To elucidate the mechanism by which DEC2 modulates the proliferation of mesangial cells (MCs) in lupus nephritis (LN).−/− mice and their serum-treated MCs were used as in vivo and in vitro LN model. MCs knocked down of DEC2 and overexpressed with DEC2 were also established. The expression of DEC2 was measured in the kidneys of Fcgr2b−/− mice and LN serum-treated MCs using RT-qPCR and Western blot. MCs proliferation was detected by 5-ethynyl-2′-deoxyuridine (EdU) labeling assay and PCNA expression using immunofluorescence. The glucose metabolism was evaluated in LN serum-treated MCs, and the levels of lactate production, glucose consumption, ATP production and mitochondrial membrane potential were assayed. The glycolysis and mitochondrial respiration function of the MCs were measured using the Extracellular Flux Analyzer. The extracellular acidification rate (ECAR) and oxygen consumption rate (OCR) were dynamically monitored and multiple important bioenergetic parameters can be calculated. The expression of Toll like receptor 4 (TLR4) and glucose transporter 1 (GLUT1) were detected in the MCs. Multiple signaling proteins were screened.The 32-week-old female Fcgr2b−/− LN mice. Knockdown of DEC2 inhibited LN serum-induced MCs proliferation. DEC2 was associated with the glucose metabolism in LN serum-treated MCs. DEC2 regulated glycolysis in LN serum-treated MCs. DEC2 was associated with mitochondrial fitness in LN serum treated MCs. DEC2 activated MCs glycolysis through TLR4 and glucose transporter 1 (GLUT1) regulation. DEC2 regulated MCs proliferation through two signaling pathways including dependent and independent of glycolysis, which located in the downstream of TLR4 signaling.DEC2 was found overexpressed in the kidney of Fcgr2bKnockdown of DEC2 expression inhibits the proliferation of MCs through suppressed glycolysis and p38 MAPK/ERK pathway in LN. Lupus nephritis (LN), a refractory glomerulonephritis found in the patients with systemic lupus erythematosus, commonly leads to chronic renal failure Clarke . An impoMesangial cells (MCs), locate among the capillary loops in the glomeruli, provide structural support and maintain the glomerular function in kidneys , which were from Jackson Laboratory . The Fcgr2b−/− mice can spontaneously develop a lupus-like pathological changes including LN after 32 weeks old  with specific Fcgr2b gene deficiency  for 1 h in a dark wet box. The slides were then rinsed in distilled water for 5 min and stained with 100 µL hematoxylin solution for 30 s, and rinsed in distilled water. The samples were differentiated by hydrochloric acid–ethanol mixtures, rinsed in distilled water and sealed with neutral balsam.The renal slides (4 μm thickness) were deparaffinized to distilled water and incubated with citrate buffer for antigen microwave retrieval. The slides were then washed with phosphate-buffered saline (PBS) and blocked using PBS containing 5% bovine serum albumin (BSA). The slides were incubated with primary antibodies including anti-DEC2 (1:200) and anti-PCNA  overnight in a wet box at 4 °C. The slides were then incubated with corresponding HRP-conjugated secondary antibodies (ThermoFisher Scientific) at room temperature for 1 h and followed by diaminobenzidine and hematoxylin staining.The MCs used in this study were from a mouse kidney mesangial cell line , purchased from Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences . The MCs were cultured in the Dulbecco’s modified Eagle medium  supplemented with 10% fetal bovine serum (Gibco). Different treatments of the cells were separately represented as follows: (1) The MCs were serum-starved overnight and exposed to LN serum (5% in DMEM) or control serum (5% in DMEM) for 24 h. The serum was detected for the endotoxin in advance and only serum with undetectable level of endotoxin could be used in this study. (2) The MCs were transfected with shRNA targeting DEC2 (Sh-DEC2) or negative control (Sh-NC). (3) The MCs were transfected with lentiviral vector overexpressing DEC2 (Lv-DEC2) or negative control (Lv-NC). (4) The MCs were treated with multiple inhibitors of signaling pathways, including TLR4-specific antagonist chloroquine phosphate , PI3K inhibitor LY294002 (Beyotime Biotechnology), Akt inhibitor AZD5363 (Beyotime Biotechnology), NF-κB inhibitor BAY 11-7082 (Beyotime Biotechnology), p38 MAPK inhibitor SB203580 (Beyotime Biotechnology) and Erk inhibitor FR 180204 according to the manufacturer’s instructions.−ΔΔCT method.The total RNAs were extracted from the MCs with TRIzol regent. The RNA precipitates were quantified with a NanoQuant spectrophotometer . A High-Capacity cDNA Reverse Transcription Kit (ThermoFisher Scientific) was used to reversely transcribe the RNA into cDNA. RT-qPCR was performed with DEC2-specific primers  and using a Rotor-Gene SYBR Green PCR Kit . GAPDH  were used as internal control. Relative RNA expression was determined by the 2The proteins were extracted from the MCs using radio immunoprecipitation assay (RIPA) lysis buffer (Beyotime Biotechnology) containing protease and phosphatase inhibitor cocktail . Equal amount of cell lysates were separated by sodium dodecylsulfate-polyacrylamide gel electrophoresis (SDS-PAGE) at suitable concentration according to the molecular weight of target protein. The proteins were then transferred to a polyvinylidene difluoride (PVDF) membrane , which was blocked by 5% BSA and then incubated with primary antibodies overnight in a wet box at 4 °C. Primary antibodies used in this study included anti-DEC2 , TLR4 , glucose transporter 1 , p-p38/p38 , p-Erk/Erk , p-PI3K/PI3K , p-Akt/Akt , NF-κB , GAPDH  and β-actin . After incubation with the corresponding secondary antibodies , the positive bands were visualized using the BeyoECL Plus chromogenic kit (Beyotime Biotechnology), and analyzed by the Tanon-4200 Gel Imaging System .To determine the proliferation level of MCs, we performed the 5-ethynyl-2′-deoxyuridine (EdU) labeling assay and observed the expression level of PCNA using immunofluorescence. The incorporation of EdU was observed with a Zeiss Axio Observer Z1 microscope  after the MCs were incubated with EdU solution (Beyotime Biotechnology) according to the manufacturer’s instructions. For the staining of PCNA, the MCs were fixed in 4% paraformaldehyde solution and permeabilized with 0.5% Triton X-100 for 15 min. After blocked by 5% BSA, the cells were incubated with anti-PCNA antibody  and corresponding secondary antibody (ThermoFisher Scientific) and 4′,6-diamidino-2-phenylindole . The samples were observed with a Carl Zeiss microscope.l-Lactate Assay Kit  according to the manufacturer’s instruction. The results were reported and analyzed with a Synergy4 microplate reader .The MCs were treated with different stimuli or inhibitors in DMEM for 24 h. The concentration lactate was determined by using The consumption of glucose by MCs was measured with 2-NBDG, a fluorescent glucose uptake probe (ThermoFisher Scientific). The cells were seeded into a 96-well plate and treated with LN serum or control serum for 24 h. Then the MCs were rinsed with Hanks balanced salt solution  and incubated with 100 μM 2-NBDG at 37 °C for 30 min. The results were reported and analyzed with a Synergy4 microplate reader (BioTek Instruments).The Mitochondrial Membrane Potential Assay Kit with JC-1 (Beyotime Biotechnology) was used to detect the mitochondrial membrane potential of MCs treated with or without LN serum. After treatments for 0, 1, 2, 4 and 6 h, the cells were rinsed with HBSS and incubated with 10 μM JC-1 at 37 °C for 30 min. The fluorescent intensity of the cells was detected according to the manufacturer’s instructions.g for 5 min at 4 ºC. The supernatant was mixed well with the ATP detecting reagent (containing firefly luciferase and luciferin) and measured on a Synergy4 microplate reader (BioTek Instruments), which has a standard luminescence setting.The ATP Assay Kit (Beyotime Biotechnology) was used to detect the ATP level of MCs treated with or without LN serum. Briefly, the MCs were treated with lysis buffer to release the cellular ATP. Then the lysate was centrifuged at 12,000https://www.agilent.com).The glycolytic function of MCs in each group was detected using a Seahorse XF Glycolysis Stress Test Kit . The change of glycolysis in treated cells was monitored in real-time by directly probe the values of extracellular acidification rate (ECAR) using the Extracellular Flux Analyzer . The MCs were seeded in a XFe24 culture plate and treated with different stimuli or inhibitors in DMEM for 24 h. The medium was then replaced by the Seahorse XF assay medium according to the manufacturer's instruction until assay. The ECAR was dynamically monitored along with the sequential addition of glucose (10 mM), oligomycin (1 µM), and 2-deoxyglucose . Several important parameters including glycolysis, glycolytic capacity and glycolytic reserve can be calculated (https://www.agilent.com).The mitochondrial function of the MCs in each group was detected using a Seahorse XF Cell Mito Stress Test Kit (Agilent Technologies). The change of mitochondrial energy pathway in treated cells was monitored in real-time by directly probe the values of oxygen consumption rate (OCR) using the Extracellular Flux Analyzer . The MCs were seeded in a XFe24 culture plate and treated with different stimuli or inhibitors in DMEM for 24 h. The medium was then replaced by the Seahorse XF assay medium according to the manufacturer's instruction until assay. The OCR was dynamically monitored along with the sequential addition of oligomycin (100 µM), FCCP (100 µM), and rotenone/antimycin A (50 µM). Several important parameters including basal respiration, ATP production-related respiration, maximal respiration, spare capacity and proton leak-related respiration can be calculated . The data are shown as the mean ± standard deviation. The data were subjected to t-test or one-way ANOVA with a post hoc multiple comparison. A −/− mice spontaneously developed LN-like symptoms from 32-week old . Using orthotopic injection method, the kidneys of the Fcgr2b−/− mice were administered DEC2-shRNA-AAV (Sh-DEC2) or NC-shRNA-AAV (Sh-NC). The level of urinary ACR in Fcgr2b−/− mice with Sh-DEC2 was significantly decreased than that in Fcgr2b−/− mice with Sh-NC (P < 0.01), suggesting that knockdown of DEC2 alleviated the development of LN proteinuria in Fcgr2b−/− mice . The MCs transfected with DEC2-specific shRNA (Sh-DEC2) showed significantly decreased level of DEC2 mRNA compared with that in MCs transfected with negative control shRNA  significantly activated the TLR4 pathway other than Lv-NC Fig. A. We theTo determine whether glycolysis activation is responsible for DEC2-induced MCs proliferation, EdU staining was used to evaluate the proliferation of MCs with overexpression of DEC2 and glycolysis inhibitor 2-DG. Significantly increased MCs proliferation was observed in MCs with overexpression of DEC2. This elevation could be completely suppressed after CP treatment, but only partly inhibited by 2-DG treatment Fig. A. This rLN, an important risk factor for mortality in systemic lupus erythematosus, is one kind of immune complex-mediated glomerulonephritis (Lech and Anders −/− mice, a LN model proved by proteinuria and pathological changes of renal tissues. Increased expression of DEC2 was found not only in the kidney of Fcgr2b−/− mice, but also in the MCs treated with LN serum, compared to those in corresponding controls. Furthermore, proliferative markers including PCNA expression and EdU staining suggested that excessive proliferation was observed in the kidney of Fcgr2b−/− mice and in the LN serum-treated MCs. To determine whether proliferative MCs are associated with the expression of DEC2, we knocked down the expression of DEC2 both in renal tissue of mice and in MCs. The results indicated that decreased proliferative markers were detected in both renal tissue and MCs exposed to LN circumstance. In addition, alleviated proteinuria and renal tissue compression were found in DEC2-knocked down mice. These data suggest that DEC2 plays critical role in regulating the proliferation of MCs in LN.Serum from the LN model animals or patients is suitable to simulate the LN circumstance exposed to MCs (Liu et al. Cell proliferation is modulated by variety of proliferative signals from extracellular and intracellular environment. Energy metabolism is also a factor that cannot be ignored to promote the cell proliferation (Lunt and Vander Heiden To elucidate the regulative mechanism of bioenergetics in MCs proliferation and the role of DEC2, we analyzed the glycolysis and mitochondrial respiration function in this process. By