HOMER1 gene and its transcript mmu_circRNA_26701 are specifically expressed in the glutamate synapse, which may provide new clues and intervention targets for the progression of this refractory disease.Postoperative delirium (POD) is a common postoperative complication in elderly patients and seriously affects postoperative recovery. The exact mechanism of POD is still unclear. Therefore, it is necessary to explore the mechanism of POD in transcriptional regulation. At present, circRNAs have been proven to play an important role in a variety of mental health and cognitive disorders, such as Alzheimer’s disease, depression and schizophrenia. To reveal the effect of circRNA on POD, we used microarray to analyze the differential expression profiles of circRNAs in the hippocampus of 12-month-old mice between the tibial fracture and control groups. A total of 1,4236 circRNAs were identified. Compared with the control group, there were 500 circRNAs with increased expression and 187 with decreased expression. The accuracy of the microarray data was further verified by qRT–PCR. Finally, GO enrichment and KEGG pathway analyses indicated that changes in axon orientation, ubiquitin-mediated proteolysis, glutamate synapses, the estrogen signaling pathway, the RAS signaling pathway and other systems may be important potential pathological mechanisms in the progression of POD. In particular, we found that the  Postoperative delirium (POD) is a common postoperative complication in elderly patients , especiaPrevious studies have suggested that POD patients and AD patients have very similar pathogenic and pathophysiological mechanisms . HoweverIn recent years, studies on the regulation of gene transcription in POD have increased. However, there are still few studies on the involvement of circRNAs in the pathogenesis of POD. We used microarray technology to analyze the differential expression profile of circRNA in the hippocampus of 12-month-old mice, which may provide new insights for research on the progress and intervention targets of circRNA on POD in aged mice.This experiment was carried out in accordance with the Guidelines for the Care and Use of Experimental Animals and approved by the Animal Ethics Committee of the First Affiliated Hospital of Chongqing Medical University. Eighteen 12-month-old male C57BL/6J mice were purchased from the Animal Experimental Center of Chongqing Medical University , weighed 30–35 g, and were group-housed with standard rodent chow for 1 week . All the animals were used for behavioral studies, and the survival rate following surgery was 100%. The success rate of modeling was 88.9% (one sample in the surgery group was excluded from the study due to modeling failure). The six samples in the microarray chip analysis were selected randomly from the successfully modeled control group and the experimental group. Another six samples were also randomly selected from the two groups for histological analysis. Investigators who performed surgery on the animals were not blinded to the treatment groups and collected samples, which were then analyzed by other investigators who were blinded to the specific treatment.Intramedullary nail fixation of tibial fracture on the left hind leg was performed under isoflurane anesthesia  and subcutaneous butylphenol analgesia . Details were as follows: the temperature was maintained with a heating pad, all mice were fixed in the supine position after successful anesthesia, the left hind leg was disinfected with povidone iodine 3 times after skin preparation, and a longitudinal incision of approximately 1 cm was made in the middle and upper tibia of the left hind leg to fully expose the tibia. Osteotomy was performed in the middle part of the tibia, and then a 0.38 mm diameter sterile steel needle was inserted into the tibial medullary cavity. The end of the steel needle was cut at the level of the tibial plateau. After rinsing the incision, the wound was closed with 5-0 nylon sutures, the maintenance of anesthesia was stopped, and the mice were placed back into the cage to wake up naturally. All surgeries were completed within 15 min. To eliminate the effects of anesthesia and analgesia on cognition, mice in the control group received the same dose of anesthesia and analgesia.The fear conditioning test (FCT) is designed to identify how animals learn and remember unpleasant experiences related to the environment. Sound and light are commonly used as conditioned stimulus (CS), while aversive stimuli (such as electric shocks to the feet) are used as unconditioned stimuli (US). These two types of stimulation appeared in pairs during the test. The animals were able to make CS-US connections between the shock and the environment in addition to the connection between the sound and the shock. Our experimental design was slightly modified on the basis of previous studies . The micContextual and cued tests were performed at 09:00 am on Day 3 after surgery. In the contextual test, mice were allowed to explore without the stimulation of sound and electric shock for 5 min; 2 h later, mice were placed in a different environment from the preoperative training environment . After a 3-min exploration, the mice were given the same sound stimulation  but no electric shock. The interval between the two stimulations was still 58 s. The box was wiped with alcohol to ensure that the next animal will not be affected by the smell of the previous mice; all tests were performed with the same equipment and analyzed by the same software.The open field test (OFT) was used to evaluate the anxiety and activity levels of the experimental animals. Mice were placed in the same corner of the experimental box  as in previous studies . During The hippocampal tissue was fixed in 4% formaldehyde, followed by regular dehydration, transparent paraffin embedding, sectioning, and dewaxing. After hematoxylin & eosin HE staining, further dehydration, transparency, and sealing, the slides were analyzed under a light microscope .The hippocampal tissues of the surgery and control group mice were harvested on Day 3 after surgery and stored at −80°C until use. Total RNA was extracted from the hippocampal samples of both groups using TRIzol reagent  according to the manufacturer’s instructions. The OD260/OD280 ratio of each sample ranged from 1.95 to 2.07, and the OD260/OD230 ratios were greater than 1.9, indicating good RNA quality .–ΔΔCt method, and β-actin mRNA was used as a normalizer gene. All experiments were performed in triplicate.qRT–PCR was performed using the TAKARA PrimeScript RT reagent Kit TRR037A reverse transcription polymerase chain reaction system  according to the manufacturer’s instructions. The specific primer pairs used in this study are listed in We randomly selected 3 pairs of hippocampal samples from the surgery group and the control group for microarray analysis. Total RNA from each sample was quantified using a NanoDrop ND-1000. Sample labeling and array hybridization were performed according to the manufacturer’s protocol (Arraystar Mouse circular RNA Mcrioarray V2.0). Briefly, total RNA was digested with RNase R  to remove linear RNAs and enrich circular RNAs. Then, the enriched circular RNAs were amplified and transcribed into fluorescent cRNA utilizing a random priming method . The labeled cRNAs were purified by an RNeasy Mini Kit (Qiagen). The concentration and specific activity of the labeled cRNAs (pmol Cy3/μg cRNA) were measured by a NanoDrop ND-1000. One microgram of each labeled cRNA was fragmented by adding 5 μl 10 × Blocking Agent and 1 μl of 25 × Fragmentation Buffer and then heated at 60°C for 30 min. Finally, 25 μl 2 × Hybridization buffer was added to dilute the labeled cRNA. Fifty microliters of hybridization solution was dispensed into the gasket slide and assembled onto the circRNA expression microarray slide. The slides were incubated for 17 h at 65°C in an Agilent Hybridization Oven. The hybridized arrays were washed, fixed and scanned using the Agilent Scanner G2505C.t-test. The circRNAs with fold changes greater than or equal to 1.3 and a p-value ≤ 0.05 were chosen as the significant differential expression. The microarray analysis was performed by KangChen Biotech .The collected array images were analyzed by Agilent feature extraction software (version 11.0.1.1). Quantile normalization and subsequent data processing were performed using the R software limma package. After quantile normalization of the raw data, circRNAs for which 2 out of two samples had flags in Present or Marginal  were chosen for further data analysis. Fold change filtering was employed for identification of differentially expressed circRNA between the two groups. Gene ontology (GO) and KEGG pathway enrichment analyses were conducted through the standard computation method. Gene ontologies are organized into a hierarchy structure of annotation terms to promote analysis and interpretation at different levels. The top-level ontologies are biological process, cellular component, and molecular function. Thus, GO database analysis was employed to reflect genetic regulatory systems based on the differentially expressed circRNAs in the biological process, cellular component and molecular function classification. KEGG database analysis was applied to identify the potential key pathways related to the differentially expressed genes. When comparing the contour differences between the two groups, the “fold range”  for each circRNA between the groups was calculated. The statistical significance of the difference was conveniently estimated by t-test, and P < 0.05 was considered statistically significant.Statistical analysis was performed by GraphPad Prism 8.3.0 . All data are expressed as the mean ± SEM. The difference between the two groups was tested by double-tailed Student’s P > 0.05), as shown in P > 0.05), but mice in the surgery group spent significantly less time in the central area of the arena (P < 0.05), as shown in P < 0.05), while there was no significant difference in the freezing time of mice in the two groups during the cued test (P > 0.05), as shown in Experimental procedures and the design of the fear conditioning test (FCT) are shown in P-value ≤ 0.0 5)  . In addi≤ 0.0 5) . These d≤ 0.0 5) .The GO and KEGG pathway analyses were performed for functional enrichment analysis of these differentially expressed circRNAs. In the GO analysis, the upregulated biological process was mainly involved in neuron projection development, as well as neuron generation, differentiation and development, while the downregulated biological process mainly included cell process and cellular macromolecule metabolism. In the GO molecular function analysis, the most significantly upregulated and downregulated GO functional items were ubiquitin-like protein ligase activity and phosphatidylinositol-3-phosphate binding, respectively. In the GO cell component analysis, the most significantly upregulated and downregulated GO functional items were synaptic function and axon function, respectively. In KEGG pathway analysis, we showed 10 upregulated pathways and 10 downregulated pathways with the most significant differences, among which upregulated pathways mainly included axonal orientation, ubiquitin-mediated proteolysis and glutamate synapses, and downregulated pathways mainly included the TGF-β signaling pathway, estrogen signaling pathway and RAS signaling pathway. The complete information of all GO functional enrichment and KEGG pathways is shown in p-value  denotes the significance of the pathway correlated to the conditions. The lower the p-value is, the more significant the pathway. We provided all differentially expressed genes in the top 3 upregulated and downregulated pathways  (GO: 0048666) (GO: 0030182) (GO: 0007399) and synapses (GO: 0045202), and KEGG pathway analysis showed that the upregulated pathways mainly included axonal orientation, ubiquitin-mediated proteolysis, glutamate-energy synapses, phospholipase D signaling pathway, and neurotrophin signaling pathway. Downregulated pathways mainly include the TGF-β signaling pathway, estrogen signaling pathway, RAS signaling pathway, etc. KEGG analysis has enriched the regulatory network of multiple signaling pathways in POD progression, and many signaling pathways have been fully validated in AD models. For example, axon-guiding molecules play a role in the occurrence and development of AD by participating in different mechanisms . Dysregutrans-synaptic transmission is considered to be closely related to the development and treatment of various mental health and cognitive diseases. Glutamate signals are processed by a variety of receptors, mainly including metabolic glutamate receptors (MGluRs), which regulate downstream Ca2+ signals by interacting with the scaffold protein Homer 1 .WR conceived and designed the study and interpreted the results. NL, RY, and ZW performed the experiments and prepared the initial draft of the manuscript. NL and JG supervised the project. All authors read and approved the final submission.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.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.


