What are the main findings?In total, 14 core genes for vitamin D against MetS are obtained via enrichment analysis.Van der Waals forces are the main interactions to sustain vitamin D binding with targets.What is the implication of the main finding?Vitamin D could reduce triglycerides significantly and improve insulin resistance.Vitamin D might modulate the PPAR signaling pathway and inhibit bile secretion.As a dietary supplement or functional food additive, vitamin D (VD) deficiency may impact extra-skeletal functions associated with metabolic syndrome (MetS) risk factors. However, the precise effects and mechanisms of VD supplementation on dyslipidemia and insulin resistance in MetS subjects remain controversial. Here, we investigate potential therapeutic targets, pathways and mechanisms of VD against MetS through a comprehensive strategy including meta-analysis, network pharmacology analysis, molecular docking, dynamics simulations, and quantum chemical calculations. Our results reveal that VD supplementation significantly reduces triglyceride levels, fasting glucose, and insulin concentrations in subjects, thereby improving insulin homeostasis to some extent. We theoretically identify 14 core MetS-associated targets. Notably, VD exhibits substantial interactions with three targets  in the PPAR signaling pathway, indicating that VD can modulate this pathway. Van der Waals forces predominantly stabilize the complexes formed between VD and the three targets. Nonetheless, to provide valuable insights for personalized MetS management, further research is necessary to confirm our findings, emphasizing the importance of exploring genetic variability in VD response. In conclusion, our study contributes insights into the mechanisms of VD in preventing and treating MetS through dietary supplementation, promoting the development of VD-based functional foods or nutritious diets. Metabolic syndrome (MetS) entails a clinical constellation of physiological and biochemical metabolic disorders, encompassing abnormal lipid profiles, insulin resistance, and central obesity and serving as a risk factor for cardiovascular disease (CVD) . Accordi2) and cholecalciferol (VD3), and can be activated through both canonical and non-canonical pathways [Hence, it is imperative to consider preventive measures for MetS, such as dietary supplements, to mitigate the side effects of drug therapy and enhance the overall quality of life for patients. Vitamin D (VD) is well-established for its multifaceted applications in the realm of nutrition, primarily through food fortification or supplementation, aimed at increasing VD accessibility, especially for individuals with limited sun exposure or dietary restrictions ,5. As wepathways ,7. In thpathways . While tpathways ,9, they pathways . Given tpathways . Consequpathways ,13. Howepathways . Moreovepathways ,16. Whilpathways  and obsepathways  have sugpathways .Therefore, more relevant randomized controlled trials (RCTs) are required to substantiate the efficacy of VD supplementation in preventing and treating MetS. To address this, we employed a meta-analysis approach, which is a statistically rigorous method involving the systematic review and quantitative synthesis of data from previous studies. Meta-analysis provides notable advantages, including cost-effectiveness and feasibility compared to large-scale trials. This approach has gained extensive use in food science, particularly in investigating prevention and treatment strategies for cardiovascular diseases ,23,24,25Here, we conducted a meta-analysis and employed network pharmacology to explore the potential pharmacological mechanisms and identify functional targets of VD in treating MetS. Furthermore, molecular docking and dynamics simulations were utilized to elucidate the interactions between VD and core targets. This study aims to provide valuable insights into dietary micronutrient supplementation, mainly focusing on VD as a strategy against MetS. In addition, we present a visual representation of our research process to illustrate the anti-MetS effects and mechanisms of VD .Inclusion and exclusion criteria for this study are described in From each study, the following information was obtained:(1) Basic details about the included studies, including the literature title, first author, and publication year. (2) Key characteristics of the study population, such as age, sample size, serum 25(OH)D levels, missed follow-up rate, and duration of follow-up. (3) Details of the VD intervention, including dosage and form. (4) Measurement data for baseline and endpoint lipid- or glucose-related outcome indicators.Cochrane Handbook (version 5.1.0). When disagreements arose, an instructor assisted in the adjudication process.In addition, the risk of bias  was indeMD) and standard deviation (SD). Then, we calculated the MD and SD for the pre- and post-intervention change values of outcome indicators, including lipid profile and insulin resistance. The unit conversions for all indicators are shown in If the extracted data were not normally distributed, we employed the methods described by Wan et al.  and Luo Review Manager 5.4. We explored the sources of heterogeneity in the effect on lipid profile by performing subgroup analysis based on subjects’ baseline serum 25(OH)D levels.The forest plots and sensitivity analysis were performed using https://www.uniprot.org/) and selected the species as ‘human’.Preliminary MeSH terms of disease were collected from the PubMed database. For retrieval keywords, we used MeSH terms such as ‘metabolic syndrome’, ‘dyslipidemia’, and ‘insulin resistance’. In addition, the MetS-driven targets and all predicted targets of VD were obtained from relevant databases  38,39,4,46,47,48https://string-db.org/) to construct the protein–protein interaction (PPI) network. The PPI network was constructed by setting the organism species as ‘Homo sapiens’, the minimum interaction threshold as ‘highest confidence’ (>0.9), and the rest of the settings as default. We employed the cytoHubba 0.1 plugin in Cytoscape (dev3.9.1) to screen the hub genes. The top 10 hub genes were screened using 12 different algorithms to create a heat map. In addition, we consulted the NCBI database (https://www.ncbi.nlm.nih.gov/) to obtain the significant roles of hub genes in metabolic regulation and to further screen for targets associated with MetS.We calculated the intersection of the two target sets to elucidate the interaction between VD-related targets and disease-associated targets. Subsequently, we created a Venn diagram using the R programming language. Then, the intersecting targets were submitted to the STRING 11.0 database (http://david.abcc.ncifcrf.gov/). To recalibrate the false discovery rate (FDR) arising from the multiple hypothesis testing, we employed the Benjamini–Hochberg method (p < 0.05 indicated significance) [http://www.bioinformatics.com.cn/), and KEGG pathway annotation was performed using OmicShare tools . Both of these platforms are online tools for data analysis and visualization.The intersecting genes were enriched and analyzed using the DAVID (ficance) . Then, bhttps://www.rcsb.org/). The PubChem database (https://pubchem.ncbi.nlm.nih.gov/) was searched to obtain the 3D molecular structure formulae (in SDF format) for VD2  and VD3 . The LibDock mode in Discovery Studio 2019 was utilized for 10 docking runs under the CHARMM force field. If the root-mean-square deviation (RMSD) ≤ 2 Å, it indicates a better reproduction of the binding pattern, rendering the docking results more reliable [The receptor proteins regulated by the core genes were downloaded from the RCSB-PDB database (reliable .GROMACS (version 2023) with the AMBER FF14SB force field, as described in previous studies [Sobtop version 1.0 (dev3.1) [Multiwfn (dev3.8) through a script [https://plip-tool.biotec.tu-dresden.de/plip-web/plip/index/, accessed on 25 October 2022). The PyMOL was used to visualize the results from the PSE files provided by the PLIP website.MD simulations were conducted using  studies ,52. The (dev3.1) . The RESa script . The conMultiwfn (dev3.8) to analyze non-covalent interactions, including hydrogen bonding, van der Waals forces, and π–π stacking [The MM-GBSA tool was used to calculate the free energy between the protein and VD based on a single trajectory . In thisstacking .In our study, a total of 2067 relevant records were retrieved through online electronic databases. We then employed the EndNote X9 literature manager to exclude 873 duplicates. We further refined our selection process by excluding 926 irrelevant studies, which encompassed conferences, reviews, books, and comments, through the examination of titles and abstracts. After this initial screening, we identified 17 articles of interest after eliminating similar studies  16,56,5,69,70,71Total cholesterol, TC. Among the 15 RCTs analyzed in 2 = 73%, p < 0.00001). Sensitivity analysis revealed that the studies by Farag (1) et al. (2018) and Farag (1) et al. (2019) were the primary sources of heterogeneity due to the inclusion of additional outdoor physical activity alongside a daily 2000 IU VD supplement [2 = 48%, p = 0.03) based on a fixed-effects model. The results indicated a non-significant increase in TC with VD intervention compared to control groups , p = 0.95) in mg/dL.pplement ,64. AfteLow-density lipoprotein cholesterol, LDL-C. The test for heterogeneity  of the 17 RCTs (p = 0.67) in mg/dL. 17 RCTs B suggestHigh-density lipoprotein cholesterol, HDL-C. The analysis of 19 RCTs in 2 = 86%, p < 0.00001) among the studies. After conducting a sensitivity analysis and excluding Najafi (1) et al. (2022) and Najafi (2) et al. (2022) [2 = 21%, p = 0.21) was used to combine effect sizes. The observed heterogeneity in combined HDL-C effect sizes may be due to the high-dose VD supplementation. The results indicated that VD intervention reduced HDL-C levels compared to the control groups, but this reduction was not statistically significant , p = 0.56) in mg/dL.. (2022) , which iTriglyceride, TG. The test for heterogeneity  of the 19 RCTs (p < 0.00001) in mg/dL. 19 RCTs D indicatFasting plasma glucose, FPG. The test for heterogeneity  of the 19 RCTs  after Najafi (2) et al. (2022) [p < 0.00001) in mg/dL. 19 RCTs E indicat. (2022)  was remoFasting insulin, FINS. The test for heterogeneity  of the 15 RCTs  to combine effect sizes. The results showed that VD intervention significantly reduced FINS levels in subjects compared to control groups , p = 0.0003) in µU/mL. 15 RCTs F indicatHomeostasis model assessment of insulin resistance, HOMA-IR. The test for heterogeneity  of the 15 RCTs  to combine effect sizes. In the study by Bhatt et al. (2020) [p < 0.00001). 