1. The Callicarpa nudiflora astringent substance evaluation method based on the effect correlation of reducing vascular permeability spectrum is characterized by comprising the following steps of:

(1) pulverizing folium Callicarpae Formosanae into coarse powder, weighing 3 parts, adding 10 times of water, 60% ethanol and 95% ethanol, reflux extracting for 2 times (2 hr each time), mixing filtrates, concentrating under reduced pressure, and drying to obtain water extract, 60% ethanol extract and 95% ethanol extract; dissolving part of 60% alcohol extract in water, passing through AB-8 macroporous adsorbent resin column, eluting with water until the eluate is clear, mixing the eluates, recovering and drying under reduced pressure to obtain 60% alcohol extract-water washed extract, further eluting with 40% ethanol until the eluate is clear, mixing the eluates, recovering and drying under reduced pressure to obtain 60% alcohol extract-40% alcohol eluate, further eluting with 60% ethanol until the eluate is clear, mixing the eluates, recovering and drying under reduced pressure to obtain 60% alcohol extract-60% alcohol eluate;

(2) precisely weighing the 6 extract powders corresponding to 1g of crude drug, placing in a bottle with plug, precisely adding 50mL of 50% methanol, dissolving, shaking, filtering, and collecting the filtrate to obtain sample solution;

(3) the chromatographic conditions are as follows: octadecyl bonded silica gel filler is adopted in the chromatographic column; the mobile phase is as follows: a is 0.5 percent phosphoric acid solution, B is acetonitrile; gradient elution was used: 0min → 10min → 20min → 30min, acetonitrile: 82% → 80% → 76% → 82%, 0.5% phosphoric acid solution: 18% → 20% → 24% → 18%; flow rate: 1.0 mL/min; a detector: a UV-DAD detector; detection wavelength: 330 nm; column temperature: 35 ℃; sample introduction amount: 10 mu L, establishing an HPLC fingerprint of the beautyberry test sample;

(4) obtaining matching data through software analysis of a traditional Chinese medicine chromatogram fingerprint similarity evaluation system, selecting characteristic peaks with matching number larger than 2, and extracting characteristic peak data;

(5) the rat with the histamine phosphate inflammation is drenched with the various extracts in the step (1), and the influence on the OD value of the skin of the rat with the histamine phosphate inflammation and the area of the blue spots is detected;

(6) and (4) statistically analyzing the characteristic peak data and pharmacodynamic activity data screened in the step (4) by a chemometrics method, substituting the characteristic peak data and the pharmacodynamic activity data into a spectral efficiency mathematical model for calculation, and evaluating the pharmacodynamic substance basis of the callicarpa nudiflora convergence effect according to the obtained result.

2. The evaluation method of callicarpa nudiflora astringent substance based on decreasing vascular permeability spectrum effect correlation according to claim 1, wherein the retention time of the common characteristic peak with the screened matching number greater than 2 is respectively: 2.727min, 2.911min, 3.738min, 5.246min, 5.775min, 6.137min, 7.079min, 8.363min, 9.790min, 11.586min, 12.810min, 13.717min, 14.992min, 17.755min, 18.584min, 19.705min, 20.298min, 21.021min, 22.862min, 24.218min and 25.078 min.

3. The method for evaluating an astringent substance of Callicarpa nudiflora based on decreasing correlation of vascular permeability spectrum effect according to claim 1, wherein peaks 2, 4, 8, 9, 11, 13, 18 and 23 of the correlated chromatograms show better correlation with OD value of rat skin and area of blue spot, namely chromatograms with retention time of 2.911min, 3.738min, 5.775min, 6.137min, 7.079min, 9.790min, 14.992min and 19.705min respectively, and further, peak 8 is protocatechuic acid, peak 11 is protocatechualdehyde, peak 13 is rutin, peak 18 is isoverbascoside and peak 23 is luteolin.

4. The method for evaluating an astringent substance of Callicarpa nudiflora based on the correlation of permeability spectrum of blood vessel of claim 1, wherein the mathematical model of spectrum effect is as follows: x₄Represents the peak area of chromatographic peak with retention time of 3.738min, X₁₁Representing the peak area of chromatographic peak with retention time of 7.079 min; y is_{OD value of skin}、Y_{Area of blue spot}Represents the astringent effect efficiency of Callicarpa nudiflora.

Y_{OD value of skin}＝0.027-0.00018*X₄，P＝0.007<0.05，R²＝0.862；

Y_{Area of blue spot}＝11.485-0.076*X₄-0.006*X₁₁，P＝0.001<0.05，R²＝0.994。

5. The method for evaluating an astringent substance of Callicarpa nudiflora based on the correlation of permeability spectrum efficacy of reducing blood vessels of claim 1, wherein the substance-based method for determining astringent effect of Callicarpa nudiflora in step (6) comprises: the characteristic peak with obvious difference P <0.05 in the correlation between the characteristic peak area and the pharmacodynamic data and the characteristic peak introduced into the spectrum effect equation are the material basis of the convergence of Callicarpa nudiflora.

6. The method for evaluating an astringent substance of Callicarpa nudiflora based on decreasing correlation of vascular permeability spectrum effect according to claim 5, wherein the active ingredient chromatographic peaks 2, 4, 8, 9, 11, 13, 18 and 23 are the basis of the astringent substance of Callicarpa nudiflora, and the active compounds mainly exerting the astringent effect are chromatographic peaks 8, 11, 13, 18 and 23.

7. The method for evaluating an callicarpa nudiflora astringent substance based on the correlation of effect of decreasing vascular permeability spectrum according to claim 1, wherein the step (6) further comprises performing principal component analysis on a plurality of groups of callicarpa nudiflora extract related peaks, and screening extract related peak components having great influence on polarity change and difference of astringent effect between the components; the principal component analysis method is based on the following three points:

A. the contribution rate of the main component is not lower than 80%;

B. the eigenvalues of the principal components that remain must be greater than 1;

C. and performing KMO test and Bartlett test.

8. The method of claim 7, further comprising validating the principal component analysis by clustering analysis.

Background

Callicarpa nudiflora (Callicarpa nudiflora hook. et Arn.) is a plant of Callicarpa of Verbenaceae, folium Callicarpa nudiflora is medicinal, can be harvested all the year round, is a commonly used traditional ethnic medicine in Hainan region, and is also called Li medicine because it grows in Hainan Li nationality region. Callicarpa nudiflora is the only new supplementary medicinal material in the 2015 edition of pharmacopoeia, and the chemical components of the callicarpa nudiflora mainly comprise flavonoids, phenylethanoid glycosides, terpenes, volatile oils and the like, have the functions of diminishing inflammation, detoxifying, astringing and stopping bleeding, and are used for suppurative inflammation, acute infectious hepatitis, respiratory tract and digestive tract bleeding, wound bleeding and the like. According to records of 'materia medica shigae', Callicarpa nudiflora can relieve all poisons, carbuncle and cellulitis, pharyngitis, toxin swelling, fistula, snake poisonous snake stings and rabies poison, and is decocted for oral administration; the decoction is also boiled to wash away sores and swellings, remove blood and grow skin.

The traditional Chinese medicine spectrum-effect relationship is characterized in that under the guidance of the traditional Chinese medicine theory, the traditional Chinese medicine fingerprint spectrum and the pharmacodynamics are associated through a chemometrics model, a comprehensive evaluation system combining chemical analysis and biological activity evaluation is established, the material basis of the traditional Chinese medicine efficacy is disclosed beneficially, and the traditional Chinese medicine spectrum-effect relationship becomes one of the traditional Chinese medicine effective component prediction and quality evaluation methods. The traditional Chinese medicine fingerprint spectrum can reveal the chemical components of the traditional Chinese medicine, can evaluate the quality of the traditional Chinese medicine on the whole, and has the characteristics of characteristics, specificity, stability, completeness and the like. However, the research and establishment of the fingerprint map only realizes the improvement of the stability and controllability of the chemical components of the traditional Chinese medicine, and does not establish direct internal connection with the efficacy of the traditional Chinese medicine. The research of the spectrum-effect relationship is established on the basis of the fingerprint, the fingerprint provides chemical component information of a complex system, the pharmacological research provides activity information of the complex system, and the research of the spectrum-effect relationship enables the two to be effectively combined, so that the material basis of the drug effect of the traditional Chinese medicine is more reliably disclosed. The current research methods of the spectral efficiency relationship comprise correlation analysis, regression analysis, principal component analysis, grey correlation degree analysis, cluster analysis and typical correlation analysis. A large number of pharmacological studies show that the n-butanol extract part of callicarpa nudiflora has the effects of stopping bleeding and clotting blood, and the total flavonoids have the effects of resisting inflammation and the like. Therefore, the invention takes HPLC finger-prints of different extraction parts of Callicarpa nudiflora as the basis, inspects the spectrum effect relationship of the Callicarpa nudiflora for reducing the vasopermeability and the astringent drug effect activity through bivariate correlation analysis and regression analysis, and establishes the Callicarpa nudiflora astringent substance evaluation method.

Disclosure of Invention

The invention aims to provide a method for evaluating callicarpa nudiflora convergence effect based on the effect correlation of the reduced vascular permeability spectrum aiming at the lacking effective and efficient method for evaluating the convergence effect of callicarpa nudiflora, which can quickly and accurately evaluate chemical components with convergence effect in callicarpa nudiflora, screen active components, provide a scientific and effective method for basic research and quality control of pharmacodynamic substances of callicarpa nudiflora, and solve the problems in the background technology.

In order to achieve the purpose, the invention provides the following technical scheme: a Callicarpa nudiflora convergence effect substance evaluation method based on correlation of vascular permeability spectrum effect reduction is characterized in that HPLC fingerprint spectrums of different polarity extracts of Callicarpa nudiflora are established, characteristic peaks with the matching number larger than 2 are calibrated and screened out through similarity evaluation software to serve as correlation peaks, a corresponding spectrum effect relation is established according to the peak area and the convergence effect of the characteristic correlation peaks of the HPLC fingerprint spectrums, and then the convergence effect of the Callicarpa nudiflora is directly evaluated by utilizing the established spectrum effect relation.

A Callicarpa nudiflora astringent substance evaluation method based on correlation of effect of reducing vascular permeability spectrum comprises the following steps:

(1) pulverizing Callicarpa nudiflora into coarse powder, weighing 3 parts, and respectively adding 10 times of water, 60% ethanol and 95% ethanol; reflux extraction is carried out for 2 hours, and extraction is carried out twice; filtering, combining the filtrates, and recovering the solvent from the filtrate; drying under reduced pressure to obtain water extract, 60% ethanol extract, and 95% ethanol extract; weighing part of 60% ethanol extract, dissolving with water, passing through AB-8 macroporous adsorbent resin column, eluting with water until eluate is clear, recovering eluate under reduced pressure, and drying to obtain 60% ethanol extract-water washed extract; eluting with 40% ethanol until the eluate is clear, recovering the eluate under reduced pressure, and drying to obtain 60% ethanol extract-40% ethanol eluate; eluting with 60% ethanol until the eluate is clear, recovering the eluate under reduced pressure, and drying to obtain 60% ethanol extract-60% ethanol eluate.

(2) Precisely weighing the extract powder corresponding to 1g of crude drug, placing in a bottle with plug, precisely adding 50mL of 50% methanol, dissolving, shaking, filtering, and collecting the filtrate to obtain sample solution;

(3) chromatographic conditions are as follows: octadecyl bonded silica gel filler is adopted in the chromatographic column; the mobile phase is as follows: a is 0.5 percent phosphoric acid solution, B is acetonitrile; gradient elution was used: 0min → 10min → 20min → 30min, acetonitrile: 82% → 80% → 76% → 82%, 0.5% phosphoric acid solution: 18% → 20% → 24% → 18%; flow rate: 1.0 mL/min; a detector: a diode array detector; detection wavelength: 330 nm; column temperature: 35 ℃; sample introduction amount: 10 mu L of the solution; establishing an HPLC fingerprint of a beautyberry test sample;

(4) obtaining matching data through software analysis of a traditional Chinese medicine chromatogram fingerprint similarity evaluation system, selecting characteristic peaks with matching number larger than 2, and extracting characteristic peak data;

(5) the rat with the histamine phosphate inflammation is drenched with the various extracts in the step (1), and the influence on the OD value of the skin of the rat with the histamine phosphate inflammation and the area of the blue spots is detected;

(6) and (4) statistically analyzing the characteristic peak data and pharmacodynamic activity data screened in the step (4) by a chemometrics method, substituting the characteristic peak data and the pharmacodynamic activity data into a spectral efficiency mathematical model for calculation, and evaluating the pharmacodynamic substance basis of the callicarpa nudiflora convergence effect according to the obtained result.

Preferably, the retention time of the characteristic correlation peak screened in step (4) is respectively as follows: 2.727min, 2.911min, 3.738min, 5.246min, 5.775min, 6.137min, 7.079min, 8.363min, 9.790min, 11.586min, 12.810min, 13.717min, 14.992min, 17.755min, 18.584min, 19.705min, 20.298min, 21.021min, 22.862min, 24.218min and 25.078 min.

Preferably, correlation analysis is performed between the peak area of the relevant peak screened in the step (4) and the convergence drug effect data, and a spectrum effect equation is established through multiple linear regression, so that the material basis of the convergence effect of the callicarpa nudiflora is judged. Wherein, the related chromatographic peaks 2, 4, 8, 9, 11, 13, 18 and 23 show better relativity with the OD value and the blue spot area of the rat skin, namely chromatographic peaks with retention time of 2.911min, 3.738min, 5.775min, 6.137min, 7.079min, 9.790min, 14.992min and 19.705min respectively, and the peak 8 is protocatechuic acid, the peak 11 is protocatechualdehyde, the peak 13 is rutin, the peak 18 is isoverbascoside and the peak 23 is luteolin; the compounds with chromatographic peaks 2, 4 and 9, such as phenylethanoid glycosides, flavonoids and phenolic acids, can be confirmed by using the ultraviolet absorption characteristics of the compounds in the DAD chromatogram.

And wherein peak 4 and peak 11 are introduced to a different extent into the mathematical model of spectral efficiency, respectively, as follows: x₄Represents the peak area of chromatographic peak with retention time of 3.738min, X₁₁Representing the peak area of chromatographic peak with retention time of 7.079 min; y is_{OD value of skin}、Y_{Area of blue spot}Represents the astringent effect efficiency of Callicarpa nudiflora.

Y_{OD value of skin}＝0.027-0.00018*X₄，P＝0.007<0.05，R²＝0.862；

Y_{Area of blue spot}＝11.485-0.076*X₄-0.006*X₁₁，P＝0.001<0.05，R²＝0.994；

Compared with the prior art, the invention has the beneficial effects that:

(1) the invention establishes the correlation between the change of chemical components and the change of drug effect of the callicarpa nudiflora extract on a fingerprint by using a chemical pattern recognition method, and determines the drug effect substance basis of the astringency effect of the callicarpa nudiflora on the histamine phosphate to the inflamed rat in the callicarpa nudiflora, wherein the phenylethanoid glycoside compound and the phenolic acid micromolecule compound are taken as main materials, and the flavonoid compound is taken as an auxiliary material.

(2) The invention establishes the Callicarpa nudiflora chemical composition evaluation method based on the convergence spectrum effect relationship of reducing vascular permeability, defines the chemical composition in the Callicarpa nudiflora which is relatively close to the convergence pharmacodynamic activity, provides a basis for the convergence pharmacodynamic substance basic research of the Callicarpa nudiflora, and simultaneously adopts the mode of combining the fingerprint spectrum and the mathematical model to avoid the interference of third party factors, thereby avoiding the individual deviation of animals and being capable of quickly and clearly determining the convergence effect evaluation of the Callicarpa nudiflora extract.

(3) The method can quickly and accurately evaluate the screening of the chemical components and the active components with the effect of improving the vascular permeability in the callicarpa nudiflora, and provides a scientific and effective method for the basic research and the quality control of the drug effect substances of the callicarpa nudiflora.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below.

FIG. 1 is an HPLC fingerprint of a Callicarpa nudiflora sample extract of the present invention;

FIG. 2 is HPLC fingerprint of Callicarpa nudiflora extract with different polarities;

FIG. 3 is a UV scan of the chromatographic peak with a retention time of 2.911 min;

FIG. 4 is a UV scan of the chromatographic peak with a retention time of 3.738 min;

FIG. 5 is a UV scan of a chromatographic peak with a retention time of 5.775 min;

FIG. 6 is a UV scan of the chromatographic peak with retention time of 6.137 min;

FIG. 7 is a UV scan of the chromatographic peak with retention time of 7.079 min;

FIG. 8 is a UV scan of the chromatographic peak with retention time of 9.790 min;

FIG. 9 is a UV scan of the chromatographic peak with retention time of 14.992 min;

FIG. 10 is a UV scan of the chromatographic peak with retention time of 19.705 min;

FIG. 11 is a linear plot of peak area of chromatographic peak with retention time of 2.911min versus convergence effect;

FIG. 12 is a linear relationship graph of the peak area of the chromatographic peak with retention time of 3.738min and the convergence effect;

FIG. 13 is a graph showing the linear relationship between the peak area of the chromatographic peak and the convergence effect for a retention time of 5.775 min;

FIG. 14 is a linear plot of peak area of chromatographic peak with retention time of 6.137min versus convergence effect;

FIG. 15 is a linear relationship graph of peak area of chromatographic peak with retention time of 7.079min and convergence effect;

FIG. 16 is a linear plot of peak area of chromatographic peak with retention time of 9.790min versus convergence effect;

FIG. 17 is a linear plot of peak area of chromatographic peak with retention time of 14.992min versus convergence effect;

FIG. 18 is a linear plot of peak area of chromatographic peak with retention time of 19.705min versus convergence effect;

FIG. 19 is a secondary mass spectrum of a chromatographic peak with a retention time of 5.775 min;

FIG. 20 is a secondary mass spectrum of the chromatographic peak with retention time of 7.079 min;

FIG. 21 is a secondary mass spectrum of the chromatographic peak with retention time of 9.790 min;

FIG. 22 is a secondary mass spectrum of the chromatographic peak with retention time of 19.705 min;

FIG. 23 is a PCA principal component analysis plot of different extracts of Callicarpa nudiflora;

FIG. 24 is a graph showing the verification of the ward method cluster analysis of the principal components.

Detailed Description

The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments of the present invention, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Example 1

1. Test instruments and materials

1.1 instruments

An Agilent model 1260 high performance liquid chromatograph; SPSS22.0 statistical analysis software; FA1004 electronic balance; YXQ-2S-50 SII vertical pressure steam sterilizer; model SP-756PC UV-VIS spectrophotometer.

1.2 materials

Callicarpa nudiflora leaf sample: collected from Hainan white sand. The amoxicillin capsules are purchased from the pharmaceutical factory of Australia America; evans blue was purchased from Shanghai Huichi Biotech limited.

Comparison products: acteoside and forsythiaside B controls were purchased from dreich biotechnology limited; the luteolin control is purchased from Dougui scientific development Co., Ltd; isoverbascoside reference substances are provided by laboratories of the department of Chinese medicine research of Shanghai pharmaceutical industry institute, and the mass fraction of all the reference substances is more than or equal to 98%.

HPLC uses acetonitrile and phosphoric acid as chromatographic purity, water is self-made redistilled water, and other reagents are analytically pure.

1.3 Experimental animals

SD rats are provided by the laboratory animal center of Nantong university and are fed with complete nutrition pellet feed, before and after administration, rats in each group are fed in cages and fed with complete nutrition pellet feed with free drinking water at room temperature of 2222 ℃ and humidity of 55-65%.

2. Preparing Callicarpa nudiflora parts with different polarities

2.1 crushing callicarpa nudiflora, sieving with a No. 4 sieve, precisely weighing 3 parts, 2kg each, placing in a round-bottom flask, respectively adding 10 times of water, 60% ethanol and 95% ethanol, reflux-extracting for 2h, extracting twice, filtering, mixing filtrates, recovering solvent from the filtrate, and drying under reduced pressure to obtain dry extracts 1, 2 and 3; .

2.2 taking part of the extract 2, adding water for dissolving, passing through an AB-8 macroporous adsorption resin column, eluting with water until the eluent is clear, combining the eluates, and recovering under reduced pressure until the eluates are dry to obtain a 60% ethanol extraction-water washing extract, namely an extract 4; continuously eluting with 40% ethanol until eluate is clear, mixing eluates, recovering under reduced pressure to dry to obtain 60% ethanol extract-40% ethanol eluate, which is called extract 5; then continuously eluting with 60% ethanol until the eluate is clear, mixing the eluates, recovering under reduced pressure to obtain 60% ethanol extract-60% ethanol eluate, which is called extract 6.

3. Establishing HPLC fingerprint of Callicarpa nudiflora extract with different polarities

3.1 preparation of test solutions

Precisely weighing extract powder 1, 2, 3, 4, 5 and 6 corresponding to 1g of crude drug, placing in a bottle with a plug, precisely adding 50mL of 50% methanol, dissolving, shaking, filtering, and collecting the filtrate to obtain sample 1.

Vacuum drying Callicarpa nudiflora at 60 deg.C, pulverizing, sieving with No. 4 sieve, precisely weighing 1g, placing in a bottle with plug, precisely adding 50% methanol 50mL, weighing, heating and refluxing for 1h, cooling, weighing again, supplementing with 50% methanol, shaking, filtering, and collecting the filtrate to obtain sample 2.

3.2 establishing the fingerprint of Callicarpa nudiflora: performing fingerprint spectrum determination on the obtained sample by adopting a high performance liquid chromatography; chromatographic conditions are as follows: octadecyl bonded silica gel filler is adopted in the chromatographic column; the mobile phase is as follows: a is 0.5 percent phosphoric acid solution, B is acetonitrile; gradient elution was used: 0min → 10min → 20min → 30min, acetonitrile: 82% → 80% → 76% → 82%, 0.5% phosphoric acid solution: 18% → 20% → 24% → 18%; flow rate: 1.0 mL/min; a detector: UV-DAD; detection wavelength: 330 nm; column temperature: 35 ℃; sample introduction amount: 10 mu L of the solution;

3.3, obtaining matching data through software analysis of a traditional Chinese medicine chromatogram fingerprint similarity evaluation system, selecting a characteristic peak with the matching number more than 2, and extracting the characteristic peak data: the retention times of 21 common peaks with matching numbers larger than 2 are respectively as follows: 2.727min, 2.911min, 3.738min, 5.246min, 5.775min, 6.137min, 7.079min, 8.363min, 9.790min, 11.586min, 12.810min, 13.717min, 14.992min, 17.755min, 18.584min, 19.705min, 20.298min, 21.021min, 22.862min, 24.218min and 25.078 min. The characteristic peak chromatogram and the matched chromatogram are shown in the attached figures 1 and 2 of the specification.

3.4 methodological considerations

3.4.1 precision investigation: 1g of callicarpa nudiflora medicinal material powder is precisely weighed, a sample solution is prepared according to a method of the sample solution 2 in 3.1, sample introduction is continuously carried out for 6 times according to the chromatographic condition in 3.2, the relative retention time RSD of each fingerprint peak is measured to be less than 0.2%, and the relative peak area RSD is measured to be less than 1.8%, so that the method has good precision.

3.4.2 repeatability test: respectively taking 1g of 6 parts of callicarpa nudiflora medicinal material powder, precisely weighing, preparing 6 parts of test solution according to a method of test solution 2 in item 3.1, sequentially injecting samples according to item 3.2 of chromatographic conditions, and measuring the relative retention time RSD of each fingerprint peak to be less than 0.2 percent and the relative peak area RSD to be less than 2.3 percent, thereby indicating that the method has good repeatability.

3.4.3 stability study: taking 1g of callicarpa nudiflora medicinal material powder, precisely weighing, preparing a sample solution according to a method of the sample solution 2 in item 3.1, respectively injecting samples for 0, 2, 4, 6, 12 and 24 hours according to the chromatographic condition of item 3.2, and measuring the relative retention time RSD of each fingerprint peak to be less than 0.2 percent and the relative peak area RSD to be less than 2.7 percent, which indicates that the sample solution is stable within 24 hours.

4. Pharmacodynamic experiment is carried out on the extracts with different polarities

4.1 taking 100 SD male rats with the weight of 140-170 g, after normally breeding for 3 days, randomly dividing the SD male rats into 10 groups, and numbering and weighing 10 rats in each group.

4.2 grouping is: normal group, model group, amoxicillin group, callicarpa nudiflora granule group, callicarpa nudiflora extract 1 group, callicarpa nudiflora extract 2 group, callicarpa nudiflora extract 3 group, callicarpa nudiflora extract 4 group, callicarpa nudiflora extract 5 group, and callicarpa nudiflora extract 6 group.

4.3 the components are respectively administrated by gastric lavage for 7 days, histamine phosphate 2mg/mL and 0.1 mL/mouse are injected into the depilated part of the back of the rat after the last administration for 1h, 1% Evans blue 50mg/kg is injected into the depilated part of the back of the rat immediately, the animal is killed after 20min, the inflamed part of the back of each rat is cut off by 2.5cm x 2.5cm, and the area of the color spot is measured;

4.4 the blue skin is cut off by a10 cm perforator, soaked in 5mL of a 7:3 mixture of acetone and normal saline for 48h in the dark, taken out at 1500r/min and centrifuged for 10min, the supernatant is taken, the optical density of the filtrate is measured at 620nm by a spectrophotometer, and the optical density of each group is recorded, the data are shown in Table 1 below.

TABLE 1 influence of different Callicarpa nudiflora extracts on OD value and blue spot of skin of rat with histamine phosphate-induced inflammation

Δ Δ P <0.01 compared to normal group; p <0.05, P <0.01 was compared to model groups.

5. Spectral efficiency correlation analysis

5.1 methods

5.1.1 bivariate correlation analysis

And (3) taking the quantized peak area as an independent variable and the pharmacodynamic index as a dependent variable, and performing data processing by adopting a bivariate correlation analysis method of SPSS22.0 statistical software to obtain the Peak-Peak correlation coefficient with the Peak-pharmacodynamic Peak correlation coefficient.

5.1.2 multiple Linear regression analysis

And (3) performing linear regression analysis on the data by using the SPSS22.0 and performing model fitting by adopting a gradual introduction method by using the quantized peak area as an independent variable and the pharmacodynamic index as a dependent variable.

5.1.3 PCA analysis and ward Cluster analysis

Carrying out PCA analysis on 21 related peaks of 6 different extracts of Callicarpa nudiflora by SPSS22.0 PCA analysis, thereby finding out an index of the related peaks which has larger influence on the difference among the 6 extract components and larger accumulated contribution rate, enabling the evaluation of the spectral efficiency relationship to be more accurate, and verifying the PCA analysis result by ward cluster analysis.

5.2 results

5.2.1 results of bivariate correlation analysis

As shown in table 2 below, peaks 2, 4, 8, 9, 11, 13, 18 and 23 show better correlation with rat skin OD value and blue spot area, i.e. peaks with retention times of 2.911min, 3.738min, 5.775min, 6.137min, 7.079min, 9.790min, 14.992min and 19.705min, respectively, and are in negative correlation relationship, wherein peak 4 shows strong correlation with skin OD value and blue spot area, peak 23 shows strong correlation with skin OD value, and peaks 2 and 11 show strong correlation with blue spot area. Comparing the control with the relative retention time, and comparing the ultraviolet visible image with the spectrum mass spectrum data to identify that the chromatographic peak 8 is protocatechuic acid, the chromatographic peak 11 is protocatechuic aldehyde, the chromatographic peak 13 is rutin, and the chromatographic peak 23 is luteolin, wherein the mass spectrum data is shown in the following table 3. Primarily determining compounds types of 2, 4 and 9, namely phenylethanoid glycosides, flavonoids and phenolic acids by using the ultraviolet absorption characteristics of the compounds in the DAD atlas.

TABLE 2 correlation Peak-Peak area and bivariate correlation analysis results

*P<0.05，**P<0.01

Table 3 Mass Spectrometry data for the identified components

5.2.2 multiple Linear regression analysis results

As shown in the following table 4, the correlation coefficient of the model established by the two indexes of the skin OD value and the blue spot area of the related chromatographic peak of the callicarpa nudiflora is higher, and R is²The values of the skin OD and the area of the blue spots are larger than 0.85, the change of the skin OD value and the area of the blue spots can be explained by independent variables, the values of the P are smaller than 0.05, the statistical significance is achieved, and the model can better evaluate the relation between the chromatographic peak of the callicarpa nudiflora and the astringent pharmacological activity.

TABLE 4 mathematical model building results

By combining the analysis results of the two analysis methods, the components of the callicarpa nudiflora which can play a role in convergence are basically determined to be phenylethanoid glycosides compounds, flavonoids and phenolic acid micromolecule compounds. Peaks 2, 4, 8 (protocatechuic acid), 9, 11 (protocatechualdehyde), 13 (rutin), 18 (isoverbascoside) and 23 (luteolin) may be the material basis for callicarpa nudiflora to exert astringent action.

5.2.3 PCA analysis and ward Cluster analysis results

The results of the analysis are shown in Table 5, which retains the components having a cumulative contribution ratio of the number of principal components > 80%, a characteristic value >1, and which have been subjected to KMO (the closer to 1, the more suitable for PCA analysis) and Bartlett test (P < 0.01).

TABLE 5 principal Components analysis results

From the principal component analysis, two principal components can be determined, wherein the first principal component contribution rate is 64.85%, the second principal component contribution rate is 22.04%, and the cumulative contribution rate of the two principal components is 86.89%, which meets the requirement. The PCA loading profile analysis of the 6 extracts was achieved using SPSS22.0 principal component analysis, as shown in FIG. 19. From the figure, it can be seen that extracts 4 and 6 are clustered, extracts 1, 3, 2 and 5 are clustered, and it is also apparent that extracts 4 and 6 have a significant effect on the main component 2, and extract 2 has a slight effect; extracts 1, 3 had a significant effect on principal component 1, with extract 5 having a slight effect.

And then, verifying the principal component analysis by using a ward method cluster analysis method in SPSS22.0 software, wherein as shown in the attached figure 20, the extracts 4 and 6 are clustered into one type, the extracts 1, 3, 2 and 5 are clustered into one type, and the result shown in the figure is basically consistent with the PCA analysis result, so that the PCA analysis result is reliable. By combining the peak areas of 21 relevant peaks and pearson correlation analysis results of each extract, it was confirmed that the component 1 was a phenylethanoid glycoside compound and a flavonoid compound, and the component 2 was a phenolic acid compound. The extracts 4, 6 and 2 contain more phenolic acid components, and the extracts 1, 3 and 5 contain more flavonoid and phenylethanoid glycosides components.