dynamically monitoring ECAR of the MCs along with the sequential addition of glucose, oligomycin and 2-DG, multiple glycolysis-related parameters including glycolysis, glycolytic capacity and glycolytic reserve can be calculated. Both glycolysis level and glycolytic capacity significantly increased in the LN serum-treated MCs compared with those in controls, suggesting that LN serum activates the glycolysis in MCs. These increases in glycolysis level and glycolytic capacity can be partly reversed after knockdown of DEC2 in the MCs, indicating that DEC2 regulates glycolysis in LN serum-treated MCs. Then we evaluate the mitochondrial respiration function in MCs. By dynamically monitoring OCR of the MCs along with the sequential addition of oligomycin, FCCP and rotenone/antimycin A, multiple mitochondrial respiration-related parameters including basal respiration, ATP production-linked respiration, maximal respiration, spare capacity and proton leak can be calculated. LN serum treatment can not influence the basal respiration and ATP production-linked respiration of the MCs, and no obvious effects can be found in DEC2-knocked down cells. These data hint that energy provided for MCs proliferation seems dose not come from the mitochondrial respiration. However, increased maximal respiration and spare capacity were found in the LN serum-treated MCs compared with those in controls, and DEC2 knockdown partly reversed these changes. Spare capacity is an important index representing mitochondrial fitness, and increased spare capacity is indicative of elevated mitochondrial activity (Everts et al. Lastly, we reported that downregulation of DEC2 and the TLR4 signaling inactivation inhibited the proliferation of MCs (Qi et al. To determine whether glycolysis activation is responsible for DEC2-induced MCs proliferation, we evaluated the proliferation of the MCs after treatment with glycolysis inhibitor 2-DG. Results showed that DEC2-induced proliferation could only be partly inhibited by 2-DG, however, it was completely suppressed after CP treatment. These data hint that other signaling pathway may participate in DEC2/TLR4-induced MCs proliferation except for glycolysis. Then we screened multiple signaling pathway proteins, and found that p38 MAPK, Erk, PI3K/Akt and NF-κB were activated in MCs with overexpression of DEC2. These pathways can be inhibited after CP treatment. To distinguish the signaling pathways associated with or without glycolysis-related MCs proliferation, corresponding inhibitors were used to detect the change of glycolysis level in DEC2-overexpressed MCs. The result showed that PI3K/AKT pathway was associated with DEC2-induced glycolysis activation, and p38 MAPK, ERK and NF-κB were independent of this process. The cell proliferation assay indicated that suppression of p38 MAPK and ERK signaling can partly inhibited DEC2-induced MCs proliferation, and combined use of p38 MAPK/ERK inhibitors and 2-DG completely inhibited DEC2-induced MCs proliferation. These data confirm that DEC2 regulates MCs proliferation through two signaling pathways including dependent and independent of glycolysis, which locates in the downstream of TLR4 signaling.In conclusion, to elucidate the mechanism by which DEC2 modulates the proliferation of MCs in LN would provide a better understanding of LN progression, and reveal a potential target for LN treatment. Here we found that DEC2 regulates MCs proliferation through TLR4 signaling pathway, and unexpectedly, we identified two pathways located in the downstream of TLR4 signaling. One is glycolysis-dependent, and modulated by PI3K/AKT pathway. The other one is glycolysis-independent, and controlled by p38 MAPK and Erk signaling. Knockdown of DEC2 expression inhibits the proliferation of MCs through suppressed glycolysis and p38 MAPK/Erk pathway in LN.


We screened out 27 active ingredients and 251 effective targets of BHDH Decoction, 3405 MS-related targets, and 133 intersection targets between BHDH Decoction and MS. Protein-protein interaction network identified tumor protein P53, Serine/threonine-protein kinase AKT, epidermal growth factor receptor, Estrogen Receptor 1, and jun proto-oncogene as critical targets. Gene ontology analysis showed that these targets were mainly involved in the cellular response to chemical stimulus, response to oxygen-containing compound, cellular response to endogenous stimulus, response to an organic substance, and response to chemical, etc. Kyoto encyclopedia of genes and genomes pathways were mainly enriched in endocrine resistance, pathways in cancer, and the ErbB signaling pathway, etc. Molecular docking results showed that emodin and stigmasterol are strongly associated with Serine/threonine-protein kinase AKT, Estrogen Receptor 1, epidermal growth factor receptor, sarcoma gene, and tumor protein P53. This study preliminarily revealed the multi-component, multi-target, and multi-channel mechanism of BHDH Decoction in treating MS. It provides a reference for in vitro and in vivo research and clinical application of BHDH Decoction in the treatment of MS.Menopausal syndrome (MS) refers to a series of symptoms with autonomic nervous system dysfunction caused by decreased sex hormones before and after menopause. Baihe Dihuang (BHDH) decoction positively affects MS, but its mechanism remains unclear. This study aimed to reveal the underlying mechanism through network pharmacology. The components of the BHDH Decoction were found through HERB, while corresponding targets were obtained from the HERB, Drug Bank, NPASS, Targetnet, and Swisstarget databases. The MS targets were obtained from GeneCards and OMIM. STRING was used to construct the protein-protein interaction networks. OmicShare tools were used for Gene Ontology and Kyoto encyclopedia of genes and genomes analyses. Finally, Autodock Vina 1.1.2 software ( Western medicine treats perimenopausal syndrome with menopausal hormone therapy and psychotherapy as the primary means. Supplementing with exogenous estrogen to maintain the function and state of estrogen target organs in vivo has a definite curative effect on alleviating related clinical symptoms. However, studies have shown that long-term estrogen use may increase the risk of breast cancer, endometrial cancer, and cardiovascular diseases.Menopausal syndrome (MS), also known as perimenopausal syndrome, is characterized by autonomic nervous system dysfunction caused by ovarian failure, pituitary hyperfunction, or low estrogen level, often accompanied by symptoms such as menstrual disorder, hot flashes, hyperhidrosis, sleep disorder, and mood disorder. The treatment of Menopause syndrome in traditional Chinese medicine mainly focuses on nourishing the kidneys and yin, calming the heart, and tranquilizing the mind. Baihe Dihuang (BHDH) decoction originated from the “Synopsis of Golden Chamber” in the Han Dynasty, which is a particular prescription for the treatment of “lily disease.” In this prescription, Lily is used as the principal drug, which has the effects of nourishing yin, moistening lungs, clearing the heart, and tranquilizing the mind; Rehmanniae Radix is used as an assistant, which has the function of clearing heat and cooling blood, nourishing yin, and promoting fluid. The compatibility of the lily bulb and Rehmanniae Radix has the functions of Nourishing Yin, clearing heat, and tonifying the heart and lungs. Modern research shows that BHDH Decoction has antidepression and antianxiety functions, regulates subhealth, and improves sleep. This is especially true in treating MS, which causes hot flashes, sweating, sleep disorders, and emotional disorders.MS belongs to the categories of “dirty mania,” “depression syndrome,” and “lily disease” in traditional Chinese medicine. Its onset is caused by the gradual decline of kidney qi, exhaustion of “tiangui,” and imbalance of yin and yang.,7 However, because of the complexity of the active components in BHDH Decoction and the diversity of potential regulatory targets in the human body, it is challenging to describe the scientific basis and potential pharmacological mechanism of BHDH Decoction in the treatment of MS using conventional methods.Some studies have explored the mechanism of BHDH Decoction in treating MS through clinical efficacy or animal experiments.This study used network pharmacology to explore the potential mechanism of BHDH in the treatment of MS. Molecular docking technology was used to virtually combine the practical active components and receptor protein molecules in BHDH Decoction to explore its action targets and binding sites and elaborate the synergistic mechanism of multi-component, multi-target, and multi-channel BHDH Decoction, to provide a theoretical basis for the clinical treatment of MS.Based on network pharmacology and molecular docking methods, we studied the mechanism of BHDH Decoction in treating MS, and the flow chart of the research methods is shown in Figure http://herb.ac.cn/) is a high-throughput and reference-guided database of traditional Chinese medicine. Its Chinese name is “Ben Cao Zu Jian,” which integrates multiple databases of traditional Chinese medicine and contains the most comprehensive list of traditional Chinese medicines and components.HERB (https://go.drugbank.com/) and the NPASS (http://bidd.group/NPASS/) databases. All components of BHDH were selected based on oral bioavailability (OB) ≥ 30% and drug-like (DL) ≥ 0.18 from the pharmacological database and analysis platform of the Chinese medicine system . The bioactive compounds that contributed to the therapeutic effect of BHDH were selected, and those with poor pharmacological properties and drug potency were removed. The targets of the 3 databases were intersected, and the intersected targets were combined with the corresponding targets obtained from the Drug Bank and NPASS databases, which are the final targets of BHDH. UniProt (https://www.uniprot.org/) was used to standardize the targets.By searching the words “Lily” and “Rehmanniae Radix,” we obtained the compounds of each herb in BHDH from HERB. The experimentally verified targets of these compounds were downloaded from the Drug Bank  is a searchable, integrative database that provides comprehensive, user-friendly information on all annotated and predicted human genes. The knowledgebase automatically integrates gene-centric data from 150 web sources, including genomic, transcriptomic, proteomic, genetic, clinical, and functional information; Online Mendelian Inheritance in Man  is a comprehensive and authoritative database for studying the relationship between human phenotype and genotype, which contains all known Mendelian diseases and information of more than 16,000 genes . OMIM does not create these data but is a systematic collation and integration of published research results, which were updated daily and obtained free of charge. We use “Menopausal syndrome” as the keyword to screen disease targets in each database and summarize the obtained targets to remove the repeated values. Finally, the obtained targets were standardized using UniProt (https://www.uniprot.org/).Referring to the research method of Lin et al,https://cytoscape.org/, version 3.8.0) to construct the drug-component-target network diagram. Cytoscape is an open-source software platform for visualizing molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles, and other state data. The software was used to analyze the network parameters, including degree, betweenness centrality (BC), and closeness centrality (CC). We used this software to screen the core components and targets of the BHDHT Decoction and the relationship between them.A Venn diagram was drawn using R language to obtain the target of drug-disease interaction, namely the target of the BHDH Decoction for MS. We used Cytoscape (https://string-db.org/) is a database of known and predicted PPI. Interactions include direct  and indirect  associations; they originate from computational prediction, knowledge transfer between organisms, and interactions aggregated from other (primary) databases. We imported the interaction target into STRING to identify the PPI information and visualize the network using Cytoscape. In addition, through further analysis of the PPI network using the MCODE plug-in, potentially important protein function modules were obtained to analyze and explain the biological process in which they participate.STRING (www.omicshare.com/tools), a free online platform for data analysis, and P ≤ .01 was considered statistically significant.GO and KEGG enrichment analyses were performed using the OmicShare tools (https://pubchem.ncbi.nlm.nih.gov/) and saved it in SDF format, then