CN112485439B - Specific protein reaction detection method, protein detection device and calibration method - Google Patents
Specific protein reaction detection method, protein detection device and calibration method Download PDFInfo
- Publication number
- CN112485439B CN112485439B CN202011250348.8A CN202011250348A CN112485439B CN 112485439 B CN112485439 B CN 112485439B CN 202011250348 A CN202011250348 A CN 202011250348A CN 112485439 B CN112485439 B CN 112485439B
- Authority
- CN
- China
- Prior art keywords
- curve
- protein
- calibration
- reaction
- sample
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
- G01N33/6893—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids related to diseases not provided for elsewhere
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/47—Scattering, i.e. diffuse reflection
- G01N21/49—Scattering, i.e. diffuse reflection within a body or fluid
- G01N21/51—Scattering, i.e. diffuse reflection within a body or fluid inside a container, e.g. in an ampoule
Abstract
A calibration method of a protein detection device comprises the steps of firstly measuring protein response curves of a first calibration sample and a second calibration sample on the protein detection device to be calibrated so as to obtain the first calibration response curve and the second calibration response curve. Then, a first curve characteristic R1 and a second curve characteristic R2 of the first calibration reaction curve and the second calibration reaction curve are respectively extracted. And inputting the protein concentration value C1 and the protein concentration value C2 of the first calibration sample and the second calibration sample into a protein reaction mathematical model to obtain a first test curve characteristic rb1 and a second test curve characteristic rb2, and further obtaining calibration coefficients according to the first curve characteristic R1, the second curve characteristic R2 and the second test curve characteristic rb2 so as to realize calibration. The calibration coefficients of the protein detection device are obtained through the test curve feature rb1 and the test curve feature rb2 obtained by extracting the curve feature R1, the curve feature R2 and the mathematical model, so that the calibration of the protein detection device is quicker and more accurate.
Description
Technical Field
The invention relates to the technical field of body fluid detection, in particular to a specific protein reaction detection method, a protein detection device and a calibration method.
Background
C-reactive protein (CRP) is an acute inflammatory timing phase response protein synthesized by the liver. CRP concentration in normal human blood is very low, synthesis is rapidly increased when the organism is subjected to stress, tissue wound and various inflammatory stimuli, blood is secreted from liver cells, and high-level CRP can be detected 12-18 hours after infection occurs. CRP elevated 12-14 days after infection can drop to baseline levels. Thus, it has been one of the indicators for evaluation of inflammatory diseases for many years, and the magnitude of the increase is related to the extent of infection. CRP has been widely used clinically as one of important markers for diagnosing bacterial infection. CRP is also a clinically important indicator for assessing heart disease incidence, recurrence rate, mortality. Recent studies have found that inflammation plays an important role in the development and progression of atherosclerosis and tumors. In view of the important role of serum CRP, the accuracy of its measurement is of great interest. Currently, the international traceability union (JCTLM) is working to advance the traceability and standardization of CRP, and there are few working researches in this area in China. Common methods for detecting CRP are varied and include nephelometry, turbidimetry, radioimmunoassay, chemiluminescence, ELISA, point of care CRP detection (POCT), and the like. At present, the method for measuring CRP in serum in a clinical laboratory mainly comprises an immunonephelometry method, which comprises a latex enhanced transmission nephelometry method and a rate scattering nephelometry method, wherein the two methods are mainly used for an automatic analysis system, the rate scattering nephelometry method is mainly used for a closed detection system in the immunodetection field, and the latex enhanced transmission nephelometry method is mainly used for an open detection system in the biochemical detection field.
In order to ensure the accuracy of the protein detection result, the protein detection device needs to be calibrated before protein detection, and in the prior art, the calibration of the protein detection device needs to be carried out on a plurality of calibration samples for multiple times, so that the calibration process is tedious, the time consumption is long, the consumed calibration samples are excessive, and the maintenance cost of the protein detection device is increased.
Disclosure of Invention
The invention mainly solves the technical problem of how to calibrate a protein detection device.
According to a first aspect, in one embodiment there is provided a method of calibrating a protein detection apparatus, comprising:
measuring protein response curves of a first calibration sample and a second calibration sample on the protein detection device to be calibrated so as to obtain the first calibration response curve and the second calibration response curve; the protein concentration value C1 and the protein concentration value C2 of the first calibration sample and the second calibration sample are known, and the protein concentration value C1 of the first calibration sample is greater than zero and less than the protein concentration value C2 of the second calibration sample;
respectively extracting curve characteristics of the first calibration reaction curve and the second calibration reaction curve to obtain a first curve characteristic R1 and a second curve characteristic R2;
Inputting a protein concentration value C1 of the first calibration sample into a protein reaction mathematical model of which the curve characteristic of a protein reaction curve is related to the protein concentration so as to obtain a first test curve characteristic rb1 output by the protein reaction mathematical model;
inputting a protein concentration value C2 of the second calibration sample into the protein reaction mathematical model to obtain a second test curve characteristic rb2 output by the protein reaction mathematical model;
obtaining a calibration coefficient of the protein detection device to be calibrated according to the first curve characteristic R1, the second curve characteristic R2, the first test curve characteristic rb1 and the second test curve characteristic rb2; the calibration coefficients of the protein detection device comprise a curve calibration slope Kb and a curve calibration intercept Bb;
and taking the acquired calibration coefficient as a protein detection calibration coefficient of the protein detection device so as to realize calibration.
In one embodiment, the protein detection apparatus to be calibrated acquires a protein response curve using nephelometry or turbidimetry;
and/or, the protein detection of the protein detection device comprises C-reactive protein detection and/or serum amyloid A detection.
In an embodiment, the extracting the curve features of the first calibration response curve and the second calibration response curve to obtain the first curve feature R1 and the second curve feature R2 includes:
Acquiring a protein reaction curve formula of the first calibration reaction curve and the second calibration reaction curve, wherein the protein reaction curve formula comprises:
V=F(t)，
wherein T is more than or equal to 0 and less than or equal to T, T is a real number, T is sampling time, V is a voltage value obtained by sampling, and T is sampling whole-course time;
extracting parameter characteristics between different two points on a protein reaction curve of the first calibration reaction curve as a first curve characteristic R1;
and extracting parameter characteristics between different two points on the protein reaction curve of the second calibration reaction curve as the second curve characteristics R2.
In an embodiment, the obtaining of the parameter feature includes:
calculating the voltage difference of different two points on the protein reaction curve to obtain a voltage difference D, wherein the calculation formula of the voltage difference D comprises:
D=F(t1)-F（t2），
wherein T1 and T2 are sampling time of two points on the protein reaction curve, and T1 is more than or equal to 0 and less than or equal to T p T2 is more than or equal to 0 and less than or equal to T, t1 is not equal to T2, D is a voltage difference value, and T is sampling whole-course time;
taking the voltage difference D as a first curve characteristic R1 or a second curve characteristic R2;
or, calculating the area between different two points on the protein reaction curve to obtain the area S between the two points, wherein the calculation formula of the area S between the two points comprises:
，
Wherein S is the area between different two points on the protein reaction curve, T1 is more than or equal to 0 and less than or equal to T, T2 is more than or equal to 0 and less than or equal to T, t1 is not equal to T2, and T is the sampling whole-course time;
and taking the area S between the two points as the first curve characteristic R1 or the second curve characteristic R2.
In an embodiment, the obtaining the calibration coefficient of the protein detection apparatus to be calibrated according to the first curve feature R1, the second curve feature R2, the first test curve feature rb1 and the second test curve feature rb2 includes:
obtaining the curve calibration slope Kb according to a curve calibration slope formula, the curve calibration slope formula comprising:
Kb=（rb2-rb1）/（R2-R1），
wherein rb1 is a first test curve characteristic value, rb2 is a second test curve characteristic value, R1 is a first curve characteristic value, R2 is a second curve characteristic value, and Kb is a curve calibration slope value;
obtaining the curve calibration intercept Bb according to a curve calibration intercept formula comprising:
Bb=（rb1×R2-R1×rb2）/（R2-R1）；
wherein rb1 is a first test curve characteristic value, rb2 is a second test curve characteristic value, R1 is a first curve characteristic value, R2 is a second curve characteristic value, and Bb is a curve calibration intercept value.
In one embodiment, the obtaining of the mathematical model of protein response comprises:
Obtaining N C-reactive protein body fluid samples S arranged according to a preset known concentration gradient 1 ,S 2 ,…，S i ,…,S N The method comprises the steps of carrying out a first treatment on the surface of the Wherein the protein concentration value of the ith C-reactive protein body fluid sample is CS i And 0 is<CS 1 <CS 2 <…<CS i <…<CS N ，1≤i≤N；
Acquiring a C protein response curve of each body fluid sample on a protein detection target machine, and extracting a curve characteristic value r of the protein response curve of each body fluid sample 1 ,r 2 ,…，r i ,…,r N , 1≤i≤N；
Establishing a mathematical function corresponding relation between the curve characteristic value of the protein response curve of each body fluid sample and the protein concentration of the body fluid sample corresponding to the curve characteristic value; wherein the characteristic value r of the protein response curve of the ith body fluid sample is calculated i Protein concentration CS of the body fluid sample corresponding to the protein concentration CS i Establishing a mathematical function corresponding relation, wherein i is more than or equal to 1 and less than or equal to N;
obtaining the mathematical model of the body fluid reaction, wherein the formula comprises:
r=Fs(c)，
wherein c is more than or equal to 0 and less than or equal to CS, c is a protein concentration value of the body fluid sample, and r is a curve characteristic value of a protein reaction curve of the body fluid sample.
According to a second aspect, in one embodiment there is provided a method of detecting a specific protein response comprising:
calibrating the protein detection apparatus according to the calibration method of the first aspect;
protein detection is carried out on a body fluid sample to be detected so as to obtain a specific protein reaction curve;
Extracting curve characteristics Rb of the specific protein reaction curve;
correcting the curve characteristic Rb according to a curve characteristic correction formula of the protein detection device to obtain a corrected curve characteristic Rb', wherein the curve characteristic correction formula comprises:
Rb′=Kb×Rb+Bb，
wherein Rb' is the curve characteristic value after obtaining the correction, kb is the curve characteristic value of the specific protein reaction curve, kb is the curve calibration slope value, and Bb is the curve calibration intercept value;
inputting the curve characteristic Rb' into the protein reaction mathematical model to obtain a protein concentration value output by the protein reaction mathematical model, and outputting the protein concentration value as a protein concentration value of the body fluid sample to be detected.
In one embodiment, the method further comprises:
the body fluid sample to be tested comprises a blood sample;
when the body fluid sample to be detected is a blood sample, performing HCT detection on the blood sample;
and carrying out HCT correction on the protein concentration value output by the protein reaction mathematical model, and outputting the protein concentration value after HCT correction as a C-reaction protein concentration value of the blood sample.
According to a third aspect, an embodiment provides a protein detection apparatus, comprising scaling means for scaling the protein detection apparatus; the calibration device comprises a protein detection module, a data post-processing module and a storage module;
The protein detection module is used for measuring protein response curves of a first calibration sample and a second calibration sample on the protein detection device to be calibrated so as to obtain the first calibration response curve and the second calibration response curve; the protein concentration value C1 and the protein concentration value C2 of the first calibration sample and the second calibration sample are known, and the protein concentration value C1 of the first calibration sample is greater than zero and less than the protein concentration value C2 of the second calibration sample;
the data post-processing module is used for respectively extracting curve characteristics of the first calibration reaction curve and the second calibration reaction curve to obtain a first curve characteristic R1 and a second curve characteristic R2; inputting a protein concentration value C1 of the first calibration sample into a protein reaction mathematical model with the curve characteristic of a protein reaction curve related to the protein concentration so as to obtain a first test curve characteristic rb1 output by the protein reaction mathematical model; the data post-processing module is further used for inputting a protein concentration value C2 of the second calibration sample into the protein reaction mathematical model to obtain a second test curve characteristic rb2 output by the protein reaction mathematical model; the data post-processing module is further used for acquiring a calibration coefficient of the protein detection device to be calibrated according to the first curve characteristic R1, the second curve characteristic R2, the first test curve characteristic rb1 and the second test curve characteristic rb2; the calibration coefficients of the protein detection device comprise a curve calibration slope Kb and a curve calibration intercept Bb;
The storage module is used for taking the acquired calibration coefficient as a protein detection calibration coefficient of the protein detection device and storing the calibration coefficient.
According to the calibration method of the protein detection apparatus of the above embodiment, first, protein response curves of a first calibration sample and a second calibration sample are measured on the protein detection apparatus to be calibrated, so as to obtain the first calibration response curve and the second calibration response curve. Then, a first curve characteristic R1 and a second curve characteristic R2 of the first calibration reaction curve and the second calibration reaction curve are respectively extracted. And inputting the protein concentration value C1 and the protein concentration value C2 of the first calibration sample and the second calibration sample into a protein reaction mathematical model to obtain a first test curve characteristic rb1 and a second test curve characteristic rb2, and further obtaining calibration coefficients according to the first curve characteristic R1, the second curve characteristic R2 and the second test curve characteristic rb2 so as to realize calibration. The calibration coefficients of the protein detection device are obtained through the test curve feature rb1 and the test curve feature rb2 obtained by extracting the curve feature R1, the curve feature R2 and the mathematical model, so that the calibration of the protein detection device is quicker and more accurate.
Drawings
FIG. 1 is a schematic diagram of the principle of nephelometry;
FIG. 2 is a schematic illustration of a specific protein response curve;
FIG. 3 is a schematic diagram of the principle of hematocrit measurement;
FIG. 4 is a schematic diagram of a frame of a specific protein response detection system in one embodiment;
FIG. 5 is a schematic diagram of a process for assigning a sample of known concentration in one embodiment;
FIG. 6 is a schematic flow chart of a mathematical model of serum response obtained in one embodiment;
FIG. 7 is a schematic diagram of a calibration sample assignment flow in one embodiment;
FIG. 8 is a flow chart of a calibration method of a protein detection apparatus according to an embodiment;
FIG. 9 is a schematic diagram of a calibration device according to another embodiment;
FIG. 10 is a flow chart of a method for calibrating a protein detection apparatus according to another embodiment;
FIG. 11 is a flow chart of a specific protein reaction detection method according to another embodiment.
Detailed Description
The invention will be described in further detail below with reference to the drawings by means of specific embodiments. Wherein like elements in different embodiments are numbered alike in association. In the following embodiments, numerous specific details are set forth in order to provide a better understanding of the present application. However, one skilled in the art will readily recognize that some of the features may be omitted, or replaced by other elements, materials, or methods in different situations. In some instances, some operations associated with the present application have not been shown or described in the specification to avoid obscuring the core portions of the present application, and may not be necessary for a person skilled in the art to describe in detail the relevant operations based on the description herein and the general knowledge of one skilled in the art.
Furthermore, the described features, operations, or characteristics of the description may be combined in any suitable manner in various embodiments. Also, various steps or acts in the method descriptions may be interchanged or modified in a manner apparent to those of ordinary skill in the art. Thus, the various orders in the description and drawings are for clarity of description of only certain embodiments, and are not meant to be required orders unless otherwise indicated.
The numbering of the components itself, e.g. "first", "second", etc., is used herein merely to distinguish between the described objects and does not have any sequential or technical meaning. The terms "coupled" and "connected," as used herein, are intended to encompass both direct and indirect coupling (coupling), unless otherwise indicated.
Referring to fig. 1, a schematic diagram of a nephelometry principle is shown, which includes a light source, a reaction cup and an optical signal receiver, wherein the reaction liquid is contained in the reaction cup, the light source vertically irradiates the reaction cup, irradiates the microspheres in the reaction liquid through the wall of the reaction cup, scatters, and the scattered light enters the wall of the reaction cup from an angle other than 90 degrees (with the side wall of the reaction cup), passes through the wall of the reaction cup to enter air, and finally reaches the optical signal receiver. The scattered light passes through three different media of the reaction liquid, the reaction cup and the air in the whole process, and the scattered light is refracted in the propagation process because the scattered light passes through the three media from a direction other than 90 degrees. In the whole reaction system, the refractive indexes of the reaction cup and the air are fixed, and the refractive indexes of the reaction liquid of different samples to be tested are different due to the fact that components of a serum sample, a plasma sample or a blood sample are added into the reaction liquid, so that the optical signal intensities received by the optical signal receiver are different, and the detection results of C-reactive proteins of three homologous serum samples, plasma samples and blood samples on the same detection instrument are inconsistent.
The specific protein reaction detection principle is that antigen and antibody react in specific electrolyte solution to form immune composite particles fast, so that the turbidity of the reaction solution appears, and the turbidity gradually increases as the composite particles polymerize with the passage of time. In nephelometry, the intensity of the optical signal received by the optical signal receiver also increases over time. The C-reactive protein is one of the specific protein detection items.
Referring to fig. 2, a specific protein response curve is shown, the horizontal axis of the coordinates is sampling time, the vertical axis of the coordinates is voltage, and the time-dependent variation curve of the intensity of the optical signal received by the optical signal receiver is also called a specific protein response curve, which is generally expressed by a mathematical function formula, and includes:
V=F（t），
wherein 0 is less than or equal to t, V is voltage, and t is sampling time.
Please refer to fig. 3, which is a schematic diagram of the principle of measuring the hematocrit, including a detector, wherein the principle of measurement is to immerse a small hole in an electrolyte solution, and to connect a constant current power supply to two ends of the small hole, when a tiny particle passes through the small hole, the voltage at two ends of the small hole changes, and the larger the volume of the tiny particle, the larger the change of the voltage (the larger the voltage pulse value). The number of particles in the whole collection time can be obtained by counting the number of pulses in the collection time, and the total volume of all particles passing through the small holes can be obtained by summing the values of each pulse. According to this principle, the measurement of HCT can be accomplished by mixing blood in a diluent (a reagent having conductivity and having physiological saline properties) and then passing through a small hole with electrodes at both ends.
HCT: hematocrit (total volume).
In the prior art, calibration of the C-reactive protein is generally performed by selecting calibration samples with 4 to 5 different concentration points (the concentration of each calibration sample is known), inputting the target value (concentration) C of each calibration sample into an instrument, and then measuring each calibration sample to obtain the curve characteristic r of the reaction curve of each calibration sample. And then establishing a mathematical function relation r=f (c) of r and c, and completing the calibration. The disadvantage is that all calibration samples need to be measured, and more C-reactive protein reagent needs to be consumed. The second disadvantage is that the calibration process takes a long time, typically half an hour. If the scaling fails, it takes longer.
In the embodiment of the invention, firstly, protein reaction curves of a first calibration sample and a second calibration sample are measured on a protein detection device to be calibrated, so as to obtain the first calibration reaction curve and the second calibration reaction curve. Then, a first curve characteristic R1 and a second curve characteristic R2 of the first calibration reaction curve and the second calibration reaction curve are respectively extracted. And inputting the protein concentration value C1 and the protein concentration value C2 of the first calibration sample and the second calibration sample into a protein reaction mathematical model to obtain a first test curve characteristic rb1 and a second test curve characteristic rb2, and further obtaining calibration coefficients according to the first curve characteristic R1, the second curve characteristic R2 and the second test curve characteristic rb2 so as to realize calibration. The calibration coefficients of the protein detection device are obtained through the test curve feature rb1 and the test curve feature rb2 obtained by extracting the curve feature R1, the curve feature R2 and the mathematical model, so that the calibration of the protein detection device is quicker and more accurate.
Embodiment one:
referring to fig. 4, a schematic diagram of a specific protein reaction detection system according to an embodiment includes a sample 1 with a known concentration, a protein detection target 2, a calibration sample 3, a protein detection device 4, a sample 5 to be tested, and an output device 6. The known concentration sample 1 includes C-reactive protein samples of a plurality of concentration gradients, and the concentration is known, and the kind of the known concentration sample 1 includes serum, plasma, blood, or the like. The protein detection target machine 2 is used for assigning a value to each sample of each sample 1 with known concentration, wherein the assigned value comprises a protein response characteristic curve, a curve characteristic value and a protein concentration value of each sample. The assigned sample is used as a calibration sample 3 to calibrate the protein detection device 4. The calibrated protein detection device 4 detects C-reactive protein of the sample 5 to be detected, and the detection result is output through the output device 6.
Referring to fig. 5, a schematic flow chart of a known concentration sample assignment process in an embodiment is shown, where the protein detection target machine sets a protein detection gain of the protein detection target machine before assigning a value to the known concentration sample, and obtains the mean voltage Vm of a blank sample protein response curve of the protein detection target machine when the gain is obtained. In one embodiment, the gain of the protein detection target for the C-reactive protein detection is in the range of 0-255. The average voltage Vm obtaining process includes:
Setting the protein detection gain of the protein detection target drone to 125, setting the detection state of the protein detection target drone to be a whole blood CRP mode, and carrying out blank sample measurement by the protein detection target drone by absorbing air or pure water so as to obtain a protein response curve of the blank sample. The method comprises the steps of obtaining the mean voltage Vm of a blank sample protein reaction curve, wherein the calculation formula of the mean voltage is as follows:
，
wherein Vm is the average voltage value of the protein response curve of the blank sample, and T is the whole-course measurement time of the blank sample.
And storing the mean voltage Vm of the blank sample protein response curve into the configuration parameters of the target machine. In one embodiment, the average voltage Vm of the blank sample protein reaction curve is copied or burned to a reagent information card of the C-reactive protein or stored in bar code or two-dimensional code information of a kit of the C-reactive protein.
After setting the protein detection gain of the protein detection target machine, the process of assigning a value to a sample with a known concentration by the protein detection target machine comprises the following steps:
step 110, a reaction mathematical model is obtained.
In one embodiment, the obtained mathematical reaction model includes a serum reaction mathematical model, a plasma reaction mathematical model, and a blood reaction mathematical model.
Please refer to fig. 6, which is a flow chart illustrating a method for obtaining a mathematical model of serum reaction according to an embodiment, wherein the method for obtaining the mathematical model of serum reaction comprises:
In step 111, a plurality of concentration gradients of serum samples are obtained.
Obtaining N C-reactive protein serum samples S arranged according to a preset known concentration gradient 1 ,S 2 ,…，S i ,…,S N The method comprises the steps of carrying out a first treatment on the surface of the Wherein the protein concentration value of the ith C-reactive protein serum sample is CS i And 0 is<CS 1 <CS 2 <…<CS i <…<CS N I is more than or equal to 1 and less than or equal to N, and i and N are natural numbers.
In one embodiment, 16 serum samples are obtained with protein C reaction concentrations of 1,2,5,10,15,20,30,40,60,80,100,110,120,150,160,200mg/L in order.
Step 112, obtaining a protein response curve of each serum sample.
Each serum sample is measured on a protein detection target to obtain a specific protein response profile for each serum sample. A specific protein response curve formulation for a serum sample comprising:
V S =F(t S )，
wherein t is 0.ltoreq.t S ≤T S ，t S E real number, t S For sampling time, V S For sampling the obtained voltage value, T S For sampling the full time.
At step 113, the characteristics of each protein response curve are obtained.
Extracting parameter characteristics between different points on a specific protein reaction curve of a serum sample as curve characteristics R S 。
In one embodiment, the voltage difference between two different points on a specific protein reaction curve of a serum sample is calculated to obtain a voltage difference D S Voltage difference D S The calculation formula of (1) comprises:
D S =F(t S1 )-F（t S2 ），
Wherein t is S1 And t S2 Is the sampling time of two points on the specific protein reaction curve, and t is more than or equal to 0 S1 ≤T S ，0≤t S2 ≤T S ，t S1 ≠t S2 ,D S Is the voltage difference, T S For sampling the full time.
Difference of voltage D S Curve characteristics R of a specific protein response curve as a serum sample S 。
In one embodiment, the voltage difference D S Take t S1 = T S And t is S2 Value at=0.
In one embodiment, the area between two different points on a specific protein reaction curve of a serum sample is calculated to obtain the area S between the two points S Area between two points S S The calculation formula of (1) comprises:
，
wherein S is S Is the area between different points on a specific protein reaction curve of a serum sample, and is more than or equal to 0 and less than or equal to t S1 ≤T S ，0≤t S2 ≤T S ，t S1 ≠t S2 , t S1 And t S2 Is the sampling time, T, of two points on a specific protein reaction curve S For sampling the full time.
The area S between two points S Curve characteristics R of a specific protein response curve as a serum sample S 。
In one embodiment, the area between two points S S Taking t S1 = T S And t is S2 Value at=0.
Step 114, a mathematical model of the serum response is obtained.
In one embodiment, the formulation of the mathematical model of the serum response comprises:
r S =F S (c S )，
wherein, c is more than or equal to 0 S ≤C SM ，c S Is the concentration value of serum C-reactive protein, C SM Is the maximum value of the concentration of the serum C-reactive protein. The mathematical model of the serum reaction represents the characteristic value r of the specific protein reaction curve of the serum sample S Concentration value of protein reactive with serum C C S For example, r is as follows S =R S The formula of the serum reaction mathematical model is brought into, and the curve characteristic R is output S Corresponding serum C-reactive protein concentration value C S 。
In one embodiment, a cubic spline interpolation is used to obtain a characteristic value r of a specific protein response curve of a serum sample S Concentration value of protein reactive with serum C C S A mathematical model of the serum response of the correspondence of (a).
The plasma reaction mathematical model and the blood reaction mathematical model were obtained by the same method as described above. Wherein, the formula of the mathematical model of the plasma reaction comprises:
r P =F P (c P )，
wherein, c is more than or equal to 0 P ≤C PM ，c P Is the concentration value of plasma C-reactive protein, C PM Is the maximum value of the concentration of the plasma C-reactive protein. The mathematical model of the plasma reaction represents the characteristic value r of the specific protein reaction curve of the plasma sample P Concentration of protein C reactive with plasma C P Corresponding relation of (e.g. will r) P =R P The formula of the plasma reaction mathematical model is carried in, and the curve characteristic R of the plasma specific protein reaction curve is output P Corresponding plasma C-reactive protein concentration value C P 。
The formula of the mathematical model of the blood reaction includes:
r b =F b (c b ′)，
wherein, c is more than or equal to 0 b ′≤C bM ，c b ' is the concentration value of C-reactive protein in blood, C bM Is the maximum value of the concentration of the blood C-reactive protein. The blood reaction mathematical model represents the characteristic value r of a specific protein reaction curve of a blood sample b Protein concentration value C in response to blood C b ' correspondence, e.g., r b =R b The formula of the blood reaction mathematical model is carried in, and the curve characteristic R of the blood specific protein reaction curve is output b Corresponding C-reactive protein concentration value C b ′。
Step 120, calibrate sample assignment.
Referring to fig. 7, a schematic diagram of a assignment flow of calibration samples in an embodiment, a method for assigning calibration samples includes:
step 121, configuring a plurality of calibration samples of concentration gradients.
M C-reactive protein calibration samples arranged according to a preset known concentration gradient are configured. Wherein the C-reactive protein calibration sample comprises a serum C-reactive protein calibration sample, a plasma C-reactive protein calibration sample or a serum C-reactive protein calibration sample.
Step 122, a protein response curve is obtained for each calibration sample.
In protein detection targetsMeasuring each calibration sample on-board to obtain a specific protein response curve C of each calibration sample 1 、C 2 、…、C j 、…、C M ，0<j is less than or equal to M, and j and M are natural numbers. A specific protein response curve formula for a calibration sample comprising:
V=F J (t)，
wherein T is more than or equal to 0 and less than or equal to T, T is a real number, T is sampling time, V is a voltage value obtained by sampling, and T is sampling whole-course time.
Step 123, obtain each protein response curve characteristic.
Extracting parameter characteristics between different points on a specific protein reaction curve of each calibration sample as curve characteristics r, and obtaining r of each calibration sample 1 、r 2 、…、r j 、…、r M ，0<j is less than or equal to M, and j and M are natural numbers.
In one embodiment, the voltage difference between different points on a specific protein reaction curve of a calibration sample is calculated to obtain a voltage difference D, and the calculation formula of the voltage difference D includes:
D=F(t 1 )-F（t 2 ），
wherein t is 1 And t 2 Is the sampling time of two points on the specific protein reaction curve, and t is more than or equal to 0 1 ≤T，0≤t 2 ≤T，t 1 ≠t 2 D is the voltage difference, and T is the sampling whole time.
The voltage difference D is taken as the curve characteristic r of the specific protein response curve of the serum sample.
And step 124, obtaining a concentration value according to the reaction mathematical model.
R of the calibration sample 1 、r 2 、…、r j 、…、r M The reaction mathematical model was carried over to obtain a C-reactive protein concentration value representing each calibration sample.
Step 125, assign a value to the calibration sample.
And inputting the information of each calibration sample into a reagent card, a bar code or a written instruction of the corresponding calibration sample, and completing the assignment of the calibration sample. The information of the calibration sample includes information such as C-reactive protein concentration.
Referring to fig. 8, a flow chart of a calibration method of a protein detection apparatus according to an embodiment is shown, where the calibration method of the protein detection apparatus includes:
At step 210, information of the calibration sample is entered.
The instrument is adjusted to the calibration interface and then a calibration sample C is taken j The information of the calibration sample is input into the protein detection device to be calibrated by scanning a bar code or swiping a card or manually inputting a target value in a specification.
Step 220, a specific protein response curve of the calibration sample is obtained.
The device is then used to detect the calibration sample, resulting in a specific protein response curve of the calibration sample on the protein detection device.
In step 230, the response curve characteristics of the calibration sample are obtained.
In one embodiment, the global voltage difference D j Response curve characteristic r as a check sample j . Wherein the voltage difference D is taken as t 1 T and T S Values at=0, i.e.:
D j =F j (T)-F j (0)。
all calibration samples are sequentially used for acquiring the response curve characteristic r according to the steps 210 to 230 1 、r 2 、…、r j 、…、r M ，0<j is less than or equal to M, and j and M are natural numbers.
Step 240, obtain a reaction mathematical model.
Obtaining a reaction mathematical model of the curve characteristic of the calibration sample and the C protein reaction concentration value of the calibration sample by applying a cubic spline interpolation method, wherein the formula of the reaction mathematical model comprises:
r =F (c)，
wherein C is more than or equal to 0 and less than or equal to C M C is the concentration value of serum C-reactive protein, C M Is the maximum value of the concentration of the serum C-reactive protein; the serum reaction mathematical model represents the corresponding relation between the characteristic value r of a specific protein reaction curve of a serum sample and the concentration value C of serum C-reactive protein 。
Step 250, store the reaction mathematical model.
And storing the obtained reaction mathematical model in a specific protein detection device to be calibrated, and completing calibration.
Referring to fig. 9, a schematic structural diagram of a calibration device according to another embodiment is shown, in which the protein detection device includes a calibration device for calibrating the protein detection device. The calibration device comprises a protein detection module 11, a data post-processing module 12 and a storage module 13.
The protein detection module 11 is configured to measure protein response curves of a first calibration sample and a second calibration sample on a protein detection device to be calibrated, so as to obtain the first calibration response curve and the second calibration response curve. Wherein the protein concentration value C1 and the protein concentration value C2 of the first calibration sample and the second calibration sample are known, and the protein concentration value C1 of the first calibration sample is greater than zero and less than the protein concentration value C2 of the second calibration sample.
The data post-processing module 12 is configured to extract curve features of the first calibration reaction curve and the second calibration reaction curve, respectively, so as to obtain a first curve feature R1 and a second curve feature R2, and input a protein concentration value C1 of the first calibration sample into a protein reaction mathematical model that is related to the curve feature of the protein reaction curve and the protein concentration, so as to obtain a first test curve feature rb1 output by the protein reaction mathematical model. The data post-processing module 12 is further configured to input the protein concentration value C2 of the second calibration sample into the protein reaction mathematical model, so as to obtain a second test curve feature rb2 output by the protein reaction mathematical model. The data post-processing module 12 is further configured to obtain a calibration coefficient of the protein detection device to be calibrated according to the first curve feature R1, the second curve feature R2, the first test curve feature rb1 and the second test curve feature rb2. The calibration coefficients of the protein detection apparatus include a curve calibration slope Kb and a curve calibration intercept Bb.
The storage module 13 is used for taking the acquired calibration coefficient as a protein detection calibration coefficient of the protein detection device and storing the calibration coefficient.
In an embodiment of the present application, first, protein reaction curves of a first calibration sample and a second calibration sample are measured on a protein detection device to be calibrated, so as to obtain the first calibration reaction curve and the second calibration reaction curve. Then, a first curve characteristic R1 and a second curve characteristic R2 of the first calibration reaction curve and the second calibration reaction curve are respectively extracted. And inputting the protein concentration value C1 and the protein concentration value C2 of the first calibration sample and the second calibration sample into a protein reaction mathematical model to obtain a first test curve characteristic rb1 and a second test curve characteristic rb2, and further obtaining calibration coefficients according to the first curve characteristic R1, the second curve characteristic R2 and the second test curve characteristic rb2 so as to realize calibration. The calibration coefficients of the protein detection device are obtained through the test curve feature rb1 and the test curve feature rb2 obtained by extracting the curve feature R1, the curve feature R2 and the mathematical model, so that the calibration of the protein detection device is quicker and more accurate.
The embodiment of the application discloses a specific protein reaction detection system, which comprises a known concentration sample 1, a protein detection target machine 2, a calibration sample 3, a protein detection device 4, a sample to be detected 5 and an output device 6. The characteristic of the specific protein reaction curve of the calibration samples with different concentrations is obtained to obtain the concentration value of the C-reactive protein of the samples with different concentrations, so that the specific protein detection device is not only suitable for the C-reactive protein, but also suitable for Serum Amyloid A (SAA), and the specific protein detection device can be used for measuring blood samples and serum and plasma samples when the blood cell-C-reactive protein joint inspection integrated machine is used for measuring the specific protein samples, thereby meeting the diversified requirements of a user side on sample measurement.
Embodiment two:
referring to fig. 10, a flow chart of a method for calibrating a protein detection apparatus according to another embodiment is shown, where the method for calibrating a protein detection apparatus includes:
in step 310, the protein detection apparatus detects preparation.
Firstly, a protein detection device to be calibrated (such as an instrument at a client) is set, and a bar code (two-dimensional code) of a C-reactive protein kit is scanned by a card swiping (C-reactive protein reagent card swiping) or a code scanning gun, so that the average voltage Vm of a blank sample reaction curve of a protein detection target machine and a protein reaction mathematical model of the protein detection target machine are stored in the device. Adjusting the instrument to a C-reactive protein gain calibration interface for performing C-reactive protein channel gain calibration to set a protein detection gain of a protein detection device to be calibrated to a calibration gain g, wherein the gain calibration flow comprises:
the gain of the protein detection apparatus is set to a first preset gain g1, and in one embodiment, the first preset gain g1 is set to 100. And measuring a protein response curve of the third calibration sample when the gain is the first preset gain g1 on the protein detection device to be calibrated so as to obtain a third calibration response curve. In one embodiment, the third calibration sample is a blank sample, i.e. air or pure water is inhaled to perform the C-reactive protein detection, so as to obtain a protein response curve of the blank sample. The mean voltage Vmg1 of the third calibration reaction curve is obtained. And obtaining the mean voltage Vmg1 of the protein reaction curve of the blank sample according to a calculation formula of the mean voltage.
The gain of the protein detection apparatus is set to a second preset gain g2, and in one embodiment, the second preset gain g2 is set to 150. And measuring a protein response curve of the third calibration sample when the gain is a second preset gain g2 on the protein detection device to be calibrated so as to obtain a fourth calibration response curve. In one embodiment, the fourth calibration sample is a blank sample, i.e. air or pure water is inhaled to perform the C-reactive protein detection, so as to obtain a protein response curve of the blank sample. The mean voltage Vmg2 of the fourth calibration reaction curve is obtained.
Obtaining a calibration gain g according to a gain calibration formula, wherein the gain calibration formula comprises:
g =[g2*（Vm-Vmg1）+ g1*(Vmg2-Vm）]/( Vmg2-Vmg1)，
wherein g1 is not equal to g2, g is a calibration gain, g1 is a first preset gain, g2 is a second preset gain, vmg1 is a mean voltage of a third calibration reaction curve, vmg2 is a mean voltage of a fourth calibration reaction curve, and Vm is a mean voltage value of a blank sample protein reaction curve of a target machine of a preset protein detection device. In one embodiment, the average voltage Vm may be pre-stored in the protein detection device, or obtained from a reagent information card of the C-reactive protein or bar code or two-dimensional code information of a kit for storing the C-reactive protein. The protein detection gain of the protein detection apparatus to be scaled is set to the calibration gain g.
In one embodiment, a protein response curve of a fifth calibration sample is obtained when the protein detection gain is set to the calibration gain g to obtain a fifth calibration response curve. In one embodiment, the fifth calibration sample is a blank sample, i.e. air or pure water is inhaled to perform the C-reactive protein detection, so as to obtain a protein response curve of the blank sample. And acquiring a curve characteristic R0 of the fifth calibration reaction curve, and storing the acquired R0 into a protein detection device to be calibrated. In one embodiment, the obtained curve characteristic R0 is a global voltage difference D0 obtained from the fifth calibration reaction curve, and the obtained formula of the global voltage difference is:
D=F(T)-F(0)，
wherein D is the whole-course voltage difference value, and T is the whole-course measurement time.
At step 320, a protein response curve is obtained.
And setting a protein detection device to be calibrated at a calibration interface of the C-reactive protein, and inputting information of the first calibration sample and the second calibration sample. In one embodiment, the concentration information of the calibration sample is entered into the instrument by scanning the bar code or swipe a card (card in the calibration sample kit) of the calibration sample, or manually entering the target value in the specification.
Measuring protein response curves of the first calibration sample and the second calibration sample on a protein detection device to be calibrated to obtain the first calibration response curve and the second calibration response curve. Wherein the protein concentration value C1 and the protein concentration value C2 of the first calibration sample and the second calibration sample are known, and the protein concentration value C1 of the first calibration sample is greater than zero and less than the protein concentration value C2 of the second calibration sample.
In one embodiment, the protein detection apparatus to be calibrated uses nephelometry or turbidimetry to obtain a protein response curve.
In one embodiment, the protein detection of the protein detection device comprises a C-reactive protein detection and/or a serum amyloid A detection.
Step 330, obtain the curve characteristics.
And respectively extracting curve characteristics of the first calibration reaction curve and the second calibration reaction curve to obtain a first curve characteristic R1 and a second curve characteristic R2.
The curve characteristic of the first calibration reaction curve is extracted to obtain a first curve characteristic R1. And extracting the curve characteristic of the second calibration reaction curve to obtain a second curve characteristic R2.
In one embodiment, a protein response curve formula for a first calibration response curve and a second calibration response curve is obtained, the protein response curve formula comprising:
V=F(t)，
wherein T is more than or equal to 0 and less than or equal to T, T is a real number, T is sampling time, V is a voltage value obtained by sampling, and T is sampling whole-course time;
extracting parameter characteristics between different two points on a protein reaction curve of a first calibration reaction curve as a first curve characteristic R1;
and extracting parameter characteristics between different two points on the protein reaction curve of the second calibration reaction curve as second curve characteristics R2.
In one embodiment, the obtaining of the parameter feature includes:
calculating the voltage difference of different two points on the protein reaction curve to obtain a voltage difference D, wherein a calculation formula of the voltage difference D comprises:
D=F(t1)-F（t2），
wherein T1 and T2 are sampling time of two points on the protein reaction curve, and T1 is more than or equal to 0 and less than or equal to T p T2 is more than or equal to 0 and less than or equal to T, t1 is not equal to T2, D is a voltage difference value, and T is sampling whole-course time;
taking the voltage difference D as a first curve characteristic R1 or a second curve characteristic R2;
in one embodiment, the calculation formula for calculating the area between two different points on the protein reaction curve to obtain the area S between the two points includes:
，
wherein S is the area between different two points on the protein reaction curve, T1 is more than or equal to 0 and less than or equal to T, T2 is more than or equal to 0 and less than or equal to T, t1 is not equal to T2, and T is the sampling whole-course time;
the area S between the two points is used as a first curve characteristic R1 or a second curve characteristic R2.
In one embodiment, the obtaining of the first curve characteristic R1 or the second curve characteristic R2 is obtaining the global voltage difference D2 of the second calibration reaction curve.
Step 340, inputting a mathematical model of protein response.
The protein concentration value C1 of the first calibration sample is input into a protein reaction mathematical model of which the curve characteristic of a protein reaction curve is related to the protein concentration, so as to obtain a first test curve characteristic rb1 output by the protein reaction mathematical model. Inputting the protein concentration value C2 of the second calibration sample into a protein reaction mathematical model to obtain a second test curve characteristic rb2 output by the protein reaction mathematical model.
In one embodiment, the obtaining of the mathematical model of protein response comprises:
obtaining N C-reactive protein body fluid samples S arranged according to a preset known concentration gradient 1 ,S 2 ,…，S i ,…,S N The method comprises the steps of carrying out a first treatment on the surface of the Wherein the protein concentration value of the ith C-reactive protein body fluid sample is CS i And 0 is<CS 1 <CS 2 <…<CS i <…<CS N ，1≤i≤N；
Acquiring a C protein response curve of each body fluid sample on a protein detection target machine, and extracting a curve characteristic value r of the protein response curve of each body fluid sample 1 ,r 2 ,…，r i ,…,r N , 1≤i≤N；
Establishing a mathematical function corresponding relation between the curve characteristic value of the protein response curve of each body fluid sample and the protein concentration of the body fluid sample corresponding to the curve characteristic value; wherein the characteristic value r of the protein response curve of the ith body fluid sample is calculated i Protein concentration CS of the body fluid sample corresponding to the protein concentration CS i Establishing mathematical function correspondenceThe relation is that i is more than or equal to 1 and N is more than or equal to N;
obtaining a mathematical model of body fluid reaction, wherein the formula comprises:
r=Fs(c)，
wherein c is more than or equal to 0 and less than or equal to CS, c is a protein concentration value of the body fluid sample, and r is a curve characteristic value of a protein reaction curve of the body fluid sample.
In step 350, calibration coefficients are obtained.
And acquiring the calibration coefficient of the protein detection device to be calibrated according to the first curve characteristic R1, the second curve characteristic R2, the first test curve characteristic rb1 and the second test curve characteristic rb 2. The calibration coefficients of the protein detection apparatus include a curve calibration slope Kb and a curve calibration intercept Bb. And taking the acquired calibration coefficient as a protein detection calibration coefficient of the protein detection device so as to realize calibration.
In one embodiment, obtaining calibration coefficients of a protein detection device to be calibrated according to the first curve feature R1, the second curve feature R2, the first test curve feature rb1 and the second test curve feature rb2 includes:
obtaining a curve calibration slope Kb according to a curve calibration slope formula, the curve calibration slope formula comprising:
Kb=（rb2-rb1）/（R2-R1），
wherein rb1 is a first test curve characteristic value, rb2 is a second test curve characteristic value, R1 is a first curve characteristic value, R2 is a second curve characteristic value, and Kb is a curve calibration slope value.
Obtaining a curve calibration intercept Bb according to a curve calibration intercept formula, the curve calibration intercept formula comprising:
Bb=（rb1×R2-R1×rb2）/（R2-R1），
wherein rb1 is a first test curve characteristic value, rb2 is a second test curve characteristic value, R1 is a first curve characteristic value, R2 is a second curve characteristic value, and Bb is a curve calibration intercept value.
In an embodiment of the present application, a two-point scaling method is used. Namely, only two calibration samples with known concentrations are needed to complete the calibration process of the C-reactive protein. The reagent consumption and the calibration time are reduced, the calibration cost is reduced, and the user experience is improved.
Embodiment III:
referring to fig. 11, a flow chart of a specific protein reaction detection method according to another embodiment is shown, where the specific protein reaction detection method includes:
And 410, scaling.
The protein detection apparatus was calibrated according to the method described in implementation two.
Step 420, obtaining a protein response curve.
Protein detection is carried out on a body fluid sample to be detected so as to obtain a specific protein response curve. In one embodiment the body fluid sample to be tested comprises a serum sample, a plasma sample and/or a blood sample.
At step 430, curve features are obtained.
And extracting the curve characteristic Rb of the specific protein reaction curve. In one embodiment, the curve characteristic Rb is the global voltage difference Db of the protein response curve.
Step 440, modifying the curve characteristics.
Correcting the curve characteristic Rb according to a curve characteristic correction formula of the protein detection device to obtain a corrected curve characteristic Rb', wherein the curve characteristic correction formula comprises:
Rb′=Kb×Rb+Bb，
wherein Rb' is the curve characteristic value after obtaining the correction, kb is the curve characteristic value of the specific protein reaction curve, kb is the curve calibration slope value, and Bb is the curve calibration intercept value.
Step 450, inputting a mathematical model of protein response.
Inputting the curve characteristic Rb' into a protein reaction mathematical model to obtain a protein concentration value output by the protein reaction mathematical model, and outputting the protein concentration value as a protein concentration value of a body fluid sample to be detected.
In one embodiment, the specific protein response detection method further comprises:
in step 460, HCT measurements of the blood sample are obtained.
The body fluid sample to be tested comprises a blood sample.
When the body fluid sample to be detected is a blood sample, performing HCT detection on the blood sample to obtain a HCT detection value H of the blood sample b 。
In step 470, HCT correction is performed.
And carrying out HCT correction on the protein concentration value output by the protein reaction mathematical model, and outputting the protein concentration value after HCT correction as a C-reaction protein concentration value of the blood sample.
According to HCT detection value H C C-reactive protein concentration value C output by mathematical model of blood reaction b ' HCT correction is performed, including:
concentration value c of blood-specific protein reaction b ' input HCT correction formula to obtain concentration value C of C-reactive protein of blood sample b The HCT correction formula includes:
c b ″ =c b ′/（1-H b ），
wherein c b ' is the concentration value of C reaction protein, H b C is the measurement of hematocrit b "is the C-reactive protein assay value of a blood sample.
Those skilled in the art will appreciate that all or part of the functions of the various methods in the above embodiments may be implemented by hardware, or may be implemented by a computer program. When all or part of the functions in the above embodiments are implemented by means of a computer program, the program may be stored in a computer readable storage medium, and the storage medium may include: read-only memory, random access memory, magnetic disk, optical disk, hard disk, etc., and the program is executed by a computer to realize the above-mentioned functions. For example, the program is stored in the memory of the device, and when the program in the memory is executed by the processor, all or part of the functions described above can be realized. In addition, when all or part of the functions in the above embodiments are implemented by means of a computer program, the program may be stored in a storage medium such as a server, another computer, a magnetic disk, an optical disk, a flash disk, or a removable hard disk, and the program in the above embodiments may be implemented by downloading or copying the program into a memory of a local device or updating a version of a system of the local device, and when the program in the memory is executed by a processor.
The foregoing description of the invention has been presented for purposes of illustration and description, and is not intended to be limiting. Several simple deductions, modifications or substitutions may also be made by a person skilled in the art to which the invention pertains, based on the idea of the invention.
Claims (4)
1. A method for calibrating a protein detection apparatus, comprising:
measuring protein response curves of a first calibration sample and a second calibration sample on the protein detection device to be calibrated so as to obtain the first calibration response curve and the second calibration response curve; the protein concentration value C1 and the protein concentration value C2 of the first calibration sample and the second calibration sample are known, and the protein concentration value C1 of the first calibration sample is greater than zero and less than the protein concentration value C2 of the second calibration sample;
respectively extracting curve characteristics of the first calibration reaction curve and the second calibration reaction curve to obtain a first curve characteristic R1 and a second curve characteristic R2;
inputting a protein concentration value C1 of the first calibration sample into a protein reaction mathematical model of which the curve characteristic of a protein reaction curve is related to the protein concentration so as to obtain a first test curve characteristic rb1 output by the protein reaction mathematical model;
Inputting a protein concentration value C2 of the second calibration sample into the protein reaction mathematical model to obtain a second test curve characteristic rb2 output by the protein reaction mathematical model;
obtaining a calibration coefficient of the protein detection device to be calibrated according to the first curve characteristic R1, the second curve characteristic R2, the first test curve characteristic rb1 and the second test curve characteristic rb2; the calibration coefficients of the protein detection device comprise a curve calibration slope Kb and a curve calibration intercept Bb;
taking the acquired calibration coefficient as a protein detection calibration coefficient of the protein detection device so as to realize calibration;
the protein detection device to be calibrated acquires a protein reaction curve by using a scattering turbidimetry or a transmission turbidimetry;
and/or, the protein detection of the protein detection device comprises C-reactive protein detection and/or serum amyloid A detection;
the extracting the curve features of the first calibration reaction curve and the second calibration reaction curve to obtain a first curve feature R1 and a second curve feature R2 includes:
acquiring a protein reaction curve formula of the first calibration reaction curve and the second calibration reaction curve, wherein the protein reaction curve formula comprises:
V=F(t)，
Wherein T is more than or equal to 0 and less than or equal to T, T is a real number, T is sampling time, V is a voltage value obtained by sampling, and T is sampling whole-course time;
extracting parameter characteristics between different two points on a protein reaction curve of the first calibration reaction curve as a first curve characteristic R1;
extracting parameter characteristics between different two points on a protein reaction curve of the second calibration reaction curve as the second curve characteristics R2;
the obtaining of the parameter characteristics comprises the following steps:
calculating the voltage difference of different two points on the protein reaction curve to obtain a voltage difference D, wherein the calculation formula of the voltage difference D comprises:
D=F(t1)-F（t2），
wherein T1 and T2 are sampling time of two points on the protein reaction curve, and T1 is more than or equal to 0 and less than or equal to T p T2 is more than or equal to 0 and less than or equal to T, t1 is not equal to T2, D is a voltage difference value, and T is sampling whole-course time;
taking the voltage difference D as a first curve characteristic R1 or a second curve characteristic R2;
or, calculating the area between different two points on the protein reaction curve to obtain the area S between the two points, wherein the calculation formula of the area S between the two points comprises:
，
wherein S is the area between different two points on the protein reaction curve, T1 is more than or equal to 0 and less than or equal to T, T2 is more than or equal to 0 and less than or equal to T, t1 is not equal to T2, and T is the sampling whole-course time;
Taking the area S between the two points as the first curve characteristic R1 or the second curve characteristic R2;
the obtaining the calibration coefficient of the protein detection device to be calibrated according to the first curve feature R1, the second curve feature R2, the first test curve feature rb1 and the second test curve feature rb2 includes:
obtaining the curve calibration slope Kb according to a curve calibration slope formula, the curve calibration slope formula comprising:
Kb=（rb2-rb1）/（R2-R1），
wherein rb1 is a first test curve characteristic value, rb2 is a second test curve characteristic value, R1 is a first curve characteristic value, R2 is a second curve characteristic value, and Kb is a curve calibration slope value;
obtaining the curve calibration intercept Bb according to a curve calibration intercept formula comprising:
Bb=（rb1×R2-R1×rb2）/（R2-R1）；
wherein rb1 is a first test curve characteristic value, rb2 is a second test curve characteristic value, R1 is a first curve characteristic value, R2 is a second curve characteristic value, and Bb is a curve calibration intercept value;
the acquisition of the protein reaction mathematical model comprises the following steps:
obtaining N C-reactive protein body fluid samples S arranged according to a preset known concentration gradient 1 ,S 2 ,…，S i ,…,S N The method comprises the steps of carrying out a first treatment on the surface of the Wherein the protein concentration value of the ith C-reactive protein body fluid sample is CS i And 0 is <CS 1 <CS 2 <…<CS i <…<CS N ，1≤i≤N；
Obtaining a protein C response curve of each body fluid sample on a protein detection target machine, and extracting eggs of each body fluid sampleCurve characteristic value r of white matter reaction curve 1 ,r 2 ,…，r i ,…,r N , 1≤i≤N；
Establishing a mathematical function corresponding relation between the curve characteristic value of the protein response curve of each body fluid sample and the protein concentration of the body fluid sample corresponding to the curve characteristic value; wherein the characteristic value r of the protein response curve of the ith body fluid sample is calculated i Protein concentration CS of the body fluid sample corresponding to the protein concentration CS i Establishing a mathematical function corresponding relation, wherein i is more than or equal to 1 and less than or equal to N;
obtaining the protein reaction mathematical model, wherein the formula comprises:
r=Fs(c)，
wherein c is more than or equal to 0 and less than or equal to CS, c is a protein concentration value of the body fluid sample, and r is a curve characteristic value of a protein reaction curve of the body fluid sample.
2. A method for detecting a specific protein reaction, comprising:
calibrating the protein detection apparatus according to the calibration method of claim 1;
protein detection is carried out on a body fluid sample to be detected so as to obtain a specific protein reaction curve;
extracting curve characteristics Rb of the specific protein reaction curve;
correcting the curve characteristic Rb according to a curve characteristic correction formula of the protein detection device to obtain a corrected curve characteristic Rb', wherein the curve characteristic correction formula comprises:
Rb′=Kb×Rb+Bb，
Wherein Rb' is the curve characteristic value obtained after correction, rb is the curve characteristic value of the specific protein reaction curve, kb is the curve calibration slope value, and Bb is the curve calibration intercept value;
inputting the curve characteristic Rb' into the protein reaction mathematical model to obtain a protein concentration value output by the protein reaction mathematical model, and outputting the protein concentration value as a protein concentration value of the body fluid sample to be detected.
3. The method for detecting a specific protein reaction according to claim 2, further comprising:
the body fluid sample to be tested comprises a blood sample;
when the body fluid sample to be detected is a blood sample, performing HCT detection on the blood sample;
and carrying out HCT correction on the protein concentration value output by the protein reaction mathematical model, and outputting the protein concentration value after HCT correction as a C-reaction protein concentration value of the blood sample.
4. A computer readable storage medium comprising a program executable by a processor to implement the method of any of claims 1-2.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011250348.8A CN112485439B (en) | 2020-11-10 | 2020-11-10 | Specific protein reaction detection method, protein detection device and calibration method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011250348.8A CN112485439B (en) | 2020-11-10 | 2020-11-10 | Specific protein reaction detection method, protein detection device and calibration method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112485439A CN112485439A (en) | 2021-03-12 |
| CN112485439B true CN112485439B (en) | 2023-07-18 |
Family
ID=74929526
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011250348.8A Active CN112485439B (en) | 2020-11-10 | 2020-11-10 | Specific protein reaction detection method, protein detection device and calibration method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112485439B (en) |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1288308A1 (en) * | 2001-08-28 | 2003-03-05 | Roche Diagnostics GmbH | A method for the determination of multiple analytes |
| CN103336130A (en) * | 2013-06-21 | 2013-10-02 | 嘉善加斯戴克医疗器械有限公司 | Whole-blood immunoassay device and blood analyzer with same |
| CN103998619A (en) * | 2011-12-22 | 2014-08-20 | 霍夫曼-拉罗奇有限公司 | Method for determining an analyte concentration |
| CN105229447A (en) * | 2013-06-12 | 2016-01-06 | 豪夫迈·罗氏有限公司 | For photometric calibration steps |
| WO2017001018A1 (en) * | 2015-07-02 | 2017-01-05 | Siemens Aktiengesellschaft | A biochemical analytical technique |
| EP3258242A1 (en) * | 2016-06-17 | 2017-12-20 | Sysmex Corporation | Blood analyzing method, blood analyzer, computer program, calibrator set, and calibrator set manufacturing method |
| CN108303548A (en) * | 2018-02-08 | 2018-07-20 | 北京市临床检验中心 | A kind of calibrating method improving c reactive protein testing result consistency |
| CN110441509A (en) * | 2018-05-02 | 2019-11-12 | 深圳市理邦精密仪器股份有限公司 | For being immunoreacted the calibrating method, device and terminal device of analyte detection |
-
2020
- 2020-11-10 CN CN202011250348.8A patent/CN112485439B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1288308A1 (en) * | 2001-08-28 | 2003-03-05 | Roche Diagnostics GmbH | A method for the determination of multiple analytes |
| CN103998619A (en) * | 2011-12-22 | 2014-08-20 | 霍夫曼-拉罗奇有限公司 | Method for determining an analyte concentration |
| CN105229447A (en) * | 2013-06-12 | 2016-01-06 | 豪夫迈·罗氏有限公司 | For photometric calibration steps |
| CN103336130A (en) * | 2013-06-21 | 2013-10-02 | 嘉善加斯戴克医疗器械有限公司 | Whole-blood immunoassay device and blood analyzer with same |
| WO2017001018A1 (en) * | 2015-07-02 | 2017-01-05 | Siemens Aktiengesellschaft | A biochemical analytical technique |
| EP3258242A1 (en) * | 2016-06-17 | 2017-12-20 | Sysmex Corporation | Blood analyzing method, blood analyzer, computer program, calibrator set, and calibrator set manufacturing method |
| CN108303548A (en) * | 2018-02-08 | 2018-07-20 | 北京市临床检验中心 | A kind of calibrating method improving c reactive protein testing result consistency |
| CN110441509A (en) * | 2018-05-02 | 2019-11-12 | 深圳市理邦精密仪器股份有限公司 | For being immunoreacted the calibrating method, device and terminal device of analyte detection |
Non-Patent Citations (1)
| Title |
|---|
| 全血C反应蛋白检测影响因素的校正方法及临床应用;裴兵;;国际检验医学杂志(02);第192-193页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112485439A (en) | 2021-03-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112485438B (en) | Specific protein reaction detection method and device | |
| US8339601B2 (en) | Counting bacteria and determining their susceptibility to antibiotics | |
| Poon et al. | Quantitative reagent-free detection of fibrinogen levels in human blood plasma using Raman spectroscopy | |
| ES2768198T3 (en) | Calibration for multi-component tests | |
| JP2011508197A5 (en) | ||
| Taavela et al. | Histological, immunohistochemical and mRNA gene expression responses in coeliac disease patients challenged with gluten using PAXgene fixed paraffin-embedded duodenal biopsies | |
| Jasensky et al. | Evaluation of three different point‐of‐care tests for quantitative measurement of canine C‐reactive protein | |
| CN112485440B (en) | Specific protein reaction detection method, protein detection device and calibration method | |
| EP1517140A2 (en) | Method and device for diagnostic investigation of biological samples | |
| JP2022120079A (en) | Analyzer and analysis method | |
| CN106324251A (en) | Preparation method of small-fragment BMG antibody and beta2-microglobulin detection kit | |
| EP3221444B1 (en) | Lateral flow assay ratio test | |
| CN106796221A (en) | The Clinics and Practices of Chuan Qishi diseases | |
| CN112710627B (en) | Detection method and detection device for specific protein concentration | |
| Karam et al. | Whole-blood validation of a new point-of-care equine serum amyloid A assay | |
| CN112485439B (en) | Specific protein reaction detection method, protein detection device and calibration method | |
| CN106872379B (en) | A kind of urinary fractions analyzer | |
| CN112710636B (en) | Method and device for detecting concentration of specific protein | |
| US20040108223A1 (en) | Simplified signal processing method for voltammetry | |
| JP4735503B2 (en) | Peritoneal function marker, analysis method thereof and use thereof | |
| JP2007513399A (en) | Generation and use of biochemical images | |
| US20200359899A1 (en) | METHODS AND COMPUTER PRODUCT FOR IDENTIFYING TISSUE COMPOSITION USING QUANTITATIVE MAGNETIC RESONANCE IMAGING (qMRI) | |
| CN112964673B (en) | Method and device for identifying abnormality of specific protein response curve | |
| KR20160006701A (en) | Method for measuring the plasma concentration of an analyte directly on a whole blood sample | |
| EP3144677A1 (en) | Rapid test for biomarker lysophosphatidylcholine using ftir |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |