Marker, reagent or kit for detecting whether COVID-19 disease is cured

A coronavirus, a new type of technology, applied in the field of reagents or kits, markers to detect whether the new coronavirus disease is cured, can solve the problem of no biomarkers for the occurrence, development and outcome of coronavirus disease

Pending Publication Date: 2020-10-02
武汉市金银潭医院
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Currently, there are no biomarkers for the onset, progression and outcome of coronavirus disease

Method used

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  • Marker, reagent or kit for detecting whether COVID-19 disease is cured
  • Marker, reagent or kit for detecting whether COVID-19 disease is cured
  • Marker, reagent or kit for detecting whether COVID-19 disease is cured

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0033] Example 1: Mass Spectrometry Analysis of Plasma Samples from Patients with New Coronary Pneumonia

[0034] 1. Experimental materials

[0035] Plasma samples from COVID-19 patients, including whole blood collected from 10 mild patients (M1T1-M10T1, referred to as MT1), 7 severe patients (S1T1-S7T1, referred to as ST1) and 10 mild patients Whole blood collected before discharge (M1T2-M10T2, referred to as MT2) and whole blood collected from 7 critically ill patients before discharge during hospitalization (S1T2-S7T2, referred to as ST2) totaled 34 whole blood samples from a hospital.

[0036] According to the "Diagnosis and Treatment Plan for Pneumonia Infected by Novel Coronavirus (Trial Version 6)" jointly issued by the General Office of the National Health Commission and the Office of the State Administration of Traditional Chinese Medicine, the clinical classification is as follows: mild, mild clinical symptoms, no pneumonia manifestations in imaging ;Severe, meeting...

Embodiment 2

[0044] Example 2: Machine learning screening for markers of cure in COVID-19 patients

[0045] 1. Experimental materials

[0046] Mass spectrometry data of 34 plasma samples (source Example 1), Python 3.7 (https: / / www.anaconda.com / ), Scikit learn 0.22.1 (https: / / scikit-learn.org / stable / ). The source code of this experiment is https: / / github.com / Ning-310 / POC-19.

[0047] 2. Experimental process

[0048] (1) Screen for differential proteins, screen for protein fold change (FC) absolute value greater than 0.8 in ST1+MT1 group and ST2+MT2 group, and two-tailed unpaired Welch T test is less than 0.01 (|log2(FC)| > 0.8, unpaired two-sided Welch'st-test, P < 0.01).

[0049] (2) Randomly select no more than 5 proteins from the differential proteins to form a potential optimal marker combination (OBC). The initial weight value of each protein is set to 1, and 1000 OBC candidates are set.

[0050] (3) For each candidate OBC, we randomly generate a training dataset and a testing data...

Embodiment 3

[0058] Example 3: Validation of OBC Predictor Accuracy

[0059] 1. Experimental materials

[0060] Mass spectrometry data of 34 plasma samples, Python 3.7 (https: / / www.anaconda.com / ).

[0061] 2. Experimental process

[0062] (1) Differentiate each protein in OBC identified as true positive (TruePositive, TP), true negative (True Negative, TN), false positive (False Positive, FP) and false negative of the possibility of COVID-19 patients and cured patients (FalseNegative, FN) ratio for chaotic logic analysis.

[0063] (2) Use Scikit learn 0.22.1 software to draw the chaos matrix.

[0064] The result is as image 3 As shown, the OBC combination predicts the true positive rate of 82% and the false positive rate of 18.

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Abstract

The invention relates to the technical field of biology, in particular to a marker, reagent or kit for detecting whether COVID-19 disease is cured. A plasma protein marker combination for diagnosing curing of a COVID-19 patient comprises a serine protease inhibitor 3, lymphocyte cytoplasmic protein 1, a peptidase inhibitor 16 and fetuin B. The results show that the area under the curve (AUC) valueof a receiver operating curve (ROC) of the four protein combinations predicting the cure of the COVID-19 patients is 0.947, the true positive rate of predicted cure is 82%, and the false positive rate is 18%. In addition, an enzyme-linked immunosorbent assay (ELISA) experiment finds that the protein concentration is significantly different in the plasma of the COVID-19 patient and a cured patient, which further confirms the accuracy of the combination for predicting the cure of the COVID-19 patient.

Description

technical field [0001] The present invention relates to the field of biotechnology, in particular to markers, reagents or kits for detecting whether the novel coronavirus disease is cured. Background technique [0002] The novel coronavirus disease (COVID-19) caused by SARS-CoV-2 infection has a wide range of symptoms, ranging from mild cold and fever, to respiratory syndrome, pneumonia, systemic multiple organ failure and even death. Currently, there are no biomarkers for the occurrence, development and outcome of coronavirus disease. Contents of the invention [0003] In view of this, the present invention provides markers, reagents or kits for detecting whether the novel coronavirus disease is cured. Alpha-1-antichymotrypsin (or Serpin A3), Plastin-2 (or L-Plastin), Peptidase inhibitor 16 and Fetuin-B protein concentrations are significantly different in the plasma of COVID-19 patients and cured patients, which further confirms the The accuracy of the combination in p...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): C12Q1/6883G01N33/68
CPCC12Q1/6883G01N33/6893C12Q2600/158Y02A50/30
Inventor 周溪尚游张定宇薛宇舒婷邱洋吴迪
Owner 武汉市金银潭医院
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