CN112326849B - Biological sample analysis method for researching fat-reducing and lipid-lowering characteristics of Eurycoma longifolia - Google Patents
Biological sample analysis method for researching fat-reducing and lipid-lowering characteristics of Eurycoma longifolia Download PDFInfo
- Publication number
- CN112326849B CN112326849B CN202011218040.5A CN202011218040A CN112326849B CN 112326849 B CN112326849 B CN 112326849B CN 202011218040 A CN202011218040 A CN 202011218040A CN 112326849 B CN112326849 B CN 112326849B
- Authority
- CN
- China
- Prior art keywords
- sample
- phase
- lipid
- water
- volume fraction
- 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.)
- Active
Links
- 240000005739 Eurycoma longifolia Species 0.000 title claims abstract description 64
- 239000012472 biological sample Substances 0.000 title claims abstract description 28
- 238000012284 sample analysis method Methods 0.000 title claims abstract description 8
- 239000000523 sample Substances 0.000 claims abstract description 86
- 239000002207 metabolite Substances 0.000 claims abstract description 65
- 150000002632 lipids Chemical class 0.000 claims abstract description 40
- 238000001514 detection method Methods 0.000 claims abstract description 35
- 238000004458 analytical method Methods 0.000 claims abstract description 34
- 238000000034 method Methods 0.000 claims abstract description 33
- 230000008569 process Effects 0.000 claims abstract description 19
- 238000001294 liquid chromatography-tandem mass spectrometry Methods 0.000 claims abstract description 10
- 238000001819 mass spectrum Methods 0.000 claims abstract description 8
- OKKJLVBELUTLKV-UHFFFAOYSA-N Methanol Chemical compound OC OKKJLVBELUTLKV-UHFFFAOYSA-N 0.000 claims description 78
- WEVYAHXRMPXWCK-UHFFFAOYSA-N Acetonitrile Chemical compound CC#N WEVYAHXRMPXWCK-UHFFFAOYSA-N 0.000 claims description 57
- BZLVMXJERCGZMT-UHFFFAOYSA-N Methyl tert-butyl ether Chemical compound COC(C)(C)C BZLVMXJERCGZMT-UHFFFAOYSA-N 0.000 claims description 27
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 27
- 239000007788 liquid Substances 0.000 claims description 19
- QTBSBXVTEAMEQO-UHFFFAOYSA-N Acetic acid Chemical compound CC(O)=O QTBSBXVTEAMEQO-UHFFFAOYSA-N 0.000 claims description 18
- 239000007864 aqueous solution Substances 0.000 claims description 16
- YMWUJEATGCHHMB-UHFFFAOYSA-N Dichloromethane Chemical compound ClCCl YMWUJEATGCHHMB-UHFFFAOYSA-N 0.000 claims description 15
- USFZMSVCRYTOJT-UHFFFAOYSA-N Ammonium acetate Chemical compound N.CC(O)=O USFZMSVCRYTOJT-UHFFFAOYSA-N 0.000 claims description 13
- 239000005695 Ammonium acetate Substances 0.000 claims description 13
- 229940043376 ammonium acetate Drugs 0.000 claims description 13
- 235000019257 ammonium acetate Nutrition 0.000 claims description 13
- 230000037353 metabolic pathway Effects 0.000 claims description 12
- 238000010171 animal model Methods 0.000 claims description 9
- 239000000243 solution Substances 0.000 claims description 9
- 238000001035 drying Methods 0.000 claims description 8
- 238000010828 elution Methods 0.000 claims description 8
- 235000009200 high fat diet Nutrition 0.000 claims description 8
- 238000005507 spraying Methods 0.000 claims description 8
- PBCJIPOGFJYBJE-UHFFFAOYSA-N acetonitrile;hydrate Chemical compound O.CC#N PBCJIPOGFJYBJE-UHFFFAOYSA-N 0.000 claims description 6
- 238000002013 hydrophilic interaction chromatography Methods 0.000 claims description 6
- 210000003734 kidney Anatomy 0.000 claims description 5
- 210000004185 liver Anatomy 0.000 claims description 5
- 239000011259 mixed solution Substances 0.000 claims description 5
- 239000000725 suspension Substances 0.000 claims description 5
- 238000002156 mixing Methods 0.000 claims description 4
- 239000000203 mixture Substances 0.000 claims description 4
- 238000000513 principal component analysis Methods 0.000 claims description 4
- 229910000831 Steel Inorganic materials 0.000 claims description 3
- VZTDIZULWFCMLS-UHFFFAOYSA-N ammonium formate Chemical compound [NH4+].[O-]C=O VZTDIZULWFCMLS-UHFFFAOYSA-N 0.000 claims description 3
- 238000002347 injection Methods 0.000 claims description 3
- 239000007924 injection Substances 0.000 claims description 3
- 239000010959 steel Substances 0.000 claims description 3
- 210000002216 heart Anatomy 0.000 claims description 2
- 210000004072 lung Anatomy 0.000 claims description 2
- 238000004949 mass spectrometry Methods 0.000 claims description 2
- 210000000496 pancreas Anatomy 0.000 claims description 2
- 230000001568 sexual effect Effects 0.000 claims description 2
- 239000002002 slurry Substances 0.000 claims description 2
- 210000001519 tissue Anatomy 0.000 abstract description 15
- 210000002381 plasma Anatomy 0.000 abstract description 13
- 230000004580 weight loss Effects 0.000 abstract description 6
- 230000002503 metabolic effect Effects 0.000 abstract description 4
- 230000001737 promoting effect Effects 0.000 abstract description 3
- 238000011160 research Methods 0.000 description 17
- 241000699666 Mus <mouse, genus> Species 0.000 description 7
- 241000699670 Mus sp. Species 0.000 description 7
- 238000005173 quadrupole mass spectroscopy Methods 0.000 description 6
- 238000007619 statistical method Methods 0.000 description 5
- 238000011161 development Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 4
- 238000002705 metabolomic analysis Methods 0.000 description 4
- 230000001431 metabolomic effect Effects 0.000 description 4
- 239000007921 spray Substances 0.000 description 4
- 239000006228 supernatant Substances 0.000 description 4
- 244000042238 Eurycoma Species 0.000 description 3
- 241001465754 Metazoa Species 0.000 description 3
- 238000005119 centrifugation Methods 0.000 description 3
- 239000003814 drug Substances 0.000 description 3
- 229940079593 drug Drugs 0.000 description 3
- 238000000605 extraction Methods 0.000 description 3
- 230000006872 improvement Effects 0.000 description 3
- 150000002500 ions Chemical class 0.000 description 3
- 238000003068 pathway analysis Methods 0.000 description 3
- 239000000843 powder Substances 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 241000894007 species Species 0.000 description 3
- 238000003756 stirring Methods 0.000 description 3
- 238000012360 testing method Methods 0.000 description 3
- 238000003260 vortexing Methods 0.000 description 3
- 241000196324 Embryophyta Species 0.000 description 2
- 208000008589 Obesity Diseases 0.000 description 2
- 239000011324 bead Substances 0.000 description 2
- 230000004071 biological effect Effects 0.000 description 2
- 238000004587 chromatography analysis Methods 0.000 description 2
- 238000012217 deletion Methods 0.000 description 2
- 230000037430 deletion Effects 0.000 description 2
- LOKCTEFSRHRXRJ-UHFFFAOYSA-I dipotassium trisodium dihydrogen phosphate hydrogen phosphate dichloride Chemical compound P(=O)(O)(O)[O-].[K+].P(=O)(O)([O-])[O-].[Na+].[Na+].[Cl-].[K+].[Cl-].[Na+] LOKCTEFSRHRXRJ-UHFFFAOYSA-I 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000002474 experimental method Methods 0.000 description 2
- 238000002695 general anesthesia Methods 0.000 description 2
- 125000005456 glyceride group Chemical group 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000010172 mouse model Methods 0.000 description 2
- 235000021590 normal diet Nutrition 0.000 description 2
- 235000020824 obesity Nutrition 0.000 description 2
- 238000010239 partial least squares discriminant analysis Methods 0.000 description 2
- 239000002953 phosphate buffered saline Substances 0.000 description 2
- 230000035945 sensitivity Effects 0.000 description 2
- 238000011725 BALB/c mouse Methods 0.000 description 1
- 241000124008 Mammalia Species 0.000 description 1
- 206010028980 Neoplasm Diseases 0.000 description 1
- 206010037660 Pyrexia Diseases 0.000 description 1
- 210000004369 blood Anatomy 0.000 description 1
- 239000008280 blood Substances 0.000 description 1
- 230000036760 body temperature Effects 0.000 description 1
- 230000037396 body weight Effects 0.000 description 1
- 201000011510 cancer Diseases 0.000 description 1
- 210000004027 cell Anatomy 0.000 description 1
- 239000003153 chemical reaction reagent Substances 0.000 description 1
- 238000003759 clinical diagnosis Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000000354 decomposition reaction Methods 0.000 description 1
- 230000032798 delamination Effects 0.000 description 1
- 201000010099 disease Diseases 0.000 description 1
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 1
- 238000009509 drug development Methods 0.000 description 1
- 238000000132 electrospray ionisation Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 206010016256 fatigue Diseases 0.000 description 1
- 230000037406 food intake Effects 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 201000001881 impotence Diseases 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 210000004731 jugular vein Anatomy 0.000 description 1
- 230000014759 maintenance of location Effects 0.000 description 1
- 201000004792 malaria Diseases 0.000 description 1
- 230000004060 metabolic process Effects 0.000 description 1
- 244000005700 microbiome Species 0.000 description 1
- 239000002547 new drug Substances 0.000 description 1
- 231100000252 nontoxic Toxicity 0.000 description 1
- 230000003000 nontoxic effect Effects 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 238000011580 nude mouse model Methods 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000000144 pharmacologic effect Effects 0.000 description 1
- 239000002244 precipitate Substances 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 238000002203 pretreatment Methods 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 238000011002 quantification Methods 0.000 description 1
- 239000002994 raw material Substances 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 239000000758 substrate Substances 0.000 description 1
- 231100000041 toxicology testing Toxicity 0.000 description 1
- 238000004704 ultra performance liquid chromatography Methods 0.000 description 1
- 238000009423 ventilation Methods 0.000 description 1
Images
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
- G01N30/88—Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Landscapes
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Other Investigation Or Analysis Of Materials By Electrical Means (AREA)
Abstract
The invention belongs to the technical field of metabonomics analysis, and particularly relates to a biological sample analysis method for researching the weight-losing and lipid-lowering characteristics of Eurycoma longifolia. Aiming at the problem that the study on the weight-losing and lipid-lowering characteristics of Eurycoma longifolia by utilizing metabonomics analysis is difficult to carry out due to the lack of a suitable metabolite detection and analysis method in the prior art, the technical scheme provided by the invention is as follows: and (3) detecting the water-soluble metabolite sample and/or the lipid sample by liquid chromatography-tandem mass spectrometry after the water-soluble metabolite sample and the lipid sample are extracted and separated. The invention optimizes the chromatographic condition and the mass spectrum condition of the detection. The invention well separates the water-soluble metabolites and lipid metabolites in the blood plasma and the tissue sample, thereby realizing accurate detection. Based on the accurate detection result, a metabolic path in the process of promoting weight loss and lipid lowering of the Eurycoma longifolia is obtained, and the purpose of analyzing and researching the weight loss and lipid lowering characteristics of the Eurycoma longifolia by utilizing metabonomics is achieved.
Description
Technical Field
The invention belongs to the technical field of metabonomics analysis, and particularly relates to a biological sample analysis method for researching the weight-losing and lipid-lowering characteristics of Eurycoma longifolia.
Background
As a classical detection and analysis technique with a variety of unique features and significant advantages, the metabonomics technique and its related principles and applications have attracted great attention, and the research on the further innovation and development of the technique has been continued for many years with great success. Since the characteristics of interest (such as biocompatibility with phenotype, high-throughput analysis process, low detection cost and rich analysis results, metabolomics has been widely used in various life systems such as microorganisms, cells, plants, mammals and environment, etc., and many advanced and meaningful results have been obtained in the research fields of toxicological evaluation, new drug development, clinical diagnosis, disease treatment, food safety and environmental chemistry, etc., the research on metabolomics is mainly focused on the technical improvement based on metabolomics and the development of a novel research field, which undoubtedly requires the rapid development of corresponding detection means and technical details in the direction of covering more metabolite species and higher sensitivity in the near future.
To achieve this goal, a novel metabonomic research platform combining high resolution analysis techniques with chemometrics statistical software successfully achieves effective detection of metabolites and integrated processing of subsequent data while also revealing endogenous and heterologous metabolic processes. The existing liquid chromatography-tandem mass spectrometry (LC-MS/MS) technology plays an important role, becomes one of several main detection means of metabonomics, and has incomparable advantages compared with other means due to high sensitivity, effective detection process, simple sample processing method and good universality. At present, an omics analysis platform based on LC-MS/MS and data statistical software is widely used for non-targeted or targeted metabonomics research, the platform realizes identification of thousands of metabolites by an efficient and time-saving process, and valuable theoretical and practical references are provided for future practical application and technical improvement. However, the reports of the metabonomics analysis platform in further cooperation with other advanced research fields (such as medicinal plants) are few, so that the deeper exploration of metabonomics becomes a great challenge facing the current needs, and a wide space is provided for the interdisciplinary development based on metabonomics.
As an outstanding solution to this challenge, researchers have been working on developing an asian herb called eurycoma ali over the past few decades, and the results of the research based on its biological properties and pharmacological activity have had a tremendous impact in the chemical and medical fields. Generally, the roots, stems and bark of Eurycoma longifolia are used as folk remedies for cancer, malaria, fever, impotence and fatigue. Recently, interest in this drug in the research field of obesity treatment and weight loss has become a current leading research based on Eurycoma longifolia. Therefore, the new concept of systematically evaluating the lipid-lowering and weight-losing properties of Eurycoma longifolia by analyzing and detecting the types and amounts of various metabolites through a metabonomics research platform has gradually shown its unique charm and bright future.
However, in trimomics, the difficulty of metabolomics analysis is relatively high. One reason for this is the difficulty in metabolite detection and analysis. This is due to the large number and large differences in metabolites of different biological species under different experimental conditions. Therefore, the detection conditions of the metabolites in the biological samples are different for different animal experimental models. Although the property of Eurycoma longifolia to reduce weight and fat has been discovered, the prior researches do not provide relevant molecular biological information for treating obesity based on Eurycoma longifolia, and the internal connection between relevant characteristic metabolites and the metabolic principles under the intervention of Eurycoma longifolia is not clear. Therefore, it cannot be expected that what metabolites need to be analyzed in the process of researching the weight-losing and lipid-lowering properties of eurycoma longifolia by utilizing metabonomics analysis, and what detection method and detection conditions are suitable for relevant biological samples is not clear. Therefore, the application of the traditional metabonomics is expanded to the research of the weight-losing and lipid-lowering characteristics of Eurycoma longifolia through further detection method improvement and detection condition optimization, the application becomes an important task to be solved by metabonomics researchers, and the application has great potential value and profound significance.
Disclosure of Invention
Aiming at the problem that the research on the weight-reducing and lipid-lowering characteristics of Eurycoma longifolia is difficult to carry out by utilizing metabonomics analysis because a proper metabolite detection and analysis method is lacked in the prior art, the invention provides a biological sample analysis method for the research on the weight-reducing and lipid-lowering characteristics of Eurycoma longifolia, and aims to provide a biological sample analysis method for the research on the weight-reducing and lipid-lowering characteristics of Eurycoma longifolia, which comprises the following steps: the optimized detection method and detection conditions are provided, the metabolite detection in the biological sample of the animal model with the Eurycoma longifolia weight-reducing effect is realized, and the application of the metabonomics analysis method in the research of the Eurycoma longifolia weight-reducing and lipid-lowering characteristics is further realized.
A biological sample analysis method for researching the weight-losing and lipid-lowering characteristics of Eurycoma longifolia comprises the following steps:
(1) taking a biological sample for researching the weight-losing and lipid-lowering characteristics of Eurycoma longifolia, and extracting and separating the biological sample into a water-soluble metabolite sample and a lipid sample;
(2) detecting the water-soluble metabolite sample and/or the lipid sample by liquid chromatography-tandem mass spectrometry;
when the water-soluble metabolite sample is detected, the water-soluble metabolite sample is dissolved in acetonitrile water solution with volume fraction of 60-70%, and the chromatographic conditions are as follows: the mobile phase takes acetonitrile aqueous solution with volume fraction of 5-10% as phase A and acetonitrile aqueous solution with volume fraction of 90-95% as phase B; the chromatographic column adopts BEH HILIC chromatographic column;
and/or, the lipid sample is dissolved in a volume ratio of 50: 50 in dichloromethane/methanol mixed solution, and the chromatographic conditions are as follows: the mobile phase takes acetonitrile water solution with volume fraction of 90-95% as phase A and acetonitrile water solution with volume fraction of 50-55% as phase B; the chromatographic column adopts BEH HILIC chromatographic column.
Preferably, the elution gradient in the detection of the water-soluble metabolite sample is:
0-0.10min, 10% of phase A and 90% of phase B in volume fraction;
0.10-1.50min, 10% phase A +90% phase B by volume fraction;
1.50-5.00min, 55% of phase A and 45% of phase B by volume fraction;
5.00-10.0min, 55% of phase A and 45% of phase B by volume fraction;
10.0-12.0min, 10% of phase A and 90% of phase B by volume fraction;
12.0-20.0min, 10% phase A +90% phase B by volume fraction;
and/or the elution gradient in the detection of the lipid sample is as follows:
0-10.0min, 80% of phase A and 20% of phase B in volume fraction;
10.0-11.0min, 2% of phase A and 98% of phase B by volume fraction;
11.0-13.0min, 2% of phase A and 98% of phase B by volume fraction;
13.0-13.1min, 99.1% phase A +0.9% phase B by volume fraction;
13.1-17.0min, 0% phase A +0% phase B by volume fraction.
Preferably, the biological sample is collected from an animal model for reducing fat and losing weight of Eurycoma longifolia, and the modeling method of the animal model for reducing fat and losing weight of Eurycoma longifolia comprises the following steps: intragastric administering an aqueous solution of an extract of Eurycoma longifolia to a high-fat diet of a laboratory animal, preferably a white mouse, a black mouse or a nude mouse.
Preferably, the biological sample is a plasma and/or tissue sample from an animal model for Eurycoma longifolia lipid-lowering weight loss, preferably the tissue sample is a liver, kidney, lung, heart or pancreas sample.
Preferably, in step (1), the process of extracting and separating the plasma sample comprises the following steps:
(1.1) mixing the plasma sample with methanol, methyl tert-butyl ether and water uniformly;
(1.2) standing for layering, collecting lower layer clear liquid, drying to obtain a water-soluble metabolite sample, collecting upper layer clear liquid, and drying to obtain a lipid sample;
preferably, the volume ratio of the plasma sample to the methanol to the methyl tert-butyl ether to the water is 4:30:100: 35; and/or, the specific process of the step (1.1) is that after the plasma sample is uniformly mixed with methanol and methyl tert-butyl ether, the mixture is kept stand for 1 to 2 hours in a dark place and then is uniformly mixed with water; and/or the standing and layering time in the step (1.2) is 10-20 min.
Preferably, in step (1), the process of extracting and separating the tissue sample comprises the following steps:
(1.1) crushing the tissue sample and adding methanol to homogenate to obtain a suspension;
(1.2) uniformly mixing the homogenized suspension with methanol, methyl tert-butyl ether and water;
(1.3) standing for layering, collecting lower layer clear liquid, drying to obtain a water-soluble metabolite sample, collecting upper layer clear liquid, and drying to obtain a lipid sample;
preferably, the specific process of step (1.1) is to mix the tissue sample, steel beads and 80-90% volume fraction of methanol into the sexual tissue homogenate; and/or the ratio of the amount of the tissue sample and 80-90% by volume of methanol is 10 mg: 200 mul; and/or the ratio of the amount of the tissue sample to the amount of methanol, methyl tert-butyl ether and water used in step (1.2) is 10 mg: 160 μ l: 1000. mu.l: 300 mu l; and/or, the specific process of the step (1.2) is that the slurry is uniformly mixed with methanol and methyl tert-butyl ether, then is kept stand for 1-2h in the dark place, and then is uniformly mixed with water; and/or the standing and layering time in the step (1.3) is 10-20 min.
Preferably, the water-soluble metabolite sample is dissolved in 60-70% acetonitrile aqueous solution containing 5-10mM ammonium formate in volume fraction, and the chromatographic conditions are as follows: the mobile phase takes acetonitrile aqueous solution with volume fraction of 10-20% containing 10-20mM ammonium acetate and volume fraction of 0.2-0.5% acetic acid as phase A, and acetonitrile aqueous solution with volume fraction of 80-90% containing 10-20mM ammonium acetate and volume fraction of 0.2-0.5% acetic acid as phase B;
the lipid sample is dissolved in a volume ratio of 50: 50 in dichloromethane/methanol mixed solution, and the chromatographic conditions are as follows: the mobile phase takes acetonitrile aqueous solution with volume fraction of 90-95% containing 10-20mM ammonium acetate as phase A and acetonitrile aqueous solution with volume fraction of 50-60% containing 10-20mM ammonium acetate as phase B.
Preferably, the chromatographic conditions of the water-soluble metabolite sample are as follows: the flow rate of the mobile phase is 200-300 mu l/min, the sample injection amount is 5-15 mu l, and the temperature of the chromatographic column is set to be 30-40 ℃;
the chromatographic conditions for the lipid sample were: the flow rate of the mobile phase is 400-.
Preferably, the mass spectrum conditions of the water-soluble metabolite sample are as follows: the temperature of the capillary tube is kept at 600-650 ℃, the pressure of the sheath gas is 50-60psi, the pressure of the auxiliary gas is 40-50psi, the primary scanning range is 5-1250m/z, the positive mode spraying voltage is 4-5kV, and the negative mode spraying voltage is-4 to-5 kV;
the mass spectrometry conditions of the lipid sample are: the temperature of the capillary tube is kept at 400-500 ℃, the pressure of the sheath gas is 50-60psi, the pressure of the auxiliary gas is 60-65psi, the primary scanning range is 5-1250m/z, the positive mode spraying voltage is 5-6kV, and the negative mode spraying voltage is-4 to-5 kV.
Preferably, in step (2), the result obtained by the liquid chromatography-tandem mass spectrometry detection is used for the analysis of the metabolic pathway.
Preferably, the analysis of the metabolic pathway comprises the steps of:
(3.1) analyzing and identifying metabolites of a result obtained by the liquid chromatography-tandem mass spectrometry detection based on an R language algorithm to obtain a statistical result;
(3.2) after normalizing the statistical result, performing principal component analysis, partial least square discriminant analysis or orthogonal partial least square discriminant analysis to group the metabolites;
(3.3) MetaboAnalyst analysis was performed by R language to identify representative metabolic pathways.
In the detection method of the biological sample, the detection conditions of the water-soluble metabolite sample and the lipid sample are optimized respectively, and the separation and detection of various characteristic metabolites in the biological sample can be met. The accuracy of detecting and identifying the metabolites is improved, and the accuracy of subsequent metabolic pathway analysis is improved.
Obviously, many modifications, substitutions, and variations are possible in light of the above teachings of the invention, without departing from the basic technical spirit of the invention, as defined by the following claims.
The present invention will be described in further detail with reference to the following examples. This should not be understood as limiting the scope of the above-described subject matter of the present invention to the following examples. All the technologies realized based on the above contents of the present invention belong to the scope of the present invention.
Drawings
FIG. 1 is a schematic flow diagram of a metabonomics analysis method of the present invention based on the lipid-lowering, weight-reducing properties of Eurycoma longifolia;
FIG. 2 is a schematic logic diagram of a metabonomic analysis method of the present invention based on the lipid-lowering, weight-reducing properties of Eurycoma longifolia;
FIG. 3 is a total ion flow diagram of water-soluble metabolites obtained in the example of the present invention;
FIG. 4 is a total ion flow graph of lipid metabolites obtained in the examples of the present invention.
Wherein, 1-original drug of Eurycoma longifolia, 2-water-soluble extract of Eurycoma longifolia, 3-injector, 4-white mouse, 5-plasma, 6-liver, 7-kidney, 8-liquid chromatogram-triple quadrupole mass spectrum, and 9-statistical result.
Detailed Description
The technical solution of the present invention is further illustrated by the following specific examples. Unless otherwise specified, the experimental methods used are conventional ones, and the instruments, reagents and raw materials used are commercially available.
Examples
This embodiment is a study on a metabonomics analysis method based on the lipid-lowering and weight-reducing characteristics of Eurycoma longifolia, fig. 1 is a schematic flow chart of the metabonomics analysis method based on the lipid-lowering and weight-reducing characteristics of Eurycoma longifolia in this embodiment, and fig. 2 is a schematic logic diagram of the metabonomics analysis method based on the lipid-lowering and weight-reducing characteristics of Eurycoma longifolia in this embodiment. The metabonomics analysis method based on the Eurycoma longifolia fat-reducing and weight-losing characteristics comprises six steps of preparing the Eurycoma longifolia water-soluble extract, constructing a mouse model for Eurycoma longifolia fat-reducing and weight-losing, collecting plasma and tissue samples, extracting water-soluble metabolites and lipid, detecting liquid chromatography-triple quadrupole mass spectrometry and analyzing bioinformatics statistics.
(1) Preparation of water-soluble extract of Eurycoma longifolia Jack
27g of eurycoma longifolia technical 1 was first ground to a fine powder and then dissolved in 200ml of pure water in the dark with vigorous stirring at 80 ℃ for 1h, filtered and the upper liquid was collected. Next, 200ml of pure water was added to the previous substrate to conduct extraction again. After vigorous stirring for 1h at 80 ℃ in the dark, all liquids were mixed and freeze-dried. The resulting powder (about 0.9g) was stored in a refrigerator at 4 ℃.
Before the Eurycoma longifolia water-soluble extract is used, the powder is re-dissolved in pure water under vigorous stirring to obtain the Eurycoma longifolia water-soluble extract, and the Eurycoma longifolia water-soluble extract is heated to be consistent with the body temperature of a mouse.
(2) Construction of mouse model for reducing fat and losing weight of Eurycoma longifolia
15 mature male BALB/c mice (5 weeks) were used with body weights between 22-28 g. These mice were kept in standard cages at room temperature (22-24 ℃) with good ventilation, 12h light-dark cycle and a humidity of about 50. + -. 5%. 5 animals were kept in each cage. Food and water were kept adequate for the mice. Mice were acclimated to dwelling conditions for 7 days prior to beginning intervention. These mice were then randomly divided into 3 groups of 5 mice each. After 12 days of feeding with either high fat diet (high fat diet group and eurycoma group) or normal diet (control group), the following 20 days of dry pre-treatment method was as follows: the control group was supplied with normal diet and pure water only; the high fat diet group is only supplied with high fat diet and pure water; the Eurycoma longifolia intragastric group was supplied with high fat diet and pure water and was intragastric administered daily using a syringe containing 200. mu.l of 120mg/ml Eurycoma longifolia water soluble extract. The concentration of the above-mentioned water-soluble extract of eurycoma longifolia is derived from the reported dose that maintains the optimum biological activity, while being non-toxic to mice and capable of forming an effective stimulus.
(3) Plasma and tissue sample collection and water-soluble metabolite and lipid extraction
The water-soluble metabolite and lipid extraction steps of the plasma are as follows: the white mice in all experimental groups were bled from the jugular vein under the general anesthesia, and the resulting blood was centrifuged (2000rpm, 10min, 8 ℃) to collect plasma. Then 40. mu.l of plasma from each sample (six replicates per set) was mixed with 300. mu.l of methanol and vortexed at 1500rpm for 10 s. After this time, 1ml of methyl tert-butyl ether was added with vortexing at 1500rpm and allowed to interact in the dark for 1 h. Then, 350. mu.l of pure water was added and vortexed at 1500rpm for 20s, followed by delamination at room temperature for 10 min. After centrifugation (14000rpm, 10min, 4 ℃) treatment, 800. mu.l of the supernatant (lipid) and 250. mu.l of the subnatant (water-soluble metabolite) were dried in vacuo for 12h, respectively. Thus obtaining a lipid sample and a water-soluble metabolite sample.
The water-soluble metabolites and lipids of tissues (including liver 6 and kidney 7) were extracted as follows: the white mouse 4 in all the experimental groups was subjected to liver 6 and kidney 7 removal under the general anesthesia condition and washed with Phosphate Buffered Saline (PBS). Next, 10mg of liver 6 or kidney 7 (six replicates per experiment) were weighed out for each sample and mixed with 6 steel beads and 200. mu.l of pre-cooled 80% methanol for 3 tissue homogenates (30 s each). After vortexing at 1500rpm for 10s, 160. mu.l of methanol was added to mix with the above suspension and vortexed at 1500rpm for 10 s. Then, 1ml of methyl t-butyl ether was added under vortex at 1500 rpm. After 1h of interaction in the dark, 300. mu.l of pure water was added and vortexed at 1500rpm for 20s, followed by 10min of demixing at room temperature. After centrifugation (14000rpm, 10min, 4 ℃) treatment, 800. mu.l of the supernatant (lipids) and 250. mu.l of the subnatant (water-soluble metabolite) were dried in vacuo for 12h, respectively. Thus obtaining a lipid sample and a water-soluble metabolite sample.
(4) Liquid chromatography-triple quadrupole mass spectrometry detection
The water-soluble metabolite samples were first redissolved in 750. mu.l of HILIC solution (volume fraction 60% acetonitrile and 5mM ammonium formate in water) and centrifuged to remove the precipitate, 100. mu.l of the supernatant was bottled and assayed by liquid chromatography-triple quadrupole mass spectrometry. The liquid chromatogram setting conditions are as follows: the flow rate of the mobile phase was 300. mu.l/min, and the mobile phase composition was (A) 10% acetonitrile in water (containing 10mM ammonium acetate and 0.2% acetic acid) and (B) 90% acetonitrile in water (containing 10mM ammonium acetate and 0.2% acetic acid), with the relevant elution gradients shown in Table 1. The column (2.1 mm. times.100 mm, 1.7 μm) was set at 40 ℃ and the sample size was 5 μ l (positive mode) or 15 μ l (negative mode). The mass spectrum consists of a heating electrospray ionization source (H-ESI) and an Orbitrap mass analyzer, and the setting conditions of the mass spectrum are as follows: for the positive mode, the capillary temperature is kept at 650 ℃, the sheath gas pressure is 50psi, the auxiliary gas pressure is 40psi, the spray voltage is 4kV, and the primary scanning range is 5-1250 m/z; for the negative mode, the capillary temperature was maintained at 650 deg.C, the sheath gas pressure was 50psi, the assist gas pressure was 40psi, the spray voltage was-4 kV, and the primary scan range was 5-1250 m/z.
TABLE 1 elution gradient in chromatographic analysis of water-soluble metabolite samples
The lipid sample was first redissolved in a mixed solution of 100. mu.l volume fraction 50% dichloromethane and volume fraction 50% methanol containing 10mM ammonium acetate, followed by vortexing (1500rpm, 10 ℃, 10s) and centrifugation (14000rpm, 10min, 4 ℃) treatment, extracting 65. mu.l of supernatant and bottling into a liquid chromatography-triple quadrupole mass spectrometry for detection. The liquid chromatogram setting conditions are as follows: the mobile phase flow rate was 500. mu.l/min and the mobile phase composition was (A) 90-95%, preferably 95% acetonitrile in water (containing 10mM ammonium acetate) and (B) 50% acetonitrile in water (including 10mM ammonium acetate), the relevant elution gradients are shown in Table 2, the temperature of the acquisition UPLC BEH HILIC column (2.1 mM. times.100 mM, 1.7 μm) was set at 35 ℃ and the sample size was 2. mu.l. The mass spectrum setting conditions are as follows: for the positive mode, the capillary temperature is maintained at 500 ℃, the sheath gas pressure is 50psi, the auxiliary gas pressure is 60psi, and the spray voltage is 5.3 kV; for the negative mode, the capillary temperature was maintained at 500 deg.C, the sheath gas pressure was 50psi, the auxiliary gas pressure was 60psi, the spray voltage was-4.5 kV, and the primary scan range was 5-1250 m/z.
TABLE 2 elution gradient in chromatographic analysis of lipid samples
Under the test conditions of the present example, the total ion flow graphs of the control group, the high fat diet group and the eurycoma group all detected a large number of chromatographic peaks and had good peak shapes. Among them, the peak intensity and area of the three experimental groups are obviously changed in the range of water-soluble metabolites (figure 3) or lipid metabolites (figure 4), and the difference among the groups is obvious. And thus can be fully used for subsequent bioinformatic statistical analysis. Meanwhile, the number and area differences of the chromatographic peaks are significant and independent of each other under positive and negative mode conditions. The result not only provides a strong proof for the effectiveness of the optimized test conditions, but also proves that the influence of Eurycoma longifolia on the living body has obvious expression in the metabonomics level.
(5) Bioinformatic statistical analysis
In the bioinformatics statistical analysis step, the statistical analysis process is implemented by data integration processing through software. The raw data of the liquid chromatography-triple quadrupole mass spectrometry of the obtained water-soluble metabolite samples and lipid samples were imported into multisquant (v2.0.3) software for pretreatment, and sample information, peak retention time, and intensity were obtained. Thereafter, metabolite analysis and identification are carried out based on the R language algorithm to obtain statistical results, and the processes comprise multivariate statistical analysis, differential metabolite statistics and quantification, differential metabolic pathway analysis and the like. Deletion values > 50% and coefficients of variation > 20% of these metabolites will be removed, where the deletion values are attributed to further data processing by KNN algorithm. After median normalization of the statistics, Principal Component Analysis (PCA), partial least squares discriminant analysis (PLS-DA) and/or orthogonal partial least squares discriminant analysis (OPLS-DA) are performed to distinguish between different groups of samples. And finally, realizing metabolic pathway analysis through R language MetabioAnalyst to identify a representative metabolic pathway in the process of promoting weight loss and lipid lowering by Eurycoma longifolia. The study of the embodiment shows that the water-soluble extract of the eurycoma longifolia has obvious influence on both the metabolites and the metabolic pathways of organisms, and meanwhile, the ingestion of the eurycoma longifolia can effectively promote the decomposition of glyceride and inhibit the generation of the glyceride, so that the effect of reducing fat and losing weight is achieved.
The analysis method of the embodiment inspects the interaction between the eurycoma longifolia water-soluble extract and the mouse based on a metabonomics test and analysis platform, and well separates the water-soluble metabolites and the lipid metabolites in the blood plasma and the tissue sample by optimizing the sample pretreatment condition, the chromatographic condition and the mass spectrum condition during the detection of the liquid chromatography-triple quadrupole mass spectrometry, thereby realizing accurate detection. And based on the accurate detection result, obtaining a metabolic pathway of the Eurycoma longifolia in the process of promoting weight loss and lipid lowering. Meanwhile, the content of the metabolic species and the metabolic path of the blood plasma and the tissue under different experimental conditions are compared, and the influence principle of the Eurycoma longifolia on the mouse metabonomics is disclosed, so that the lipid-lowering and weight-losing characteristics of the Eurycoma longifolia are evaluated, and a theoretical basis is provided for the modification and clinical application of subsequent medicines.
Claims (7)
1. A biological sample analysis method for researching the weight-losing and lipid-lowering characteristics of Eurycoma longifolia, which is characterized by comprising the following steps:
(1) taking a biological sample for researching the weight-losing and lipid-lowering characteristics of Eurycoma longifolia, and extracting and separating the biological sample into a water-soluble metabolite sample and a lipid sample;
(2) detecting the water-soluble metabolite sample and/or the lipid sample by liquid chromatography-tandem mass spectrometry;
when the water-soluble metabolite sample is detected, the water-soluble metabolite sample is dissolved in acetonitrile water solution with volume fraction of 60-70%, and the chromatographic conditions are as follows: the mobile phase takes acetonitrile aqueous solution with volume fraction of 5-10% as phase A and acetonitrile aqueous solution with volume fraction of 90-95% as phase B; the chromatographic column adopts a BEH HILIC chromatographic column;
and/or, the lipid sample is dissolved in a volume ratio of 50: 50 in dichloromethane/methanol mixed solution, and the chromatographic conditions are as follows: the mobile phase takes acetonitrile water solution with volume fraction of 90-95% as phase A and acetonitrile water solution with volume fraction of 50-55% as phase B; the chromatographic column adopts a BEH HILIC chromatographic column;
the elution gradient in the detection of the water-soluble metabolite sample is as follows:
0-0.10min, 10% of phase A and 90% of phase B by volume fraction;
0.10-1.50min, 10% of phase A and 90% of phase B by volume fraction;
1.50-5.00min, 55% of phase A and 45% of phase B by volume fraction;
5.00-10.0min, 55% of phase A and 45% of phase B by volume fraction;
10.0-12.0min, 10% phase A +90% phase B by volume fraction;
12.0-20.0min, 10% phase A +90% phase B by volume fraction;
and/or the elution gradient in the detection of the lipid sample is as follows:
0-10.0min, 80% of phase A and 20% of phase B by volume fraction;
10.0-11.0min, 2% of phase A and 98% of phase B by volume fraction;
11.0-13.0min, 2% of phase A and 98% of phase B by volume fraction;
13.0-13.1min, 99.1% phase A +0.9% phase B by volume fraction;
13.1-17.0min, 0% phase A +0% phase B by volume fraction;
in the step (1), the process of extracting and separating the plasma sample comprises the following steps:
(1.1) mixing the plasma sample with methanol, methyl tert-butyl ether and water uniformly;
(1.2) standing for layering, collecting a lower layer clear liquid, drying to obtain a water-soluble metabolite sample, collecting an upper layer clear liquid, and drying to obtain a lipid sample;
the volume ratio of the plasma sample to the methanol to the methyl tert-butyl ether to the water is 4:30:100: 35; and/or, the specific process of the step (1.1) is that after the plasma sample is uniformly mixed with methanol and methyl tert-butyl ether, the mixture is kept stand for 1 to 2 hours in a dark place and then is uniformly mixed with water; and/or, the standing and layering time in the step (1.2) is 10-20 min;
in the step (1), the process of extracting and separating the tissue sample comprises the following steps:
(1.1) crushing the tissue sample and adding methanol to homogenate to obtain a suspension;
(1.2) uniformly mixing the homogenized suspension with methanol, methyl tert-butyl ether and water;
(1.3) standing for layering, collecting the lower layer clear liquid, drying to obtain a water-soluble metabolite sample, collecting the upper layer clear liquid, and drying to obtain a lipid sample;
the concrete process of the step (1.1) is that a tissue sample, steel balls and methanol with 80-90% of volume fraction are mixed into a sexual tissue homogenate; and/or the ratio of the amount of the tissue sample and 80-90% by volume of methanol is 10 mg: 200 mul; and/or the ratio of the amount of the tissue sample to the amount of methanol, methyl tert-butyl ether and water used in step (1.2) is 10 mg: 160 μ l: 1000 μ l: 300 mu l; and/or, the specific process of the step (1.2) is that the slurry is uniformly mixed with methanol and methyl tert-butyl ether, then is kept stand for 1-2h in the dark place, and then is uniformly mixed with water; and/or, the standing and layering time in the step (1.3) is 10-20 min;
the biological sample is collected from an animal model for reducing fat and losing weight of Eurycoma longifolia, and the modeling method of the animal model for reducing fat and losing weight of Eurycoma longifolia comprises the following steps: the experimental animals on high-fat diet were intragastrically gavaged with an aqueous solution of eurycoma longifolia extract.
2. The method for analyzing a biological sample for researching fat-reducing and lipid-lowering properties of Eurycoma longifolia according to claim 1, wherein the experimental animal is a white mouse, a black mouse or a naked mouse.
3. The method for analyzing a biological sample for researching fat-reducing and lipid-lowering properties of Eurycoma longifolia according to claim 1, wherein the biological sample comprises: the tissue sample is a liver, kidney, lung, heart or pancreas sample.
4. The method for analyzing a biological sample for researching fat-reducing and lipid-lowering properties of Eurycoma longifolia as claimed in claim 1, wherein the method comprises the following steps:
when the water-soluble metabolite sample is detected, the water-soluble metabolite sample is dissolved in acetonitrile aqueous solution with volume fraction of 60-70% containing 5-10mM ammonium formate, and the chromatographic conditions are as follows: the mobile phase takes acetonitrile aqueous solution with 10-20% by volume fraction containing 10-20mM ammonium acetate and 0.2-0.5% by volume fraction of acetic acid as phase A, and acetonitrile aqueous solution with 80-90% by volume fraction containing 10-20mM ammonium acetate and 0.2-0.5% by volume fraction of acetic acid as phase B;
the lipid sample is dissolved in a volume ratio of 50: 50 in dichloromethane/methanol mixed solution, and the chromatographic conditions are as follows: the mobile phase takes acetonitrile aqueous solution with volume fraction of 90-95% containing 10-20mM ammonium acetate as phase A and acetonitrile aqueous solution with volume fraction of 50-60% containing 10-20mM ammonium acetate as phase B.
5. A method for analyzing a biological sample for researching fat-reducing and lipid-lowering properties of Eurycoma longifolia according to claim 1 or 4, wherein the method comprises the following steps:
the chromatographic conditions of the water-soluble metabolite sample are as follows: the flow rate of the mobile phase is 200-300 mu l/min, the sample injection amount is 5-15 mu l, and the temperature of the chromatographic column is set to be 30-40 ℃;
the chromatographic conditions for the lipid sample were: the flow rate of the mobile phase is 400-fold and 500 mu l/min, the sample injection amount is 2-3 mu l, and the temperature of the chromatographic column is set to be 35-40 ℃.
6. The method for analyzing a biological sample for researching fat-reducing and lipid-lowering properties of Eurycoma longifolia according to claim 1, wherein the biological sample comprises:
the mass spectrum conditions of the water-soluble metabolite sample are as follows: the temperature of the capillary tube is kept at 600-650 ℃, the pressure of the sheath gas is 50-60psi, the pressure of the auxiliary gas is 40-50psi, the primary scanning range is 5-1250m/z, the positive mode spraying voltage is 4-5kV, and the negative mode spraying voltage is-4 to-5 kV;
the mass spectrometry conditions of the lipid sample are as follows: the temperature of the capillary tube is kept at 400-500 ℃, the pressure of sheath gas is 50-60psi, the pressure of auxiliary gas is 60-65psi, the primary scanning range is 5-1250m/z, the positive mode spraying voltage is 5-6kV, and the negative mode spraying voltage is-4 to-5 kV.
7. The method for analyzing a biological sample for researching fat-reducing and lipid-lowering properties of Eurycoma longifolia according to claim 1, wherein in the step (2), the result obtained by the liquid chromatography-tandem mass spectrometry is used for analyzing a metabolic pathway, and the analysis of the metabolic pathway comprises the following steps:
(3.1) analyzing and identifying metabolites of a result obtained by the liquid chromatography-tandem mass spectrometry detection based on an R language algorithm to obtain a statistical result;
(3.2) after normalizing the statistical results, performing principal component analysis, partial least square discriminant analysis or orthogonal partial least square discriminant analysis to group the metabolites;
(3.3) MetaboAnalyst analysis was performed by R language to identify representative metabolic pathways.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011218040.5A CN112326849B (en) | 2020-11-04 | 2020-11-04 | Biological sample analysis method for researching fat-reducing and lipid-lowering characteristics of Eurycoma longifolia |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011218040.5A CN112326849B (en) | 2020-11-04 | 2020-11-04 | Biological sample analysis method for researching fat-reducing and lipid-lowering characteristics of Eurycoma longifolia |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112326849A CN112326849A (en) | 2021-02-05 |
| CN112326849B true CN112326849B (en) | 2022-07-12 |
Family
ID=74323632
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011218040.5A Active CN112326849B (en) | 2020-11-04 | 2020-11-04 | Biological sample analysis method for researching fat-reducing and lipid-lowering characteristics of Eurycoma longifolia |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112326849B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113917062A (en) * | 2021-10-26 | 2022-01-11 | 四川大学华西医院 | Metabonomics analysis method of multi-dimensional MXene nano material |
| CN114636765A (en) * | 2022-03-02 | 2022-06-17 | 四川大学华西医院 | Metabonomics analysis method for sugar reduction characteristic research of ficus glomerata |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103776911A (en) * | 2012-10-22 | 2014-05-07 | 中国科学院大连化学物理研究所 | Method for simultaneous extraction and analysis of metabolite group and lipid group in microtissue |
| CN108593821B (en) * | 2018-06-26 | 2021-06-22 | 上海市疾病预防控制中心 | Sample extraction method for tissue sample metabonomics and lipidomics research |
-
2020
- 2020-11-04 CN CN202011218040.5A patent/CN112326849B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN112326849A (en) | 2021-02-05 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109884302B (en) | Lung cancer early diagnosis marker based on metabonomics and artificial intelligence technology and application thereof | |
| CN112326849B (en) | Biological sample analysis method for researching fat-reducing and lipid-lowering characteristics of Eurycoma longifolia | |
| Peng et al. | Fingerprint profile of active components for Artemisia selengensis Turcz by HPLC–PAD combined with chemometrics | |
| CN102914597B (en) | Quality testing method for fingerprint of herbal medicine musk | |
| CN107037146B (en) | Method for controlling quality of compound wood chicken granules | |
| Chen et al. | Metabolomic comparison between wild Ophiocordyceps sinensis and artificial cultured Cordyceps militaris | |
| CN112151121B (en) | Diagnostic marker for diagnosing esophageal cancer, kit and screening method thereof, and construction method of esophageal cancer diagnostic model | |
| CN112666287B (en) | GCMSMS-based high-throughput analysis method and application of animal intestinal flora metabolites | |
| CN111681715A (en) | Raspberry quality marker and preparation method thereof | |
| Yang et al. | Untargeted metabolomics and targeted quantitative analysis of temporal and spatial variations in specialized metabolites accumulation in Poria cocos (Schw.) wolf (Fushen) | |
| CN110208392B (en) | Method for metabonomics research of selenium-rich tobacco leaves based on UPLC-QTOF-MS | |
| CN114002368A (en) | Method for determining illegal added components in health food by ultra-high performance liquid chromatography-quadrupole-time-of-flight high resolution mass spectrometry | |
| CN112147265A (en) | Honeysuckle anti-inflammatory quality marker screening and quality identification method and application | |
| CN114428130B (en) | Method for obtaining potential lipid-lowering markers and metabolic pathways of walnut green seedcase polyphenol extract | |
| CN109929006B (en) | Extraction method and application of ergosterol peroxide in pleurotus ferulae | |
| CN114191461A (en) | Application of maca in treatment of alcoholic fatty liver | |
| CN114636765A (en) | Metabonomics analysis method for sugar reduction characteristic research of ficus glomerata | |
| CN113848261B (en) | Identification method of fungi based on lipidomic | |
| CN110531001B (en) | Metabolism marker for distinguishing taxus yunnanensis and taxus mairei and detection method thereof | |
| CN1807429A (en) | Use of fern in extracting harringtonine or homoharringtonine | |
| Liu et al. | Comparative immune-related metabonomics analysis of plasma from mouse after given long-term astragalus membranaceus and panax ginseng | |
| CN110441439B (en) | Metabolism marker for distinguishing taxus mairei and taxus yunnanensis and detection method thereof | |
| CN116270628B (en) | Pharmaceutical composition for preventing and treating Alzheimer disease and related diseases causing cognitive dysfunction | |
| CN115902234A (en) | Liver metabolite detection marker composition for detecting calcium and phosphorus metabolic disorder of sheep under natural grazing | |
| CN115290782B (en) | Identification method of preparation containing Hirudo, scorpio, bombyx Batryticatus and/or Eupolyphaga Seu Steleophaga and its application |
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 |