CN108398511A - A kind of quality determining method of Dendrobidium huoshanness - Google Patents
A kind of quality determining method of Dendrobidium huoshanness Download PDFInfo
- Publication number
- CN108398511A CN108398511A CN201710064180.3A CN201710064180A CN108398511A CN 108398511 A CN108398511 A CN 108398511A CN 201710064180 A CN201710064180 A CN 201710064180A CN 108398511 A CN108398511 A CN 108398511A
- Authority
- CN
- China
- Prior art keywords
- variable
- sample
- dendrobidium huoshanness
- finger
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N30/04—Preparation or injection of sample to be analysed
- G01N30/06—Preparation
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N30/62—Detectors specially adapted therefor
- G01N30/74—Optical detectors
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N30/86—Signal analysis
- G01N30/8675—Evaluation, i.e. decoding of the signal into analytical information
- G01N30/8686—Fingerprinting, e.g. without prior knowledge of the sample components
Landscapes
- Physics & Mathematics (AREA)
- Analytical Chemistry (AREA)
- General Health & Medical Sciences (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Pathology (AREA)
- Biochemistry (AREA)
- Immunology (AREA)
- General Physics & Mathematics (AREA)
- Library & Information Science (AREA)
- Engineering & Computer Science (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Other Investigation Or Analysis Of Materials By Electrical Means (AREA)
- Investigating Or Analysing Biological Materials (AREA)
Abstract
The present invention discloses the quality determining method of Dendrobidium huoshanness, including：1) it using ITS 26SE and ITS 17SE as primer, is sequenced, to identify the kind of stem of noble dendrobium medicinal material to be measured；2) chromatography detection is carried out to the sample that sample size is n, obtained using chemical small molecule ingredient schaftoside and/or naringenin as the detection data of reference ingredient；3) finger-print detection is carried out respectively to sample, obtains the finger-print peak area value of the full chemistry ingredient of Dendrobidium huoshanness；4) with the component content value of schaftoside in chromatographic data and/or naringenin variable in response, the peak area value of other ingredients in finger-print is established into analysis model as independent variable, the correlated characteristic fingerprint model of chemical small molecule ingredient is established by Lasso method selection variables.By generation sequencing and characteristic fingerprint pattern, accurately differentiate and control the quality of Dendrobidium huoshanness medicinal material.
Description
Technical field
The invention belongs to Chinese medicinal ingredients to test and analyze field, and in particular to a kind of quality determining method of Dendrobidium huoshanness.
Background technology
Dendrobidium huoshanness (Dendrobium huoshanense C.Z.Tang＆S.J.Cheng) also known as the suddenly stem of noble dendrobium.Stem is upright,
Meat, intensive raw, long 3cm~9cm obviously attenuates upwards from base portion, base portion top diameter 0.3cm~1.0cm, not branch,
Tool 3 section~7 section, internode length 0.3cm~0.8cm, pistac, and when band lilac red spot, do after it is faint yellow.Leaf base has
The sheath of stem is embraced, leaf sheath film quality harbors.Raceme 1~3, sends out from the old stem top of fallen leaves, has 1~2 flowers；Flower
Long 0.2cm~the 0.3cm of sequence handle, base portion have 1 piece~2 pieces sheaths；Sheath papery, ovum shape lanceolar, long 0.3cm~0.4cm, apex are sharp
Point；The shallow white band maroon of petal piece, oval, long 0.3cm~0.4cm, the sharp point of apex；Bennet and ovary chartreuse, long 2cm~
2.7cm；Flower pistac, carries out；Middle sepal ovum shape lanceolar is about 1.2cm~1.4cm, wide 0.4cm~0.5cm, apex
It is blunt, have 5 arteries and veins；Side sepal falciform lanceolar, long 1.2cm~1.4cm, wide 0.5cm~0.7cm, apex is blunt, and base portion is crooked；Calyx
The nearly rectangle of capsule, long 0.5cm~0.7cm, end subcircular；Petal ovate oblong, usual long 1.2cm~1.5cm, wide 0.6cm
~0.7cm, apex is blunt, has 5 arteries and veins；The nearly diamond shape of lip, long and width are approximately equal, 1cm~1.5cm, and base portion wedge shape simultaneously has a callosity
Zhi bodies, top slightly 3 are split, dense undercoat between two side slivers, dense long white hair at nearly base portion；Middle sliver semicircle shape triangle, first
Hold nearly blunt point, the dense long white hair of base portion and the patch for having the lateral ellipse of a yellow；Stamen column light green, is about 0.4cm, tool
The stamen column foot of long 0.7cm；Stamen column foot base portion yellow, dense long white hair, occasionally tool tooth is prominent for both sides；The green white of anther cap, nearly hemispherical are long
About 0.15cm, top dimple.
The stem of noble dendrobium is considered as always precious Chinese herbal medicine by people, has highly important nourishing effects.Clinically, stem of noble dendrobium quilt
For treating a variety of diseases, there are the pharmacological effects such as strengthen immunity, anti-oxidant, hypoglycemic and inhibition cancer.Due to artificially growing
Excavation that phase is uncontrolled and the irrational utilization stem of noble dendrobium, wild resource are reduced increasingly, are occurred some in the market and are mixed the spurious with the genuine, with secondary
The phenomenon that substituting the bad for the good.Further, since dendrobium species are more, interracial hybridization makes the kind of its nearly edge is intersected there are character to show
As classification difference is relatively difficult.Therefore, it is necessary to which the characteristic fingerprint pattern for establishing the stem of noble dendrobium comments the quality of medicinal material of the stem of noble dendrobium
Valence.
Chromatographic fingerprinting is a kind of synthesis, quantifiable discriminating means, as a kind of panning mode of global analysis,
What is reflected is the overall condition of sample.But in chromatographic fingerprinting analytic process, many data are all higher-dimension, i.e. data packet
Preferably Dendrobidium huoshanness can be described for example relating to Dendrobidium huoshanness chromatographic fingerprinting containing many attributes or feature, but
The problem of will facing " dimension disaster " is directly operated to high dimensional data in practical applications, " dimension disaster " can cause to build
The required sample number of mold process exponentially increases as dimension increases.In face of high dimensional data, conventional least square
Method is no longer applicable in, and in order to improve the interpretation of model and the accuracy of prediction, variables choice becomes critically important.How efficiently
Several variables to play an important role to dependent variable are filtered out from numerous variables, be when analyzing finger-print urgently
It need to solve the problems, such as.
National Pharmacopeia is using a certain active constituent or active ingredient, that is, small molecule ingredient in quantitative determination Chinese medicine at present
The height of content evaluates its quality.But the effect of research has shown that, Chinese medicine is the collaboration between its a variety of " active constituents "
Effect, even by universally recognized effective synergistic effect or " raw gram of work between " active constituent " and " non-active ingredient "
With " can be only achieved Chinese medicine the effect of, rather than the result of a certain active constituent independent role.In under instruction of Chinese Medicine theory
Medicine, the whole curative effect that medical drugs are embodied any type active constituent cannot reflect comprehensively in.
Invention content
The present invention provides a kind of quality determining methods of Dendrobidium huoshanness, and the product of identification stem of noble dendrobium medicinal material are sequenced by a generation
Kind, the correlated characteristic fingerprint model of the chemical small molecule ingredient in Dendrobidium huoshanness is established using Lasso method selection variables,
Pass through the quality of generation sequencing and the medicinal material of correlated characteristic fingerprint model accurate evaluation Dendrobidium huoshanness.
The purpose of the present invention is what is be achieved through the following technical solutions：
A kind of quality determining method of Dendrobidium huoshanness, including：
1) with ITS-26SE：5’GAATTCCCCGGTTCGCTCGCCGTTAC 3’；
ITS-17SE：5 ' ACGAATTCATGGTCCGGTGAAGTGTTCG 3 ' are primer, carry out PCR amplification sequencing, with mirror
The kind of fixed stem of noble dendrobium medicinal material to be measured is Dendrobidium huoshanness sample；
2) chromatography detection is carried out to the Dendrobidium huoshanness sample that sample size is n, obtained with chemical small molecule ingredient Xia Fotuo
Glycosides and/or naringenin are as the detection data with reference to ingredient；
3) finger-print detection is carried out respectively to sample, obtains the finger-print peak area of the full chemistry ingredient of Dendrobidium huoshanness
Value；
4) with the component content value of schaftoside in chromatographic data and/or naringenin variable in response, by finger-print
In the peak area values of other ingredients establish analysis model as independent variable, pass through Lasso (The Least Absolute
Shrinkage and SelectionOperator) method selection variables establish the correlated characteristic fingerprint of chemical small molecule ingredient
Spectrum model, basic model are：
Y=XTβ+ε
Wherein, y is response variable, y=(y1,y2,...,yn)T；X is matrix, X=(x1,x2,...,xn)T；E (ε)=0；
Var (ε)=σ2In；ε is the stochastic error of model；σ is the standard deviation of stochastic error；N is sample size；InIt is a n × n
Unit matrix.
It is assumed that random entry is obeyed classic it is assumed that being：
(1) random entry has zero-mean, E (εi|xi)=0；
(2) random entry has same variance, Var (εi|xi)=σ2；
(3) random entry is without serial correlation, Cov (εi,εj)=0, i ≠ j；
(4) ε Normal Distributions, εi~N (0, σ2)。
The variance matrix of random entry is that a diagonal line is σ2, elsewhere for 0 square formation, as follows：
Wherein, InIt is the unit matrix of a n × n, n is the sample size of data,
Further, the Lasso methods are to calculate to realize by formula I：
In formula I, n is sample size；p*For variable number；P is the dimension of sample；Y=(y1,y2,...,yn)T∈RnFor response
Variable；X=(x1,x2,...,xn)TFor the design matrix of n × p, including all candidate independents variable influential on response variable；λ
For adjusting parameter；For penalty；β0Meaning be formula intercept item, that is, when all independent variable x be 0 when ring
The value of dependent variable y；βjIt is meant that independent variable xjCoefficient, i.e. independent variable xjTo the influence degree of response variable y.
Further, the selection method of the λ is that K rolls over cross-validation method：
K-fold CV：
Wherein, K is 5 or 10.
Further, the analysis model is to take the submodel of CV values minimum.
Further, the selection of the λ follows GCV criterion, and the GCV rule definitions are：
Wherein, SSEkIt is the residual sum of squares (RSS) of the CV submodels containing k variable, df=trace { P (λ) }；Trace tables
Show the mark of matrix.In linear algebra, on the leading diagonal (diagonal line from upper left side to lower right) of the matrix A of a n × n
The summation of each element is referred to as the mark (or mark number) of matrix A, is generally denoted as tr (A).That is, df is equal in matrix P (λ)
The sum of all elements on leading diagonal.
Further, the analysis model is to take the submodel of GCV values minimum.
Further, when superelevation, which is presented, in chromatographic data ties up situation, following SIS (Sure Independence are used first
Screening) method selection variables recycle the processing of Lasso methods；
SIS：Mγ={ 1≤i≤p:|ωi| before being | γ n | a bigger
Wherein, M*={ 1≤i≤p:βi≠ 0 } the subscript collection of nonzero coefficient in true mode is indicated；S=| M*| indicate non-zero system
Several numbers；ω=(ω1,ω2,...,ωp)T=XTy；For any given γ ∈ (0,1), the p element of ω is by absolute
Value is arranged and is defined from big to small；At this time | γ n | ＜ n choose MγThe corresponding independent variable of middle subscript is that superelevation dimension drops to d (d
≤ n) dimension；Wherein, d=n or d=[n/logn].
The present invention also provides application of the above method in Dendrobidium huoshanness quality control.
Compared with prior art, the present invention has at least the following advantages：
(a) characteristic sequence for first measuring stem of noble dendrobium medicinal material in the present invention using ITS-26SE and ITS-17SE as primer, with determination
The stem of noble dendrobium medicinal material is Dendrobidium huoshanness kind；It thereafter, will be above-mentioned using the chromatographic data of schaftoside and/or naringenin as independent variable
The chromatographic data of other ingredients in detection data establishes small molecule ingredient and finger-print linear regression model (LRM) as dependent variable,
Keep the quality evaluation of stem of noble dendrobium medicinal material more accurate；
(b) present invention carries out variables choice, effective solution " dimension using Lasso methods to Dendrobidium huoshanness finger-print
The problem of number disaster "；
(c) present invention carries out dimensionality reduction to original finger-print, establishes the correlated characteristic of Dendrobidium huoshanness chemical small molecule ingredient
Finger-print explains that specific aim and applicability are stronger to the content of single chemical small molecule ingredient；
(d) present invention realizes chemical small molecule by the correlated characteristic finger-print of Dendrobidium huoshanness chemical small molecule ingredient
The correlation analysis of component content can effectively differentiate and control the quality of Dendrobidium huoshanness medicinal material；
(e) it when superelevation, which is presented, in chromatographic data ties up situation, uses SIS methods to carry out dimensionality reduction first, recycles Lasso methods
Processing.
Description of the drawings
Fig. 1 is the full ingredients fingerprint chromatogram of Dendrobidium huoshanness；
Fig. 2 is the chromatogram of schaftoside chemical small molecule standard of physical sample；
Fig. 3 is the chromatogram of naringenin chemical small molecule standard of physical sample；
Fig. 4 is the chromatogram of Dendrobidium huoshanness ancient name for China Buddhist support glycosides chemical small molecule；
Fig. 5 is the chromatogram of naringenin chemical small molecule in Dendrobidium huoshanness.
Note：No. 1 peak schaftoside；No. 2 peak naringenins.
Specific implementation mode
The invention will be further described with reference to the accompanying drawings and examples, and following embodiment is descriptive, is not
Limited, protection scope of the present invention cannot be limited with this.
A generation for 1 Dendrobidium huoshanness of embodiment is sequenced
Generation sequencing primer sequence：
ITS-26SE：5’GAATTCCCCGGTTCGCTCGCCGTTAC 3’；
ITS-17SE：5’ACGAATTCATGGTCCGGTGAAGTGTTCG 3’.
Parameter is sequenced in amplification：PCR cycle is carried out after 98 DEG C of denaturation 2min, PCR cycle parameter is 98 DEG C of 20s；52℃
30s；68 DEG C of 1min, 38 cycles, 68 DEG C of 7min are arranged 4 DEG C of heat preservations, and carry out generation molecule sequencing after amplification.
It is sequenced by a generation, differentiates that the kind of stem of noble dendrobium medicinal material to be measured is Dendrobidium huoshanness.
The extracting method of 2 Dendrobidium huoshanness of embodiment
Dendrobidium huoshanness drying sample is taken, is crushed with pulverizer, pharmacopeia sieve (aperture 0.335mm) is crossed, precision weighs dendrobe powder
Last 1.000g (weighing error is no more than 0.2%), is placed in 100ml conical flasks, is separately added into 50mL 75% methanol (V water：V
Methanol=25:75) it, takes out, filters after ultrasound 30min at room temperature, filtrate concentrated by rotary evaporation is to doing, with 75% methanol solvate (V water：V
Methanol=25:75) it dissolves, is finally transferred to constant volume in 10ml volumetric flasks, shakes up, with 0.45 μm of filtering with microporous membrane to get suddenly
Mountain stem of noble dendrobium sample solution.
The chromatographic detection method of 3 Dendrobidium huoshanness extract of embodiment
1. prepared by reference substance solution
Precision weighs schaftoside 4.10mg and naringenin 4.08mg respectively, is respectively placed in 10ml volumetric flasks, adds 75%
(V/V) methanol dissolved dilution shakes up, as storing solution.It is spare in being refrigerated in 4 DEG C of refrigerators.
Accurate a certain amount of reference substance stock solution of absorption accurately prepares Xia Fotuo using 75% methanol dilution respectively again
Glycosides and naringenin mixed reference substance solution.By different dilution ratios, 7 concentration points of prepared composition are diluted.Inject efficient liquid
Chromatography.
2. the small molecule component content determination sample extraction process method of Dendrobidium huoshanness：
This product powder (crossing No. three sieves) 1.00g is taken, it is accurately weighed, it sets in 100ml volumetric flasks, precision plus methanol-water (75:
25) 50ml, is ultrasonically treated (power 250W, frequency 40kHz) 30 minutes, lets cool, and filters, and filtrate concentrated by rotary evaporation is to doing, with 5ml first
Alcohol-water (75:25) dissolve, supernatant crosses 0.45 μm of miillpore filter, take subsequent filtrate to get.
3. Dendrobidium huoshanness small molecule component content measures chromatographic condition：
Chromatographic condition：
Assay chromatographic condition：GraceAllitima C18 chromatographic columns (250mm*4.6mm, 5 μm)；Mobile phase uses
Binary gradient elutes system, A phases：0.2% Acetic Acid-Water, B phases：Acetonitrile；Gradient elution program such as table 1；It is measured with wavelength 290nm
Naringenin measures schaftoside with wavelength 334nm；Reference wavelength is 500nm, 30 DEG C of column temperature；Flow velocity 1.0mL/min, sample size
20μL。
Finger-print chromatographic condition：GraceAllitima C18 chromatographic columns, preferably 250mm × 4.6mm, 5 μm of specifications
Chromatographic column；Mobile phase：A phases：0.4% acetic acid+20mmol/L ammonium acetate aqueous solutions, B phases：Acetonitrile；Gradient elution：0~12min：
2%~15%B phases, 12~35min：15%~24%B phases, 35~45min：24%~36%B phases, 45~60min：36%~
75%B phases, 60~80min：75%~95%B phases；Flow velocity 1.0mL/min；30 DEG C of column temperature；20 μ L of sample size；Detection wavelength
280nm。
The gradient that 1 Dendrobidium huoshanness small molecule component content of table measures
Fig. 1 is the full ingredients fingerprint chromatogram of Dendrobidium huoshanness, Detection wavelength 280nm；
Fig. 2 is the test map figure of schaftoside (No. 1 peak) standard sample；
Fig. 3 is the test map figure of naringenin (No. 2 peaks) standard sample；
Fig. 4 is the test map of schaftoside (No. 1 peak) in Dendrobidium huoshanness；
Fig. 5 is the test map of naringenin (No. 2 peaks) in Dendrobidium huoshanness.
The foundation of the correlated characteristic finger-print of 4 Dendrobidium huoshanness schaftoside of embodiment
1. prepared by stem of noble dendrobium sample solution
Stem of noble dendrobium drying sample is taken, is crushed with pulverizer, pharmacopeia sieve (aperture 0.335mm) is crossed, precision weighs Dendrobium
1.000g (weighing error is no more than 0.2%), is placed in 100ml conical flasks, is separately added into 50mL75% methanol (V water：V first
Alcohol=25:75) it, takes out, filters after ultrasound 30min at room temperature, filtrate concentrated by rotary evaporation is to doing, with 75% methanol solvate (V water：V first
Alcohol=25:75) dissolve, be finally transferred to constant volume in 10ml volumetric flasks, shake up, with 0.45 μm of filtering with microporous membrane to get.Table 2
For the linear relationship of obtained reference substance schaftoside.
2 reference substance schaftoside linear relationship table of table
2. the method for building up of the correlated characteristic finger-print of Dendrobidium huoshanness schaftoside
The first step：Calculate the related coefficient of all covariant x and y；
Second step：The absolute value of related coefficient is arranged from big to small, preceding 2 √ n covariants is selected, is denoted as x_1,
x_2,…,x_p；
Third walks：By y and x_1, x_2 ..., x_p carry out linear regression, using Lasso methods, carry out variables choice.
First part's table of Lasso (LeastAbsolute Shrinkage and Selection Operator) function
The Optimality of representation model fitting, second part can be considered as punishment.This method is compressed small coefficient toward 0, once some coefficient
It is compressed to 0, corresponding variable is just deleted.Just look like use " sieve " filtering, the variable for influencing small is once just screened out.λ
Smaller, the more λ of variable in model are bigger, and shrinkage is bigger, and the variable selected is fewer.And Lasso methods are a kind of continuous
, orderly process, variance is smaller.When adjustment parameter is sufficiently large, penalty term has the estimated value of some of which coefficient is strong
Set up be set to 0 effect, thus LASSO can carry out variables choice, can obtain sparse model.
When independent variable is p, sample size n works as p>>N is used SIS method dimensionality reductions, then is screened using Lasso methods first
Variable.
SIS：Mγ={ 1≤i≤p:|ωi| before being | γ n | a bigger
Wherein, M*={ 1≤i≤p:βi≠ 0 } the subscript collection of nonzero coefficient in true mode is indicated；S=| M*| indicate non-zero system
Several numbers；ω=(ω1,ω2,...,ωp)T=XTy；For any given γ ∈ (0,1), the p element of ω is by absolute
Value is arranged and is defined from big to small；At this time | γ n | ＜ n choose MγThe corresponding independent variable of middle subscript makes superelevation dimension drop to d (d
≤ n) dimension；Wherein, d=n or d=[n/logn].
Lasso methods screening linear model be：
Wherein, yiFor i-th of response variable, y=(y1,y2,...,yn)'；XiIt is PnThe covariant of × 1 rank, X=(x1,
x2,...,xn)'；εiBe mean value be 0, variance σ2I.i.d stochastic error, E (ε)=0, Var (ε)=σ2In。
It is assumed that random entry is obeyed classic it is assumed that being：
(1) random entry has zero-mean, E (εi|xi)=0；
(2) random entry has same variance, Var (εi|xi)=σ2；
(3) random entry is without serial correlation, Cov (εi,εj)=0, i ≠ j；
(4) ε Normal Distributions, εi~N (0, σ2)。
The variance matrix of random entry is that a diagonal line is σ2, elsewhere for 0 square formation, as follows：
Wherein, InIt is the unit matrix of a n × n, n is the sample size of data,
In order to be carried out at the same time variables choice and estimate parameter, Lasso methods pass through penalized least-squares target letter
The minimum of numerical expression I is realized.
Wherein, y=(y1,y2,...,yn)T∈RnFor response variable vector.With stem of noble dendrobium data instance, there are two each stems of noble dendrobium
Response variable sequence (schaftoside (μ g/g), naringenin (μ g/g)).Response variable is influenced by independent variable, under normal circumstances y
For continuous variable.
X=(x1,x2,...,xn)TFor the design matrix of n × p, including influential on response variable all candidate from becoming
Amount.
P is the dimension of sample, and n is sample size.In stem of noble dendrobium data, dimension p is much larger than sample size n sample range, therefore minimum
Two, which multiply estimation, is no longer applicable in, and needs the method using variables choice to carry out model estimation.
β=(β1,β2,...,βp)TIt is the parameter of p dimensions.
For penalty, λ is adjusting parameter.In Variable Selection, the excellent degree of models fitting with for
Balance between the dynamics of selected variable number punishment is embodied by different criterion, and is adjusted here by directly choosing
For parameter come what is realized, different λ values corresponds to different punishment dynamics.λ is bigger, and the degree of compression is stronger, and finally estimation obtains
Non-zero parameter is fewer, and it is K folding cross-validation methods to select the most common methods of λ：
K-fold CV：
Generally, K can be taken as 5 or 10.
GCV criterion are a kind of approximate situations when K in CV criterion takes n, are defined as：
Wherein, SSEkIt is the residual sum of squares (RSS) of the CV submodels containing k variable, df=trace { P (λ) }.For final
The selection of optimal models can take the submodel of CV values or GCV value minimums.
Using linear model, due to initial argument p=333, sample size n=9, p>>N, thus Variable Selection be compared with
For important work.First after SIS dimensionality reductions, using Lasso method selection variables.
Lasso methods screening gained independent variable has 4, R-square 0.9848.
Lasso methods screening gained independent variable and its corresponding coefficient such as the following table 3, wherein first is classified as selected independent variable volume
Number, second is classified as corresponding coefficient, and third is classified as parameter variance, and the 4th is classified as inspection P values.
It is selected in independent variable and its corresponding coefficient obtained by 3 Lasso methods of table
| X_model (the independent variable X of selection) | β (coefficient of independent variable X) | Varbeta (variance of β) | P-value (P values) |
| Constant term | 7.757795 | 1.398185 | 2.88E-08 |
| 120 | 0.016332 | 0.003653 | 7.8E-06 |
| 83 | -0.00419 | 0.002873 | 0.145201 |
| 225 | 0.011372 | 0.006713 | 0.090248 |
| 243 | 0.007317 | 0.001999 | 0.000252 |
Table 3 the results show that using schaftoside as the selection result of response variable：1st is classified as and is selected using Lasso methods
Variable, that is, have selected variable 120,83,225 and 243, corresponding to p value (row 4) be respectively less than significance 0.05, have
Significant difference.The meaning of above-mentioned independent variable：The finger-print of Dendrobidium huoshanness n batches sample (n is not less than 10) is according to reservation
Finger-print peak area value after time unifying.
Row 2 are each variable specifically corresponding β parameter values.β value is just to illustrate the variable to stem of noble dendrobium schaftoside small molecule
It is influenced in the presence of forward direction；β value is that there are negative sense influences on stem of noble dendrobium schaftoside small molecule for negative explanation variable.The absolute value of β value is big
It is small that size of the variable to stem of noble dendrobium schaftoside small molecule influence degree is shown.Specifically, in table 3, variable 120,
The influence of 225 and 243 pairs of stem of noble dendrobium schaftoside small molecules is that just, wherein the positive of variable 120 influences maximum；Variable 83 is to the stem of noble dendrobium
The influence of schaftoside small molecule is negative.
The foundation of the correlated characteristic finger-print of 5 Dendrobidium huoshanness naringenin of embodiment
1. prepared by reference substance solution
Accurately weighed naringenin 4.08mg, is placed in 10ml volumetric flasks, adds 75% methanol dissolved dilution, shakes up, as deposit
Liquid.It is spare in being refrigerated in 4 DEG C of refrigerators.It is accurate again to draw a certain amount of reference substance stock solution, add 75% methanol dilution, accurately matches
Naringenin reference substance solution processed.By different dilution ratios, 7 concentration points of prepared composition are diluted, inject high performance liquid chromatography
Instrument.Table 4 is the linear relationship of obtained reference substance naringenin.
4 reference substance naringenin linear relationship table of table
2. the foundation of naringenin correlated characteristic finger-print
Using linear model, due to initial argument p=333, sample size n=10, p>>N, thus Variable Selection be compared with
For important work.The present invention uses Lasso method selection variables.
Lasso methods screening gained independent variable has 3, R-square 0.9203.
Lasso methods screening gained independent variable and its corresponding coefficient such as the following table 5, wherein first is classified as selected independent variable volume
Number, second is classified as corresponding coefficient, and third is classified as parameter variance, and the 4th is classified as inspection P values.
It is selected in independent variable and its corresponding coefficient obtained by 5 Lasso methods of table
| X_model (the independent variable X of selection) | β (coefficient of independent variable X) | Varbeta (variance of β) | P-value (P values) |
| Constant term | 3.226154 | 1.499972 | 0.031491 |
| 231 | 0.0075 | 0.003113 | 0.015995 |
| 65 | 0.009792 | 0.001398 | 2.49E-12 |
| 214 | -0.16808 | 0.145634 | 0.248446 |
Table 5 the results show that using naringenin as independent variable result：The variable selected using Lasso methods is 1 institute of row
Show, that is, filtered out variable 231,65 and 214, the p value (row 4) of the variable is respectively less than significance 0.05, has conspicuousness
Difference.The meaning of above-mentioned independent variable：The finger-print of the n batches sample (n is not less than 10) of Dendrobidium huoshanness is according to retention time pair
Finger-print peak area value after neat.
What row 2 provided is each variable specifically corresponding β parameter values.β value is just to illustrate that the variable is small to stem of noble dendrobium naringenin
There is positive influence in molecule；β value is that there are negative sense influences on stem of noble dendrobium naringenin small molecule for negative explanation variable.The absolute value of β value
Size of the variable to stem of noble dendrobium naringenin small molecule influence degree is shown in size.Specifically, in table 5,231 He of variable
The influence of 65 pairs of stem of noble dendrobium naringenin small molecules is that just, wherein the positive of variable 65 influences maximum；Variable 214 is small to stem of noble dendrobium naringenin
The influence of molecule is negative.
Show that the technology can distinguish Dendrobidium huoshanness and other stems of noble dendrobium to circle of good definition according to the result of generation molecular data
It comes, has the function of to identify that kind, generation sequencing molecular sequences can be used as this kind of identification of indicator.Meanwhile Dendrobidium huoshanness
The each sample performance in kind of two kinds of chemical small molecule contents of characteristic fingerprint pattern is stablized, and clear can be distinguished with other stems of noble dendrobium
Come, can also be used as one of identification of indicator of this kind.Therefore, a codes or data and finger-print can be used as the finger for identifying this kind
Mark, and the two has following incidence relation：(1) when generation data authentication sample is Dendrobidium huoshanness, the finger-print of the sample
With specific feature, i.e., this kind can be identified by a codes or data, and understand the Fingerprints of this kind；(2) work as fingerprint
When map identification sample is Dendrobidium huoshanness, one codes or data can also be deduced.Both therefore sufficient and necessary condition each other, and by
Stabilization is showed in each representative sample in the Fingerprints of this kind, it may be determined that the efficacy component content of this kind.Therefore, a generation
Sequencing data and finger-print can be used as the identification of indicator of this kind, and can be used as the evaluation index of medicinal material.If in cultivar identification
Be respectively adopted in quality evaluation a generation sequencing and finger-print be measured when, the qualification result of two methods can be incorporated in
Together so that more accurate to the qualification result of stem of noble dendrobium medicinal material, reliable.
A generation for 7 Dendrobidium huoshanness of embodiment is sequenced and the correlated characteristic finger-print of small molecule ingredient is in stem of noble dendrobium quality of medicinal material
Application in evaluation
1. utilizing the sequence with next-generation sequencing primer sequence and amplification sequencing parametric measurement stem of noble dendrobium medicinal material to be measured, reflected
It is set to Dendrobidium huoshanness medicinal material.
Generation sequencing primer sequence：
ITS-26SE：5’GAATTCCCCGGTTCGCTCGCCGTTAC 3’；
ITS-17SE：5’ACGAATTCATGGTCCGGTGAAGTGTTCG 3’；
Parameter is sequenced in amplification：PCR cycle is carried out after 98 DEG C of denaturation 2min, PCR cycle parameter is 98 DEG C of 20s；52℃
30s；4 DEG C of heat preservations are arranged in 68 DEG C of 1min, 38 cycles, 68 DEG C of 7min after amplification.
By being sequenced above, determine that stem of noble dendrobium medicinal material to be measured is Dendrobidium huoshanness kind.
2. the preparation of test sample determination sample
Precision weighs Dendrobidium huoshanness powder, sets in 100ml volumetric flasks, and it is 75 that volume ratio is added per 1g sample precisions:25 first
Alcohol-water 50ml is handled 30 minutes, cooled and filtered with 250W power, 40kHz frequency ultrasounds, by filtrate concentrated by rotary evaporation to doing, often
It is 75 that 1g Dendrobidium huoshanness powder, which accordingly uses 5ml volume ratios,:25 methanol-water dissolving, supernatant are crossed 0.45 μm of miillpore filter, are taken
Subsequent filtrate to get Dendrobidium huoshanness small molecule component content determination sample.
3. chromatography detects
Chromatographic condition：
Chromatographic column：GraceAllitima C18 chromatographic columns (250mm × 4.6mm, 5 μm)；Mobile phase：A phases：0.4% acetic acid
+ 20mmol/L ammonium acetate aqueous solutions, B phases：Acetonitrile；Gradient elution：0~12min, 2%~15%B, 12~35min, 15%~
24%B, 35~45min, 24%~36%B；45~60min, 36%~75%B；60~80min, 75%~95%B, flow velocity
1.0mL/min；30 DEG C of column temperature；20 μ L of sample size；Detection wavelength 280nm.
Sample preparation methods：
This product powder (crossing No. three sieves) 1.00g is taken, it is accurately weighed, it sets in 100ml volumetric flasks, precision plus methanol-water (75:
25) 50ml, is ultrasonically treated (power 250W, frequency 40kHz) 30 minutes, lets cool, and filters, and filtrate concentrated by rotary evaporation is to doing, with 5ml first
Alcohol-water (75:25) dissolve, supernatant crosses 0.45 μm of miillpore filter, take subsequent filtrate to get.
Full ingredient fingerprint chromatogram is measured with wavelength 280nm when detecting, is by obtained full ingredients fingerprint and Fig. 1
The finger-print of control carries out similarity comparison；It is up-to-standard that similarity, which is more than 0.85,.
Traditional Chinese medicine fingerprint be analytical instrument detect various reflection Chinese medicines, semi-finished product and Chinese patent drug (or plant
Medicine) contained by the distribution of complicated chemical material composition quantization characteristic association drug activity control with the characteristics of, from macroscopically whole reflection
Type, quantity and the content characteristics of contained chemical compositions in Chinese medicine, semi-finished product and Chinese patent drug (or autonomic drug), and energy
Change the collection of illustrative plates for the bioactivity information characteristics for disclosing potential complexity.
The type for determining the stem of noble dendrobium is sequenced in the present invention by a generation first, then by measuring stem of noble dendrobium small molecule component content data
Be associated Journal of Sex Research with stem of noble dendrobium finger-print whole peak area, modeled by associated data, find out in the stem of noble dendrobium relevance,
In this way can thoroughly evaluating stem of noble dendrobium quality, and effectively can accurately differentiate and control the quality of Dendrobidium huoshanness medicinal material so that analysis
As a result relatively reliable, avoid the interference of other kinds of stem of noble dendrobium medicinal material.
More than, it is merely preferred embodiments of the present invention, but the protection domain invented is not limited thereto, it is any ripe
Know those skilled in the art in the technical scope disclosed by the present invention, the change or replacement that can be readily occurred in should all be contained
Lid is within protection scope of the present invention.Therefore, the scope of protection of the invention shall be subject to the scope of protection specified in the patent claim.
Claims (7)
1. a kind of quality determining method of Dendrobidium huoshanness, which is characterized in that including：
1) with ITS-26SE：5 ' GAATTCCCCGGTTCGCTCGCCGTTAC 3 ' and
ITS-17SE：5 ' ACGAATTCATGGTCCGGTGAAGTGTTCG 3 ' are primer, carry out PCR amplification sequencing, are waited for identification
The kind for surveying stem of noble dendrobium medicinal material is Dendrobidium huoshanness；
2) chromatography detection is carried out to the sample that sample size is n, obtained with chemical small molecule ingredient schaftoside and/or naringenin
As the detection data with reference to ingredient；
3) finger-print detection is carried out respectively to sample, obtains the finger-print peak area value of the full chemistry ingredient of Dendrobidium huoshanness；
It 4), will be in finger-print with the component content value of schaftoside in chromatographic data and/or naringenin variable in response
The peak area value of other ingredients establishes analysis model as independent variable, passes through Lasso (The Least Absolute
Shrinkage and Selection Operator) method selection variables establish the correlated characteristic fingerprint of chemical small molecule ingredient
Spectrum model, basic model are：
Y=XTβ+ε
Wherein, y is response variable, y=(y1,y2,...,yn)T；X is matrix, X=(x1,x2,...,xn)T；E (ε)=0；Var
(ε)=σ2In；ε is the stochastic error of model；σ is the standard deviation of stochastic error；N is sample size；InIt is the list of a n × n
Position battle array.
2. according to the method described in claim 1, it is characterized in that, the Lasso methods are to calculate to realize by formula I：
In formula I, n is sample size；p*For variable number；P is the dimension of sample；Y=(y1,y2,...,yn)T∈RnBecome for response
Amount；X=(x1,x2,...,xn)TFor the design matrix of n × p, including all candidate independents variable influential on response variable；λ is
Adjusting parameter；For penalty；β0Meaning be formula intercept item, that is, when all independent variable x be 0 when respond
The value of variable y；βjIt is meant that independent variable xjCoefficient, i.e. independent variable xjTo the influence degree of response variable y.
3. according to the method described in claim 2, it is characterized in that, the selection method of the λ, which is K, rolls over cross-validation method：
K-fold CV：
Wherein, K is 5 or 10.
4. according to the method described in claim 3, it is characterized in that, the analysis model is to take the submodel of CV values minimum.
5. according to the method described in claim 2, it is characterized in that, the selection of the λ follows GCV criterion, the GCV criterion are fixed
Justice is：
Wherein, SSEkIt is the residual sum of squares (RSS) of the CV submodels containing k variable, df=trace { P (λ) }.
6. according to the method described in claim 5, it is characterized in that, the analysis model is to take the submodel of GCV values minimum.
7. according to the method described in claim 2, when chromatographic data is presented superelevation and ties up situation, following SIS (Sure are used first
Independence Screening) method selection variables, recycle the processing of Lasso methods；
SIS：Mγ={ 1≤i≤p:|ωi| before being | γ n | a bigger
Wherein, M*={ 1≤i≤p:βi≠ 0 } the subscript collection of nonzero coefficient in true mode is indicated；S=| M*| indicate nonzero coefficient
Number；ω=(ω1,ω2,...,ωp)T=XTy；For any given γ ∈ (0,1), the p element of ω by absolute value from
It to minispread and defines greatly；At this time | γ n | ＜ n choose MγThe corresponding independent variable of middle subscript makes superelevation dimension drop to d (d≤n)
Dimension；Wherein, d=n or d=[n/log n].
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710064180.3A CN108398511B (en) | 2017-02-04 | 2017-02-04 | Quality detection method for dendrobium huoshanense |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710064180.3A CN108398511B (en) | 2017-02-04 | 2017-02-04 | Quality detection method for dendrobium huoshanense |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108398511A true CN108398511A (en) | 2018-08-14 |
| CN108398511B CN108398511B (en) | 2021-03-16 |
Family
ID=63093427
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710064180.3A Active CN108398511B (en) | 2017-02-04 | 2017-02-04 | Quality detection method for dendrobium huoshanense |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108398511B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108398515A (en) * | 2017-02-04 | 2018-08-14 | 北京蓝标成科技有限公司 | A kind of quality determining method of Dendrobium Chrysotoxum Lindl |
| CN108398516A (en) * | 2017-02-04 | 2018-08-14 | 北京蓝标成科技有限公司 | A kind of quality determining method of Dendrobium fimbriatum Hook |
| CN114304639A (en) * | 2022-02-24 | 2022-04-12 | 河南城建学院 | Tortoise jelly for lowering blood pressure by using linseed gum as stabilizer and preparation method thereof |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101020921A (en) * | 2006-12-22 | 2007-08-22 | 福建省农业科学院生物技术研究所 | Process of analyzing descending differentiated fatty acid type of Ralstonia solanacearum |
| CN101726547A (en) * | 2008-10-15 | 2010-06-09 | 中山市中智药业集团有限公司 | Dendrobe chromatogram finger print measuring method |
| CN101979052A (en) * | 2010-09-30 | 2011-02-23 | 广西壮族自治区农业科学院蔬菜研究所 | Method for establishing high-performance liquid chromatography (HPLC) fingerprint of Guangxi dendrobium candidum wall. ex lindl and standard fingerprint of Guangxi dendrobium candidum wall. ex lindl |
| CN102879486A (en) * | 2012-09-05 | 2013-01-16 | 山东大学 | Method for screening traditional Chinese medicine effect related ingredients and model building method |
| CN105138861A (en) * | 2015-05-31 | 2015-12-09 | 青岛市食品药品检验研究院 | Building method for rhubarb medicinal material trueness/falseness and species prediction model |
| CN105424850A (en) * | 2015-11-05 | 2016-03-23 | 北京蓝标一成科技有限公司 | Quality evaluation method for dendrobe medicinal material |
| CN105477006A (en) * | 2015-10-14 | 2016-04-13 | 广州白云山和记黄埔中药有限公司 | Stomatitis clearing active component group and fingerprint characteristic spectrum constructing and quality detecting method for same |
| CN105758962A (en) * | 2016-03-03 | 2016-07-13 | 山东世博金都药业有限公司 | Quality control method of liuwei wuling tablets |
-
2017
- 2017-02-04 CN CN201710064180.3A patent/CN108398511B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101020921A (en) * | 2006-12-22 | 2007-08-22 | 福建省农业科学院生物技术研究所 | Process of analyzing descending differentiated fatty acid type of Ralstonia solanacearum |
| CN101726547A (en) * | 2008-10-15 | 2010-06-09 | 中山市中智药业集团有限公司 | Dendrobe chromatogram finger print measuring method |
| CN101979052A (en) * | 2010-09-30 | 2011-02-23 | 广西壮族自治区农业科学院蔬菜研究所 | Method for establishing high-performance liquid chromatography (HPLC) fingerprint of Guangxi dendrobium candidum wall. ex lindl and standard fingerprint of Guangxi dendrobium candidum wall. ex lindl |
| CN102879486A (en) * | 2012-09-05 | 2013-01-16 | 山东大学 | Method for screening traditional Chinese medicine effect related ingredients and model building method |
| CN105138861A (en) * | 2015-05-31 | 2015-12-09 | 青岛市食品药品检验研究院 | Building method for rhubarb medicinal material trueness/falseness and species prediction model |
| CN105477006A (en) * | 2015-10-14 | 2016-04-13 | 广州白云山和记黄埔中药有限公司 | Stomatitis clearing active component group and fingerprint characteristic spectrum constructing and quality detecting method for same |
| CN105424850A (en) * | 2015-11-05 | 2016-03-23 | 北京蓝标一成科技有限公司 | Quality evaluation method for dendrobe medicinal material |
| CN105758962A (en) * | 2016-03-03 | 2016-07-13 | 山东世博金都药业有限公司 | Quality control method of liuwei wuling tablets |
Non-Patent Citations (6)
| Title |
|---|
| JIANQING FAN ET AL: "A Selective Overview of Variable Selection in High Dimensional Feature Space", 《STATISTICA SINICA》 * |
| TOMOKO T AKAMIYA ET AL: "Identification of Dendrobium Species Used for Herbal Medicines Based on Ribosomal DNA Internal Transcribed Spacer Sequence", 《BIOL. PHARM. BULL.》 * |
| 周桂芬 等: "江省铁皮石斛黄酮类成分高效液相色谱指纹图谱的建立", 《中国药学杂志》 * |
| 朱尔一: "一种适合用于处理中药指纹图谱数据的偏最小二乘法", 《计算机与应用化学》 * |
| 滕会会 等: "基于中药指纹图谱结合模式识别的清开灵软胶囊批次间稳定性控制研究", 《环球中医药》 * |
| 高少龙: "几种变量选择方法的模拟研究和实证分析", 《中国优秀硕士学位论文全文数据库（基础科学辑）》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108398515A (en) * | 2017-02-04 | 2018-08-14 | 北京蓝标成科技有限公司 | A kind of quality determining method of Dendrobium Chrysotoxum Lindl |
| CN108398516A (en) * | 2017-02-04 | 2018-08-14 | 北京蓝标成科技有限公司 | A kind of quality determining method of Dendrobium fimbriatum Hook |
| CN108398516B (en) * | 2017-02-04 | 2020-12-15 | 北京蓝标一成科技有限公司 | Quality detection method of dendrobium fimbriatum |
| CN114304639A (en) * | 2022-02-24 | 2022-04-12 | 河南城建学院 | Tortoise jelly for lowering blood pressure by using linseed gum as stabilizer and preparation method thereof |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108398511B (en) | 2021-03-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105424850B (en) | A kind of detection method of stem of noble dendrobium medicinal material | |
| CN106990214A (en) | A kind of method for evaluating Chinese medicine quality | |
| CN108398511A (en) | A kind of quality determining method of Dendrobidium huoshanness | |
| CN105987966B (en) | Callicarpa kwangtungensis Chun method of quality control and its method for establishing model based on spectrum effect relationship | |
| CN102370891A (en) | Method for authenticating dendrobium officinale by using HPLC fingerprint | |
| CN111272904B (en) | Construction method and application of characteristic spectrum of medicine terminalia chebula and fructus chebulae tomentosa | |
| CN108398513A (en) | A kind of quality determining method of Herba Dendrobii | |
| CN108398512A (en) | A kind of quality determining method of dendrobium devonianum | |
| CN108398510A (en) | A kind of quality determining method of Dendrobium aphyllum (Roxb.) C. E. Fisch. | |
| CN108398491A (en) | A kind of quality determining method of Dendrobium loddigesii | |
| CN108398490A (en) | A kind of quality determining method of HERBA DENDROBII | |
| CN108398492A (en) | A kind of quality determining method of dendrobium candidum | |
| Li et al. | Identification of Bletilla striata and related decoction pieces: a data fusion method combining electronic nose, electronic tongue, electronic eye, and high-performance liquid chromatography data | |
| Jiang et al. | In-line spectroscopy combined with multivariate analysis methods for endpoint determination in column chromatographic adsorption processes for herbal medicine | |
| CN108398515A (en) | A kind of quality determining method of Dendrobium Chrysotoxum Lindl | |
| CN108398516A (en) | A kind of quality determining method of Dendrobium fimbriatum Hook | |
| CN108205028A (en) | The method for building up of the correlated characteristic finger-print of HERBA DENDROBII chemical small molecule ingredient | |
| CN108205025A (en) | The method for building up of the correlated characteristic finger-print of dendrobium devonianum chemical small molecule ingredient | |
| Patel et al. | Arbitrating Identification Issues of Picrorhiza kurroa Samples by ATR-FTIR Spectroscopy Using Multivariate Analysis | |
| CN115060695A (en) | Method for identifying storage years of wolfberry fruits based on three-dimensional fluorescence spectrum | |
| CN108205026A (en) | The method for building up of the correlated characteristic finger-print of Dendrobidium huoshanness chemical small molecule ingredient | |
| CN108205029A (en) | The method for building up of the correlated characteristic finger-print of Dendrobium loddigesii chemical small molecule ingredient | |
| CN108205037A (en) | The method for building up of the correlated characteristic finger-print of dendrobium candidum chemical small molecule ingredient | |
| CN108205039A (en) | The method for building up of the correlated characteristic finger-print of Dendrobium aphyllum (Roxb.) C. E. Fisch. chemical small molecule ingredient | |
| CN108205038A (en) | The method for building up of the correlated characteristic finger-print of Dendrobium Chrysotoxum Lindl chemical small molecule ingredient |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |