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Hindawi Journal of Analytical Methods in Chemistry Volume 2023, Article ID 9030015, 20 pages https://doi.org/10.1155/2023/9030015 Research Article A Novel Strategy for Screening Active Components in Cistanche tubulosa Based on Spectrum-Effect Relationship Analysis and Network Pharmacology 1 2 1 2 2 Xiao-Tong Liu, Dong-Mei Sun, Wen-Xin Yu, Wei-Xiong Lin, Liao-Yuan Liu, and Yu Zeng School of Chinese Materia Medica, Guangdong Pharmaceutical University, Guangzhou 510006, China Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Formula Granule, Guangdong E-Fong Pharmaceutical Co. Ltd., Foshan 528244, China Correspondence should be addressed to Yu Zeng; email@example.com Received 28 August 2022; Revised 12 January 2023; Accepted 19 January 2023; Published 31 January 2023 Academic Editor: Cecilia Cagliero Copyright © 2023 Xiao-Tong Liu et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Cistanche tubulosa (Schenk) R. Wight is a valuable herbal medicine in China. Te study aimed to explore the potential mechanisms of C. tubulosa on antioxidant activity using spectrum-efect relationship and network pharmacology and the possibilities of utilizing herbal dregs. In this work, diferent extracts of C. tubulosa, including herbal materials, water extracts, and herbal residues, were evaluated using high-performance liquid chromatography (HPLC) technology. In addition, the antioxidant activities were estimated in vitro, including 2, 2-diphenyl-1-picrylhydrazyl; superoxide anion; and hydroxyl radical scavenging assays. Te spectrum-efect relationships between the HPLC fngerprints and the biological capabilities were analyzed via partial least squares regression, bivariate correlation analysis, and redundancy analysis. Furthermore, network pharmacology was used to predict potential mechanisms of C. tubulosa in the treatment of antioxidant-related diseases. According to the results, eleven common peaks were shared by diferent extracts. Geniposidic acid, echinacoside, verbascoside, tubuloside A, and isoacteoside were quantifed and compared among diferent forms of C. tubulosa. Te spectrum-efect relationship study indicated that peak A might be the most decisive component among the three forms. Based on network pharmacology, there were 159 target genes shared by active components and antioxidant-related diseases. Targets related to antioxidant activity and relevant pathways were discussed. Our results provide a theoretical basis for recycling the herbal residues and the potential mechanisms of C. tubulosa in the treatment of antioxidant-related diseases. from Cistanche species can elevate the activities of super- 1. Introduction oxide dismutase (SOD) and glutathione peroxidase (GSH- Cistanche tubulosa (Schenk) R. Wight, one of the most Px) . Echinacoside, one member of the PhG family, re- frequently used herbs in the Cistanche family, is known as verses efectively in vivo oxidative stress induced by high- glucose diets via downregulation of the nitrous oxide system the “Ginseng of the Desert” for its various health benefts . Modern pharmacological investigations have discovered (NOS) activity and phospho-eNOS expression . Te basic that the Cistanche family ofers various pharmaceutical ef- skeleton of the PhG consists of phenylethyl alcohol and fects, such as antioxidant, anticancer, hypoglycemic, anti- glycosyl moieties. PhGs are believed to have a signifcant depressant, cognitive improvement, and antimicrobial activity due to phenolic hydroxyl groups in their structure. efects . Te primary chemical cluster in Cistancheherb Te antioxidant activity of PhGs increases with the presence a is phenylethanoid glycosides (PhGs) . PhGs derived of phenolic hydroxyl groups . 2 Journal of Analytical Methods in Chemistry Reactive oxygen species (ROS) have crucial roles in become a focus of our attention. In addition to considering many physiological processes and essential protective WEs of C. tubulosa, it is hoped to determine whether HRs can prove useful as candidate TCMs and to explore op- mechanisms. Frequent exposure to high ROS concentrations may contribute to nonspecifc damage to proteins, lipids, portunities for transforming discarded C. tubulosa waste and nucleic acids. ROSs can be neutral molecules (e.g., material into feasible products. hydrogen peroxide), ions (e.g., superoxide anion), or radi- Spectrum-efect relationships are utilized to determine cals (e.g., hydroxyl radicals) and exert their efects via efective components in complex mixtures and refect the regulation of cell signaling cascades . Teir rapid pro- internal quality of herbal medicine. It is indispensable in duction and removal are infuenced by a variety of mech- the process of modernization and internationalization of anisms. Tey are lightweight and difuse easily across short herbal medicine. Since the spectrum-efect relationship •− distances . Te superoxide anion (O ) is a precursor of research of herbal medicines is based on the chromato- graphic fngerprint, a suitable analytical method is required most ROSs and an intermediate species in oxidative re- actions. Hydroxyl radicals (OH•) are catalyzed by reduced to generate a fngerprint that refects the chemical in- •− gredients of herbal medicines. High-performance liquid transition metals, which may in turn be reoxidised by O . An imbalance between excessive production of ROS and chromatography (HPLC) is an important analytical limited antioxidant defenses leads to various deleterious method that has many advantages, such as high separation, processes also called “oxidative stress” . If such an im- good stability, high efciency, and high quantitative pre- balance can be corrected, the management of several defense cision. PLSR (partial least squares regression) simplifes the mechanisms may be manipulated. Oxidative stress is in- data structure and correlation analysis between two sets of volved in various pathological conditions, such as cancer, variables by using regression modeling . In bivariate cardiovascular disease, neurological disorders, and diabetes correlation analysis (BCA), test scores are correlated with . In addition, the 2,2-diphenyl-1-picrylhydrazyl (DPPH•) conceptually related constructs in order to establish valid evidence . RDA (redundancy analysis) has been used to radical is colored and remarkably stable, and thus is among the most common radicals considered in numerous studies identify the primary microbial communities related to special biological capacity, but we applied it to the . A DPPH scavenging assay is an easy-to-implement, accurate method of measuring the total antioxidant ca- spectrum-efect relationship . To evaluate the corre- lation coefcients, PLSR and BCA were used. Te results pacities of botanical or herbal extracts . Terefore, DPPH, superoxide anion, and hydroxyl radical scavenging were then verifed using RDA to determine which models assays have been used to evaluate the antioxidant capacity of were more appropriate for studying the spectrum-efect diferent extracts of C. tubulosa. relationship with C. tubulosa. Te extract production steps for traditional Chinese In the methodologies of “multicomponent therapeu- medicine (TCM) are complex and involve cutting, pro- tics, biological network” in network pharmacology, we try cessing, extraction, concentration, and drying . It is to search for common targets between active molecules and diseases, which may play an indispensable role in providing inevitable that active components in herbal materials (HMs) will be lost during such sophisticated manufacturing stages. a reference for the prevention of diseases. Cistanche herba exhibit potential multicomponent and multitarget prop- PhGs are characterized by at least one glycosyl moiety at their core, which determines their properties. Tese com- erties in the previous reports [19, 20]. Biomarkers of ox- pounds are water soluble and easy to extract via traditional idative damage associated with human diseases are methods. It is also the case that water extraction technology summarized . Few studies clarify the antioxidative is widely used in the production of TCM . Te resulting mechanism of C. tubulosa. Hence, the network pharma- water extracts (WEs) are formulated into various dosage cology technology was adopted to investigate bioactive forms such as tablets, granules, capsules, and mixtures. molecules of C. tubulosa and mechanisms of C. tubulosa Inevitably, the loss of biological ingredients occurs during against oxidation. such a large-scale production process. Tis is why quality In this study, the chromatographic fngerprints and antioxidant activities of HMs, WEs, and HRs from 11 assessment is an indispensable step and is required to ensure the quality of semifnished products from processes. Some batches of C. tubulosa were evaluated simultaneously via HPLC and antioxidant assays. A spectrum-efect re- researchers have already utilized these residual materials via structural modifcation. Astragalus membranaceus residue lationship between the HPLC fngerprints and the anti- was purifed to produce a polysaccharide that improved oxidant efects of C. tubulosa was revealed clearly via cognitive dysfunction by altering gut microbiota in diabetic a series of correlation analyses. Existing studies mainly mice . A neutral polysaccharide extracted from Codo- report on the antioxidative properties of C. tubulosa herbs nopsis pilosula residue exhibited a hypoglycemic efect . [22–24], but few of them highlight the antioxidant ca- Large amounts of herbal residues (HRs) are manufactured in pabilities of the HEs. In addition, the role of HRs might be understated, and this study provides a new opportunity to China. Te reutilization of HRs has become a new and novel research feld as TCM processes have undergone modern- take advantage of new research in this feld. Te purpose of this research was to identify the major active in- ization . Te potential for diferences between the an- tioxidant properties of various herbs and their WEs has gredients within and the antioxidant activities of HMs, Journal of Analytical Methods in Chemistry 3 WEs, and HRs of C. tubulosa. Ten, chemometrics was dried at 50 C to give the HRs. Figure 1 shows the procedure applied to identify spectrum-efect relationships for the for preparing WEs and HRs. HMs, WEs, and HRs from 11 batches of C. tubulosa. Tis is the frst time that diferences among HMs, WEs, and 2.3. HPLC Condition. Chromatography was performed HRs of C. tubulosa have been studied in this manner. In using a Vanquish Horizon UHPLC (Termo Fisher Sci- addition, the network pharmacology analysis was per- entifc, Massachusetts, USA) with an ultraviolet detector and formed to elucidate the underlying mechanisms of an ACQUITY UPLC BEH C column (2.1 mm × 100 mm, C. tubulosa in the treatment of antioxidant-related 1.7 μm) at 30 C. Te mobile phase consisted of 0.1% diseases. phosphoric acid solution (A) in acetonitrile (B) in gradient elution mode as follows: 0–8 min 5%–13% B, 8-9 min 13%– 2. Materials and Methods 15% B, 9–19 min 15% B, 19–20 min 15%-5% B, and 20–26 min 5% B. Te fow rate was 0.3 mL/min, the sample 2.1. Materials and Reagents. Eleven batches of Cistanche injection volume was 1 μL, and the detector wavelength was tubulosa (S1–11) were supplied by the Guangdong E-Fong set to 238 nm. Pharmaceutical Co. Ltd. (Foshan, China). A hydroxyl radical scavenging capacity kit (number: ml076360, specifcation: 2.4. Preparation of Samples and Standards for HPLC Analysis 48T), superoxide anion radical scavenging capacity kit (number: G0129F, specifcation: 48T), and 1,1-Diphenyl-2- 2.4.1. Preparation of Sample Solutions. Sample solutions picrylhydrazyl radical scavenging capacity kit (number: were prepared according to Zhen et al. with modifcations JN6547, specifcation: 48T) were purchased from Shanghai . Cistanche tubulosa herbs and the dregs were ground Enzyme-linked Biotechnology Co., Ltd. (Shanghai, China); into powder (65 mesh). Te pulverized samples (1.0 g) were Suzhou Grace Biotechnology Co., Ltd. (Suzhou, China); and soaked for 30 min and extracted with 50 mL of 50% aqueous Shanghai Jining Industrial Co., Ltd. (Shanghai, China), methanol in an ultrasonic bath for 40 min (250 W, 40 kHz). respectively. Te solutions were then fltered through a 0.22-μL micro- HPLC-grade methanol and acetonitrile were from porous membrane. Ten, the samples of WEs (0.2 g) were Merck (Darmstadt, Germany), and HPLC-grade phosphoric extracted with 50 mL of 50% aqueous methanol in an ul- acid was purchased from Tianjin Kemiou Chemical Reagent trasonic bath for 30 min (250 W, 40 kHz). Te solutions were Co., Ltd. (Tianjin, China). Geniposidic acid (111828–201805, then fltered through a 0.22-μL microporous membrane. purity: 98.1%), tubuloside A (19051602, purity: 99.49%), and isoacteoside (19092702, purity: 98.58%) were purchased from Chengdu GLP Biotechnology Co., Ltd. (Chengdu, 2.4.2. Preparation of Standard Solutions. Appropriate China). Verbascoside (111530–201914, purity: 95.2%) and amounts of fve reference compounds were dissolved in 50% echinacoside (111670–201907, purity: 91.8%) were pur- aqueous methanol and then fltered through a 0.22-μL chased from the National Institutes for Food and Drug microporous membrane to yield a mixed standard solution. Control (Beijing, China). Te water in the experimental Upon adding 50% aqueous methanol to a 10-mL volumetric studies was purifed using a Merck Millipore purifcation fask, the mixed standard solution contained geniposidic system (Merck, Darmstadt, Germany). All other chemicals acid, echinacoside, verbascoside, tubuloside A, and iso- were of analytical grade. acteoside. Pure reference compound solutions were injected into the HPLC system for qualitative analysis, and their retention times were recorded. Comparing retention times 2.2. Collection of WEs and HRs. WEs were prepared as allowed reference compounds to be identifed. described in the previous article with modifcations [25–27]. Herbs (100 g) were extracted with water at a ratio of 1 :10 2.5. Methodology Validation (w/v) in a ceramic container and heated for 2 hours. After fltration, the extract and wet material were separated. Te 2.5.1. Precision, Reproducibility, and Stability. Te powder extraction process was repeated using water at a ratio of 1 : 8 of HM1 was prepared as described in Section 2.4. Method (w/v) and the resulting material was heated for 1 hour. Te precision was evaluated using six successive injections of one two separate extracts were combined. Te mixed extracts sample solution, while reproducibility was estimated by were concentrated using a rotary evaporator to yield performing six replicates of a sample. Stability tests were a creamy solution with a density of 1.05 g/cm³. An appro- performed by replicating injections of one sample solution priate amount of maltodextrin was added. Spray dryers have that had been kept at 15 C for 0, 2, 4, 8, 12, and 24 h. fast drying speeds and good product performance. Spraying atomizes the liquid material into dispersed particles, thereby increasing its surface area. Contacting hot air facilitates the 2.5.2. Linearity. Te mixed reference solutions with diferent drying process very quickly. A Buchi B-290 spray dryer gradient concentrations were injected and analyzed. Te con- (Buchi, Switzerland) was used to spray dry the mixture. Te centration ranges for geniposidic acid, echinacoside, verbasco- inlet and outlet temperatures were set to 175–205 C and side, tubuloside A, and isoacteoside were 0.0011–0.3414 mg/mL, 85–95 C, respectively. Te WEs were collected. During 0.0081–2.421 mg/mL, 0.001–0.3132 mg/mL, 0.0005–0.1518 mg/ processing of the WEs, the wet residues were collected and mL, and 0.0004–0.1116 mg/mL, respectively. Analytical curves 4 Journal of Analytical Methods in Chemistry Maltodextrin Water added Drying Chamber Herbal materials Heating Concentration Spray-drying Drying Herbal residues Water extracts Figure 1: Te procedure of processing raw materials of C. tubulosa into diferent forms. for each standard were obtained by considering the correlation (A) values were recorded. Te 50% inhibiting concentration between the peak area (y) and concentration (x, mg/mL) using (IC ) was calculated using GraphPad Prism 8 (GraphPad a linear least squares model. Software, California, USA). 2.5.3. Sample Recovery. Sample recovery was investigated by 2.7.1. DPPH Assay. First, 0.1 g of HM, WE, and HR powders adding an accurate amount of standard solution to 0.5 g of were extracted using 1 mL of an 80% aqueous methanol HM1 sample powder. Nine samples were prepared in par- solution. Te resulting material was sonicated for 30 min and allel according to Section 2.4. Te mean sample recovery of centrifuged at 12, 000 × g for 5 min. A 400 μL sample was each component was determined. mixed with the working fuids (Table S1), and a 1-mL cuvette was prepared. After the reaction in the dark at 25 C for 30 min, the absorbance at 517 nm was recorded and con- 2.5.4. Sample Determination. As described in Section 2.4, verted to radical scavenging activity (S ) as follows: DPPH HMs, Wes, and HRs were prepared in parallel. Tese sample solutions were injected following the chromatographic A − A sample control S (%) � 1 − × 100%. (1) conditions described in Section 2.3. Te peak area was DPPH blank recorded and the contents were calculated. Te data were analyzed using GraphPad Prism 8 (GraphPad Software, Dehydrated ethanol was used to adjust to zero. California, USA). p values were calculated using the one-way analysis of variance followed by the Tukey method. p < 0.05 •− was considered statistically signifcant. 2.7.2. O Assay. First, 0.1 g of HM, WE, and HR powders were extracted using 1 mL of an 80% aqueous ethanol so- lution. Te resulting material was sonicated for 30 min and 2.6. Fingerprint Establishment and Evaluation. HPLC centrifuged at 12, 000 × g for 5 min. A 100 μL sample was chromatographic data were output from Chromeleon 7.2.8 added into the working fuids (Table S2). After the reaction Software (Termo Fisher Scientifc, Massachusetts, USA) in was allowed to proceed at 37 C for 10 min, the absorbance at CDF and TXT format. Te HM-WE, WE-HR, and HM-HR 570 nm was recorded and converted to radical scavenging similarity values were calculated using a similarity evalua- activity (S •−) as follows: tion system designed for chromatographic fngerprints A − A within TCM Software (Version 2004A). HPLC fngerprints sample control S •−(%) � 1 − × 100%. (2) were drawn using Origin 2021 Software (OriginLab, 2 blank Massachusetts, USA). Purifed water was used to adjust to zero. 2.7. Antioxidant Activity Evaluation. Te measurement procedures for the antioxidant level were conducted 2.7.3. OH• Assay. First, 0.1 g of HM, WE, and HR powders according to the instructions provided in the various kits. were extracted using 1 mL of diluent from the manufac- Te absorbance values were measured using a Shimadzu turer’s kit. Te resulting material was sonicated for 30 min UV-2600i (Shimadzu, Japan). Each sample was run in and centrifuged at 12, 000 × g for 5 min. Te working fuids triplicate, and the average data were recorded. Various were mixed quickly to avoid over color rendering. Ten, sample concentrations and their corresponding absorbance a 250-μL sample solution was transferred to the working Journal of Analytical Methods in Chemistry 5 2.9.2. Construction of a Component-Target Network. Te fuids (Table S3). After incubation at 37 C for 20 min, the absorbance at 536 nm was recorded, and the radical scav- keyword “antioxidant” was used to search for disease-related targets on the GeneCards database (https://www.genecards. enging activity (S ) was determined as follows: OH• org/) and OMIM database (https://omim.org/). Te in- A − A sample control tersections of genes between active components and disease- S (%) � × 100%. (3) OH• A − A blank control related targets were visualized using a Venn diagram online (https://bioinformatics.psb.ugent.be/webtools/Venn/). Te Purifed water was used to adjust to zero. bioactive ingredient targets of C. tubulosa were mapped to the target genes using Cytoscape 3.9.1 software (https:// cytoscape.org/) for constructing the component-target 2.8. Data Analysis (C-T) network. 2.8.1. PLSR Analysis. Te main chromatographic peak areas served as the independent variables (X) and the levels of an- 2.9.3. Gene Ontology and Kyoto Encyclopedia of Genes and tioxidant activity for the various assays were the dependent Genomes Enrichment Analyses. Gene ontology (GO) en- variables (Y). PLSR modeling was performed using Un- richment in biological processes (BP), cellular component scrambler X 10.4 Software (CAMO Software, Bangalore, In- (CC), and molecular function (MF), and kyoto encyclopedia dia). Te weighted regression coefcients revealed correlations of genes and genomes (KEGG) pathway enrichment were between the peak areas and antioxidant activity levels, and the analyzed online using the Metascape database (https://www. raw regression coefcients defned the model equation. metascape.org/) with the “Homo sapiens” setting. Te vi- sualization bubble chart and GO histogram were formed 2.8.2. BCA Analysis. Peak areas were the independent online (https://www.bioinformatics.com.cn/). variables (X), and the antioxidant levels for the various assays were treated as the dependent variables (Y). Ten, the 2.9.4. Establishment of Protein-Protein Interaction and BCA between X and Y was analyzed using a Pearson model. Component-Target-Pathway Networks. Te overlapping Tis procedure was performed using SPSS statistical soft- antioxidation-related and predicted targets from active ware (SPSS for Windows 26.0, SPSS Inc., San components were used to construct a protein-protein in- Francisco, USA). teraction (PPI) using the STRING database (https://stringdb. org/). Te conditions were set as described by Xin et al. . Te PPI network was visualized using the Cytoscape software. 2.8.3. Heatmap Chart, Venn Chart, and RDA. Heatmap Degree centrality (DC), betweenness centrality (BC), and charts were drawn using GraphPad Prism 8 (GraphPad closeness centrality (CC) were calculated through the “net- Software, California, USA). Based on the PLSR and BCA work analysis” function. DC, BC, and CC were set as >100, models, the relationship values between the peak area and >0.03, and >0.3, respectively. According to KEGG pathways the antioxidant capabilities of 11 peaks were ranked from and target genes, Cytoscape software was used to construct large to small, and the top fve grades were recorded. Tese a component-target-pathway (C-T-P) network. peaks were used to draw Venn diagrams online (https:// bioinformatics.psb.ugent.be/webtools/Venn/). Te data for the various peak areas and antioxidant levels for the three 3. Results and Discussion forms of C. tubulosa were visualized via RDA. Te RDA tests 3.1. HPLC Fingerprints were performed using CANOCO Software (Biometris— Plant Research International, Wageningen, Te 3.1.1. Method Validation. Te validation for the HPLC Netherlands). method showed that the relative standard deviation (RSD) for method precision, reproducibility, and stability was less than 2.85% for the relative peak area (n � 11) and 0.77% for 2.9. Network Pharmacology Analysis the relative retention time (n � 11). Te precision of the same 2.9.1. Screening for Active Ingredients of C. tubulosa. All the sample solution appeared within the range of 0.05–0.77% for chemical constituents of C. tubulosa were obtained using relative time and 0.28–2.70% for the relative area of the traditional Chinese medicine systems pharmacology common peaks. Te reproducibility of the experiment was (TCMSP, https://www.tcmsp-e.com/). Te screening thresh- within the range of 0.03–0.20% for the relative time and olds of each chemical component were set as oral bio- 0.23–2.59% for the relative area of the common peaks. Te availability (OB)≥ 30% and drug-likeness (DL)≥ 0.18, sample stability was 0.09–0.24% for relative retention time respectively. Te InChIKey of bioactive ingredients was col- and 0.75–2.85% for the relative area of the common peaks. lected through the PubChem database (https://pubchem.ncbi. Tese results indicated that the established fngerprint was nlm.nih.gov/). Te protein targets of the active compounds satisfed. Te linear relationships for geniposidic acid, were screened out through the SwissTargetPrediction database echinacoside, acteoside, tubuloside A, and isoacteoside are (https://www.swisstargetprediction.ch/). Te target names shown in Table S4. Te value of R square was 1.0000, in- were converted into gene names using the UniPort protein dicating good linearity. Te results of sample recovery database (https://www.uniprot.org/). showed that the average recoveries of geniposidic acid, 6 Journal of Analytical Methods in Chemistry thermal stability of verbascoside is investigated by moni- echinacoside, acteoside, tubuloside A, and isoacteoside were 100.37%, 103.59%, 98.46%, 100.81%, and 101.19%, and the toring the changes in the peak area through HPLC during the heating process. After heating for 4 h, 41.6% of ver- RSD for sample recoveries was less than 2.68%. bascoside is left. It indicates that verbascoside is thermo- sensitive . Isoacteoside, tubuloside A, and echinacoside 3.1.2. Peak Area (PA) and Relative Retention Time (RRT). in WEs remained stable after complex processing pro- Te reference fngerprints and fngerprints of HMs, WEs, cedures. During the long-term drying process, the accu- and HRs from 11 batches of C. tubulosa are presented in mulation of PhGs showed a signifcant decrease, which Figure 2. Eleven peaks, which exhibited good separation and might be attributed to the thermal degradation of these resolution, were identifed as common peaks among HMs, thermosensitive components . In terms of the other WEs, and HRs. Te fve standard compounds were identifed target components, HRs and WEs did not difer signifcantly as geniposidic acid (A ), echinacoside (A ), acteoside (A ), 2 8 9 except for verbascoside. Our understanding of this difer- tubuloside A (A ), and isoacteoside (A ). Te standard 10 11 ence will enable us to develop better quality standards for compound, echinacoside, which was present in all chro- herbal dregs in the future and advance them into products. matograms (average retention time 12.86 min) with a suit- able peak area and good stability, was selected as the reference peak and used to calculate the relative retention 3.1.4. Fingerprint Similarity Analysis. Te similarities among the three C. tubulosa groups were evaluated. Te times (RRTs) of the other ten common peaks. Te RRTs of these diferent forms are in the 0.16–1.51 range. Te PA and herbal material-water extract, herbal material-herbal resi- due, and water extract-herbal residue similarity values were coefcient of variance (CV%) of these common peaks are listed in Tables S5–S7. From the data, the CV% values for PA in the ranges 0.943–0.994, 0.847–0.995, and 0.938–1.000, respectively (Table 3). in various forms are 25.78%–142.02%, 23.36%–150.38%, and 28.91%–112.78% for HMs, WEs, and HRs, respectively. Tese results reveal signifcant diferences in the concen- 3.2. Antioxidant Activity Test Results. Te antioxidant ac- tration of each Cistanche tubulosa compound among the tivities of the various forms of C. tubulosa were determined diferent forms. Te fngerprints of HMs, WEs, and HRs are •− using the DPPH, O , and OH• scavenging capacity assays, shown in Figure 3. and the relevant results are presented in Figure 5. In •− Table S8, the ranges for the DPPH, O and OH• scavenging 3.1.3. Contents of HMs, WEs, and HRs. Five standard capacity assay results were 0.04–37.80, 0.98–843.90, and constituents of C. tubulosa were measured. Te contents of 0.32–27.65 mg/mL for the three diferent forms among the the main components are shown in Table 1. Te comparison 11 batches of C. tubulosa. In three antioxidant activity tests, between HMs, WEs, and HRs is shown in Table 2 and HMs and WEs exhibited close inhibition activity, whereas Figure 4. PhGs in C. tubulosa are biologically active but HRs showed the weakest inhibition. thermosensitive. Heat-sensitive components dissolving in Te spray-dried WEs were found to exhibit signifcant water can be efciently extracted using a reasonable method. activities even at low concentrations. A previous report Generally, Cistanche herba is extracted with water and then indicated that a spray-driedVernonia amygdalina WE evaporated into a concentrated solution for the following achieved 50% scavenging inhibition at 0.17 mg/mL . Te chemical analysis [26, 27, 30]. After extraction and con- application of long extraction times and high temperatures is centration, spray-drying technology was used and the a double-edged sword. On the one hand, increasing the procedure was modifed from the previous article. Water extraction time and spray drying inlet temperature improves was quickly removed from the liquid steam, and then dry the yield and efciency. Moreover, the extracts achieve extracts of raw materials from plants were obtained. In this strong antioxidant activity and higher concentrations of step, the addition of maltodextrin is considered as a com- biological components than those plants . On the other mon carrier to enhance the dispersion and extend the hand, excessively hot inlet air degrades the bioactive com- storage time. Trough a series of manufacturing processes, pounds. Such elevated air inlet temperatures led to losses of herbal plants were then pressed into formula granules with antioxidant Bidens pilosa extract activity and were attributed additives. Tis step of adding excipients was not included in to decreases in phenolic compounds . Present results are the experiment. Generally speaking, our production process consistent with the aforementioned report. For instance, the includes extraction, concentration, and spray drying, as WE in S6 exhibited weaker radical inhibitory abilities than described in Section 2.2, in parallel with a formula granule both HM and HR. Furthermore, HR in S5 exhibited stronger production process. In order to produce these semifnished DPPH and superoxide anion scavenging abilities than HM products, the above three steps must be followed. Te and WE. Te structure of PhGs consists of glycosidic bonds procedure of forming WEs involves concentration and and acetyl groups that are hydrolyzed easily under enzymatic spray-drying, which easily cause the loss of thermosensitive action or decomposed at high temperatures. Tese reactions components, but HRs are obtained after extraction and may account for decreases in some main components during drying of HMs. We wonder whether it is possible that active large-scale production. However, the hydrolysis or isom- components remain in HRs. According to our results, the erization of certain components might accelerate the syn- content of verbascoside reduced signifcantly from HMs to thesis of other components. Such transformations are WEs and HRs (p < 0.05 and p < 0.01, respectively). Te common when processing Cistanches herbs [36–38]. PhGs HM1 HM2 HM3 HM4 HM5 HM6 HM7 HM8 HM9 HM10 HM11 WE1 WE2 WE3 WE4 WE5 WE6 WE7 WE8 WE9 WE10 WE11 Journal of Analytical Methods in Chemistry 7 A8 Echinacoside A10 Tubuloside A A9 Verbascoside A1 Geniposidic acid A11 Isoacteoside 0 5 10 15 20 t, min Figure 2: HPLC fngerprints of standard samples. HM 0 5 10 15 20 25 (a) WE 05 10 15 20 25 (b) Figure 3: Continued. U, mAV HR1 HR2 HR3 HR4 HR5 HR6 HR7 HR8 HR9 HR10 HR11 8 Journal of Analytical Methods in Chemistry HR 0 5 10 15 20 25 (c) Figure 3: HPLC fngerprints of 11 batches of C. tubulosa samples. being water-soluble implies that most biological compo- A are the common peaks shared by HM, WE, and HR nents can be utilized via water extraction. Te contention (Figures 7(d)–7(f)). Notably, the overlaps in the Venn di- that the majority of the active components remain in WEs agram indicate that the BCA model appears more suitable has persisted for decades, so it seems reasonable to assume than the PLSR model, the former exhibiting more repetition. that the wet residual materials can be discarded after ex- Te BCA model coefcients and antioxidant ability IC traction. However, it is incorrect to regard HRs of values were analyzed via RDA. As the RDA shown in C. tubulosa as waste. Researchers point out that PhGs are Figure 8, A , A , and A from HM and HR are related 1 3 6 unstable, and they are susceptible to enzymatic or hydrolytic positively to the antioxidant indexes, except that A is related degradation . Hydrolysis or isomerization reactions that negatively to the hydroxyl radical scavenging capacity. A contribute to decreases in biological ingredients within and A from WE have strong correlations with DPPH and phytomedicines during processing might at the same time the superoxide anion. Te A peaks noted from the various present new opportunities for exploiting HRs. By converting forms exhibit the strongest connection to the DPPH, su- traditional extraction methods, medicinal residues can be peroxide anion, and hydroxyl radicals. A and A also exhibit 1 3 developed and utilized more efectively. Enzymatic hydro- a similar connection. lysis was performed to convert the Panax ginseng residue into monosugars. Yields of polysaccharides and ginsenosides 3.4. Network Pharmacology-Based Analysis increased, such as sugar, succinic acid, ginseng poly- saccharides, and ginsenosides . Sophora favescens res- 3.4.1. Construction of C-T Network. A total of 4359 targets idues are reextracted by ultrasonic waves with ethyl acetate related to the antioxidant activity were obtained from the . Te updated technologies for utilizing herbal residues GeneCards database and the OMIM database. At the same are summarized by Huang et al. . time, active components were screened from the TCMSP database and the SwissTargetPrediction database. Ten, 3.3. Spectrum-Efect Relationship. Te spectrum-efect re- 198 targets were collected and standardized through the lationships between chromatographic peaks and antioxidant UniPort database. Tere were 159 target genes shared by abilities were revealed using PLSR (regression equations active components and antioxidant-related diseases obtained using the PLSR model can be seen in Supple- (see Figure S1). Te C-T network was constructed to il- mentary Materials) and BCA models. Te heatmap diagram lustrate the correlation between the compounds and the was drawn to visualize the relationship (Figure 6). Te re- key gene targets (Figure 9). lationship values and ranks are listed in Table 4. Based on the PLSR and BCA results, the top fve peaks of diferent forms were screened using the DPPH, superoxide 3.4.2. Construction of the PPI Network and Screening of Key anion, and hydroxyl radical scavenging assays to identify the Targets. PPI was visualized using the STRING database most important peaks. Te results are illustrated in the Venn (Figure 10). Te network included 159 nodes and 2528 chart (Figure 7). A , A , A , and A are the common peaks edges. In the entire interaction network, the connecting 2 6 8 10 that are shared by HM, WE, and HR (Figures 7(a) and 7(c)) components or the nodes with more target points may be the in the superoxide anion and hydroxyl radical scavenging key component or target gene that plays an antioxidant role assays, whereas HM, WE, and HR share no DPPH assay in C. tubulosa. Te results were downloaded and introduced peaks. Meanwhile, the BCA models show that A , A , A , and into Cytoscape for visualization. Te higher the DC value, 1 2 3 Journal of Analytical Methods in Chemistry 9 Table 1: Contents of 11 batches of C. tubulosa. HM WE HR Geniposidic Echinacoside Verbascoside Tubuloside Isoacteoside Geniposidic Echinacoside Verbascoside Tubuloside Isoacteoside Geniposidic Echinacoside Verbascoside Tubuloside Isoacteoside (mg/g) acid (mg/g) (mg/g) (mg/g) A (mg/g) (mg/g) acid (mg/g) (mg/g) (mg/g) A (mg/g) (mg/g) acid (mg/g) (mg/g) (mg/g) A (mg/g) S1 1.02 30.54 5.30 4.64 1.10 1.98 57.58 5.13 5.58 8.09 0.34 20.09 1.92 2.81 2.92 S2 1.99 5.99 1.34 0.11 0.24 2.51 8.59 1.07 — 1.39 0.55 2.05 0.23 — 0.37 S3 1.58 8.80 2.19 0.25 0.41 2.01 15.85 2.02 0.60 1.85 0.34 5.16 0.58 0.17 0.60 S4 7.89 18.43 2.50 1.17 0.90 8.96 35.41 1.61 1.21 3.72 0.77 11.15 0.81 0.86 0.95 S5 0.97 32.31 6.46 2.67 0.95 1.38 13.01 1.58 0.43 1.52 0.30 9.74 1.22 0.87 1.00 S6 0.39 16.82 4.62 0.26 1.15 0.45 14.00 2.31 0.29 2.50 0.06 11.62 1.50 0.81 1.63 S7 0.69 34.69 6.45 3.75 1.24 0.70 13.83 1.33 0.63 1.53 0.19 9.99 1.08 1.03 0.92 S8 0.60 12.00 3.53 1.18 0.37 0.50 6.53 0.57 — 1.15 0.12 1.70 0.17 — 0.32 S9 0.59 75.95 7.14 3.48 1.52 1.03 127.43 5.89 4.46 11.80 0.34 24.70 1.30 0.93 2.08 S10 0.58 9.43 3.21 0.42 0.66 0.53 16.35 3.12 0.39 3.19 0.22 2.72 0.43 0.23 0.44 S11 0.42 2.18 0.98 0.11 0.13 0.79 4.55 0.92 — 0.62 0.25 2.28 0.38 — 0.41 10 Journal of Analytical Methods in Chemistry Table 2: Comparison of contents of main components (n � 11). Components HM WE HR c a Geniposidic acid (mg/g) 1.52 ± 2.17 1.9 ± 2.45 0.32 ± 0.2 Echinacoside (mg/g) 22.47 ± 20.9 28.47 ± 36.2 9.2± 7.64 c a b Verbascoside (mg/g) 3.97 ± 2.16 2.32 ± 1.73 0.87 ± 0.57 Tubuloside A (mg/g) 1.64 ± 1.68 1.24 ± 1.92 0.7± 0.81 Isoacteoside (mg/g) 0.79 ± 0.45 3.4 ± 3.46 1.06 ± 0.83 a b c indicates p < 0.05 versus HM, indicates p < 0.001 versus HM, and indicates p< 0.05 versus WE. Tubuloside A Echinacoside Verbascoside Geniposidic acid *** ns * ns ns ns ns ns * * 10 6 0 0 0 0 HM WE HR HM WE HR HM WE HR HM WE HR HM HM HM HM WE WE WE WE HR HR HR HR (a) (b) (c) (d) Isoacteoside ns ns ns HM WE HR HM WE HR (e) ∗ ∗∗∗ Figure 4: Content determination of fve components from diferent forms (n � 11). p < 0.05, p < 0.001, ns: not signifcant. Table 3: Similarities of HM-WE, HM-HR, and WE-HR for 11 batches of C. tubulosa. Batches Samples S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 HM-WE 0.985 0.989 0.981 0.970 0.963 0.974 0.973 0.943 0.994 0.967 0.959 HM-HR 0.984 0.974 0.933 0.847 0.989 0.972 0.991 0.934 0.995 0.966 0.898 WE-HR 0.998 0.999 0.979 0.938 0.973 0.968 0.988 0.997 1.000 0.983 0.979 Content (mg/g) Content (mg/g) Content (mg/g) Content (mg/g) Content (mg/g) Journal of Analytical Methods in Chemistry 11 O � DPPH � OH 40 1000 0 0 0 HM WE HR HM WE HR HM WE HR HM HM HM WE WE WE HR HR HR (a) (b) (c) Figure 5: Column chart of IC50 of diferent forms for 11 batches of C. tubulosa samples. A1 A1 0.5 A2 A2 0.5 A3 A3 A4 A4 A5 A5 A6 A6 A7 A7 A8 A8 A9 A9 -0.5 A10 A10 -0.5 A11 A11 HM WE HR HM WE HR HM WE HR HM WE HR HM WE HR HM WE HR - - DPPH O � � DPPH O � � OH OH 2 2 (a) (b) Figure 6: Heatmap diagrams: (a) PLSR model. (b) BCA model. the darker the color, and the larger the combined score growth by downregulating the expression of VEGFA to value, the thicker the edge. We found that RAC-alpha serine/ inhibit angiogenesis , which is closely correlated to the threonine-protein kinase (AKT1), interlukin-6 (IL6), tumor ROS system for ROS induces the expression of VEGF necrosis factor (TNF), and vascular endothelial growth signaling . factor A (VEGFA) were centrally located (Figure 11), in- dicating that they were key targets when active components 3.4.3. Enrichment Analysis and C-T-P Network exerted an antioxidant efect. It is reported that echinacoside Establishment. Te potential antioxidant compounds acted reduces mitochondrial dysfunction via regulation of on numerous biological functions, including BP, CC, and mitogen-activated protein kinases (MAPK) and AKT and MF. In Figure 12(a), the top 10 pathways are shown. Te their phosphorylated forms . Researchers speculated that predicted targets from the PPI network mainly responded to the antidiabetic efect of glycosides of C. tubulosa might be many biological processes, such as organic cyclic com- due to the antioxidant activity of PhGs by downregulating pounds, xenobiotic stimulus, inorganic substances, oxygen proinfammatory cytokines, such as IL-6 and TNF-α . In levels, and positive regulation of the cellular component addition, echinacoside could impair ovarian cancer cell IC (mg/mL) IC (mg/mL) IC (mg/mL) 50 12 Journal of Analytical Methods in Chemistry Table 4: Correlation coefcients of PLSR and BCA models for the peak area and antioxidant assay. •− DPPH O OH• Groups Peaks PLSR Ranks BCA Ranks PLSR Ranks BCA Ranks PLSR Ranks BCA Ranks A1 0.204 2 0.602 1 0.288 2 0.645 1 −0.413 11 0.070 2 A2 0.058 4 0.036 4 0.122 3 0.154 4 −0.096 2 −0.133 4 A3 0.282 1 0.418 2 0.387 1 0.588 2 −0.319 9 −0.111 3 A4 −0.084 7 −0.586 11 −0.037 9 −0.435 9 −0.112 3 −0.570 7 A5 −0.069 6 −0.564 8 −0.012 7 −0.399 7 −0.171 5 −0.609 8 H A6 −0.112 9 0.334 3 0.022 5 0.345 3 −0.257 7 0.162 1 A7 −0.124 10 −0.574 9 0.007 6 −0.358 6 −0.217 6 −0.614 9 A8 0.069 3 −0.418 5 0.029 4 −0.343 5 −0.148 4 −0.533 6 A9 −0.148 11 −0.583 10 −0.064 11 −0.441 10 −0.321 10 −0.669 10 A10 −0.092 8 −0.559 6 −0.022 8 −0.407 8 −0.079 1 −0.501 5 A11 −0.059 5 −0.563 7 −0.047 10 −0.450 11 −0.300 8 −0.702 11 A1 0.246 4 0.089 2 0.331 2 0.571 2 −0.231 11 −0.423 7 A2 −0.578 9 −0.220 7 −0.124 11 −0.148 8 −0.029 1 −0.289 2 A3 −0.666 11 −0.197 6 −0.044 8 0.023 4 −0.099 6 −0.365 3 A4 0.807 1 −0.076 3 0.112 4 0.013 5 −0.108 7 −0.558 10 A5 0.644 2 −0.102 4 0.127 3 0.053 3 −0.127 10 −0.593 11 WE A6 0.114 5 0.115 1 0.343 1 0.605 1 −0.098 5 −0.137 1 A7 0.274 3 −0.157 5 0.009 6 −0.072 7 −0.120 8 −0.557 9 A8 −0.401 8 −0.315 10 −0.073 9 −0.258 10 −0.040 3 −0.366 4 A9 −0.184 6 −0.244 8 0.065 5 −0.045 6 −0.125 9 −0.471 8 A10 −0.626 10 −0.357 11 −0.103 10 −0.282 11 −0.044 4 −0.375 5 A11 −0.342 7 −0.307 9 −0.030 7 −0.199 9 −0.038 2 −0.377 6 A1 −0.249 10 −0.049 2 −0.102 7 0.199 3 −0.251 10 0.053 2 A2 −0.186 9 −0.369 5 0.023 2 −0.107 4 −0.087 5 −0.276 4 A3 −0.323 11 −0.275 3 0.060 1 0.256 2 −0.283 11 −0.134 3 A4 −0.158 8 −0.533 11 −0.215 11 −0.688 11 −0.201 9 −0.689 11 A5 −0.136 7 −0.518 10 −0.164 9 −0.647 10 −0.186 8 −0.683 10 HR A6 0.170 1 0.430 1 −0.017 3 0.287 1 0.180 1 0.499 1 A7 −0.090 5 −0.430 8 −0.172 10 −0.614 9 −0.183 6 −0.632 8 A8 −0.068 4 −0.399 7 −0.048 6 −0.513 7 −0.043 4 −0.499 7 A9 −0.128 6 −0.466 9 −0.117 8 −0.599 8 −0.184 7 −0.645 9 A10 −0.028 2 −0.360 4 −0.046 5 −0.509 6 −0.038 3 −0.495 6 A11 −0.052 3 −0.370 6 −0.035 4 −0.491 5 −0.031 2 −0.473 5 HM WE HM WE HM WE A1 0 A1 A8 A4,A5,A9 A2,A3 A4,A5 A4,A5 0 0 A6 A2,A8,A10 A2,A3 0 A8,A11 A6,A7 0 A6,A11 A10 A10,A11 HR HR HR (a) (b) (c) Figure 7: Continued. Journal of Analytical Methods in Chemistry 13 HM WE HM WE HM WE 0 0 A10 A8 A4,A5,A7 A4,A5 0 A8 A8 A1,A6 A1,A3,A6 A2,A3,A6 A2,A3 0 A2 0 A1 0 A10 A11 A11 HR HR HR (d) (e) (f) •− Figure 7: Venn diagrams of PLSR and BCA model: (a) DPPH assay. (b) O scavenging assay. (c) OH• scavenging assay were analyzed by •− the PLSR model. (d) DPPH assay. (e) O scavenging assay. (f) OH• scavenging assay were analyzed by the BCA model. Te overlapping section was the common peaks shard by HM, WE, and HR. 1.0 1.0 -1.0 -0.8 -0.6 RDA1 (63.63%) 1.0 -0.4 RDA1 (60.86%) 1.0 (a) (b) 0.6 -0.4 -1.0 RDA1 (85.14%) 1.0 (c) Figure 8: RDA between antioxidant ability and peaks: (a) HM of C. tubulosa. (b) WE of C. tubulosa. (c) HR of C. tubulosa. Te intersection angle represents the relevance between the scavenging ability of the free radicals and the peak. Te smaller the angle is, the more relevance there is with the peak of the antioxidant. RDA2 (34.91%) RDA2 (12.12%) RDA2 (32.39%) 14 Journal of Analytical Methods in Chemistry Figure 9: C-T network. Te network showed the correlation between active components and the key gene targets. movement. Te cellular component analysis showed that the To investigate the biological functions of these major genes were mainly related to the membrane raft, extracel- hubs, a pathway enrichment analysis was conducted. From lular matrix, secretory granule lumen, transcription regu- KEGG enrichment results, a bubble diagram was drawn to lator complex, and apical part of the cell. Tese targets are show top 20 pathways. Te larger the spot was, the more also involved in many molecular functions, including DNA- genes were included in the pathway. As shown in binding transcription factor binding, protein homodime- Figure 12(b), the key pathways of C. tubulosa were related to pathways in cancer, lipid and atherosclerosis, AGE-RAGE rization activity, protein domain-specifc binding, and cy- tokine receptor binding. signaling pathway in diabetic complications, chemical Journal of Analytical Methods in Chemistry 15 Figure 10: PPI network. 16 Journal of Analytical Methods in Chemistry Figure 11: Te key targets were screened out according to DC, CC, and BC. 35 Pathways in cancer Lipid and atherosclerosis AGE−RAGE signaling pathway in diabetic complications Chemical carcinogenesis − receptor activation MAPK signaling pathway Platinum drug resistance Relaxin signaling pathway count Transcriptional misregulation in cancer Malaria 0 Calcium signaling pathway ft −log10 (P) Estrogen signaling pathway Insulin resistance 40 cAMP signaling pathway Necroptosis cGMP-PKG signaling pathway Insulin signaling pathway Complement and coagulation cascades Viral myocarditis Leukocyte transendothelial migration Ovarian steroidogenesis Biological process Cellular component Molecular function 20 30 40 50 Enrichment BP CC MF (a) (b) Figure 12: Enrichment analysis: (a) GO enrichment analysis. (b) KEGG enrichment analysis. Enrichment score cellular response to organic cyclic compound response to xenobiotic stimulus response to hormone response to inorganic substance response to oxygen levels positive regulation of cellular component movement response to lipopolysaccharide negative regulation of cell population proliferation response to extracellular stimulus response to wounding membrane ra extracellular matrix secretory granule lumen transcription regulator complex apical part of cell side of membrane dendrite plasma membrane protein complex perinuclear region of cytoplasm organelle outer membrane DNA-binding transcription factor binding protein homodimerization activity serine hydrolase activity protein domain specific binding cytokine receptor binding oxidoreductase activity kinase regulator activity lipid binding protein kinase activity protein heterodimerization activity Pathway Journal of Analytical Methods in Chemistry 17 Figure 13: C-T-P network. carcinogenesis—receptor activation, and MAPK signaling TNF, and VEGFA, were mapped to KEGG pathways asso- pathway. Efects of C. tubulosa on apoptosis and cellular ciated with pathways in cancer. redox homeostasis were investigated. Te data suggest that C. tubulosa can be a promising candidate for anti-colon- 4. Conclusions cancer therapy . C. deserticola extract is found in aged In this study, we primarily probed complex situations when people . considering the spectrum-efect relationships among HM, Figure 13 illustrates the correlation between the pathways WE, and HR of C. tubulosa. Te HPLC fngerprints and and their related targets and the relationship between the antioxidant assays were used to identify the diferences overlapping target genes and biologically active components between Hs, WEs, and HRs of C. tubulosa. According to the of C. tubulosa. A global view of the C-T-P network was HPLC fngerprints, 11 peaks were common among the 11 generated, which consisted of 12 ingredients, 159 targets, and batches of Hs, WEs, and HRs. Geniposidic acid, echina- 20 pathways. Most of the targets were shared by the candidate coside, verbascoside, tubuloside A, and isoacteoside were active compounds. Tese candidate active ingredients with identifed among these peaks. Te contents of these fve high interconnection degrees were responsible for the high components were determined. In addition, the antioxidant interconnectedness of the C-T-P network, especially quercetin efects of the C. tubulosa Hs, WEs, and HRs varied due to the (degree � 131). Te majority of the targets, such as AKT1, IL6, 18 Journal of Analytical Methods in Chemistry alterations in the chemical compositions caused by complex Data Availability manufacturing conditions. Based on diversifed statistical All data generated or analyzed during this study are included models, the spectrum-efect relationship study indicated that in this paper. peak A might be the most decisive component among the three forms of C. tubulosa. Te study was based on network Disclosure pharmacology to explore potential mechanisms of C. tubulosa on antioxidation through screening of com- Xiao-Tong Liu and Dong-Mei Sun are the co-frst authors. pounds, prediction of key targets, construction of networks, and conduction of enrichment analysis. Our results provide Conflicts of Interest a theoretical basis for recycling the herbal residues and the potential of C. tubulosa in the treatment of antioxidant- Te authors declare that they have no conficts of interest. related diseases. Authors’ Contributions Abbreviations Xiao-Tong Liu and Dong-Mei Sun contributed equally to HMs: Herbal materials this study. Xiao-Tong Liu and Dong-Mei Sun performed the WEs: Water extracts experiments, analyzed the data, and wrote the draft. HRs: Herbal residues Wen-Xin Yu conceived and designed the study. Wei-Xiong PhGs: Phenylethanoid glycosides Lin and Liao-Yuan Liu guided the study. Yu Zeng revised the SOD: Superoxide dismutase manuscript. GSH-Px: Glutathione peroxidase NOS: Nitrous oxide system Acknowledgments ROS: Reactive oxygen species Tis study was supported by the Industrial Technology DPPH: 2,2-diphenyl-1-picrylhydrazyl •− Foundation Public Service Platform Project of 2019 (2019- O : Superoxide anion 00902-1-2), which was ofered by the Ministry of Industry OH•: Hydroxyl radicals and Information Technology of the People’s Republic of TCM: Traditional Chinese medicine China. HPLC: High-performance liquid chromatography PA: Peak area Supplementary Materials RRT: Relative retention time RSD: Relative standard deviation Tables S1–S3 shows the experimental procedures for anti- PLSR: Partial least squares regression oxidant assays. HPLC linearity results are shown in Table S4. BCA: Bivariate correlation analysis In Tables S5–S7, peak areas for HMs, Wes, and HRs are RDA: Redundancy analysis displayed, see Table S8 for IC data. Tis fle contains the IC : Half inhibiting concentration PLSR equation. 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