Application of total monoterpene glycosides of Paeonia veitchii Lynch and analysis method for active ingredients in total monoterpene glycosides of Paeonia veitchii Lynch

Abstract

Application of total monoterpene glycosides of Paeonia veitchii Lynch and analysis method for active ingredients in total monoterpene glycosides of Paeonia veitchii Lynch. For the first time, the UPLC-MS / MS technology is adopted in the present invention to establish the fingerprint of total monoterpene glycosides of Paeonia veitchii Lynch from 11 batches of different producing areas, laying a foundation for revealing the effective ingredient group of total monoterpene glycosides of Paeonia veitchii Lynch. Five compounds with muscle-building effects mainly composed of total monoterpene glycosides of Paeonia veitchii Lynch are determined in the present invention, including 4 monoterpene glycoside compounds, and one belongs to the isomer of benzoylpaeoniflorin. Application of total monoterpene glycosides of Paeonia veitchii Lynch in preparing animal feed or medicine for increasing muscle. The present invention establishes a fingerprint-pharmacodynamic correlation model of total monoterpene glycosides of Paeonia veitchii Lynch. While establishing the quality evaluation standard for muscle-building effects based on the fingerprint of the effective part of total monoterpene glycosides of Paeonia veitchii Lynch, it also provides a new idea for screening active ingredients of other pharmacological effects of Paeonia veitchii Lynch. The present invention lays a theoretical foundation for the development of muscle-building foods for fitness people and provides new resources for the development of animal feed additives in animal husbandry.

Description

Technical Field

[0001] The present invention belongs to the field of uses of total monoterpene glycosides of Paeoniae Radix Rubra. Background Art

[0002] Paeoniae Radix Rubra (PRR) is the dried root of Paeonia lactiflora Pall. or Paeonia anomala subsp. veitchii (Lynch) D.Y. Hong & K.Y. Pan of the genus Paeonia in the family Ranunculaceae. It has a slightly fragrant smell, a slightly bitter, sour and astringent taste, and is slightly cold in nature. It belongs to the liver meridian and has the effects of clearing heat and cooling blood, and dispersing stasis and relieving pain. Modern pharmacological studies have shown that Paeoniae Radix Rubra has many pharmacological activities and is extremely widely used. It can be used for the treatment of various diseases, including antibacterial, anti-tumor, anti-muscular atrophy, etc., and has extremely high medicinal value.

[0003] Although there are many reports by domestic and foreign scholars on the treatment of mice with muscle atrophy by Paeoniae Radix Rubra at present, there is no research on the muscle-building effect of Paeoniae Radix Rubra on normal mice. Summary of the Invention

[0004] The present invention provides a compound for building muscle. In addition, by using UPLC-MS / MS and multivariate statistical analysis methods, a "spectrum-effect relationship" model is established to systematically study the muscle-building effect of total monoterpene glycosides of Paeoniae Radix Rubra and explore its main active ingredients. The method of the present invention can further explore various medicinal materials corresponding to the active ingredients of pharmacological effects and determine their pharmacodynamic material basis. The present invention provides a basis for the development of Paeoniae Radix Rubra in fitness food and provides an experimental basis for the development of animal feed that can increase muscle.

[0005] The application of total monoterpene glycosides of Paeoniae Radix Rubra in the preparation of animal feed or drugs for increasing muscle.

[0006] Further limited, the animal is a mammal.

[0007] The present invention also provides an analysis method for the active ingredients in total monoterpene glycosides of Paeoniae Radix Rubra, and the specific steps are as follows:

[0008] Step 1: Measure the total reducing power, ·OH - , ·DPPH, ·O2 - and ABTS + radical scavenging rates, which are set to be equally important. The maximum value of each group of data is taken as 1, and the minimum value is taken as 0. Then all the data are normalized. According to the formula Y = Y1×1 / 5 + Y2×1 / 5 + Y3×1 / 5 + Y4×1 / 5 + Y5×1 / 5, calculate the values and list them, and analyze the strength of antioxidant ability from them;

[0009] Step 2: Conduct tensile strength and swimming time, gastrocnemius muscle and epididymal fat index, and histopathological experiments and obtain the results; use SPSS 29.0 software to process the data involved in the above experiments. Measurement data are expressed in the form of mean ± standard deviation and perform repeated measures analysis of variance on the data, and use the Duncans multiple range test method for one-way analysis of variance. A P value < 0.05 is considered to indicate a significant difference.

[0010] Step 3: Accurately weigh 3.75 g of total monoterpene glycosides powder from different sources and perform the following operations respectively: dilute with 10 mL of 70% (v / v) ethanol, then take 1.0 mL and centrifuge at 12000 r·min -1 at high speed for 5 min, and then filter the supernatant with a 0.22 μm microfiltration membrane and wait for detection.

[0011] Step 4: Obtain UPLC-MS / MS data.

[0012] Step 5: Then process with Xcalbur 4.2 software. By analyzing and comparing the positive and negative ion mass spectra, on the basis of consulting relevant literature, using the information of tandem mass spectrometry, using the ChEMBL database and the PubChem website to determine the substance composition and obtain the accurate relative molecular mass.

[0013] Step 6: Import the total ion chromatograms of total monoterpene glycosides from Paeonia lactiflora Pall. of each producing area into the "Similarity Evaluation System for Traditional Chinese Medicine Chromatographic Fingerprints" (version 2012.130723), and establish the fingerprint of total monoterpene glycosides from Paeonia lactiflora Pall. through the software.

[0014] Step 7: Take the mouse tensile strength coefficient, swimming time, and gastrocnemius muscle index as the reference sequences, and take the common peak areas of total monoterpene glycosides from Paeonia lactiflora Pall. as the comparison sequences. List the common peak areas and data groups of each pharmacodynamic index and input them into the following formula for calculation:

[0015] Select the above indexes as the reference sequences, denoted as x0(K), k = 1, 2, 3,..., m,

[0016] Select the peak areas of the common peaks as the comparison sequences, denoted as x i (K), i = 1, 2, 3,..., n,

[0017] Since the units of the reference sequence and the comparison sequence are different, dimensionless processing is required. The mean normalization method is used to process the reference sequence and the comparison sequence respectively. The formula for calculating the average value is as follows:

[0018]

[0019] Wherein, X(k)-is the result of data meanization, x(k)-is the reference sequence and the comparison sequence, -is the average value of the reference sequence and the comparison sequence,

[0020] X0(k) and X i (k)'s grey correlation coefficient Loi(k) is calculated by the following formula:

[0021] Loi(k) = (△ min + △ max ) / (△oi(k) + ρ△ max )

[0022] Wherein, Loi(k)-is the absolute value of the difference between the two comparison sequences, that is, △oi(k) = |Xo(k) - Xi(k)| (1 ≤ i ≤ m), △ max -is the maximum value among the absolute differences of all comparison sequences, △ min -is the minimum value among the absolute differences of all comparison sequences, ρ-is the resolution coefficient, generally taking 0.5.

[0023] The correlation degree is the average value of the correlation coefficients between the reference sequence and the comparison sequence, and its calculation formula is as follows:

[0024]

[0025] Wherein, roi-is the correlation degree, that is, the average value of the correlation coefficients, n-is the number of samples, Loi(k)-is the grey correlation coefficient;

[0026] Step 8: List the common peaks of each efficacy index and the data grouping of each efficacy index, and perform standardization processing on the data. Input the 13 common peaks (matrix X) of the total monoterpene glycosides effective part fingerprint of Paeonia lactiflora Pall. and the efficacy indexes (matrix Y) of the muscle-building effect of Paeonia lactiflora Pall. into the SPSS 29.0 software, and use the neural network multi-layer perceptron module in the software to conduct correlation research. The former is the covariate and the latter is the response variable. Through the important analysis of independent variables, screen the active ingredients of the efficacy indexes. The peak areas of the total monoterpene glycosides common peaks of Paeonia lactiflora Pall. are used as independent variables (matrix X), and the mouse pulling force coefficient, swimming time, and gastrocnemius muscle index are used as dependent variables (matrix Y). Normalization is calculated according to the following formula:

[0027] X0 = (X - X min ) / (X max - X min ) + 0.0001

[0028] Wherein, X0-is the result of data standardization, X-is the numerical value of each group of data, X min -is the minimum value in each group of data, X max -is the maximum value in each group of data,

[0029] Step 9: Select the antioxidant activity, tensile coefficient, swimming time, and gastrocnemius index, which are closely related to the activity of total monoterpene glycosides in Paeonia lactiflora Pall., as reference sequences for grey relational analysis and neural network analysis to identify the active ingredients.

[0030] Step 10: Use the CORREL function in Excel software to calculate the correlation coefficients between the antioxidant activity, tensile coefficient, swimming time, gastrocnemius index, and the total chromatographic peak area of the pharmacodynamic-related compounds.

[0031] The muscle-building effect of the monoterpene glycosides of Paeonia lactiflora Pall. in the present invention; it is experimentally verified that the monoterpene glycosides of Paeonia lactiflora Pall. have a good muscle-building effect, and a total of 5 components with muscle-building effects are identified. Among them, there are 4 monoterpene glycoside compounds, one of which is an isomer of benzoylpaeoniflorin, and the other three are Albiflorin, 4-O-Galloylalbiflorin, and Isopaeoniflorin; there is 1 tannin compound, which is Pentagalloylglucose. The monoterpene glycoside extracts in Paeonia lactiflora Pall. of the present invention interact with each other and have a certain degree of muscle-building effect on normal mice.

[0032] The present invention first adopted UPLC-MS / MS technology to establish the fingerprint of total monoterpene glycosides in 11 batches of Paeonia lactiflora Pall. from different producing areas, laying a foundation for revealing the effective component group of total monoterpene glycosides in Paeonia lactiflora Pall. By using multivariate statistical analysis methods, a total of 5 compounds with muscle-building effects mainly composed of total monoterpene glycosides in Paeonia lactiflora Pall. were determined. Among them, there were 4 monoterpene glycoside compounds, one of which was an isomer of benzoylpaeoniflorin, and the other three were Albiflorin, 4-O-Galloylalbiflorin, and Isopaeoniflorin; there was 1 tannin compound, which was Pentagalloylglucose. The total peak area of the above 5 peaks was positively correlated with the magnitude of the mouse pulling force coefficient, indicating that the total monoterpene glycosides in Paeonia lactiflora Pall. had muscle-building effects and were related to the contents of the above five compounds. Combining with the pharmacodynamic results, compared with each administration group, the total peak areas of the above 5 compounds in the AB (Aba), DF (Daofu), and CB (Chiba) groups were larger, so the muscle-building effect was better, and it was significantly higher than that of the protein powder (positive) group (P < 0.05). The PG muscle-building effects of the remaining administration groups were equivalent to those of the group administered with protein powder, and there were no significant differences compared with each other (P > 0.05). Combining with the compounds with strong correlation with muscle-building effects screened by network pharmacology in the early stage and the fingerprint results, it was speculated that the muscle-building effect was the result of the combined action of the above 5 compounds. Application of total monoterpene glycosides in Paeonia lactiflora Pall. in the preparation of animal feeds or drugs for increasing muscle. The present invention established a fingerprint-pharmacodynamic correlation model of total monoterpene glycosides in Paeonia lactiflora Pall., and while establishing a quality evaluation standard for muscle-building effects based on the fingerprint of the effective part of total monoterpene glycosides in Paeonia lactiflora Pall., it also provided new ideas for the screening of active ingredients for other pharmacological effects of Paeonia lactiflora Pall. The present invention filled the blank in the research on the muscle-building effect of total monoterpene glycoside active ingredients in Paeonia lactiflora Pall., completed the determination of the muscle-building effect components of the total monoterpene glycoside extract in Paeonia lactiflora Pall., and was of great significance for the further development and resource utilization of Paeonia lactiflora Pall. - laying a theoretical foundation for the development of muscle-building foods for fitness people and providing new resources for the development of animal feed additives in animal husbandry.

[0033] The purpose of the present invention is to provide a basis for the future development of Paeonia lactiflora Pall. in fitness food development and provide experimental evidence for the development of animal feed additives that can increase muscle. The present invention established a fingerprint-pharmacodynamic correlation model of total monoterpene glycosides in Paeonia lactiflora Pall., filled the blank in the research on the muscle-building effect of total monoterpene glycoside active ingredients in Paeonia lactiflora Pall. on normal mice, and was of great significance for the further development and resource utilization of Paeonia lactiflora Pall. Description of the Drawings

[0034] Figure 1 For the determination of total reducing power; Figure 2 For ·OH - Determination of free radical scavenging rate; Figure 3 For the DPPH· free radical scavenging rate; Figure 4 For ·O2 - Determination of free radical scavenging rate;Figure 5 is for ABTS + Determination of free radical scavenging rate; Figure 6 shows the determination results of the pulling force coefficient of mice in the drug administration groups from different origins (%, n = 8), (a) Line graph of the change in the pulling force coefficient of mice at 14 d; (b) Bar graph of the pulling force coefficient of mice at 0 d; (c) Line graph of the pulling force coefficient of mice at 14 d; Figure 7 is for the determination results of the swimming time of mice in the drug administration groups from different origins (s, n = 8); Figure 8 shows the effects of total monoterpene glycosides of Paeonia lactiflora from different origins on the (a) gastrocnemius muscle index and (b) epididymal fat index of mice (%, n = 8); Figure 9 is the pathological section of the gastrocnemius muscle of mice (10×40); Figure 10 is the fingerprint of the effective part of total monoterpene glycosides of Paeonia lactiflora (S1 is SL, S2 is JGDQ, S3 is HH, S4 is DYS, S5 is CF, S6 is HB, S7 is AB, S8 is YJ, S9 is DF, S10 is ZX, S11 is CF); Figure 11 is the graph of the comprehensive analysis intersection result; Figure 12 is the molecular formula of Paeoniflorin; Figure 13 is the molecular formula of Albiflorin; Figure 14 is the molecular formula of Oxypaeoniflorin; Figure 15 is the molecular formula of 1,2,3,6-Tetra-O-Galloylglucos; Figure 16 is the molecular formula of Ellagic Acid; Figure 17 is the molecular formula of Galloylpaeoniflorin; Figure 18 is the molecular formula of 4-O-Galloylalbiflorin; Figure 19 is the molecular formula of Benzoic Acid; Figure 20 is the molecular formula of Pentagalloylglucose; Figure 21 is the molecular formula of Salicylic Acid; Figure 22 is the molecular formula of Azelaic Acid. Specific implementation manner

[0035] Reagents used

[0036] Benzoic acid (purity ≥ 98%, batch number: PS020532), Chengdu Pusi Biotechnology Co., Ltd.; Sodium chloride injection (Jilin Dubang Pharmaceutical Co., Ltd.); Whey protein powder (Anhui Kangente Biotechnology Co., Ltd.); 4% paraformaldehyde fixative (Fuzhou Wenlai Biotechnology Co., Ltd.); Methanol, formic acid, acetonitrile (Thermo Fisher Scientific).

[0037] Instrument

[0038] FA2004 Analytical Balance (Shanghai Hengping Scientific Instrument Co., Ltd.); HPLC Chromatograph (1260 Infinity II) (Agilent Technologies, Inc., USA); Dionex Ultimate 3000 RSLC Liquid Chromatograph, Q-Ecactive Seres Electrostatic Field Orbitrap High-Resolution Mass Spectrometer, HESI-II Ion Source (Thermo Fisher Scientific, USA); Tensile Tester (Weidu Electronics Co., Ltd.).

[0039] Preparation of the Active Fraction from Paeonia lactiflora Pall

[0040] Paeonia lactiflora Pall was purchased from Heilongjiang Province, Inner Mongolia Autonomous Region, Hebei Province, Sichuan Province and Gansu Province in 2021. The reflux extraction method was adopted, and the extraction process was reflux extraction with 70% ethanol (1:10) for 2 times, 2 h each time. The filtrates were combined, filtered and concentrated to obtain the concentrated solution of paeoniflorin monoterpenoids. The crude extract was purified by HPD300 macroporous resin, and the content of total paeoniflorin monoterpenoids was determined by the method of alkaline hydrolysis of benzoic acid. The results of the content of total paeoniflorin monoterpenoids are shown in Table 1.

[0041] Table 1 Source Information of Total Paeoniflorin Monoterpenoids from Paeonia lactiflora Pall

[0042]

[0043] Experimental Design and Methods

[0044] Study on the in Vitro Antioxidant Pharmacodynamics of Total Paeoniflorin Monoterpenoids from Paeonia lactiflora Pall with Different Origins

[0045] Determination of Total Reducing Power

[0046] Add 2.0 mL of the total paeoniflorin monoterpenoid sample solution from different origins, 2.0 mL of phosphate buffer solution with pH 7.2, and 2.0 mL of 1% potassium ferricyanide solution into a test tube respectively. After mixing evenly, water bath at 50 °C for 20 min, then add 2.0 mL of 10% trichloroacetic acid, stand at 25 °C for 10 min, centrifuge at 3000 r·min -1 for 10 min under the condition, take 2.0 mL of the supernatant, add 2.0 mL of pure water and 0.4 mL of ferric chloride in turn and react for 10 min, and measure the absorbance at 700 nm.

[0047] ·OH - Determination of Scavenging Ability

[0048] Add 2 mL of 6 mmol·L -1 FeSO4 solution, 2 mL of the total paeoniflorin monoterpenoid sample solution from different origins and 2 mL of 6 mmol·L-1 H2O2 solution, mix evenly and react in a water bath at 37 °C for 10 min, then add 2 mL of 6 mmol·L -1 salicylic acid-ethanol solution, shake well, let stand in a water bath at 37 °C for 30 min, and measure the absorbance value at a wavelength of 510 nm.

[0049] ·OH - The calculation formula for the scavenging rate is as follows:

[0050]

[0051] In the formula: P%-·OH - scavenging rate; A0-absorbance value with distilled water replacing the sample solution; A s -absorbance value after adding the sample solution; A x -absorbance when the salicylic acid solution is not added.

[0052] Determination of DPPH· free radical scavenging rate

[0053] Add 2 mL of the sample, 2 mL of DPPH solution, and 2 mL of absolute ethanol solution to the test tube in sequence, shake well, and place in the dark at 37 °C for 30 min. Use absolute ethanol as the blank to adjust A to 0.00, and measure the absorbance value at a wavelength of 517 nm.

[0054] Calculate the DPPH· scavenging rate according to the absorbance of the sample using the following formula.

[0055]

[0056] In the formula: P%-DPPH· free radical scavenging rate; A0-blank absorbance value; A1-sample absorbance value; A2-sample blank absorbance.

[0057] ·O2 - Determination of free radical scavenging rate

[0058] Accurately measure 4.5 mL of Tris-hydrochloric acid buffer solution with pH 8.2, place it in a water bath at 25 °C and preheat for 5 min. Operate the test solution according to the data in Table 2, mix evenly, heat in a water bath at 25 °C for 5 min, take it out, and add 0.1 mol·mL to the test solutions with different concentrations every 30 s -1 hydrochloric acid to terminate the reaction. Use an ultraviolet spectrophotometer to measure the absorbance value at a wavelength of 267 nm.

[0059] ·O2 - The calculation formula for the scavenging rate is as follows:

[0060]

[0061] In the formula: P%-·O2- Clearance rate; A s - Absorbance of the sample; A x - Absorbance of the control; A0 - Absorbance of the blank.

[0062] Table 2·O2 - Method for measuring the clearance rate

[0063]

[0064] ABTS + Method for measuring the clearance rate

[0065] Mix 0.8 mL of the ABTS + working solution with 0.2 mL of absolute ethanol and 0.2 mL of the total monoterpene glycoside sample solution from Paeonia lactiflora Pall. of different origins, shake for 10 s, let stand for 6 min, and then measure the absorbance at A = 734 nm.

[0066] ABTS + The formula for calculating the clearance rate is as follows:

[0067]

[0068] In the formula: P% - ABTS + clearance rate; A0 - Absorbance value after mixing 0.8 mL of the ABTS + working solution with 0.2 mL of absolute ethanol; A x - Absorbance value after mixing 0.8 mL of the ABTS + working solution with 0.2 mL of the sample solution.

[0069] Animal grouping

[0070] Male SPF - level KM mice were purchased from the Experimental Animal Department of Harbin Medical University (No. SCXK: 2019 - 001) (Harbin, China) and were raised in the Animal Center of Jiamusi University. All operations of the present invention comply with the "Regulations on the Administration of Experimental Animals". The breeding environment temperature is maintained at 24 ± 1 °C, the relative humidity is maintained at 50 - 60%, and a 12 - h light - dark cycle breeding is maintained. During this period, the rats can drink water and eat freely.

[0071] KM mice were randomly divided into 13 groups, namely the blank group (KB), positive control group (PG), Songling dosage group (SL), Jiagedaqi dosage group (JGDQ), Heihe dosage group (HH), Dayangshu dosage group (DYS), Chifeng dosage group (CF), Hebei dosage group (HB), Aba dosage group (AB), Yajiang dosage group (YJ), Daofu dosage group (DF), Zhangxian dosage group (ZX), and Chiba dosage group (CB), with 8 mice in each group. The mice in the KB group were administered 0.9% normal saline by gavage; according to the instructions of the protein powder, the mice in the PG group were administered the protein powder solution dissolved in distilled water, and the dosage was 0.44 g·kg -1 ·d -1 ; according to the instructions of total glucosides of paeony and the calculated content of total monoterpene glycosides of Paeonia lactiflora from different producing areas obtained previously, the dosage of each dosage group was 68.25 mg·kg -1 ·d -1 , a total of 11 groups.

[0072] Determination of mouse pulling force and swimming time

[0073] After three days of adaptive feeding, the mice were administered drugs by gavage at 8:00 a.m. every day. The body weight of the mice was weighed and recorded, and the drugs were administered continuously for 14 days. The pulling force of the mice was measured on the 0th, 4th, 7th, 10th, and 14th days of drug administration, and the swimming time of the mice was measured on the 14th day.

[0074] Determination of gastrocnemius and epididymal fat indexes

[0075] After drug administration on the last day, the mice were fasted but not water-deprived, and were decapitated on the 15th day. The gastrocnemius and epididymal fat were dissected and weighed, and the gastrocnemius index and fat index were calculated according to the formula.

[0076]

[0077] In the formula, W1 is the gastrocnemius index; m0 is the body weight of the mouse; m1 is the mass of the mouse gastrocnemius; m2 is the mass of the mouse epididymal fat.

[0078] Gastrocnemius and epididymal fat indexes

[0079] The gastrocnemius of the mouse was fixed in 4% paraformaldehyde, embedded in paraffin, and stained with HE. And its tissue changes were observed under a microscope.

[0080] Sample pretreatment and UPLC-MS / MS conditions

[0081] Accurately weigh 3.75 g of total monoterpene glycosides of Paeonia lactiflora powder from each source, and then dilute it to a 10 mL volumetric flask containing 70% ethanol. Take 1.0 mL of the solution and put it into a centrifuge tube. Centrifuge at 12000 r·min -1 at high speed for 5 min. Filter the supernatant with a 0.22 μm microfiltration membrane and wait for detection.

[0082] The chromatographic column was a Thermo Fisher Science Hypersil Gold AQ C18 column (100×2.1 mm, 1.9 μm). Mobile phase A was water containing 0.1% formic acid (v / v), and mobile phase B was acetonitrile containing 0.1% formic acid (v / v). The flow rate of the mobile phase was 0.3 mL·min -1 . The gradient program was as follows: 0 - 1 min, 2% B; 1 - 2 min, 2% - 5% B; 5 - 10 min, 12% - 20% B; 10 - 12 min, 20% - 30% B; 12 - 13 min, 30% - 50% B; 13 - 15 min, 50% - 100% B; 15 - 16 min, 100% B. The injection volume was 5 μL. The mass spectrometry conditions were as follows: the high-resolution mass spectrometry parameters were set as follows: sheath gas pressure (Sheath gas flow rate), 30 psi; auxiliary gas pressure (Aux gas fiow rate), 10 psi; sweep gas pressure (Sweep gas flow rate), 0 psi; capillary voltage (Spray voltage), 3.5 kV; capillary temperature (Capilary temp), 320 °C. AUX gas heating temperature (Aux gas heater temp), 350 °C; the collision gas was nitrogen; the normalized collision energies were 20, 40, 60 eV; s-lens 60.0. The combined selection of full scan of primary mass spectrometry automatically triggered the secondary mass spectrometry scan mode (Fullms-ddms 2 ). Resolution: the resolution of the first and second levels was 70000 FWHM / 17500 FWHM respectively; the ion scanning range was m / z 50 - 1500; the cycle count was 3 times; the quadrupole isolation window was 1.5 m / z; the dynamic exclusion time was 5 s.

[0083] The UPLC-MS / MS data was processed using Xcalbur 4.2 software. By analyzing and comparing the positive and negative ion mass spectra, and on the basis of consulting relevant literature, using the information of secondary mass spectrometry, the composition of substances was determined using the ChEMBL database and the PubChem website to obtain the accurate relative molecular mass.

[0084] Establishment of fingerprint

[0085] The total ion current chromatogram of total monoterpene glycosides from Paeonia lactiflora Pall. from each producing area was imported into the "Similarity Evaluation System for Traditional Chinese Medicine Fingerprints" (version 2012.130723), and the fingerprint of total monoterpene glycosides from Paeonia lactiflora Pall. was established through the software.

[0086] Study on the correlation between spectrum and efficacy based on grey relational analysis

[0087] The present invention uses the mouse pulling force coefficient, swimming time, and gastrocnemius muscle index as reference sequences, and the total monoterpene glycoside common peak area of Paeonia lactiflora Pall as the comparison sequence. The common areas and data of each pharmacodynamic index are grouped and listed in an Excel table, and the following formula is input for calculation.

[0088] Select the above indexes as reference sequences, denoted as x0(K), k = 1, 2, 3, …, m.

[0089] Select the peak area of the common peak as the comparison sequence, denoted as x i (K), i = 1, 2, 3, …, n.

[0090] Since the units of the reference sequence and the comparison sequence are different, dimensionless processing is required. In this article, the method of dimensionless averaging is used to process the reference sequence and the comparison sequence respectively. The formula for calculating the average value is as follows:

[0091]

[0092] In the formula, X(k)- is the result of data mean normalization, x(k)- is the reference sequence and the comparison sequence, - is the average value of the reference sequence and the comparison sequence,

[0093] The grey correlation coefficient Loi(k) between X0(k) and X i (k) is calculated by the following formula:

[0094] Loi(k) = (△ min + △ max ) / (△oi(k) + ρ△ max )

[0095] In the formula, Loi(k)- is the absolute value of the difference between the two comparison sequences, that is, △oi(k) = |Xo(k) - Xi(k)| (1 ≤ i ≤ m), △ max - is the maximum value of the absolute differences of all comparison sequences, △ min - is the minimum value of the absolute differences of all comparison sequences, ρ- is the resolution coefficient, generally taken as 0.5.

[0096] The correlation degree is the average value of the grey correlation coefficients of the reference sequence and the comparison sequence, and its calculation formula is as follows:

[0097]

[0098] In the formula, roi- is the correlation degree, that is, the average value of the correlation coefficients, n- is the sample size, and Loi(k)- is the grey correlation coefficient.

[0099] Spectral effect-related research based on artificial neural network analysis

[0100] List the common peaks of each efficacy index and the data grouping of each efficacy index, and perform standardization processing on the data. Input the 13 common peaks (matrix X) of the total monoterpene glycosides effective part fingerprint of Paeonia lactiflora Pall. and the efficacy index (matrix Y) of the muscle-building effect of Paeonia lactiflora Pall. into SPSS 29.0 software, and use the neural network multi-layer perceptron module in the software to conduct correlation research. The former is the covariate and the latter is the response variable. Through the important analysis of independent variables, screen the active ingredients of the efficacy index. The peak area of the total monoterpene glycosides common peak of Paeonia lactiflora Pall. is used as the independent variable (matrix X), and the mouse pulling force coefficient, swimming time, and gastrocnemius muscle index are used as the dependent variables (matrix Y). Normalization is calculated according to the following formula:

[0101] X0 = (X - X min ) / (X max - X min ) + 0.0001

[0102] In the formula, X0 is the data standardization result, X is the data value of each group, X min - is the minimum value in each group of data, X max - is the maximum value in each group of data,

[0103] Calculation of correlation coefficient

[0104] Use the CORREL function in Excel to calculate the correlation coefficients of the antioxidant capacity scores, mouse pulling force coefficients, swimming times, gastrocnemius muscle indices of the total monoterpene glycoside extracts of Paeonia lactiflora Pall. from different origins and the total peak areas of compounds related to the efficacy results. A result between [-1, 0] indicates a negative correlation between the two, a result of 0 indicates no correlation between the two, and a result between [0, 1] indicates a positive correlation between the two.

[0105] Statistical processing

[0106] Use SPSS 29.0 software to process the data involved in the above experiments. Measurement data are expressed in the form of mean ± standard deviation (-x ± s), and repeated measures analysis of variance is performed on the data, and one-way analysis of variance is performed using the Duncans multiple range test method. P < 0.05 is recorded as having a significant difference.

[0107] Results of in vitro antioxidant efficacy study of total monoterpene glycosides of Paeonia lactiflora Pall. from different origins

[0108] Results of total reducing power determination

[0109] The results of the total reducing power determination of the total monoterpene glycosides of Paeonia lactiflora Pall. from different origins are as Figure 1 shown. The absorbance values of the total monoterpene glycosides of each Paeonia lactiflora Pall. are different. Among them, the absorbance values of the total monoterpene glycosides in the SL, JGDQ, AB, ZX, DF, and CB groups are the highest, indicating that the total monoterpene glycosides in the above 6 groups reduce Fe3+ Reduced to Fe 2+ The strongest ability.

[0110] OH - Determination results of the scavenging ability

[0111] The results are as Figure 2 shown. At the same concentration, the total monoterpene glycosides of Paeonia lactiflora from each origin all have the ability to scavenge ·OH - Among them, the total monoterpene glycosides of Paeonia lactiflora in the JGDQ group have the strongest scavenging ability against ·OH - The total monoterpene glycosides of Paeonia lactiflora produced by SL, HH, and CB also have a scavenging rate of ·OH - higher than 50%.

[0112] Determination results of the DPPH· radical scavenging rate

[0113] The determination results of the DPPH· radical scavenging rate are as Figure 3 shown. The total monoterpene glycosides of Paeonia lactiflora from each origin all have the effect of scavenging DPPH·. Among them, the scavenging rates of the total monoterpene glycosides of Paeonia lactiflora in the HH group and the ZX group against the DPPH· radical are higher than 95%, and the scavenging rates of the total monoterpene glycosides of Paeonia lactiflora produced by JGDQ, AB, DF, and CB against the DPPH· radical are higher than 90%, indicating that the total monoterpene glycosides of Paeonia lactiflora exhibit strong antioxidant activity.

[0114] ·O2 - Determination results of the scavenging rate

[0115] ·O2 - The determination results of the scavenging rate are as Figure 4 shown. At the same concentration, the total monoterpene glycosides of Paeonia lactiflora from each origin all have a certain scavenging ability against ·O2 - Among them, the Paeonia lactiflora produced by AB, DF, and CB have the strongest scavenging ability against ·O2 - The strongest ability.

[0116] ABTS + Determination results of the scavenging rate

[0117] The scavenging effects of the total monoterpene glycosides of Paeonia lactiflora from different origins on ABTS + are as Figure 5 shown. At the same concentration, the total monoterpene glycosides of Paeonia lactiflora from each origin all have a certain scavenging effect on ABTS + Among them, the total monoterpene glycosides of Paeonia lactiflora in the DYS group have the best scavenging effect on the ABTS + radical, higher than 50%.

[0118] Antioxidant ability weight analysis

[0119] To facilitate the final comprehensive scoring, the antioxidant ability is first summarized into a set of data. The total reducing power, ·OH - , ·DPPH, ·O2- With ABTS + The radical scavenging rate of ABTS is set to be equally important. The maximum value of each group of data is taken as 1, and the minimum value is taken as 0, and then all the data is normalized. Since the importance levels are the same, the formula is Y = Y1×1 / 5 + Y2×1 / 5 + Y3×1 / 5 + Y4×1 / 5 + Y5×1 / 5.

[0120] From the final obtained values shown in Table 3, it can be seen that the total monoterpene glycosides of Paeonia lactiflora in the CB group have the strongest antioxidant ability, with a score of 0.83796. In addition, the total monoterpene glycosides of Paeonia lactiflora in the SL, JGDQ, and YJ groups have relatively strong antioxidant abilities, with scores of 0.66502, 0.72616, and 0.60166 respectively; while the total monoterpene glycosides of Paeonia lactiflora from the CF origin have the weakest antioxidant ability, with a score of only 0.24480.

[0121] Table 3 Normalization and comprehensive analysis of antioxidant ability data

[0122]

[0123] Pharmacodynamic study results of the total monoterpene glycosides of Paeonia lactiflora on muscle gain in normal mice

[0124] Determination results of mouse pulling force and swimming time

[0125] After administration, repeated measures analysis of variance was used for the pulling force values of mice in each group on different days. The Mauchly's sphericity test showed P < 0.05, indicating that the data did not meet the sphericity assumption. Multivariate analysis of variance was required, and the results of the multivariate analysis of variance are shown in Table 4. The test results of the four statistics, Pillai's trace, Wilk's Lambda, Hotelling's trace, and Roy's largest root, were consistent, indicating that there were statistically significant differences in the data for different days, and there were significant differences in the pulling force coefficients for different days (P < 0.01). In addition, there was an interaction effect between the group and the days (P < 0.01), indicating that the changes in the pulling force values of mice in each group varied with the administration days.

[0126] Table 4 Results of repeated measures analysis of variance of pulling force coefficients of mice in each group on different administration days

[0127]

[0128]

[0129] The pulling force of mice was measured using a tensiometer, and the results are shown in Figure 6. Set the day before drug administration as 0d. It can be seen that at 0d, there was no significant difference in the pulling force of mice in each group (P>0.05), indicating that the mice in each group could be used for the determination of the subsequent mouse pulling force experiment. On the 4th day of drug administration, the pulling force coefficients of mice in each group, including the KB group, increased. As the number of breeding days increased, the body weight of the mice also increased, and their muscle strength also increased, so the pulling force coefficients of mice in each group increased; the pulling force coefficients of each drug administration group were significantly increased compared with the blank group (P<0.05), and the pulling force coefficients of mice in the AB, DF, and ZX groups were significantly higher than those in the PG group (P<0.05). On the 7th day of drug administration, except for the PG and YJ groups, the pulling force coefficient levels of mice in each group were higher than those in the KB group (P<0.05), and the pulling force coefficient levels of mice in the DYS, AB, DF, and CB groups were higher than those in the PG group (P<0.05). On the 10th day of drug administration, the pulling force coefficient levels of mice in each group were higher than those in the KB group (P<0.05). In addition, the pulling force coefficient levels of mice in the AB and CB groups were significantly higher than those in the PG group (P<0.05). On the 14th day of drug administration, the pulling force coefficient levels of mice in each group were significantly higher than those in the KB group (P<0.05), and the pulling force coefficient levels of mice in the AB, DF, and CB groups were significantly higher than those in the PG group. The above results indicate that total monoterpene glycosides of Paeonia lactiflora can effectively increase the muscle strength of mice.

[0130] Note: Analyzed by Duncan's multiple range test method. Different letters in the same column indicate significant differences. When comparing two groups of data, those without the same letter indicate significant differences, and those with the same letter indicate no significant differences. The same applies hereinafter.

[0131] In addition, we also measured the swimming time of mice in each group, and the results are as Figure 7 shown. Except for the JGDQ, CF, YJ, and ZX groups, the swimming time of mice in the remaining groups was significantly higher than that in the KB group (P<0.05), and the SL, DYS, and HB groups were significantly higher than those in the PG group (P<0.05).

[0132] Results of gastrocnemius muscle and epididymal fat index determination

[0133] The results of the gastrocnemius muscle and epididymal fat indices of mice in each group are shown in Figure 8. Compared with the KB group, the gastrocnemius muscle indices of mice in each group increased compared with it, but there was no significant difference between the PG group and the KB group (P>0.05). Except for the PG group, the gastrocnemius muscle indices of mice in the remaining groups were significantly higher than those in the KB group (P<0.05), and there were significant differences in the gastrocnemius muscle indices of mice in the HH, AB, YJ, DF, ZX, and CB groups compared with the PG group (P<0.05). Compared with the KB group of mice, the epididymal fat indices of mice in the remaining groups were significantly lower than those in the KB group (P<0.05), and there was no significant difference compared with the PG group.

[0134] Histopathological results

[0135] After hematoxylin and eosin (HE) staining of the gastrocnemius muscles of mice in each group, they were observed and photographed under a microscope. The pathological sections of the gastrocnemius muscles of mice in the KB, PG, SL, JGDQ, HH, DYS, CF, HB, AB, YJ, DF, ZX, and CB groups corresponded to A, B, C, D, E, F, G, H, I, J, K, L, and M in Figure 9 respectively (the scale of each figure is as shown in A). As can be seen from Figure 9 , the diameter of the gastrocnemius muscle of mice in the KB group was 29.76 μm. Compared with the mice in the KB group, the diameters of the gastrocnemius muscles of mice in the other groups were all larger than those in the KB group..

[0136] Confirmation of active ingredients

[0137] The UPLC-MS data of total monoterpene glycosides of Paeonia lactiflora from various sources were exported to RAW format using Xcalbur 4.2 software, and then the RAW format data was converted to TXT format. Then, the relevant information (time, signal [MV], peak order, retention time, peak height, peak area) of the total monoterpene glycoside components of Paeonia lactiflora from various sources was exported and imported into TXT (ANSI format) text in a certain order, and extracted through the "Similarity Evaluation System for Traditional Chinese Medicine Chromatographic Fingerprints" (version 2012.130723). The results are as Figure 10 shown. Using the above similarity evaluation system software, a fingerprint of the effective part of total monoterpene glycosides of Paeonia lactiflora with 13 common peaks was established.

[0138] Then, the UPLC-MS data was processed with Xcalibur 4.2 software. By analyzing and comparing the mass spectrometry information in positive and negative ion modes, comparing the secondary ion fragments, referring to relevant literature, and using databases such as ChemSpider, ChEMBL and other databases as well as websites such as PubChem to determine the substance composition and obtain the accurate molecular weight, a total of 13 compounds were identified. The results are shown in Tables 5 and 6.

[0139] Table 5 Identification results of common peaks of Paeonia lactiflora from different producing areas

[0140]

[0141]

[0142]

[0143] Table 6 Peak areas of common peaks of total monoterpene glycoside compounds of Paeonia lactiflora

[0144]

[0145] Continued Table 6:

[0146]

[0147]

[0148] Study on Spectrum-Efficacy Correlation Based on Grey Relational Analysis

[0149] Calculate the normalization results of the original data and the grey correlation coefficients of each index, and list them in Tables 7 and 8. As shown in Table 6, through grey relational analysis and calculation results, it can be seen that peaks 8, 9, 5, 7, 12, 11, 4, 3, 10, 6, 2 and 13 have strong antioxidant ability (correlation degree ≥ 0.8), while peak 1 has no antioxidant ability. Peaks 9, 8, 7, 5, 12, 11, 4, 2, 10, 3, 6 and 13 have a greater effect on the increase of the tensile coefficient of mice (correlation degree ≥ 0.8); Peak 1 has a certain or small effect on the increase of the tensile coefficient of mice. Peaks 7, 9, 8, 1 and 5, 2, 4, 3, 6, 10 and 13 have a greater effect on the increase of the swimming time of mice (correlation degree ≥ 0.8); Peak 1 has a certain or small effect on the increase of the swimming time of mice. Peaks 9, 8, 7, 5, 12, 11, 4, 2, 10, 6, 3 and 13 have a greater effect on the increase of the gastrocnemius muscle index of mice (correlation degree ≥ 0.8); Peak 1 has a certain or small effect on the increase of the gastrocnemius muscle index of mice.

[0150] Table 7 Mean Results of Pharmacodynamic Indexes

[0151]

[0152] Table 8 Correlation Degree between Common Peak Area and Pharmacodynamic Indexes

[0153]

[0154] Note: A correlation degree ≥ 0.8 indicates a greater effect; a correlation degree ≥ 0.7 indicates a certain effect, a correlation degree ≥ 0.6 indicates a small effect, and a correlation degree < 0.6 indicates no effect

[0155] Study on Spectrum-Efficacy Correlation Based on Artificial Neural Network Analysis

[0156] The original data was normalized through artificial neural network calculation and analysis, and the results are shown in Tables 9 and 10. After data modeling and analysis using SPSS 29.0 software, the results of artificial neural network analysis show that the antioxidant capacities of peaks 1, 2, 7, 9, 11, and 13 are relatively strong; peaks 1, 2, 7, 9, 11, and 13 have a greater effect on increasing the tensile coefficient of mice; peaks 11 and 13 have a greater effect on increasing the swimming time of mice; peaks 11 and 13 have a certain or relatively small effect on increasing the gastrocnemius index of mice. In summary, a total of 6 peaks have a contribution rate greater than 50%, namely 1, 2, 7, 9, 11, and 13, indicating that these 6 peaks contribute to the four pharmacodynamic indicators. Among them, 5 compounds were identified, namely Paeoniflorin, Albiflorin, 4-O-Galloylalbiflorin, Pentagalloylglucose, and Isopaeoniflorin.

[0157] Table 9 Matrix Y Standardization Results

[0158]

[0159]

[0160] Table 10 Results of Artificial Neural Network Analysis

[0161]

[0162] Comprehensive Analysis Combining Grey Relational Degree and Artificial Neural Network

[0163] By taking the intersection of the results of grey relational degree analysis and artificial neural network analysis, Figure 11 . As Figure 11 shown, by taking the intersection of the common peaks of the pharmacodynamic indicators obtained by the two mathematical statistical methods, the active ingredients of the muscle-building effect of total monoterpene glycosides of Paeonia lactiflora Pall. can be obtained, namely peaks 2, 7, 9, 11, and 13. Among them, peak 11 is an isomer of benzoylpaeoniflorin. The other four peaks are Albiflorin, 4-O-Galloylalbiflorin, Pentagalloylglucose, and Isopaeoniflorin. Among them, there are 4 monoterpene glycoside compounds and 1 tannin compound.

[0164] The peak areas of the above-mentioned common effective peaks were summed up, and the results are shown in Table 11. As can be seen from Table 11, the total peak area of these 5 common peaks in group CB is the largest, which is 70350707764; there are 3 peaks with 5×10 10 <peak area<7×10 10 , namely AB, YJ, and DF; 4×10 10< 0 < peak area < 5×10 10 There are two peaks, namely SL and DYS. The sum of the above peak areas is positively correlated with the tensile coefficient of mice in different groups, indicating that the above five common peaks have a combined effect on muscle growth in mice.

[0165] Table 11 Peak areas and total of 5 common peaks with muscle growth effect

[0166]

[0167] Continued Table 11:

[0168]

[0169] Calculation results of correlation coefficient

[0170] The calculation results of the correlation coefficient are shown in Table 12. As can be seen from Table 2, the above 4 pharmacodynamic indexes are all positively correlated with the total peak area of 5 compounds. Among them, the correlation coefficients of the total peak area with the tensile coefficient and the gastrocnemius index are greater than 0.5, indicating a strong correlation; the correlation coefficient with the antioxidant capacity is 0.47, indicating a certain correlation; while the correlation coefficient with the swimming time is only 0.07, indicating a weak correlation. The above results show that the above 5 compounds have a certain muscle growth effect.

[0171] The results of the tensile coefficient of mice in different groups and the sum of peak areas are shown in Table 4 - 13. As can be seen from Table 4 - 13, except for the YJ, JGDQ, and HB groups, the tensile coefficient of mice in the other groups increases with the increase of the sum of the peak areas of the 5 compounds, indicating that these 5 compounds have a strong effect on the increase of the tensile coefficient of mice.

[0172] Table 12 Correlation coefficient between pharmacodynamic results and peak area

[0173]

[0174] Table 4 - 13 Tensile coefficient and sum of 5 peak areas

[0175]

[0176]

[0177] The present invention discovers for the first time that Paeonia lactiflora Pall. from various producing areas all has a certain muscle growth effect on normal mice.

[0178] The correlation study of the spectrum-effect relationship of traditional Chinese medicine requires the use of mathematical statistics methods. According to the specific research content, the optimal data analysis method is determined, and the corresponding spectrum-effect relationship model is established. In this invention, antioxidant activity, tensile coefficient, swimming time, and gastrocnemius index, which are closely related to the muscle-building effect, are selected as reference sequences for grey correlation analysis and neural network analysis. The analysis results show that Albiflorin, 4-O-Galloylalbiflorin, Pentagalloylglucose, and Isopaeoniflorin may be closely related to the muscle-building effect of Paeonia lactiflora Pall. The sum of the peak areas of the above 5 peaks is positively correlated with the size of the tensile coefficient of mice. Combining the compounds with strong correlation to the muscle-building effect screened by network pharmacology and the fingerprint results, it is speculated that the muscle-building effect is the result of the combined action of the above 5 compounds.

[0179] This invention discovers that the monoterpene glycosides of Paeonia lactiflora Pall. have a good muscle-building effect. This invention first explores the muscle-building effect of the monoterpene glycosides of Paeonia lactiflora Pall., evaluates the muscle-building effect of the monoterpene glycosides of Paeonia lactiflora Pall. from different origins, and also uses UPLC-MS / MS and multivariate statistical analysis methods to systematically study the muscle-building effect of the total monoterpene glycosides of Paeonia lactiflora Pall. A total of 5 components with muscle-building effects are identified. Among them, there are 4 monoterpene glycoside compounds, one of which is an isomer of benzoylpaeoniflorin, and the other three are Albiflorin, 4-O-Galloylalbiflorin, and Isopaeoniflorin; there is 1 tannin compound, which is Pentagalloylglucose. Combining the pharmacodynamic results and fingerprint peak area results obtained from the previous network pharmacology and experiments, it is speculated that the monoterpene glycoside extracts in Paeonia lactiflora Pall. interact with each other and have a certain degree of muscle-building effect on normal mice.

[0180] The purpose of this invention is to provide a basis for the future development of Paeonia lactiflora Pall. in fitness food and provide experimental evidence for the development of animal feed additives that can increase muscle. This invention establishes a fingerprint-spectrum-effect correlation model of the total monoterpene glycosides of Paeonia lactiflora Pall., fills the blank in the research on the muscle-building effect of the active components of the total monoterpene glycosides of Paeonia lactiflora Pall. on normal mice, and is of great significance for the further development and resource utilization of Paeonia lactiflora Pall.

Claims

1. Application of total monoterpene glycosides of red peony root in the preparation of animal feed or medicine for increasing muscle mass of healthy animals.

2. The application according to claim 1, characterized in that The animal is a mammal.

3. A method for analyzing active ingredients in total monoterpene glycosides of Paeonia veitchii Lynch, characterized in that, The analysis method is achieved by the following steps: Step 1: Measure the total reducing power, ·OH - , ·DPPH, ·O2 - and ABTS + radical scavenging rates, assuming them to be equally important. Take the maximum value of each group of data as 1 and the minimum value as 0, then normalize all the data. Use the formula Y = Y1×1 / 5 + Y2×1 / 5 + Y3×1 / 5 + Y4×1 / 5 + Y5×1 / 5 to calculate the values and list them. Analyze the strength of antioxidant ability according to the list. Step 2: Using total monoterpene glycosides of red peony root from different origins to conduct tension and swimming time, gastrocnemius muscle and epididymal fat index, and histopathological experiments on normal mice and obtain the results. SPSS29.0 software was used to process the data involved in the above experiments. The measurement data were expressed as mean ± standard deviation. The data were expressed in the form of repeated measures analysis of variance and one-way analysis of variance using Duncans multiple range test. P < 0.05 was considered to be significantly different. Step 3: Accurately weigh 3.75 g of total monoterpene glycosides of red peony root powder from different sources and perform the following operations: dilute with 10 mL of 70% (volume) ethanol, then take 1.0 mL and spin at 12000 r·min. -1 Centrifuge at high speed for 5 minutes, then filter the supernatant with a 0.22 μm microfiltration membrane and wait for detection; Step 4: Acquire UPLC-MS / MS data; Step 5: Xcalbur 4.2 software was then used to analyze and compare the positive and negative ion mass spectra. Based on the relevant literature review, the information of secondary mass spectrometry was used to determine the composition of the substance using the ChEMBL database and PubChem website to obtain the accurate relative molecular mass. Step 6: The total ion current of total monoterpene glycosides of red peony root from each origin was imported into the "Chinese Medicine Chromatographic Fingerprint Similarity Evaluation System" (version 2012.130723), and the fingerprint of total monoterpene glycosides of red peony root was established by the software; Step 7: Using antioxidant capacity, mouse pulling coefficient, swimming time, and gastrocnemius muscle index as reference sequences and the common peak area of total monoterpene glycosides of red peony root as comparison sequence, group the common peak area and data of each pharmacodynamic index into a table and enter the following formula for calculation: Select the above index as the reference sequence, denoted as x0(K), k=1,2,3,…,m, Select the peak area of the common peaks as the comparison sequence, denoted as x i (K), i = 1, 2, 3, …, n, Since the units of the reference sequence and the comparison sequence are different, dimensionless processing is required. The averaging method is used to process the reference sequence and the comparison sequence respectively. The formula for calculating the average value is as follows: Where X(k)- is the result of data meanization, and x(k)- is the reference sequence and the comparison sequence, - is the average value of the reference sequence and the comparison sequence, X0(k) and X i (k) of the grey correlation coefficient Loi(k) is calculated by the following formula: Loi(k) = (△ min + △ max ) / (△oi(k) + ρ△ max ) Where Loi(k) is the absolute value of the difference between the two comparison sequences, that is, △oi(k)=|Xo(k)-Xi(k)|(1≤i≤m), △ max - is the maximum absolute difference among all comparison sequences, min - is the minimum value of the absolute difference of all compared sequences, ρ- is the resolution coefficient, which is generally taken as 0.5; The correlation degree is the average of the correlation coefficients of the reference series and the comparison series, and its calculation formula is as follows: In the formula, roi- is the correlation degree, that is, the average value of the correlation coefficient, n- is the number of samples, Loi(k)- is the grey correlation coefficient; Step 8: The common peaks of each efficacy index and the data of each efficacy index are grouped and tabulated, and the data are standardized. The 13 common peaks of the fingerprint of the effective part of total monoterpene glycosides of red peony root and the efficacy index of the muscle-increasing effect of red peony root are input into SPSS29.0 software, and a correlation study is performed using the neural network multilayer perceptron module in the software. The former is a covariate and the latter is a dependent variable. The active ingredients of the efficacy index are screened through the important analysis of independent variables. The peak area of the common peak of total monoterpene glycosides of red peony root is used as the independent variable, the independent variable is the matrix X, the mouse pulling coefficient, swimming time, and gastrocnemius index are the dependent variables, and the dependent variable is the matrix Y. Normalization is calculated according to the following formula: X0=(XX min ) / (X max -X min )+0.0001 Wherein, X0- is the result of data standardization, X- is the value of each group of data, and X min - is the minimum value in each group of data, and X max - is the maximum value in each group of data; Step 9, antioxidant activity, tension coefficient, swimming time, and gastrocnemius index, which are closely related to the activity of total monoterpene glycosides of red peony root, are selected as reference sequences for gray correlation analysis and neural network analysis to identify the active ingredients; Step 10: Calculate the correlation coefficients of antioxidant activity, tension coefficient, swimming time, gastrocnemius index and the total area of chromatographic peaks of efficacy-related compounds using the CORREL function in Excel software.

4. The analysis method according to claim 3, wherein In step 4, the chromatographic column was a Thermo Fisher Scientific Hypersil Gold AQ C18 column (100×2.1 mm, 1.9 μm), the mobile phase A was water containing 0.1% formic acid (v / v), the mobile phase B was acetonitrile containing 0.1% formic acid (v / v), and the mobile phase flow rate was 0.3 mL min -1 The gradient program was as follows: 0-1 min, 2% B; 1-2 min, 2%-5% B; 5-10 min, 12%-20% B; 10-12 min, 20%-30% B; 12-13 min, 30%-50% B; 13-15 min, 50%-100% B; 15-16 min, 100% B. The injection volume was 5 μL. The mass spectrometry conditions were high-resolution mass spectrometry parameters as follows: sheath gas flow rate, 30 psi; auxiliary gas pressure (Aux gas flow rate), 10 psi; sweep gas flow rate, 0 psi; capillary voltage, 3.5 kV; capillary temperature, 320 °C; AUX gas heater temperature, 350 °C; collision gas: nitrogen; normalized collision energies: 20, 40, and 60 eV; s-lens 60.0, combined with the selection of a full mass spectrometry scan to automatically trigger a secondary mass spectrometry scan mode (Fullms-ddms 2 ), resolution: primary and secondary resolutions were 70,000 FWHM / 17,500 FWHM, respectively; ion scan range, m / z 50-1500; cycle count, 3 times; fourth-level isolation window, 1.5 m / z; dynamic exclusion time, 5 s.

5. The analysis method according to claim 3, characterized in that, Determination of total reducing power: Add 2.0 mL of total monoterpene glycoside sample solution of red peony root from different origins, 2.0 mL of phosphate buffer with a pH of 7.2, and 2.0 mL of 1% potassium ferricyanide solution into a test tube, mix well, and place in a water bath at 50°C for 20 minutes. Then add 2.0 mL of 10% trichloroacetic acid, let it stand at 25°C for 10 minutes, and centrifuge at 3000 r / min for 10 minutes. Take 2.0 mL of supernatant, add 2.0 mL of pure water and 0.4 mL of ferric chloride in sequence, and react for 10 minutes. Measure the absorbance at 700 nm.

6. The analysis method according to claim 3, wherein ·OH - Determination of scavenging ability: Into a 10 mL test tube, 2 mL of 6 mmol·L -1 FeSO4 solution, 2 mL of total monoterpene glycoside samples solution of Paeonia lactiflora Pall from different origins, and 2 mL of 6 mmol·L -1 H2O2 solution were added successively. After mixing evenly, the reaction was carried out in a water bath at 37 °C for 10 min. Then, 2 mL of 6 mmol·L -1 salicylic acid-ethanol solution was added, shaken well, and left standing in a 37 °C water bath for 30 min. The absorbance value was measured at a wavelength of 510 nm: OH - The clearance rate is calculated as follows: Where: P%-·OH - Clearance rate; A0 - Absorbance value with distilled water replacing the sample solution; A s - Absorbance value after adding the sample solution; A x - Absorbance without adding salicylic acid solution.

7. The analysis method according to claim 3, characterized in that, DPPH free radical scavenging rate determination: add 2 mL of sample, 2 mL of DPPH solution, and 2 mL of anhydrous ethanol solution to the test tube in sequence, shake evenly, and place in the dark at 37°C for 30 minutes. Use anhydrous ethanol as a blank to adjust A to 0.00, measure the absorbance at a wavelength of 517 nm, and calculate the DPPH scavenging rate according to the sample absorbance using the following formula: Where: P%-DPPH·free radical scavenging rate; A0-blank absorbance value; A1-sample absorbance value; A2-sample blank absorbance.

8. The analysis method according to claim 3, wherein ABTS + Clearance rate measurement method: 0.8 mL of ABTS + The working solution was mixed with 0.2 mL of anhydrous ethanol and 0.2 mL of total monoterpene glycosides sample solution of red peony root from different origins, shaken for 10 seconds, and allowed to stand for 6 minutes. The absorbance was measured at A = 734 nm. ABTS + The clearance rate is calculated as follows: Where: P%-ABTS + Clearance; A0-0.8mL of ABTS + The absorbance value after the working solution is mixed with 0.2 mL of anhydrous ethanol; A x -0.8 mL of ABTS + The absorbance value after mixing the working solution with 0.2 mL of sample solution.

9. The analysis method according to claim 3, characterized in that Active ingredients: There are 4 monoterpene glycoside compounds, one of which is an isomer of benzoylpaeoniflorin, and the other three are Albiflorin, 4-O-Galloylalbiflorin, and Isopaeoniflorin; there is 1 other compound, Pentagalloylglucose.

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