15 RCTs G indicat. (2020) , particiThe study included serum 25(OH)D H, blood Endocrine Society Clinical Practice Guidelines [Global Consensus (p < 0.00001 *) and LDL-C levels , p = 0.01 *), indicating that VD supplementation can significantly improve lipid profiles in individuals with severe vitamin D deficiency.The current primary international clinical diagnostic criteria for determining serum 25(OH)D status are the idelines . Recentlidelines  have staonsensus  recommenonsensus  for analp < 0.00001 *), along with an increase in HDL-C levels , p < 0.00001 *) among the subjects. However, the subgroup analysis revealed a high heterogeneity of HDL-C  among subjects with baseline serum 25(OH)D levels of 12~20 ng/mL. The source of this heterogeneity was identified as Najafi et al. (2022) [In a subgroup analysis of serum 25(OH)D levels ranging from 12 to 20 ng/mL, VD supplementation resulted in a significant reduction in TG levels , . (2022) , as conf. (2022)  found thCytoscape (version dev-3.9.1) to evaluate the topological parameters associated with the interaction of VD with MetS. The heat map in In our study, we initially screened potential disease-related targets from six databases: Genecards, DisGeNET, TTD, OMIM, PharmGkb, and DrugBank. This yielded different numbers of potential targets from each database: 697, 153, 45, 330, 1093, and 32, respectively. After merging the targets from these six disease databases, we removed any duplicate entries, resulting in a total of 2068 targets related to MetS. Furthermore, we employed five online databases  to predict potential therapeutic targets for VD. These databases provided varying numbers of potential targets: 83, 186, 287, 31, and 26, respectively. In the final compilation, a total of 389 predicted targets were aggregated from these five databases, with careful removal of any duplicate entries. As depicted in In our GO functional enrichment analysis, we observed the following results: 55 entries enriched for cell components, 108 entries enriched for molecular functions, and 388 entries enriched for biological processes. Our findings revealed that the primary cell components of core targets included the plasma membrane, cytosol, and insulin receptor complex A. RegardIn addition, we identified 20 KEGG pathways E associaDiscovery Studio 2019 to redock the proto-ligands to the three target proteins. As shown in By searching for annotation information on the 14 core genes in the NCBI database, we identified three genes primarily associated with MetS and heavily involved in lipid metabolism. These three genes were peroxisome proliferator-activated receptor gamma  , fatty aAs depicted in To investigate the convergence of protein free energy in MD simulations, we plotted the co-correlation matrix plot and free energy landscape (FEL) using the RMSD and gyration of protein backbones as horizontal and vertical coordinates . In the 2  had an unfavorable contribution to ligand–protein binding. In contrast, van der Waals interactions (ΔvdWE), electrostatic interactions (ΔeleE), and the non-polar solvation free energy (Δnon-polG) provided favorable contributions to ligand–protein binding, with ΔvdWE contributing the most to the binding free energy. These findings were consistent with the results of the IGM. Therefore, it could be speculated that van der Waals forces were the driving forces behind the interactions between VD and the core protein receptors.In MetS refers to a pathological state of abnormal metabolism, including central obesity, glucose intolerance, and abnormal lipid metabolism. Due to the diversification of diets and the modernization of lifestyles, the incidence of MetS is not only increasing globally but also affecting individuals at a younger age. As a dietary supplement and nutritional fortifier, VD improves the nutritional value of foods and helps consumers more easily meet their daily VD requirements. VD plays a crucial role in regulating physiological processes, but its relationship with MetS biomarkers remains controversial due to a lack of definitive scientific evidence. This enlightens us to explore new methodologies for investigating VD as a potential treatment for MetS.In this study, we employed meta-analysis, a commonly used method in dietary nutrition research, to examine the effects of VD supplementation on lipid profiles and insulin resistance in individuals with MetS. Our results indicated that VD supplementation effectively reduced serum TG concentrations during the early intervention phase. However, we did not observe statistically significant changes in other vital biomarkers for monitoring lipid metabolism, such as serum LDL-C, HDL-C, and TC levels. These findings were consistent with AlAnouti, F. et al. . FurtherHMG-CoA reductase, a rate-limiting enzyme in cholesterol synthesis, was found to interact with VD through hydrogen and alkyl bonds. Previous studies have also demonstrated that VD directly influences the lipid profile by inhibiting the enzymatic activity of HMGCR ,80. FABPRecent research has linked reduced serum VD levels to an increased risk of MetS and cardiovascular events ,82,83,84In brief, our study represents a pioneering effort to combine meta-analysis and in silico approaches to comprehensively investigate the pharmacological mechanisms and potential targets of VD in individuals with MetS, focusing on dyslipidemia and insulin resistance.We demonstrate the beneficial effects of VD supplementation on MetS, including the regulation of lipid profiles and attenuation of insulin resistance. Given the intricate nature of the occurrence and progression of MetS, there has been increased interest in employing multitarget and multichannel therapeutic strategies, such as dietary VD supplementation, for the prevention of MetS. Through in silico approaches, we predict three key targets , revealing that VD exerts a therapeutic influence on MetS by inhibiting bile secretion and modulating the PPAR signaling pathway. Our findings provide valuable insights into the potential use of VD as a dietary supplement for preventing MetS. In summary, our research on the role of VD in addressing MetS within the field of nutrition can enhance subjects’ quality of life and raise public awareness of health. Future research can involve larger, high-quality RCTs to further elucidate the effects of VD in chronic clinical conditions or other diseases.


Peach kernel and safflower herb-pair (PKSH) are widely used in traditional Chinese medicine for the treatment of liver fibrosis. Therefore, network pharmacology was performed to explore potential therapeutic targets and pharmacological mechanisms of PKSH. The active components of PKSH from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform database and potential targets of liver fibrosis from the Online Mendelian Inheritance in Man, Pharmacogenetics and Pharmacogenomics Knowledge Base, GeneCards, and DrugBank Database were identified. The protein-protein interaction network was constructed using Cytoscape (v3.8.0). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed for the treatment of liver fibrosis, and molecular docking was carried out to verify the results of network pharmacology analysis. After screening disease-related genes, 179 intersection genes overlapped between 196 target proteins of the active compound and 9189 potential disease targets. Furthermore, we obtained 15 hub nodes and 146 edges to establish a related network diagram using CytoNCA. 2559 Gene Ontology biological processes underlying PKSH have been explored for the treatment of liver fibrosis, in which the response to oxidative stress plays a vital role. Furthermore, Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed that PKSH might play a role in inhibiting liver fibrosis, mainly through the PI3K-Akt signaling pathway. PKSH can regulate the response to oxidative stress through the PI3K-Akt signaling pathway for the treatment of liver fibrosis. The main bioactive components in PKSH, including quercetin and luteolin, can activate the PI3K-Akt signaling pathway by binding with the hub targets of the disease, which may provide insights into drug development for liver fibrosis. Liver fibrosis, the main pathological change in the development of chronic liver disease, manifests as excessive proliferation and deposition of extracellular matrix (ECM) in liver tissue. The progression of liver fibrosis can lead to abnormal changes in the structure of the liver tissue and affect the normal physiological function of the liver. Furthermore, the liver parenchyma is gradually replaced by scar tissue formed by the ECM, which eventually leads to liver cirrhosis and even cancer. Long-term stimulation by various pathogenic factors, including hepatitis virus, ethanol, toxins, parasites, and autoimmune abnormalities, can lead to the progression of liver fibrosis.Most chronic liver diseases are accompanied by liver fibrosis owing to the long-term stimulation of pathogenic factors.Chronic liver injury can lead to liver cirrhosis, which seriously affects the health and quality of life of patients. Of approximately 6 billion people in the world, about 2 billion have evidence of hepatitis B virus (HBV) infection, of which 350 to 400 million have chronic HBV infections, accounting for approximately 6% of the global population. Prospective studies have shown that the annual incidence of chronic HBV infection developing into cirrhosis is 2 to 10%, and liver cirrhosis is a common cause of death in gastrointestinal diseases. However, there are still some limitations in the treatment of liver fibrosis. It is important to treat liver fibrosis in patients with chronic liver disease by inhibiting the proliferation of fibrotic tissue and promoting the degradation of ECM. Liver cirrhosis is the outcome of the development of liver fibrosis, and the prevention or reversal of liver fibrosis is an important treatment.Research shows that etiological treatment can help inhibit or even reverse liver fibrosis, which can effectively inhibit viral replication and reverse liver fibrosis in chronic hepatitis B. Traditional Chinese medicine (TCM) against liver fibrosis has been widely used in clinical practice for >20 years, and a large amount of clinical data has been accumulated. Therefore, Chinese medicine has attracted increasing attention because it provides more opportunities for the treatment of chronic liver diseases.Owing to the complex pathological mechanism of liver fibrosis, drugs developed for a single target are difficult to work with in clinical practice; therefore, there is still no biological drug with definite efficacy available to inhibit the proliferation of fibrotic tissue and promote the degradation of ECM. Recent decades of research and applications have shown that Chinese medicine is effective in the treatment of chronic liver disease, especially in the prevention and treatment of liver fibrosis. Furthermore, inflammation is also involved in diseases that may cause liver fibrosis, such as hepatosteatosis, and viral and autoimmune hepatitis.