Nonalcoholic fatty liver disease (NAFLD) is a common chronic liver disease, characterized by excessive accumulation of hepatocyte fat. However, there is no exact and effective pharmacotherapy for NAFLD. Yinchen linggui zhugan decoction (YLZD) has been widely used to treat NAFLD. Nevertheless, its pharmacological and molecular mechanisms have not been clearly elucidated. This study was carried out to investigate the active components of YLZD and explore its potential mechanisms for treating NAFLD by network pharmacology and experimental verification. The results showed that a total of 120 active components of YLZD and 365 targets were retrieved through databases, and the main active ingredients of YLZD consisted of chlorogenic acid, emodin, aloe-emodin, rhein, and geniposide. KEGG enrichment analysis revealed fundamental roles of TNF, PI3K/AKT, HIF-1α, and insulin resistance signaling pathways in the treatment of NAFLD by YLZD. Moreover, our experimental verification results showed that YLZD improved the liver pathological and cholesterol level, and reduced the expressions of TNF-α, IL-1β, IL-6, NF-κB, CCL2, and CXCL10 in NAFLD rats, which all belonged to TNF signaling pathway. The molecular docking confirmed the correlation between the four core components  and key factors  in TNF signaling pathway. In conclusion, the present study systematically clarified the protective mechanisms of YLZD against NAFLD through targeting the TNF signaling pathway, and provided new ideas for the drug research of this disease. Nonalcoholic fatty liver disease (NAFLD) is characterized by excessive accumulation of hepatocyte fat , which iArtemisiae scopariae (“Yinchen” in Chinese), Gardeniae fructus (“Zhizi” in Chinese), Radix rhei et rhizome (“Dahuang” in Chinese), Poria (“Fuling” in Chinese), Cinnamomi ramulus (“Guizhi” in Chinese), Atractylodes macrocephala koidz. (“Baizhu” in Chinese), and Licorice (“Gancao” in Chinese). Our previous study showed that YLZD improved oxidative stress and lipid metabolism in HFD-induced NAFLD rats  has been found to be effective for treating NAFLD in China and some other Asian countries . PreviouFLD rats , but itsin vivo. Furthermore, a molecular docking technology was used for verification. The workflow of this investigation is shown in Network pharmacology, as a bridge between TCM and modern medicine, is a new interdisciplinary approach . Networkhttp://tcmspw.com/tcmsp.php)  Database (msp.php)  was emplmsp.php) . In addihttp://herb.ac.cn/) (https://www.uniprot.org) (Homo sapiens (Human),” and Cytoscape (v 3.6.1) software was used to construct the active component-target network. NAFLD-related potential targets were collected from the GeneCards (https://www.genecards.org/) (http://disgenet.org/)   databaserot.org)  with theds.org/)  and DisGet.org/)  databasehttp://bioinformatics.psb.ugent.be/webtools/Venn/) to obtain the anti-NAFLD action targets of YLZD. Next, these intersecting targets were uploaded to the STRING database (https://string-db.org/) (The YLZD action targets were intersected with NAFLD targets using a Venn diagram (db.org/)  for obtahttps://david.ncifcrf.gov/)  to generate bubble plots. Finally, the component-target-pathway-disease network was established by Cytoscape to further illustrate the action mechanisms and targets of YLZD for treating the NAFLD.The DAVID database (rf.gov/)  was applArtemisiae scopariae, 0.9 g G. fructus, 1.2 g Radix rhei et rhizome, 2.4 g Poria, 0.45 g Cinnamomi ramulus, 1.2 g Atractylodes macrocephala koidz, and 1.2 g Licorice. All herbal decoction pieces were decocted twice after soaking, and the solid-liquid separation was carried out while hot. Concentration was performed at a reduced pressure and a temperature lower than 65°C and then freezing method was used for drying. For quality assurance, the procedure was carried out by Beijing Tcmages Pharmaceutical Co., Ltd.  in accordance with the Good Manufacturing Practice for Drugs. For High Performance Liquid Chromatography (HPLC) analysis, standards of chlorogenic acid, geniposide, isochlorogenic acid A, isochlorogenic acid B, isochlorogenic acid C, aloe-emodin, rhein, glycyrrhizic acid, and emodin were purchased from Chengdu Pufei De Biotech Co., Ltd. . Then, a Waters 2695 HPLC system and a Hypersil ODS-2 Column  were employed for the major YLZD components detecting. The column temperature was adjusted to 30°C, the flow rate was set as 1.0 ml/min and detection wavelength was 203 nm. Acetonitrile and 0.1% phosphoric acid solution were used as mobile phase A and B, respectively. The following gradient conditions were applied: 0.0∼60 min with 10%–50% A and 90%–50% B; 60–80 min with 50%–90% A and 50%–10% B; 80–80.1 min with 90%–10% A and 10%–90% B; 80.1–85 min with 10% A and 90% B.YLZD was provided by the Pharmacy Department of Dongfang Hospital, Beijing University of Chinese Medicine  and consisted of the following herbs: 1.8 g https://www.rcsb.org/) (https://pubchem.ncbi.nlm.nih.gov/) (The 3D structures of the target proteins were obtained from the RCSB PDB database (sb.org/) , and theih.gov/)  and wereih.gov/) . The docih.gov/) .Six-week-old male Sprague-Dawley (SD) rats (weighing 180 ± 20 g) were bought from Beijing Vital River Laboratory Animal Technology Co., Ltd. . The experimental animals were all housed in a controlled environment with temperature of 22 ± 2°C, humidity of 50∼60% and a 12/12 h light/dark cycle. The rats were free to sterile water and standard laboratory chow during the adaptive feeding for 7 days. The experimental process was conducted strictly following the guidelines for the management and the use of laboratory animals of Animal Ethics Committee of Beijing University of Chinese Medicine (No. BUCM-4-2020102104-4162).n = 6), model group (n = 24). The NC group rats were fed with standard laboratory feed for 10 weeks, followed by gavage with sterile distilled water (1.0 ml/kg/day) for 4 weeks. The model group rats were fed with HFD  purchased by Beijing Keao Xieli Feed Co., Ltd.  for 10 weeks to induce NAFLD. After successful model making, the rats were randomly divided into the HFD group (n = 6), YLZD low-dose group , medium-dose group , and high-dose group . During the 4-weeks intervention period, the HFD group rats were orally administered sterile distilled water (1.0 ml/kg/day) and the intervention group was instilled with different concentrations of YLZD . The equivalent dose for animals was obtained by calculating the equivalent amount of body surface area ratio between experimental animal and human. The equivalent dose of YLZD administered in this study was 6.93 g/kg, which is the medium-dose. The low-dose (3.465 g/kg) was 1/2 times of the medium-dose and the high-dose (13.86 g/kg) was twice of the medium-dose. The behavioral activities and fur status of rats were observed every day, and the weight together with food intake of rats were monitored every week. After 4 weeks’ treatment, the rats were anesthetized and sacrificed to collect serum and liver tissue samples.Thirty SD rats were randomly divided into a negative control group  was used to analyze the contents of alanine aminotransferase (ALT), aspartate aminotransferase (AST), total cholesterol (TC) and triglyceride (TG).Fresh liver tissues were fixed in 4% paraformaldehyde fixative for 24 h. After several steps such as ethanol dehydration, xylene transparency, and paraffin embedding, the sections were produced using a microtome and then they were stained with hematoxylin and eosin (H and E). In addition, the frozen liver tissues were sliced and mounted on glass slides to recover to room temperature and soaked in distilled water for 5 min and 60% isopropanol for 2 min. Then they were stained with Oil Red O (ORO) dye for 10 min and fully washed with distilled water. The histopathological changes in the H&E and ORO-stained slides were characterized by light microscopy.via a NanoDrop® ND-2000 (Therno scientific). Ten microliters of RNA were extracted from each rat, PrimeScript™ RT reagent Kit with gDNA Eraser  was performed to reverse transcription. Then, the RT-qPCR was performed on the ABI7500 fast system (Applied Biosystems). The relative mRNA expression was calculated by the 2−ΔΔCT method. The primers of tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), interleukin-1β (IL-1β), nuclear factor kappa-B (NF-κB), C-C motif chemokine 2 (CCL2), and C-X-C motif chemokine 10 (CXCL10) were designed and synthesized by Invitrogen. The sequences of the primers are given in The total RNA extraction was carried out after the liver tissues homogenization by Trizol reagent . The concentration and purity of RNA were determined The collected liver tissues were washed 2 to 3 times with physiological saline to remove blood and to strip the fat from the connective tissue on the surface. 1 g liver tissues were accurately weighed, cut up and homogenized with 9 ml phosphate buffer (0.01 mol/L) on ice and then the mixtures were centrifuged at 3,000 rpm for 15 min at 4°C. The supernatant was removed and stored in a refrigerator at −20°C. The levels of liver TNF-α (No. YJ432890), IL-6 (No. YJ052732), IL-1β (No. YJ435222), NF-κB (YJ093211), CCL2 (No. YJ097621), and CXCL10 (No. YJ654321) were detected through conventional double-sandwich Enzyme-Linked Immunosorbent Assay (ELISA). The above kits were purchased from Shanghai Enzyme-linked Biotechnology Co., Ltd. , and the procedures were operated strictly following the kit instructions.2O2 solution and incubated for 25 min at room temperature in dark to block endogenous peroxidase. Then, non-specific binding sites on the sections were blocked off using 3% BSA, and the tissues were incubated with primary antibodies of TNF-α , IL-6 , and NF-κB p65  overnight at 4°C. After that, the sections were incubated with secondary antibody of HRP conjugated Goat Anti-Rabbit IgG (H + L)  and Anti-Mouse IgG (H + L)  at room temperature for 50 min. The antibodies used in the experiment were purchased from Wuhan Servicebio Technology Co., Ltd.  and Proteintech Group, Inc. . Finally, the expressions of TNF-α, IL-6 and NF-κB p65 in liver tissue were observed using light microscope after color development with DAB, re-staining with hematoxylin, dehydration with ethanol, and sealing with neutral glue. The Image Pro Plus 6.0 software  was adopted to analyze the IOD/Area  for antigen retrieval. After washing in PBS (pH 7.4), the sections were placed in a 3% HIOD/Area .p < 0.05.The statistical analysis was carried out by Graphpad Prism 8.0, and the measurement results were expressed as mean ± standard error of the mean (SEM). One-way analysis of variance was adopted for the comparison among multiple groups, and a marked statistical difference was determined at A total of 120 active components were obtained through TCMSP database and related literatures searching, and these ingredients were listed in detail in The term “nonalcoholic fatty liver disease” was used for searching in the GeneCards and DisGeNET databases. The median relevance score of the GeneCards database was calculated to be 20.63 twice, and 413 data points with relevance scores ≥20.63 were screened. A total of 140 data points with Score_gda ≥0.1 were screened from the DisGeNET database. A total of 487 potential disease targets associated with NAFLD were obtained after deduplication and correction using the UniProt database . The aboThe above 130 common targets were imported into the STRING database to obtain the protein interaction network. The PPI network in p < 0.01 and FDR <0.01 as screening conditions , cellular component (CC) and molecular function (MF). A total of 261 biological entries were involved in the GO analysis of YLZD for NAFLD using counts >3, nditions . Among tp < 0.01) were obtained, and the results were given in DAVID database was employed to analyze the 130 overlapped targets between YLZD and NAFLD. 101 pathways  and three core targets  on the TNF signaling pathway were used as ligands and receptors, respectively. The lower binding energy indicates a more stable binding conformation between the receptor and ligand . A thresThe network pharmacology analysis results were validated through the establishment and treatment of an HFD-induced NAFLD rat model with YLZD. NAFLD rats had notably higher body weights and liver wet weights at week 14 by comparison with the NC group . An inspMoreover, the serum AST, ALT, TC, and TG levels were markedly increased in NAFLD rats compared with the NC group . NotablyH and E and Oil Red O staining of liver tissues in NC group showed a radial arrangement of hepatocytes, centered on the central vein, with clearly visible hepatic lobules and hepatic cords. No steatosis, necrosis or obvious inflammatory cell infiltration was observed . In the TNF-α, IL-6, IL-1β, NF-κB, CCL2, and CXCL10 gene expression levels were notably elevated in the liver of HFD-induced NAFLD rats, while YLZD treatment effectively inhibited the mRNA expression levels of these cytokines.KEGG pathway enrichment analysis revealed that the identified candidate targets of YLZD were enriched in the TNF signaling pathway, which had a significant impact on the pathogenesis of NAFLD. Therefore, we focused on the exploration of TNF signaling pathway related factors expression for further verification. As shown in To further verify the expression of TNF signaling pathway-related proteins, the expression levels of TNF-α, IL-6, IL-1β, NF-κB, CCL2, and CXCL10 were measured by ELISA. As shown in NAFLD is a global public health problem with no U. S. Food and Drug Administration (FDA)-approved pharmacological therapies . In receRadix rhei et rhizome and have good anti-inflammatory, anti-tumor, cardiovascular and liver protective effects (G. fructus, could alleviate liver injury by enhancing antioxidant defense system and inhibiting apoptotic signaling pathways (via antioxidant and anti-inflammatory effects (Associations between the components and their corresponding potential targets were established by a component-target network. The results from network pharmacology approach and HPLC analysis demonstrated that emodin, aloe-emodin, rhein, geniposide, and chlorogenic acid may be the main active ingredients for YLZD in NAFLD treatment. Interestingly, previous investigations have revealed that these five ingredients were associated with NAFLD. Emodin, aloe-emodin and rhein are the main free anthraquinones of the  effects . For exapathways . It has pathways . Chlorog effects . Moreove effects . This ilMost notably, we found that TNF signaling pathway was more closely associated with NAFLD pathogenesis by comparison with other pathways on the basis of the KEGG pathway enrichment analysis. It is well known that aberrant regulation of inflammation is a prominent driver in the progression of NAFLD, and persistent inflammation can lead NAFLD to evolve into cirrhosis, HCC, and end-stage liver disease . Abnormavia experimental verification in NAFLD model rats. These findings provide novel insights into the regulatory role of YLZD in the treatment of NAFLD and hold promise for herb-based complementary and alternative therapy.In summary, the main active components, candidate targets and related signaling pathways of YLZD for NAFLD treatment were obtained through network pharmacology. We found that YLZD might exert a therapeutic effect on NAFLD by inhibiting the TNF signaling pathway


Chinese herbal medicine (CHM) is characterized by “multi- compounds, multi-targets and multi-pathway”, which has advanced benefits for preventing and treating complex diseases, but there still exists unsolved issues, mainly include unclear material basis and underlying mechanism of prescription. Integrated pharmacology is a hot cross research area based on system biology, mathematics and poly-pharmacology. It can systematically and comprehensively investigate the therapeutic reaction of compounds or drugs on pathogenic genes network, and is especially suitable for the study of complex CHM systems. Intracerebral Hemorrhage (ICH) is one of the main causes of death among Chinese residents, which is characterized with high mortality and high disability rate. In recent years, the treatment of ICH by CHM has been deeply researched. Xue Fu Zhu Yu Decoction (XFZYD), one of the commonly used prescriptions in treating ICH at clinic level, has not been clear about its mechanism.vitro experiments. The molecular mechanism of XFZYD in treating ICH was deduced based on CCG and their targets.Here, we established a strategy, which based on compounds-targets, pathogenetic genes, network analysis and node importance calculation. Using this strategy, the core compounds group (CCG) of XFZYD was predicted and validated by in The results show that the CCG with 43 compounds predicted by this model is highly consistent with the corresponding Compound-Target (C-T) network in terms of gene coverage, enriched pathway coverage and accumulated contribution of key nodes at 89.49%, 88.72% and 90.11%, respectively, which confirmed the reliability and accuracy of the effective compound group optimization and mechanism speculation strategy proposed by us.Our strategy of optimizing the effective compound groups and inferring the mechanism provides a strategic reference for explaining the optimization and inferring the molecular mechanism of prescriptions in treating complex diseases of CHM. ICH refers to the hemorrhage caused by spontaneous and non-traumatic cerebral vascular rupture, which is often located in the deep brain tissues such as basal nucleus, putamen, and thalamus, etc. It has the characteristics of acute onset, rapid change of disease condition, high mortality and disability rate, and is more common in middle-aged and elderly people. According to the statistical results, the prevalence rate of hemorrhagic stroke in China is 406.16/100,000, and the incidence rate is 26.34/100,000 [In recent years, reports about treating ICH with CHM have gradually increased. For example, Buyang Huanwu Decoction can alleviate brain edema after ICH, reverse blood–brain barrier (BBB) damage and reduce nerve function damage . Di DangRehmannia glutinosa (Gaertn.) (15 g), Bupleurum chinense DC (5 g), Glycyrrhiza uralensis Fisch (5 g), Citrus aurantium L (10 g). Platycodon grandiflorus (Jacq.) A.DC (7.5 g), Achyranthes bidentata Blume(15 g), Prunus alleghaniensis Porter (20 g), Carthamus tinctorius (15 g), Ligusticum chuanxiong S.H.Qiu (7.25 g), Paeonia veitchii Lynch (10 g), Angelica sinensis (Oliv.) (15 g). Among these herbs, Prunus alleghaniensis Porter breaks blood and moistens dryness, while Carthamus tinctorius L promotes blood circulation and removes blood stasis to relieve pain. Paeonia veitchii Lynch and Ligusticum chuanxiong S.H.Qiu help the monarch to dispel blood stasis and promote blood circulation. Achyranthes bidentata Blume can enhance blood circulation, clear channels, remove blood stasis and relieve pain, and lead blood downward. Rehmannia glutinosa (Gaertn.) and Angelica sinensis (Oliv.) Diels are usually used to nourish blood and nourish yin, clear heat and promote blood circulation; Platycodon grandiflorus (Jacq.) A.DC. and Citrus aurantium L can be used to disperse lung, relieve sore throat, eliminate phlegm and discharge pus; Bupleurum chinense DC can be used to liver stagnation and qi stagnation, chest and rib pain, Glycyrrhiza uralensis Fisch has the efficacy of relieving pain and harmonizing various drugs. XFZYD composed of these herbs has the effects of eliminating edema and improving local circulation, so it is widely used in the treatment of ICH. Although it has been reported, the mechanism is still unclear. How to find the key compounds to deduce the potential mechanism is the key step to understand the treatment of ICH by XFZYD.The prescription contains 11 herbs: At present, systems pharmacology is a product of interdisciplinary research, including chemical and structural biology, bioinformatics, computer technology and mathematics, and also covers a large number of experimental disciplines including research technologies from cells, tissues to organs. In the recent researches, systems pharmacology is widely used to explore the hidden mechanisms of CHM prescriptions on complex diseases. Such as, Wang Chun et al. built a contribution index model to analyze the molecular mechanism of Zhi-zhu Wan in treating Functional Dyspepsia , Wang KeSystems pharmacology of CHM provides novel ideas and perspectives for the study of complex CHM system. By using systems pharmacology technology, the theories and methods of studying the active substances and combinations of CHM, identifying the targets of pharmacodynamics compounds, and the relationship between pharmacodynamic substances and diseases were studied, so as to establish the pharmacodynamics of CHM and the basic theory of CHM based on systematic level. For example, Liu et al. used network pharmacology to prove the action of Jinshui Huanxian Formula on Idiopathic Pulmonary Fibrosis . He et avitro experiments, which would provide methodological reference and advice for the systematic analysis of CHM in treating other complex diseases.In this study, a new systems pharmacology model was designed for capturing the key compounds and deducing the potential mechanism of XFZYD in treating ICH. This model is based on novel node importance calculation method, and integrates compound monomer structure and target information, protein–protein interaction (PPI) network response mode and pathogenic genes reported in literature, and systematically explores the key effective compounds in treating ICH with XFZYD. The mechanism of CCG was deduced by using the target protein response score(TPRS) model. The reliability of the model is further confirmed by the verification of functional coverage and The PPI data was extracted from seven published database, include STRING , BioGRIDAll compounds of XFZYD were derived from three public herb medical data sources, TCMSP database , TCM intThree ADME-related modules  were used to screen biologically active compounds. OB stands for the radio of the oral constant-dose ingredient or drug that can be delivered to the circulation system . Higher Three public databases, Similarity Ensemble Approach (SEA) , HitPick(s) represents the genes which contains nodes;  represents the length of a shortest path between nodes s and w; The dist is equal to infinite if C(s) ≠ C(w), and it makes methods of this category cannot be applied to networks with disconnected genes. For calculating the importance of each node in the network, we constructed a node importance calculation method (BCR), in which, n represent the number of nodes in the network; s, v and t represent nodes in the network; V represents the collection of nodes within the network; |V| represents the number of nodes; There are n nodes in the network. After being quantized, BR was sorted from small to large, and was represented by a new variable G.The new variable P represented the nodes in the network. Each P responds to its unique G.BCR represented the important nodes selected form all nodes in the network. N represented natural number.p-values of 0.05 [p-values of 0.05 [For analyzing the targets of XFZYD at the functional level, Gene Ontology (GO) analysis were performed by clusterProfiler package of R software with  of 0.05 , Kyoto E of 0.05 . Graphs Acacetin, quercetin, luteolin (≥ 98% purity by HPLC) was obtained from Jiangsu Yongjian Biotech Co., Ltd . Fetal bovine serum (FBS) and Dulbecco’s modifified Eagle’s medium (DMEM) were purchased from Gibco . The mouse hippocampal HT22 cells were obtained from CHI SCIENTIFIC . Hypoxic bags were purchased from Mitsubishi Gas Chemical Company, Inc (Japanese). Cell Counting Kit-8 (CCK-8) was purchased from Dojindo Laboratories (Japanese).2. Hypoxic bags were used to perform OGD model according to the method which had been reported [HT22 cells were cultured in DMEM with 10% FBS, and incubated at 37 °C under 5% COreported .4 cells/well) were plated in 96-well plates for 24 h, then the cells were exposed to OGD model with hypoxia for 12 h, followed by treatment with 40, 80, 120, 160 and 200 μM acacetin, quercetin, and luteolin, respectively. The acacetin, quercetin, and luteolin were dissolved in DMSO to reach a final concentration and further diluted to different concentrations using medium. After 24 h of incubation, 10 μL of CCK8 was added and incubated for a further 4 h. The plate reader was utilized to detect the absorbance at 450 nm.HT22 cells  mutation can cause typical pathological changes of AD and perivascular amyloid deposition . Fu et aChemical identification is the critical step to clarify the material basis and action mechanism of prescription. In this study, the information of specific chemical compounds of XFZYD Chinese herbal medicines was obtained from literatures Table . The resA total of 716 compounds were found in XFZYD through systematic search of the compounds in the published database of 11 herbs. Each CHM prescription contains hundreds of compounds, only a few compounds possess suitable pharmacokinetic and pharmacology dynamics properties. In the present work, three published ADME models, OB, Caco-2 and DL, were used to pick out the active compounds. After ADME screening, due to its high concentration and high biological activity, some compounds which did not meet the three screening criteria were also kept as the active compounds. Finally, 179 active compounds were selected from 716 compounds  has the greatest number of targets, followed by MOL007022 (degree = 114), MOL000131 (degree = 111), MOL000098 (degree = 107) and MOL004996 (Degree = 106)), MOL001689 (degree = 104), MOL003896 , MOL004985 , MOL002203 . Most of these compounds are related to ICH apoptosis, inflammation and immune-related pathways. Parveen et al. found that ACER2 was involved in sphingomyelin metabolism, which could catalyze ceramide hydrolysis to produce sphingosine, and sphingosine was further phosphorylated to produce sphingosine monophosphate . ACER2 cIn the C-T network, the average target degree of different targets is 7.83. Most of the top 20 targets including MAPT, ALOX5AP, ESR2, ODC1, and ESR1, etc. which have the higher weights in the C-T network, are associated with immunity and inflammation and have been confirmed to be related to the pathogenesis of ICH, and may indicate the potential mechanism of XFZYD on ICH. For example, Markoula et al. found that ESR2 was significantly related to the risk of stroke . ESR2 anThe main targets of the active compounds are often involved in HIF-1 signaling pathway (hsa04066), VEGF signaling pathway (hsa04370), MAPK signaling pathway (hsa04010), Alzheimer disease (hsa05010) and PI3K-Akt signaling pathway . VEGF signaling pathway is very important for cell proliferation and growth. According to literatures, VEGF stimulates the expression level of the PI3K-Akt and MAPK-ERK proteins in the cerebral cortex of rats through phosphate Akt and activate MAPK-regulated ERK pathways, thus reducing the lesion volume of cerebral infarction and promoting angiogenesis in rats with cerebral infarction . StudiesUsing weighted pathogenic gene–gene interactions and C-T network to construct compounds-targets-pathogenic genes (C-T-P) network. This network is consisting 2,932 nodes and 48,980 edges. Degree of each node can be used to evaluate the importance of nodes in the network. The node with the degree which is greater than the average degree of all nodes in the network is considered to play a key role in the network structure and can be regarded as a central node. According to this rule, the transmitted nodes and their edges are retained in the C-T-P network, and defined as the effective space. 445 effective proteins were identified from the effective space. There are three kinds of effective proteins in the effective space. The first category of making a table is the direct interaction between pathogenic genes and compounds targets. We defined this category as the basic effective compounds. The second category we defined as the targets specific interactions, which contain the interactions, only existed between the targets of compounds. The third category we defined as the pathogenic genes specific interactions, which mean the interactions linked the different pathogenic genes.In order to further prove the reliability and accuracy of our model, we compare our proposed node importance calculation method with other commonly used node importance calculation methods, including degree, betweenness centrality, and clustering coefficient. We used our model and these models to obtain respective coefficient proteins and used these effective proteins to perform pathway and GO enrichment analysis, respectively, and then check the percentages of effective protein-enriched pathways and GO terms in intervention pathways and intervention GO terms, respectively. The higher the percentage, the higher the reliability and accuracy of the model. Results show that the percentage of effective protein enriched pathways found in our model in intervention pathway and intervention GO term is significantly higher than that in the degree model, betweenness centrality model, and clustering coefficient model. These results show that compared with other node importance models, our model has higher accuracy and better functional coverage Fig. .Fig. 2Cop < 0.05), while pathogenic genes can be enriched to 195 pathways (p < 0.05). It was found that effective protein enriched pathways covered 88.21% of pathogenic gene enriched pathways  and 195 pathogenic gene enrichment pathways (p < 0.05). It was found that CCG targeted enrichment pathway covered 88.72% of pathogenic gene enrichment pathways , the production of molecular mediators involved in inflammatory responses , and inflammatory responses to antigen stimulation . These results confirmed that XFZYT could treat ICH by reducing inflammatory reaction, reducing oxidative stress and inhibiting apoptosis.ICH-related pathways can be decomposed into functional modules such as apoptosis, inflammation, and oxidative stress. Increasing evidences confirmed that the PI3K-Akt signaling pathway (hsa04151), JAK-STAT Signaling pathway (hsa04630), NF-kappa B signaling pathway (hsa04064), and IL-17 signaling pathway (hsa04657) respond to these functional modules. For example, PI3K-Akt signaling pathway (hsa04151) has been reported to be involved in the inhibition of apoptosis, cell proliferation, and expression of inflammatory cytokines. JAK-STAT signaling pathway (hsa04630) is involved in pathophysiological changes in damaged peripheral brain tissue after cerebral hemorrhage, leading to brain tissue edema. NF-kappa B signaling pathway (hsa04064) is a general name of a family of transcription factors that function as dimers to regulate genes of immunity, inflammation and cell survival. IL-17 signaling pathway (hsa04657), a subset of cytokines composed of IL-17A-F, plays an important role in acute and chronic inflammatory responses. For exploring the mechanism of XFZYT in the treatment of ICH at the system level, we constructed a comprehensive signaling pathway using two important molecular pathways  markedly increased the cell viability level by 16.00%, 18.10%, 20.73% and 12.42% (Fig. In the process of treating complex diseases, Chinese medicine prescriptions usually exert their functional effects according to compatibility principles. Chinese medicinal prescriptions composed of different herbal medicines often contain hundreds of chemical compounds. Some of these chemicals have a synergistic therapeutic effect, while some may have an antagonistic therapeutic effect. How to figure out the synergistic or antagonistic effects of these chemical compounds and optimize the core therapeutic chemical compounds is the main purpose of prescription optimization.In addition, in the process of treating diseases, the action form of prescriptions in TCM is relatively complex, and usually acts in the form of multi-compounds, multi-targets and multi-pathways, which constitutes a multi-dimensional regulatory network. How to find the core functional compound groups in these regulatory networks and analyze the mechanism is one of the key ways for us to understand the mechanism of prescriptions in the treatment of complex diseases.Node importance is one of the most important ways to depict the network. In this research, we designed a new node importance calculation method and validated the accuracy and reliability. Based on this new node importance calculation method, optimization space was constructed. Potential effective proteins were screened out based on the optimization space, and then the key constituent groups corresponding to the effective proteins were obtained using the reverse programming algorithm. We analyzed the enrichment pathways of these CCG and found that the target enrichment pathways of these CCG accounted for 90.11% of the enrichment pathways of pathogenic genes. These results fully proved the accuracy and reliability of our computational model for screening key compound groups based on the optimization space. Our proposed screening strategy consists of two levels of design. The first level of design is to construct the optimization space based on the node importance calculation method, and verify that the information of disease-related genes will be preserved as much as possible in this step as the core protein or functional protein in the optimization space. In the second step, potential CCG are reversely screened based on the core proteins or functional proteins, and further pathway enrichment analysis is performed on the functional compound group for verification. The results of this dual model and verification fully demonstrate the reliability of our integrated analysis model, and provide methodological reference for other prescription optimization in TCM.


Sanguisorba officinalis has been shown to have anti-inflammatory, anti-bacterial, antioxidant, and anti-tumor effects, while its molecular mechanism against CRC remains unclear. The aim of this study is to explore the underlying mechanism of S. officinalis against CRC cell lines using network pharmacology and transcriptomic sequencing methods.Colorectal cancer (CRC) is the most common malignant cancer worldwide. S. officinalis against CRC were screened from databases. Secondly, the networks of ingredient–target, ingredient–target–CRC and protein–protein interaction were constructed. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of network pharmacology and transcriptomic sequencing were performed. Finally, the effect of S. officinalis against CRC was verified by in vitro experiments.Firstly, the active ingredients and potential targets of S. officinalis by network pharmacology. PI3K–Akt, HIF-1, and MAPK signaling pathways related to cell proliferation were regulated by S. officinalis in enrichment analyses and transcriptomic sequencing. In vitro, S. officinalis inhibited the proliferation and migration of CRC cells and arrested the cell cycle at the G0–G1 phase. The western blot showed that S. officinalis downregulated the expression of p-PI3K, p-Akt, HIF-1A, VEGFA, cyclin D1, c-Myc, and p-MAPK proteins in CRC cells.In total, 14 active ingredients and 273 potential targets against CRC were identified in in vitro studies, have been successfully applied to study the underlying mechanism of S. officinalis against CRC cells. Our results demonstrate that S. officinalis suppresses the proliferation, survival, and migration of CRC cells through regulating the PI3K–Akt, HIF-1, and MAPK signaling pathways.In conclusion, network pharmacology and transcriptomic sequencing analyses, in combination with  Colorectal cancer (CRC) is a kind of cancer in the alimentary canal which ranks as the third in morbidity and mortality in the world . In 2020Sanguisorba officinalis (known as Di Yu in Chinese), a member of Rosaceae family, exhibits a wide range of pharmacological activities, such as hemostatic, anti-inflammatory, anti-allergy, anti-bacterial, antioxidant, hypoglycemic, neuroprotective, and anticancer effects  by activating a reactive oxygen species-mediated and mitochondria caspase-dependent apoptotic pathway , consisting of various active ingredients, has been studied against cancer considering its unique advantages of good efficacy and minimal side effects . Sanguis effects , 5. The pathways . We have pathway .S. officinalis against CRC is still lacking. Network pharmacology analyzes the links among drugs, targets, and diseases to demonstrate the synergistic effects of TCM on multiple targets and pathways , Traditional Chinese Medicine Integrated Database , and references (https://pubchem.ncbi.nlm.nih.gov/).The potential chemical ingredients in ferences , 10. Thehttp://www.swisstargetprediction.ch/). The UniProt database (https://www.uniprot.org/) was applied to change the protein targets’ names to their corresponding gene symbols. The GeneCards database (https://www.genecards.org/), Online Mendelian Inheritance in Man database , DrugBank online database (https://go.drugbank.com/) and Therapeutic Target Database  were searched to identify potential targets related to CRC by using keywords such as “colorectal cancer”, “colon carcinoma”, or “rectum carcinoma”.The putative protein targets of active ingredients were accessed from TCMSP and Swiss Target Prediction database . The nodes represent ingredients or targets, and the edges reflect the interaction between nodes. The bioinformatics (http://www.bioinformatics.com.cn/) platform was performed to draw a Venn diagram of common target numbers of ingredient–disease. Cytoscape3.7.1 software was applied to construct the active ingredient–CRC-target network. The degree value represents the significance of the target.The active ingredient–target network was constructed by Cytoscape, version 3.7.1 software (http://string-db.org), with a correlation degree greater than 0.4 as the confidence score. Then, the nodes and score information were combined into the Cytoscape3.7.1 software for analysis. Degree, betweenness centrality, and closeness centrality were three parameters used to assess the topological features of nodes in the network. Among them, the size and the color of nodes both reflect the degree values.The protein–protein interaction (PPI) network of targets of the active ingredients against CRC were conducted by STRING software (http://metascape.org/) was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of common targets. The results of GO and KEGG pathway enrichment analyses were visualized on the bioinformatics platform. Cytoscape3.7.1 software was used to construct the target–pathway network. The nodes represent targets or signaling pathways, and the edges present the interaction between nodes.The Metascape platform -2,5-diphenyltetrazolium bromide (MTT) was purchased from MP . Dulbecco’s modified Eagle’s medium (DMEM), penicillin–streptomycin, phosphate-buffered saline (PBS), fetal bovine serum (FBS), Pierce BCA protein assay kit, and Super Signal™ West Pico Chemiluminescent Substrate kit were obtained from Thermo Fisher Scientific . Calcein/propidium iodide (PI) kit, RIPA buffer, crystal violet, 4% paraformaldehyde, and PI/RNase kit were from Beyotime Biotechnology . Trizol buffer was purchased from Invitrogen . The primary antibodies against cyclin D1, c-Myc, PI3K, P-PI3K, Akt, P-Akt, HIF-1A, VEGFA, MAPK, and P-MAPK were purchased from Affinity , and β-actin and GAPDH were from Cell Signaling Technology . The secondary antibodies were obtained from Millipore Corporation .S. officinalis  was authenticated by Prof. Depo Yang (Sun Yat-sen University). The dried rhizome of S. officinalis was boiled and refluxed with ultrapure water for 1 h at each time . After filtration, the extracted solution was evaporated, then lyophilized to dried powder, and stored at -20°C before use.2 at 37°C.RKO and HCT-15 cells were used in the following experiments, which were kindly gifted by Professor Huangliang Liu from Sixth Affiliated Hospital, Sun Yat-Sen University, China. All cell lines were cultured in DMEM containing 10% FBS and 1% penicillin–streptomycin under a humidified incubator with 5% COS. officinalis extract (31.25 to 500 μg/ml) for 24 or 48 h. Then, 20 μl of 5 mg/ml MTT buffer was added to each well and incubated for 4 h at 37°C. The absorbance at 570 nm was measured on a microplate reader .Cell proliferation of CRC cells was determined by MTT assay. The cells were seeded in 96-well plates . After 24 h of incubation, the cells were treated with different concentrations of 3 cells per well, incubated for 24 h, and then exposed to various concentrations of S. officinalis extract  for 48 h. Then, 100 μl of calcein/PI solution was added to each well for 30 min of incubation at 37°C in the dark. Then, the cells were observed and photographed under a fluorescence microscope .CRC cells were seeded into 96-well plates at a density of 5 × 105 CRC cells were seeded into each well of 6-well plates and exposed to different concentrations of S. officinalis extract  for 48 h. Then, the cells were washed twice by PBS, fixed in 4% paraformaldehyde for 20 min, and stained with crystal violet.A total of 1 ×10S. officinalis extract , the cells were harvested and incubated with PI/RNase solution . Then, cellular samples were immediately analyzed on flow cytometry , see the details in a previous study . After 0, 12, and 24 h of incubation, the wound areas were observed under a light microscope . The wound areas were measured by ImageJ software and normalized with the control group.Cells were incubated in 6-well plates with 100% confluence and then scratched using a sterile pipette tip on the cell monolayer. The cells were washed 3 times with PBS, and S. officinalis extract (100 μg/ml), and total RNA was extracted according to the manual’s instruction and quantified using a Nano Drop and Agilent 2100 bioanalyzer . The mRNA library was constructed on a BGISEG500 platform according to the BGI protocol (https://pan.genomics.cn/ucdisk/s/BFFr6j).The transcriptomics analysis was accomplished by our collaborator, Beijing Genomics Institute . The cells were incubated in 6-well plates and exposed to https://pan.genomics.cn/ucdisk/s/RzEr6b), and differently expressed genes (DEGs) were screened . Then, GO and KEGG enrichment analyses of DEGs were performed by Phyper. The terms and pathways are significant when Q ≤0.05.The sequencing data was analyzed according to the BGI protocol , see the details in a previous study .The obtained data were expressed as mean ± SD (n = 3). The statistical analysis was performed by t-test by GraphPad Prism 8.0 software, and p <0.05 was considered to be significantly different.S. officinalis. After using ADME screening parameters (OB >30% and DL >0.18), a total of 14 candidate compounds were identified as active ingredients of S. officinalis  and 903 edges was constructed , 120 cellular component (CC), and 259 molecular function (MF) terms in total. The top 15 significantly enriched terms of BP, CC, and MF are shown in S. officinalis might regulate cell proliferation, apoptosis, or metastasis through these cellular terms. The KEGG analysis results showed that S. officinalis significantly influenced the pathways in cancer, such as PI3K–Akt, HIF-1, TNF, IL-17, Ras signaling pathways, etc.  values of S. officinalis at 24 h in RKO and HCT-15 cells were 214.8 and 192.2 μg/ml, respectively. The IC50 values of S. officinalis in RKO and HCT-15 cells at 48 h were 108.2 and 121.2 μg/ml, respectively  and increased the percentage of dead cells (red fluorescence) in a dose-dependent manner after S. officinalis treatment for 48 h  between the S. officinalis-treated and control groups (etc. (MF), and extracellular space and region, cytoplasm and transcription factor complex, etc. (CC) , and p-MAPK proteins were determined by western blot. The data showed that the expression of p-PI3K, p-Akt, HIF-1A, VEGFA, and p-MAPK proteins was remarkably downregulated in a dose-dependent manner after 24 h of S. officinalis treatment -catechin, which were active compounds in S. officinalis with good anticancer activity. In terms of mechanism, we verified the downstream targets affected by the PI3K–Akt pathway, such as HIF-1α, VEGFA, and cyclin D1 proteins related to cell metastasis and cell cycle, revealing the molecular mechanism of S. officinalis in a more comprehensive way.Our findings are similar to those recently reported in hepatocellular carcinoma . Our stuS. officinalis which were not found in UPLC-MS should be identified by a more optimal method. Secondly, there are other targets  or pathways (Ras and P53) which may play critical roles in the anti-CRC effect of S. officinalis. Further studies should be performed to explore the effect of S. officinalis on CRC cells. In addition, there is a lack of in vivo study on S. officinalis. Despite the limitations, this study provides a scientific basis for S. officinalis as a potential therapeutic agent for CRC treatment. This study supports the combination of network pharmacology, transcriptomics, and experimental verification to understand the mechanism of actions of Chinese herbal medicines.These are some limitations to this study. Firstly, the ingredients of in vitro studies, have been successfully applied to study the underlying mechanism of S. officinalis against CRC cells. Our results demonstrate that S. officinalis suppresses the proliferation, survival, and migration of CRC cells through regulating the PI3K–Akt, HIF-1, and MAPK signaling pathways.In conclusion, network pharmacology and transcriptomic sequencing analysis, in combination with https://www.ncbi.nlm.nih.gov/bioproject/, PRJNA796145.The original contributions presented in the study are publicly available. This data can be found here: in vitro experiments. LO studied the network pharmacology analysis. ZF and YZ performed data processing. GL and YY participated in the revision of the manuscript. MY designed the overall study and prepared the manuscript. All authors contributed to the article and approved the submitted version.WZ designed and performed the overall experiments and prepared the manuscript. SS and CP participated in the This work was supported by the National Natural Science Foundation of China (number 81973552) and the Natural Science Foundation of Guangdong Province (2022A1515012056).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.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.


We integrated the key VA-biological target-signaling pathway-As-related dermatitis networks for identifying core drug targets and interaction pathways associated with VA action. The network pharmacology data indicated that VA may possess potential activity for treating As-related dermatitis through the effective regulation of core target genes. An enrichment analysis in biological processes further revealed multiple immunoregulation-associated functions, including interferon-gamma production and negative regulation of T-cell activation and production of molecular mediator of immune response. An enrichment analysis in molecular pathways mainly uncovered multiple biological signaling, including natural killer cell mediated cytotoxicity, autophagy, apoptosis, necroptosis, platelet activation involved in cell fate, and immunity regulations. Molecular docking study was used to identify docked well core target proteins with VA, including Jun, tumor protein p53 (TP53), mitogen-activated protein kinase-3 (MAPK3), MAPK1, and MAPK14. In conclusion, the potential use of VA may suppress the inflammatory stress and enhance the immunity against As-related dermatitis. In the future, VA might be useful in the treatment of dermatitis associated with As through multi-targets and multi-pathways in clinical practice.Exposure to arsenic (As), an inorganic poison, may lead to skin lesions, including dermatitis. Vitamin A (VA), a fat-soluble vitamin essential for mucous membrane integrity, plays a key role in skin protection. Although the beneficial actions of VA are known, the anti-As-related dermatitis effects of VA action remain unclear. Hence, in this study, we aimed to interpret and identify the core target genes and therapeutic mechanisms of VA action in the treatment of As-related dermatitis through integrated  In addition, colorized nodes were denoted as target proteins, and interlaced edges were denoted as target gene-gene interactions  were identified as multiple key signaling pathways, comprising mitophagy-animal, Rap1 signaling pathway, shigellosis, natural killer-cell mediated cytotoxicity, cAMP signaling pathway, autophagy-animal, Ras signaling pathway, phospholipase D signaling pathway, antifolate resistance, asthma, apoptosis-multiple species, necroptosis, Alzheimer’s disease, circadian entrainment, hematopoietic cell lineage, progesterone-mediated oocyte maturation, insulin resistance, type II diabetes mellitus, autoimmune thyroid disease, and platelet activation. The bubble charts of KEGG pathway enrichments are shown in A total of 151 Encyclopedia of Genes and Genomes (KEGG) molecular pathways enriched , TP53 (PDB ID: 6MXY), MAPK3 (PDB ID: 6GES), MAPK1 (PDB ID: 6G9M), and MAPK14 (PDB ID: 6SFO) were screened out for docking determination. In The metabolic pathways were enriched with Arginine biosynthesis and Arginine and proline metabolism, mainly characterized by the NOS2 signaling pathway .in silico findings suggested that VA structurally docked well with some core target proteins, including JUN, TP53, MAPK3, MAPK1, and MAPK14. JUN can directly interact with specific target DNA sequences to regulate gene expression (TP53 is a well-known anti-apoptotic gene. In the event of functional loss, TP53-induced systemic inflammation occurs and evolves over time (in vitro therapeutic effectiveness and adverse actions in vivo prior to future clinical validation.Repurposing an existing drug can be achieved through bioinformatics analysis, such as network pharmacology approach . Identifpression . JUN is pression . In addipression . TP53 isver time . Clinicaver time . MAPKs, ver time . In partver time . TherebyThis study provides a potent, integrative pharmacological approach for the effective identification of repurposing VA as a potential therapy for As-related dermatitis. Using this bioinformatics methodology, we can reduce the translational period in clinical trials, resulting in rapid therapy strategy for the use of VA in As-related dermatitis.The original contributions presented in the study are included in the article/CG and BY contributed to the conception, design of the manuscript, drafted the manuscript, and revised the manuscript. QQ, LQ, RX, and SP contributed to the acquisition, analysis, and interpretation of data in the manuscript. All authors agreed to be accountable for all aspects of work ensuring integrity and accuracy.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.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.


Head and neck squamous cell carcinoma (HNSCC) represents one of the most malignant and heterogeneous tumors, and the patients have low 5-year survival. Traditional Chinese medicine (TCM) has been demonstrated as an effective complementary and/or alternative therapy for advanced malignancies including HNSCC. It has been noted that several herbs that are used for preparing Yinchen Wuling San (YWLS) have anti-tumor activities, whereas their mechanisms of action remain elusive. In this study, network pharmacology and molecular docking studies were employed to explore the underlying mechanisms of action of YWLS against HNSCC. The 58 active ingredients from six herbs used for YWLS and their 506 potential targets were screened from the traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) and SwissTargetPrediction database. A total of 2,173 targets associated with HNSCC were mainly identified from the DisGeNET and GeneCards databases. An active components-targets-disease network was constructed in the Cytoscape. Top 20 hub targets, such as AKT1, EGFR, TNF, ESR1, SRC, HSP90AA1, MAPK3, ERBB2, and CCND1, were identified by a degree in the protein–protein interaction (PPI) network. Gene functional enrichment analysis showed that PI3K-AKT, MAPK, Ras, TNF, and EGFR were the main signaling pathways of YWLS in treating HNSCC. There were 48 intersected targets such as EGFR, AKT1, and TNF that were associated with patients’ outcomes by the univariate Cox analysis, and most of them had increased expression in the tumor as compared to normal tissues. The area under curves of receiver operating characteristic indicated their diagnostic potential. Inhibition of these survival-related targets and/or combination with EGFR or AKT inhibitors were promising therapeutic options in HNSCC. The partial active components of YWLS exhibited good binding with the hub targets, and ADME analysis further evaluated the drug-likeness of the active components. These compounds and targets identified in this study might provide novel treatment strategies for HNSCC patients, and the subsequent work is essential to verify the underlying mechanisms of YWLS against HNSCC. Head and neck cancer (HNC) is one of the most common and aggressive human malignancies worldwide and is also one of the most lethal causes of death . HNC is Poria cocos (PC) and Atractylodes macrocephala koidz (AMK) (Artemisiae scopariae herba (ASH) and Wuling San have anti-tumor efficacy , Poria cocos , Alisma orientale , Atractylodes macrocephala koidz , Polyporus umbellatus , and Cinnamomi ramulus  (Most patients with head and neck squamous cell carcinoma (HNSCC) are diagnosed at advanced stages and have a 40–50% 5-year survival rate when receiving standard therapies . The surdz (AMK) . In addiefficacy . For exaefficacy . Yinchen Guizhi) . Thus, tNetwork pharmacology as a novel analytical approach has been widely used to predict pharmacological action and potential mechanisms of TCM through integrating drug targets, diseases, and their targets into biomolecular networks  Sun et . In thishttp://lsp.nwu.edu.cn/tcmsp.php) (http://www.swisstargetprediction.ch/) (https://www.uniprot.org/) was used to standardize gene names and target information.YWLS is a common traditional Chinese prescription that includes six herbs: ASH, PC, AO, AMK, CR, and PU. These herbs contain a variety of compounds with the effects of anti-inflammatory, antioxidant, immune regulation, and anti-tumor. ASH has been demonstrated to induce KB epithelioid cell apoptosis through elevated mitochondrial stress and caspase activation mediated by the MAPK-stimulated signaling pathway . The actmsp.php)  with parion.ch/)  since itThe DisGeNET  and GeneTo investigate potential interactions among intersecting targets of YWLS and HNSCC, the PPI network was obtained using the STRING database  and visuTo interrogate the potential functions of these intersecting targets of YWLS and HNSCC, gene functional enrichment analysis including biological process (BP), molecular function (MF), and cellular components (CC) was performed using the clusterProfiler package . The patIn order to illustrate the regulatory network of all active compounds of YWLS and their corresponding targets and HNSCC-related targets, the compound–disease regulatory network was generated by Perl and visualized using the Cytoscape software .https://portal.gdc.cancer.gov/). The expression matrix of intersecting targets in each HNSCC patient was extracted. The expression levels of these genes between normal and cancerous tissues were compared using Wilcoxon tests and illustrated as a heatmap by the pheatmap R package. To determine their prognostic utility, univariate Cox regression analysis was employed to screen overall survival (OS)-related genes.Gene expression profiles measured by Fragments Per Kilobase of transcript per Million mapped reads (Log2 (FPKM+1)) and clinical information of HNSCC patients were acquired from The Cancer Genome Atlas (TCGA) database   was usedhttps://www.rcsb.org), and their available 3D protein conformations with resolutions less than 3Å as determined by X-ray crystal diffraction were used. The structures of the selected active ingredients of YWLS were downloaded from the PubChem database (SDF.files). SybylX-2.0 software was used to perform energy minimization and optimize geometry in the Tripos force field. SybylX-2.0 software was applied for molecular docking studies. We processed proteins as follows: removing the co-crystalized ligand and water molecules from the structure, adding the H atoms, and fixing the terminal. The Surflex-Dock (SFXC) docking mode was applied, and the obtained total scores usually indicate the binding force.The overlapped genes of the top 20 hub targets and the genes that have a prognostic effect were searched in the RCSB PDB database   .A total of 58 active ingredients of YWLS with OB ≥ 30% and DL ≥ 0.18 were acquired in the TCMSP database . There wThe targets of these active ingredients in YWLS were predicted in the SwissTargetPrediction database, and 506 potential targets were obtained after the duplicate deletion . Among tThe keywords “head and neck carcinoma” and “head and neck squamous cell carcinoma” were used to search in DisGeNET and GeneCards databases. A total of 2,173 potential pathological targets related to HNSCC were acquired . The relThe ingredient-target-disease interaction network was established using Perl and constructed via Cytoscape , and 242The PPI analysis was performed to investigate the potential interactions of 212 targets. Four significant modules, AKT1, EGFR, TNF, and CYP3A4, were identified in the whole network . The AKTTo investigate the biological functions of 212 potential targets, GO terms analysis showed that they were mainly involved in the biological processes of response to oxidative and chemical stress, peptidyl-serine/tyrosine modification, and protein kinase B signaling pathway. Membrane raft and microdomain, focal adhesion and cell-substrate junction, and protein kinase complex were the main cellular components. Protein kinase activity, growth factor binding activity, and nuclear receptor and ligand-activated transcription factor activity are the top molecular functions . The patTo determine the clinical relevance of 212 intersecting targets in HNSCC patients, the univariate Cox regression analysis showed that 48 targets were significantly correlated with patients’ outcomes . Among tThe principal component analysis (PCA) showed that the expression pattern of 212 intersecting genes in the normal tissues was distinct from those in tumor samples . As illuMolecular docking is a powerful structure-based approach to characterize the binding behavior of small molecules in the target proteins and elucidate fundamental interactions at the atomic level . We founThe pharmacokinetics, drug-likeness, and medical chemistry features of 10 active compounds were predicted using SwissADME and were compared to reference clinical drugs for HNSCC patients including methotrexate, hydroxycarbamide, and erlotinib. Gastrointestinal absorption, blood–brain barrier permeability, uptake, and drug-likeness of most compounds were comparable to the current clinical drugs. The five liver drug enzymes in HNC is the sixth most prevalent human cancer worldwide, which originates from the head and neck sites including the lips, pharynx, larynx, and tongue . Rare spin vitro and in vivo experiments’ validation are necessary. Polyporusterone E which is isolated from PU belongs to cytotoxic steroids. Pharmacological studies showed that steroids exert anti-tumor effects mainly by preventing cancer cell proliferation and inducing cancer cell apoptosis -ergosta-6-en-3beta,5alpha,6beta-triol, polyporusterone E, genkwanin, and polyporenic acid C were the top 5 components that have relatively high degrees, which were 228, 119, 113, 108, and 105, respectively. This suggests that they might be the main active ingredients for treating HNSCC. Cerevisterol and -ergosta-6-en-3beta,5alpha,6beta-triol belong to steroids. Studies have found that steroids have anti-inflammatory, immunomodulatory , and antpoptosis . Polyporpoptosis . As one poptosis . Polyporpoptosis . These dWe intersected the potential targets of active ingredients of YWLS and HNSCC-related genes. Four modules named AKT1, EGFR, TNF, and CYP3A4, respectively, were identified in the PPI network of the overlapped genes. Additionally, AKT1, EGFR, and TNF are the top 3 hub genes ranked by degrees. AKT1 is one of the serine-threonine protein kinase families and is a downstream target of phosphoinositide 3-kinase (PI3K). It was a key regulator in various cell processes including cell proliferation, survival, and angiogenesis in normal and tumor cells . Activatin vitro and in vivo cytotoxicity in HNSCC (Increased EGFR expression, amplification, and low frequencies of single nucleotide variations/indels have been observed in HNSCC . The ovein HNSCC . This miin HNSCC . In addiin HNSCC . For exain HNSCC . TNF-α cin HNSCC . It was The KEGG pathway analysis indicated that these 212 targets were mainly enriched in PI3K-AKT, MAPK, RAS, EGFR tyrosine kinase inhibitor resistance, ErbB, PD-L1 expression, PD-1 checkpoint pathway in cancer, and TNF signaling pathways. Previous reports demonstrated that activation of these pathways is highly correlated with cell proliferation, survival, and metastasis in HNC carcinogenesis  Marquar and drugThe molecular docking study was used to validate the interactions between eight survival-related hub targets and their possible active components of YWLS. The compounds showed good binding scores with the corresponding targets such as AKT1, EGFR, PPARG, ESR1, and SRC. The ADME analysis was conducted to further assess the drug potentials of these compounds for HNSCC patients. Partial components exhibited comparable pharmacological characteristics with current clinical agents. These data indicated that these compounds might be used as potential therapeutic drugs to treat HNSCC.In summary, the potential therapeutic targets of active ingredients of YWLS for treating HNSCC were predicted by the network pharmacology studies, and molecular docking predicted the interactions between the active compounds and the related targets, and the drug-likeness properties of these compounds were further evaluated by the ADME analysis. The underlying mechanism of YWLS against HNSCC might be associated with PI3K-AKT, MAPK, and EGFR signaling pathways. These compounds might provide novel treatment strategies for HNSCC themselves or in combination with current molecular targeted therapies, and further verification by subsequent experiments is imperative.


Cydonia oblonga Mill. (COM), mature fruit of genus Rosaceae, is consumed as a kind of traditional Chinese medicinal herb. Previous studies have shown that the components in COM extract have antioxidant, anti-inflammatory, blood pressure-lowering, blood lipid-lowering, antithrombotic, and other biological activities. However, the quality markers (Q-markers) of atherosclerosis (AS) have not been elucidated. The Q-marker is based on the five core principles of traceability, transferability, specificity, measurability, validity, and prescription dispensing. In this study, the quality markers of quince were investigated by applying the ultraperformance liquid chromatography-time-of-flight mass spectrometry (UHPLC/Q-TOF-MS/MS) method and network pharmacology method to highlight the three core elements which are, respectively, traceability transmission, measurability, and validity. At the first step, 72 components were identified by applying the ultraperformance liquid chromatography-time-of-flight mass spectrometry (UHPLC/Q-TOF-MS/MS) method. In the next step, 46 candidate components of COM anti-AS were obtained by network pharmacology, and then, 27 active components were filtered with the molecular docking assay. Finally, the 27 active components were intersected with 10 active components obtained by mass transfer and traceable quality markers. Four anti-AS Q-markers of COM were identified, including caffeic acid, chlorogenic acid, ellagic acid, and vanillic acid, which provided a reference for the quality control of quince. The methods and strategies can also be applied to other traditional Chinese medicines and their compound preparations, providing new ideas on the quantitative evaluation and identification of quality markers. Cydonia oblonga Mill. (COM), a traditional Chinese medicine (TCM) with Xinjiang characteristics, is effective in reducing blood pressure, lowering blood fat, supplementing blood volume and improving brain health, relieving cough, resolving phlegm, and appetizing, as well as relieving diarrhea symptoms, etc. It is mostly used in treating cardiovascular diseases and gastrointestinal diseases and is most efficient in relieving cough and diarrhea [diarrhea , 2.COM is rich in various active components which present potential medical therapeutical value. The domestic research data on the chemical composition analysis of Xinjiang COM is limited. Parida Abuliz et al. demonstrated that Xinjiang COM fruits contain polysaccharides, phenolic acids, flavonoids, alkaloids, tannins, organic acids, volatile oils, triterpenoids, and other components by mutual validation of two methods: systematic pretesting and special pretesting . Our preThe quality markers (Q-markers) in a TCM are the core concept of quality evaluation and quality control of Chinese medicine, proposed by Academician Liu Chang-xiao, based on the five core principles of traceability and transferability, specificity, measurability, efficacy, and prescription dispensing –10. The in vivo study, which is very similar to the principles of the holistic and dynamic nature of TCM. UHPLC Q-TOF-MS/MS has been widely used for the multicomponent analysis of drugs for its sharp specificity, fast speed, and strong selectivity [The non-targeted metabolism of TCM components emphasizes the ectivity . Therefoμm 2.1∗100 mm; Waters).COM was purchased from Yecheng County, Kashgar, Xinjiang Uyghur Autonomous Region, and was identified by Professor Parida Abuliz. The voucher specimens were stored at the Center Laboratory of Xinjiang Medical University, China. Chromatographic grade acetonitrile, methanol, and formic acid were purchased from Merck . The Rutin standard sample is purchased from Shanghai Yuanye Biotechnology Co., Ltd. 95% ethanol is purchased from Tianjin Fengchuan Chemical Reagent Technology Co., Ltd. AB-8 macroporous adsorption resin is purchased from Cangzhou Baoen Adsorption Materials Technology Co., Ltd. The ultraviolet-visible spectrophotometer is purchased from Shimadzu, Japan; Milli-Q Integral from Millipore, USA; UHPLC ; high-resolution mass spectrometry ; centrifuge ; analytical balance ; grinder ; ultrasonic apparatus ; chromatographic column ; take a certain amount of solution and centrifuge in 13000 rpm for 10 min; take out supernatant and filter with a 0.22 μm∗2.1∗100 mm). The mobile phase was 0.1% formic acid water (A)-acetonitrile (B) with gradient elution , flow rate of 0.4 μl/min, column temperature of 40°C, injection volume of 5 μl, and full wavelength scanning of 200-600 nm.The column was Waters UHPLC BEH C18 : 55 Psi, auxiliary pressure: 55 Psi, curtain pressure: 35 Psi, temperature: 550°C, and spray voltage: 5500 V (positive ion mode) or -4000 V (negative ion mode). In each data acquisition cycle, the strongest and more than 100 molecular ions were selected to collect the corresponding secondary mass spectrometry data. The original mass spectrometry was imported by Progenesis QI software. The retention time correction, peak recognition, extraction, and integration were carried out by MAPS software. The peaks of MS/MS data were identified by the Biotree self-built secondary mass spectrometry database and the corresponding pyrolysis law matching method.P < 0.05 was considered statistically significant.SPSS 21.0 statistical software was used for data processing. Data are expressed as the mean ± standard deviation. Analysis of variance was used to compare the orthogonal experiment between groups; http://www.tcmip.cn/TCMIP/index.php). The above COM components were used as the limiting words. According to the molecular fingerprint feature extraction method of MACCS (molecular ACCess system) and the similarity measurement method defined by the Tanimoto coefficient, the similarity scores of the chemical components of traditional Chinese medicine and the drugs listed in FDA were scored. When the score was ≥0.8, the desired targets were extracted to avoid the screening of components with high recognition; the targets of COM components were searched by TCMSP (http://lsp.nwu.edu.cn/tcmsp.php) and SwissTargetPrediction (http://www.swisstargetprediction.ch/). Due to the problems of irregular naming of drug targets retrieved from the three databases, this paper uses the UniProtKB search function in the protein synthesis database  to correct all the retrieved targets to their official names by inputting the name of the target and limiting the species to “human.”The COM chemical components obtained by UHPLC-Q-TOF-MS/MS analysis were input into the database of traditional Chinese medicine components of Integrative Pharmacology-based TCMIP V2.0 (http://www.disgenet.org) (with “UMLS CUI: C0004153” as the limiting word) and GeneCards database (http://www.genecards.org/) were searched, and the Comparative Toxicogenomics Database (CTD) (http://ctdbase.org/) (with “marker/mechanism and therapeutic” as the limiting word) was combined to retrieve and screen known AS disease targets and delete repeated targets, to obtain known targets in the pathogenesis of AS. The AS disease target was mapped to the action target of COM active components to obtain the action target of COM against AS.The term “atherosclerosis” was used in the TCMIP V2.0 disease-related molecular library. The DisGeNET database (http://genemania.org/), species selection “Homo sapiens,” and “minimum required interaction score” ≥ 0.999, the rest were used to analyze the interaction between each target by default parameters. In the construction of protein-protein interaction (PPI), delete isolated nodes to get the initial network. The intersection of “Node1” and “Node2” was obtained, and the intersection target was a target with strong interaction among proteins, which was used as a candidate target for COM treatment of AS. The candidate targets of COM anti-AS and the COM components acting on this candidate were used to construct a visualized association integration network of “Candidate Component-C Candidate Target, CC-CT” by Cytoscape software. The common target network of COM-AS was calculated by the Cytoscape plug-in Network Analyzer, and the target was the main target of COM in the treatment of AS. The possible quality markers of COM intervention AS in Xinjiang COM were analyzed and excavated, and the preliminary screening of quality markers of COM intervention AS in Xinjiang was completed.In String (https://david.ncifcrf.gov/) with the error detection rate (FDR) as screening criteria. GO gene functions include biological process (BP), molecular function (MF), and cellular component (CC) analysis. The smaller the FDR value, the higher the enrichment of GO and KEGG. Ranked by FDR values, the top-down pathway is the key pathway. Finally, the “Candidate Compound-Candidate Target-Candidate Pathway, CC-CT-CP” network diagram was constructed by Cytoscape software, and the targets and their active components involved in the key signaling pathways were visually analyzed by degree to screen the main components.“Effectiveness” is the core element of quality marker determination. Because the control of the effectiveness of TCM is the fundamental purpose of quality control, the discovery of disease-related chemical components of traditional Chinese medicine as candidate quality markers from the network diagram of “traditional Chinese medicine-composition-target-pathway” by network pharmacology is the key idea for effective efficacy research. Gene function (GO) and pathway enrichment analysis of COM anti-AS candidate targets were performed using DAVID  plug-in to simplify the network with the median ≥ 2 of topological properties such as betweenness centrality (BC), closeness centrality (CC), eigenvector centrality (EC), degree centrality (DC), local average connectivity-based method (LAC), and network centrality (NC) of initial network nodes as screening criteria, and the obtained targets were used as potential targets for COM in the treatment of AS.http://vina.scripps.edu/index.html). COM components were confirmed by PubChem (https://www.ncbi.nlm.nih.gov) and Chemical Book database . Files in mol format are saved through the Chemical Book database. The structural components were loaded into the AutoDock Tools 1.5.6 program, and atomic charges were added to distribute atomic types. All flexible bonds were rotated by default as docking ligands. AutoTools software was used to pretreat the protein crystal structure of the core targets, remove the redundant protein chains and ligands, remove water molecules by hydrogenation, and calculate the Gasteiger charge as the receptor for molecular docking. Then, Autodock Vina software was used for docking small molecules with proteins. Finally, we complete the conformation analysis and mapping.The preliminary screening components of the integrated pharmacology platform were sorted out through molecular docking technology. The main targets obtained under “2.5.3” and “2.6” and the potential targets obtained by the above network topology parameters such as BC, CC, EC, DC, LAC, and NC are mapped to the intersection core targets as receptors. In the “CC-CT” and “CC-CT-CP” networks obtained under “2.5.3” and “2.6,” respectively, the components screened by degree were intersected, and the main components of the intersection were used as ligands for molecular docking. Receptors and ligands are docked via Autodock Vina  is used to determine the matching degree between COM components and core targets. When the ligand and receptor conformation is stable, the lower the energy, the greater the possibility of interaction. In general, BE ≤ −4.25 kcal/mol indicates that the active ingredient has certain binding energy with the target, BE ≤ −5.00 kcal/mol indicates that the active ingredient has stable binding energy with the target, and BE ≤ −7.00 kcal/mol indicates that the active ingredient has strong binding energy. In this paper, BE ≤ −5.00 kcal/mol was selected as the standard, and the components with good docking with the main target of COM in the treatment of AS were finally obtained as the Q-marker of COM in the treatment of AS. Finally, the Q-marker was crossed with the Q-marker obtained under “2.5.3” and “2.6,” and the common Q-marker was used as the main quality marker for COM intervention in AS.Total ion chromatogram (TIC) refers to the figure of the total time or scanning times of all ions after the intensity of all ions which is added within the selected mass range. All the compounds detected by UHPLC-Q-TOF-MS/MS were retrieved from the Biotree DB database and compared with the references. The chemical components observed in the extract were analyzed by integrating the first-order and second-order mass spectra under (+) ESI and (−) ESI modes. A total of 72 compounds were identified, including 39 compounds in negative ion mode and 33 compounds in positive ion mode. The total ion flow diagram of positive and negative ions and the list of identification components are shown in Figures “minimum required interaction score” ≥ 0.999 as criteria, and 46 candidate targets were screened. The interaction between the targets is shown in The above 72 components collected by TCMIP, TCMSP, and SwissTargetPrediction database were obtained, respectively, 243, 133, and 1017 targets. After deleting repetitive targets, 1202 targets were obtained. The TCMIP, CTD, DiSGeNET, and GeneCards databases were used to search for 65, 62, 2044, and 4329 disease targets, respectively, related to the pathogenesis of AS, and 737 common targets were obtained by crossing with 1202 COM targets, as shown in Nodes represent proteins, and edges represent the correlation of functions. The more lines represent the greater correlation. In addition, the degree of COM-AS common target network was calculated by the Cytoscape plug-in network analyzer with a degree as the screening condition. The top 10 targets with higher degrees include estrogen receptor , epidermal growth factor receptor , cell division protein kinase 2 , glycogen synthase kinase-3 beta , protooncogene tyrosine-protein kinase SRC , peroxisome proliferator-activated receptor gamma , cell division control protein 2 homolog , insulin-like growth factor 1 receptor , insulin receptor , and integrin alpha-L . It can be the main target of COM for the treatment of AS.The initial screening of the 64 components of COM was performed according to the screening criterion of degree ≥ 6, and the obtained components were used as the initial screening results for the COM intervention AS quality markers. As shown in The results of GO gene function analysis of 46 candidate targets by DAVID showed that a total of 426 items were obtained, including 301 BP, 80 MF, and 45 CC, and the top 20 results were sorted according to the corrected FDR pairs as shown in The top 10 biological functions induced by the 64 COM components include enzyme binding, kinase activity, protein binding, transcription factor binding, insulin receptor substrate binding, nuclear hormone receptor binding, chromatin binding, identical protein binding, protein phosphatase binding, and protein heterodimerization activity . The topForty-six candidate targets were imported into the DAVID for analysis of KEGG signaling pathways, and the pathways were further screened according to FDR size, with the FDR value indicating that the smaller the value in the enrichment analysis, the higher the enrichment significance . A totalTo further determine the quality markers identified for COM treatment of AS, a component-target-pathway network map was constructed by Cytoscape software, which contains 127 nodes  and 618 edges. The edges between components (red quadrangles), candidate targets (yellow circles), and signaling pathways (green diamonds) represent interactions. The larger the size of the circles, the larger the degrees of the components, targets, and pathways represented, the more important is the network.The top 10 targets with high degrees include EGFR (degree = 45), ESR1 (degree = 39), GSK3B (degree = 37), phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform, PI3-kinase subunit alpha, PI3K-alpha, PI3Kalpha, PtdIns-3-kinase subunit alpha , CDK2 (degree = 34), SRC (degree = 32), phosphatidylinositol 3-kinase regulatory subunit alpha , IGF1R (degree = 28), INSR (degree = 27), and cell division control protein 2 homolog . It can be a candidate target for COM treatment of AS.The 63 components of COM were screened according to the screening criterion of degree ≥ 5, and the obtained components were used as rescreening results for the COM intervention AS quality markers. As shown in in vivo, respectively. The optimal lgP value for a drug is −1 < lgP < 2 for better absorption [P values of −1 < lgP < 2 and ADMET absorption level > 0 were used as criteria for screening to obtain vanillic acid, chlorogenic acid, cryptochlorogenic acid, isolariciresinol-4-O-Î′-D-glucopyranoside, ellagic acid, luteolin-4′-O-glucoside, isochlorogenic acid B, sophoricoside, caffeic acid, and eucommin A, which can be used as quality markers for COM intervention in AS.The common physicochemical properties of the above components such as oil-water partition coefficients  were summarized in conjunction with the TCMIP V2.0 chemical composition database, and the specific parameters are shown in sorption . In thisThe 46 candidate targets were simplified by using the CytoNCA plug-in for the initial network nodes with the median ≥ 2 of the topological properties of BC, CC, EC, DC, LAC, NC, etc. The screening criteria and the 31 potential targets obtained as potential targets for COM treatment of AS are shown in the In the “CC-CT” and “CC-CT-CP” networks obtained under “3.2” and “3.3,” respectively, network, the 46 candidate components obtained according to degree screening were intersected with 49 candidate components, which can be seen in The 27 core components that dovetailed well with the 10 components obtained based on “3.4” were intersected to obtain 4 components as the main Q-markers for COM for AS, which are shown in π interactions with PHE404 (3.0 Å) to bind to ESR1  to form hydrogen bonds and  Figures . Caffeic Figures . Caffeic Figures .π interaction with adjacent residues LEU349, GLU353, ALA350, LEU346, LEU525, HIS524, GLY521, MET421, TRP383, LEU384, MET388, LEU391, ARG394, ILE424, and PHE425. Caffeic acid binds to ESR1 by forming hydrophobic interactions with PHE404 (3.0 Å) , resulting in ESR1 binding  is a natural phenolic compound belonging to the family of polyphenolic phenolic acids with a hydroxybenzoic acid structure that is most abundant in fruits, vegetables, and beverages and has biological activities such as antioxidant, anti-inflammatory, antibacterial, and cytostatic . CA moduActivation of the epidermal growth factor receptor (EGFR) is closely linked to the physiology and pathophysiology of the cardiovascular system, and inhibition of EGFR activity is emerging as a potential therapeutic strategy for the treatment of diseases such as hypertension, cardiac hypertrophy, renal fibrosis, and abdominal aortic aneurysms . StudiesEstrogen receptor alpha (ESR1) is an important gene transcriptional regulator known to mediate the effects of estrogen. Alterations in ESR1 expression and its function affect the atheroprotective effects of circulating estrogen in insulinogenic atherosclerosis . ESR1 plCycle protein-dependent kinase 1 (CDK1) is one of the important kinases that drive cell entry into mitosis and is involved in cell cycle M phase, G2/M transition point, and G1 phase activities, as well as being a key protein for cell cycle passage through G1/S and G2/M phase restriction points. CDK1 inhibits microtubule-associated protein hydrolysis and regulates centrosome segregation and also promotes spindle assembly and centrosome maturation. Its overactivation, abnormal regulation of mitotic entry and progression, and deranged centrosome segregation accelerate cell proliferation . CDK2 isγ), Liver X Receptor α (LXRα), ATP Binding Cassette Subfamily A Member 1 (ABCA1), and ATP Binding Cassette Subfamily G Member 1 (ABCG1) as well as the transcriptional activity of PPARγ, resulting in an effective reduction of ApoE−/− development of atherosclerosis in mice and promote cholesterol efflux from RAW264.7 macrophages [Chlorogenic acid (CGA) is a phenolic compound composed of CA and quinic acid. CGA increased the mRNA levels of peroxisome proliferator-activated receptor gamma , CCATT/enhancer-binding protein α (C/EBPα), sterol regulatory element-binding protein-1c (SREBP-1c), acetyl coenzyme A carboxylase (ACC), and fatty acid synthase (FAS) lipid accumulation and expression levels [Ellagic acid (EA) a polyphenolic compound extracted from pomegranate fruit extract reduced the lipid accumulation and expression of key adipogenic genes peroxisome proliferator-activated receptor n levels . It alson levels . Wang etn levels . Howevern levels . It can κB activation, proinflammatory cytokine production, oxidative stress, and acetylcholinesterase [Vanillic acid (VA) is a phenolic compound in the oxidized form of vanillin, and VA has analgesic, antioxidant and anti-inflammatory, and neuroprotective effects on nuclear factor-esterase , 40. Stuesterase . AccordiIn summary, this study targeted three core elements of traceability and deliverability, measurability, and efficacy, and applied the UHPLC-Q-TOF-MS/MS assay and network pharmacology methods to study the quality markers of COM, and finally identified that caffeic acid, chlorogenic acid, ellagic acid, and vanillic acid were identified as potential Q-markers for COM anti-AS, providing a reference for COM quality control. The method and strategy can also be extended and applied to compound preparation of other traditional Chinese medicines, as well as to provide new ideas for the quantitative evaluation and identification of quality markers.