imported it into ChemDraw 3D, used the MM2 module to minimize the energy, obtained the advantage idea of the lowest energy, and saved it in the MOL2 file. The protein structure was downloaded from the Protein Data Bank  and visualized using PYMOL. After dehydration, hydrogenation, charge calculation, and a combination of nonpolar hydrogen with MGtools 1.5.6, the ligand and receptor were stored as PDPQT. Autodock vina 1.1.2 was used to dock the ligand with the receptor, and ideas with high scores were visualized using PYMOL and Discovery Studio.To verify whether the compound had an excellent binding activity with the target, we selected the top 5 hub components of the drug-composition-target network and the top 7 hub targets of the drug-disease target PPI network for molecular docking. We downloaded the 3D structure of the compound from PubChem .A total of 156 compounds from the 2 herbs in the BHDH Decoction were obtained from the HERB database. After screening and removing the repeat values, we obtained 27 active compounds, including 14 from Lily and 13 from Rehmanniae Radix. Finally, 251 targets were obtained for the BHDH Decoction Based on these results from drug-disease targets from STRING, we constructed a PPI network with 133 nodes and 1611 edges using Cytoscape. The results are shown in Figure P value , 499 cellular components (CC), and 730 molecular functions. We saved the first 25 results of each project in a bubble plot for further analysis , and the top 25 pathways from small to large according to P values are shown in Figure A total of 238 pathways were obtained by KEGG enrichment analysis  with a score between −4.25 kcal/mol and 5.0 kcal/mol;12 (34.28%) with a score of −5.0 kcal/mol between 7.0 kcal/mol; and 18 (51.43%) lower than −7.0 kcal/mol. The results of molecular docking between the core components and key targets of the BHDH Decoction in the treatment of MS are shown in Figure The molecular ligands of the 5 main active components screened were docked with 7 key targets, and the docking parameters were as follows Table . It is ge were 3 .57% with In some instances, the decline in estrogen levels caused by ovarian failure leads to a series of autonomic nervous system dysfunctions, often accompanied by hot flashes, insomnia, anxiety, depression, fatigue, and other neuropsychological symptoms. The extensive practice has shown that traditional estrogen replacement therapy can alleviate menopausal symptoms. However, long-term use of estrogen frequently increases the risk of breast, endometrial, and other gynecological cancers. Therefore, there is an urgent need to find complementary and alternative therapies, such as Traditional Chinese medicine. The BHDH Decoction has pharmacological effects, such as improving insomnia, anxiety, and depression. It is a representative prescription for treating MS clinically, but its molecular mechanism for treating MS has yet to be fully clarified. At the same time, BHDH Decoction is a commonly used prescription for the treatment of Lily disease with heart-lung yin deficiency and internal heat syndrome. Modern medicine also includes relevant research. Lily Bulbs have an excellent antioxidant capacity.,16 According to Kan et al, Lily Bulbs ameliorated oxidative stress and lipid metabolism. It can improve liver steatosis in mice fed a high-fat diet. Rehmannia inhibits adipocyte differentiation and adipogenesis. It also plays an antioxidative role in improving the bone structure of osteoporosis rats by improving muscle atrophy.Menopause is a natural physiological process in women. Therefore, the targets of compounds in the BHDH Decoction that do not meet the standards of OB ≥ 30% and DL ≥ 0.18, but have been verified by experiments, are also retained in our study, and these targets were obtained from the Drug Bank and NPASS databases. Finally, 133 common targets were obtained. We then constructed a PPI network and screened the key modules, and found that genes such as TP53, AKT1, EGFR, ESR1, and JUN were essential in this respect. We then analyzed these targets according to the symptoms of MS. Symptoms of MS include vasomotor symptoms ; neuropsychiatric symptoms ; musculoskeletal symptoms ; genitourinary symptoms ; and urinary tract infection. Estrogen plays a vital role in the full function of the female reproductive system as well as in the maintenance of bone metabolism and cognition. Menopause syndrome is closely associated with decreased estrogen secretion. Estrogen therapy alleviates menopause-related symptoms. ESR1 is the central mediator of estrogen, and its encoded transcription factor, estrogen receptor-α, plays a crucial role in regulating the hormone response of estrogen-sensitive tissues.,25 ESR1 is broadly expressed in the central nervous system and peripheral tissues, including adipose tissue, skeletal muscle, liver, and immune cells. Skeletal muscle ERα plays a critical and protective role in regulating mitochondrial function, metabolic homeostasis, and insulin activity. ESR1 may play a role in susceptibility to the depressive mood in postmenopausal women. Estrogen mediates its effects by binding to ESR1, leading to the expression of genes that control cell proliferation and survival. ESR1 gene polymorphisms are associated with metabolic syndromes  in postmenopausal women in China. DHTKD1 and RBBP4 may be involved in postmenopausal osteoporosis by regulating mitochondrial dysfunction and interacting with ESR1, respectively. The distribution of body fat in postmenopausal women changes and subcutaneous fat is transferred to abdominal visceral fat, resulting in central obesity and metabolic syndrome. AKT1 affects cellular homeostasis and is considered to be a survival factor that suppresses apoptosis. Studies have shown that the proliferative capacity of adipose tissue in postmenopausal women is lower than that in premenopausal women.–33 The content of AKT1 in the subcutaneous adipose tissue of postmenopausal women is lower than that in premenopausal women, which is related to the slow proliferative activity of AKT1 in subcutaneous adipose tissue obtained from the abdomen. The ESR1 signaling pathway in adipose tissue is likely to be followed by the activation of AKT1, leading to more proliferative or antiapoptotic processes. Combined with this literature, the targets of BHDH Decoction mainly focus on the endocrine resistance pathway, and we speculate that BHDH Decoction can enhance the sensitivity of ESR1, which not only reduces the side effects of hormone replacement therapy but also regulates fat metabolism and reduces systemic inflammation. MS is an endocrine disease associated with aging. TP53, as a “guardian gene,” has been shown to be a good target for preventing age-related disorders. The physiological function of EGFR is to regulate epithelial tissue development and homeostasis and is also a crucial regulator of autophagy. EGFR signaling is associated with insulin resistance and liver, muscle, and adipose inflammation. Inhibition of EGFR can improve tyrosine phosphorylation of insulin receptors and insulin receptor substrates in obese mice. EGFR signaling and its downstream pathways provide new therapeutic targets for regulating sleep. Insomnia is a common condition in menopausal women. The Jun family includes c-Jun, JunB, and JunD. Jun N-terminal kinase, a member of the MAPK family, is associated with the inhibition of cell proliferation.,39 Increasing evidence suggests that the MAPK/ERK pathway is involved in the pathogenesis of depression and mediates the regulation of the circadian system. This suggests that mental symptoms such as insomnia, anxiety, and depression during menopause may be related to the MAPK/ERK pathway.The components of the BHDH Decoction were identified using HERB. At present, most studies take OB ≥ 30% and DL ≥ 0.18 as the criteria for screening ingredients, which is not comprehensive.P value, the functions of the 3 biological processes with the highest scores in the 5 modules were pathways in cancer, endocrine resistance, and protein phosphorylation. The endocrine resistance signaling pathway is currently considered one of the pathways in the pathogenesis of MS. To further evaluate the complex relationships among different components, targets, and pathways of the BHDH Decoction in the treatment of MS, GO and KEGG analyses were conducted. According to the P value, the most important biological processes are cellular response to chemical stimuli, cellular response to oxygen-containing compounds, response to oxygen-containing compounds, response to endogenous stimuli, and cellular response to organic substances. These biological processes are closely related to MS.,42In addition, we screened modules in the PPI network and described their functions. According to the  Osteoarthritis is a frequently occurring disease in menopausal women. Colchicine is commonly used for the treatment of gout. Colchicine can reduce cardiovascular risk owing to its anti-inflammatory effects. Furthermore, adenosine modulates vascular homeostasis in the heart. Stigmasterol is a plant sterol reported to have a variety of physiological functions. It can reduce inflammation by regulating the MAPK/NF-κB ROCK1 pathway. The oxidation products of stigmasterol interfere with the female sex hormone 17β-estradiol in human breast and endometrial cells. Stigmasterol Causes Ovarian Cancer Cell Apoptosis by Inducing Endoplasmic Reticulum and Mitochondrial Dysfunction. Stigmasterol is also a potential metabolic regulator of neurodegenerative diseases. BHDH Decoction may treat MS through possible signaling pathways, including endocrine resistance, the ErbB signaling pathway, Hepatitis B, Progesterone-mediated oocyte maturation, and the relaxin signaling pathway. The Endocrine resistance signaling pathway is the most critical, and CCL2 activates the PI3K/Akt/mTOR pathway, which is a classical endocrine resistance pathway.Furthermore, depending on the degree, BC, and CC of the BHDH decoction-components-target-pathways network, we predicted emodin, adenine, colchicine, adenosine, stigmasterol, and emodin to be the core components of the BHDH Decoction. Emodin exhibits a variety of pharmacological benefits, including anticancer, anti-inflammatory, antioxidant, antimicrobial, immunosuppressive, and osteogenesis promotion activity, suggesting it could be used for the treatment of menopause-related anxiety, depression, osteoporosis, and other symptoms.Finally, Autodock Vina 1.1.2 software for docking the central components and targets. The docking results showed that the central active components of BHDH have an excellent binding activity to the central targets of MS. In this study, the predicted core components and critical targets have strong binding abilities, among which emodin with AKT1, stigmasterol with AKT1, EGFR, ESR1, SRC, and TP53 have solid binding abilities. In summary, BHDH Decoction alleviates MS through its main components, emodin, and stigmasterol, acting on AKT1, EGFR, ESR1, SRC, TP53, and other targets, as well as endocrine resistance and other pathways. The results of molecular docking further suggest that the chemical components of the BHDH Decoction may have good prospects as therapeutic drugs for MS and also provide molecular research ideas for subsequent basic research.Based on network pharmacology and molecular docking, this study explains the practical components of the BHDH Decoction and its related targets and pathways for treating MS. The central components may be emodin, adenine, colchicine, adenosine, and stigmasterol. It probably pairs core targets such as ESR1, AKT1, TP53, EGFR, and JUN to regulate endocrine resistance, ErbB signaling pathway, Hepatitis B, Progesterone-mediated oocyte maturation, and relaxin signaling pathway, which play a role in the treatment of MS. In addition, we demonstrated an excellent combination of hub components and hub targets through molecular docking, which provides a reference for exploring the pharmacological effects of DHDH Decoction. This study preliminarily reveals the mechanism of BHDH Decoction in treating Menopausal Syndrome. It provides a reference for in vitro and in vivo research and clinical application of BHDH Decoction in treating MS.Conceptualization: Mingmin Tian, Gaofeng Liu.Data curation: Anming Yang, Guangjie Liu.Formal analysis: Qinwei Lu, Xin Zhang.Investigation: Mingmin Tian.Methodology: Anming Yang, Xin Zhang.Project administration: Mingmin Tian, Gaofeng Liu.Resources: Mingmin Tian.Software: Guangjie Liu, Xin Zhang.Supervision: Mingmin Tian, Gaofeng Liu.Validation: Qinwei Lu.Writing-original draft: Mingmin Tian, Anming Yang.Writing-review & editing: Guangjie Liu, Gaofeng Liu.