–10 Thus, studying the effects of peach kernel and safflower herb-pair (PKSH) on inhibiting inflammatory response through the PI3K-AKT pathway for the treatment of liver fibrosis makes sense. The formula composed of PKSH is widely used in China to treat chronic hepatitis and liver fibrosis and has a satisfactory therapeutic effect.,12 PKSH improves liver fibrosis by promoting blood circulation. However, few studies have addressed the association between cirrhosis and PKSH. The mechanism by which PKSH plays an antifibrotic role remains to be elucidated. Therefore, it is important to clarify the specific mechanisms of PKSH in the treatment of liver fibrosis by using network pharmacology.PI3K-Akt signaling pathway is involved in inflammation. Molecular docking is a theoretical method used to study the interaction and recognition between protein receptors and small molecule ligands, which can predict the binding mode and strength of drug ligands and targets. In general, network pharmacology and molecular docking in combination can be used to explore the potential mechanism of action of active compounds in TCM and to verify target binding.Network pharmacology systematically predicts possible mechanisms and discusses the relationship between medicine and diseases by constructing a “drug-gene-target-disease” network, which conforms to the holistic view of TCM theory.This study aimed to explore the key components of PKSH through network pharmacology and investigate the key targets and possible mechanisms of action in the treatment of liver fibrosis. In this study, we conducted a comprehensive network pharmacology study to investigate the possible pharmacological mechanism of PKSH in treating liver fibrosis based on Network Pharmacology and Molecular Docking Technology and comprehensively and systematically characterized the intervention and impact of drugs on diseases.http://tcmspw.com/tcmsp.php). The various compounds in PKSH were screened according to pharmacokinetic absorption (A), distribution (D), metabolism (M), and excretion (E) parameters, so molecules with oral bioavailability ≥ 30% and drug-likeness ≥ 0.18 were defined as active molecules. The corresponding target gene information was searched for using the UniProt database (https://www.uniprot.org/). The active compound targets in PKSH were screened in TCMSP and annotated using UniPort and GeneCards databases.The active components and targets of PKSH were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) (https://omim.org/); GeneCards Human Gene database ; DrugBank Database (https://go.drugbank.com/); and Pharmacogenetics and Pharmacogenomics Knowledge Base (https://www.pharmgkb.org/). Furthermore, we removed duplicate targets and merged all collected targets from the 4 databases. Finally, the gene targets were standardized using the UniProt database, and the species was selected as “Homo sapiens.”The gene targets of liver fibrosis were collected from 4 databases by querying with the keywords “liver fibrosis”: Online Mendelian Inheritance in Man database , USA).https://string-db.org/). The liver fibrosis-related target genes of PKSH were input into the STRING database for amplification and prediction, and the interaction of target proteins in the network diagram was obtained. The confidence score in PPIs was set to 0.9 for the highest confidence from the STRING database. The amplified target proteins of PKSH for the treatment of liver fibrosis in the STRING database were input into Cytoscape software V3.8.0, and the protein interaction network was obtained.The protein-protein interaction (PPI) network construction of target proteins in treating liver fibrosis was conducted using Online STRING 11.0  functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed using the cluster Profiler R package 4.1.2 , and the enrichment analysis results were visualized.https://pubchem.ncbi.nlm.nih.gov/), and the structures of key targets were downloaded from the Protein Database database (http://www.rcsb.org/pdb/home/home.do). The Ligand Docking module was used to verify the reliability of the results using AutoDockTools Version 1.5.6 , and the bonding activity of the compound to the key targets was evaluated using the docking score. The higher the absolute value of the docking score, the stronger the binding ability of the small molecules to protease targets.The structures of all compounds were downloaded from the PubChem database , distribution (D), metabolism (M), and excretion (E) parameters. Based on the TCMSP database, there were 23 and 22 compounds in PKSH respectively, which met the criteria of oral bioavailability ≥ 30% and drug-likeness ≥ 0.18. The top 33 compounds of degree in PKSH are listed in Table We screened disease-related genes from the GeneCards, DrugBank, OMIM, and Pharmacogenetics and Pharmacogenomics Knowledge Base databases, there were 179 intersection genes overlapped between 196 target proteins of the active compound and 9189 potential disease targets Fig. .Cytoscape 3.8.0 software was used for network construction. According to this network model, we conducted a scientific analysis of the relationships between the herbs, ingredients, targets, and diseases. We established a “herbal-compound-gene target” network diagram composed of 212 nodes and 415 edges. Through this diagram, we can easily observe the relationship between the herbs, ingredients, and targets, to reveal the potential pharmacological effects of PKSH. The multi-target and synergistic effects of the compatibility of PKSH can be observed through the network diagram , and KEGG signal pathways, we built a “Compounds-Core targets-GO biological processes-Signal Pathways” network diagram, which was composed of 8 compounds, 15 targets, 10 GO BPs, and 10 KEGG signal pathways Fig. B.By analyzing the diagram, targets including EGFR, AKT1, MYC, RELA, JUN, MAPK1, FOS, HIF1A, CTNNB1, CCND1, ESR1, TP53, RUNX2, RB1, and CDKN1A may be core targets of the PKSH in the treatment of liver fibrosis . The GO database including BP, molecular function (MF), and cellular component (CC), was used to explore the potential biological molecular mechanisms. The KEGG database was used to identify biological functions and candidate targets.After enrichment analysis of 179 hub targets, we got 2559 GO BPs and 168 KEGG pathways . According to the P value, we selected the top 10 GO BPs for analysis, and the following were identified: (GO: 0009410) response to xenobiotic stimulus, (GO: 0010038) response to metal ion, (GO: 0006979) response to oxidative stress, (GO: 0032496) response to lipopolysaccharide, (GO: 0002237) response to molecule of bacterial origin, (GO: 0031667) response to nutrient levels, (GO: 0062197) cellular response to chemical stress, (GO: 0070482) response to oxygen levels, (GO: 0034599) cellular response to oxidative stress, and (GO: 0000302) response to reactive oxygen species , human cytomegalovirus infection signaling pathway (hsa05163), PI3K-Akt signaling pathway (hsa04151), Kaposi sarcoma-associated herpesvirus infection signaling pathway (hsa05167), and chemical carcinogenesis receptor activation signaling pathway (hsa05207)  in PKSH played a coordinating role in the treatment of liver fibrosis. Meanwhile, the main bioactive components, including quercetin and luteolin, could activate the PI3K-Akt signaling pathway by binding with the hub targets of disease and inhibiting liver fibrosis. By observing a Venny diagram of the disease and targets of PKSH, we identified 179 related genes and 15 hub genes. Overlapping genes between the target genes of active compounds and liver fibrosis-related genes, including PTGS2, GABRA1, PTGS1, HSP90AB1, PGR, CHRM1, PRSS1, CHRM2, CASP3, and DPP4, may play an important role in the treatment of liver fibrosis. Subsequently, 15 hub targets including EGFR, AKT1, MYC, RELA, JUN, MAPK1, FOS, HIF1A, CTNNB1, CCND1, ESR1, TP53, RUNX2, RB1, and CDKN1A in PPI network were obtained using Cytoscape software. Meanwhile, several typical targets and pathways in PKSH, including Lipid and atherosclerosis and PI3K-Akt signaling pathways, may contribute to the treatment of liver fibrosis. By constructing the Drug-Compound-Target-Diseases Network, we revealed that multiple ingredients in PKSH affected liver fibrosis-related targets and predicted potential signaling pathways in the treatment of liver fibrosis.A total of 2559 GO BPs, including 2283 BP, 190 MF, and 86 CC terms, were found to be enriched in GO enrichment analysis. (GO: 0006979) response to oxidative stress in GO BPs is the main BP for the treatment of liver fibrosis. Highly expressed hub genes are associated with lipid and atherosclerosis and PI3K/Akt pathways to treat liver fibrosis. In the current study, we performed a network pharmacology analysis to explore the mechanism of PKSH in the prevention of liver fibrosis. Our results revealed that 33 key ingredients were screened and predicted as the active ingredients of PKSH. According to the degree of composition, the components of PKSH are quercetin (MOL000098), luteolin (MOL000006), kaempferol (MOL000422), baicalein (MOL002714), and stigmasterol (MOL000449). We used the main bioactive components, including quercetin and luteolin, to bind to the hub targets of the disease. The results revealed that quercetin and luteolin could activate the PI3K-Akt signaling pathway and inhibit liver fibrosis by binding to hub targets, including AKT1, CCND1, EGFR, MAPK1, MYC, and RELA. Quercetin has many functions, such as antioxidant, anti-inflammatory, and immune regulation, and many studies have confirmed the biological activity of quercetin in the treatment of liver fibrosis. Quercetin acts on 138 target genes related to liver fibrosis and plays an antifibrotic role in our PPI network; thus, it might be a promising therapeutic agent for liver fibrosis. Luteolin prevents the progression of liver fibrosis through multiple mechanisms. In our results, Luteolin acted on 53 target genes related to liver fibrosis and played an antifibrotic role in our PPI network. Kaempferol and baicalein have been proven to play antifibrotic roles. The common ingredient β-sitosterol (MOL000358) in PKSH also played a role in the treatment of liver fibrosis.Previous studies have indicated that PKSH contributes to pharmacological effects, including improving blood circulation, preventing atherosclerosis, regulating menstruation, and relieving pain. Both the expression and synthesis of these inflammatory and pro-fibrogenic cytokines, which are secreted by these cells, are regulated mainly by oxidative stress. In addition, the participation of reactive oxygen species and lipid peroxidation products, such as the activation and action of stellate cells, can be clearly demonstrated in other basic events of liver fibrosis. Hence, the response to oxidative stress contributes to both the onset and progression of liver fibrosis, and PKSH may inhibit liver fibrosis by regulating oxidative stress reactions.The formation mechanisms of liver fibrosis, which are caused by various factors, are complicated. The response to oxidative stress (GO: 0006979) in the BP played a vital role in the treatment of liver fibrosis. In the process of liver fibrosis, Kupffer cells recruit mononuclear cells, and hepatic stellate cells play a key role in liver fibrosis. Our results also revealed that the PI3K-Akt signaling pathway may be the main regulatory pathway for PKSH to play an inhibitory role in liver fibrosis. AKT and mTOR, key molecules of the PI3K pathway, can inhibit the activation of HSC and liver fibrosis. Therefore, PKSH may inhibit the activation of HSC by inhibiting the key molecules AKT and mTOR in the PI3K/AKT signaling pathway, thus inhibiting liver fibrosis.Research has indicated that the PI3K-AKT pathway is associated with the degree of liver fibrosis.Although network pharmacology has many advantages, it has some limitations. First, the reliability of network pharmacology needs to be further verified for network pharmacology is based on databases and computer analysis. Second, some active drug components identified by network pharmacology do not play important roles in clinical practice. Third, network pharmacology cannot detect the efficacy of drugs, which requires experimental verification.In summary, we demonstrated that PKSH has a notable effect on inhibiting liver fibrosis. The main bioactive components in PKSH, including quercetin and luteolin, could activate the PI3K-Akt signaling pathway by binding with the hub targets of disease and inhibit liver fibrosis. The mechanism of action may regulate the response to oxidative stress through the PI3K-Akt signaling pathway, which may provide insights into drug development and follow-up pharmacologic research for liver fibrosis.We would like to acknowledge the support of the Department of No. 1 Surgery, The First Hospital Affiliated to Anhui Chinese Medical University, China.Conceptualization: Long Huang.Data curation: Long Huang, Qingsheng Yu.Formal analysis: Long Huang, Hui Peng.Funding acquisition: Qingsheng Yu.Investigation: Long Huang.Methodology: Long Huang.Project administration: Long Huang, Qingsheng Yu.Resources: Long Huang, Hui Peng, Zhou Zhen.Software: Long Huang, Hui Peng, Zhou Zhen.Validation: Long Huang, Qingsheng Yu, Hui Peng, Zhou Zhen.Visualization: Long Huang, Zhou Zhen.Writing – original draft: Long Huang, Zhou Zhen.Writing – review & editing: Long Huang, Zhou Zhen.


Idiopathic sudden hearing loss (ISHL) is characterized by sudden unexplainable and unilateral hearing loss as a clinically emergent symptom. The use of the herb Erlongjiaonang (ELJN) in traditional Chinese medicine is known to effectively control and cure ISHL. This study explored the underlying molecular mechanisms using network pharmacology and molecular docking analyses.The Traditional Chinese Medicine System Pharmacological database and the Swiss Target Prediction database were searched for the identification of ELJN constituents and potential gene targets, respectively, while ISHL-related gene abnormality was assessed using the Online Mendelian Inheritance in Man and Gene Card databases. The interaction of ELJN gene targets with ISHL genes was obtained after these databases were cross-screened, and a drug component–intersecting target network was constructed, and the gene ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes, and protein–protein interaction networks were analyzed. Cytoscape software tools were used to map the active components–crossover target–signaling pathway network and screened targets were then validated by establishing molecular docking with the corresponding components.Erlongjiaonang contains 85 components and 250 corresponding gene targets, while ISHL has 714 disease-related targets, resulting in 66 cross-targets. The bioinformatical analyses revealed these 66 cross-targets, including isorhamnetin and formononetin on NOS3 expression, baicalein on AKT1 activity, and kaempferol and quercetin on NOS3 and AKT1 activity, as potential ELJN-induced anti-ISHL targets.This study uncovered potential ELJN gene targets and molecular signaling pathways in the control of ISHL, providing a molecular basis for further investigation of the anti-ISHL activity of ELJN. Idiopathic sudden hearing loss (ISHL), a class of sudden sensorineural hearing loss (SSNHL), is characterized by sudden unexplainable and unilateral hearing loss. Clinically, ISHL can cause persistent tinnitus and/or hearing loss, leading to reduced quality of life. It affected an estimated 27 per 100,000 individuals in 2007 . To dateTraditional Chinese medicine, as one form of alternative medicine, utilizes botanical, mineral, or animal-derived agents to control or release human diseases and syndromes. According to Chinese Pharmacopoeia 2020, Erlongjiaonang (ELJN), as an oral capsule, is prescribed to treat dizziness, headache, deafness, tinnitus, and ear discharge as caused by the TCM theory of “damp heat” in the liver and gallbladder . A recenNetwork pharmacology refers to a combination of pharmacology with bioinformatics and systems biology to assess the multi-compound, multi-targets, and multi-pathway characteristics in TCM . Thus, iErlongjiaonang contains 10 different TCM herbs: Gardeniae Fructus, Alisma, Caulis Akebiae, Gentianae Radix Et Rhozima, Anemone Altaica Fisch, Rehmanniae Radix Praeparata, Angelicae Sinensis Radix, Licorice, Scutellariae Radix, and Antelope Horn. These herbs were used to search the 2020 Chinese Pharmacopoeia and the Traditional Chinese Medicine System Pharmacological (TCMSP) databasesExcel file.The terms “idiopathic sudden deafness” and “idiopathic sudden hearing loss” were used as the keywords when searching the Online Mendelian Inheritance in Man (OMIM) databaseWe mapped the potential ELJN gene targets and ISHL targets with a Venn diagram using the Venny2.1 toolp-value of <0.05 was considered statistically significant.We next performed the GO and KEGG analyses of the intersecting genes. The GO terms included biological processes (BPs), cellular components (CCs), and molecular functions (MFs). The GO and KEGG analyses were performed using Metascape softwareThe data on the common targets of ELJN and ISHL were imported into the STRING V11.5 databaseWe performed molecular docking analysis of the target and corresponding active components from the above procedures using the retrieved InChlKey components from the TCMSP and PubChem databases , in ordeErlongjiaonang, as in a powder form, contains 10 different TCM herbs, i.e., Gardeniae Fructus, Alisma, Caulis Akebiae, Gentianae Radix Et Rhozima, Anemone altaica Fisch, Rehmanniae Radix Praeparata, Angelicae Sinensis Radix, Licorice, Scutellariae Radix, and Antelope Horn. We then searched the constituent herbs of ELJN in the TCMSP database and reviewed the relevant PubMed literature, as well as considered Lipinski’s rules  and founSubsequently, we utilized the 85 active components in ELJN, using the cutoff values of >30% OB, and > 0.18 DL, and obtained 250 gene targets accordingly ; thus, wSimilarly, we obtained a total of 714 ISHL-related gene targets after searching the OMIM, Genecards, and TTD databases. We then constructed a Venn diagram using Venn 2.1 to illustrate the connection between ELJN and ISHL with 66 drug–disease intersection targets . After cThe results of the GO analysis show that mainly enriched biological processes, such as the responses to stimuli, regulation of biological processes, multicellular organismal processes, negative regulation of biological processes, positive regulation of biological processes, metabolic processes, biological processes involved in interspecies interaction between organisms, signaling pathways, biological regulation, growth, immune system processes, and many others. Furthermore, the enriched cellular components included cytokine activity, protease binding, protein domain-specific binding, phosphatase binding, metalloendopeptidase activity, scaffold protein binding, inorganic molecular entity transmembrane transporter activity, lipid binding, neurotransmitter receptor activity, kinase regulator activity, oxidoreductase activity, protein homodimerization activity, and protein kinase activity .Helicobacter pylori infection, and retrograde endocannabinoid signaling . We ranked the intersection targets according to the “degree” value for the top 10 intersection gene targets . Next, wIn addition, we searched for components that are associated with these two genes and identified isorhamnetin, formononetin, kaempferol, quercetin, naringenin, oroxylin A, 7-methoxy-2-methyl isoflavone, Glepidotin A, Salvigenin, Skullcapflavone II, 5,2′-dihydroxy-6,7,8, trimethoxyflavone, coptisine, epiberberine, rivularin, sesamin, 5-hydroxy-7-methoxy-2-chromone, beta-sitosterol, acacetin, wogonin, and baicalein. After narrowing these down, we concluded that isorhamnetin, formononetin, kaempferol, quercetin, and baicalein were somehow associated with ISHL .We then molecularly docked NOS3 and AKT1 with five ligands  and identified nine sets of docking results . The binThe precise etiology of ISHL remains to be defined, but multiple causes have been hypothesized, including vascular obstruction in the ear, viral infection, and/or labyrinthine membrane ruptures . ClinicaIsorhamnetin, a component of ELJN, is also one of the most important active components in sea buckthorn fruit and ginkgo biloba . It is aThe ELJN component formononetin is an isoflavone derived from the legume family. It is a member of the phytoestrogen class of compounds and clinically possesses antioxidative, anti-inflammatory, neuroprotective, and blood pressure-lowering activities . For exaIn addition, the ELJN component baicalein is the most abundant active component in Scutellaria baicalensis with neuroprotective effects . Baicalevia CD36 inhibition chromone, beta-sitosterol, acacetin, and wogonin might have similar effects in the therapeutic process, but we excluded them after our screening, perhaps more evidence for their effects will be available later.In conclusion, our network pharmacology and molecular docking analyses revealed the potential gene targets of both ELJN and ISHL. The effect of ELJN treatment on ISHL could be due to the ELJN components isorhamnetin, formononetin, baicalein, kaempferol, and quercetin binding to AKT1 and NOS3 to reduce inflammatory responses and damage to inner ear hair cells. Further studies are needed to experimentally confirm these data.The original contributions presented in the study are included in the article/Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent from the patients/participants or patients/participants’ legal guardian/next of kin was not required to participate in this study in accordance with the national legislation and the institutional requirements.XS, YY, and YaS: conceptualization of the study. HZ and YW: data acquisition. CX and JQ: data analysis and processing. HZ, YW, and CX: software research. GL, YuS, JQ, LC, XS, YY, and YaS: supervision and design of this study. HZ, YW, and CX: preparation of the original draft of this manuscript. XS, YY, and YaS: manuscript revision, critical review and editing. All authors contributed to the article and approved the submitted version.This work was supported in part by grants from Natural Science Foundation of Shandong Province (ZR2021MH378), Natural Science Foundation of Shandong Province (ZR2022QH073), Shandong Society of Geriatrics science and technology project (LKJGG2021Z020), and the Yantai Science and Technology Innovation Development Project (2021MSGY046).The authors declare that this research was conducted in the absence of any commercial or financial support that could be considered a conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.https://www.frontiersin.org/articles/10.3389/fneur.2023.1121738/full#supplementary-materialThe Supplementary material for this article can be found online at: Click here for additional data file.


