown to be critically involved in cell differentiation and proliferation. MAPK1 (ERK1) and MAPK3 (ERK2) were the most important MAPKs for signal transduction. CCND1, whose up-and-down-regulation could profoundly change the course of the cell cycle, is a vital gene in the cell cycle, especially in the process for cell from the G1 phase to the S phase. EGFR, a protein encoded by this gene is a tyrosine-protein kinase, was shown to participate in cell migration via regulating Ras-MAPK-ERK and PI3K-AKT signal pathways. Those results further suggested that MAPK and PI3K-AKT signal pathways were profoundly regulated by YSNJF in the treatment of MDS.+ cells was highly associated with over-activation of the p38 MAPK signaling pathway in low-risk MDS patients [+ cells and improve ineffective hematopoiesis in low-risk MDS patients [The above-mentioned analysis was further validated by enrichment analysis from GO and KEGG. Particularly, KEGG enrichment analysis revealed that MAPK and PI3K-AKT signaling pathways were among the top enriched pathways. Research from patients of low-risk MDS has found that bone marrow stromal cells and MDS clonal cells secrets excessive hematopoietic inhibitory factors like TNF-α, IFN-γ, TGF-β, and VEGF. Those factors induce hyperphosphorylation of the p38 MAPK signaling pathway and subsequently induced the immoderate apoptosis of bone marrow hematopoietic stem/progenitor cells, especially the normal stem/progenitor cells ,31. As dpatients . Anotherpatients . Mammalipatients . Aberranpatients , includipatients ,35–38. Cpatients , suggestpatients . Togethe+ T cells. The transcriptional signature of Th17 cells was RORγt and these kind cells were known to secret pro-inflammatory cytokines, like IL-17, IL-21, and IL-22. Report has demonstrated that T cell-mediated immune dysfunction is a key characteristic of MDS [Another interesting finding from our result was that the therapeutic effects of YSNJF to MDS might also be achieved in an immunomodulatory manner. From our GO and KEGG analysis, we have found that leukocytes differentiation and Th17 cell differentiation signaling pathways were significantly enriched in the core targets network. Th17 cells were differentiated from CD4c of MDS . Imbalanc of MDS ,43. Alsoc of MDS .Also, even not included in the current work, cancer early detection is a well-acknowledged critical pre-step for effective cancer treatment. Cost-effectiveness early detection method was of great need. An interesting work performed by Low et al. developed a smartphone-based electrochemical biosensing system for the detection of cancer biomarkers with good accuracy and recovery ratio , which iin vitro and in vivo could be adopted in future research. Finally, limited by current pharmacology technology, the dose-effect relationship between YSNJF and MDS was not able to be determined.This research has several limitations. Firstly, as proved by previous reports, signaling pathways could cross regulate each other, key signaling pathways involved in therapeutic effects of YSNJF to MDS still need to be explored. Secondly, works done in the current study were mainly obtained from the bioinformatic analysis, experimental validations both By utilizing network pharmacology, the present study has revealed for the first time that therapeutic effects of YSNJF to MDS might be mainly achieved by quercetin, luteolin, crocetin, baicalein, nobiletin, and tanshinone IIb via regulating cell proliferation-related and immune-related signal pathways. Our research has provided a direction for specific mechanism exploration of YSNJF, several potential targets for MDS treatment, and a promising reference for exploring the mechanism of other TCM formulas.