To develop and validate a conventional MRI-based radiomic model for predicting prognosis in patients with IDH wild-type glioblastoma (GBM) and reveal the biological underpinning of the radiomic phenotypes.A total of 801 adult patients  diagnosed with IDH wild-type GBM were included. A 20-feature radiomic risk score (Radscore) was built for overall survival (OS) prediction by univariate prognostic analysis and least absolute shrinkage and selection operator (LASSO) Cox regression in the training set. GSEA and WGCNA were applied to identify the intersectional pathways underlying the prognostic radiomic features in a radiogenomic analysis set with paired MRI and RNA-seq data (N = 132). The biological meaning of the conventional MRI sequences was revealed using a Mantel test.Radscore was demonstrated to be an independent prognostic factor (P < 0.001). Incorporating the Radscore into a clinical model resulted in a radiomic-clinical nomogram predicting survival better than either the Radscore model or the clinical model alone, with better calibration and classification accuracy . Three pathway categories  were significantly correlated with the prognostic radiomic phenotypes.Our findings indicated that the prognostic radiomic phenotypes derived from conventional MRI are driven by distinct pathways involved in proliferation, DNA damage response, and immunity of IDH wild-type GBM.The online version contains supplementary material available at 10.1186/s12967-023-04551-3. Glioblastoma (GBM) accounts for 50.1% of primary malignant brain tumors, with a median survival rate of 8 months and 5-year survival rate of 6.9% . The pooRadiomics can non-invasively quantify tumor phenotypes by converting visual medical images into robust sub-visual digital indicators , and is Conventional MRI sequences have been extensively investigated in radiomics because of their accessibility and widespread use , 14, 19.Therefore, the current study has two objectives. First, a prognostic radiomic risk score (Radscore) was constructed and validated to stratify the patients with IDH wild-type GBM. Second, radiogenomic analysis utilized intersectional pathways enriched by both GSEA and WGCNA to explore the biological underpinnings of prognostic radiomic phenotypes.This study was a part of the ongoing research of the registered clinical trial “MR Based Survival Prediction of Glioma Patients Using Artificial Intelligence” . The Human Scientific Ethics Committee of the First Affiliated Hospital of Zhengzhou University (FAHZZU) and Henan Provincial People’s Hospital (HPPH) approved the study, and the requirement for written informed consent was waived due to the retrospective nature of this analysis. For patients providing fresh tumor specimens, informed consent was obtained. The study framework is shown in Fig. This study collected information on patients with histologically confirmed IDH wild-type GBM from FAHZZU and HPPH, between January 2011 and December 2021. Our study cohort (n = 801) had three sets: (1) a radiomics analysis set  with preoperative conventional MRI sequences including T2-weighted fluid-attenuated inversion recovery, T1-weighted gadolinium contrast-enhanced, T1-weighted, and T2-weighted images  for developing and validating the prognostic Radscore; (2) an external validation set  with preoperative MRI  to externally validate the reproducibility of the prognostic radiomic model; and (3) a radiogenomics analysis set  with paired MRI and RNA-seq to identify biological pathways underlying the radiomic features, which is a subset of the radiomics analysis set. Specifically, patients in the radiomics analysis set were randomly divided into a training data set (n = 471) and an internal validation set (n = 239), where clinical parameters including sex, age, preoperative Karnofsky performance status (KPS) scale, extent of resection, and adjuvant therapies were balanced. The selection procedure is shown in Additional file 3 voxels using trilinear interpolation. Rigid registration was performed on the MRI for each patient using axial resampled T1c as a template with a mutual information similarity metric, generating the registered images, namely rFLAIR, rT1c, rT1, and rT2. Histogram matching was performed to normalize intensity distributions. The whole tumor area  was delineated as the signal abnormal regions in the white matter on rFLAIR images, whereas rT2w and rT1c images were used to cross-check the extension of the whole tumor areas. A neuroradiologist (J.Y.) with 12 years of experience, who was blinded to the clinical data, manually delineated the tumor contours section by section on transverse sections using open-source software . To select robust features against intra-rater and inter-rater variations, the delineation was repeated by the same neuroradiologist (J.Y.) and another neuroradiologist  on 100 randomly selected patients, yielding an intra-rater repeatability test dataset and an inter-rater data set, respectively.This study followed image biomarker standardization initiative (IBSI) guidelines , 24. AllBased on this delineation, we extracted 4746 IBSI-based features using PyRadiomics (version 3.0) within the quantitative image feature pipeline from all four MRI sequences. The extracted features included shape features, first-order intensity features, and higher-order texture features. All the extracted features are summarized in Additional file The radiomics analysis set was divided into a radiomics training subset n = 471) and an internal validation subset (n = 239), using stratified random sampling at a ratio of 2:1 with balanced patient characteristics. A three-stage feature selection approach was used. First, to enhance the robustness of the features, any feature with an intraclass correlation coefficient (ICC) < 0.85 is discarded. Second, we selected the features that were highly correlated with OS. The remaining features with univariate concordance index (C-index) ≥ 0.55 (positive correlation) or ≤ 0.45 (negative correlation) were selected as better prognostic variables for further analysis. Third, least absolute shrinkage and selection operator (LASSO) penalized Cox proportional hazards regression  was used and an iBased on the radiogenomics analysis set with both MRI and RNA-seq, the biological pathways underlying Radscore were identified using GSEA and WGCNA.2FoldChange for each gene were arranged in reverse order and used to enrich the overrepresented pathways with an R package clusterPro-filer based on six annotated genes: Kyoto Encyclopedia of Genes and Genomes (KEGG), Hallmark, Reactome, BioCarta, Pathway Interaction Database (PID), and WikiPathways (WP). False-discovery rate (FDR)-corrected P < 0.05 was considered as significant enrichment. Thereafter, a gene set variation analysis (GSVA) was used on each enriched pathway to quantify its activity [First, differentially expressed genes (DEGs) between the high- and low-risk subgroups stratified by Radscore were identified using the R package DESeq2. Then, the values of Logactivity . PearsonFirst, WGCNA was performed on the radiogenomics analysis set to cluster highly interconnected genes into a few gene modules that may be involved in common biological processes . ModulesFirst, the intersectional pathways of GSEA and WGCNA were identified to improve the biological reliability of the enriched pathways. The identified pathways were categorized into several types. A Pearson correlation was performed on prognostic radiomic features and intersection pathways, where FDR < 0.05 indicated significance. The top feature-associated pathways of each pathway category were selected for further exploration. Finally, a Mantel test was used to assess the potential associations between the pathway categories and MRI sequences using ‘vegan’ R package.In total, 801 patients were included in this study. The distribution of clinical characteristics was balanced between the training and validation sets . The demographic and clinical information of the study cohort is summarized in Additional file After the three-stage feature selection, 20 features remained. Based on the LASSO COX regression model  and further confirmed in the internal validation set  and external validation sets , as shown by the Kaplan–Meier curves in Fig. Based on the radiogenomics analysis set, 646 pathways were enriched by GSEA analysis, where FDR < 0.05 was considered as significant enrichment. Then, 466 derived from the 646 pathways were obtained after performing a Pearson correlation between the enriched pathways and the Radscore, where FDR < 0.01 was considered as a significant association. A complete list of radscore-related pathways is provided in Additional file The results of WGCNA are summarized in Fig. https://www.gsea-msigdb.org, and subsequently these pathways were classified into several different categories according to their different biological functions, including tumor proliferation, immune regulation, DNA damage response (DDR), and others . We focused on revealing the potential biological underpinnings of the radiomic phenotype in the former three distinct pathway categories. The pathways and their categories are summarized in Additional file A total of 318 intersectional pathways were derived from GSEA and WGCNA approaches, as illustrated in Fig. First, After performing a Pearson correlation with the prognosis-related features, 14 features  and 219 pathways  were obtained, where the Pearson’s FDR < 0.05 was considered significant. The detailed results are shown in Fig. Our research focused on the following three endeavors. First, we constructed and independently validated a Radscore calculated from preoperative conventional MRI sequences for predicting OS in adult IDH wild-type GBM. Second, in contrast to previous studies in radiogenomics that used pathways enriched by a single approach, our study acquired the intersectional pathways enriched by both GSEA and WGCNA methods to reveal the biological underpinnings behind radiomic features. Third, the biological pathways underlying the radiomic phenotypes were systematically investigated.As the field of radiomics flourishes, biological validation will become an indispensable assessment criterion in clinical decision-making, and has recently been applied to radiomics studies . For GBMSeveral previous studies have confirmed the association of MRI features with prognosis and molecular subgroups of gliomas –31. In tWe elaborated on the biological meaning of individual prognostic features in terms of the categories and number of driving pathways. For the categories of driving pathways, our radiogenomics analysis revealed that five prognostic radiomic features  are associated with three major pathway categories , while the RF12 are only associated with one pathway related to the immune response. These findings demonstrate that multiple biological processes may be involved in different radiomic features. It is worth noting that RF5-RF7 and RF9 all belong to the T1c sequence, whereas RF12 is the only radiomic feature derived from the T1 sequence, which indicates that the radiomic features from the T1c sequence are associated with more biological information than those from other sequences. For the number of driving pathways, we found that each of the top features  had more than 100 associated pathways. Further radiogenomic analysis revealed that these three features were all derived from imaging textures. Consistent with previous radiomics findings , 33, ourWhen it comes to MRI sequence, radiomic features extracting form T1c and FLAIR were more related to biological pathways of GBM compared to T1 and T2. For T1c, the result shows that all three pathway categories  and 100 intersectional pathways (58.8%) are associated with radiomic features derived from T1c. This partly explains why imaging features derived from T1c showed substantially incremental value in GBM prognostication , 35. ForCombining the genetic characteristics of IDH wildtype GBM and our radiogenomic findings, we propose potential explanations for the biological mechanisms underlying the radiomic model. First, the high-risk group identified by the radiomic model is associated with proliferation and DDR pathway categories that promote GBM progression. More specifically, the positive activity of proliferation and DDR pathways in high-riks group, including MAPK signaling pathway, P53 pathway, STAT3 pathway, and DNA damage response pathways are reported to result in the induction of GBM growth –40. SecoThis study has several limitations. First, the current study is retrospective and needs to be substantiated by prospective multicenter studies. Second, incorporation of advanced MRI sequences, such as perfusion-weighted imaging (PWI), diffusion tensor imaging (DTI), and magnetic resonance spectroscopy (MRS), may provide additional imaging information and enhance prognostication performance of the radiomic model. Third, IDH wild-type astrocytomas with TERT promoter mutations, EGFR amplification, and + 7/− 10 chromosome copy number changes need to be further considered in future study to fully elucidate the intratumoral heterogeneity of IDH wild-type GBM according to the WHO CNS5.In conclusion, this study proposed a radiomic model using preoperative conventional MRI sequences to predict the clinical outcomes of patients with IDH wild-type GBM. Remarkably, radiogenomic results demonstrated that prognostic radiomic phenotypes derived from conventional MRI are associated with distinct pathways involved in proliferation, DDR, and immunity in IDH wild-type GBM.Additional file 1. A1: MRI sequence parameters. A2: Description of radiomic features used in our study. A3: RNA samples preparation and sequencing. A4: Detection of IDH mutation. A5: WGCNA process and module acquisition details. Table S1. A summary of the radiomic features extracted. Table S2. A summary of the parameters according to Image Biomarker Standardisation Initiative (IBSI). Table S3. Characteristics of patients in the training set, internal validation set and external validation set. Table S4. A summary of the C-index and AIC values for OS prediction of three models. Table S5. A summary of the Radscore-related pathways enriched by GSEA. Table S6. A summary of the genes in the five Radscore-related modules. Table S7. A summary of the pathways enriched by Radscore-related modules. Table S8. A summary of the intersectional pathways enriched by GSEA and WGCNA. Table S9. A summary of the pathway categories on proliferation, DDR and Immune. Figure S1. The criteria for patients’ inclusion and exclusion. Figure S2. Forest plot of prognostic radiomic features. Figure S3. Radiomic feature selection 1. Figure S4. Radiomic feature selection 2. Figure S5. Incremental value of radiomic model. Figure S6. Radscore for each patient. Figure S7. Cluster dendrogram and corresponding trait heat map for each patient in WGCNA. Figure S8. The Soft threshold selection process. Figure S9. Kaplan–Meier plot of fivefold cross-validation.


