CN101813680A - Method for quantitatively evaluating medicament toxicity by using metabonomic technology - Google Patents
Method for quantitatively evaluating medicament toxicity by using metabonomic technology Download PDFInfo
- Publication number
- CN101813680A CN101813680A CN201010141847A CN201010141847A CN101813680A CN 101813680 A CN101813680 A CN 101813680A CN 201010141847 A CN201010141847 A CN 201010141847A CN 201010141847 A CN201010141847 A CN 201010141847A CN 101813680 A CN101813680 A CN 101813680A
- Authority
- CN
- China
- Prior art keywords
- group
- toxicity
- sample
- administration
- adopt
- 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.)
- Pending
Links
Images
Landscapes
- Other Investigation Or Analysis Of Materials By Electrical Means (AREA)
- Investigating Or Analysing Biological Materials (AREA)
Abstract
The invention discloses a method for quantitatively evaluating medicament toxicity by using metabonomic technology, which is characterized by comprising the following steps: comprehensively and quantitatively measuring small molecule compounds in a biological sample by using the measuring technology based on mass spectrum, nuclear magnetic resonance and the like, then establishing a multi-dimensional spatial mathematical model by adopting a multi-variable data processing method, calculating a relative distance between an administration group and a control group and taking the relative distance as a quantitative index for evaluating the medicament toxicity so as to solve the difficult problem that the medicament toxicity evaluation lacks the quantitative evaluating index. Compared with the conventional toxicity evaluating method, the method has the advantages of wide application, sensitivity, simple and convenient sampling, no harm to the body, and capability of reflecting the toxicity function more comprehensively, and providing a comprehensive and reliable quantitative evaluating method for toxicity evaluation in new medicament research and development and pharmacologic research.
Description
Technical field
The present invention relates to the new method of drug toxicity quantitative evaluation, be specifically related to adopt endogenous micromolecular compound in gas chromatography detection by quantitative people, animal or the cell, adopt multivariate data disposal route computational mathematics model, calculating administration group and control group relative distance method as the drug toxicity quantitative evaluation.
Background technology
For a long time, in pharmacological research, the toxicity of many medicines relies on qualitative and non-quantitation, subjectivity but not objective, rough but not accurate, unilateral but not comprehensive standard are estimated, and the concrete deficiency of these methods is mainly reflected in:
1.
Quantizating index lacksThough toxicity assessment has adopted some convenient, effectively evaluating indexs, as transaminase, white blood cell number etc., also has many toxicity to lack clear and definite quantizating index, is difficult to carry out accurate detection and evaluation with existing method.For example medicine to the power of the toxicity of tissue or organ such as liver, kidney, pain degree, allergic reaction, rejection, cause the degree to neural excitement, inhibition such as unreal, dizzy etc.
2.
SubjectivityFor want of objective quantitative target, that the evaluation of many toxicity can only be taked is subjective, external, artificial observational technique carries out qualitative evaluation, as histotomy, imaging technique, various electron microscopic examination, cell dyeing, or the dependence experience is judged or subjective sensation is carried out scalar quantization, makes drug toxicity pass judgment on and has very big subjectivity and uncertainty.
3.
One-sidednessThere is certain one-sidedness in many indexs, have just reflected the state of indivedual biochemical functions, organ-/ tissue, lack evaluation criterion whole, system.As indexs such as transaminase, kreatinin, erythrocyte sedimentation rates.
4.
SuperficialityMany indexs have only reflected presentation (as blood pressure, tic, hydrostomia, pupil size etc.), do not reflect the change of body inward nature.
5.
Rough propertyThe index of toxicity assessment is sensitive inadequately, often needs heavy dose, long-time administration just can observe xicity related index.
6.
NocuitySome evaluation methods are big or expense is expensive to body injury, as biopsy, intervention, radiography, tomoscan etc., lack damaging little, economy method easily.
In a word, the method limitation of existing many toxicity assessments is bigger, lack quantitative criterion, lack objectivity, comprehensive, specific aim, be unfavorable for drug toxicity is carried out quantitative, objective and accurate evaluation, become the huge obstacle of serious restriction pharmacology/toxicologic study.Press for and seek and found new drug toxicity evaluation method.
Body endogenous small-molecule substance group is the basis of vital movement, and the functional status of body must be reflected on the internal metabolism group (endogenous micromolecular compound general name).Studies show that under toxic state, the metabolism of biosome and wherein a lot of micromolecular compound level occur obviously unusual.Toxicity is strong more, and is also big more to the influence of the every function of biosome, and the micromolecule level also departs from normal condition more in every functional status/body of body, and the performance on metabolism group is exactly that the medication group is away from normal group; And toxicity is weak more, and is also more little to the influence of the every function of biosome, departs from normal condition on the also less degree of micromolecule level in every functional status/body of body, and the performance on metabolism group is exactly that medication group and normal group have on a small quantity and depart from.And in toxicity over time in the process, along with every function of body is recovered gradually, micromolecule and metaboilic level also are restored gradually in the body, and the performance on metabolism group is exactly gradually near normal group.But therefore adopt the toxicity of metabolism group method quantitative evaluation medicine.
Utilize suitable metabolism group testing tool, hundreds of even thousands of molecular weight are less than 1000 all kinds of micromolecular compounds in can the one-time detection biological specimen.Be determined as example with GC/TOFMS, to a lot of compound test sensitivity up to 10
-12Mol (absolute sense limit), relative sensitivity reaches 10
-9Mol/mL.These compounds comprise nearly all amino acid, glycitols compound, fatty acid, lipid, small molecular organic acid class, nucleosides and purine compound, ammoniac compounds, neurotransmitter or the like, they are the essential raw material of vital movement, also be organism metabolism product/intermediate, or the important substance basis of body growth, growth, bio signal conduction and metabolic cycles.Closely related with the glycometabolism that plays vital role very in the vital movement, lipid metabolism, tricarboxylic acid cycle, urea cycle, amino acid circulation etc.Therefore, micromolecular variation both can embody to system synthesis the result of dealed with medicine went in the body of detection, can also be according to sample displacement quantitative evaluation drug toxicity before and after the administration.Up to now, also do not utilize the metabolism group data to set up mathematical model, calculating administration group and control group relative distance are carried out quantitative evaluation to drug toxicity report.
Summary of the invention
Technical matters to be solved by this invention is: utilize the metabolism group method, endogenous micromolecule in the quantitative measurement biological specimen comprehensively,, the The data multivariate data disposal route that obtains is set up mathematical model, calculate the relative distance of administration group and control group, index so that this quantitative value is estimated as drug toxicity solves the problem that drug toxicity lacks accurate method for quantitatively evaluating.
For addressing the above problem, the invention provides following technical scheme, step comprises:
Sample collecting and processing: gather all kinds of biological specimens of clinical patient, animal pattern, tissue/cell, be generally the cell or the nutrient solution of blood, urine, in vitro culture; Sample carries out liquid-liquid through organic solvent and extracts, and organic solvent comprises ethyl acetate, chloroform, ether, normal butyl alcohol, sherwood oil, methylene chloride, acetonitrile; Or through albumen precipitation, the method for albumen precipitation comprises that the independent or comprehensive modes of method such as adding organic solvent (as methyl alcohol, ethanol, acetone, acetonitrile, isopropyl alcohol), various soda acid salt precipitation, thermal precipitation, filtration/ultrafiltration, Solid-Phase Extraction handle; Sample can not carry out drying, or first drying is utilized all kinds of solvent dissolvings that contain organic solvent and water (saliferous or not saliferous separately or comprehensive) again; Sample does not carry out derivatization or utilizes reagent to carry out derivatization treatment.
Sample analysis and data processing: adopt based on mass spectroscopy and chromatograph joint used technical method or the assay method of nuclear magnetic resonance technique above-mentioned sample is detected, these methods can be liquid chromatography-mass spectrography, gas chromatography-mass spectrum, Capillary Electrophoresis chromatography-mass spectroscopy, nuclear magnetic resonance etc.; Through obtaining the quantitative data at each peak in the chromatogram after the data processing, these data can be peak area or peak height, or the quantitative data that is calculated by peak area or peak height.
An outstanding advantage of the present invention be above-mentioned detection method can detection bodies in a large amount of micromolecular compounds, and thoroughly evaluating drug effect effect/or the health status of body based on this.When dealed with medicine went was strong, whole metabolism spectrum departed from normally bigger, and drug toxicity is when more weak, and whole metabolism spectrum departs from normally less.GC/TOF-MS measured the total ions chromatogram of serum sample after Fig. 1 had provided normal SD rats and given triptolide, can find that from chromatogram sample and control group have notable difference after the administration.But the method for this visual observations can only be done rough, a subjective judgement, can't realize quantitative evaluation.
The calculating of mathematical model foundation and relative distance value: the various multivariate data process softwares of above-mentioned The data, can be SPSS, Matlab, SIMCA-P etc., select partial least square method-discriminatory analysis (PLS-DA), quadrature partial least square method (OPLS), quadrature partial least square method-discriminatory analysis (OPLS-DA), principal component analysis (PCA) (PCA), Nonlinear Mapping (Nonlinemapping, NLM), cluster analysis methods such as (HCA) sets up mathematical model, obtains model parameter and the sample volume coordinate in the multidimensional mathematical model; Calculate administration group sample and control group relative distance.The hyperspace here can be 1,2,3 dimensions, also can be 4,5,6 even hyperspace more.Above-mentioned control group can be an own control before the administration, also can be the model group parallel control of not administration, can also be the normal group contrast of not administration.Above-mentioned space relative distance can be got the coordinate mean value of respectively organizing sample earlier, calculates again, also can calculate distance between each sample earlier, and averaging obtains again.
The outstanding advantage that adopts the method for principal component analysis (PCA) (PCA), partial least square method-discriminatory analysis Projection Analysis such as (PLS-DA) is to observe the relative position of each sample in the hyperspace model convenient, intuitively, Fig. 2 shows that high dose triptolide (2.4mg/kg) administration causes that the metabolism of SD rat composes now obviously unusual, particularly after the administration 1,3 day, recovery trend was arranged to the 5th, 7 day; And low dosage triptolide (0.6mg/kg) administration causes that SD rat metabolism spectrum occurred unusually at first day, and (3,5,7 days) very fast trend is normal subsequently, embodies tangible dosage and temporal correlation.
The same with above-mentioned total ion current figure, though the method for visualization is used for the qualitative judge of toxicity in a large number like this, its subject matter is to quantize, and the result judges and has subjectivity.
Beneficial effect of the present invention:
Body endogenous small-molecule substance group is the basis of vital movement, and the functional status of body must be reflected on the internal metabolism group (endogenous micromolecular compound general name).Studies show that under toxic state, the metabolism of biosome and wherein a lot of micromolecular compound level occur obviously unusual.Toxicity is strong more, and it is big more that the medication group departs from normal group; And toxicity is weak more, and it is more little to depart from normal group.But therefore adopt the toxicity of metabolism group method quantitative evaluation medicine.
1. utilize the metabolism group result of study can quantitative response drug toxicity, strengthened objectivity and accuracy, avoided that some drug toxicity indexs only rely on artificially, the problem of subjective and qualitative evaluation.
2. utilize the metabolism group result of study can synthetically reflect drug toxicity comprehensively, avoided some drug toxicity indexs only to reflect the problem of topical remedy's toxicity.
3. the quantizating index of metabolism group is widely applicable, applicable to the quantitative evaluation of all kinds of toxicity.
4. the drug toxicity evaluation method of metabolism group adopts blood plasma, urine equal samples, and cost is low, little to the body injury.
5. the evaluation method of metabolism group is sensitiveer than conventional method, can save drug dose, reduce injury and death toll to animal, helps reducing research cost and watches for animals.
Description of drawings
The total ions chromatogram of rat blood serum sample after Fig. 1 GC/TOF-MS measures normal SD rats and gives triptolide.Significant change appears in SD rat blood serum total ions chromatogram after the administration as can be seen.A: normal SD rats serum total ions chromatogram; B: administration rat blood serum total ions chromatogram.Can find that from chromatogram sample and control group have notable difference after the administration.But the method for this visual observations can only be done rough, a subjective judgement, can't realize quantitative evaluation.
Mark chromatographic peak 1-31 is the part of compounds of identifying in the chromatogram among the figure, is specially: 1, and lactic acid; 2, alanine; 3, the 3-hydroxybutyric acid; 4, urea; 5, valine; 6, phosphoric acid; 7, leucine; 8, glycocoll; 9, serine; 10, threonine; 11, amidomalonic acid; 12, pyroglutamic acid; 13, halfcystine; 14, ornithine; 15, glutamic acid; 16, phenylalanine; 17, the acid of methyl nutmeg; 18, glutamine; 19, [
13C
2]-nutmeg acid (interior mark); 20, citric acid; 21, glucose; 22, palmitic acid; 23, uric acid; 24, inositol; 25, linoleic acid; 26, oleic acid; 27, tryptophane; 28, stearic acid; 29, the 6-glucose 1-phosphate1-; 30, the 1-phosphoinositide; 31, cholesterol.
Cause after the administration of Fig. 2 triptolide that the metabolism of SD rat composes existing variation in various degree.High dose triptolide (2.4mg/kg) administration causes that the metabolism of SD rat composes now obviously unusually, particularly after the administration 1,3 day, recovery trend is arranged to the 5th, 7 day; It is unusual that low dosage triptolide (0.6mg/kg) administration causes that SD rat metabolism spectrum occurred at first day, and (3,5,7 days) very fast trend is normal subsequently.The same with above-mentioned total ion current figure, though the method for visualization is used for the qualitative judge of toxicity in a large number like this, its subject matter is to quantize, and the result judges and has subjectivity.L: low dosage; H: high dose; 0,1,3,5,7: before the administration or after the administration 1,3,5,7 day.
Embodiment
The present invention carries out detailed explanation by the following examples, but and does not mean that the present invention only limits to this.
Embodiment
Triptolide is to the metabolism group research of SD rat toxicity effect
1. experimental program, sample collecting
8 all Sprague Dawley in age (SD) rat adaptability raised for two weeks, after the grouping respectively by high and low (2.4 and 0.6mg/kg) dosage single gastric infusion, 1,3,5,7 day blood (the rat fasting is 12 hours before the blood sampling) after (0 day), the administration before the collection administration, blood leaves standstill 1h 37 ℃ of water-baths, 3500rpm is centrifugal, and upper serum ,-80 ℃ of preservations are collected in the back.Gather liver, nephridial tissue and section simultaneously, a part is used for the mensuration of metabolism group; Another part serum and histotomy are used for clinical biochemical and histopathological examination.
The result: the visible liver cell nuclear pyknosis of liver tissue slices after the administration of high dose triptolide, acidophilia dyeing strengthen, and the clinical biochemical inspection finds that glutamic-pyruvic transaminase, glutamic-oxalacetic transaminease raise, leukocyte count increases, the prompting overt toxicity; And the low dosage triptolide is not seen overt toxicity, table 1.
2. sample preparation
Freezing serum is at 37 ℃ of water-baths 20min that thaws, and after the vortex vibration, gets 50 μ l and adds 200 μ l and contain stable isotope
13The methanol solution (12.5 μ g/ml) of the interior mark meat bandit acid of C, vortex vibration 3min, 4 ℃ of refrigerators left standstill 1 hour, and 19600g and 4 ℃ of centrifugal 10min get 100 μ l supernatants in the GC bottle, and decompression volatilizes.Add 30 μ l methoxamine pyridine solutions (10mg/ml) in the GC bottle, vortex vibration 3min leaves standstill 16h and carries out oximate under the room temperature.Add 30 μ l TMS trifluoroacetyl MSTFA (containing 1%TMCS) as catalyzer, vortex vibration 1min, room temperature leaves standstill 1h and carries out derivative reaction, adds the n-heptane solution (30 μ g/ml) of 30 μ l external standard methyl meat bandit acid esters at last again, carries out GC-TOF/MS after the mixing and detects.
3.GC/TOF-MS measure
Instrument: (GC:Angilent 6890N gas chromatograph is equipped with Angilent 7683B automatic sampler and 100 sample feeding dishes of G2614A type to gas chromatography-flight time mass spectrum (GC/TOF-MS) detection system; TOF-MS:Pegasus III, Leco, USA).
Chromatographic condition: chromatographic column is DB-5 quartz capillary column (10m * 0.18mm i.d., J﹠amp; W Scientific, USA), sample size: 1 μ l, adopt the original mold formula that flows to that is regardless of; Carrier gas: helium; Constant current speed: 1ml/min; The temperature programme pattern: 70 ℃ keep 2.0min, with 35 ℃/min linearity linear temperature increase to 305 ℃ at the uniform velocity, keep 2.0min then.
Mass spectrum condition: injector temperature: 250 ℃; Scavenging period and flow velocity: 1min, 20ml/min; Transfer tube temperature: 250 ℃; Ion source temperature: 200 ℃; Ion gun voltage and current :-70eV, 3.0mA; MS adopts the full scan mode to carry out data acquisition, and MS adopts the full scan mode to carry out data acquisition; Sweep limit: m/z 50-800; Sweep velocity: 20spectra/s; Detecting voltage is-1690v.
Measurement result: the GC/TOF-MS total ions chromatogram (Fig. 1) that under above-mentioned testing conditions, can obtain sample.The software (ChromaTOF 2.00) that utilizes instrument to carry can extract each chromatographic peak peak area in each working sample chromatogram, form a data matrix of forming by peak area, this data matrix is organized totally 60 samples (being first row) and 195 chromatographic peaks (being first row) before comprising high dose triptolide administration group (1,3,5,7 day) and low dosage triptolide administration group (1,3,5,7 day) and administration, is kept in the excel file.
4. the calculating of mathematical model foundation and relative distance value
With above-mentioned data call in multivariate data analysis soft sim CA P-11 (Umetrics AB,
Sweden) in, utilize data internal relation projection-offset minimum binary-discriminatory analysis (PLS-DA) computational mathematics model, the major component number of determining model is 2, this mathematical model is one 2 dimension space model, each sample all is a point in this space, and its position is determined by x and y coordinate parameters.Can obtain the distribution plan of each sample in the planimetric coordinates of this model, Fig. 2 by above-mentioned model.
Extract the volume coordinate parameter of each sample in model, calculate the mean value of every group of sample horizontal ordinate (x) and comprehensive coordinate (y) according to following formula (1); By formula (2) calculate each/change distance before and after the group sample administration, this distance value has promptly been represented the influence degree of triptolide to rat internal metabolism group, promptly a little less than the strong toxicity.
Formula 1:
Xi＝(Xi1+Xi2+Xi3+Xi4+Xi5+Xi6)/6
Yi＝(Yi1+Yi2+Yi3+Yi4+Yi5+Yi6)/6
Xi, Yi are respectively i days horizontal ordinates of administration group and ordinate mean value.Wherein Xi1～6 are 1～No. 6 sample abscissa value; Yi1～6 are 1～No. 6 sample ordinate value.
Formula 2:
Si＝[(Xi-X
0)
2+(Yi-Y
0)
2]
1/2
Si is i days and an administration front distance after the administration; X
0, Y
0Be respectively the preceding X of administration, Y coordinate figure.
Can calculate administration front and back sample distance and group distance respectively according to above-mentioned formula, the results are shown in Table 2.By table 2 result as can be seen, 1 day, 3 days distance value maximums of high dose group illustrate that toxicity is the most obvious, weakened gradually to 5,7 days, and near group before the administration; And low dose group just occurred departing from more greatly after administration in 1 day, thereafter rapidly near control group.It can also be seen that the dosage and the time dependence of toxicity from The above results.Because conventional toxicity index is not found ANOMALOUS VARIATIONS to occur under the low dosage, and the relative distance method of metabolism group, therefore metabolism group method and relative distance method may be more sensitiveer than conventional method, and can represent the power that medicine is regulated whole metabolism group quantitatively, promptly comprehensive, quantitative response drug toxicity size.
Table 1SD rat gives triptolide front and back biochemical analysis result
*P＜0.05,
*P＜0.01,
* *Contrast before P＜0.001vs administration.
ALT, glutamic-pyruvic transaminase; AST, glutamic-oxalacetic transaminease; NE, neutrocyte; WBC, leucocyte.
Table 2 respectively organize sample in mathematical model average coordinates and the triptolide administration after with the relative distance of control group
Claims (10)
- One kind use metabonomic technology carry out the toxicity quantitative evaluation method relied on is the resulting metabolism group data of Instrument measuring, its feature comprises the following aspects:A) adopt serum to detect as sample;B) adopt the method for methanol extraction albumen that micromolecule in the serum is extracted;C) adopt the method for TMS trifluoroacetyl MSTFA that sample is carried out derivatization;D) adopt gas chromatography-flight time mass spectrum (GC/TOF-MS) to carry out sample analysis;E) use SIMCAP-11 software and offset minimum binary one discriminatory analysis (PLS-DA) and set up mathematical model;F) extracting parameter from the hyperspace mathematical model calculates relative distance between medication group and the control group.
- 2. require in 1 serum as the biological specimen except that right, biological specimen also can derive from people, animal, cell, mushroom, histotomy etc., specifically comprises whole blood, blood plasma, serum, urine, cerebrospinal fluid, saliva, tear, sweat, tissue homogenate, cell or cell culture fluid/base, bacterium and inoculum/base.
- 3. one of them group of above-mentioned biological specimen is to gather biological specimen (administration group) after the medication in the claim 2, and one group is control group; Control group can be an own control before the administration, also can be the model group parallel control of not administration, can also be the normal group contrast of not administration.
- 4. require animal in 1 except that rat except that right, can also for toad, frog, fish, mouse, cavy, dog, rabbit,, monkey chicken, pig, sheep, ox; Cell can be pathologic, hereditary change type or the normal cell in various sources; Bacterium can be all kinds of hereditary change type, transgenosis type or the normal bacterias that report is arranged.
- 5. require to adopt gas chromatography-flight time mass spectrum (GC/TOF-MS) to carry out the sample analysis in 1 except that right, also comprise other any analytical approach based on mass spectroscopy technology, nuclear magnetic resonance measuring technology and other metabolism group determination techniques.
- 6. resulting data can be the absolute quantitation data in the claim 1, also can the sxemiquantitative data, and as peak area, peak height, or the data that adopt mathematical method to calculate thus.
- 7. application SIMCA P-11 software and offset minimum binary one discriminatory analysis (PLS-DA) are set up the method for mathematical model in right requirement 1, also comprise other metabolism group data processing software, as all kinds of versions such as SPSS, Matlab, SIMCA-P; Comprise other method of selecting except that partial least square method-discriminatory analysis (PLS-DA), as quadrature partial least square method (OPLS), quadrature partial least square method-discriminatory analysis (OPLS-DA), principal component analysis (PCA) (PCA), Nonlinear Mapping (Nonlinemapping, NLM), the mathematical model set up of cluster analysis methods such as (HCA).
- 8. the mathematical model in the claim 1 can be dimension space model arbitrarily, and the hyperspace here can be 1,2,3 dimensions, also can be 4,5,6 even hyperspace more.
- In the claim 1 between medication group and the control group relative distance two kinds of account forms can be arranged, get the coordinate mean value of respectively organizing sample earlier, calculate again; When the own control sample is arranged, also can calculate each sample administration front and back earlier and change distance, averaging obtains again.
- 10. claim 9 Chinese traditional medicine toxicity is represented to adopt relative distance between medicine group and the control group, also can be the function calculation value of relative distance, and as usual have any mathematical computations mode gained results such as logarithm value, natural logarithm value, square value, square root.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201010141847A CN101813680A (en) | 2010-04-08 | 2010-04-08 | Method for quantitatively evaluating medicament toxicity by using metabonomic technology |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201010141847A CN101813680A (en) | 2010-04-08 | 2010-04-08 | Method for quantitatively evaluating medicament toxicity by using metabonomic technology |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN101813680A true CN101813680A (en) | 2010-08-25 |
Family
ID=42620991
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201010141847A Pending CN101813680A (en) | 2010-04-08 | 2010-04-08 | Method for quantitatively evaluating medicament toxicity by using metabonomic technology |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN101813680A (en) |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102323285A (en) * | 2010-11-15 | 2012-01-18 | 上海聚类生物科技有限公司 | Method for analyzing NMR (Nuclear Magnetic Resonance) metabonomics detection data |
| CN102323286A (en) * | 2010-11-15 | 2012-01-18 | 上海聚类生物科技有限公司 | Method for analyzing primary biliary cirrhosis metabolite based on H1NMR technology |
| CN102339356A (en) * | 2011-07-01 | 2012-02-01 | 苏州大学 | Method for evaluating and predicating toxicity and efficacy of medicament by using metabonomic technology |
| CN103558354A (en) * | 2013-11-15 | 2014-02-05 | 南京大学 | Water toxicity analysis method based on biologic omics integrated technology |
| CN103714233A (en) * | 2013-05-10 | 2014-04-09 | 上海阿趣生物科技有限公司 | Univariable and multi-variable combined data analysis method |
| CN105651868A (en) * | 2014-11-14 | 2016-06-08 | 中国科学院大连化学物理研究所 | A method of screening a marker of renal toxicity caused by aristolochic acid by utilizing cell metabolic profiling in vitro |
| CN106706692A (en) * | 2016-12-30 | 2017-05-24 | 南京理工大学 | Pesticide toxicity evaluation method based on metabonomical technique |
| CN109900884A (en) * | 2017-12-08 | 2019-06-18 | 中国科学院大连化学物理研究所 | A kind of research method of the short chain chlorinated paraffin zebrafish embryo poisonous effect based on metabolism group |
| CN110376137A (en) * | 2018-12-18 | 2019-10-25 | 权冉(银川)科技有限公司 | A kind of method that high-purity sea-buckthorn brass VC detection is chosen |
-
2010
- 2010-04-08 CN CN201010141847A patent/CN101813680A/en active Pending
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102323285A (en) * | 2010-11-15 | 2012-01-18 | 上海聚类生物科技有限公司 | Method for analyzing NMR (Nuclear Magnetic Resonance) metabonomics detection data |
| CN102323286A (en) * | 2010-11-15 | 2012-01-18 | 上海聚类生物科技有限公司 | Method for analyzing primary biliary cirrhosis metabolite based on H1NMR technology |
| CN102339356A (en) * | 2011-07-01 | 2012-02-01 | 苏州大学 | Method for evaluating and predicating toxicity and efficacy of medicament by using metabonomic technology |
| CN102339356B (en) * | 2011-07-01 | 2013-08-28 | 苏州大学 | Method for evaluating and predicating toxicity and efficacy of medicament by using metabonomic technology |
| CN103714233A (en) * | 2013-05-10 | 2014-04-09 | 上海阿趣生物科技有限公司 | Univariable and multi-variable combined data analysis method |
| CN103558354A (en) * | 2013-11-15 | 2014-02-05 | 南京大学 | Water toxicity analysis method based on biologic omics integrated technology |
| CN103558354B (en) * | 2013-11-15 | 2015-07-15 | 南京大学 | Water toxicity analysis method based on biologic omics integrated technology |
| US10041118B2 (en) | 2013-11-15 | 2018-08-07 | Nanjing University | Method for analyzing water toxicity |
| CN105651868A (en) * | 2014-11-14 | 2016-06-08 | 中国科学院大连化学物理研究所 | A method of screening a marker of renal toxicity caused by aristolochic acid by utilizing cell metabolic profiling in vitro |
| CN106706692A (en) * | 2016-12-30 | 2017-05-24 | 南京理工大学 | Pesticide toxicity evaluation method based on metabonomical technique |
| CN109900884A (en) * | 2017-12-08 | 2019-06-18 | 中国科学院大连化学物理研究所 | A kind of research method of the short chain chlorinated paraffin zebrafish embryo poisonous effect based on metabolism group |
| CN110376137A (en) * | 2018-12-18 | 2019-10-25 | 权冉(银川)科技有限公司 | A kind of method that high-purity sea-buckthorn brass VC detection is chosen |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN101813680A (en) | Method for quantitatively evaluating medicament toxicity by using metabonomic technology | |
| Kostidis et al. | Quantitative NMR analysis of intra-and extracellular metabolism of mammalian cells: A tutorial | |
| Bingol et al. | Knowns and unknowns in metabolomics identified by multidimensional NMR and hybrid MS/NMR methods | |
| CN102901789A (en) | Determination method of serum metabolic marker for early diagnosis of diabetic nephropathy. | |
| Vuckovic | Current trends and challenges in sample preparation for global metabolomics using liquid chromatography–mass spectrometry | |
| Le Guennec et al. | Fast determination of absolute metabolite concentrations by spatially encoded 2D NMR: application to breast cancer cell extracts | |
| CN102901790A (en) | Determination method of urine metabolic marker for early diagnosis of diabetic nephropathy. | |
| Alshamleh et al. | Real‐time NMR spectroscopy for studying metabolism | |
| CN103616450A (en) | Serum specificity metabolite spectrum for patient with lung cancer, and building method thereof | |
| Crutchfield et al. | Mass spectrometry-based metabolomics of yeast | |
| You et al. | Application of stable isotope-assisted metabolomics for cell metabolism studies | |
| CN102175809A (en) | New method for performing data correction by using cell metabolite relative content as cell number index | |
| CN105301163A (en) | Targeted metabo lomics analysis method for determining metabolites of living body | |
| CN101799462A (en) | Method for quantitative evaluation of drug effect by applying metabonomic technology | |
| CN104020241A (en) | Synchronous analysis method for trace nicotine in blood-brain samples of animal and main metabolites thereof | |
| Kang et al. | UPLC/Q-TOF MS based metabolomics approach to post-mortem-interval discrimination: Mass spectrometry based metabolomics approach | |
| Onorato et al. | Applications of HILIC for targeted and non‐targeted LC/MS analyses in drug discovery | |
| Yu et al. | Metabolic profile of fish muscle tissue changes with sampling method, storage strategy and time | |
| da Silva et al. | Molecularly imprinted polymer-coated probe electrospray ionization mass spectrometry determines phorbol esters and deoxyphorbol metabolites in Jatropha curcas leaves | |
| Humston et al. | Time-dependent profiling of metabolites from Snf1 mutant and wild type yeast cells | |
| CN103197006A (en) | Method for determining serous metabolic biomarker of heroin abuse crowd | |
| Crooks et al. | Metabolic labeling of cultured mammalian cells for stable isotope-resolved metabolomics: Practical aspects of tissue culture and sample extraction | |
| CN104251889A (en) | Method for determining content of three components comprising phenylephrine hydrochloride, chlorphenamine maleate and ibuprofen in compound cold treatment tablet | |
| Zhang et al. | Metabolomic study of the fever model induced by baker's yeast and the antipyretic effects of aspirin in rats using nuclear magnetic resonance and gas chromatography–mass spectrometry | |
| Gorman et al. | Mass spectrometry imaging of metals in tissues and cells: Methods and biological applications |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C02 | Deemed withdrawal of patent application after publication (patent law 2001) | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20100825 |