78 results about "Targeted metabolomics" patented technology

The invention discloses a plant lactobacillus. The plant lactobacillus has the characteristic of efficiently tolerating 30% (w / v) cistanche substrate. The invention also discloses a medicinal and edible composition consisting of 85 parts of cistanche deserticola, 5 parts of rehmannia, 5 parts of fructus alpiniae oxyphyllae and 5 parts of Chinese yam, the composition is fermented by using plant lactobacillus, and the cistanche deserticola fermentation liquor is prepared by adopting a multi-stage temperature fermentation process to ferment for 16 hours. A non-targeted metabonomics result shows that the phytobacterium plantarum activates an upstream channel for synthesis of phenylethanoid glycoside substances, and the abundance of forsythiaside B is increased by 133 times compared with that before fermentation. The fermentation liquor can achieve the functions of reproductive anti-aging, kidney protection and body endurance improvement by down-regulating COX-2a and TGF-beta-1 gene expression.

The invention relates to the field of strong wine detection, and discloses a strong wine visual non-target metabonomics origin traceability method, which comprises the following steps: firstly, collecting strong wine original data, digitizing and outputting the collected strong wine original data to obtain strong wine output data; performing preliminary analysis by using a clustering analysis method to obtain first analysis data; performing secondary analysis on the first analysis data by using a principal component analysis mode to obtain second analysis data; and finally analyzing the second analysis data by partial least square discriminant analysis or orthogonal partial least square discriminant analysis, and screening, comparing and identifying the characteristic compounds to obtain the non-target metabonomics origin traceability place of the strong wine. According to the method, the problems that a non-target metabonomics traceability technology easy to visually display does not exist in the prior art, and a standardized operation instruction integrating efficient pretreatment, non-target screening, rapid traceability, accurate confirmation and visual display does not exist are solved.

The invention belongs to the technical field of biological medicine, and particularly relates to application of phenylalanine in evaluating Kawasaki disease and treating effect thereof and application of a phenylalanine inhibitor in treating Kawasaki disease. According to serum non-targeted metabonomics analysis and verification of KD children and IVIG treated KD children, phenylalanine is highly expressed in KD children, and phenylalanine is remarkably reduced after IVIG treatment of KD and tends to healthy children. The phenylalanine can be used as a serological marker for evaluating the Kawasaki disease treatment effect and diagnosing IVIG second-line treatment, and is high in specificity and sensitivity. After the phenylalanine inhibitor is administered to a KD model mouse, the content of phenylalanine in serum is remarkably reduced and is consistent with the trend in serum of the KD mouse treated by IVIG, myrica tongues are remarkably relieved, arterial dilatation is slowed down, and expression of inflammatory factors is reduced. The phenylalanine inhibitor has the effects of treating Kawasaki disease, improving myrica rubra tongue and slowing down arterial dilatation.

The invention discloses a method for analyzing component difference between Maotai-flavor yeast and yeast-making wheat by using non-targeted metabonomics. The method comprises the following steps: S1, pre-treating a sample; s2, detecting each sample by adopting the combination of an ultra-high performance liquid chromatograph and a quadrupole time-of-flight mass spectrometer; s3, acquiring original data, performing peak extraction, peak alignment and normalization by adopting metabonomics data analysis software, and evaluating the overall difference and intra-group variation among sample groups by adopting principal component analysis; constructing a grouping discrimination model through discriminant analysis of an orthogonal partial least square method; determining differential metabolites of the two groups of samples by taking variable projection importance (VIP) greater than 1 and statistical significance P less than 0.01 as a primary screening standard and combining a secondary screening standard that the difference multiple log2FC greater than 2 is up-regulated and the difference multiple log2FC less than-2 is down-regulated; s4, performing compound structure and category annotation on the screened differential metabolites through a metabolome database; and performing pathway enrichment analysis by adopting a statistical test method, and determining a core metabolic pathway enriched by the differential metabolites.

The invention discloses an application of astaxanthin in preparation of a regulator for improving the gentisic acid level. On the basis of non-targeted metabonomics analysis, it is found for the first time that in the SAP pathogenesis process, the level of a flora metabolite, namely gentisic acid (GA), in intestinal contents is remarkably reduced, and in-vivo gentisic acid level can be remarkably callback through astaxanthin intervention. Further research proves that exogenous supplement of gentisic acid can effectively simulate the protection effect of astaxanthin, including improvement of pancreatic tissue pathological damage, reduction of serum lipase and amylase activity, and inhibition of systemic inflammatory response (down-regulation of IL-1beta, IL-6 and TNF-alpha and up-regulation of IL-10). The invention not only discloses a new mechanism that astaxanthin plays a therapeutic role through an'intestinal flora-metabolite 'axis, but also determines that gentisic acid is used as a novel drug target for treating SAP, and constructs a new method for screening drugs for treating SAP according to the novel drug target.

The invention belongs to the technical field of compound analysis and identification, and discloses application of a metabonomics analysis technology to identification of lycium seed oil. According to the metabonomics analysis technology, the characteristic components of the lycium seed oil are identified through Log2 Fold Channel and VIP values, and the screening conditions for identifying the characteristic components of the lycium seed oil are | Log2 Fold Channel | > 1.5, and VIP < gt >; the method specifically comprises the steps of sample preparation, non-targeted metabonomics analysis, extraction and identification of characteristic peaks, similarity analysis, difference analysis and screening of differential markers. According to the method, a non-targeted metabonomics analysis method is adopted, various metabolic components in the lycium barbarum seed oil can be undiscriminately covered, the limitation that a traditional identification technology only aims at a few indexes is broken through, the unique characteristic components of the lycium barbarum seed oil can be accurately screened out, and the accuracy and specificity of an identification result are greatly improved.

The invention belongs to the technical field of drug detection, and particularly relates to a method for detecting lycium barbarum glycopeptide metabolites in rat plasma and tissues based on non-targeted metabonomics. According to the method, after rat lycium barbarum glycopeptides are administered through intragastric administration, blood, liver, intestine, lung and brain tissue samples after administration are collected. A UPLC-Q-TOF-MS (Ultra Performance Liquid Chromatography-Quadrupole Time of Flight Mass Spectrometry) analysis method is combined with a statistical analysis method comprising principal component analysis (PCA) and orthogonal-partial least squares discriminant analysis (OPLS-DA) to carry out in-vivo metabonomics analysis on the wolfberry glycopeptide. Then, based on a human metabolome database (HMDB), lycium barbarum glycopeptide differential metabolite is searched, so that the pharmacological action mechanism of the lycium barbarum glycopeptide is clarified from the perspective of metabolism, and a foundation is laid for deep research and development of the medicinal value of the lycium barbarum glycopeptide in future.

The application discloses a plant lactobacillus. The plant lactobacillus has the characteristics of high tolerance to 30% (w / v) cistanche matrix. The application also discloses a homologous medicinal and edible formula which is composed of 85 parts of cistanche, 5 parts of rehmannia root, 5 parts of yizhi kernel and 5 parts of yam. The formula is fermented by the plant lactobacillus, and a cistanche and yam fermented liquid is prepared by adopting a multi-stage temperature fermentation process for 16 hours. Non-targeted metabolomics results show that the plant lactobacillus activates the upstream pathway of phenylethanoid glycoside synthesis, and the abundance of forsythoside B is up-regulated by 133 times compared with that before fermentation. The fermented liquid can play the functions of reproductive anti-aging, kidney protection and body resistance improvement by down-regulating the expressions of COX-2a and TGF-beta-1 genes.

The invention provides application of acetylcholine and 1-carboxyl-6-hydroxy-3, 4-dihydro-beta-carboline (the code in the attached drawing of the abstract is CHEMBL461889) in early pregnancy diagnosis, non-targeted metabonomics detection and analysis are carried out on the urine of pregnant and non-pregnant sows by virtue of a liquid chromatography-mass spectrometry technology; the two metabolic markers capable of being used for early pregnancy diagnosis of the sows are screened out by introducing two deep learning models for joint analysis, the AUC values of ROC curves of the two metabolic markers are 1, the accuracy is very high, and the pregnancy state of the sows can be accurately judged only 18 days after the sows are bred. The invention provides a novel effective sow early pregnancy diagnosis method for the pig breeding industry, and has important significance for reducing the breeding cost.

The invention discloses a drug collaborative screening system based on artificial intelligence prediction and metabonomics verification, and belongs to the technical field of artificial intelligence and bioinformatics crossing. Comprising a multi-source data acquisition and feature fusion module, an artificial intelligence prediction module, a drug screening and visualization module, a metabonomics verification module and a feedback optimization and self-learning module. According to the invention, through multi-modal data integration and feature coding, unified modeling of a drug-disease-molecule network is realized; drug combination synergistic effect prediction is realized through an artificial intelligence algorithm; a prediction result is verified by using non-targeted metabonomics data, and the mechanism interpretability of the model is enhanced; a technical system capable of realizing closed-loop optimization is constructed, and an algorithm and experiment dual-verification platform is provided for drug discovery and precision medicine.

The invention provides an application of metabolites in sow vaginal secretion in early pregnancy diagnosis, and finds that three metabolic molecules can be used as markers for the early pregnancy diagnosis of sows for the first time on the basis of non-targeted metabonomics and machine learning conjoint analysis. According to the present invention, the metabolic markers are respectively INDOLEPROPIONIC ACID (indolepropionic acid), cis-Amonitate (cis-Amonitate) and 4-p-Coumaroylquinic acid (4-p-coumaroylquinic acid), the ROC curve AUC values of the metabolic markers are respectively 0.88, 0.92 and 0.77, and the metabolic markers have excellent diagnosis performance during the combination diagnosis. The pregnancy diagnosis is carried out by adopting the vaginal secretions of the sows 18 days after hybridization, the effective pregnancy diagnosis time is advanced by 5-8 days on the basis of a wave diagnosis method, and the method has important significance for reducing cost and increasing ultrasonic efficiency in live pig feeding.

The invention discloses a euphorbia helioscopia seed extract as well as a preparation method and application thereof in preparation of an anti-lung cancer medicine, and belongs to the field of biological medicines. The preparation method comprises the following steps: performing vortex extraction, centrifugation and concentration on a methanol extracting solution to prepare a euphorbia helioscopia seed extract; wide targeted metabonomics research results show that chemical components of the euphorbia helioscopia seed extract and chemical components of the euphorbia helioscopia whole herb extract are remarkably different. Experimental results show that the euphorbia helioscopia seed extract provided by the invention has strong toxicity to lung cancer A549 cells, has a remarkable inhibition effect on EMT generation and invasion and metastasis capacities in the A549 cells induced by TGF-beta1, and can be used for preparing medicines for resisting lung cancer. The invention provides technical support for development of the euphorbia helioscopia seed extract as a novel anti-lung cancer drug, lays a foundation for full utilization of euphorbia helioscopia seed resources, and has a wide application prospect.

The invention relates to the technical field of food identification, in particular to a method for identifying sheep milk and milk based on metabonomics, and aims to solve the industrial pain point that cheap milk is doped into current high-end sheep milk products and is difficult to detect through conventional physicochemical indexes, and the problems that existing protein, DNA and other identification methods are insufficient in sensitivity, complex in operation and the like. According to the invention, a non-targeted metabonomics analysis strategy is innovatively adopted. The saliency difference metabolites between the sheep milk and the milk are systematically screened from the omics level, and rapid, high-sensitivity and high-specificity identification on the authenticity of the sheep milk and whether the sheep milk is mixed with the milk is realized. According to the invention, a key technical basis and a material core are provided for developing corresponding detection products and market supervision methods.

This invention provides a method for increasing flavonoid production in longan embryogenic callus using exogenous quercetin or vitexin, belonging to the field of plant tissue culture. Key metabolites quercetin and vitexin were screened from extensive targeted metabolomics data of longan embryogenic callus treated with arginine and D-arginine. Quercetin or vitexin was added to the subculture medium of longan embryogenic callus, and the growth and flavonoid content of longan embryogenic callus at different treatment times were measured. The relative flavonoid production rate was calculated, thereby achieving the goal of high flavonoid production. The key metabolites quercetin and vitexin identified in this invention can significantly increase flavonoid production in longan embryogenic callus and have significant application prospects.

The invention provides a metabolic marker combination for identifying okra related species, an identification method and application of the metabolic marker combination, and belongs to the technical field of drug detection. The identification method provided by the invention comprises the following steps: carrying out non-targeted metabonomics detection on dry powder samples of Abelmoschus manihot (L.) Medik., Abelmoschus moschus (L.) Meduli, Abelmoschus sagittifolius (L.) Merr. And Abelmoschus esculentus (L.) Moench by adopting ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS / MS), so as to obtain metabolite data, and carrying out quantitative analysis on the metabolite data, so as to obtain a sample of the Abelmoschus manihot (L.) Meduli, the sample of the Abelmoschus moschus (L.) Merr. And carrying out mass spectrum qualitative and quantitative analysis on metabolite data, and screening out common differential metabolites among the four plants as characteristic metabolites to realize variety identification of okra related species. The method can effectively distinguish okra species with similar morphologies, and has application value in traditional Chinese medicinal material original identification, germplasm resource screening and variety purity detection in a seedling raising stage.

This invention relates to a method for identifying and detecting urinary biomarkers of whole-grain wheat intake. These biomarkers include glycine conjugates of 3,5-dihydroxybenzoic acid, sulfate conjugates of o-aminophenol, sulfate conjugates of 2-acetaminophen, sulfate conjugates of 3,5-dihydroxyphenylvaleric acid, glucuronic acid conjugates of o-aminophenol, or glucuronic acid conjugates of 2-acetaminophen. The invention also relates to a high-throughput screening method for urinary biomarkers of whole-grain wheat intake. A whole-grain wheat dietary intervention experiment was designed, and through comparative analysis of human urinary metabolic profiles, non-targeted metabolomics technology was used to screen for urinary metabolic biomarkers of whole-grain wheat, providing a method for accurately assessing whole-grain wheat intake.

The application discloses a metabolic marker for distinguishing metabolic syndrome and simple obesity and application thereof. The marker comprises eight metabolites, i.e. glycocholic acid, lithocholic acid, linoleic acid, valine, leucine, alanine, serine and glycine. The application performs non-targeted metabolomics analysis on serum of metabolic syndrome and simple obesity patients by liquid chromatography mass spectrometry, finds eight metabolites with significant difference between the two, and finds that the eight metabolic markers have high AUC when used for diagnosing and distinguishing metabolic syndrome patients or simple obesity patients alone or in combination.

The invention relates to a quasi-targeting metabonomics analysis method based on liquid chromatography-mass spectrometry (LC-MS). The quasi-targeting metabonomics analysis method is used for simultaneously determining the relative content of 21 arginine anabolites in the liver. The method comprises the following steps: preparing a metabolite and an internal standard solution, optimizing multiple reaction monitoring (MRM) parameters, carrying out homogenization and acetonitrile precipitation pretreatment on a liver tissue sample, preparing a quality control (QC) sample, and establishing a standard curve through series dilution. The method meets analysis requirements in the aspects of linearity, precision, stability and the like, is suitable for relative quantitative research of arginine metabolites in liver tissues, and provides reliable technical support for related metabolic pathway analysis.

Targeting mitochondrial function is a strategy for preventing metabolic disorders, but restoring mitochondria diurnal regulation remains to be explored. Using targeted metabolomics, we identified 24-hour mitochondrial rhythms promoted by nocturnal time-restricted feeding (TRF) in mice fed a high-fat diet (HFD). Preceding its metabolic benefits, TRF promoted mitochondrial daily rhythms by converging on the enzyme dihydroorotate dehydrogenase (DHODH), which coordinates pyrimidine biosynthesis and mitochondrial oxidative metabolism. The inhibition of DHODH activity by the short half-life inhibitor BAY-2402234 modulated mitochondrial oxidative metabolism, thereby preventing diet-induced obesity, but only when injected at the transition between night and day. This timed inhibition of DHODH promoted oscillations in mitochondrial metabolic pathways and oscillations in the CoQ / CoQH2 ratio, improving metabolic adaptation to the HFD challenge. Our results highlight the role of mitochondrial daily rhythms in the pathophysiology of obesity and open avenues for chronopharmacological treatments targeting these rhythms. Thus, the present invention pertains to a method for treating or preventing obesity in a subject in need thereof. This method includes administering to the subject, at a specific time of the circadian rhythm, a therapeutically effective amount of a dihydroorotate dehydrogenase inhibitor that exhibits an inhibitory duration of less than 24 hours, and more specifically, a short half-life of less than 24 hours.

The invention discloses a colla corii asini in-vivo bioactive component cyclic dipeptide and a discovery method thereof, and belongs to the technical field of bioactive component analysis and application. The method comprises the following steps: establishing a rat donkey-hide gelatin administration model and collecting a sample, performing solid-phase extraction on the sample, performing LC-MS / MS peptidomics analysis and PEAKS database search, screening exogenous oligopeptides based on a feature-based molecular network (FBMN), performing cyclic dipeptide targeted metabonomics identification, and verifying cell viability. According to the method, 29 cyclic dipeptides are produced by metabolism in donkey-hide gelatin, and the cyclic dipeptides containing hydroxyproline (Hyp) can significantly improve the survival rate of HT-22 cells damaged by glutamic acid or hydrogen peroxide induction and have neuroprotective activity.

The application belongs to the technical field of biological medicine, and discloses application of NP in preparation of a preparation for regulating metabolism of the intestines of senile type 2 diabetes. The NP is formed by hydrogen bond combination of a peptide from soft-shelled turtle eggs with naringenin in a mass ratio of 100:1, and the mass of the peptide is less than 3 kDa; the preparation is used for regulating phenotype-related metabolic modules and intestinal micro-ecological-related metabolic modules, remodeling the intestinal metabolic regulation network taking differential metabolites as a bridge, and thus systemically improving metabolic disorders related to senile type 2 diabetes. It is found that NP intervention can obviously correct abnormal total metabolic profiles of feces of senile type 2 diabetes mice, and make the disease type metabolic profile shift to a new steady state of intervention type. Non-targeted metabolomics analysis by LC-MS / MS shows that the overall metabolic profile of the high-dose NP group is closer to that of the classic hypoglycemic drug metformin group, indicating that NP has a significant metabolic remodeling capacity.

The invention discloses an application of intestinal flora metabolite salicylic acid as a predictive marker of Escherichia coli calf diarrhea. The obviously up-regulated metabolite salicylic acid is screened out from the diarrhea calf feces through a non-targeted metabonomics technology, and in a group of new independent samples, it is verified through an ELISA test that the salicylic acid concentration of the diarrhea calf feces is obviously higher than that of a healthy group. ROC curve analysis shows that the area under curve (AUC) of SA for predicting escherichia coli calf diarrhea is 0.8148, and the method has good prediction capability. The invention provides a non-invasive, cheap, rapid and high-specificity prediction method, can be used for early warning and auxiliary diagnosis of Escherichia coli calf diarrhea, and has important significance for guiding clinical precise medication and reducing the death rate of calves.

This invention discloses a set of biomarkers, reagents, kits, and applications for predicting alcoholic liver disease (ALD), belonging to the field of biomarker technology. The key technical points are: This invention uses non-target metabolomics to analyze plasma from ALD patients and healthy controls to identify potential biomarkers and related metabolic pathways in the plasma of ALD patients. Through human fecal metagenomic sequencing, potential biomarkers in the microbiome of ALD patients are identified, providing a scientific basis for the pathogenesis and early screening of ALD. Furthermore, this invention evaluates the therapeutic effect of L-threonine on ALD and explores its molecular mechanism, providing solid preclinical evidence and theoretical basis for L-threonine as a safe and effective natural metabolite-derived drug for the treatment of ALD, opening new directions for the development of innovative ALD therapies.

The invention discloses a bifidobacterium activity dominant population induction culture method and application thereof, and belongs to the technical field of microbial fermention.The induction culture method comprises the steps that a seed solution is inoculated into a culture medium containing lactose, saccharose or maltose to be subjected to anaerobic fermentation to the end of logarithm; after the fermentation liquor is diluted, SYTOTM9 and PI dye are added, and a flow cytometer is used for sorting. According to the method, lactose, cane sugar or maltose is selected as a carbon source for high-density fermentation, living cells, damaged cells and dead cell subgroups are separated in combination with a flow cytometry sorting technology, and a subgroup differentiation mechanism is analyzed by utilizing non-targeted metabonomics, so that the sugar uptake capacity of the living cell subgroups cultured by cane sugar is improved by 30.55% compared with that of the damaged subgroups; the flowability of the membrane is improved by 95.23% compared with that of maltose culture, the thallus activity is remarkably improved, and a theoretical support and a technical method are provided for industrial production of probiotic high-activity preparations.

The present invention proposes a method and device for intelligently generating molecular fingerprints for non-targeted metabolomics, which relates to the field of data processing technology, including: performing weak enhancement processing on labeled data in mass spectrometry sample data, and performing weak enhancement processing and strong enhancement processing on unlabeled data in mass spectrometry sample data to obtain mass spectrometry training data; using a Transformer encoder to extract features from the mass spectrometry training data to obtain a Morgan molecular fingerprint, and using the Morgan molecular fingerprint as a constraint condition, using the forward diffusion process to generate random Gaussian noise as the basis for reverse diffusion to generate a target molecular fingerprint; using the screened target molecular fingerprint to train a preset network model to obtain a target network model to complete the processing of the mass spectrometry data to be processed. The present invention extracts features from mass spectrometry data and uses them as constraints to generate molecular fingerprints of metabolites to be analyzed, thereby realizing the training of the diffusion model and improving the generalization ability of the model.

The invention relates to an identification and detection method of a whole grain wheat urine intake marker, and the whole grain wheat urine intake marker comprises a glycine conjugate of 3, 5-dihydroxybenzoic acid, a sulfuric acid conjugate of ortho-aminophenol, a sulfuric acid conjugate of 2-acetaminophen, a glycine conjugate of 3, 5-dihydroxybenzoic acid, a sulfuric acid conjugate of 2-acetaminophen, a glycine conjugate of 3, 5-dihydroxybenzoic acid and a sulfuric acid conjugate of 2-acetaminophen. The invention also relates to a sulfuric acid conjugate of 2, 5-dihydroxyphenyl valeric acid, a glucuronic acid conjugate of ortho-aminophenol or a glucuronic acid conjugate of 2-acetaminophen. The invention further relates to a high-throughput screening method of the whole-grain wheat urine intake marker, a whole-grain wheat diet intervention experiment is designed, and the urine metabolism marker of the whole-grain wheat is screened out by utilizing a non-targeted metabonomics technology through contrastive analysis of a human urine metabolism spectrum. And the method is provided for accurately evaluating the intake of the whole-grain wheat.

The invention belongs to the technical field of biomedicine, and particularly relates to a method for detecting potential biomarkers of myocardial of an HFpEF mouse based on non-targeted metabonomics, which comprises the following steps: constructing an HFpEF mouse model by combining high fat diet with L-NAME, setting a conventional feeding control group, monitoring myocardial glucose metabolism through longitudinal [18F] FDG PET / CT, collecting myocardial tissues, and performing non-targeted metabonomics detection. And screening differential metabolites through Foldchange greater than or equal to 1.2 or less than or equal to 0.83 and p less than 0.05, and carrying out correlation analysis on the differential metabolites and [18F] FDG SUVmean to obtain 25 potential biomarkers. According to the method, the steps are clear and repeatable, the marker is directly related to myocardial energy metabolism, the diagnosis specificity is improved, and a support is provided for HFpEF targeted therapy research and development and molecular mechanism research.

The invention relates to the technical field of biomedicine, in particular to a group of key biomarkers for predicting endometrial receptivity, including specific microbial strains and metabolites, and a prediction model containing the markers. The method comprises the following steps: collecting a uterine cavity lavage fluid sample, carrying out 16S rRNA gene sequencing and non-targeted metabonomics analysis, and screening out eight key microbial strains and eight key metabolites; based on the markers, the following diagnostic models are constructed: a model only based on eight microbial strains; a model based on only eight metabolites; a combined microorganism and metabolite model; and a clinical data model is further combined. According to the method, a microbiome and metabolome multi-omics conjoint analysis strategy is adopted, strict screening is carried out in combination with LASSO regression, SVM-RFE and other machine learning algorithms, and the obtained biomarker is high in specificity. The constructed model, especially a combined model, shows high prediction precision and good calibration degree through verification of various curves.

The application discloses a kind of based on metabolic pathway analysis's Iresine heratensis fermentation quality regulation method, it is related to food biotechnology field, including, the sample of different varieties Iresine heratensis is obtained, carries out non-targeted metabolomics analysis, obtains metabolite spectrum data;The metabolite spectrum data carries out difference analysis, constructs key difference metabolite dataset;Metabolic pathway enrichment analysis is carried out to the key difference metabolite dataset, determines core metabolic pathway;Regulate the process parameter in Iresine heratensis fermentation process, obtain the fermentation product after regulation;The quality of the fermentation product after regulation is verified, feedback optimization the process parameter, form closed loop quality regulation method;The application is determined core metabolic pathway by constructing key difference metabolite dataset and enrichment analysis, realizes from traditional experience type fermentation process optimization to the change of accurate regulation based on metabolic mechanism, solves the problem that fermentation quality in prior art is greatly blind, target is not clear.

This invention belongs to the field of biomedical technology and discloses a bile acid-based predictive model for the severity of acute pancreatitis, its detection method, and its application. This invention establishes a combination of biomarkers that accurately reflect the pathological changes of acute pancreatitis by performing targeted metabolomics analysis on multiple small bile acid metabolites in serum, and further constructs a predictive model suitable for early clinical warning and severity stratification. This invention also provides a corresponding detection method for rapid and quantitative detection of the bile acid metabolites, enabling early identification and auxiliary diagnosis of severe acute pancreatitis.