However, its main mechanism and related signaling pathways in the treatment of inflammation are still unclear. In this study, component target prediction was performed by using literature retrieval and the SwissTargetPrediction database. Disease targets were collected from various databases, including DisGeNET, OMIM, Drug Bank, and GeneCards. A protein–protein interaction (PPI) network was constructed, and enrichment analysis of gene ontology and biological pathways was carried out for important targets. The analysis showed that there were 191 unique targets of β-carotene after removing repeat sites. A total of 2067 targets from the three databases were integrated, 58 duplicate targets were removed, and 2009 potential disease action targets were obtained. Biological function enrichment analysis revealed 284 biological process (BP) entries, 31 cellular component (CC) entries, 55 molecular function (MF) entries, and 84 cellular pathways. The biological processes were mostly associated with various pathways and their regulation, whereas the cell components were mainly membrane components. The main molecular functions included RNA polymerase II transcription factor activity, DNA binding specific to the ligand activation sequence, DNA binding, steroid binding sequence-specific DNA binding, enzyme binding, and steroid hormone receptors. The pathways involved in the process included the TNF signaling pathway, sphingomyelin signaling pathway, and some disease pathways. Lastly, the anti-inflammatory signaling pathway of β-carotene was systematically analyzed using network pharmacology, while the molecular mechanism of β-carotene was further explored by molecular docking. In this study, the anti-inflammatory mechanism of β-carotene was preliminarily explored and predicted by bioinformatics methods, and further experiments will be designed to verify and confirm the predicted results, in order to finally reveal the anti-inflammatory mechanism of β-carotene. The inflammation response is a defense mechanism activated by the immune system when the body is exposed to harmful stimuli, such as microbial infection, allergens, radiation, etc. Cell surface pattern receptors identify harmful stimuli and activate corresponding signaling pathways. Immune cells then release pro-inflammatory cytokines that guide the synthesis of inflammatory mediators. This process leads to the activation and recruitment of white blood cells to the damaged sites for further treatment ,2. In thTraditional inflammatory treatment regimens include the use of steroidal anti-inflammatory drugs and nonsteroidal anti-inflammatory drugs. However, these drugs can cause various adverse reactions such as gastrointestinal diseases, cardiovascular and cerebrovascular diseases, infections, and even drug resistance . TherefoIn recent years, the study of natural products has gained increasing attention, particularly the study of β-carotene and its various physiological effects and functions that have been confirmed . β-carotHowever, the precise mechanism and related signaling pathways of β-carotene in treating inflammation remain unclear. In 2007, Hopkin  proposedFritillariae thunbergii for treating influenza-related inflammation. Based on the analytical method of network pharmacology, this article aims to construct a β-carotene target network by assimilating and analyzing data. Consequently, this research enriches the biological functions and information regulation pathways of potential targets and analyzes anti-inflammatory genes, molecules, and signal pathways of β-carotene.Alamri et al.  used netAccording to SwissTargetPrediction and BATMAN-TCM prediction, 75 and 125 targets related to β-carotene were obtained, respectively. After removing the duplicate targets, a total of 191 β-carotene targets were identified.Using “inflammation” as the keyword, relevant targets were searched for in the GeneCards, OMIM, TTD, and DisgeNET databases. A total of 1190 inflammation-related targets (score > 3) were retrieved from the GeneCards database. The score indicates the correlation between search results and search entries. The higher the score, the better the match between the search results and search terms. The OMIM database yielded 13 inflammatory targets and the TTD database yielded 158 targets. Finally, the DisgeNET database was searched for relevant targets, resulting in the identification of 467 targets. Integration of the results from all four databases yielded a total of 1828 targets, from which 354 repeats were removed, resulting in 1474 potential disease targets.A total of 54 candidate targets were identified through matching and mapping analysis of 1474 potential disease targets related to β-carotene. The results are illustrated in The active ingredient–action target network diagram of β-carotene and its corresponding 191 action targets was constructed by using Cytoscape 3.9.1 software . The parProtein–protein interaction refers to proteins that have physical contact with each other or functionally related proteins that form a network through complex and diverse interactions. Protein–protein interaction is the basis of exploring biological function, and the study of protein–protein interaction is of great significance for understanding and analyzing the biological function of drugs. Protein–protein interaction has been widely used in protein function prediction, disease research and prevention, drug candidate research, etc. Each node in Fifty-four potential targets were analyzed by using Cytoscape 3.9.1 software and a PPI network diagram was drawn . The inep < 0.05. A total of 370 entries were obtained via functional enrichment analysis, including 284 entries in BP , accounting for 76.76% of the results, 31 entries in CC (cellular component), accounting for 8.38%, and 55 entries in MF (molecular function), accounting for 14.86%.A bioinformatic analysis of 54 potential targets was carried out using the DAVID database with a screening condition of Based on the results of the molecular functional enrichment analysis presented in p-value). The top ten pathways are non-alcoholic fatty liver disease, neuroactive ligand–receptor interaction, TNF signaling pathway, proteoglycans in cancer, alcoholic liver disease, chemical carcinogenesis–receptor activation, AGE-RAGE signaling pathway in diabetic complications, Chagas disease, and sphingolipid signaling pathway.According to the genome-wide and metabolic pathway enrichment analysis of β-carotene anti-inflammatory targets, we have identified 84 pathways. As shown in To score the molecular docking results, we utilized the LibDockScore function of the software. Based on the findings as illustrated in The human body has a highly regulated system for controlling inflammation. This enables the effects of inflammation to be limited to specific times and places, resulting in a timely response to any harmful stimuli . Howeverβ-carotene is a natural pigment that has both coloring and nutritional functions and is permitted as a food additive. Research has shown that β-carotene possesses anti-inflammatory and anti-cancer properties and can improve animal immunity . It is aIn this study, 54 anti-inflammatory core targets of β-carotene were identified through network pharmacology. Among them, 10 key targets  were selected based on their degree value. Inflammatory factors are closely related to the occurrence of many diseases, and studies have shown that high expression of inflammatory cytokines is associated with drug resistance of cancer cells . TNF , and subsequently assessed through the SwissTargetPrediction  and BATMAN-TCM  online data sites to predict its potential targets [p-value of 0.05 utilized during target analysis [The molecular structure of β-carotene was retrieved using the PubChem database , GeneCards , TTD , and OMIM  were utilized. These databases were employed to collate all targets, remove duplicates, and subsequently integrate the resulting targets.To screen for relevant targets associated with “inflammation”, online network databases such as DisGeNET  to obtain the common action targets of active substances and diseases, resulting in the identification of common targets. The intersection of these targets was represented using a Venn diagram for active substances and diseases. These intersection targets are considered as the anti-inflammatory targets of β-carotene.The targets obtained for β-carotene and for inflammation were integrated and matched using the Weishengxin website (The corresponding relationship between β-carotene and its target information was established using WPSOffice (12.1.0.15712) software, and saved as an Excel.xls file. This file was then imported into Cytoscape 3.9.1 software to construct the “active ingredient-targets” network.https://string-db.org, accessed on 8 March 2023) with the human option selected. The minimum required interaction score was set to moderate confidence (0.400), and unrelated proteins were hidden before visualizing using the Cytoscape 3.9.1 software. The target result is sorted based on the degree value, and different colors and circle sizes are assigned to represent varying levels of gradient. This process resulted in the construction of a PPI network for the targets.The collected common targets were imported into the STRING protein–protein interaction online database  for analysis of gene ontology (GO) function and Kyoto Encyclopedia of Gene and Genome (KEGG) pathways. GO enrichment was utilized to obtain possible cellular components (CC), molecular function (MF), and biological processes (BP) of the target genes involved in vivo. Through comprehensive analysis of these enriched targets, the biological functions of these genes were obtained. By enriching the signal pathways involved in the target through the KEGG pathway, the main anti-inflammatory signal pathways and biological processes of β-carotene were obtained [p-value of less than 0.05, the top 20 GO enrichment analysis results and the top 20 KEGG enrichment results were selected for visualization and analysis [The common targets of β-carotene and inflammation were input into the DAVID database  was utilized to retrieve and download the structure of the core target proteins in PDB format. The 3D structure of β-carotene was obtained from the PubChem database and saved in SDF format. These structures were then prepared using Discovery Studio 2019 (v19.1.0.) software, which involved removal and hydrogenation of the molecular structure of the core target protein. Molecular docking was subsequently performed.The RCSB database (To conclude, this study applied network pharmacology to identify potential core targets and possible signal pathways of the anti-inflammatory effects of β-carotene. The active ingredient showed a good affinity with the targets, which were verified by molecular docking analysis. TNF, IL1B, and LEP were identified as key targets for the anti-inflammatory effects of β-carotene. These findings may contribute to the development of β-carotene and its potential use as a therapeutic agent for inflammation-related diseases.


A total of 1481 differentially expressed genes were identified, including 381 upregulated and 1100 downregulated genes, with enriched functions and pathways related to apoptosis, RNA splicing, signaling pathways, and lipid metabolism. Seven hub genes  were also identified using the cytoHubba plugin in Cytoscape. This study further screened small-molecule drugs using CMap and verified the results using molecular docking methods. This study identified 3-(5-(4-(Cyclopentyloxy)-2-hydroxybenzoyl)-2-((3-hydroxybenzo[d]isoxazol-6-yl) methoxy) phenyl) propanoic acid as a potential drug treatment and prognostic marker for BRONJ. The findings of this study provide reliable molecular insight for biomarker validation and potential drug development for the screening, diagnosis, and treatment of BRONJ. Further research is needed to validate these findings and develop an effective biomarker for BRONJ.This study aimed to identify potential molecular mechanisms and therapeutic targets for bisphosphonate-related osteonecrosis of the jaw (BRONJ), a rare but serious side effect of bisphosphonate therapy. This study analyzed a microarray dataset (GSE7116) of multiple myeloma patients with BRONJ  Bisphosphonate-related osteonecrosis of the jaw (BRONJ) is characterized by an exposed refractory bone in the area of the jaw, caused by an adverse effect of bisphosphonate (BP) treatment . CurrentDiagnostic bioinformatics is the application of bioinformatic techniques towards the development and improvement of diagnostic tests . The impA broad spectrum of gene expression data is available online. If thoroughly investigated, these data may provide predictive insights into the molecular mechanisms underlying diseases. As such, this study aimed to utilize these data, together with powerful informatic tools, to unravel and identify potential biomarkers for BRONJ diagnosis, and to identify potential drugs and drug targets for the treatment of BRONJ.A robust analytical method was used in this study. While an analysis of a single gene chip, as performed in this study, may yield false-positive results, we used a robust multichip array average (RMA) method, which integrated four important features: strong robustness to noise, incomplete ranking, significant scores in the result ranking, and high computational ranking. To the best of our knowledge, no previous study has used the RMA method that facilitated this study to identify differentially expressed genes (DEG) in BRONJ. A group from Korea used similar datasets for a combined predictor analysis and did not conduct any pre-processing of the data . Using aIn this study, we performed gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and protein–protein network analyses. We also provided the relationship between different genes and their regulatory networks, using the cytoHubba plugin of Cytoscape. Previous studies have successfully utilized this approach for biomarker discovery ,21,22. Fp < 0.05) is shown in Our search strategy yielded several relevant studies, and we downloaded and analyzed the microarray dataset GSE7116. This study was a platform based on GPL570, containing total samples from 11 MM patients with BRONJ and 10 MM patients without BRONJ. A volcano plot of the microarray results after RMA normalization  to perform a functional analysis of these DEGs. As shown in We used STRING to examine and identify possible PPI networks. A PPI network was constructed using the identified DEGs, which is presented in We utilized the CMap network to analyze the seven identified DEGs. The top six compounds with the highest negative enrichment scores were identified as potential therapeutic targets for BRONJ, Alantolactone, 1,4-dihydronicotinamide adenine dinucleotide, Glycitein, Napabucasin, 3-(5-(4-(cyclopentyloxy)-2-hydroxybenzoyl)-2-((3-hydroxybenzo[d]isoxazol-6-yl) meth-oxy) phenyl) propanoic acid, and Tanshinone IIA. The chemical structures of these compounds, and the hydrogen bonds surrounding the carbon compound, are illustrated in −1, showing that the target protein had a high affinity for the active component. The summary of binding energies is shown in Using PyRx 0.8, the screened small-molecule drugs were docked with seven core targets . A binding energy lower than 0 suggests that the ligand and receptor bind spontaneously. The possibility of a higher activity was determined by the stability and binding energy of the conformation. The lowest binding energy was usually less than −11 kcal moleTraditional gene expression analysis poses a challenge considering the biological heterogeneity and technical biases of sequencing platforms . In thisAll hub genes were directly or indirectly involved in bone metabolism. The FN1 gene provides instructions for producing fibronectin-1 protein . FN1 hasBased on our scoping review of the genes studied in BRONJ, STAT3 is postulated to be activated subsequent to the immune response. Treatment with BP elevates IL-6 and IL-36a levels, which then activates the STAT3 pathway . The mol3-{5-[4-(cyclopentyloxy)-2-hydroxybenzoyl]-2-[ methoxy] phenyl} propanoic acid is an organic compound that is classified as a benzophenone, which has a ketone attached to two phenyl groups. Despite being a relatively unknown compound, it has been detected in human blood, indicating that it is not a naturally occurring metabolite, and is only present in people who have been exposed to it or its derivatives . This coThis study lends itself to several limitations. Although bioinformatics data mining can provide valuable information, available datasets, particularly those related to BRONJ, are limited. As such, we utilized a single center study. Additionally, a single chip analysis should be interpreted with caution as it may account for limited coverage, technical variability, and cross hybridization, making it less feasible to arrive at a plausible conclusion.https://www.ncbi.nlm.nih.gov/, accessed on 28 November 2022)]. The search strategy [“bisphosphonate related osteonecrosis of the jaw” (MeSH Terms) OR “bisphosphonate related osteonecrosis of the jaw” (All fields)] and [“Home sapiens” (Organism) and “Expression profiling” (Filter)] were used. The data contained 11 multiple myeloma (MM) patients with BRONJ, against 10 age-matched MM patients without BRONJ. Further details are provided in http://www.R-project.org/, accessed on 28 November 2022). Using the R package ‘limma,’ a linear model was used to assess differential expression. The cut-off parameters for determining DEGs were [log2 fold change (FC)] > 1 and p-value p < 0.05.The expression profile for BRONJ was obtained from the Gene Expression Omnibus (GEO) database [. GO annotates gene products and functions into three categories: biological processes (BP), molecular functions (MF), and cellular components (CC), allowing us to compare and analyze genes across control versus BRONJ subjects. A p-value of 0.05 was used as the cutoff criterion.GO enrichment and KEGG pathway analyses were performed using a freely available Database for Annotation, Visualization, and Integrated Discovery (DAVID) . The cut-off point was set to a credibility score higher than 0.4. PPI visualization was performed using the Cytoscape software.The STRING online database was used to construct a functional PPI network for the identified DEGs . Cytoscape is an open-source software platform used for visualizing and analyzing molecular interaction networks. CytoHubba is a plugin for Cytoscape that provides various network analysis algorithms to identify important nodes or subnetworks within a given network. Several topological algorithms were used to identify interactome networks in this plug-in. The following metrics were used: density of the maximum neighborhood component (MNC), maximal clique centrality (MCC), density of the maximum neighborhood component (DMNC), closeness, betweenness, and degree. Venn diagrams were used to locate the shared genes.The Cytoscape cytoHubba plugin was used to select hubs from the DEGs. , whereas the mol2 file formats of the compounds were retrieved from the PubChem database. Target proteins were extracted from PyMOL 2.3.2, and their ligands were stored in PDB format. The target protein was then hydrogenated, and its charge was calculated and stored in PDBQT format using AutoDock Tools 1.5.6 software. Grid box data for the protein of interest were obtained, and molecular docking was performed using AutoDock Vina 1.1.2. The results of molecular docking were visualized using PyRx software. PyRx 0.8 is a useful tool for computational drug discovery and design, used to perform virtual screening experiments by docking small molecule ligands to protein targets.To assess the potential effectiveness of the medication treatment for BRONJ, we measured the binding energy between the small-molecule medications predicted in CMap and the possible target proteins of BRONJ. The crystal structures of the principle targets were obtained from the RCSB Protein Data Bank (PDB, There is currently no known biomarker for BRONJ. The present study used bioinformatics to analyze the gene chip data of MM patients with BRONJ. The resulting findings allowed us to identify potential molecular biomarkers for BRONJ. Apart from that, we were also able to identify potential therapeutic targets for BRONJ. All identified hub genes were either directly or indirectly related to bone metabolism, which could potentially be aberrated in disease, and hence a factor in the development of BRONJ. The present results are based only on bioinformatics analysis, and further validation is required to verify this finding. Further efforts in utilizing microarray studies may benefit efficient biomarker development.


