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Integrated Network Pharmacology and Metabolomics Analysis to Reveal the Potential Mechanism of Siwu Paste on Aplastic Anemia Induced by Chemotherapy Drugs

Purpose This study aimed to reveal the multicomponent synergy mechanisms of SWP based on network pharmacology and metabolomics for exploring the relationships of active ingredients, biological targets, and crucial metabolic pathways. Materials Network pharmacology, including TRRUST, GO, and KEGG, enrichment was used to discover the active ingredients and potential regulation mechanisms of SWP. LC-MS and multivariate data analysis method were further applied to analyze serum metabolomics profiling for discovering the potential metabolic mechanisms of SWP on AA induced by Cyclophosphamide (CTX) and 1-Acetyl-2-phenylhydrazine (APH). Results A total of 27 important bioactive ingredients meeting the ADME (absorption, distribution, metabolism, and excretion) screening criteria from SWP were selected. Interaction networks were constructed and validated based on the 10 associated ingredients with the relevant targets. A total of 125 biomarkers were found by Metabolomics approach, which associated with the development of AA, mainly involved in amino acid metabolism and lipid metabolism. While SWP can reverse the above 12 metabolites changed by AA. Network analysis revealed the synergistic effects of SWP through the 43 crucial pathways, including Sphingolipid signaling pathway, Sphingolipid metabolism, Arginine and proline metabolism, VEGF signaling pathway, Estrogen signaling pathway. Conclusion The study suggested that SWP is a useful alternative for the treatment of AA induced by CTX + APH. Its potential mechanisms are to improve hematopoietic microenvironment and promote bone marrow hematopoiesis therapies.


Introduction
Aplastic anemia (AA), a bone marrow hematopoietic failure (BMF) syndrome, is characterized by attenuated bone marrow hematopoietic cell proliferation, decreased peripheral whole blood cell and immune dysfunction. 1 It has high prevalence in the Asian population, especially young adults. 2 Chemotherapy is the most common cause of AA. Although the immunosuppressive therapy provide an strategy for patients who are not suitable for allogeneic hematopoietic stem cell transplant, some patients after treated with a single therapeutic method show relapse or poor efficacy. 3,4 Therefore, expanding an alternative and more effective therapy for AA is needed. Moreover, the pathogenesis of AA induced by chemotherapy drugs is complex, and combination therapy may supply better service for it than monotherapy.
Siwu Paste (SWP), a popular prescription for tonifying blood, has over 1000 years history in the clinical application of Traditional Chinese Medicine (TCM). It described as good effects in promoting blood circulation, ameliorating anemia and pain, with the feature of, including four herbs: Angelica sinensis (Oliv.) Diels (Dang Gui, DG), Ligusticum chuanxiong Hort. and SWP group (SWP). During the experiment, all animals were access to food and water freely, with standard surroundings: 12 h light and shade cycle, 50-55% humidity and temperature at 20-22°C. In this section, the model of aplastic anemia was established on the basis of previous study. 6 The model group and SWP group were intraperitoneal injected with Cyclophosphamide (CTX) (Baxter International Co., Ltd., Illinois, USA) and 1-Acetyl-2-phenylhydrazine (APH) (Meilun Biotechnology Co., Ltd., Dalian, China), while the control group received an equal volume of phosphate-buffered saline. Additionally, the SWP group was orally administered 22.68g/ kg/d SWP, whereas the control and model groups obtained an equal amount of distilled water, lasted for 14 days.

Peripheral Blood Routine and Histological Analysis
After 14 days, rats were sacrificed under anesthesia and blood sample was collected through the abdominal aorta. The peripheral blood (PB) routine test, including white blood cell count (WBC/10 9 ·L −1 ), red blood cell count (RBC/10 12 ·L −1 ), hemoglobin (HGB/g·L −1 ), haematocrit (HCT/%), and platelet count (PLT/10 9 ·L −1 ), was applied to evaluate the quantity of blood cells and to diagnosis conditions of blood. 13 HE staining of femur was also employed to evaluate the medullary hematopoiesis function and the changes of hematopoietic microenvironment. 14 Specific methods are as follows: the fixed femur (decalcified in 5.5g EDTA-2K + 100 mL 4% paraformaldehyde for 20 days in 4°C prior to the following experiments) were embedded in paraffin, and sectioned at 5 mm followed by staining with hematoxylin/eosin. Olympus BH-2 light microscope was used to observe the stained sections of femur tissue (Tokyo, Japan).

Network Pharmacology Prediction Compound Data Preparation and ADME Screening
Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database (http://lsp. nwu.edu.cn/tcmsp.php, Ver.2.3), and Bioinformatics Analysis Tool for Molecular mechanism of Traditional Chinese Medicine (BATMAN) (http://bionet.ncpsb.org/batman-tcm/, updated January 2016) 15,16 were used to select all candidate compounds of four herbs in SWP. In order to obtain bioactive components contributing to its therapeutic effect, all selected ingredients should meet the principle of ADME: 1. Oral bioavailability (OB) ≥30%, 2. Drug-likeness (DL ≥ 0.18. 17 In addition, a widely scale data-mining strategy was adopted to replenish some bioactive ingredients, while those with poor pharmacological properties and bad drug ability compounds were removed. 18

GO and KEGG Enrichment Analysis for Targets
To investigate the potential biological pathways and critical targets, our study analyzed the PPI targets with Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and TRRUST (https://www.grnpedia.org/trrust/, ver.2). 25 The terms of GO or KEGG with p-value ≤ 0.05 were finally screened out for the research.

Metabolomics Analysis Collection and Preparation of Serum Sample
The following methods were employed to prepare serum samples: 100 μL aliquot of serum sample were taken from the −80°C refrigerator, thawed at 4°C for 30 minutes. To remove the protein in the sample, 10 μL internal standard (0.3 mg/ mL 2-chloro-l-phenylalanine was dispersed in 300 μL ice-cold mixture contented methanol and acetonitrile (2/1, v/v).

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Then they were vortexed for one minute. Subsequently, the mixtures were handled with concentration under 13,000 rpm and 4°C for 15 min. 400 μL of the clear supernatant was evaporated, reconstituted with 200 μL of 20% methanol, vortexed for 30s, and sonicated for 2 min. After centrifugation for 10 minutes (13,000 rpm, 4°C), the supernatant was filtered through a 0.22 μm microfilter and transferred to LC vial. Finally, 10 μL of the supernatant was taken for LC-MS test. Equal volume samples from each group were mixed as Quality Control (QC) in our experiment. Aim to ensure the stability of the samples, the above samples were stored at 4°C during the LC/MS experiment.

Identification and Quantitative Analysis
In the study, progenesis QI software (Waters Corporation, Milford, USA) was employed to perform standardized preprocessing of metabolomics data. 26 Subsequently, the acceptable ranges of Precursor, fragment and retention time are set as 5 ppm, 10 ppm and 0.02 min, respectively. In order to obtain reliable peak information, we exclude the interference of isotopes, internal standard and noise, and limit the minimum intensity of chromatographic peak to 15% of the base peak intensity. The peaks will be eliminated when their ion intensity equal to 0 exists in more than 60% of samples. The retention time, m/z and MS/MS information are used to automatically match the metabolite information of human metabolite database (HMDB), lipid maps (v2.3) and metlin database to identify the chromatographic peak. Finally, the endogenous metabolites with P < 0.05 were considered as the differential metabolites to distinguish SWP, model and control group after Student's test.

Virtual Docking
To decrease the complexity and improve the accuracy of the constituent-target network, Molecular Operating Environment (MOE 2015.10 software) was further employed in our study to validate the interaction between compounds and critical targets, according to previous studies. 17 Elisa Serum was obtained from the supernatant of blood sample after centrifugation at 4°C. The levels of serum SPHK-1 (NO. 1229A15), PLD1 (NO. 1228A11), and PLD2 (NO. 1228A09) were monitored by ELISA kits according to the instructions of the manufacturer. All of the ELISA kits were purchased from ZCIBIO Technology Co., Ltd. (Shanghai, China).

Western Blot Analysis
Bone marrow cells (BMCs) were obtained for Western blot (WB) analysis. BMCs were washed out from rat femurs and tibiae using a 5 mL syringe with PBS (prechilled overnight at 4°C). The suspension was then centrifuged at 3000 rpm under 4°C for 15 min. The precipitate was collected, quenched in liquid nitrogen and stored at -80°C until analysis. WB analysis was performed as accordance with previous report. 27 In brief, BMCs sample were homogenized on ice in RIPA lysis buffer (Beyotime Biotechnology, China). After the above mixture was centrifuged, the supernatant was collected. Membranes were blotted with primary antibodies, anti-rat p-STAT1 (1:500 dilution), anti-rat GRB2 (1:1000 dilution) or anti-rat GSPT1 (1:1000 dilution), overnight at 4°C. Then incubated with horseradish peroxidase bound secondary antibody for 2 hours. ImmunoWay Biotechnology Company (USA). Antibodies GRB2 (NO. ba32111) were purchased from Abcam (UK). Immunoreactive proteins were detected by ELX800 and quantified by ClinxChemiScope 6000 System.

Multivariate Statistical and Pathway Analysis
SPSS 23.0 software was used to analyze the experimental data. An analysis of variance (ANOVA) is performed to obtain statistical significance for comparisons between multiple parameters. The LSD test is performed under the assumption of equal variances; otherwise, Dunnett's T3 test is carried out to data with unequal variances. Statistical significance is established at P < 0.05 or P < 0.01. We tested the normality of the data. If the data fit the normal distribution, we did homogeneity analysis of variance, otherwise we did Kruskal-Wallis test and Dunn's test. Normally distributed data are displayed by X ± SD or X ± SEM, while skewed data are presented as median (min-max). According to our previous study, random forest and SIMCA software package (version 14.0, Umetrics, Umeå, Sweden) was used to observe the metabolic profiles and differential metabolites in different experimental groups under positive and negative mode. As described in previous studies, differential metabolites were sent to Metaboanalyst 4.0 for pathway enrichment analysis and pathway topological analysis. 28

Results and Discussion
Therapeutic Effect of Siwu Paste on AA Induced by CTX + APH The results of peripheral blood (PB) and Histological examination indicated that we not only successfully established the aplastic anemia model, but also proved that SWP at the dose of this study had a positive effect on AA. Contrasted with control group, the level of WBC, RBC, HCT and PLT in AA model group was reduced obviously (P < 0.01). The above indices in SWP increased significantly compared with model group (P < 0.05, P < 0.01), suggesting that treatment of SWP could relieve the blood deficiency in AA rats. The details are displayed in Figure 1A and Figure S1.
HE staining clearly shown the structure of periosteum, marrow cavity and cartilage tissue in control group, and abundant cellular components (granulocytes, megakaryocytes, nucleated cells, etc.) were observed in the medullary cavity. However, AA rats had serious medullary cavity injury, including edema of vascular fibrosis and significant fibrosis. After the treatment of SWP, the pathological condition of femur was improved significantly. The myelofibrosis, medullary cavity edema and fat cells were inhibited efficiently in SWP group. It was also observed that the proliferation of nucleated cells increased actively, and the number of erythrocytes in parenchyma vessels increased ( Figure 1B). Overall, all the investigated parameters were changed significantly in AA rats, but they were restored by the SWP treatments.
The pharmacological study displayed the improving anemia and recovering hematopoietic functions effects of SWP treatment on AA animals, that were conformed to previous research. 6,7 It suggests that SWP may be an alternative manner for AA induced by CTX + APH.

Identification of Siwu Paste's Ingredients and Target Genes
To explore its specific mechanism of anti-anemia, network pharmacology analysis was performed. 230 ingredients were identified in SWP, containing 88 in Angelicae Sinensis Radix, 40 in Rehmanniae radix preparata, 81 in Ligusticum chuanxiong Hort., and 41 in Cynanchum otophyllum Schneid., and some repeating compounds were removed (Table S1).

Network Construction and Enrichment Analysis
Protein-Protein (PPI) interaction, GO and KEGG analysis were performed in 64 common targets to investigate target function and the potential mechanism of SWP on AA. A view of PPI network is displayed in Figure 2B. In this network, 7 nodes (containing ALB, AKT1, MAPK1, CASP3, HRAS, CAT, IL-2) with the value of degree > 20, were regarded as potential hub target for SWP to ameliorate the hematopoiesis disorder caused by AA.
As results shown in GO enrichment ( Figure 2C), the top 4 enriched terms are positive regulation of biological process (GO:0048518), cellular protein metabolic process (GO:0044267), regulation of metabolic process (GO:0019222), and regulation of catalytic activity (GO:0050790), all of which belonged to Biological Process. Extracellular vesicle (GO:1903561), vesicle (GO:0031982), and cytosol (GO:0005829) with gene number > 7 belong to terms of GO cellular compound. The terms of GO molecular functions mainly included catalytic activity (GO:0003824) and transferase activity, transferring phosphorus-containing groups (GO:0016772). Further TRRUST analysis demonstrates that the 64 targets were primarily regulated by Sp1 transcription factor (SP1, TRR00641), v-rel reticuloendotheliosis viral oncogene homolog A (avian) (RELA, TRR00575), nuclear factor of kappa light polypeptide gene enhancer in B-cells 1 (NF-κB1, TRR00452), and jun proto-oncogene (JUN, TRR00323). Those results indicated that SWP may be mainly involved in regulation of metabolic and protein on treating AA.
In our research, there are 12 KEGG pathway (P < 0.05). The top 3 terms are FoxO signaling pathway (map04068), MAPK signaling pathway (map04010), Ras signaling pathway (map04014) which play an important role in the occurrence and development of AA ( Figure 2D). A map of the "Herb-Compound-target-pathway" (including 71 nodes and 354 edges) based on KEGG analysis were established to investigate the mechanism of SWP on AA ( Figure 2D). In     DovePress this network, DG was considered as a principal drug herb for regulating the most multiple compounds, which meet the TCM principles that DG is the sovereign drug in SWP. Moreover, we found that Mitogen-activated protein kinase 1 (MAPK1), RAC-alpha serine/threonine-protein kinase (AKT1), Glutathione S-transferase P (GSTP1), signal transducer and activator of transcription 1-alpha/beta (STAT1), growth factor receptor-bound protein 2 (GRB2) with higher degree also act critical targets for regulating or participating in multiple herbs or signaling pathways. Take GRB2 for example, it involves in multiple pathways related to the blood system, such as FoxO signaling pathway, Phospholipase D signaling pathway (map04072), MAPK signaling pathway, Ras signaling pathway. GRB2, which links IL3 signaling to the ERK/MAPK proliferative pathway, has been reported to play important functions during the HSPC proliferation, survival and expansion. 29 STAT1 plays an important role in the regulation of erythropoiesis. Studies have shown that STAT1 deficiency leads to increased red blood cell apoptosis. 30 As a stem cell factor (SCF) receptor gene, KIT play a key role in regulating the growth, survival, and differentiation of erythroid progenitors alone, as well as a synergistic effect with erythropoietin (EPO). 31,32 Ratajczak et al, demonstrated that the growth of hematopoietic colony would be inhibited by more than 30%, when the mRNA expression of KIT was blocked in bone marrow mononuclear cells (MNC). 33 Analysis of miRNA differential gene expression in bone marrow revealed that Ras signaling pathways and Rap1 signaling pathway were the most significantly altered pathways between AA patients and healthy controls. 34 The damage of aplastic anemia to bone marrow, HSPC and metabolism is partly due to antigen mediated immune response, which eventually leads to increased oxidative stress or inflammatory response. [35][36][37][38] It has been recently reported that FoxO signaling-mediated autophagy and regulation of mitochondrial activity are necessary for maintenance of hematopoiesis homeostasis in HSPC metabolic. [39][40][41] Our results suggest that promoting erythropoiesis may be an effective strategy for SWP in the treatment of AA.
Those results provide that the herbal combination may have a great range of possible molecular targets than each individual herb, which might help to explain the synergistic of SWP effects in treatment of AA. 17

Identification of Differential Metabolites and Multivariate Data Analysis
LC-MS was used to identify endogenous serum metabolic profile between control, model, and SWP group ( Figure S2). It can be clearly seen from the random forest method under positive and negative ion modes that the above three groups have been completely separated ( Figure 3A). Compared with model group, SWP were closer to control group, as well as the latter one had the trend of regression to the control group. This part indicated that our SWP have the positive regulation on AA. Meanwhile, the QC group was clustered together tightly. It indicated that our metabolic profile is stable and reliable.
In addition, the differences between each two groups were analyzed by orthogonal partial least square-discriminate analysis (OPLS-DA), and the metabolic characteristics of different groups were visualized by SIMCA. In positive ( Figure 3B) and negative ( Figure 3C) ion modes, there was significant separation between each two groups. If the 1244 metabolite meets the conditions of VIP > 1 and P < 0.05, it will be selected as a potential biomarker. Based on positive ions mode, there are 111 (93 up-/18 down-regulation) and 77 (45 up-/32 down-regulation) biomarkers identified respectively between control and model, and model and SWP. Analogously, 40 (28 up-/12 down-regulation) and 28 (3 up-/25 down-regulation) biomarkers were separately identified under negative ion mode in above mentioned groups ( Figure 4, Table S2).

Metabolic Pathway Analysis
A total of 106 differential metabolites regulated by SWP were further analyzed at Metaboanalyst 4.0 to reveal their functional and metabolic characteristics. 17 metabolic pathways were enriched in our research (Table S3, Figure S3). The regulation of SWP on the above 12 metabolites is regarded as a potential biomarker for SWP to reduce AA metabolic disorder (Table 3). Study testified that Nicotinamide Riboside (NR) and Niacinamide, as nicotinamide adenine dinucleotide (NAD + ) dietary supplements, recovery hematopoiesis function in mice suffering from hematological failure through reduced mitochondrial activity within HSPC. [42][43][44][45] Though products of lipoxygenase in arachidonic acid metabolism are regarded as typical pro-inflammatory, recently study has been proved that 15-HPETE exhibit anti-inflammatory activity by destabilizing TNFmRNA. 46,47 However, abnormal elevation of the membrane-located 15(S)-HPETE can trigger greater levels of oxidative damage to the polyunsaturated fatty acid side-chains, witch finally induces the loss of erythrocyte membranes integrity. 48 In this study, the serum level of Nicotinamide Riboside, Niacinamide and 15(s)-HPETE in AA model group was significantly higher than that in control group, whereas the levels of LysoPC (17:0), LysoPC (24:1 (25Z) and PE (16:1 (9Z)/ P-18:1 (11Z)) were decreased markedly (P < 0.05). After SWP treatment, the above indexes were significantly restored (P < 0.05). Phosphatidylethanolamine (PE) regarded as a potent anti-inflammatory lipid. 49 It has been confirmed that an abundant of lyso-phosphatidylcholine (LPC) such as LysoPC (17:0) and LysoPC (24:1 (25Z) in plasma, contributes to driving the activation of inflammatory responses. 50 We speculate that SWP may suppress the inflammation and oxidative damage by restoring the level of PE and LPC and balancing the abnormally increased 15(s)-HPETE under the AA. SWP may also promote the metabolism of Niacinamide for maintenance of adult HSC quiescence. It provides a better hematopoietic microenvironment for promoting hematopoiesis.
Our observations also illustrated that Glycerophospholipid metabolism and Sphingolipid metabolism including PE (16:1 (9Z)/P-18:1 (11Z), Glycerophosphocholine, Sphingosine, Sphinganine, and Sphingosine-1-phosphate, were related to the dysregulation of hematopoietic. 51, 52 Orsini's study provides evidence that sphingolipid was participated in TNFαmediated modulation of TF/miR network and autophagy inhibition in HSPCs, affecting the formation of erythrocytes. 53 Sphinganine is a derivative of Sphingosine. The accumulation of them has been verified to suppresses Bcl-xL expression and downregulates Bcl-2 to enhance apoptosis, which accompanied by the strong inhibition of MAPK cascade. [54][55][56][57] Whatmore, Thiet et al, study indicated that a significantly decrease in plasma S1P level in Major-facilitator superfamily transporter 2b (Mfsd2b) knockout mice would result in damaged membrane of erythrocyte and disordered PB. 58 They also found that sphingosine was highly accumulated when the secretion of S1P were block by knockout the Mfsd2b in red blood cell (RBC). On contrary, Sphingosine-1-phosphate (S1P), synthesized by phosphorylation of sphingosine in the presence of sphingosine kinase 1 (SphK1), was shown to have antiapoptotic properties. 54 Our and Wątek's research demonstrate that the levels of Sphingosine and Sphinganine were up-regulated significantly in the model with immune damage mediated by chemotherapeutic drugs, while the concentration of Sphingosine-1-phosphate (S1P) was significantly lower (P < 0.05). 59 After the treatment of SWP, the concentration of Sphingosine and Sphinganine was declined significantly compared with model (P < 0.05). The Sphingosine-1-phosphate has elevated tendency after treated with SWP with no significance.

Network Pharmacology and Metabolomics Integration Analysis
To further clarify the molecular mechanism and potential biological pathway of SWP for treatment of AA, we comprehensively analyzed the results of network pharmacology and metabonomics. Firstly, we searched the HMDB DovePress database for 12 different metabolites obtained by metabolic pathway analysis, and then acquired the enzymes involved in the regulation of these metabolites. The 64 targets of PPI were then linked to these enzymes through string website. Finally, the network of component target gene enzyme metabolite was constructed ( Figure 6). Four hub compounds (cisligustilide, paeoniflorin, betulinic acid and senkyunolide-B) screened from the network "Herb-Compound-Target-Pathway" were docked with three key targets (GSTP1, STAT1 and GRB2) selected from the "Metabolites-enzymetarget" network, respectively.
The three-dimensional structures of proteins 4K2R, 3GUR and 4U2X were obtained by searching GSTP1, GRB2 and STAT1 from PDB protein database. All of the docking scores were less than −3.8, which indicated that the proteins shown well binding activity (Table S4, Figure 7). The docking results are shown in Figure 7. It suggests that paeoniflorin, betulinic acid and senkyunolide-B may be involved in the regulation of GSTP1, STAT1 and GRB2 to support SWP in the treatment of AA caused by chemotherapy drugs. Western blot was also applied to further validate the results of virtual docking. In our study, compared with the control group, the protein expression of p-STAT1 (p <0.05) and GSTP1 (p <0.01) have been significant decreased by CTX-treatment, while the protein expression of GRB2 (p <0.01) increased significantly (Figure 8 and Figure S4). After treated with SWP, p-STAT1 protein was significantly increased (p <0.05) and GRB2 was obviously declined (p <0.05) as compared to model group.
Compared with control group, model group developed higher serum levels of SPHK-1 (p < 0.001) and PLD1 (p < 0.01), while SWP obviously reduced above indexes (p < 0.01, 0.05) (Figure 8, Figure S5). Additionally, in contrast to control group, the serum levels of PLD2 were significantly decreased in model group (p < 0.01). After SWP intervention, the serum PLD2 were elevated as compared to model group (p < 0.05). Although the role of PLD

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in AA remains unclear, our study suggests that PLD expression is disrupted in chemotherapy-induced AA and that SWP reverses this imbalance. In addition, it is partly consistent with the prediction of our networked pharmacology combined with metabolomics.  Although we have examined the possible role of SWP in treating AA induced by CTX + APH, there are some limitations in the present study. Due to the limitation of the sample size, we cannot estimate the efficacy of SWP in large samples. Therefore, it is necessary to enlarge the sample size in future experiments. In addition, the potential targets and biological pathways predicted by network pharmacology combined with metabolomics methods need to be validated by more in vitro experiments. Targeting lipid metabolism is also the direction we need to work on in the next step.

Conclusion
In summary, our research confirmed the positive effect of SWP on aplastic anemia (AA), and enriched the possible pathway of SWP via network pharmacology and metabonomics analysis. In the component-target and PPI network, we identified 27 active compounds from SWP and 64 common proteins associated with AA. Furthermore, MAPK1, CASP3, STAT1, GRB2 and KIT were identified as the hub targets for SWP in treating AA. Metabolomics was employed to characterize the metabolic profiles of APH together with CTX-induced AA rats, attending to identified the endogenous markers that drive molecular mechanisms. SWP improved inflammation and oxidative damage of hematopoietic microenvironment predominantly by significantly down-regulated the elevated levels of 15(s)-HPETE, as well as dramatically up-regulated the levels of LysoPC (17:0), LysoPC (24:1 (25Z) and PE (16:1 (9Z)/P-18:1 (11Z)). Most importantly, SWP effected hematopoietic by declined the accumulation of Niacinamide, Sphingosine and Sphinganine. The alter of these metabolites mainly involve in Sphingolipid metabolism, Glycerophospholipid metabolism, Arachidonic acid metabolism, Nicotinate and nicotinamide metabolism. Although we have examined the possible role of SWP in treating AA, there are some limitations in the present study. Further vitro and vivo experimental validation will be involved in our next step study.