Abstract

Purpose

   Few studies have evaluated the mechanisms of the specific efficacy of
   Panax notoginseng-Radix Salviae couplet medicines (PN-RS) in the
   treatment of atherosclerosis (AS). This study aims to explore the
   potential bioactive ingredients and molecular mechanisms of PN-RS in
   the treatment of AS.

Materials and Methods

   C57BL/6J mice were fed a common diet as the control group. ApoE^−/−
   mice were randomly divided into the model, PN-RS treatment (0.75
   mgPN+3.75 mgRS/g/day via gavage), and positive drug groups
   (rosuvastatin, 1.25 mg/kg/day via gavage). After two months of drugs
   intervention, H&E and Masson staining, the serum lipid concentration
   and atherosclerotic index were conducted to verify the PN-RS efficacy.
   Network pharmacology analysis was carried out to identify the pathways
   and targets of PN-RS. The signaling pathway-related targets and
   cytokines were tested via enzyme-linked immunosorbent assay (ELISA),
   Western blotting and real-time polymerase chain reaction (PCR).

Results

   Network pharmacology analysis identified the JAK2-STAT3 signaling
   pathway as a key pathway through which PN-RS exerts its therapeutic
   effects. Results from animal experiments demonstrated that PN-RS
   significantly reduced the atherosclerotic lesion area and decreased
   serum levels of total cholesterol (TC), triglycerides (TG), low-density
   lipoprotein cholesterol (LDL-C), and atherogenic index (AI).
   Mechanistic studies further revealed that PN-RS inhibited the
   JAK2-STAT3 signaling pathway and reduced the concentrations of
   pro-inflammatory cytokines, including tumor necrosis factor-alpha
   (TNF-α), interleukin-6 (IL-6), vascular endothelial growth factor
   (VEGF), and monocyte chemoattractant protein-1 (MCP-1).

Conclusion

   These findings suggest that PN-RS could be a promising treatment for
   atherosclerosis, applicable across diverse populations. Future research
   should investigate its efficacy in various demographic groups and in
   combination with other therapies.

   Keywords: traditional Chinese medicine, atherosclerosis, lipid
   metabolism, inflammatory reaction, network pharmacology

Introduction

   Cardiovascular disease (CVD) is a major barrier to sustainable human
   development due to its high morbidity and mortality
   worldwide.[40]^1^,[41]^2 Atherosclerosis (AS) is a chronic inflammatory
   artery disease characterized by the accumulation of lipids and fibrous
   elements in the large arteries, which is the primary cause of CVD and
   stroke.[42]^3 As a slowly progressing disease, AS remains the leading
   cause of mortality worldwide despite its declining incidence in some
   countries. Although the pathogenesis of AS is not clear, according to
   different causative factors, there are several recognized hypotheses,
   such as lipid infiltration, endothelial injury, oxidative stress, and
   inflammatory response.[43]^4 Plasma lipoproteins are complexes of
   lipids with proteins being transported through the circulation, the
   levels of which constitute the major risk factors for AS. In the early
   stages of AS, hyperlipidemia can lead to endothelial damage and induce
   cytokine release and adhesion molecule expression. Then, macrophages
   move to sites of injury, where they promote the secretion of
   inflammatory factors, plaque formation and even rupture. Therefore, the
   therapeutic strategy should be focused on intervention in dyslipidemia,
   reducing the inflammatory response and protecting endothelial function.
   As the rate-limiting enzyme in cholesterol synthesis, statins are
   widely used to treat AS by inhibiting 3-hydroxy-3-methyl glutaryl
   coenzyme A (HMG-CoA) reductase to effectively lower low-density
   lipoprotein (LDL) levels,[44]^5 and statins can inhibit high-fat
   diet-induced lipid metabolism disorders in rats by inhibiting
   bacteroides reduction and improving metabolism.[45]^6 However, statins
   have significant side effects, such as muscle pain and weakness.[46]^7
   In recent years, traditional Chinese medicine (TCM) has been widely
   used to treat AS.[47]^8 Rauf et al[48]^9 pointed out that combination
   therapy with TCM regulates blood lipids has great prospects.

   Panax notoginseng (PN) (SAN QI), a perennial herb, is the dried root
   and rhizome of the Araliaceae plant Panax notoginseng (Burk). F.H.Chen.
   It was first recorded in the Compendium of Materia Medica (Ben Cao Gang
   Mu) compiled by Li Shizhen in the Ming dynasty and has been used for
   more than 400 years. PN is often used to promote blood circulation and
   dispel blood stasis in traditional applications. Accumulating evidence
   suggests that the main chemical ingredients of PN, including saponins,
   flavonoids, volatile oils and polysaccharides, have good treatment
   effects on AS and other CVDs. Panax notoginseng saponin R1 mediates its
   anti-atherogenic effects through the multiple targeting effects of
   anti-inflammatory, oxidative stress, lipid metabolism, and miRNA
   expression.[49]^10^,[50]^11 Therefore, the pharmacological actions of
   PN are mainly manifested in its effect on circulatory systems and
   cerebrovascular systems.

   Radix Salviae (RS) (DAN SHEN), the root and rhizome of Salvia
   miltiorrhiza Bge., a plant of the labiate family, has been widely used
   to treat various diseases, such as cardiovascular and immune system
   diseases.[51]^12 Clinical studies show that RS has anti-inflammatory
   effects because of the tanshinones and rich phenolic acids in the stems
   and leaves, and more evidence shows that RS can enhance recovery after
   myocardial ischemia and decrease adhesion molecule
   expression.[52]^13^,[53]^14 In addition, the main pharmacological
   effects of RS include protecting vascular endothelial cells, lowering
   blood lipids, improving microcirculation and exerting antitumor
   effects.[54]^15 Panax notoginseng and Radix Salviae have been widely
   used clinically in the treatment of CVD. However, few studies have
   evaluated the mechanisms of the specific efficacy of Panax
   notoginseng-Radix Salviae couplet medicines (PN-RS) in the treatment of
   AS.

   Network pharmacology was proposed by Andrew L Hopkins in 2007. It is a
   systematic research method of study that uses omics and network
   visualization techniques to reveal complex biological network
   relationships among drugs, active ingredients, diseases, and targets
   and then to predict and analyze the action targets and mechanisms of
   drugs.[55]^16 Given the complexity of the composition and function,
   network pharmacology is able to evaluate the multichannel regulation of
   signaling pathways and is particularly suited to elucidating the
   intrinsic link between bioactive ingredients of Chinese herbals and
   disease treatment targets.[56]^17 Therefore, the network pharmacology
   approach has important guiding significance to clarify the
   pharmacological mechanisms of Chinese herbs.[57]^18

   In this study, we first conducted animal experiments to verify the
   therapeutic effect of PN-RS on AS. Then, we used network pharmacology
   methods to predict the potential targets and signal transduction
   pathways of PN-RS treatment in AS and further verified the mechanism of
   PN-RS through experiments, which provides a basis for subsequent
   pharmacological experimental research and clinical transformation
   research.

Materials and Methods

Animal Experiments

Drug Preparation

   PN and RS were manufactured by Beijing Kangrentang Pharmaceutical Co.,
   Ltd (Beijing, China), and authenticated by Hospital of Shandong
   University of Traditional Chinese Medicine (Jinan, Shandong, China).

Animals and Groups

   Male C57BL/6 mice and ApoE^−/− mice (both 8 weeks old) under specific
   pathogen-free (SPF) laboratory conditions were purchased from Beijing
   Weitonglihua Experimental Animal Technology Co., Ltd (Animal
   Qualification License No. SCXK (Beijing) 2021–0006). Animal experiments
   were approved by Animal Ethics Committee of Affiliated Hospital of
   Shandong University of Traditional Chinese Medicine (Approval number
   2021–66) and carried out according to the Guide for the Care and Use of
   Laboratory Animals published by the National Institutes of Health. The
   animals were tested after one week of adaptive feeding under SPF
   laboratory conditions. ApoE^−/− mice were fed continuously for 12 weeks
   with a high-fat diet including 0.15% cholesterol and 21% pork fat, and
   then randomly divided into model group, which received an equal amount
   of distilled water by gavage every day; the PN-RS treatment group, 0.75
   mgPN+3.75 mgRS/g/day; and the positive drug group, rosuvastatin, 1.25
   mg/kg/day. C57BL/6J mice were fed with common diet as control group.
   All animals received treatment continuously by gavage for eight weeks.

Specimen Collection

   Blood samples were drawn from the orbital cavity. Serum was centrifuged
   at 1300×g for 10 min at 4°C. After the thoracic cavity and abdominal
   cavity opened, the myocardial tissue and aortic root were removed and
   quickly fixed in 4% paraformaldehyde (PFA). Parts of the aorta samples
   were stored at −80°C for subsequent experiments.

Oil Red O Staining

   After removal of the outside connecting tissue and fat, the entire
   aorta was opened longitudinally from the aortic root to the renal
   artery and fixed with 4% PFA solution for 24 h. Then, the entire aorta
   was stained with 0.5% Oil-red O working solution at 37°C in a
   biochemical incubator. After 1 h of staining, the entire aorta was
   immersed in 70% ethanol for destaining. The stained aorta was scanned,
   and the total morphometric lesion area was evaluated with En face
   method by using Image-Pro Plus 6.0 software.

Hematoxylin-Eosin and Masson Staining

   The aortic arch tissue was sliced into 5 µm serial paraffin sections.
   After deparaffinization and rehydration, the sections of the aortic
   arch were stained with hematoxylin and eosin (H&E) and Masson staining
   to determine aortic lipid plaque areas and collagen fiber content,
   respectively. Images were collected under a microscope and measured by
   Image-Pro Plus 6.0 software. After H&E staining and photography, the
   ratio of plaque area and lumen area was calculated by Image-Pro Plus
   6.0. Relative plaque area = plaque area/lumen area × 100%. Section
   collagen fibers are colored blue after Masson staining. The total area
   of positive staining and the area of the intima, media were determined
   by Image-Pro Plus to calculate the percentage of vascular collagen
   fiber area.

Determination of the Serum Lipids

   Serum total cholesterol (TC), triglyceride (TG), high-density
   lipoprotein cholesterol (HDL-C), and low-density lipoprotein
   cholesterol (LDL-C) levels in mice were determined by a Chemray 240
   Automatic Biochemistry Analyzer (Shenzhen Ledu Life Technology,
   Shenzhen, China). The blood lipid levels were determined by calculating
   the AS index (AI) (AI = (TC-HDL-C)/HDL-C).

Network Pharmacology Analysis

   Based on the theory of network pharmacology, this topic studied the
   public resource database and applied for exemption to the Ethics
   Committee of the Affiliated Hospital of Shandong University of
   Traditional Chinese Medicine. According to the ethics committee
   requirements, exemption application is allowed for the collection or
   research of previously archived data, documents, records, pathological
   specimens, or diagnostic specimens, and these resources are public
   resources. After the approval of the Ethics Committee of the Affiliated
   Hospital of Shandong University of Traditional Chinese Medicine, the
   project passed the application for exemption.

Collection of BioactiveiIngredients and Targets of PN and RS

   We used the TCMSP database[58]^19
   ([59]https://old.tcmsp-e.com/tcmsp.php) and the ETCM database[60]^20
   ([61]http://www.tcmip.cn/ETCM/) to collect bioactive ingredients of PN
   and RS. The screening conditions were oral bioavailability (OB) ≥ 30%
   and drug-likeness (DL) ≥ 0.18. In addition, we reviewed the pertinent
   literature to supplement the bioactive ingredients. The targets of the
   ingredients were searched through the TCMSP database, ETCM database and
   SwissTargetPrediction database
   ([62]http://www.swisstargetprediction.ch/). After screening, the
   UniProt ID of the protein target was then searched through the UniProt
   database ([63]https://www.uniprot.org) with species defined as Homo
   sapiens. Finally, the obtained potential targets were collated, and a
   diagram was constructed after removing duplicate targets.

Collection of Targets of AS

   The targets of AS were collected through the DisGeNET database[64]^21
   ([65]https://www.disgenet.org/), GeneCards database[66]^22
   ([67]https://www.genecards.org/) and DrugBank database[68]^23
   ([69]https://go.drugbank.com/). We screened out targets of AS using a
   relevance score greater than the median as the criterion. The
   intersection targets between drugs and diseases were visualized by
   BioVenn[70]^24 ([71]http://www.biovenn.nl).

Construction and Analysis of Ingredient and Target Network

   Via Cytoscape software (v3.9.1),[72]^25 network-built editing and
   analysis software, drugs and ingredients were used to construct a
   relationship network. Then, ingredients and intersection targets were
   uploaded to Cytoscape software to generate a network and analyzed by
   the Network Analyzer plug-in of Cytoscape. In the network, the degree
   value of a node reflected the importance of ingredients or targets.

Construction of the Protein-Protein Interaction Network (PPI) and Screening
of Core Clusters and Key Targets

   We imported the intersection targets into the STRING database
   ([73]https://string-db.org/) with a minimum needed interaction score
   ≥0.900 to obtain the protein interaction relationship. Then, the
   results were uploaded into Cytoscape software to construct the
   interaction network. Under the following filter conditions: degree
   cutoff 2 and k-core 2, the MCODE plug-in of Cytoscape was applied for
   cluster analysis to select the core cluster with the closest
   relationship in the network. Then, the CytoHubba plug-in was used to
   carry out network topology analysis for the PPI network and to screen
   the key targets based on MCC.

GO and Kyoto Encyclopedia of Genes and Genomes (KEGG) Enrichment Analyses

   Enrichment analysis of GO function for the intersection targets was
   performed using the Metascape database ([74]https://Metascape.org/)
   according to a P value cutoff < 0.01, and enrichment analysis of KEGG
   pathways was performed using the R language clusterprofiler computer
   package. Via tools on the Bioinformatics website, the significant terms
   and pathways were used to generate diagrams.

Mechanism Research

   According to the above animal experiments and network pharmacology
   studies, we further explored the mechanism of PN-RS in AS. To further
   validate the combination effect of PN and RS, we added a single-drug
   treatment group. ApoE^−/− mice were randomly divided into four groups:
   the model group, PN treatment group (0.75 mgPN/g/day), RS treatment
   group (3.75 mgRS/g/day) and PN-RS treatment group (0.75 mgPN+3.75
   mgRS/g/day). C57BL/6J mice were used as the control group.

Enzyme-Linked Immunosorbent Assay

   According to the manufacturer’s instructions, the concentrations of
   vascular endothelial growth factor (VEGF), monocyte chemotactic
   protein-1 (MCP-1), tumor necrosis factor-α (TNF-α) and interleukin-1
   (IL-6) were examined by enzyme-linked immunosorbent assay (ELISA) kits
   (Wuhan Servicebio Technology Co., Ltd., Wuhan, China).

Protein Extraction and Western Blotting

   The levels of Janus kinase 2 (JAK2) and signal transduction and
   activator of transcription 3 (STAT3) in mice were detected by Western
   blot. Tissue homogenate was prepared using phenylmethanesulfonyl
   fluoride (PMSF) lysis buffer. The protein concentration was determined
   using a bicinchoninic acid (BCA) kit (Dalian Meilun Biotechnology Co.,
   Ltd., Dalian, China). The isolated protein (30 μg) was separated by 10%
   sodium dodecyl sulfate‒polyacrylamide gel electrophoresis (SDS‒PAGE)
   and transferred onto polyvinylidene fluoride (PVDF) membranes. After
   blocking with TBST containing 5% skim milk for 1 h, the membranes were
   incubated overnight at 4°C with specific primary antibodies. Then, the
   membranes were washed and incubated with secondary antibodies for 1.5 h
   at room temperature. Finally, the blot signal was detected by using ECL
   (Millipore Corporation, USA) with β-actin as the internal reference,
   and data were analyzed with Image-Pro Plus 6.0 software.

RNA Extraction and Quantitative Real-Time PCR Analysis

   Following the kit instructions, total RNA was isolated from mouse
   tissue using an RNA extraction kit (Omega, USA) under RNase-free
   conditions. Then, SweScript All-in-One First-Strand cDNA Synthesis
   SuperMix for qPCR (Wuhan Servicebio Technology Co., Ltd., Wuhan, China)
   was used to reverse transcribe total RNA (2 μg) samples into cDNA.
   qRT‒PCR was performed with 2×SYBR Green qPCR Master Mix (Wuhan
   Servicebio Technology Co., Ltd., Wuhan, China). The sequences of
   gene-specific primers were synthesized as follows:

   JAK2: CTTATTCATGGGAATGTGTGTGC (F), ATCCAGAGCACTCAGGGGCTTA (R);

   Stat3: TGCGGAGAAGCATTGTGAGTG (F), TCTTAATTTGTTGGCGGGTCT (R);

   GAPDH: CCTCGTCCCGTAGACAAAATG (F), TGAGGTCAATGAAGGGGTCGT (R).

Statistical Analysis

   We used GraphPad Prism 9.0.0 software (San Diego, CA, USA) to analyze
   and visualize the data. Statistical differences among more than two
   groups were calculated using analysis of variance (ANOVA) followed by
   Tukey’s post hoc test. A p value <0.05 was considered to indicate
   statistical significance.

Results

PN-RS Significantly Attenuated Atherosclerotic Pathology

   We evaluated the inhibitory effect of PN-RS on the AS lesion process by
   studying aortic pathological section changes in animals. Oil red O
   staining showed that the atherosclerotic plaque-positive area in the
   model group was significantly higher than that in the control group
   ([75]Figure 1A). After PN-RS treatment, the size of the atherosclerotic
   plaque in the whole aorta was significantly reduced, and the treatment
   effect of PN-RS was similar to that of rosuvastatin ([76]Figure 1A).

Figure 1.

   [77]Figure 1
   [78]Open in a new tab

   PN-RS influences the development of atherosclerosis. (A) Oil red O
   staining of the entire aorta and quantification of the En face lesion
   area of the entire aorta. (B) H&E staining and quantification of aortic
   plaque area. (C) Masson staining and quantification of collagen fibril
   content. The data are expressed as the mean ± SD, n = 6 for each group.
   *P<0.05, **P<0.01, ****P<0.0001, vs Model group.

   H&E and Masson staining can be used to assess the severity of AS. H&E
   staining showed that the arterial vascular structure of the control
   group was regular, with smooth intima and uniform media thickness, and
   intact lumen. In the model group, the vascular intima was thickened,
   and the significant formation of atherosclerotic plaques with a large
   number of foam cells and cholesterol crystals was observed. The
   relative plaque area was significantly higher than that in the control
   group ([79]Figure 1B). Masson staining showed that the arterial
   collagen tissue of the control group was evenly distributed. The
   arterial intima and media collagen fibers were significantly increased
   in the model group. Compared to the control group, the arterial
   collagen fiber area percentage increased significantly ([80]Figure 1C).
   However, the relative plaque area and the percentage of the collagen
   fiber area were significantly decreased after PN-RS and rosuvastatin
   treatment ([81]Figure 1B and [82]C).

PN-RS Significantly Reduced Serum Lipid Levels

   We assessed the effect of PN-RS on AS lipid metabolism by measuring
   serum lipid levels in mice. The levels of TC, TG, LDL-C, and AI were
   significantly higher while HDL-C was decreased in ApoE^−/− mice
   compared to the control group. However, PN-RS improved the lipid index
   to varying degrees, and the effect was similar to that of rosuvastatin
   treatment. These results suggested that PN-RS significantly regulated
   dyslipidemia ([83]Figure 2A–E).

Figure 2.

   [84]Figure 2
   [85]Open in a new tab

   PN-RS affects lipids in serum. (A) Serum levels of TG, (B) serum levels
   of TC, (C) serum levels of HDL-C, (D) serum levels of LDL-C in mice,
   (E) AS index (AI). The data are expressed as the mean ± SD, n = 6 for
   each group (A–E). ***P<0.001, ****P<0.0001, vs Model group.

Ingredient and Target Collection and Network Analysis

   Screening through the TCMSP, ETCM, and SwissTargetPrediction databases
   and pertinent literature, 10 bioactive ingredients of PN and 306
   ingredient-related targets were selected, as well as 66 bioactive
   ingredients of RS and 251 ingredient-related targets. The network
   relationship of ingredients and drugs is shown in [86]Figure 3. With
   “atherosclerosis” as the keyword, after deleting duplicates, a total of
   2412 AS disease targets were identified from the DisGeNET and the
   GeneCards databases under the condition of a relevance score greater
   than the median. There were 222 intersection targets of
   ingredient-related and AS-related targets using the BioVenn diagram
   ([87]Figure 4). Among the total intersection targets, PN and RS jointly
   shared 112 disease-associated intersection targets, and each had
   specific distinct intersection targets (79 for PN and 31 for RS)
   ([88]Figure 4), which indicated that these two Chinese herbs may have
   synergistic effects on AS.

Figure 3.

   [89]Figure 3
   [90]Open in a new tab

   Network diagram of bioactive ingredients and herbs. The hexagon nodes
   represent Panax notoginseng and Radix Salviae, and the diamond nodes
   represent the bioactive ingredients.

Figure 4.

   [91]Figure 4
   [92]Open in a new tab

   Venn diagram of PN and RS targets and AS targets. PN, Panax
   notoginseng; RN, Radix Salviae; AS, atherosclerosis.

   Using Cytoscape software and the Network Analyzer plug-in, a network
   relationship diagram of ingredients and intersection targets was
   constructed including 291 nodes and 1029 interaction edges, and the
   diagram revealed the main ingredients by the degree value ([93]Figure
   5). [94]Table 1 shows the top 10 bioactive ingredients of PN and RS
   that bind to key regulatory targets. The results showed that not only
   could one ingredient of PN and RS act on multiple target proteins, but
   multiple different ingredients could also act on the same target.

Figure 5.

   [95]Figure 5
   [96]Open in a new tab

   Network diagram of ingredients and targets. The purple node represents
   the ingredient. The gray node represents the intersection target.

Table 1.

   Top 10 Ingredients of PN and RS
    Mol ID                Ingredient Name               OB (%)  DL  Degree
   MOL000098 Quercetin                                  46.43  0.28 155
   MOL000006 Luteolin                                   36.16  0.25 76
   MOL007154 Tanshinone iia                             49.89  0.4  39
   MOL000358 Beta-sitosterol                            36.91  0.75 35
   MOL000449 Stigmasterol                               43.83  0.76 33
   MOL007041 2-isopropyl-8-methylphenanthrene-3,4-dione 40.86  0.23 27
   MOL007100 Dihydrotanshinlactone                      38.68  0.32 25
   MOL007061 Methylenetanshinquinone                    37.07  0.36 22
   MOL007049 4-methylenemiltirone                       34.35  0.23 21
   MOL007093 Dan-shexinkum d                            38.88  0.55 21
   [97]Open in a new tab

Construction of the PPI Network and Functional Enrichment Analysis

   Using STRING and Cytoscape with a confidence of 0.900, the PPI network
   of intersection targets was created, including 221 nodes and 973
   interaction edges ([98]Figure 6A). Through the analysis of CytoHubba
   and MCODE, the core clusters were obtained from the PPI network
   ([99]Figure 6B), and then the core targets were screened based on the
   MCC according to core clusters ([100]Figure 6C). In [101]Figure 6, a
   darker color and a larger diameter of nodes indicate a larger degree
   value. The top 10 targets affecting each other were RELA, JUN, TNF,
   IL6, IL1B, IL1A, CCL2, CXCL8, IL4 and STAT3 ([102]Table 2).

Figure 6.

   [103]Figure 6
   [104]Open in a new tab

   (A) PPI network diagram of intersection targets, (B) Core clusters, (C)
   Core targets.

Table 2.

   Top 10 Targets in the PPI Network
   Gene names UniProt ID                    Protein Names
   RELA       [105]Q04206 Transcription factor p65
   JUN        [106]P05412 Transcription factor Jun
   TNF        [107]P01375 Tumor necrosis factor
   IL6        [108]P05231 Interleukin-6
   IL1B       [109]P01584 Interleukin-1 beta
   IL1A       [110]P01583 Interleukin-1 alpha
   CCL2       [111]P13500 C-C motif chemokine 2
   CXCL8      [112]P10145 Interleukin-8
   IL4        p05112      Interleukin-4
   STAT3      p40763      Signal transducer and activator of transcription 3
   [113]Open in a new tab

   The KEGG pathway enrichment analysis of the top 10 targets showed that
   the most relevant signaling pathways were the AGE-RAGE signaling
   pathway in diabetic complications, the IL-17 signaling pathway, the
   chemokine signaling pathway and the JAK-STAT signaling pathway
   ([114]Figure 7).

Figure 7.

   [115]Figure 7
   [116]Open in a new tab

   Top 10 targets in the GO enrichment analysis of biological processes.

   The intersection targets of the PPI network were then used for GO and
   KEGG enrichment analysis. The GO analysis results revealed that
   biological processes (BP) were mainly related to cellular response to
   nitrogen compound, lipid, lipopolysaccharide and oxygen levels and
   positive regulation of cell migration. Cellular components (CC) were
   mainly connected with membrane rafts, transcription regulator
   complexes, side of membranes, receptor complexes and neuronal cell
   bodies. The relevant molecular functions (MF) included kinase binding,
   DNA-binding transcription factor binding, nuclear receptor activity,
   oxidoreductase activity, and protein homodimerization activity. The top
   10 BP, MF and CC subcategories are shown in [117]Figure 8.

Figure 8.

   [118]Figure 8
   [119]Open in a new tab

   GO functional analysis of BP, MF and CC.

   Abbreviations: BP, biological process; MF, molecular function; CC,
   cellular component.

   According to the P value, the KEGG pathway enrichment analysis screened
   the top 10 signaling pathways, as shown in the bubble diagram
   ([120]Figure 9A), and the relationship between pathways and targets is
   shown in [121]Figure 9B. The size and color of each bubble represent
   the number of enriched genes and the degree of enrichment in the
   pathway, respectively. The results indicated that PN-RS inhibited the
   AS pathophysiological process by modulating the AGE-RAGE signaling
   pathway in diabetic complications, fluid shear stress and
   atherosclerosis, lipid and AS, hepatitis B and endocrine resistance. On
   the other hand, these results also showed that PN-RS might have a
   multichannel synergistic effect on AS by participating in lipid
   metabolism, the oxidative stress response, the regulation of
   endothelial cell function, and the inflammatory response.

Figure 9.

   [122]Figure 9
   [123]Open in a new tab

   The results of KEGG pathway enrichment analysis. (A) The top 10
   signaling pathways. (B) The relationship between pathways and targets.
   The size and color of each bubble represent the number of genes and the
   degree, respectively.

PN-RS Inhibited the JAK2-STAT3 Signaling Pathway and Attenuated Inflammation
in Mice

   Combined with the results of network pharmacology analysis, based on
   the JAK-STAT signaling pathway, the mechanism of PN-RS in AS was
   further explored, and the inflammatory response was used as the entry
   point.

   The JAK2-STAT3 signaling pathway is closely related to the development
   of AS. By Western blotting detection, the protein expression levels of
   JAK2, p-JAK2, STAT3, and p-STAT3 in the model group were significantly
   increased compared with those in the control group. However, after drug
   treatment, especially after PN-RS treatment, the protein expression
   levels of JAK2, p-JAK2, STAT3, and p-STAT3 were significantly decreased
   ([124]Figure 10A). Similar to the protein expression, compared with the
   control group, the mRNA expression of JAK2 and STAT3 was significantly
   increased in the model group, which was significantly reduced in the
   drug treatment group, especially in the PN-RS treatment group
   ([125]Figure 10B).

Figure 10.

   [126]Figure 10
   [127]Open in a new tab

   PN-RS affects the JAK2-STAT3 signaling pathway. (A) Western blot
   analysis of the protein expression of JAK2, p-JAK2, STAT3, and p-STAT3.
   (B) PCR analysis of the mRNA expression of JAK2 and STAT3. The data are
   expressed as the mean ± SD, n = 3 for each group. **P<0.01, ***P<0.001,
   ****P<0.0001, vs Model group.

   The expression of the multiplication factor VEGF, chemotactic factor
   MCP-1 and the inflammatory cytokines TNF-α and IL-6 was measured by
   ELISA. Compared with the control group, the contents of plasma VEGF,
   MCP-1, TNF-α and IL-6 were significantly increased in the model group.
   PN, RS and PN-RS significantly decreased the levels of VEGF, MCP-1,
   TNF-α and IL-6 in mice. PN-RS provided the best treatment results
   ([128]Figure 11A–D).

Figure 11.

   [129]Figure 11
   [130]Open in a new tab

   PN-RS influences the secretion of cell factors in serum. ELISA analysis
   of the levels of VEGF (A), MCP-1 (B), TNF-α (C) and IL-6 (D) in mice.
   The data are expressed as the mean ± SD, n = 3 for each group. *P<0.05,
   **P<0.01, ***P<0.001, ****P<0.0001, vs Model group.

Discussion

   Atherosclerosis (AS), accompanied by fragile plaque and altered
   structure and function of the vessel wall, has become a frequent
   disease worldwide. To date, the detailed mechanism of AS is not fully
   understood, as the activation mechanism involves multiple factors and
   many genes. Ross et al[131]^26 proposed the hypothesis that AS results
   from damage to vascular endothelial structures. AS mainly results from
   a series of inflammatory reactions and complex endothelial dysfunction
   after endothelial injury, which is an important cause of cardiovascular
   and cerebrovascular diseases. Therefore, it is important to develop
   drugs that effectively control the development of AS. TCM has a
   significant therapeutic effect on AS through the synergistic effect of
   various ingredients and various targets. Moreover, it has fewer toxic
   and side effects, which has unique therapeutic advantages for AS.

   In this study, we explored the potential mechanisms of PN-RS in AS
   using network pharmacology and animal experiments. First, aortic
   histopathological changes and serum lipid levels in ApoE^−/− mice were
   detected through experiments to observe the effect of PN-RS on lipid
   metabolism. Pathological tissue staining and serum lipid detection
   showed that PN-RS could significantly improve aortic intimal damage,
   lipid deposition and serum lipid levels, and the treatment effect was
   the same as the effect of rosuvastatin ([132]Figures 1 and [133]2). To
   further explore the potential targets and signal transduction pathways
   of PN-RS treatment in AS, a network pharmacology analysis was performed
   based on the data of this animal experiment.

   Through screening from multiple databases, a network consisting of 76
   bioactive ingredients of PN-RS and 222 intersection targets was
   generated ([134]Figure 5). Based on the ingredient-target-disease
   network and the degree values, we screened the top 10 ingredients
   binding to key regulatory targets, including quercetin, luteolin,
   tanshinone IIA, β-sitosterol, stigmasterol,
   2-isopropyl-8-methylphenanthrene-3,4-dione, dihydrotanshinlactone,
   methylenetanshinquinone, 4-methylenemiltirone, and dan-shexinkum D
   ([135]Table 1). Among the top 10 ingredients, quercetin could act on
   155 targets and probably played the most extensive and important role
   in therapy. Quercetin can prevent cell infiltration in atherosclerotic
   plaques and reduce the risk of stroke by inhibiting THP-1 monocyte
   migration and increasing cholesterol efflux.[136]^27 Luteolin has many
   pharmacological effects, such as anti-inflammatory, antitumor,
   antiviral and CVD effects. Luteolin inhibits abdominal aortic plaque
   development and lipid accumulation by reducing macrophage inflammation
   in AS, and its mechanism involves the AMPK-SIRT1 signaling
   pathway.[137]^28 β-sitosterol is a plant sterol that can inhibit blood
   lipids by inhibiting exogenous absorption, endogenous synthesis,
   reverse transport and excretion, and some animal experiments have
   proven that β-Sitosterol has anti-inflammatory effects.[138]^29
   Tanshinone IIA can achieve anti-AS effects by promoting autophagy in
   macrophages, attenuating the inflammatory damage caused by ox-LDL, and
   regulating IL-6 expression.[139]^30 In summary, the bioactive
   ingredients of PN and RS screened by network pharmacology have a wide
   range of pharmacological effects and strong anti-AS effects.

   After obtaining the bioactive ingredients of PN-RS, PPI and functional
   enrichment analyses were performed on these 222 ingredient targets. The
   GO enrichment analysis showed that the BP included response to nitrogen
   compound, lipid, lipopolysaccharide, and regulation of cell migration
   ([140]Figure 8). BP was compatible with the process of occurrence and
   development of AS, which was that the vascular intima was damaged by
   stimulation factors, monocytes adhered and migrated, macrophages
   invaded and formed foam cells, and lipid deposition eventually resulted
   in AS. The KEGG pathway enrichment analysis showed that PN-RS inhibited
   AS by modulating the AGE-RAGE signaling pathway in diabetic
   complications, fluid shear stress and atherosclerosis, lipid and
   atherosclerosis, hepatitis B, endocrine resistance and human
   cytomegalovirus infection ([141]Figure 9). In the AGE-RAGE signaling
   pathway, AGEs can interact with RAGE to activate NF-kappa-B, thus
   inducing the oxidative stress response, promoting inflammation and the
   accumulation of extracellular matrix, enhancing the formation of
   atherosclerotic plaques and accelerating the development of
   atherosclerosis.[142]^31 The second KEGG pathway of enrichment analysis
   was fluid shear stress and atherosclerosis. The fluid shear stress is a
   tangential stress parallel to the tube wall caused by the friction
   between the blood flow and the tube wall, and it has been confirmed to
   be closely related to the occurrence and development of AS.[143]^32
   Abnormal changes in fluid shear stress, such as too low of fluid shear
   stress or oscillation, will lead to the disturbance of endothelial cell
   function and promote the development of AS.[144]^33 For lipid and
   atherosclerosis, the imbalance in lipid metabolism is a central aspect
   of disease progression, and dysfunction of lipid metabolism has been
   demonstrated as an independent risk factor for AS-associated
   CVD.[145]^34 The results of enrichment analysis and animal experiments
   support each other that PN-RS can exert its anti-AS effect by
   intervening in lipid metabolism ([146]Figures 2 and [147]9).

   According to the PPI network map, the top 10 core targets involved in
   the treatment of PN-RS for AS were screened, including RELA, JUN, TNF,
   IL6, IL1B, IL1A, CCL2, CXCL8, IL4 and STAT3 ([148]Table 2). RELA
   (NF-κ-B) can participate in immune and inflammatory responses and is
   also involved in the regulation of cell differentiation, proliferation,
   and apoptosis processes. A study reported that inhibiting
   STAT3/NF-kappa-B and endoplasmic reticulum stress signaling pathways
   can protect endothelial cells and alleviate atherosclerotic
   inflammation.[149]^35 The STAT3 protein mediates the expression of
   multiple genes in response to cell stimulation and thus plays a key
   role in many cellular processes, such as cell growth, apoptosis, and
   carcinogenesis. In addition, STAT3, TNF, IL-6 and CXCL8 proteins are
   all associated with the inflammatory response. The core targets of
   PN-RS are involved in the whole process of AS development, and the
   mechanisms are related to the AGE-RAGE signaling pathway in diabetic
   complications, the IL-17 signaling pathway, the chemokine signaling
   pathway and the JAK-STAT signaling pathway through KEGG pathway
   enrichment analysis ([150]Figure 7).

   The JAK-STAT signaling pathway is a common pathway by which various
   cytokines and growth factors transmit signals inside cells,
   participating in various biological activities, such as the immune
   response, vascular cell migration, proliferation and apoptosis.[151]^36
   There are four isoforms of JAK, namely, JAK 1, JAK 2, JAK 3, and JAK 4.
   As the target protein of JAK, STAT has seven isoforms, including STAT
   1, STAT 2, STAT 3, STAT 4, STAT5a, STAT5b, and STAT
   6.[152]^37^,[153]^38 The signal transduction process of the JAK-STAT
   pathway is that cytokines first combine with their specific receptor to
   form receptor dimers and recruit JAK family members. Nearby JAKs are
   phosphorylated by each other and provide anchor sites for STAT in the
   cytoplasm. Subsequently, STAT phosphorylation and dimerization occur,
   and activated STAT is transferred to the nucleus to interact with other
   transcription factors to regulate gene transcription and protein
   expression.[154]^39 Many studies have confirmed that the JAK-STAT
   signaling pathway acts on various aspects of AS formation, including
   dysfunction of vascular endothelial cells (ECs), proliferation and
   migration of smooth muscle cells (SMCs) and inflammatory cells, and
   overexpression of inflammatory cytokines. The activation of the
   JAK-STAT protein in cells can cause increased expression of various
   inflammatory mediators, such as MCP-1[155]^40 and VCAM-1,[156]^41 which
   can result in increased cell proliferation and migration and promote
   the adhesion and infiltration of inflammatory cells to the vascular
   endothelium. MCP-1 is one of the most important monocyte chemokines
   that can mediate the migration of monocytes to the blood vessel wall.
   VEGF is the major factor inducing the proliferation and migration of
   ECs. TNF-α and IL-6 inflammatory cytokines can promote AS development
   by enhancing the inflammatory response. As an inducer of the acute
   phase inflammatory response, IL-6 promotes the phosphorylation of STAT3
   and the transfer of STAT3 to the nucleus, promotes the activation of
   various downstream inflammatory factors, such as TNF-α and IL-6, and
   finally mediates the inflammatory damage of cells. Moreover, Watanabe
   et al[157]^42 experiments demonstrated that IL-6 could promote the
   proliferation of vascular smooth muscle cells (VSMCs) and the release
   of MCP-1 through the JAK-STAT signaling pathway.

   Based on the results of the GO and KEGG pathway enrichment analysis and
   previous animal experiment data, we hypothesized that PN-RS might exert
   anti-AS effects by regulating the JAK-STAT signaling pathway. The
   JAK2-STAT3 signaling pathway, as a classical inflammatory pathway, is
   closely related to AS. Therefore, we conducted further mechanistic
   studies based on the JAK2-STAT3 signaling pathway using the
   inflammatory response as the entry point. In this study, to further
   verify the effect of PN-RS drugs on AS treatment, the drug treatment
   groups were divided into PN, RS and PN-RS treatment groups. The
   expression levels of JAK2-STAT3 pathway-related proteins and mRNA were
   determined by Western blot and real-time PCR. The results showed that
   each treatment group, especially the PN-RS treatment group, could
   effectively inhibit the protein and mRNA expression of JAK 2 and STAT3
   in AS mice ([158]Figure 10). The expression of cytokines was measured
   by ELISA, and the experimental results showed that each treatment group
   could inhibit the secretion of TNF-α and IL-6 inflammatory cytokines,
   and the best anti-inflammatory effect of PN-RS was achieved
   ([159]Figure 11C and [160]D). In addition, PN-RS significantly reduced
   the serum VEGF and MCP-1 concentrations in ApoE^−/− mice, which was
   better than the monotherapy group ([161]Figure 11A and [162]B). The
   above series of experimental results suggest that PN-RS can inhibit the
   JAK2-STAT3 signaling pathway, thus reducing inflammatory factor and
   cytokine expression, inhibiting cell proliferation and migration and
   inflammatory cell infiltration, and reducing the inflammatory response
   to effectively exert anti-AS effects.

   We combined network pharmacology and animal experiments to verify that
   the anti-AS mechanism of PN-RS may be related to the regulation of the
   JAK2-STAT3 signaling pathway, inflammatory response and abnormal lipid
   metabolism regulation, which provides a theoretical basis and research
   direction for further experimental verification.

Conclusion

   Based on the network pharmacological data analysis, the potential
   effective mechanism of PN-RS treatment for AS relates to the regulation
   of targets and pathways in various biological processes, especially
   lipid metabolism and inflammatory reactions. Animal experiments
   confirmed the anti-AS effect of PN-RS in ApoE^−/− mice. PN-RS
   significantly reduced the atherosclerotic area and lipid levels in
   ApoE^−/− mice. Further experimental results showed that PN-RS could
   significantly inhibit the JAK2-STAT3 signaling pathway and reduce the
   concentrations of the inflammatory factors TNF-α and IL-6, the growth
   factor VEGF, and the chemokine MCP-1 in mice. In conclusion, PN-RS can
   protect against AS through multiple targets and pathways.

Funding Statement

   This article is supported by the National Natural Science Foundation of
   China (81974566), Taishan Scholars, Shandong Province.

Abbreviations

   AI, AS index; ANOVA, Analysis of variance; AS, Atherosclerosis; BCA,
   Bicinchoninic acid; BP, Biological Processes; CC, Cellular Components;
   CVD, Cardiovascular disease; DL, Drug-likeness; ECs, Endothelial cells;
   ELISA, Enzyme-linked immunosorbent assay; GO, Gene Ontology; H&E,
   Hematoxylin and Eosin; HDL-C, High-density lipoprotein cholesterol;
   HMG-CoA, 3-Hydroxy-3-methyl glutaryl coenzyme A reductase; IL-6,
   Interleukin-1; JAK2, Janus kinase 2; KEGG, Kyoto Encyclopedia of Genes
   and Genomes; LDL, Low-density lipoprotein; LDL-C, Low-density
   lipoprotein cholesterol; MCP-1, Monocyte chemotactic protein-1; MF,
   Molecular Functions; OB, Oral bioavailability; PFA, Paraformaldehyde;
   PMSF, Phenylmethanesulfonyl fluoride; PN, Panax Notoginseng; PN-RS,
   Panax Notoginseng-Radix Salviae couplet medicines; PPI, Protein-protein
   interaction network; PVDF, Polyvinylidene fluoride; RS, Radix Salviae;
   SDS-PAGE, Sodium dodecyl sulfate-polyacrylamide gel electrophoresis;
   SMCs, Smooth muscle cells; SPF, Specific pathogen-free; STAT3, Signal
   transduction and activator of transcription 3; TC, Total cholesterol;
   TCM, Traditional Chinese medicine; TG, Triglyceride; TNF-α, Tumor
   necrosis factor-α; VEGF, Vascular endothelial growth factor; VSMC,
   Vascular smooth muscle cell.

Data Sharing Statement

   The datasets and all data in this study are available from the
   corresponding author.

Author Contributions

   All authors made a significant contribution to the work reported,
   whether that is in the conception, study design, execution, acquisition
   of data, analysis and interpretation, or in all these areas; took part
   in drafting, revising or critically reviewing the article; gave final
   approval of the version to be published; have agreed on the journal to
   which the article has been submitted; and agree to be accountable for
   all aspects of the work.

Disclosure

   The authors declare that the study was conducted in the absence of any
   commercial or financial relationship that could be interpreted as a
   potential conflict of interest.

References