The aim of this study was to integrate metabolomics and network pharmacology to reveal the mechanism of EGCG in the prevention of obesity-related precocious puberty.A high-performance liquid chromatography-electrospray ionization ion-trap tandem mass spectrometry (LC-ESI-MS/MS) was used to analyze the impact of EGCG on serum metabolomics and associated metabolic pathways in a randomized controlled trial. Twelve weeks of EGCG capsules were given to obese girls in this trail. Additionally, the targets and pathways of EGCG in preventing obesity-related precocious puberty network pharmacology were predicted using network pharmacology. Finally, the mechanism of EGCG prevention of obesity-related precocious puberty was elucidated through integrated metabolomics and network pharmacology.Serum metabolomics screened 234 endogenous differential metabolites, and network pharmacology identified a total of 153 common targets. These metabolites and targets mainly enrichment pathways involving endocrine-related pathways , and signal transduction . The integrated metabolomics and network pharmacology indicated that AKT1, EGFR, ESR1, STAT3, IGF1, and MAPK1 may be key targets for EGCG in preventing obesity-related precocious puberty.EGCG may contribute to preventing obesity-related precocious puberty through targets such as AKT1, EGFR, ESR1, STAT3, IGF1, and MAPK1 and multiple signaling pathways, including the estrogen, PI3K-Akt, MAPK, and Jak-STAT pathways. This study provided a theoretical foundation for future research. PrecociDespite the etiology being incompletely understood, precocious puberty is thought to be associated with obesity, genes, lifestyle habits, environmental endocrine disruptors, and other factors , 8. NutrMetabolomics is a comprehensive technique for monitoring the dynamics of endogenous small molecule metabolites and reflecting changes in metabolic pathways throughout the metabolic network in an organism . Network22.1Serum samples were derived from our prior randomized control trial (NCT03628937). Briefly, researchers assigned six to ten-year-old obese girls to two groups: placebo and EGCG. Twelve weeks of EGCG capsules  were given to girls in the EGCG group (n=18). The placebo group (n=16) received placebo capsules that appeared the same for twelve weeks. Detailed descriptions of the research design have been provided previously .Serum metabolomics were analyzed using a high-performance liquid chromatography-electrospray ionization ion-trap tandem mass spectrometry (LC-ESI-MS/MS) in both positive and negative ion modes. Chromatographic conditions were based on the prior description .https://cloud.majorbio.com), based on the description given previously (P < 0.05) were used to identify differential metabolites. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Human Metabolome Database (HMDB) were employed to identify and analyze implicated pathways associated with the metabolites.Data analysis was carried out utilizing Majorbio Cloud  were visualized with OmicShare Tools.GO and KEGG pathway enrichment analyses were completed using the ClusterProfiler package of R 4.0.3 to elucidate the role of the common targets in gene function and signaling pathways . The GO 2.6To validate the aforementioned results, molecular docking analysis was conducted to calculate the affinity of hub target gene products in the network. We selected hub target gene products and EGCG for molecular docking. From the PubChem database, three-dimensional (3D) structures of ligands were obtained . The RCS33.1This study applied metabolomic analysis to identify endogenous differential metabolites in serum of obese girls following intervention with EGCG. The OPLS-DA analysis revealed that serum samples from the EGCG and placebo groups were clearly separated in both positive and negative modes . The top ten significantly enriched terms from the three categories were output based on gene count , cellular processes (cell growth and death), and organismal systems (endocrine system) , resulting in the premature development of internal and external genitalia . Girls wThe pathogenesis of precocious puberty is related to early initiation of the HPGA, and the pivotal factor in the HPGA initiation is the pulsatile secretion of gonadotropin-releasing hormone (GnRH) . Among tin vivo studies suggests that the JAK/STAT pathway plays a crucial role in modulating GnRH neurons during puberty. Female GnRH neuron-specific JAK2 conditional knockout mice (JAK2 G-/-) shows reduced GnRH expression and neuronal activity. Furthermore, JAK2 G-/- female mice exhibits delayed puberty and reduced fertility  has been demonstrated to be strongly correlated with the pubertal development in children . ERα andertility . Therefoin vivo and in vitro experiments. In the future, it will be necessary to thoroughly validate the details of omics data, including species markers that are distinct, predicted metabolic pathways, and potential functional interactions. Additionally, we can continue to explore the effects of EGCG on genes associated with estrogen, lipid metabolism, and energy metabolism, and further investigate the potential role of EGCG in regulating the endogenous metabolites of obesity-related precocious puberty. Furthermore, considering that the physiological association between EGCG and obesity-related precocious puberty is multifactorial, we will also use transcriptomic and proteomic technologies to reveal the correlation between EGCG and obesity-related precocious puberty at the gene and protein levels with the technical advantages of their high sensitivity and quantitative accuracy in the future research.Despite the findings of this study, the current study has certain limitations which should not be overlooked. Firstly, despite the advancements being made, there is still a lack of metabolomics data available for the precise identification of metabolites. Secondly, the sample size was too small. To improve this, it is essential to conduct future studies with a greater sample size of patients. Thirdly, due to the restrictions imposed by certain databases, it is not possible to retrieve all the active targets of EGCG, and the targets and pathways are interrelated and modulate each other. Further research is still required to gain a more comprehensive understanding of EGCG’s pharmacological effects and mechanisms in the prevention of obesity-related precocious puberty, which can be explored and confirmed through both In summary, EGCG may serve a role in preventing obesity-related precocious puberty through targets such as AKT1, EGFR, ESR1, STAT3, IGF1, and MAPK1 that acted on multiple signaling pathways, including the estrogen, PI3K-Akt, MAPK, and Jak-STAT pathways. In this study, we investigated the mechanism by which EGCG prevented obesity-related precocious puberty through a network pharmacology approach and found that multiple targets and pathways were involved in the underlying mechanism. This study provided a theoretical foundation for subsequent research.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/The studies involving human participants were reviewed and approved by the Ethics Committee of Xinhua Hospital. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin. The animal study was reviewed and approved by the Ethics Committee of Xinhua Hospital.XS and LL conceived and designed the study. QG, LX, QD, YS, and JH collected data. QG drafted the manuscript. PW provided major comments to the manuscript. All authors contributed to the article and approved the submitted version.


Naoshuantong capsule (NST capsule) is a classic Chinese patent medicine, which can treat ischemic stroke (IS) and has good clinical efficacy. However, its pharmacological mechanism remains to be further explored in the treatment of IS.The bio-active components and potential targets of NST Capsules were obtained by ETCM and TCMSP databases. In addition, the related targets of IS were collected by Genecard, OMIM, DrugBank, TTD and DisGeNET databases. NST-IS common target was obtained by Venn platform. PPI network of NST-IS common target and the composition - target network diagram of NST Capsule were constructed by Cytoscape3.8.1. Finally, AutoDock was used for molecular docking.265 targets were predicted from 32 active compounds in NST Capsule, 109 common targets were identified between NST Capsule and IS. The top 10 key targets of PPI network were ALB, TNF, TP53, VEGFA, CASP3, MYC, etc. Enrichment analysis showed that NST capsules treated IS mainly through lipid and atherosclerosis, fluid shear stress and atherosclerosis signaling pathways.Through the methods of network pharmacology and molecular docking, this study clarified that NST capsules play a role in the treatment of IS, which is multi-target, multi-channel and multi-component regulation. This study further explored the pharmacological mechanism of NST capsule in the treatment of IS, which can provide some references for the subsequent research in the pharmacological mechanism of NST capsule. IS refers to a disease of focal neurological deficit in the brain, which is caused by the interruption of cerebral blood flow caused by thrombosis or embolism in a certain area.–7 It has the characteristics of high morbidity, high mortality and high disability rate.,9 The occurrence of IS is closely related to several risk factors, including diabetes, smoking, hyperlipidemia and hypertension.–13 After the occurrence of IS, the main manifestations are facial paralysis, crooked mouth, slurred speech, paralysis and other clinical symptoms. At present, Tissue plasminogen activator (r-tPA) is the main drug for the treatment of IS,,16 but its use has a strict time limit and needs to be administered within 4.5 hours after the onset of IS, there is a risk of secondary brain damage during treatment and increases the risk of disability and stroke recurrence.–19 It is necessary to explore new methods to prevent the occurrence of IS and treat the brain damage caused by IS.Stroke is one of the major diseases that cause death and disability in the world, Studies have shown that TCM has a good effect on IS, which can effectively prevent the occurrence of IS and delay the progress of the disease.,22 Therefore, exploring the mechanism of action of TCM in the treatment of diseases will help to make better use of TCM in the treatment of diseases. Naoshuantong capsule (NST capsule) is a classic drug for the treatment of IS, which has been widely used in clinical practice. It is composed of Typha angustifolia L, Paeoniae Radix Rubra, Curcumae Radix, Rhizom Gastrodiae and Rhaponticum uniflorum (L.) DC. It has the effects of promoting blood circulation, eliminating wind and phlegm, improving blood circulation and protecting nerve cells, which is consistent with the pathogenesis of IS. NST capsule can effectively reduce the brain damage caused by IS. However, the mechanism of NST capsule in the treatment of IS is not very clear, Therefore, it is very important to systematically study the multi-component, multi-target and multi-pathway mechanism of NST capsule in the treatment of IS.In recent years, people pay more and more attention to traditional Chinese medicine (TCM) because of its low toxicity and good effect. it provide a method to study the mechanism of action of complex components of TCM. In this study, we explored the targets and pathways of NST capsule in the treatment of IS by network pharmacology and molecular docking methods, then further elucidated the action mechanism of NST capsule in the treatment of IS. The research workflow is shown in Figure TCM compound preparations are often composed of a variety of Chinese herbs, which have many components that it is difficult to elucidate their mechanism of action by traditional methods. Network pharmacology can reveal the mechanism of action of TCM prescriptions in treating diseases by constructing a multi-layer network of drug-component-gene-disease, which is consistent with the holistic view of TCM,http://tcmspw.com/TCMSP.PHP) database and ETCM database (http://www.tcmip.cn/ETCM/index.php/Home/Index/), if OB > 30% and DL > 0.18 are set, the active components of NST capsule can be obtained, its related targets can be obtained according to its active components. The obtained relevant targets were converted into standard gene names by Uniprot platform (https://www.uniprot.org). “Cerebral arterial thrombosis” was set as the search term, then IS related to target is collected by Genecard database (https://www.genecards.org/), OMIM database (https://omim.org/), providing database (http://db.idrblab.net/ TDD/) and DisGeNET database (http://www.disgenet.org/), The obtained genes were pooled and duplicated genes were further deleted, finally, the final gene set of IS was obtained. NST capsule gene set and IS set to be imported Venny2.1.0 platform (https://bioinfogp.cnb.csic.es/tools/venny/) to gain common genes of NST-IS.The main components of NST capsule are Typha angustifolia L, Paeoniae Radix Rubra, Curcumae Radix, Rhizom Gastrodiae and Rhaponticum uniflorum (L.) DC Based on the network pharmacological method, the active ingredient and related targets of Typha angustifolia L, Paeoniae Radix Rubra, Curcumae Radix, Rhizom Gastrodiae and Rhaponticum uniflorum (L.) DC are collected through Traditional Chinese Medicine Systems Pharmacology, Database and Analysis Platform , the common target of NST capsule and IS was imported into the String platform, medium reliability was set as 0.400, the PPI network data table was derived. The PPI data table was imported into Cytoscape3.8.1 to calculate the obtained network diagram and export the calculated data table, then the median of degree values (D), betweenness centrality (BC), closeness centrality (CC), and R were calculated, Degree above 2 times the median, BC, CC and R above the median are set, the sub-network diagram was obtained. D, BC, CC, and R medians are calculated again in the data table. D, BC, CC, and R above the median are set, finally, the core network diagram was obtained.The Protein-Protein Interaction (PPI) network diagram of the common target of NST capsule and IS was constructed based on the String platform (http://www.metascape.org/), which can explore the potential mechanism of action of NST capsules in the treatment of IS. GO enrichment analysis includes cell component (CC), molecular function (MF) and biological process (BP) analysis, KEGG enrichment analysis includes key signaling pathway analysis.Based on the common genes of NST capsules and IS, the common gene sets of NST capsules and IS were performed for gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis by the metascape platform (http://www.rcsb.org/). ChemDraw18.1 software was used to draw the chemical structure of the corresponding components of the 3 genes. In order to obtain the 3D structure of the components, after energy was minimized, the 3D structure of each component was exported by Chem3D 18.1 software. PyMOL software was used to remove the water molecules of the receptor proteins and components, the receptor proteins were imported into Autodock software for hydro-treating and charge calculation. Based on Autodock Vina software, docking pockets and docking parameters were set to perform molecular docking between receptor proteins and small molecular ligands.The 3 most significant genes were selected in the core target network diagram for molecular docking. The corresponding receptor proteins of the 3 target were obtained from the Uniprot database, the structure of the proteins was obtained from the PDB database  DC. Based on TCMSP database, there were 8 active compounds and 153 targets in Typha angustifolia L, 29 active compounds and 61 targets in Paeoniae Radix Rubra, 15 active compounds and 29 targets in Curcumae Radix, 5 components and 21 targets in Rhaponticum uniflorum (L.) DC. 21 components and 291 targets of Rhizom Gastrodiae were obtained from ETCM database. 78 active compounds and 555 related targets were obtained from the TCMSP database and ETCM database. After 46 common components and 290 common targets were removed, 32 components and 265 targets were obtained. Based on Genecard database, OMIM database, TTD database and DisGeNET database, 3041, 129, 0 and 15 IS-related targets were obtained respectively, then 36 common targets were removed, finally, 3149 IS-related targets were obtained. Based on Venn platform, a total of 109 targets of NST capsule in the treatment of IS were predicted. The Venn diagram is shown in Figure Based on Cytoscape3.8.1 software, active ingredients and targets of NST capsule were analyzed. 303 nodes and 559 edges were obtained. The composition and target network diagram of NST capsules are shown in Figure R value 0.991 can be calculated, the above data are used for secondary screening of PPI network, then 11 core targets are obtained. Among them, the degree values of ALB, TNF, and TP53 were the highest, which indicated that these 3 targets were the key targets of NST capsule in the treatment of IS. The core target screening process is shown in Figure Based on the String platform, the PPI network diagram of the common targets between NST capsule and IS was obtained. Based on Cytoscape3.8.1, PPI network diagrams were analyzed, the median double of Degree is 26, the BC median is 0.02, the CC median is 0.495, and the R median is 0.986. The above data were used to screen PPI networks, 23 core targets are obtained. Then, according to the filtered data table, Degree value 37, BC value 0.018, CC value 0.596, Based on GO enrichment analysis, the GO pathway of the common target of NST capsule and IS can be obtained. In GO pathway analysis, 321 terms pathway were obtained from biological process (BP) analysis, 85 terms pathway were obtained from cell component (CC) analysis, 120 terms pathway were obtained from molecular function (MF) analysis. The 10 most significant GO terms pathway are shown in Table After the core target network diagram was analyzed, the top 3 targets ALB, TNF and TP53 were selected, their corresponding active ingredients were Vanillin, P-Hydroxybenzaldehyde, Eleutheroside A, Baicalin and Quercetin respectively. Molecular docking was performed between the target and its corresponding protein. After molecular docking, 5 docking results were obtained, the binding energy of all molecular docking results was less than −5.4 KJ, which indicate that 5 molecules could combine well with their targets and play a good role in the treatment of IS. The docking results are shown in Figure  The pathogenesis of IS is complex, its prevention and recovery require multiple-target and multiple-pathways to play a role at the same time. In recent years, NST Capsule has been widely used in the treatment of IS. The drug is composed of 5 TCM, such as Typha angustifolia L, Paeoniae Radix Rubra, Curcumae Radix, Rhizom Gastrodiae and Rhaponticum uniflorum (L.) DC. The drug contains a variety of effective components. However, the mechanism of NST capsule in the treatment of IS remains to be further explored. In this study, network pharmacology and molecular docking methods were used to further explore the pharmacological mechanism of NST capsule in the treatment of IS.IS seriously affects people’s physical health and brings serious economic burden to patients and their families. Experiments have shown that P-Hydroxybenzaldehyde can regulate the expression of Bcl-2, Bax and cleaved caspase-3 proteins, which can improve oxidative stress and mitochondrial dysfunction, so play a protective role in the injured brain. Eleutheroside A is mainly involved in tissue inflammation and autoimmune response, which is related to the recovery of IS. Baicalein can protect mitochondria and promote neuronal protective factors through antioxidant, anti-apoptotic, anti-inflammatory and anti-excitotoxic pathways, which are involved in the prevention and recovery of IS. Quercetin can inhibit the secretion of inflammatory cytokines by immune cells and reduce platelet aggregation, which can reduce the formation of inflammatory thrombosis and play a role in the treatment of IS. Rhizom Gastrodiae has more active ingredients in NST capsules, so it can be inferred that Rhizom Gastrodiae is an important component of NST capsules. According to reports, Rhizom Gastrodiae has the effect of anti-oxidative stress, reduces neuroinflammation and inhibits apoptosis. Therefore, Rhizom Gastrodiae plays a role in treating IS by protecting the blood-brain barrier. By analyzing the PPI network of NST capsule and IS, we found that the core targets of NST capsule in the treatment of IS include ALB, TNF, TP53, CASP3, VEGFA, SRC, etc. These targets are involved in transcriptional regulation, gene regulation, apoptosis regulation and other biological processes. These biological processes are closely related to the occurrence of IS.In this study, 2280 targets of IS were obtained by Genecard database, OMIM database, DrugBank database, TTD database and DisGeNET database. Based on TCMSP and ETCM databases, 32 effective components and 265 targets were obtained from Typha angustifolia L, Paeoniae Radix Rubra, Curcumae Radix, Rhizom Gastrodiae and Rhaponticum uniflorum (L.) DC. The NST-IS has 109 common targets. Through network pharmacological analysis, we found that the core targets of NST capsule in the treatment of IS include ALB, TNF, TP53, CASP3, VEGFA, SRC, MYC, PPARG, ICAM1, EGF, CCND1, etc. These targets have the effects of anti-oxidation, anti-apoptosis, anti-inflammation, regulation of blood lipids and atherosclerosis. Based on the core target network diagram, the top 5 components were selected: Vanillin, P-Hydroxybenzaldehyde, Eleutheroside A, Baicalein and Quercetin. Vanillin has the effect of antioxidant, anti-apoptotic, anti-inflammatory, neuroprotective and maintaining the integrity of the blood-brain barrier, which has a good effect in the treatment of IS. NST capsule can inhibit the expression of pro-inflammatory factor TNF, which suggest that NST capsule may alleviate brain injury of IS by regulating lipid and atherosclerosis, fluid shear stress and atherosclerotic pathways. According to literature reports, TP53 factor can play a role in regulating glycolysis and apoptosis of cytokines by transferring glucose metabolism to pentose phosphate metabolic pathway, which can reduce oxidative stress response of brain nerves and play a protective role in injured ischemic neurons. Through network pharmacology and molecular docking, we found that the mechanism of action of NST capsule in the treatment of IS is related to ALB, TNF, TP53 and other targets, At the same time, lipid and atherosclerosis, fluid shear stress, atherosclerosis and chemical carcinogenic-receptor activation pathways are important. Our results are consistent with published research.Base on network pharmacology and molecular docking, ALB, TNF and TP53 are the key targets of NST Capsule in the treatment of IS. According to reports, ALB has a good effect on the treatment of recurrent IS, which mainly plays a role in the treatment of IS by enhancing the synthesis of neuroprotectin D1 and resisting the synthesis of lipoxins and inflammatory factors. In addition, ALB can also play an anti-coagulant role by inhibiting platelet aggregation and increasing the production of anti-aggregation prostaglandin D2, which can play a role in the treatment of IS.This study elucidated the mechanism of NST capsule in the treatment of IS through network pharmacology and molecular docking, which will provide a more reliable basis for the clinical use of NST capsule in the treatment of IS, it can promote the rational use of NST capsule. Secondly, this study can provide some reference for the future research of NST capsule. However, this study only explored the theoretical part of NST capsule in the treatment of IS, this study did not conduct in vitro experiments to verify the theoretical results. In the future research, we hope that researchers will conduct deeper research on the mechanism of NST capsule.In this study, based on network pharmacology and molecular docking, we designed a strategy to analyze the pharmacological mechanism of NST Capsule in the treatment of IS. We found that hormone, nutrient level, positive regulation of cell death, extracellular stimulation, oxygen content reduction and other processes are closely related to the treatment of IS with NST capsule, these processes are related to lipid and atherosclerosis, fluid shear stress and atherosclerosis pathways. This indicates that NST capsules play a role in the treatment of IS through multi-target and multi-pathway. This study provides basic evidence for the drug safety management of NST capsule in the treatment of IS, this can prove that it is feasible to analyze the pharmacological mechanism of NST capsule by using network pharmacological strategies, which is conducive to the systematic safety management and evaluation of NST capsules.Formal analysis: Kezhen Qi.Methodology: Yun Gu.Resources: Guangming Wang.Software: Fengjiao Yang.Supervision: Ya Yan.Validation: Jianjie Chen.Visualization: Yun Gu, Ya Yan.Writing – original draft: Fengjiao Yang.Writing – review & editing: Guangming Wang.