Huangkui Capsule is a single herbal concoction prepared from the flower of Abelmoschus manihot, which is used to treat idiopathic membranous nephropathy (IMN), a frequent pathologically damaging kidney condition. It has been widely utilized to treat a variety of renal disorders, including IMN, in clinical practice. However, the active compounds and mechanism of action underlying the anti-IMN effects of Huangkui Capsule remain unclear. In this study, we aimed to predict the potential active compounds and molecular targets of Huangkui Capsule for the treatment of IMN.The possible active components of Huangkui were located using the SymMap v2 database. The targets of these drugs were predicted using Swiss Target Prediction, while IMN-related genes with association scores under 5 were gathered from the GeneCards and DisGeNET databases. The common targets of the disease and the components were determined using VENNY 2.1. Using Cytoscape 3.8.0, a drug-disease network diagram was created. Molecular docking was carried out with Pymol, AutoDock Tools, and AutoDock Vina.With 1260 IMN-related illness genes gathered from GeneCards and DisGeNET databases, we were able to identify 5 potentially active chemicals and their 169 target proteins in Huangkui. Based on degree value, the top 6 targets for Huangkui treatment of IMN were chosen, including AKT, MAPK3, PPARG, MMP9, ESR1, and KDR.This work theoretically explains the mechanism of action of Huangkui Capsule in treating IMN and offers a foundation for using Huangkui Capsule in treating IMN in clinical settings. The findings require additional experimental validation. Its traits include the thickening of the kidney’s capillary wall, modifications to the basement membrane, and the presence of substantial immune deposits in the subepithelial area. The incidence of IMN, the most prevalent pathogenic form of adult nephrotic syndrome, is rising in China and is one of the major causes of renal failure. Approximately 1 to 3rd of IMN patients experience a spontaneous remission, 1 to 3rd experience chronic proteinuria and long-term preservation of renal function, and the remaining 1 to 3rd experience a steady progression of the disease till end-stage renal disease. As a result, the prognosis of the condition depends on how IMN patients are treated. Immunosuppressive therapy, which involves the use of numerous hormone drugs to weaken the patient’s own immunity in order to diminish proteinuria and postpone the future development of IMN, is currently the most common form of treatment. However, it is impossible to overlook the negative effects of hormone therapy, and IMN following hormone therapy is still prone to relapse.One of the most common glomerular disorders in adults is Membranous Nephropathy, a condition characterized by glomerular damage brought on by autoimmune responses. It is known as primary membranous nephropathy or idiopathic membranous nephropathy (IMN) and affects about 80% of MN cases. Huangkui capsule may treat kidney diseases by reducing inflammation and oxidative stress, enhancing immune responses, protecting renal tubular epithelial cells, reducing podocyte apoptosis, glomerulosclerosis, and mesangial proliferation, and inhibiting renal fibrosis, according to recent pharmacological studies.,8 However, little is known about the chemical constituents and mechanisms underlying Huangkui anti-IMN actions. With its Holistic Concept, TCM diagnosis and treatment philosophy has spawned a new wave of research models that are defined by “network” and “system” aspects. To comprehend the multi-target and multi-pathway processes of TCM, emerging network pharmacology and molecular docking approaches are now frequently employed to determine the effective components of medications.,10 Therefore, in this study, we used network pharmacology and molecular docking techniques to predict the potential active ingredients, molecular targets, and signaling pathways of Huangkui against IMN.Over the course of thousands of years, Traditional Chinese Medicine (TCM) has amassed invaluable information in the fight against diseases. Water hibiscus, also known as huangkui (Abelmoschus manihot), has a history that dates back to Ge Hong “Prescriptions for Emergent Reference” in the Eastern Jin Dynasty (3–4th century AD), or roughly 2000 years ago. In China, the ethanol extract of Huangkui is used to make the TCM supplement known as the Huangkui capsule, which is used to treat renal illnesses such as IMN. In China, the ethanol extract of Huangkui is used to make the TCM supplement known as the Huangkui capsule, which is used to treat renal illnesses such as IMN.http://www.symmap.org/) contains a large number of herbs, components, and matching TCM symptoms that are closely related to modern medicine (MM) symptom words. Through symptom-disease or constituent-target interactions, SymMap also gathers the targets (genes) and diseases linked to these herbs, totaling 4302 targets and 5235 disorders. As a result, SymMap offers a wealth of descriptive data on herbs, TCM symptoms, MM symptoms, ingredients, targets, and disorders. Additionally, it gives pairwise correlations between all 6 types of components, including associations between herbs, TCM syndrome, MM symptoms, constituent diseases, and targets, using either direct or indirect statistical inference. This links TCM and modern medicine from the phenotypic to the molecular levels. The keyword “Abelmoschus manihot” was used to do a search in SymMap, and its component parts were exported.A database of TCM syndrome correlations called Symptom Mapping  includes information on the absorption, distribution, metabolism, and excretion characteristics of each compound. Oral bioavailability (OB) is a term that refers to “the rate and extent of absorption of the active ingredient or active part from the therapeutic product, which is available at the target site “. Drug-likeness (DL) is a qualitative paradigm for drug design that combines the ADME  qualities of ingredients and existing drugs. In the TCMSP database, potential active compounds from Huangkui were collected by searching for compounds that simultaneously meet the requirements of OB ≥ 30% and DL ≥ 0.18 for subsequent target prediction.The Traditional Chinese Medicine Systems Pharmacology database and analysis platform , a freely accessible open database initiative funded by the National Institutes of Health and built on the bioinformatics platform of the National Center for Biotechnology Information. A significant amount of experimental structural and biochemical data on small molecule drugs is kept in PubChem. The SMILES formula was discovered while scanning Pubchem for maybe active Huangkui compounds.A search for possible Huangkui active ingredients was carried out in PubChem  being human proteins. Swiss Target Prediction provides a score for each predicted target to assess the likelihood of correct prediction. It also makes predictions based on homology mapping between different species and provides probability scores for correctness.https://www.disgenet.org/) is a database that specializes in gathering data on human genes and mutation sites associated with diseases. Gene Cards, a comprehensive database of human genes, may be found at https://www.genecards.org. It offers short details on all identified and expected human genes in relation to genomics, proteomics, transcription, genetics, and function. Gene Cards provide useful data, such as associations with illnesses, polymorphisms and mutations, gene expression, gene function, pathways, protein-protein interactions, and more.DisGeNet (We searched and gathered genes in the DisGeNet and Gene Cards databases using the phrase “Idiopathic Membranous Nephropathy” and chose genes with a relevance score of 5 as disease-associated targets for IMN.https://bioinfogp.cnb.csic.es/tools/venny/index.html). Huangkui prospective targets for treating IMN are represented by the resulting collection of common targets.IMN-related targets were compared to the putative targets of Huangkui active components, and the intersection of the 2 sets was discovered using the Venny 2.1.0 online tool (https://cn.string-db.org/) to analyze the potential targets of Huangkui for treating IMN, limited to Homo sapiens, with a minimum interaction score set at medium confidence (0.400), and hidden nodes without connections in the network. This analysis allowed us to fully understand biological phenomena and identify the relationships among the 67 potential targets of Huangkui for treating IMN. The protein-protein interactions (PPI) were gathered. The String database, a database for searching protein-protein interactions, was created by Peer Bork team at the European Molecular Biology Laboratory on the functional link between genes. It encompasses both indirect functional correlations between proteins and their direct physical interactions. Along with experimental data, outcomes gleaned from PubMed abstracts, and combined information from other sources, it also contains outcomes foreseen using bioinformatics techniques.,18 Cytoscape software (version 3.8.0) was used to further visualize the results of the PPI study.The relationship between proteins and their functions, as is widely known, is the basis of cellular systems. Proteins are the primary carriers of all biological activity. We used the Search Tool for the Retrieval of Interaction Gene/Proteins , cellular component (CC), and molecular function, which can help identify basic genes in specific organisms to facilitate the study of their basic roles in living organisms. KEGG is a manually curated database resource that integrates various biological objects classified into systems, genomes, chemistry, and health information. The core pathways revealed by KEGG enrichment analysis and the connections between these basic genes can further help us understand the key roles of these genes. GO and KEGG enrichment analysis were performed using the DAVID Bioinformatics Resources database, which was developed by the Laboratory of Human Retrovirology and Immunoinformatics. Running the database yielded the results of the GO functional enrichment analysis and KEGG pathway enrichment analysis after importing the target genes of Huangkui for IMN and choosing the species as humans.GO and KEGG enrichment analysis are common tools for analyzing genes.,24 The PubChem database was searched for probable Huangkui active ingredients, and their 2D structures were obtained in SDF format for this investigation. ChemDraw V20 and Chem3D were used to convert the structures into 3D structures and save them in pdb format. Using Auto Dock Tools 1.5.7, the compounds were transformed into ligands by adding charges before being exported in pdpqt format for future molecular docking. The protein sequence database Uniprot (https://www.uniprot.org) was used to identify the core target, and the Protein Data Bank (https://www.rcsb.org) was used to locate the related 3D crystal structure. In pymol, the 3D structure was opened, and extra chains, ions, and water molecules were taken out. Auto Dock Tools 1.5.7 was then used to convert the protein into pdbqt format for molecular docking. The macromolecule (core target protein) and ligand  structures were successively imported into AutoDockTools 1.5.7 in the pdbqt format, the Grid Box parameters were configured and saved, AutoDock Vina 1.2.3 was used to perform molecular docking, and the outcomes were exported. Pymol 2.5 was used to visualize and analyze the complex of the core target protein and the ligand following molecular docking in order to determine their relative binding affinities.Molecular docking is a widely used in drug discovery that aims to predict the binding conformation of small molecule ligands to appropriate target binding sites. Docking can identify new compounds with therapeutic potential, predict ligand-target interactions at the molecular level, or depict structure-activity relationships without prior knowledge of the chemical structures of other target modulators.In SymMap v2, 29 elements were connected to Huangkui. Five possible active compounds were discovered following screening in TCMSP using the criterion of OB ≥ 30% and DL ≥ 0.18, as shown in Table According to the Swiss Target Prediction website, the 5 possible active Ingredients could each affect 500 different targets. Setting a threshold of probability > 0 and eliminating duplicate targets among the 5 Ingredients allowed for further selection, leaving 169 viable targets for additional study, as shown in Figure 2316 IMN-related genes and 79 IMN-related genes were found in the Gene Cards database and DisGeNET, respectively. We ultimately found 1260 IMN-related genes by restricting the Relevance Score ≥ 5 and taking the intersection.The possible targets of Huangkui for the treatment of IMN are depicted in Figure P value < 1.0E-16.In order to create the PPI network depicted in Figure https://cytoscape.org/) was used to import the TSV-formatted results of the String database analysis. AKT1, MAPK3, PPARG, MMP9, ESR1, and KDR were chosen as the key targets of Huangkui for the therapy of IMN . A smaller value denotes a tighter and more substantial binding. Typically, a value of < 1.2 kcal/mol is considered relevant for docking. For each core target and component docking, the highest 9 sets of binding energy scores were chosen and displayed in a circular cluster map Fig. . The fin–28 On the other hand, there is not a lot of study on its application in the management of IMN. Therefore, this study analyzes the potential active ingredients and potential molecular mechanisms of Huangkui capsule in the treatment of IMN based on systems biology theory and molecular docking technology  rat model, which was connected to the development of considerable proteinuria following glomerular filtration barrier disruption. Additionally, it was discovered that MMP9 was considerably elevated in IMN patients” urine as compared to urine samples from healthy controls. ESR1 is an estrogen receptor, a transcription factor that is activated by ligands and mediates the actions of estrogen. The renal endothelin-1 system and mitochondrial homeostasis are both controlled by estrogen receptors. Through its receptor in the proximal tubule, estrogen controls phosphate balance and contributes to kidney repair and regeneration.–45 Vascular endothelial growth factor receptor-2 is the protein that KDR encodes, and its stimulation can result in or exacerbate kidney damage. A VEGFR2 kinase inhibitor was used by Lavoz C et al to cure mouse diabetic nephropathy. The restoration of podocyte marker gene expression and the downregulation of renal injury biomarkers and pro-inflammatory mediators are examples of downstream pathways that greatly improved interstitial nephritis, tubular atrophy, and renal function. Furthermore, inhibiting VEGFR2 with pharmacological kinase inhibitors or gene silencing reversed alterations in epithelial-mesenchymal transition-related genes and decreased the activation of fibrotic factors mediated by Gremlin, delaying the onset of renal fibrosis.According to the PPI study based on the STRING database, Huangkui capsules target numerous drug-disease common targets when treating IMN. Following screening, AKT1, MAPK3, PPARG, MMP9, ESR1, and KDR were shown to be the primary core targets. AKT1, one of the primary targets suggested for Huangkui capsule therapy for IMN, contributes to the emergence and development of IMN via the PI3K/AKT signaling pathway. AKT1 is a crucial component in this pathway and encodes serine/threonine-protein kinases. It is a member of the AKT family. It is activated by extracellular signals and takes role in boosting biological activities like metabolism, cell proliferation, cell survival, growth, and angiogenesis through a mechanism that depends on PI3K. Triptolide cures MN through modifying the P13K/AKT1/mTOR signaling pathway, according to Zhang P. et al Nephrin is a crucial protein that makes up the glomerular filtration barrier, and it’s phosphorylation level is linked to the development of IMN proteinuria.,51 One of the characteristics of MN is podocyte apoptosis, and some studies have suggested that preventing or even lowering podocyte apoptosis is advantageous for the treatment of MN.,53 These existing research frameworks attest to the applicability of the GO enrichment analysis findings in this study to IMN. The key active compounds in Solanum nigrum’s treatment of IMN involve multiple signal pathways, including the PI3K-Akt signaling pathway, Endocrine resistance, Phospholipase D signaling pathway, Rap1 signaling pathway, Ras signaling pathway, and others, according to the results of KEGG pathway enrichment analysis  cell subsets, including dominant subsets like Th2, Th17, follicular helper T cells, and subdominant subsets like regulatory T cells, which promote the occurrence and development of autoimmune reactions, is what distinguishes IMN as an autoimmune disease. One method for treating this illness is to control T cell growth.There are certain restrictions to this study, despite the fact that it potentially identifies the targets and signaling pathways of Huangkui capsule in the therapy of IMN. The chemical components of Huangkui that have been found are used as the research subject in network pharmacology. The advantage of this approach is that the structure and chemical constituents are both transparent, but TCM is not just a straightforward collection of chemical constituents. The concentration, content, and interactions of the various ingredients in Huangkui capsule all have an impact on their effectiveness. Additionally, the databases utilized to compile data on targets, components, etc. have limits and are unable to reveal the full scope of Huangkui capsule pharmacological effects in the management of IMN. The most crucial point is that network pharmacology research has the same limitations – any scientific hypothesis cannot be divorced from experimental verification. Only by combining network-based computational prediction and experimental confirmation, and carrying out biological experiments on the prediction results of network pharmacology of Huangkui capsules in the treatment of IMN, can the accuracy and reliability of the prediction results be verified, providing strong evidence support for the development of new Chinese medicine for treating “modern diseases”.This study examined putative active ingredients and hypothesized potential molecular pathways for Huangkui capsule treatment of IMN. Six key targets for treating IMN and 5 probable active ingredients in Huangkui capsule were found in this investigation. RNA polymerase II promoter transcription and cell proliferation are positively regulated, apoptosis is negatively regulated, and tyrosine kinase signaling pathways are involved in the process by which Huangkui capsule treats IMN. Six major signaling pathways, including the PI3K-Akt signaling pathway, metabolic pathways, cancer pathways, protein glycosylation pathways in cancer, chemical carcinogenesis-receptor activation pathway, and chemical carcinogenesis-reactive oxygen species pathway, were also found to be potentially involved. Of these, the PI3K-Akt signaling pathway is the most extensively researched. The positive docking of active ingredients in Huangkui capsule with core targets was confirmed by molecular docking data. According to the findings of our study, the therapeutic impact of Huangkui capsule on IMN is attained through a variety of elements, a variety of paths, and a variety of targets. The findings of this study serve as a theoretical underpinning for the therapeutic treatment of IMN with Huangkui capsules as well as a foundation for further Huangkui capsule promotion.Conceptualization: Yongjing Xiang.Data curation: Juan Xie.Funding acquisition: Zhengsheng Li.Methodology: Zhengsheng Li.Writing – original draft: Meng Cai.Writing – review & editing: Fulong Wen.


Flowering is a crucial process in the life cycle of most plants as it is essential for the reproductive success and genetic diversity of the species. There are situations in which breeders want to expedite, delay, or prevent flowering, for example, to shorten or prolong vegetative growth, to prevent unwanted pollination, to reduce the risk of diseases or pests, or to modify the plant’s phenotypes. This review aims to provide an overview of the current state of knowledge to use CRISPR/Cas9, a powerful genome-editing technology to modify specific DNA sequences related to flowering induction. We discuss the underlying molecular mechanisms governing the regulation of the photoperiod, autonomous, vernalization, hormonal, sugar, aging, and temperature signal pathways regulating the flowering time. In addition, we are investigating the most effective strategies for nominating target genes. Furthermore, we have collected a dataset showing successful applications of CRISPR technology to accelerate flowering in several plant species from 2015 up to date. Finally, we explore the opportunities and challenges of using the potential of CRISPR technology in flowering time engineering. The induction of flowering is a key process in the life cycle of mature angiosperms because it marks the transition from vegetative growth to reproductive development. During this process, shoot apical meristems (SAM) undergo several changes in their metabolism, morphology, and gene expression.Natural selection exerts selective pressure on plants that exhibit synchronized flowering, eliminating individuals that deviate from this optimal timing. Early flowering carries risks, such as being susceptibility to damage from late frosts, and the insufficient availability of pollinators and other flowering individuals for effective pollination. Conversely, delayed flowering can lead to inhospitable conditions for seed maturation or dispersal, failure to complete the seed set before mortality from late season frost or drought, or the production of progeny in unfavorable growing environments ,2,3,4,5.In addition to natural selection, as part of the domestication process, early farmers made conscious or unconscious choices regarding the flowering time in light of the harvest time and yield practices. These decisions focused on strategically managing workloads over different time frames, optimizing the use of labor, and maximizing overall productivity ,7. TodayGlobal climate change causes heat waves, extreme cold, changing temperatures and rainfall patterns, and disrupts the phenology of many plant species and the development of their pollinators, leading to anomalous fertility and a suboptimal fruit set ,24,25,26The recent pioneering technique of CRISPR offers a revolutionary solution to the above challenges. To effectively select the genes to be edited, a solid understanding of the relevant pathways and molecular mechanisms is essential. In the following chapter, we will take a closer look at these mechanisms and pathways.A series of experiments beginning in 1865 led to the introduction of the florigen hypothesis, which postulated the existence of a substance that could be transferred from the leaf to the shoot and induce flowering. This hypothesis led to widespread research efforts to elucidate the nature and existence of florigen ,28. FlorThe generally accepted schematic of physiological pathways proposed by Corbesier and Coupland (2005)  to contrThe transcription factor, known as CONSTANS (CO), plays a central role in this pathway. Its role is to enhance FT expression by forming a complex with NUCLEAR FACTORY Y subunits (NF-Ys), TGACG MOTIF- BINDING FACTOR 4 (TGA4), or ASYMMETRIC LEAVES 1 (AS1). The activation of this pathway is primarily controlled by the circadian clock, orchestrated by GIGANTEA (GI), FLOWERING BHLHs (FBHs), RED AND FAR-RED INSENSITIVE 2 (RFI2), REPRESSOR OF UV-B PHOTOMORPHOGENESIS 2 (RUP2), and CONSTITUTIVE PHOTOMORPHOGENIC 1 (COP1). In addition, non-circadian regulators such as the MULTICOPY SUPPRESSOR OF IRA1 (MSI1), DAY NEUTRAL FLOWERING (DNF), and MEDIATOR25 (MED25) also play a role in the initiation of this pathway. All these elements can either positively or negatively influence the expression of CO. CO activity is also modulated by PHYTOCHROME A (PHYA), which is more sensitive to far-red light, and PHYTOCHROME B (PHYB), which responds better to red light. While PHYA acts as a positive regulator, PHYB exerts a negative control on CO. CO is regulated in transcriptional and translational levels. On short days (SDs), although the mRNA levels are high, the translation into protein does not take place. This is because COP1 and PHYB act