Abstract Background Diabetic cardiovascular complications are the leading cause of diabetes-related deaths. These complications place an enormous and growing burden on global health systems and economies. The objective of this study was to conduct a systematic review on the therapeutic mechanisms of Taohe Chengqi Decoction (THCQD) in the treatment of diabetic cardiovascular complications. To predict the potential mechanisms of action of THCQD on diabetic cardiovascular complications using network pharmacology, and to validate these predictions through molecular docking analysis. Methods To collect relevant animal experiments, we searched a total of 6 databases. Eligibility for the study was determined based on inclusion and exclusion criteria. Data extraction was then performed on the literature. Methodological quality of animal studies was assessed using SYRCLE criteria. Based on network pharmacology, intersecting genes for THCQD and diabetic cardiovascular complications were obtained using Venny, PPI analysis and topology analysis of intersecting genes were performed; GO and KEGG were used for enrichment analysis and prediction of new targets of action. Molecular docking techniques were employed to model the interactions between drug components and target genes, thereby validating the results of network pharmacology predictions. Results A total of 16 studies were finally identified that fit the direction of this review. Included 6 studies of the myocardium, 1 study of the aortic arch, 5 studies of the femoral artery, 4 studies of the thoracic aorta. THCQD exhibited anti-inflammatory, anti-fibrotic and anti-atherosclerotic effects on cardiovascular complications in diabetic rats. Network pharmacology results showed that C0363 (Resveratrol), C0041 (Emodin), and C1114 (Baicalein) were the key components in the treatment of diabetic cardiovascular complications by THCQD. PPI results showed that INS, AKT1, TNF, ALB, IL6, IL1B as the genes that interact with the top 6. KEGG enrichment analysis identified the AGE-RAGE signaling pathway in diabetic complications as the most prominent pathway enriched by THCQD for diabetic cardiovascular complications genes. The results of molecular docking showed that the key active components demonstrated favorable interactions with their corresponding target genes. Conclusion In conclusion, the results of both basic and web-based pharmacological studies support the beneficial effects of the natural herbal formulation THCQD on diabetic cardiovascular complications. This decoction has anti-inflammatory and antifibrotic properties and is effective in ameliorating diabetic cardiovascular disease. The network pharmacology results further support these ideas and identify the AGE-RAGE signaling pathway in diabetic complications as possibly the most relevant pathway for THCQD in the treatment of diabetic cardiovascular complications. The extent of the therapeutic potential of all-natural herbal components in the treatment of diabetic cardiovascular disease merits further investigation. Keywords: Taohe Chengqi Decoction, Diabetic cardiovascular complications, Chinese herbal medicine, Systematic review, Network pharmacology Highlights * • This study presents the first systematic review of the mechanisms by which the traditional Chinese herbal formula Taohe Chengqi Decoction (THCQD) treats cardiovascular complications of diabetes. * • We employed network pharmacology to analyze the pharmacological mechanisms of THCQD in treating these complications * • Molecular docking was also conducted to validate the results of the network pharmacology analysis. * • The findings indicate that THCQD has a protective effect against diabetic cardiovascular complications in terms of anti-inflammation, anti-fibrosis, and anti-atherosclerosis. Abbreviations DM Diabetes mellitus DCM diabetic cardiomyopathy HYP hydroxyproline GLUT4 glucose transporter protein-4 GSH-Px glutathione peroxidase MDA malondialdehyde TGF-β1 transforming growth factor β1 CTGF connective tissues growth factor TGF-β: Transforming Growth Factor β IGF-1 Insulin-Like Growth Factor-1 TLR-2 Toll Like Receptors-2 TLR-4 Toll Like Receptors-4 VCAM-1 Vascular Cell Adhesion Molecule-1 MCP-1 Monocyte Chemoattractant Protein-1 AGEs Advanced Glycosylation End products RAGEs Receptor of Advanced Glycation End products eNOS endothelial Nitric Oxide Synthase GSH-Px glutathione peroxidase VSMC vascular smooth muscle cells NO Nitric Oxide Trial registration The study has been registered at PROSPERO (CRD42023392260). 1. Introduction Diabetes mellitus (DM) is a very common and increasingly significant chronic disease. In recent years, the prevalence of DM has been increasing worldwide, and the number of people with DM is expected to reach 700 million worldwide by 2045 [[27]1,[28]2]. The high prevalence of DM, the deaths caused by DM, and the health expenditures associated with the complications of diabetes continue to rise globally, placing a serious burden on society, finances, and health systems [[29][3], [30][4], [31][5]]. Cardiovascular complications of diabetes, including coronary heart disease and peripheral vascular disease, as well as microvascular complications, are major contributors to the burden associated with DM [[32]6,[33]7]. Approximately 70–75 % of patients with diagnosed coronary artery disease have DM or abnormalities in blood glucose [[34]8]. Diabetic cardiovascular complications already account for more than half of DM mortality [[35]9]. Diabetic cardiovascular complications have become a very heavy and unavoidable problem. Taohe Chengqi Decoction (THCQD) is a well-known herbal formula that first recorded in the Treatise on Miscellaneous Diseases of Typhoid Fever (circa 200 AD). THCQD is composed of Peach Seed, Rhubarb, Cassia twig, Licorice Root, and Mirabilite. Studies have found that the combination of herbs in THCQD can improve glucose metabolism and lower high blood sugar levels in diabetic patients [[36][10], [37][11], [38][12], [39][13]]. Research confirms that THCQD improves vascular endothelial function in diabetic patients [[40]14], and alleviation of oxidative damage in kidney and heart tissues of diabetic rats by scavenging oxygen free radicals and anti-lipid peroxidation effects [[41]15]. In recent years, a very large number of scholars have confirmed the protective effect of THCQD on diabetic cardiovascular complications, and much scientific evidence has been found regarding its mechanisms. To our knowledge, the protective mechanism of THCQD for diabetic cardiovascular disease has not been systematically summarized. In this review, we provide a systematic review of the mechanism of action of THCQD for the treatment of diabetic cardiovascular complications, a broad overview of existing studies, and a summary of the combined use of herbal therapies. In addition, we comprehensively analyzed the chemical constituents in THCQD and used the network pharmacology approach to predict its potential mechanisms for the treatment of diabetic cardiovascular complications. Molecular docking was utilized to confirm the interactions between key components and their corresponding target genes. 2. Materials and methods This systematic review was based on the latest PRISMA guidelines. The study has been registered at PROSPERO (CRD42023392260). 2.1. Literature search A total of 6 databases were searched to collect relevant animal experiments, including 2 English databases (PubMed and EMBASE) and 4 Chinese databases (CNKI, WanFang, VIP, SinoMed). Searches were conducted until December 31, 2022, and updated prior to submission of the paper. The related terms were as follows: (“taohechengqi”[Title/Abstract]) AND (“diabetes mellitus”[MeSH Terms] OR “diabetes complications”[MeSH Terms] OR “diabet*”[Title/Abstract] OR “IDDM”[Title/Abstract] OR “NIDDM”[Title/Abstract] OR “MODY”[Title/Abstract] OR “T1DM”[Title/Abstract] OR “T2DM”[Title/Abstract] OR “T1D”[Title/Abstract] OR “T2D”[Title/Abstract]) AND (“Animal Experimentation” OR “rat*”). The literature collection was conducted by a researcher (ZHANG) for all published studies up to the cut-off date. The complete search strategy is presented in [42]Appendix 1. 2.2. Study selection 2.2.1. Inclusion criteria Animals: 1. STZ induced diabetes model; 2. Cardiovascular-related content in the study results. Interventions: Herbs for THCQD, Chinese herbal soup. Comparators: 1. STZ induced diabetes model; 2. The rearing conditions and living environment were the same as those of the experimental group. 3. Did not receive any therapeutic measures. 2.2.2. Exclusion criteria Model: 1. No accurate description of the model; 2. Human studies; 3. In vitro studies. Interventions: 1. No accurate description of the composition of THCQD used; 2. Finished drugs whose existence of interest relationship cannot be confirmed; 3. Failure to follow animal ethics. Comparators: 1. Control group was given the treatment before the end of the experiment. 2. Control group lived in a different environment than the experimental group and may have experienced treatment that would appear to be harmful. 3. Non-STZ-induced diabetes model. 