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Rapid mass spectrometry and spectrum identifying method for peptide fingerprint spectrum

A technology of fingerprint and mass spectrometry, applied in the direction of analyzing materials, material separation, measuring devices, etc., can solve the problems that hinder the clinical application of peptide spectrum analysis technology, lack of rapid analysis kits, etc., and achieve accurate, fast, simple and easy storage of detection methods , Improve the effect of detection throughput

Pending Publication Date: 2018-11-27
HANGZHOU WELL HEALTHCARE TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, the complexity of biological samples and peptide mapping data, as well as the lack of supporting rapid analysis kits, databases and software are bottlenecks hindering the clinical application of peptide mapping technology

Method used

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  • Rapid mass spectrometry and spectrum identifying method for peptide fingerprint spectrum
  • Rapid mass spectrometry and spectrum identifying method for peptide fingerprint spectrum
  • Rapid mass spectrometry and spectrum identifying method for peptide fingerprint spectrum

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0042] 1) Fix the P-type boron-doped crystalline silicon wafer in the electrolytic cell, add 55ml of ethanol with a volume ratio of 1:0.05-1:6 and 10%-40% hydrofluoric acid as the electrolyte, and The silicon wafer is used as the anode, and the platinum electrode is used as the cathode. Perform DC electrolytic etching and stripping. Set the current intensity to 0.2-2 1, and the etching time to 60-600 s. After vacuum drying for 10 minutes, porous silicon particles with a pore diameter of 1-15 nm, a thickness of 0.1-10 μm, and a diameter of 10-50 μm were obtained.

[0043] 2) Porous silicon particles modified by gold nanoparticles are prepared by electrochemical deposition, and the freshly prepared porous silicon chip is placed in a Teflon tank, and electrolyzed with chloroauric acid (0.01-0.1% w / v) solution. liquid for electrochemical deposition. After the completion, the porous silicon layer is peeled off, and the surface-modified gold porous silicon particles are obtained a...

Embodiment 2

[0048] Collection of serum samples: Serum samples from cancer patients have been verified by the clinical gold standard. The sample information is shown in Table 1. Serum samples from 24 colorectal cancer patients, 24 liver cancer patients and 24 healthy people were collected; the male to female ratio of colorectal cancer patients in the samples was 15:9, the average age was 56, and the age range Between 20 and 72; the male to female ratio of liver cancer patients is 13:11, the average age is 60, and the age range is between 38 and 81; the male to female ratio of healthy people is 12:12, the average age is 58, and the age range is 51 Between -79.

[0049] Table 1 Serum sample information of patients with colorectal cancer, liver cancer and healthy people

[0050] sample source

Number of samples

male / female ratio

average age

age range

colorectal cancer patients

24

15 / 9

56

20-72

liver cancer patients

24

13 / 11

...

Embodiment 3

[0055] 1) Data processing: use Flex1n1lysis software to smooth the original spectrum and subtract baseline processing to eliminate background influence and noise interference, and then export the list of protein molecular weights. Perform peak alignment and normalization in M1TL1B, and use the t-test to select the three surface-modified porous silicon particles to detect the difference between healthy people and colorectal cancer patients, healthy people and liver cancer patients, and liver cancer patients and colorectal cancer patients. There were differences (p<10-7) between peaks; further screening finally obtained 8 peaks as characteristic values, m / z were 495.27, 1894.94, 3213.78, 4048.97, 6650.63, 8145.10, 8619.19, 9389.30.

[0056] 2) Artificial neural network to establish a predictive model: Combine the generated characteristic peak data with artificial neural network software to generate a predictive model to diagnose colorectal cancer. The selected 8 peaks are used a...

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Abstract

The invention discloses a rapid mass spectrometry and spectrum identifying method for a peptide fingerprint spectrum. The method comprises the following steps: 1) preparing porous silica particles andperforming surface chemical modification; 2) utilizing the porous silica particles to enrich polypeptide substances in a biological sample; 3) mixing the porous silica particles capturing polypeptidesubstances of the biological sample with a mass spectrum substrate and then directly applying to a target, and performing particle in situ mass spectrum detection; and 4) adopting a statistic algorithm and an artificial neural network for establishing an identifying prediction model on the basis of serum peptide fingerprint spectrum. In the invention, the porous silica particle material is adopted for achieving the function of one-step separating, enriching and detecting low-medium abundance small-molecular protein in a serum sample. According to the method, a disease prediction model is established on the basis of the peptide fingerprint spectrum through the statistic algorithm and the artificial neural network, so that a patient can be identified from a plenty of samples and the diseaseprediction model has higher specificity and sensitivity. According to the invention, a mass spectrum kit for identifying and monitoring diseases on the basis of the peptide fingerprint spectrum is simple and easy to store and the detection method is accurate, convenient and quick.

Description

technical field [0001] The invention belongs to an innovative in vitro diagnostic mass spectrometry detection method, relates to the field of peptide fingerprint mass spectrometry detection, in particular to a method for rapid mass spectrometry analysis and spectrum discrimination of peptide fingerprints. Background technique [0002] Proteomics takes all the proteins expressed by the genome of a cell or tissue as the research object, and analyzes the protein composition and activity rules in cells, tissues or organisms from the overall system level. In the process of tumor research, many related genes such as oncogenes and tumor suppressor genes have been discovered. In normal cells, oncogenes are suppressed, and tumor suppressor genes are activated. In contrast, in tumor cells, the activation and suppression of genes ultimately require the participation of proteins. Therefore, there must be differences in the proteins, polypeptides and proteases expressed in normal cells a...

Claims

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Application Information

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IPC IPC(8): G01N30/06G01N30/72G01N30/86
CPCG01N30/06G01N30/72G01N30/8686
Inventor 邬建敏谈洁钟巧玲陈锡胜栾春燕余捷凯
Owner HANGZHOU WELL HEALTHCARE TECH CO LTD
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