as negative regulators during the translation process. On the other hand, on long days (LDs), GI and PHYA stimulate the translation of CO mRNA. The presence of CO protein peaks during the last hours of daylight and decreases as darkness begins ,44,45,46In the autonomous pathway, the FLOWERING LOCUS C (FLC) serves as the major player, forming a complex with the SHORT VEGETATIVE PHASE (SVP) to negatively regulate FT in leaves and the SUPRESSOR OF OVEREXPRESSION OF CO1 (SOC1) in SAM.The autonomous pathway is the most crowded of the flowering pathways, involving approximately 115 genes, mostly multifunctional, that control diverse processes including the cell cycle and DNA replication, chromatin modification, transcriptional regulation, the control of protein stability, and the processing of mRNA and microRNA. Notably, FLOWERING CONTROL LOCUS A (FCA) induces a reduction in FLC mRNA levels, FLOWERING LOCUS D (FLD) represses FLC by facilitating histone H3 Lys-4 demethylation at the FLC site, and FLOWERING LOCUS KH (FLK) represses FLC through post-transcriptional modification. It is also important to note that biotic stress, which affects flowering, is also considered as a part of the autonomous pathway. For instance, a single mutation in CADMIUM SENSITIVE 2 (CAD2), which is responsible for the biotic stress response, shows a delayed flowering phenotype under long days in Arabidopsis ,48,49.The vernalization pathway has FLC as its central component, similar to the autonomous pathway. Before the cold phase, six protein complexes  are more active and positively regulate FLC in the transcriptional level. After cold exposure, three different protein complexes  increase their role in repressing FLC by not allowing RNA Polymerase to attach to the FLC locus. The prolonged exposure to cold shifts more cells to suppress FLC, increasing FT signaling from the leaves to SAM, and increases SOC1 activity in the SAM and, therefore, activates the meristem identity genes (MIs) to facilitate the transition from the vegetative to the reproductive phase ,52,53,54The hormonal pathway, also known as the gibberellin pathway, involves the activity of cytokinins and gibberellins. Cytokinin affects the TWIN SISTER OF FT (TSF), while GAs affect the regulation of FT. Cytokinin, in a putative mechanism, positively regulates the transcription of TSF both in leaves and in SAM. TSF can be transferred from the leaf to the SAM and forms a complex there with a transcription factor, FD, and acts directly on MIs, making this the only pathway that can affect flowering independently of FT and SOC1.In addition, GA4 boosts GID proteins, resulting in reduced DELLA proteins, which subsequently downregulate FT in leaves and MIs in SAM. In essence, GA4 positively controls FT in leaves and MIs in SAM, but negatively regulates SOC1 via its interaction with SQUAMOSA PROMOTER BINDING PROTEIN-LIKE 9 (SPL9).Gibberellin signaling affects flowering by interfering with established endogenous and environmental flowering pathways, as well as by interacting with various phytohormone signaling pathways. In addition, cytokinins (CKs), abscisic acid (ABA), jasmonic acid (JA), ethylene (ET), brassinosteroids (BRs), and auxin also interact with DELLA proteins and, therefore, affect MIs. In conclusion, although this pathway has been traditionally referred to as the “Gibberellic pathway”, it would be more accurate to call it the “Hormonal pathway” ,57,58,59Trehalose-6-phosphate (T6P) is the main actor of this pathway which positively regulates FT in leaves and SOC1 in SAM by affecting the MIR156-SPL9 pathway. This signaling molecule (T6P) is the product of URACIL-DIPHOSPHATE GLUCOSE (UDPG) and GLUCOSE 6-PHOSPHATE (G6P) catalyzed by TREHALOSE-6-PHOSPHATE SYNTHASE 1 (TPS1). It is highly dependent on photosynthesis and reaches its peak concentration just before darkness under LD conditions, gradually decreasing with the onset of darkness ,63,64,65The aging pathway, delays flowering in the juvenile phase and promotes it in the adult phase, even in the absence of external triggers. In particular, the miR156, SPL transcription factors (SPLs), miR172, SCHLAFMUTZE (SMZ), and TARGET OF EARLY ACTIVATION TAGGED 1 (TOE1) are key players in this ageing pathway, driving the transition from the juvenile to adult phase and then promoting flowering. MiRNA156 is more abundant in young plants and decreases as they mature, while miRNA172 shows the opposite pattern, increasing with age. The SMZ and TOE1 exert a repressive influence on the FT gene in the leaves and APETALA1 (AP1) in the SAM, affecting the expression of MIs and, consequently, controlling the initiation of flowering ,72,73,74The ambient temperature pathway influences FT through various components. At high temperatures, PHYTOCHROME INTERACTING FACTOR 4 (PIF4) and FLOWERING CONTROL LOCUS A (FCA) enhance FT. Conversely, at low temperatures, the SHORT VEGETATIVE PHASE (SVP) negatively regulates FT and SOC1 through a complex with FLC  ,84,85,86It is important to note that these pathways interact with each other, and it is difficult to completely distinguish between them. For example, miR172 is influenced by SPLs (“aging pathway”), FCA (“temperature pathway”), and GI (“Photoperiodic pathway”), demonstrating the interconnectedness of these pathways. Or in another example, the production of T6P, which is considered as the key player of the sugar pathway, is obviously dependent on photosynthesis and, therefore, the photoperiodic pathway.FT and its homologous counterparts, known as FT-likes (FTLs), are synthesized in leaf tissues via the above-mentioned biochemical pathways. These molecules are then transported by specific transporters to the apical meristems in the shoots. The process of FT migration, a 22 kD protein with 175 amino acids, can be divided into two steps: first, it must be exported from companion cells into sieve elements, and second, it must cross sieve elements to reach the SAM.The involvement of the transmembrane region proteins FT-INTERACTING PROTEIN1 (FTIP1) and QUIRKY (QKY) in the initial export step has been identified. To reach the SAM, another protein called SODIUM POTASSIUM ROOTDEFECTIVE 1 (NaKR1) with a heavy-metal-associated (HMA) domain plays a crucial role. The activity of NaKR1 is positively regulated by the product of the photoperiodic pathway, CO, in the model plant Arabidopsis ,87,88,89In rice, the long-distance transporter for FT is the tetratricopeptide repeat 075 (TPR075) protein, while FTIP1 and FTIP9 are involved in the translocation of FT from companion cells to sieve elements .Taken together, the FTIPs appear to play a critical role in the short-range transport of FT. Given recent research suggesting the involvement of different proteins in the long-distance transport of FT, further investigation is needed to determine whether the ortholog of TPR075 has a similar function in dicots, whether the ortholog of NaKR1 plays a role in monocots, and whether other heavy-metal-associated domain proteins or tetratricopeptide repeat proteins may also play a role.In summary, our understanding of florigen transport remains largely incomplete, highlighting the need for comprehensive studies in a wide range of plant species to develop a more comprehensive understanding.Identifying the most effective gene(s) for either delaying or accelerating the flowering process depends on variables such as the species, cultivar, and growth environment, such as the plant’s response to the day length. The first step is to identify the predominant pathway(s) involved. For example, in the case of cabbage, where vernalization is a key determinant, genes such as BraFLC2, BraFLC3, AGL19s, and AGL24s associated with the vernalization pathway have shown remarkable success in breeding trials ,92.However, as a comprehensive strategy, targeting key proteins that are central to the overall flowering mechanism is a viable option. In genes such as FT, TFL1, and SOC1, as detailed in In addition to TFL1, in Arabidopsis, AGAMOUS-LIKE 12 (AGL12) displays late flowering under LD, but also the short root phenotype . The oveThe concept of interfering with transporters has also become a subject of debate. First, it is likely that NaKR1 in Arabidopsis or TPR075 in rice are not the only transporters of the FT protein. In addition, FT mRNA has the ability to migrate as well. Furthermore, NaKR1 also serves as a transporter for a wide range of sugars . MutatioFrom a holistic perspective, a breeding project focusing on flowering time requires us to consider the various interrelated pathways highlighted in this article, including signaling proteins, miRNAs, transcription regulators, transporters, etc. By recognizing the importance of these key components, we can gain a thorough understanding of the complex mechanisms that regulate flowering time and, therefore, successful breeding.As many of the proteins involved in flowering have multiple functions and diverse effects, one strategy for regulating their activity is to place greater emphasis on manipulating cis-regulatory elements . This apAs recent advancements, in grapefruit plants, CsLOB1 knockout mutants by CRISPR showed a delayed flowering time compared to WT . The tecThe idea of non-flowering angiosperms seems unlikely from a botanical point of view. However, in horticulture, postponing the flowering process could lead to a state of non-flowering cultivars. The disruption of FT or its transporter alone is not sufficient to achieve this result. This is due to the probability that FT is not solely dependent on a single transporter, and also because FT is not the only signaling molecule transmitted from the leaves to the shoot apical meristem (SAM). In fact, there are at least three known molecules—TSF, T6P, and AGL17—that also transduce the signal. What is more, certain pathways in the SAM can function independently of the leaves, ultimately influencing the expression of MI genes and thus the development of floral structures.Of particular note is the structural similarity between FT and TFL1, two proteins with opposing functions. By exploiting these similarities, we can change specific amino acids, such as substituting His-88 in TFL1 and Tyr-85 in FT . This siSince 2015, there has been a striking trend in the scientific literature regarding the manipulation of the flowering time using CRISPR technology. From then until now (mid-2023), there have been numerous publications investigating different gene families. These studies cover a wide range of plant species, with a particular focus on altering the flowering time. A thorough review was conducted of 103 peer-reviewed research publications, which are listed in The visual representation in The use of CRISPR technology for gene knockout, particularly in flowering projects, has seen sustained growth B. FurtheFlowering-related breeding projects sometimes aim to completely inhibit flowering, while in other cases, a delay or advance of days to weeks is desired. To achieve these goals, the selection of the right pathway and protein to engineer is critical. In addition, the location of the mutation on the gene and the type of mutation affects the flowering time, which can vary from species to species based on the genotype or environmental factors.About 300 genes are directly or indirectly involved in the flowering process . To obtaCRISPR technology is a leading innovation in plant breeding, offering precision, speed, and flexibility. The rapid generation of plants with desired traits surpasses the time limits of traditional breeding methods, while the scalability of CRISPR allows multiple target genes to be edited in parallel. However, to fully achieve CRISPR’s potential, it is increasingly recognized that it must be strategically combined with complementary techniques.In this context, using inventive techniques and approaches to increase efficiency and save time is critical to the success of molecular breeding projects. Recent advances include improvements in delivery using improved Agrobacterium strains ,209, virThrough such comprehensive and interconnected approaches, breeders can gain new insights into the intricate web of regulatory networks that regulate the flowering time. This new knowledge can guide targeted breeding initiatives aimed at producing crop varieties with improved flowering traits.


Introduction: Chuanxiong, a traditional Chinese medicine, has been proved to treat a variety of cardiovascular and cerebrovascular diseases by promoting angiogenesis. However, the mechanisms of Chuanxiong’s pro-angiogenesis is currently unknown. This study aimed to uncover the effect and mechanisms of Chuanxiong promoting angiogenesis in vivo and in vitro.Methods: First, potential targets were predicted by network pharmacology analysis, and PPI network was established and the pathways were enriched. Then, the chorioallantoic membrane test on quails was applied to assess the proangiogenic effects in vivo. As well, to evaluate the effects in vitro, real-time PCR, western blot analysis, the scratch test, and the tube formation experiment were used. Subsequently, the major metabolic pathways were analyzed using non-targeted metabolomics.Results: As a result of network pharmacological analysis, 51 collective targets of Chuanxiong and angiogenesis were identified, which are mainly associated with PI3K/AKT/Ras/MAPK pathway. And the biological verification results showed that Chuanxiong could increase the vessel numbers and vessel area in qCAM models. Meanwhile, Chuanxiong contributed to HUVEC proliferation, tube formation, migration, by encouraging scratch healing rates and boosting tube branch points. In addition, the levels of VEGFR2, MAPK and PI3K were elevated compared to the control group. The western blot analysis also confirmed Chuanxiong could promote an increase in AKT, FOXO1 and Ras. Furtheremore, metabolomic results showed that the proangiogenic effect of Chuanxiong is associated with glycine, serine and threonine metabolism.Discussion: In conclusion, this study clarified that Chuanxiong could promote angiogenesis in vivo and in vitro via regulating PI3K/AKT/Ras/MAPK pathway. Angiogenesis is an important physiological process involved in almost all diseases, and it specifically plays an important role in the treatment of myocardial infarction, stroke, cerebral embolism, and other ischemic diseases . TherefoLigusticum chuanxiong Hort., is a kind of traditional Chinese medicine named Chuanxiong. Numerous pharmacological investigations suggest that it has an impact on the circulatory, digestive, and central nervous systems. So a wide range of cardiovascular and cerebrovascular diseases were cured by Chuanxiong, including hypertension, cerebral infarctions, angina pectoris, and coronary heart disease . To find the active ingredients, the DL value should be less than 0.18, and the OB value should be less than 30%. Second, each ingredient’s SMILE and SDF files were obtained from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/). Third, the targets associated with Chuanxiong were ascertained from SwissTargetPrediction. The targets related to Chuanxiong were demonstrated in SwissTargetPrediction (http://www.swisstargetprediction.ch/). We chose the targets with probability values less than 0. Using “angiogenesis” as the search term, we used the DrugBank (https://www.drugbank.com/) to extract angiogenesis-related targets. The obtained Chuanxiong targets and disease targets were topologically calculated by Cytoscape 3.7.1, and the “drug–ingredient–disease–target” network was performed. Based on Chuanxiong targets for angiogenesis, protein–protein interactions (PPIs) were gathered from STRING (https://cn.string-db.org/cgi/input.pl).The network of PPI was constructed, and the topological features of the network were analyzed to screen out the core targets that play a crucial role in the PPI network. We used Metascape to perform GO enrichment and KEGG pathway enrichment analyses of target genes, screening results with a p-value of 0.01, a minimum count of 3, and an enrichment factor of 1.5%.First, the active ingredients of Chuanxiong were screened from the TCMSP database  , heat-inactivated fetal bovine serum (FBS), streptomycin, and penicillin were obtained from Thermo Scientific . Power SYBR Green PCR Master Mix reagents and gel embedding medium were obtained from Sigma-Aldrich , pyridine (≥99%), and acetonitrile (HPLC grade) were obtained from Beijing Chemical Plant Co. Ltd. . Compounds 2-chloro-L-phenylalanine (≥98%) and N, O-Bis (trimethylsilyl) trifluoroacetamide with 1% trimethylchlorosilane (BSTFA +1% TMCS) were obtained from Shyuanye Biochemical Co., Ltd. . Double-distilled water was purified from the Millipore water purification system . Methoxyamine hydrochloride (≥98%) and thiazolyl blue tetrazolium bromide  were purchased from Beijing Biorigin Biotechnology Co., Ltd. . Tetrahydropalmatine  and tert-butylhydroperoxide  were purchased from Innochem .The Chuanxiong decoction was purchased from Beijing Tong Ren Tang . The Chuanxiong decoction was pulverized into powder using a disintegrator and sieved through a 24-mesh sieve. Then, 60 g of Chuanxiong powder was extracted with the 10-fold volume of deionized water for 60 min and refluxed four times (1 h/reflux). The filtrate is combined and used for lyophilization. The Chuanxiong extract was stored as a lyophilized powder at −20°C after 3 days of lyophilization.in vivo system of vascular microcirculation was observed in the embryos by optical coherence tomography . Then, the CAMs were excised, unfolded, and photographed. The pictures were analyzed on the MATLAB platform.Quail eggs  were incubated in an egg incubator under specific pathogen-free conditions, such as maintaining at 37°C and 60% humidity. The eggs were separated into five groups at random, namely, negative control, positive control, low dose (1 mg/mL), medium dose (2 mg/mL), and high dose (4 mg/mL), comprising 10 eggs per group. After 7 days of incubation, a window was opened on the egg shell, the medicine (1mL/egg) is injected into the egg through the window, and then, the eggs were put back in the incubator after the window was taped shut. After 48 h of treatment and subsequent incubation at 37°C, the The TRIzol Reagent RA First Strand cDNA Synthesis Kit and an ABI Prism 7,500 sequence detection kit were used to isolate the total RNA from HUVEC samples. Life Technologies  provided the specific VEGFR2, PI3K, and MAPK primers. The primer sequences are as follows: VEGFR2 primers were forward, 5′- AGCATAGACAGCCCTTTGGT -3′ and reverse 5′- CACAATCTCTGCTGGTGCAA -3′; PI3K primers were forward, 5′-ACTGCCGAGAGATTTTCCCAC -3′ and reverse, 5′- TCACTCATCTGTCGCAGGCA -3′; and MAPK primers were forward, 5′- GAGAGATGTCTACATTGTGCAGGAC -3′ and reverse, 5′- AATCTTAAGGTCGCAGGTGGTG -3’ (reverse primer). We used human GAPDH as an internal reference.2, and 100% humidity were the conditions used to sustain the cultures. When the cells reached 70%–80% confluence, HUVECs were digested and centrifuged. Then, one 96-well plate of HUVECs was seeded for 24 h at 37°C before it was added for an additional 24 h of incubation. A Bio-Rad 550 spectrophotometer plate reader was used to detect the optical density at 550 nm .HUVECs were cultivated in Dulbecco's modified Eagle’s medium supplemented with 15% fetal bovine serum (FBS), 100 U/mL penicillin, and 100 g/mL streptomycin. In addition, 37°C, 5% COHUVECs were cultured in 24-well plates until forming a monolayer. A clean scratch was made down the middle of the cell using a sterile pipette tip. Images of the same location were photographed using a light microscope . Using Image-Pro Plus , we calculated the cell migration distance.4 cells/cm2 with a basement membrane matrix  until the cell confluence reached 100%, and then, Chuanxiong was added for additional 6 h. Light microscopy  and Image-Pro Plus  was used to measure the length of the tubes and capture pictures of the tube networks.An assay for the closure of scratch wounds was used to investigate cell migration. In a 96-well plate, HUVECs were grown at a density of 1 × 10In an optimal cutting temperature (OCT) compound, quail samples were solidified at 40°C. The samples were constantly sliced with a thickness of 15 μm. Then, the DESI-MSI system was used to scan them.The scan area’s dimensions  were measured and scanned in accordance with the sections using the DESI and SYNAPT HDMS G2-Si system . On the scanning platform, the sample slices were fixed. The scan’s parameters are as follows. Vertical displacement was set as 0 mm, scan line spacing was set as 0.15 mm, and the delayed start was set as 6 s. The scan speed was set as 0.1 mm/s. For mass spectrometry, a desorption electrospray ionization source (DESI) was used. The voltage of the electrospray was 5.0 kV. The spray solution utilized was 90% methanol, and the flow rate was set at 1.5 L/min. The nebulizer’s setting was 100 pis. The distance between pixels was 50–200 m. A mass range of 80–1,000 m/z was chosen.https://www.metaboanalyst.ca/home.xhtml), data were analyzed and the metabolic pathway was obtained. The findings of the t-test (p <0.05), the ANOVA (p< 0.05), and the fold change value (>1.5) were used to filter out significant differences. Using the online METLIN database, variables with substantial changes were identified as prospective biomarkers for provisional identification. MetaboAnalyst 5.0 was used to conduct pathway analysis based on the discovered biomarkers.Data preprocessing was carried out using MarkerLynx . With the aid of MetaboAnalyst 5.0  according to the manufacturer’s instructions. SDS-PAGE gel electrophoresis was used to separate the proteins, and they were then transferred to a polyvinylidene fluoride film. After blocking in 5% BSA for 1 h, the membranes were treated with the corresponding primary antibodies  at 4°C overnight. After washing, the membranes were then incubated with the corresponding alkaline phosphatase-conjugated secondary antibodies  for 1 h. The Tanon 4200 SF Chemiluminescent Imaging System  was used to expose the membranes.p-value of 0.05.Data were analyzed by SPSS 16.0 software . The data are displayed as mean ± standard deviation. In order to compare different groups, one-way analysis (ANOVA) of variance was used. Each two groups were contrasted using the independent t-test. These data discrepancies were deemed statistically significant when the differences reached a The TCMSP database had 189 active components of Chuanxiong in total, and seven active ingredients satisfied the criteria of OB value ≥30% and DL value ≥0.18. Then, 627 targets were obtained by SwissTargetPrediction. A total of 4,975 targets related to angiogenesis were obtained from the DrugBank. The intersection of component and angiogenesis targets yielded 51 common targets, and the drug–ingredient–disease–target network was constructed .p-value, the top 20 pathways in the KEGG enrichment study are shown (The target interaction network graph is obtained with the confidence score set at 0.4 . The nodre shown .p < 0.05) increased in the medium- and high-dose group  was chosen as the positive control. The survival rate of HUVEC was represented by MTT assays after 4 h of exposure to 5.5 μM tert-butylhydroperoxide (t-BHP), according to the preliminary assay that we performed . The resin vitro. The model condition and positive control stayed together with the proliferation assays. As shown by the results, Chuanxiong could promote scratch healing percentages and increase the branch points of tubes  was connected to metabolic pathways. Therefore, we used DESI-MSI based on non-targeted metabolomics to explore the possible metabolic pathway of the pro-angiogenic effect of Chuanxiong. A scoring plot with R2Y (cum) of 0.779 and Q2 (cum) of 0.463 was obtained, showing that the principal component analysis (PCA) and orthogonal structure to latent structure discriminant analysis (OPLS-DA) projection had good adaptability and predictive power for the potential model (p < 0.05).The results of Chuanxiong’s target prediction indicated that the main mechanism of Chuanxiong  family of enzymes plays an important role in the control of cellular processes such as proliferation, apoptosis, motility, and cell growth . GCPRs aMetabolomic analysis of qCAM models after Chuanxiong administration using DESI-MSI identified seven metabolic differentials, which were considered to be related to the metabolism of glycine, serine, and threonine. Glycine, serine, and threonine are important biosynthetic linkers that together provide precursors necessary for the synthesis of proteins, nucleic acids, and lipids, and also play important roles in enhancing protein synthesis and inhibiting protein degradation in cells, activating mTOR expression and inhibiting protein hydrolysis gene expression, all of which are essential for cell proliferation . The metThis study identified that Chuanxiong could protect damaged HUVECs and promote angiogenesis by pharmacological tests and investigated the potential mechanisms of the proangiogenic effects of Chuanxiong through network pharmacology combined with metabolomics. In addition, we used Western blotting and RT-PCR to verify the possible pathway. In conclusion, the present study showcased that Chuanxiong promotes angiogenesis through the PI3K/AKT/Ras/MAPK pathway . This st