2.2.3. Data extraction Two investigators (CAO and ZHANG) independently read and assessed the literature. In case of any disagreements, the literature was reassessed by a third researcher (YANG) to decide whether to be included in the analysis. Data were extracted from all included studies, which included: 1.The method for inducing the diabetes model; 2. The rat species used; 3. The intervention mode; 4. The method of administration; 5. The composition of the THCQD formulation; 6. Description of the results and the mechanism of action involved in the study. For studies without data descriptions, we contacted the corresponding author via their email address to obtain the data. To ensure the completeness and accuracy of the data, one researcher (ZHANG) extracted the data, and another researcher (CAO) double-checked the data. 2.3. Quality assessment Two reviewers evaluated the methodological quality of the animal studies using SYRCLE [[43]16] criteria, which assessed the following ten items: 1. adequate sequence generation; 2. baseline characteristics; 3. allocation concealment; 4. randomized housing; 5. blinding (performance bias); 6. randomized outcome assessment; 7. blinding (detection bias); 8. incomplete outcome data; 9. selective outcome reporting; 10. other sources of bias. The results of the bias assessment will be presented using graphs and charts, indicating the level of risk of bias (high, low, or unclear) for each of the ten items in each trial. 2.4. Data analysis The included studies were categorized based on the site of the study, and a count was made of the medications used in conjunction with THCQD. The results were only categorized and described, without providing quantitative statistics. 2.5. Gene targets of THCQD and diabetic cardiovascular complications The HIT database [[44]17] were utilized to screen the active ingredients present in THCQD. The target genes obtained from the HIT database were combined, and then the target genes of THCQD were obtained after removing the duplicate entries. To obtain the target genes for Diabetic cardiovascular complications, the term “Diabetic cardiovascular complications” was entered into the GeneCards database ([45]https://www.genecards.org/). Select target genes with relevance score greater than 10.0. 2.6. Intersecting genes and “drug-target-intersecting genes-disease” network construction Use bioinformatics ([46]https://www.bioinformatics.com.cn/) to make a jvenn diagram to get the drug gene-disease gene intersection. The “drug-target-intersecting genes-disease” network constructionwas built by Cytoscape 3.9.1 software. Sorting the compounds by their degree values to identify key components. 2.7. PPI network construction and topology analysis The PPI network was constructed using the STRING database [[47]18] and analyzed using Cytoscape 3.9.1 software. The intersection genes were imported into the STRING database, and the species type was set to “Homo sapiens”, hide disconnected nodes in the network, and export the PPI network images and TSV files. The obtained TSV files were imported into Cytoscape 3.9.1 software to construct the network. The genes were sorted according to the degree value, and the core targets were screened according to the degree value. 2.8. GO functional enrichment and KEGG pathway enrichment analysis Enrichment analysis was conducted utilizing the DAVID database [[48]19] to identify enriched biological processes (BP), molecular functions (MF), cellular components (CC), and KEGG pathways of the intersecting genes. The results of the top 20 were presented visually by bioinformatics. 2.9. Molecular docking Molecular docking of key compounds to their corresponding targets was conducted to validate the results of network pharmacology. The PDB database ([49]https://www1.rcsb.org/) and Uniprot database [[50]20] were used to find and download the molecular structure files and 3D structure models of the target proteins. The molecular structures of target compounds were downloaded from PubChem, and PyMOL 2.3.0 was utilized for operations including the removal of water molecules and proto-ligands from the downloaded target proteins. Ligand molecules were optimized to their minimal energy conformations using Chem3D Ultra 11.0 for molecular mechanics. Pre-processed target proteins were hydrogenated using AutoDock Tools 26, followed by hydrogenation and torsional bond assignment of the optimally conformed ligands from molecular mechanics. The target protein and ligand molecules were subjected to molecular simulation of docking using AutoDock Vina software ([51]https://vina.scripps.edu/). The docking algorithm was Lamarckian Genetic Algorithm, the docking mode was semi-flexible docking, the exhaustiveness was set to 8, and the maximal number of conformations in the output was set to 9, to obtain the docking binding free energy as well as docking Result file. The free binding energy is less than −5 kcal/mol, the binding is excellent, and less than −7 kcal/mol, the binding is strong. PyMOL2.3.0 software was used to visualize the docking results of this group. 3. Results 3.1. Included studies A total of 179 records were retrieved from the selected database. After removing duplicates, 83 records remained. The titles and abstracts of the articles were read carefully, and 48 records were excluded based on the inclusion and exclusion criteria approach. The full text of the remaining 35 records was read, and 19 records were excluded. 16 studies were finally identified that fit the direction of this review. As shown in Flow Chart. [52]Image 1 [53]Open in a new tab 3.2. Characteristics of the study In this review, a total of 16 studies were included [[54][21], [55][22], [56][23], [57][24], [58][25], [59][26], [60][27], [61][28], [62][29], [63][30], [64][31], [65][32], [66][33], [67][34], [68][35], [69][36]]. Included 6 studies of the myocardium [[70]21,[71]22,[72]24,[73]25,[74]28,[75]36], 1 study of the aortic arch [[76]23], 5 studies of the femoral artery [[77]26,[78]27,[79]30,[80]31,[81]33], 4 studies of the thoracic aorta [[82]29,[83]32,[84]34,[85]35]. The period of inclusion in the study was from 2005 to 2022. The results are shown in [86]Table 1. Table 1. Summary table of literature. Study Diabetic model Intervention Composition Results LI Saimei [[87]21] STZ induced diabetes 1 Normal group 2 Diabetes group 3 Taohe Chengqi decoction group 4 Water extracted alcoholic sedimentation group 5 n-Butanol group 6 Ethyl acetate group 7 Diamicron group Peach Seed Rhubarb Cassia twig Licorice Root Mirabilite Astragalus membranaceus Radix Ophiopogonis Rehmannia glutinosa Radix scrophulariae Improvement of the ultrastructure of myogenic fibers and mitochondria in cardiac myocytes of diabetic rats LI Saimei [[88]22] STZ induced diabetes 1 Normal group 2 Diabetes group 3 Taohe Chengqi decoction group 4 Water extracted alcoholic sedimentation group 5 n-Butanol group 6 Ethyl acetate group 7 Diamicron group Peach Seed Rhubarb Cassia twig Licorice Root Mirabilite Astragalus membranaceus Radix Ophiopogonis Rehmannia glutinosa Radix scrophulariae Taohe Chengqi decoction decreases myocardial HYP content and reduces myocardial type III collagen mRNA expression LI Saimei [[89]23] STZ induced diabetes 1 Normal group 2 Diabetes group 3 Taohe Chengqi decoction group 4 Water extracted alcoholic sedimentation group 5 n-Butanol group 6 Ethyl acetate group 7 Diamicron group Peach Seed Rhubarb Cassia twig Licorice Root Mirabilite Astragalus membranaceus Radix Ophiopogonis Rehmannia glutinosa Radix scrophulariae Damectin and n-butanol groups improve the structure of elastic membrane in the aortic arch of diabetic rats and improve the morphology of mid-membrane smooth muscle cells and mitochondria CHU Quan-gen [[90]24] STZ induced diabetes 1 Normal group 2 Diabetes group 3 Taohe Chengqi decoction group 4 Water extracted alcoholic sedimentation group 5 n-Butanol group 6 Ethyl acetate group 7 Diamicron group Peach Seed Rhubarb Cassia twig Licorice Root Mirabilite Astragalus membranaceus Radix Ophiopogonis Rehmannia glutinosa Radix scrophulariae Taohe Chengqi decoction stabilizes myocardial GluT4 mRNA expression in the heart CHU Quan-gen [[91]25] STZ induced diabetes 1 Normal group 2 Diabetes group 3 Taohe Chengqi decoction group 4 Water extracted alcoholic sedimentation group 5 n-Butanol group 6 Ethyl acetate group 7 Diamicron group Peach Seed Rhubarb Cassia twig Licorice Root Mirabilite Astragalus membranaceus Radix Ophiopogonis Rehmannia glutinosa Radix scrophulariae Taohe Chengqi decoction increases Na + -K + -ATPase and Ca2+-ATPase activities in diabetic rat cardiac myocytes WANG Jun [[92]26] STZ induced diabetes 1 Normal group 2 Diabetes group 3 Taohe Chengqi decoction high dose group 4 Taohe Chengqi decoction medium dose group 5 Taohe Chengqi decoction low dose group 6 Metformin group Peach Seed Rhubarb Cassia twig Licorice Root Mirabilite Astragalus membranaceus Radix Ophiopogonis Rehmannia glutinosa Radix scrophulariae Taohe Chengqi decoction reduces the expression of TGF-β1 and CTGF in the femoral artery of diabetic rats DING Zhi-ming [[93]27] STZ induced diabetes 1 Normal group 2 Diabetes group 3 Taohe Chengqi decoction group 4 Metformin hydrochloride group Peach Seed Rhubarb Cassia twig Licorice Root Mirabilite Astragalus membranaceus Radix Ophiopogonis Rehmannia glutinosa Radix scrophulariae Taohe Chengqi decoction reduces the expression of collagen I and III in femoral arteries. LI Jing [[94]28] STZ induced diabetes 1 Normal group 2 Diabetes group 3 Taohe Chengqi decoction group Peach Seed Rhubarb Cassia twig Licorice Root Mirabilite Astragalus membranaceus Radix Ophiopogonis Rehmannia glutinosa Radix scrophulariae Salviae Miltiorrhizae Taohe Chengqi decoction enhances GSH-Px activity in heart tissue and reduces MDA content antioxidant effect DENG Xiao-feng [[95]29] STZ induced diabetes 1 Normal group 2 Model group 3 Taohe Chengqi decoction Group A 4 Peach Nucleus Cheng Qi Tang Group B 5 Taohe Chengqi decoction Group C 6 Metformin group Peach Seed Rhubarb Cassia twig Licorice Root Mirabilite Astragalus membranaceus Radix Ophiopogonis Rehmannia glutinosa Radix scrophulariae Salviae Miltiorrhizae cooked Rhubarb Asarum Decreased VCAM-1, MCP-1, NF-κB in thoracic aorta; decreased NF-κ B mRNA, MCP-1 mRNA, VCAM-1 mRNA expression in thoracic aorta XU Yang [[96]30] High fat and high sugar diet induced diabetes model 1 Normal group 2 Model group 3 Taohe Chengqi decoction