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
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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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