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Method for establishing intestinal health state diagnosis model based on fat-soluble metabolite factor in serum and application

A technology for intestinal health and state diagnosis, applied in biological neural network models, neural learning methods, character and pattern recognition, etc., can solve problems such as non-specific tumor applications and poor creativity

Pending Publication Date: 2019-10-25
中精普康(北京)医药科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0015] The third category is similar to the present invention in that the detection methods are similar, but there is no application for specific tumors, such as:
[0018] 1. For the third category of applications, although the detection methods are similar, the detected metabolites may overlap. The third category of applications is to patent the detection method, and then must rely on the use of all the information of all selected metabolites. Differentiate and identify different disease states, the detection method itself is the method and data published by the instrument manufacturer, and the creativity is not good;

Method used

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  • Method for establishing intestinal health state diagnosis model based on fat-soluble metabolite factor in serum and application
  • Method for establishing intestinal health state diagnosis model based on fat-soluble metabolite factor in serum and application
  • Method for establishing intestinal health state diagnosis model based on fat-soluble metabolite factor in serum and application

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0060] Example 1: Establishment of a liquid-phase-tandem mass spectrometry method for simultaneous detection of 110 kinds of fat-soluble metabolites in human serum

[0061] 1. Purpose

[0062] Take "RFA446", "RFA447", "RFA449", "myo-inositol", "citrate-isocitrate", "citrate", "uridine", "shikimate-3-phosphate", "cyclic-AMP", "Sedoheptulose 1 ,7-bisphosphate(SBP)", "S-adenosyl-L-homocysteine_neg", "adenosine 5-phosphosulfate", "ADP_neg", "dGDP_neg", "IDP_neg", "cholesteryl sulfate", "ATP_neg", "dGTP" , "Dephospho-CoA_neg", "NADPH_neg", "coenzyme A_neg", "taurine", "benzeneacetic acid", "hypoxanthine", "acetylphosphate", "Hydroxyphenylaceticacid", "Uric acid", "shikimate", "lysine", "D-glyceraldehdye-3-phosphate", "2-Isopropylmalic acid", "dephospho-CoA_pos", "Imidazole", "glutamine", "Gln", "glutamate", "methionine", "Met1", "Met2" , "N1-methyl 2-pyridone-5-carboxamide", "histidine", "His", "2-Aminooctanoic acid", "carnitine", "phenylalanine", "Phe", "1-Methyl-Histidine"," argini...

Embodiment 2

[0107] Example 2: Metabonomics study of targeted lipid-soluble metabolites in patients with precancerous lesions or colorectal cancer

[0108] 1. Purpose

[0109] Carry out the metabolomics study of serum targeted lipid-soluble metabolites.

[0110] 2 Data processing and statistical methods

[0111] Use R language software for multi-dimensional data processing, use ANOVA to analyze the difference in the content of lipid-soluble metabolites in the serum of each group, and p <0.01 is statistically significant, and the artificial intelligence pattern recognition technology is used to calculate the proportional relationship between the data of different groups, and the feature items with a difference greater than 1.20 are selected. Finally, the random forest model and pattern recognition technology are used to further optimize the differential fat-soluble metabolism Things.

[0112] 3 Multidimensional data analysis and analysis of difference variables of fat-soluble metabolites in serum

[...

Embodiment 3

[0119] Example 3: Establishment of a diagnostic model of intestinal health status based on fat-soluble metabolite factors in serum

[0120] 1. Purpose

[0121] The intestinal health diagnosis model was established based on the serum fat-soluble metabolite factors, and the model was validated.

[0122] 2 Data processing and statistical methods

[0123] Using R language for artificial intelligence analysis, drawing receiver operating characteristic curve (receiver operating characteristic curve, ROC curve).

[0124] 3 Establishment of intestinal health diagnosis model and verification of diagnosis model

[0125] 3.1 Establishment of intestinal health diagnosis model

[0126] The ROC curve is a curve drawn with the false positive rate [expressed in 1-specificity] as the abscissa and the true positive rate [expressed in sensitivity] as the ordinate. It is mainly used to evaluate clinical indicators for disease To confirm the best diagnostic cut-off value, and to compare the diagnostic effica...

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Abstract

The invention relates to a method for establishing an intestinal health state diagnosis model based on a fat-soluble metabolite factor in serum and an application. The diagnosis model is established by using a feedforward back propagation neural network algorithm, a joint factor is determined, and a screening method for the construction of the fat-soluble metabolite factor in the intestinal healthstate diagnosis model is proposed. The method of the invention comprises the steps of establishing a liquid phase tandem mass spectrometry combined detection method for the simultaneous detection ofthe content of 110 lipid-soluble metabolites in a human serum, ie, screening for 110 lipid-soluble metabolites with better peak shapes, and then performing serum-targeted fat-soluble metabolite metabolomics study to determine a best differential fat-soluble metabolite as the fat-soluble metabolite factor. The intestinal health state diagnosis model constructed in the invention provides an effective and reliable method for the clinical diagnosis of intestinal health and has a good value of intestinal health assisted diagnosis.

Description

Technical field [0001] The invention belongs to the technical field of intestinal health diagnosis, and particularly relates to a method for establishing an intestinal health status diagnosis model based on fat-soluble metabolite factors in serum and its application. Background technique [0002] Intestinal health, especially colorectal cancer, is a common cancer that occurs in the gastrointestinal tract. The cause of the disease is mostly related to poor living habits and aging. The risk of disease in people over 40 has risen sharply. Colorectal cancer has the third highest incidence and second mortality among global cancers. In China, the incidence of colorectal cancer ranks third among cancers, and the mortality rate ranks fifth. Colorectal cancer is a relatively slow-developing cancer. It may take ten years to develop from early stage to stage IV. The 5-year survival rate of stage 0 / I colorectal cancer can reach 90%, while the survival rate of stage IV is only 5-7%. . Earl...

Claims

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Application Information

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IPC IPC(8): G01N30/02G01N30/72G01N30/86G06N3/08G06K9/62
CPCG01N30/02G01N30/72G01N30/8631G06N3/084G06F18/214
Inventor 戴旭东林凯
Owner 中精普康(北京)医药科技有限公司
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