high dose group 4 Tao Nucleus Cheng Qi Tang medium dose group 5 Tao Nucleus Cheng Qi Tang low dose group Peach Seed Rhubarb Cassia twig Licorice Root Mirabilite Taohe Chengqi decoction intervention reduces TGF-β expression in diabetic rats TGF-β expression and IGF-1 expression in the femoral artery of rats XU Yang [[97]31] High fat and high sugar diet induced diabetes model 1 Normal group 2 Model group 3 Taohe Chengqi decoction high dose group 4 Tao Nucleus Cheng Qi Tang medium dose group 5 Tao Nucleus Cheng Qi Tang low dose group Peach Seed Rhubarb Cassia twig Licorice Root Mirabilite Taohe Chengqi decoction intervention reduces TLR-2 and TLR-4 expression in the lower limb femoral artery vasculature of diabetic rats TLR-4 expression XU Shuai [[98]32] STZ induced diabetes 1 Normal group 2 Model group 3 Taohe Chengqi decoction Group A 4 Taohe Chengqi decoction Group B 5 Taohe Chengqi decoction Group C 6 Aminoguanidine hydrochloride group Peach Seed Rhubarb Cassia twig Licorice Root Mirabilite Astragalus membranaceus Rehmannia glutinosa Radix Ophiopogonis Radix scrophulariae cooked Rhubarb Asarum Taohe Chengqi decoction reduces the production of AGEs and the expression of receptor RAGE mRNA in the thoracic aorta. XU Yang [[99]33] STZ induced diabetes 1 Normal group 2 Model group 3 Taohe Chengqi decoction Group A 4 Taohe Chengqi decoction Group B Peach Seed Rhubarb Cassia twig Licorice Root Mirabilite Taohe Chengqi decoction decreases the expression of TLR-2 and TLR-4, decreases the content of TGF-β and increases the content of IGF-1 in the femoral artery of diabetic rats GU Yu-mei [[100]34] STZ induced diabetes 1 Normal group 2 Model group 3 Taohe Chengqi decoction Group I 4 Taohe Chengqi decoction Group II 5 Metformin group Peach Seed Rhubarb Cassia twig Licorice Root Mirabilite Astragalus membranaceus Radix Ophiopogonis Rehmannia glutinosa Radix scrophulariae Salviae Miltiorrhizae Asarum Taohe Chengqi decoction reduces PI3K(P85) mRNA and Akt mRNA expression in the thoracic aorta of diabetic rats and inhibits the development of atherosclerosis in the thoracic aorta XU Shuai [[101]35] STZ induced diabetes 1 Model group 2 Taohe Chengqi decoction Group A 3 Taohe Chengqi decoction Group B 4 Taohe Chengqi decoction Group C 5 Metformin group Peach Seed Rhubarb Cassia twig Licorice Root Mirabilite Astragalus membranaceus Rehmannia glutinosa Radix Ophiopogonis Radix scrophulariae cooked Rhubarb Asarum Taohe Chengqi decoction enhances eNOS mRNA expression in the thoracic aorta of diabetic rats ZHANG Ya-nan [[102]36] STZ induced diabetes 1 Normal group 2 Model group 3 Taohe Chengqi decoction low dose group 4 Taohe Chengqi decoction high dose group 5 Metformin Hydrochloride Group Peach Seed Rhubarb Cassia twig Licorice Root Mirabilite Astragalus membranaceus Rehmannia glutinosa Radix Ophiopogonis Salviae Miltiorrhizae Taohe Chengqi decoction reduces NLRP3, ASC, Caspase-1 and p–NF–κB p65 protein expression in myocardial tissue of diabetic rats [103]Open in a new tab 3.3. Cardiovascular protection mechanism of THCQD in diabetic rats 3.3.1. Effects of THCQD on the myocardium in diabetic rats 6 studies [[104]21,[105]22,[106]24,[107]25,[108]28,[109]36] reported significant effects of THCQD on myocardium in diabetic rats. Compared with the model group, the use of THCQD improved the ultrastructure of cardiomyocytes [[110]21]. Reduced myocardial hydroxyproline (HYP) content and decreased myocardial type III collagen mRNA expression [[111]22]. And stabilized myocardial glucose transporter protein-4 (GLUT4) mRNA expression [[112]24]. Increased Na^+-K^+-ATPase and Ca^2+-ATPase activities in cardiomyocytes [[113]25]. Enhanced myocardial glutathione peroxidase (GSH-Px) activity and reduced malondialdehyde (MDA) content [[114]28]. Decreased NLRP3, ASC, Caspase-1, and p–NF–κB p65 protein expression in myocardium [[115]36]. These findings suggest that THCQD has a protective effect on the myocardium of diabetic rats, potentially improving cardiac function and reducing the negative effects of diabetes on heart tissue. 3.3.2. Effect of THCQD on the aortic arch in diabetic rats One study [[116]23] reported a significant effect of THCQD on the aortic arch in diabetic rats. Compared with the model group, THCQD improved the internal elastic membrane structure within the aortic arch and improved the morphology of mid-membrane smooth muscle cells and mitochondria in diabetic rats [[117]23]. These improvements suggest that THCQD may have a beneficial impact on the vascular health of diabetic rats, particularly in the aortic arch region. 3.3.3. Effects of THCQD on the femoral artery in diabetic rats Five studies [[118]26,[119]27,[120]30,[121]31,[122]33] reported significant effects of THCQD on the femoral arteries in diabetic rats. Compared with the model group, THCQD decreased the expression of collagen I and III in the femoral arteries [[123]27]. Decreased the expression of transforming growth factor β1 (TGF-β1) and connective tissues growth factor (CTGF) [[124]26]. Decreased the expression of Transforming Growth Factor β (TGF-β) and increased the expression of Insulin-Like Growth Factor-1 (IGF-1) in femoral arteries [[125]30]. Decreased the expression of Toll Like Receptors-2 (TLR-2), Toll Like Receptors-4 (TLR-4) expression in femoral arteries [[126]31]. Decreased femoral artery TLR-2 and TLR-4 expression, reduced TGF-β content and elevated IGF-1 content in femoral arteries [[127]33]. These findings suggest that THCQD may have therapeutic potential in improving vascular health by modulating key growth factors and immune response markers in the femoral arteries of diabetic rats. 3.3.4. Effects of THCQD on the thoracic aorta in diabetic rats Four studies [[128]29,[129]32,[130]34,[131]35] reported significant effects of THCQD on the thoracic aorta in diabetic rats. Compared with the model group, THCQD decreased the expression of Vascular Cell Adhesion Molecule-1 (VCAM-1), Monocyte Chemoattractant Protein-1 (MCP-1) and NF-κB protein in the thoracic aorta; decreased the expression of NF-κB mRNA, MCP-1 mRNA, and VCAM-1 mRNA expression [[132]29]. Decreased the expression of PI3K (P85) mRNA and Akt mRNA [[133]34]. Reduced Advanced Glycosylation End products (AGEs) and decreased expression of Receptor of Advanced Glycation End products (RAGEs) mRNA [[134]32]. And increased expression of endothelial Nitric Oxide Synthase (eNOS) mRNA in the thoracic aorta [[135]35]. Overall, these studies suggest that THCQD may exert beneficial effects on the thoracic aorta of diabetic rats by reducing inflammation, modulating key signaling pathways, and improving vascular function. 3.4. Herbs used in combination with THCQD THCQD has been used in combination with other herbs when used to in the treatment of diabetic cardiovascular disease. 3 studies [[136]30,[137]31,[138]33] used only the fixed herbal formula of THCQD. 13 studies [[139][21], [140][22], [141][23], [142][24], [143][25], [144][26], [145][27], [146][28], [147][29],[148]32,[149][34], [150][35], [151][36]] used other herbs in combination with THCQD. 12 studies [[152][21], [153][22], [154][23], [155][24], [156][25], [157][26], [158][27], [159][28], [160][29],[161]32,[162]34,[163]35] used Astragalus membranaceus, Radix Ophiopogonis, Rehmannia glutinosa and Radix scrophulariae in combination with THCQD; 4 studies [[164]28,[165]29,[166]34,[167]36] added Salviae Miltiorrhizae; 4 studies [[168]29,[169]32,[170]34,[171]35] added Asarum; and three studies [[172]29,[173]32,[174]35] added cooked Rhubarb. 3.5. Quality assessment Of the included literature, 9 studies (56 %) mentioned the method of random assignment. 7 studies (44 %) reported baseline characteristics of the animals. All studies had no studied that mentioned allocation concealment, randomized housing, blinding (performance bias), randomized outcome assessment, and blinding (detection bias). All but one study was unclear, others had complete outcome data results and no other sources of bias. The results are presented in [175]Table 2. Table 2. Risk of bias for included studies. Study a b c d e f g h i j LI Saimei [[176]21] Y U U U U U U N N N LI Saimei [[177]22] Y U U U U U U N N N LI Saimei [[178]23] Y U U U U U U N N N CHU Quan-gen [[179]24] Y U U U U U U N N N CHU Quan-gen [[180]25] Y U U U U U U N N N WANG Jun [[181]26] Y U U U U U U N N N DING Zhi-ming [[182]27] Y U U U U U U N N N LI Jing [[183]28] U U U U U U U N N N DENG Xiao-feng [[184]29] Y Y U U U U U N N N XU Yang [[185]30] U Y U U U U U N N N XU Yang [[186]31] U Y U U U U U N N N XU Shuai [[187]32] Y Y U U U U U N N N XU Yang [[188]33] U Y U U U U U N N N GU Yu-mei [[189]34] U Y U U U U U N N N XU Shuai [[190]35] U U U U U U U U U U ZHANG Ya-nan [[191]36] U Y U U U U U N N N [192]Open in a new tab a: Sequence generation; b: Baseline characteristics; c: Allocation concealment; d: Random housing; e: Blinding (performance bias); f: Random outcome assessment; g: Blinding (detection bias); h: Incomplete outcome data; i: Selective outcome reporting; j: Other sources of bias; Y: yes; N: no; U: unclear. 3.6. Gene targets of THCQD and diabetic cardiovascular complications Peach kernel, Rhubarb, Cassia twig, Licorice Root and Mirabilite were imported into the HIT database. And 17 compounds and 227 genes were obtained from the Peach Seed, 31 compounds and 414 genes from the Rhubarb, 8 compounds and 54 genes from the Cassia twig, 41 compounds and 380 genes from the Licorice Root, and 1 compound and 5 genes from the Mirabilite. The chemical composition is shown in [193]Table 3, the network of component targets is shown in [194]Appendix 2. Table 3. THCQD chemical composition. Id Pref Name CAS Pubchem ID Smiles C1125 Baicalin CAS:21967-41-9 CID:64982 OC(=O)[C@H]1O[C@@H](Oc2cc3oc(cc(=O)c3c(c2O)O)c2ccccc2)[C@@H]([C@H]([C@@ H]1O)O)O C0485 Wogonin CAS:632-85-9 CID:5281703 COC1 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C2 Created by potrace 1.16, written by Peter Selinger 2001-2019 C1OC(=CC2 Created by potrace 1.16, written by Peter Selinger 2001-2019 O)C3 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C3)O)O C1221 Catechol CAS:120-80-9 CID:289 C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C(=C1)O)O C1114 Baicalein CAS:491-67-8 CID:5281605 C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C1)C2 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=O)C3 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(O2)C Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C(=C3O)O)O C1178 Beta-Sitosterol CID:222284 CCC(CCC(C)C1CCC2C1(CCC3C2CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C4C3(CCC(C4)O)C)C)C(C)C C1237 Chrysin CAS:480-40-0 CID:5281607 C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C1)C2 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=O)C3 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C3O2)O)O C0267 Oroxylin A CAS:480-11-5 CID:5320315 COC1 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C2 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C1O)OC(=CC2 Created by potrace 1.16, written by Peter Selinger 2001-2019 O)C3 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C3)O C0263 Oleic Acid CAS:112-80-1 CID:445639 CCCCCCCCC Created by potrace 1.16, written by Peter Selinger 2001-2019 CCCCCCCCC(=O)O C0189 Linoleic Acid CAS:60-33-3 CID:5280450 CCCCC/C Created by potrace 1.16, written by Peter Selinger 2001-2019 C\C/C Created by potrace 1.16, written by Peter Selinger 2001-2019 C\CCCCCCCC(=O)O C0843 Abscisic Acid CAS:21293-29-8 CID:5375199 OC(=O)/C Created by potrace 1.16, written by Peter Selinger 2001-2019 C(\C Created by potrace 1.16, written by Peter Selinger 2001-2019 C\C1(O)C(=CC(=O)CC1(C)C)C)/C C0447 Thymol CAS:89-83-8 CID:6989 CC1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C1)C(C)C)O C1162 Benzaldehyde CID:240 O=Cc1ccccc1 C0259 Octanol CAS:111-87-5 CID:957 CCCCCCCCO C1218 Carvacrol CAS:499-75-2 CID:10364 CC(c1ccc(c(c1)O)C)C C0064 Eugenol CAS:97-53-0 CID:3314 COC1 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=C1)CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C)O C0839 (2E,4E)-Deca-2,4-Dienal CAS:25152-84-5 CID:5283349 CCCCCC Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 O C0808 5,7-Dihydroxy-2-(4-Hydroxyphenyl)-2,3-Dihydrochromen-4-One CID:932 C1C(OC2 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=CC(=C2C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 O)O)O)C3 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C3)O C0041 Emodin CAS:518-82-1 CID:3220 CC1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC2 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C(=C1)O)C(=O)C3 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C2 Created by potrace 1.16, written by Peter Selinger 2001-2019 O)C Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C3O)O C0397 Serotonin CAS:50-67-9 CID:5202 NCCc1c[nH]c2c1cc(O)cc2 C0377 Rutin CAS:153-18-4 CID:5280805 CC1C(C(C(C(O1)OCC2C(C(C(C(O2)OC3 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(OC4 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=CC(=C4C3 Created by potrace 1.16, written by Peter Selinger 2001-2019 O)O)O)C5 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C5)O)O)O)O)O)O)O)O C0881 Aloe-Emodin CID:10207 C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC2 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C(=C1)O)C(=O)C3 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C2 Created by potrace 1.16, written by Peter Selinger 2001-2019 O)C Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C3O)CO C0306 Physcion CAS:521-61-9 CID:10639 COc1cc(O)c2c(c1)C(=O)c1c(C2 Created by potrace 1.16, written by Peter Selinger 2001-2019 O)c(O)cc(c1)C C1240 Chrysophanol CAS:481-74-3 CID:10208 Cc1cc(O)c2c(c1)C(=O)c1c(C2 Created by potrace 1.16, written by Peter Selinger 2001-2019 O)c(O)ccc1 C0369 Rhein CAS:478-43-3 CID:10168 C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC2 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C(=C1)O)C(=O)C3 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C2 Created by potrace 1.16, written by Peter Selinger 2001-2019 O)C Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C3O)C(=O)O C0090 Gallic Acid CAS:149-91-7 CID:370 C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C(=C1O)O)O)C(=O)O C0045 Epicatechin Gallate CAS:1257-08-5 CID:107905 Oc1cc(O)c2c(c1)O[C@@H]([C@@H](C2)OC(=O)c1cc(O)c(c(c1)O)O)c1ccc(c(c1)O)O C1220 Catechin CID:1203 C1C(C(OC2 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=CC(=C21)O)O)C3 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C3)O)O)O C0356 Quinalizarin CAS:81-61-8 CID:5004 Oc1c(O)ccc2c1C(=O)c1c(C2 Created by potrace 1.16, written by Peter Selinger 2001-2019 O)c(O)ccc1O C0339 Purpurin CAS:81-54-9 CID:6683 Oc1c(O)cc(c2c1C(=O)c1ccccc1C2 Created by potrace 1.16, written by Peter Selinger 2001-2019 O)O C0912 Anthraquinone CAS:84-65-1 CID:6780 O Created by potrace 1.16, written by Peter Selinger 2001-2019 C1c2ccccc2C(=O)c2c1cccc2 C0119 Hesperidin CAS:520-26-3 CID:10621 CC1C(C(C(C(O1)OCC2C(C(C(C(O2)OC3 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=C4C(=O)CC(OC4 Created by potrace 1.16, written by Peter Selinger 2001-2019 C3)C5 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C5)OC)O)O)O)O)O)O)O)O C0110 Glycyrrhizin CAS:103000-77-7 CID:14982 CC1(C2CCC3(C(C2(CCC1OC4C(C(C(C(O4)C(=O)O)O)O)OC5C(C(C(C(O5)C(=O)O)O)O)O )C)C(=O)C Created by potrace 1.16, written by Peter Selinger 2001-2019 C6C3(CCC7(C6CC(CC7)(C)C(=O)O)C)C)C)C C1125 Baicalin CAS:21967-41-9 CID:64982 OC(=O)[C@H]1O[C@@H](Oc2cc3oc(cc(=O)c3c(c2O)O)c2ccccc2)[C@@H]([C@H]([C@@ H]1O)O)O C0114 (−)-Epicatechin CID:72276 C1C(C(OC2 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=CC(=C21)O)O)C3 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C3)O)O)O C0203 Magnolol CAS:528-43-8 CID:72300 C=CCc1ccc(c(c1)c1cc(CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C)ccc1O)O C0126 Honokiol CAS:35354-74-6 CID:72303 C Created by potrace 1.16, written by Peter Selinger 2001-2019 CCC1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C1)O)C2 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C2)O)CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C C0243 Naringin CAS:10236-47-2 CID:442428 CC1C(C(C(C(O1)OC2C(C(C(OC2OC3 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=C4C(=O)CC(OC4 Created by potrace 1.16, written by Peter Selinger 2001-2019 C3)C5 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C5)O)O)CO)O)O)O)O)O C1243 Cinnamic Acid CAS:621-82-9 CID:444539 C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C1)C Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=O)O C0363 Resveratrol CAS:501-36-0 CID:445154 C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C1C Created by potrace 1.16, written by Peter Selinger 2001-2019 CC2 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=CC(=C2)O)O)O C0073 Ferulic Acid CAS:1135-24-6 CID:445858 COc1cc(/C Created by potrace 1.16, written by Peter Selinger 2001-2019 C/C(=O)O)ccc1O C0308 Piceatannol CAS:10083-24-6 CID:667639 Oc1cc(/C Created by potrace 1.16, written by Peter Selinger 2001-2019 C/c2ccc(c(c2)O)O)cc(c1)O C1203 Caffeic Acid CAS:331-39-5 CID:689043 C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C1C Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=O)O)O)O C1114 Baicalein CAS:491-67-8 CID:5281605 C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C1)C2 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=O)C3 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(O2)C Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C(=C3O)O)O C0364 Resveratrol 4′-Methyl Ether CAS:33626-08-3 CID:6255462 COc1ccc(cc1)/C Created by potrace 1.16, written by Peter Selinger 2001-2019 C/c1cc(O)cc(c1)O C0618 Sennoside A CAS:81-27-6 CID:73111 OC[C@H]1O[C@@H](Oc2cccc3c2C(=O)c2c([C@@H]3[C@H]3c4cc(cc(c4C(=O)c4c3cccc 4O[C@@H]3O[C@H](CO)[C@H]([C@@H]([C@H]3O)O)O)O)C(=O)[O-])cc(cc2O)C(=O)[O -])[C@@H]([C@H]([C@@H]1O)O)O C0714 Rhaponticin CAS:155-58-8 CID:637213 OC[C@H]1O[C@@H](Oc2cc(/C Created by potrace 1.16, written by Peter Selinger 2001-2019 C/c3ccc(c(c3)O)OC)cc(c2)O)[C@@H]([C@H]([C@@H]1O)O)O C0775 Rhapontigenin CAS:500-65-2 CID:5320954 COC1 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C1)C Created by potrace 1.16, written by Peter Selinger 2001-2019 CC2 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=CC(=C2)O)O)O C1241 Cianidanol CID:9064 C1C(C(OC2 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=CC(=C21)O)O)C3 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C3)O)O)O C0045 Epicatechin Gallate CAS:1257-08-5 CID:107905 Oc1cc(O)c2c(c1)O[C@@H]([C@@H](C2)OC(=O)c1cc(O)c(c(c1)O)O)c1ccc(c(c1)O)O C0188 Linalool CAS:78-70-6 CID:6549 CC(=CCCC(C)(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C)O)C C1243 Cinnamic Acid CAS:621-82-9 CID:444539 C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C1)C Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=O)O C1242 Cinnamaldehyde CAS:104-55-2 CID:637511 C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C1)C Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 O C1259 Coumarin CAS:91-64-5 CID:323 C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C2C(=C1)C Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=O)O2 C0419 Styrene CAS:100-42-5 CID:7501 C Created by potrace 1.16, written by Peter Selinger 2001-2019 CC1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C1 C0333 Protocatechuic Acid CAS:99-50-3 CID:72 C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C1C(=O)O)O)O C0532 Procyanidin B2 CAS:29106-49-8 CID:122738 C1C(C(OC2 Created by potrace 1.16, written by Peter Selinger 2001-2019 C1C(=CC(=C2C3C(C(OC4 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=CC(=C34)O)O)C5 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C5)O)O)O)O)O)C6 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C6)O)O)O C0193 Liquiritin CAS:551-15-5 CID:503737 C1C(OC2 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 O)C Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=C2)O)C3 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C3)OC4C(C(C(C(O4)CO)O)O)O C0041 Emodin CAS:518-82-1 CID:3220 CC1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC2 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C(=C1)O)C(=O)C3 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C2 Created by potrace 1.16, written by Peter Selinger 2001-2019 O)C Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C3O)O C0152 Isoliquiritigenin CAS:961-29-5 CID:638278 C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C1C Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=O)C2 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C2)O)O)O C0156 Isoquercetin CAS:482-35-9 CID:5280804 OC[C@H]1O[C@@H](Oc2c(oc3c(c2 = O)c(O)cc(c3)O)c2ccc(c(c2)O)O)[C@@H]([C@H ]([C@@H]1O)O)O C1208 Calycosin CAS:20575-57-9 CID:5280448 COc1ccc(cc1O)c1coc2c(c1 = O)ccc(c2)O C0333 Protocatechuic Acid CAS:99-50-3 CID:72 C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C1C(=O)O)O)O C0914 Apigenin CAS:520-36-5 CID:5280443 C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C1C2 = CC(=O)C3 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C3O2)O)O)O C0044 Enoxolone CAS:471-53-4 CID:10114 O Created by potrace 1.16, written by Peter Selinger 2001-2019 C1C Created by potrace 1.16, written by Peter Selinger 2001-2019 C2[C@@H]3C[C@](C)(CC[C@]3(C)CC[C@]2([C@]2([C@H]1[C@@]1(C)CC[C@@H](C([C@ @H]1CC2)(C)C)O)C)C)C(=O)O C0124 Hispidulin CAS:1447-88-7 CID:5281628 COc1c(O)cc2c(c1O)c(=O)cc(o2)c1ccc(cc1)O C0109 Glycyrol CAS:23013-84-5 CID:5320083 COc1c(CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C)C)c(O)cc2c1c1oc3c(c1c(=O)o2)ccc(c3)O C1278 Daidzein CAS:486-66-8 CID:5281708 C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C1C2 = COC3 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C2 Created by potrace 1.16, written by Peter Selinger 2001-2019 O)C Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=C3)O)O C0164 Kaempferol CAS:520-18-3 CID:5280863 C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C1C2 = C(C(=O)C3 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C3O2)O)O)O)O C0083 Formononetin CAS:485-72-3 CID:5280378 COC1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C1)C2 Created by potrace 1.16, written by Peter Selinger 2001-2019 COC3 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C2 Created by potrace 1.16, written by Peter Selinger 2001-2019 O)C Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=C3)O C0074 Fisetin CAS:528-48-3 CID:5281614 C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C1C2 = C(C(=O)C3 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(O2)C Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C3)O)O)O)O C0291 Paraben CID:3702506 Oc1ccc(cc1)C(=O)O C0108 Glycybenzofuran CAS:1253641-15-4 CID:46934435 COc1c(CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C)C)c(O)cc(c1c1oc2c(c1C)ccc(c2)O)O C0838 8-Prenylnaringenin CAS:53846-50-7 CID:480764 CC(=CCc1c(O)cc(c2c1O[C@@H](CC2 Created by potrace 1.16, written by Peter Selinger 2001-2019 O)c1ccc(cc1)O)O)C C0090 Gallic Acid CAS:149-91-7 CID:370 C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C(=C1O)O)O)C(=O)O C0312 Pinocembrin CAS:480-39-7 CID:68071 Oc1cc2O[C@@H](CC(=O)c2c(c1)O)c1ccccc1 C0114 (−)-Epicatechin CID:72276 C1C(C(OC2 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=CC(=C21)O)O)C3 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C3)O)O)O C0105 Glabridin CID:124052 Oc1ccc(c(c1)O)[C@@H]1COc2c(C1)ccc1c2C Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(O1)(C)C C1239 Chrysoeriol CAS:491-71-4 CID:5280666 COc1cc(ccc1O)c1cc(=O)c2c(o1)cc(cc2O)O C0110 Glycyrrhizin CAS:103000-77-7 CID:14982 CC1(C2CCC3(C(C2(CCC1OC4C(C(C(C(O4)C(=O)O)O)O)OC5C(C(C(C(O5)C(=O)O)O)O)O )C)C(=O)C Created by potrace 1.16, written by Peter Selinger 2001-2019 C6C3(CCC7(C6CC(CC7)(C)C(=O)O)C)C)C)C C0242 Naringenin CAS:480-41-1 CID:439246 Oc1ccc(cc1)[C@@H]1CC(=O)c2c(O1)cc(cc2O)O C0089 Galangin CAS:548-83-4 CID:5281616 C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C1)C2 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C(=O)C3 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C3O2)O)O)O C0935 Astragalin CAS:480-10-4 CID:5282102 OC[C@H]1O[C@@H](Oc2c(oc3c(c2 = O)c(O)cc(c3)O)c2ccc(cc2)O)[C@@H]([C@H]([ C@@H]1O)O)O C0045 Epicatechin Gallate CAS:1257-08-5 CID:107905 Oc1cc(O)c2c(c1)O[C@@H]([C@@H](C2)OC(=O)c1cc(O)c(c(c1)O)O)c1ccc(c(c1)O)O C1243 Cinnamic Acid CAS:621-82-9 CID:444539 C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C1)C Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=O)O C1259 Coumarin CAS:91-64-5 CID:323 C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C2C(=C1)C Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=O)O2 C0013 Dibenzoylmethane CAS:120-46-7 CID:8433 O Created by potrace 1.16, written by Peter Selinger 2001-2019 C(c1ccccc1)CC(=O)c1ccccc1 C1178 Beta-Sitosterol CID:222284 CCC(CCC(C)C1CCC2C1(CCC3C2CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C4C3(CCC(C4)O)C)C)C(C)C C0905 Anethole CAS:104-46-1 CID:637563 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 CC1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C1)OC C0377 Rutin CAS:153-18-4 CID:5280805 CC1C(C(C(C(O1)OCC2C(C(C(C(O2)OC3 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(OC4 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=CC(=C4C3 Created by potrace 1.16, written by Peter Selinger 2001-2019 O)O)O)C5 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C5)O)O)O)O)O)O)O)O C0101 Genistein CAS:446-72-0 CID:5280961 C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C1C2 = COC3 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=CC(=C3C2 Created by potrace 1.16, written by Peter Selinger 2001-2019 O)O)O)O C0053 Esculetin CAS:305-01-1 CID:5281416 C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=O)OC2 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C21)O)O C0836 8-Prenylapigenin CAS:72357-31-4 CID:10246505 CC(=CCc1c(O)cc(c2c1oc(cc2 = O)c1ccc(cc1)O)O)C C0602 2,3,9,10-Tetramethoxy-6,8,13,13A-Tetrahydro-5H-Isoquinolino[2,1-B]Isoqu inoline CAS:2934-97-6 CID:5417 COc1cc2CCN3C(c2cc1OC)Cc1c(C3)c(OC)c(cc1)OC C0493 Licochalcone D CAS:144506-15-0 CID:10473311 COc1c(/C Created by potrace 1.16, written by Peter Selinger 2001-2019 C/C(=O)c2ccc(c(c2)CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C)C)O)ccc(c1O)O C0808 5,7-Dihydroxy-2-(4-Hydroxyphenyl)-2,3-Dihydrochromen-4-One CID:932 C1C(OC2 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=CC(=C2C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 O)O)O)C3 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C3)O C0185 Licoagrochacone A CID:5318998 CC(C)(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C)C1 Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C(=C1)C Created by potrace 1.16, written by Peter Selinger 2001-2019 CC(=O)C2 Created by potrace 1.16, written by Peter Selinger 2001-2019 CC Created by potrace 1.16, written by Peter Selinger 2001-2019 C(C Created by potrace 1.16, written by Peter Selinger 2001-2019 C2)O)OC)O C0262 Oleanolic_Acid CID:10494 CC1(CCC2(CCC3(C(=CCC4C3(CCC5C4(CCC(C5(C)C)O)C)C)C2C1)C)C(=O)O)C C0462 Tromethamine CAS:77-86-1 CID:6503 OCC(CO)(CO)N [195]Open in a new tab The term “Diabetic cardiovascular complications” was entered into the GeneCards database, select the relevance score greater than 10.0. A total of 1831 target genes were obtained. The results are shown in [196]Appendix 3. 3.7. Intersecting genes and “drug-target-intersecting genes-disease” network construction 275 intersecting genes were obtained using Venny 2.1. The mappings were analyzed using the network analysis plugin and the compounds with the top degree values were C0363 (Resveratrol), C0041 (Emodin), C1114 (Baicalein), ranked according to their degree values. The gene intersection were shown in [197]Fig. 1, and the “drug-target-intersecting genes-disease” network was shown in [198]Appendix 4. Fig. 1. [199]Fig. 1 [200]Open in a new tab THCQD-disease gene intersection. 3.8. PPI network construction and topology analysis The PPI network display was obtained using STRING database, 275 genes were imported, hide disconnected nodes in the network, 269 nodes and 9312 edges were obtained. Export the PPI network data and import the data into Cytoscape 3.9.1 software for analysis. The genes were ranked according to the degree value, and the top degree values were INS, AKT1, TNF, ALB, IL6, IL1B, etc. The PPI results were shown in [201]Appendix 5, the topology analysis results were shown in [202]Fig. 2, and the topology analysis information were shown in [203]Table 4. Fig. 2. [204]Fig. 2 [205]Open in a new tab Topology analysis. The genes in the figure are sorted by degree, the genes marked in red, the redder the color the larger the degree. Table 4. Topology analysis information. Name Stress Degree TopologicalCoefficient INS 49006 221 0.295989 AKT1 41802 210 0.306749 TNF 40022 209 0.309836 ALB 42916 208 0.306517 IL6 38444 208 0.310566 IL1B 29264 192 0.325971 TP53 28822 181 0.329435 PPARG 27470 179 0.329756 STAT3 20972 170 0.346548 EGFR 21884 165 0.337564 JUN 17580 161 0.358608 CASP3 17880 160 0.355428 HIF1A 16086 156 0.361998 TGFB1 16402 156 0.360188 IGF1 16386 156 0.356072 BCL2 16292 154 0.360853 NFKB1 15054 153 0.368167 MMP9 15408 153 0.363621 PTGS2 16178 151 0.363089 ESR1 16846 150 0.357082 CTNNB1 17688 150 0.352352 IL10 14088 149 0.366772 LEP 17906 148 0.347231 SRC 13432 147 0.365588 CCL2 14084 145 0.368234 IFNG 12540 145 0.3708 TLR4 12200 141 0.375432 SIRT1 13706 140 0.358512 FN1 12166 139 0.376308 EGF 10858 138 0.373946 CXCL8 9436 133 0.384598 MTOR 10988 131 0.375682 ADIPOQ 12322 130 0.352337 GSK3B 10978 129 0.371186 CD4 10158 127 0.386879 FOS 10042 127 0.383641 IL1A 7848 124 0.394887 PTEN 8614 122 0.385772 ICAM1 6932 122 0.398855 FGF2 6840 121 0.393678 PPARA 10646 119 0.360713 VCAM1 6330 118 0.396936 FOXO1 13896 118 0.370835 MMP2 7066 117 0.406798 CRP 8440 116 0.367326 HMOX1 9102 114 0.408127 IL4 5032 113 0.415085 BDNF 8264 113 0.39065 CREB1 10860 113 0.395146 KDR 6348 111 0.394049 HSP90AA1 8416 111 0.374693 SERPINE1 5644 111 0.40254 PECAM1 5298 110 0.407063 HSPA4 9734 110 0.387775 ACE 18020 109 0.369604 IL2 5366 108 0.408635 STAT1 4720 108 0.414006 IRS1 7706 107 0.365088 SMAD3 5180 107 0.41683 JAK2 5116 107 0.41068 NOS3 13142 105 0.39632 CD36 6562 104 0.381252 PPARGC1A 14988 103 0.355865 IGF1R 5046 102 0.393055 NFKBIA 3952 102 0.42127 MAPK1 8278 100 0.391635 SMAD2 3988 100 0.421565 EDN1 8316 100 0.404885 CAV1 8730 97 0.406311 NFE2L2 4376 97 0.410458 PRKACA 15114 96 0.376703 SPP1 3656 94 0.41784 MAPK14 4302 93 0.410557 EP300 4996 93 0.389313 HGF 3270 93 0.418188 SLC2A4 8478 90 0.369686 MPO 3990 90 0.39106 IL17A 2318 90 0.438507 TLR2 2708 90 0.431595 CDKN2A 3312 90 0.423248 SREBF1 7234 89 0.356912 TIMP1 3100 89 0.430078 POMC 14284 89 0.363182 NOTCH1 3228 88 0.428059 MYD88 2566 88 0.431252 MAPK8 2838 88 0.43737 CCK 3130 87 0.436077 NR3C1 6332 86 0.40397 CCN2 2932 86 0.428302 IL13 2080 86 0.434543 MMP3 2224 85 0.442353 TNFSF11 2522 84 0.438606 APOB 6138 83 0.339732 PARP1 2726 81 0.422502 GCG 3814 81 0.390152 SOD2 18696 80 0.378267 SELE 2362 79 0.42691 TNFRSF1A 2170 79 0.433225 FOXP3 1804 79 0.447632 HMGCR 5628 77 0.350747 MMP1 1832 77 0.443698 HMGB1 1986 77 0.44928 CD274 1548 76 0.447112 IGF2 4016 76 0.412162 SLC2A1 5408 75 0.422545 PLG 2566 75 0.430579 RPS6KB1 2094 75 0.446439 RUNX2 2468 75 0.438 AR 2230 73 0.426376 ESR2 2812 72 0.431881 FLT1 1498 72 0.458012 MAP2K1 1356 72 0.461165 NOX4 2156 71 0.43512 ATM 2010 70 0.434647 TGFB2 1542 69 0.445892 DPP4 2344 68 0.411485 FASLG 1054 68 0.470362 PRKCA 1908 66 0.432549 IL5 1310 66 0.434363 GFAP 1876 66 0.440143 LCN2 1798 65 0.432729 APOA1 5480 64 0.349691 PPARD 3970 64 0.430284 ACE2 2252 64 0.436897 SOD1 21996 64 0.399639 AGTR1 3842 62 0.414578 NLRP3 1164 62 0.453226 PLAT 3532 61 0.458763 TIMP2 792 61 0.474198 SELP 958 61 0.42981 TGFBR1 1278 61 0.456336 AKT2 1452 61 0.421286 NOS2 5984 61 0.444867 BMP2 1174 60 0.459073 XDH 3754 59 0.402942 LPL 2718 58 0.340419 F3 1478 58 0.42923 DNMT1 900 58 0.466446 BRCA1 1286 57 0.428715 NR1H4 2068 57 0.375452 TGFB3 774 57 0.463816 PRL 2062 57 0.418162 ITGB3 1906 57 0.391926 CD40LG 530 56 0.468524 INSR 1556 55 0.386014 ABCB1 1998 54 0.406553 NPY 2192 54 0.363232 UCP2 1486 54 0.376799 PTPN1 1070 54 0.457842 SHH 592 52 0.477626 CYP3A4 6400 52 0.322372 G6PC 1662 52 0.338842 UCP1 1308 51 0.3724 CYP19A1 7142 51 0.400646 MMP14 400 50 0.470388 ACACA 1602 49 0.308905 NPPA 3950 49 0.405593 GJA1 2426 49 0.458284 PIK3CG 818 49 0.45776 CPT1A 1116 48 0.350032 ADRB2 3274 48 0.415802 FGFR2 902 48 0.388505 FABP4 966 47 0.401298 G6PD 6652 47 0.314295 NCF1 940 47 0.441226 ELANE 532 47 0.446306 GSR 8432 47 0.397485 CYP2E1 2890 46 0.389381 SLC2A2 1368 46 0.357662 SIRT3 3544 46 0.439346 GLP1R 930 44 0.410906 RAF1 584 44 0.433498 FAS 2258 44 0.4915 PIK3CB 700 44 0.412789 CCL11 292 44 0.465819 PON1 1842 43 0.342511 GSTP1 2880 43 0.351056 SCD 680 43 0.369479 OLR1 522 42 0.434016 GCK 816 40 0.346469 PRKCD 546 40 0.436454 FOXM1 898 40 0.420866 ADIPOR1 626 38 0.437874 TRPV1 1252 38 0.456745 ACHE 896 37 0.425061 S100B 448 37 0.474785 TTR 912 36 0.382752 TXNIP 526 36 0.468764 CFTR 1754 35 0.383673 COMT 1744 34 0.259076 AKR1B1 4368 34 0.363269 HK2 5742 33 0.394057 NOD2 112 33 0.484972 RAC1 414 33 0.442496 PTGS1 3238 33 0.453838 SGK1 660 33 0.429156 FLT4 212 33 0.493608 CS 2446 32 0.302083 MGAM 5396 32 0.365709 ENO2 686 32 0.418132 PRKCB 438 32 0.42981 NR1H3 262 31 0.412725 CYP1A2 1346 30 0.301667 DRD2 1830 30 0.340304 GHR 244 30 0.456955 GDF15 180 30 0.498958 COL18A1 88 30 0.479416 BRCA2 296 30 0.427404 FABP1 382 29 0.330629 KL 310 29 0.473599 CYP2C9 908 28 0.286951 ABCG1 288 28 0.391446 GNRH1 1582 28 0.396154 MAP2K2 150 28 0.472647 SLC6A4 1400 27 0.327713 CETP 628 26 0.346003 LPIN1 360 26 0.374886 BCHE 536 26 0.40638 SOST 306 26 0.521484 CYP2D6 1170 25 0.214661 UCP3 198 25 0.366275 PRKAA1 242 25 0.381176 ADIPOR2 184 25 0.465238 GSTM1 1076 24 0.295704 HSD11B1 2016 24 0.3167 HDAC9 110 24 0.460676 PRKAA2 216 23 0.38359 CYP2C19 656 22 0.228381 NPPB 122 22 0.447117 ACTA2 124 22 0.448789 TRPV4 422 22 0.368806 RPS6KA3 788 22 0.479899 MTTP 58 21 0.329109 CYP17A1 1488 21 0.287032 ALDH2 952 20 0.19532 HTR2A 316 20 0.289394 HAMP 844 20 0.5368 ADA 94 19 0.486475 PNLIP 170 19 0.377873 NPHS1 218 18 0.461505 GUSB 126 18 0.516276 FTO 84 15 0.452058 HSD11B2 836 14 0.286876 CYP11B2 560 14 0.25 LDLR 184 14 0.300912 PRSS1 106 14 0.374052 PLA2G7 148 14 0.452478 TCF4 120 13 0.551489 LIPG 96 12 0.286568 TNFRSF11B 44 12 0.424309 APC 30 11 0.619939 CRYAB 22 10 0.508642 TF 286 10 0.319828 PDX1 8 10 0.430126 FXN 44 9 0.373016 RYR1 80 8 0.317551 ECE1 20 7 0.438837 PKD2 188 7 0.354978 CAT 60 7 0.33887 CYP21A2 8 7 0.3053 NPHS2 0 6 0.526812 GLO1 14 6 0.383202 PEA15 20 6 0.410185 LIN28B 2 5 0.660944 MT-ND6 8 3 0.516779 GAA 0 2 0.601852 DNAH8 0 1 0 GAR1 0 1 0 SPOUT1 0 1 0 [206]Open in a new tab 3.9. GO functional enrichment and KEGG pathway enrichment analysis A total of 1196 BPs, 101 CCs and 210 MFs were obtained from GO functional enrichment. The results of enrichment analysis were sorted according to P-value, The top 3 BPs focused on positive regulation of gene expression, response to hypoxia, positive regulation of transcription from RNA polymerase II promoter. The top 3 CCs focused on extracellular space, extracellular region, cell surface. The top 3 MFs focused on enzyme binding, identical protein binding, cytokine activity. A total of 192 KEGG pathways were obtained, and sorted according to the P-value, KEGG pathways were mainly concentrated in AGE-RAGE signaling pathway in diabetic complications, Pathways in cancer, Lipid and atherosclerosis, Fluid shear stress and atherosclerosis, etc. The top 10 bars of BP, CC, MF and the top 20 bars of KEGG were made as bubble plots, see [207]Fig. 3, [208]Fig. 4; examples of pathways with minimal P-value in KEGG see [209]Fig. 5. Fig. 3. [210]Fig. 3 [211]Open in a new tab Top 10 GO functionality enrichment. BP: biological process, CC: cellular composition, MF: molecular function. The colors range from red to green, with redder colors representing smaller P-value. Bubble size represents the number of basic enrichment, the larger the bubble the more gene enrichment. Fig. 4. [212]Fig. 4 [213]Open in a new tab Top 20 KEGG pathway enrichment analysis. The colors range from red to green, with redder colors representing smaller P-value. Bubble size represents the number of basic enrichment, the larger the bubble the more genes are enriched. Fig. 5. [214]Fig. 5 [215]Open in a new tab Examples of pathways with minimal P-value in KEGG. The red markers in the figure show the position of the target gene in the pathway. May 14, 2024. 3.10. Molecular docking Molecular simulations of the docking process between key components and target genes were performed using AutoDock Vina v.1.2.0 software. This analysis aimed to obtain the binding free energies and the corresponding docking result files. The binding energy data are presented in [216]Table 5. It is important to note that the smaller the binding energy observed in molecular docking, the stronger the binding affinity between the compound and the target protein. The molecular docking results for the three compounds with the six core protein receptors indicated that Resveratrol was able to form strong interactions with all six core protein receptors. Detailed results of the molecular docking are provided in [217]Fig. 6, [218]Fig. 7. Table 5. Combining energy data. Ligand Protein Energy (kcal/mol) Resveratrol INS −6.2 AKT1 −5.6 TNF −8.4 ALB −9.2 IL6 −5.9 IL1B −6.7 Emodin INS AKT1 −6.7 TNF −9.3 ALB IL6 IL1B −7.4 Baicalein INS AKT1 −6.1 TNF −9.3 ALB IL6 −6.3 IL1B [219]Open in a new tab Fig. 6. [220]Fig. 6 [221]Open in a new tab Molecular docking results of key components with target genes. Fig. 7. [222]Fig. 7 [223]Open in a new tab Receptor-ligand binding region. 4. Discussion Taohe Chengqi Decoction is a very commonly used herbal combination for the treatment of diabetes mellitus, and THCQD is also frequently used for the treatment of diabetic cardiovascular complications. This review summarizes the mechanism of THCQD in treating diabetic cardiovascular complications. Although the number of studies is limited, most of the findings suggest that THCQD does have a beneficial effect on diabetic cardiovascular complications ([224]Fig. 8). Fig. 8. [225]Fig. 8 [226]Open in a new tab Mechanism of THCQD for diabetic cardiovascular complications. 4.1. THCQD improves myocardial function in diabetic rats A study by Li [[227]22] found that in diabetic rat model, myocardial fibrosis occurred with increased HYP content and increased expression of type I and III collagen in the myocardium, and that THCQD could counteract fibrosis by reducing myocardial HYP content and decreasing myocardial type III collagen mRNA expression. And Li [[228]21] observed by electron microscopy that THCQD could improve the ultrastructure of myogenic fibers and mitochondria in diabetic rat cardiac myocytes. Heart Injuries in DCM is associated with myocardial fibrosis, which is characterized by ventricular remodeling and interstitial fibrosis, ultimately leading to heart failure [[229]37]. High blood glucose levels can alter cardiac metabolism and function, leading to cardiac stiffness, as well as systolic and relaxation dysfunction [[230]38]. Moreover, persistent hyperglycemia increases the inflammatory response, which exacerbates myocardial fibrosis [[231]39]. Cardiac fibrosis impairs the contractile function of the heart and leads to impaired ventricular relaxation, which eventually leads to ventricular hypertrophy, reduced cardiac output, and heart failure [[232]40]. In healthy cardiac tissue, the extracellular matrix plays a key role in maintaining the structural integrity of the heart, and HYP, a collagen-synthesizing extracellular matrix, is increased in the cardiac tissue of type 2 diabetic rats [[233]41]. Cardiac tissue is mainly composed of collagen I (85 %) and collagen III (11 %) [[234]42], and myocardial fibrosis alters the normal myocardial structure, with increased expression of collagen types I and III leading to cardiac remodeling and consequent myocardial dysfunction [[235][43], [236][44], [237][45]]. The THCQD could stabilize myocardial GLUT4 mRNA expression [[238]24], thereby increasing myocardial glucose utilization and improving myocardial energy balance. Data show that diabetic patients are more prone to myocardial ischemia reperfusion injury (MIRI) [[239]46,[240]47], and MIRI-triggered arrhythmias may lead to myocardial infarction [[241]48]. That is important in patients with diabetic myocardial ischemia. GLUT4 is a glucose transporter responsible for the uptake of glucose into the myocardium. In the case of diabetes, the level of GLUT4 is affected, thus promoting an increase in blood glucose [[242]49] and a decrease in the ability of the myocardium to utilize glucose, which affects myocardial energy balance and consequently abnormal cardiac function. That THCQD could improve myocardial function by increasing cardiomyocyte Na^+-K^+-ATPase and Ca^2+-ATPase activities. Abnormal regulation of Ca^2+ is one of the important reasons for the development of DCM. Increased intracellular Ca^2+ concentration is the main stimulus for smooth muscle contraction [[243]50]. Abnormal Ca^2+ is the main cause of decreased contractility and slow diastole in DCM myocardium, triggering arrhythmias and cellular changes [[244]51]. Increased intracellular Ca^2+ with decreased K^+ can decrease membrane potential and enhance vasoconstrictor response [[245]52]. THCQD could reduce the expression of NLRP3, ASC, and Caspase-1 in myocardial tissue, delay the progression of DCM, reduce p–NF–κB p65 protein expression, and inhibit the activation of NLRP3 inflammatory vesicles [[246]36]. Oxidative stress injury is considered to be one of the major causes of the development of cardiovascular complications in diabetic patients [[247]53]. The development of DCM consists of a hidden subclinical period characterized by damage and abnormalities at the cellular and molecular levels, as well as initial diastolic dysfunction followed by the development of systolic dysfunction, ultimately leading to heart failure [[248]54,[249]55]. GSH-Px is an important peroxidolytic enzyme that protects the structure and function of cell membranes from peroxide disruption and damage, both of which play a crucial role in the balance of oxidation and antioxidation in vivo [[250]56]. MDA content is an important indicator of the body's antioxidant capacity [[251]57]. Increase the activity of GSH-Px and reduce the content of MDA [[252]28], by inhibiting oxidative stress, thus protecting myocardial tissue. Chronic inflammation caused by hyperglycemia is the main feature of DM [[253]58]. Immunoregulation and inflammatory responses play a crucial role in the initiation and development of DCM [[254]59,[255]60]. NLRP3 inflammatory vesicles are multiprotein complexes that coordinate the innate immune response, while activation of unregulated NLRP3 inflammatory vesicles in pathological responses can lead to unexpected immune and inflammatory pathological conditions [[256]61]. NLRP3 inflammatory vesicles are composed of NLRP3, ASC, and Caspase-1 [[257]62], and the inflammatory factors released upon activation can lead to an inflammatory response in the heart, resulting in myocardial pathological changes such as cardiac hypertrophy and myocardial fibrosis [[258]63,[259]64]. p–NF–κB p65 activates NLRP3 and contributes to the regulation of inflammatory cytokines [[260]65,[261]66]. By inhibiting the NF-κB pathway, oxidative stress and apoptosis can be suppressed [[262]67]. This leads to anti-fibrotic and oxidative stress inhibiting effects. 4.2. Protective effect of THCQD on the aortic arch in diabetic rats Li [[263]23] observed by electron microscopy that THCQD improved the elastic membrane structure within the aortic arch and reduced mitochondrial swelling within the mesangial smooth muscle cells in diabetic rats. Previous studies show changes in aortic structure in diabetic rat models [[264]68,[265]69], with increased permeability of damaged aortic endothelial cells, damaged mitochondrial membranes within mid-membrane smooth muscle cell membranes, and swollen mitochondria. 4.3. Anti-fibrosis and anti-atherosclerosis of THCQD in diabetic rat femoral artery THCQD can decrease the expression of collagen I and III in femoral arteries [[266]27]. Vascular fibrosis requires the accumulation of collagen, fibronectin and other extracellular matrix components in the vessel wall [[267]70]. THCQD can decrease TGF-β1 and CTGF expression in the femoral artery of diabetic rats [[268]26]. Overexpression of TGF-β is associated with the pathogenesis of diabetic microvascular and macrovascular complications [[269]71], and TGF-β promotes extracellular matrix deposition leading to vascular fibrosis [[270]72]. CTGF is a secreted protein that plays a major role in angiogenesis and fibrosis [[271]73,[272]74]. The expression of this protein is efficiently induced by TGF-β [[273]75]. CTGF is thought to be both closely associated with vascular fibrosis [[274]76] and to act as a downstream effector of TGF-β, mediating at least part of its pro-fibrotic activity [[275]77,[276]78]. Increased expression of TGF-β1 and CTGF is thought to be related to the mechanisms of fibrosis [[277]79]. These may be the mechanisms through which THCQD exerts its protective effects against diabetic vascular fibrosis. THCQD can decrease the content and expression of TGF-β and increase the expression of IGF-1 in the femoral arteries of diabetic rats [[278]30,[279]33]. IGF-1 can promote angiogenesis and neovascularization [[280]80,[281]81], and IGF-1 can stimulate smooth muscle proliferation in early atherosclerosis [[282]82] and has a protective effect against atherosclerosis [[283]83]. Toll-like receptors may play an important role in the process of arterial fibrosis [[284]84,[285]85] and atherosclerosis [[286]86,[287]87]. TLR-2 and TLR-4 are central to the progression of atherosclerosis [[288]88,[289]89]. TLR-2 and TLR-4-mediated inflammation are involved in the formation of atherosclerotic calcification [[290][90], [291][91], [292][92]] and contribute to the development of atherosclerosis [[293][93], [294][94], [295][95]]. Just THCQD can decrease TLR-2 and TLR-4 expression in the femoral artery vasculature. These evidences above suggest that THCQD has a protective effect on femoral artery fibrosis and atherosclerosis. 4.4. Anti-inflammatory and vasoprotective effects of THCQD in thoracic aorta of diabetic rat One of the key factors of vasculopathy and inflammatory response includes VCAM-1 and MCP-1 [[296][96], [297][97], [298][98]]. NF-κB activation triggers reactive oxygen species accumulation and inflammation [[299]99]. Inflammatory factors such as MCP-1 and VCAM-1 are involved in the pathophysiological process of DCM [[300]100,[301]101]. THCQD could reduce the expression of VCAM-1, MCP-1, and NF-κB proteins in the thoracic aorta of diabetic rats, and reduce the expression of NF-κB mRNA, MCP-1 mRNA, and VCAM-1 mRNA in the thoracic aorta [[302]29], thereby reducing inflammation. THCQD can reduce the production of AGEs and decrease the expression of RAGE mRNA in the thoracic aorta of diabetic rats [[303]32]. THCQD may exhibit a protective effect on the thoracic aorta by reducing the expression of RAGE and AGEs. Specific receptor binding of RAGE and AGEs is important in the function of atherosclerotic vascular smooth muscle cells (VSMC) [[304]102]. AGEs and oxidative stress are considered to be key factors in the development of cardiovascular disease and diabetic complications [[305]103,[306]104]. Accelerated formation of AGEs is associated with the pathogenesis of diabetic macrovascular complications [[307]71]. Also AGEs are thought to play a role in the development and progression of atherosclerosis [[308]105]. RAGE is produced through non-enzymatic glycosylation reactions and is thought to be a major causative factor in triggering diabetic vascular complications [[309]106]. THCQD can decrease the expression of PI3K (P85) mRNA and Akt mRNA in the thoracic aorta of diabetic rats [[310]34]. Vascular endothelial cells have the function of regulating vascular tone, and vascular endothelial cell dysfunction is an important pathological feature of several cardiovascular diseases, which is mainly characterized by a decrease in endothelium-dependent vasodilatory function with varying degrees of inflammatory response and elevated levels of oxidative stress [[311]107,[312]108]. Nitric Oxide (NO) mediated by vascular eNOS production has strong anti-inflammatory effects [[313]109]. THCQD can increase the expression of eNOS mRNA in the thoracic aorta [[314]35]. eNOS-mediated anti-inflammatory effects are closely related to the PI3K-Akt signaling pathway [[315]110]. PI3K-Akt is an important intracellular signaling pathway that mediates endothelial cell proliferation, migration, and survival and plays an important role in angiogenesis [[316]111,[317]112]. The Akt cascade response initiated by tyrosine kinases, immune cell receptors, cytokine receptors, G protein-coupled receptors, and PI3K-stimulated PIP3 generation activation may further influence the immune inflammatory response [[318]113,[319]114]. Research shows that, inhibition of PI3K and Akt expression attenuates injury-induced vascular VSMC proliferation, thereby affecting the further development of atherosclerosis [[320]115]. There are may be the mechanism by which THCQD can improve diabetic atherosclerosis. 4.5. Herbs used in combination with THCQD THCQD contains Peach Seed as a drug, and some studies have confirmed that Peach Seed can improve the level of macrovascular fibrosis in diabetes [[321]116,[322]117]. Moreover, the combination of herbs containing Peach Seed can treat cardiovascular diseases and improve atherosclerosis [[323]118,[324]119]. THCQD was used in combination with other herbs when used to improve diabetic cardiovascular disease. Of all the studies included in this review, 3 studies [[325]30,[326]31,[327]33] used only fixed combinations of THCQD. 13 studies [[328][21], [329][22], [330][23], [331][24], [332][25], [333][26], [334][27], [335][28], [336][29],[337]32,[338][34], [339][35], [340][36]] used THCQD in combination with other herbs. 12 studies [[341][21], [342][22], [343][23], [344][24], [345][25], [346][26], [347][27], [348][28], [349][29],[350]32,[351]34,[352]35] added Astragalus membranaceus, Radix Ophiopogonis, Rehmannia glutinosa and Radix scrophulariae to THCQD. The Radix Ophiopogonis, Rehmannia glutinosa and Radix scrophulariae form a traditional Chinese herbal formula called “Zengye Decoction”. Zengye Decoction is from “Identification of Warm Disease” (written in 1798) and has been used to treat diabetes since the Qing Dynasty, and research [[353]120,[354]121] has shown that Zengye Decoction exerts significant hypoglycemic effects in type 2 diabetes by improving insulin resistance. 4 studies [[355]29,[356]32,[357]34,[358]35] added Salviae Miltiorrhizae. The Salviae Miltiorrhizae is effective in the treatment of diabetic complications and anti-fibrosis [[359][122], [360][123], [361][124]]. In addition, Salviae Miltiorrhizae is also very effective in improving MIRI [[362]125,[363]126]. Four studies [[364]29,[365]32,[366]34,[367]35] added Asarum. Asarum has anti-inflammatory and cardiovascular protective effects [[368]127,[369]128]. And three studies [[370]29,[371]32,[372]35] added cooked Rhubarb. Cooked Rhubarb is the result of the concoction of Rhubarb and the concoction of cooked Rhubarb can reduce the diarrhea effect of Rhubarb. 4.6. Network pharmacology and molecular docking In this study, we used network pharmacology to further predict the targets of action of THCQD for the treatment of diabetic cardiovascular complications. The results of “drug-target-intersecting genes-disease” showed that Resveratrol, Emodin, and Baicalein were the most critical compounds for THCQD in the treatment of diabetic cardiovascular complications. Resveratrol is a natural product with anti-oxidative stress, anti-inflammatory, and pancreatic β-cell protection properties, and may ameliorate diabetic cardiovascular complications through multiple signaling pathways [[373]129]. Emodin is the main constituent of rhubarb, which is widely used in the treatment of cardiovascular diseases and has very excellent antifibrotic properties [[374]130,[375]131]. Baicalein is a flavonoid that has been shown to improve insulin resistance, combat oxidative stress and protect cardiomyocytes. These three compounds show great potential in the treatment of diabetic cardiovascular complications. The results of PPI protein interactions and topology analysis, we screened the top 6 target genes INS, AKT1, TNF, ALB, IL6, IL1B by degree value. INS is the only human insulin-encoding gene that regulates insulin synthesis and secretion. Insulin resistance not only leads to hyperglycemia, but also to atherosclerosis, hypertension, and endothelial dysfunction, all of which are risk factors for cardiovascular complications [[376]132]. AKT1 is a molecule that plays a key role in cell signaling and is involved in the regulation of a variety of processes including cell growth, survival, metabolism and differentiation. The effects of AKT1 on diabetes and cardiovascular complications are bidirectional. Activation of AKT1 benefits vascular repair and regeneration, improves mitochondrial function, and reduces oxidative stress, but excessive activation leads to diminished cellular response to insulin and promotes the development of atherosclerosis. The ALB gene is the genetic code for human albumin. The assessment and management of albumin levels are crucial for the effective management of cardiovascular risk in patients with diabetes [[377]133]. TNF, IL6 and IL1B play key roles in the development of cardiovascular complications in diabetes, and their role in the AGE-RAGE signaling pathway in diabetic complications is critical for the course of diabetic complications. Among the KEGG results, the most relevant to the target was AGE-RAGE signaling pathway in diabetic complications. The AGE-RAGE signaling pathway in diabetic complications, Fluid shear stress and atherosclerosis, Lipid and atherosclerosis are the important pathways in the prevention and treatment of cardiovascular complications in diabetes. This corroborates the results of our systematic review. The AGE-RAGE pathway can elicit a variety of intracellular signals. With the binding of O[2] to NADPH oxidase to generate ROS leading to the activation of MAPKs (p38, ERK, JNK), PI3K-AKT and JAK-SATAT, which leads to the activation of transcription factors (NF-κB, ERK1) and further promotes the expression of various pro-inflammatory cytokines (IL-1, IL-6, TNF-α) and genes related to atherosclerosis (VCAM-1, tissue factor, VEGF, and RAGE) [[378]134,[379]135]. As suggested by the results in the systematic review, THCQD can positively affect both the activation, transduction (NF-κB) and product components (VCAM-1, VEGF, RAGE) in this pathway. This study utilized molecular docking to analyze the relationship between key components and target genes. Combined with free energy data, it was found that there is a significant binding affinity between the key components and target genes. Specifically, the binding free energy data in [380]Table 5 shows that Resveratrol can form strong interactions with all six core protein receptors. This may be the key component of THCQD in treating diabetic cardiovascular complications. Furthermore, the detailed docking images displayed in [381]Fig. 6, [382]Fig. 7 provide intuitive evidence for understanding the molecular mechanism of action between the key components and target genes. In particular, the docking results clearly demonstrate the hydrogen bonds and hydrophobic interactions between the components and receptors, which are crucial for their pharmacological effects. With these findings, we have gained a deeper understanding of the role of THCQD in the treatment of diabetic cardiovascular complications. 5. Conclusion In summary, Taohe Chengqi Decoction (THCQD) has shown promising therapeutic effects in the treatment of diabetic cardiovascular complications. The review indicates that THCQD improves myocardial function, reduces fibrosis, and exhibits anti-inflammatory and anti-atherosclerotic properties. Network pharmacology and molecular docking studies have identified key compounds like Resveratrol, Emodin, and Baicalein that target critical pathways in diabetic complications. Future research should focus on elucidating the long-term clinical outcomes of THCQD treatment and optimizing its formulation for maximal efficacy and safety. 6. Limitations and prospects While providing valuable insights, this review has some limitations. First, a limited number of studies were included, which may limit the generalizability of the conclusions we draw. Second, some of the studies had quality issues in reporting baseline characteristics, description of randomization methods, and other key study designs. In addition, although network pharmacology is based on network analysis in systems biology, the results derived from it still need to be validated by animal experiments to ensure its scientific validity and reliability. In spite of these limitations, THCQD, an all-natural herbal formula, shows promising potential in the treatment of diabetic cardiovascular disease. With ongoing research in this field, discoveries about the underlying mechanisms of its positive effects on cardiovascular health are anticipated. By identifying such mechanisms, THCQD's therapeutic effects can be better understood, paving the way for improved treatment strategies for diabetic cardiovascular disease, benefiting many patients worldwide. Statement The exact experimental data were not available in the original literature retrieved (results were given in figures), and therefore the data could not be obtained for Meta-analysis. Therefore, sections 12, 13a, 13b, 13e, 13f, and 20d of the PRISMA 2020 checklist were not reported in this article. Ethics approval and consent to participate Not Applicable. Consent for publication All the authors agreed to the manuscript's publication. Funding The implementation of this study was supported by the Shanghai TCM Inheritance and Scientific Technological Innovation Project (NO: ZYCC2019011). Availability of data and material The dataset used in this study is available upon reasonable request from the corresponding author. CRediT authorship contribution statement ZHANG Chun-peng: Writing – review & editing, Writing – original draft, Software, Data curation. CAO Tian: Writing – review & editing, Writing – original draft, Data curation. YANG Xue: Writing – review & editing, Methodology, Funding acquisition, Conceptualization. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements