CN109682968B - Temperature correction method for quantitative detection test signal of fluorescence immunoassay strip - Google Patents
Temperature correction method for quantitative detection test signal of fluorescence immunoassay strip Download PDFInfo
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- G—PHYSICS
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- 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
- G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
- G01N33/558—Immunoassay; Biospecific binding assay; Materials therefor using diffusion or migration of antigen or antibody
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- 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
- G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
- G01N33/5306—Improving reaction conditions, e.g. reduction of non-specific binding, promotion of specific binding
Abstract
The invention discloses a temperature correction method for a fluorescent immune test strip quantitative detection test signal, and belongs to the technical field of biology, medical engineering and computer signal processing. The invention obtains optical signals of a detection line and a quality control line on the basis of a fluorescent immunoassay strip quantitative detection measurement technology, and the measurement result is influenced by environmental factors such as temperature, humidity, pH value and the like, wherein the influence of the temperature is strong. In order to improve the stability and the precision of detection, a temperature-based compensation and correction unit is provided by detecting and analyzing the temperature and based on the principles of antigen-antibody immunoreaction and fluorescence reaction, so that the interference caused by the temperature is eliminated.
Description
Technical Field
The invention relates to a temperature correction method for a fluorescent immune test strip quantitative detection test signal, in particular to a method for correcting the temperature of a fluorescent immune test strip quantitative detection test result by using known measurement signals with different concentrations at different temperatures, which belongs to the technical field of biology, medical engineering and computer signal processing.
Background
Fluorescence Immunoassay (FIA) was the first established immuno-labeling technique, originated by Coons et al during the early 40 s of the 20 th century. The basic principle is that the sensitivity and the detectability of fluorescence are combined with the high specificity reaction of antigen and antibody, and fluorescent substance is used as a marker. Fluorescent substances are capable of absorbing light energy into an excited state under the action of excitation light of a specific wavelength, releasing the previously absorbed light energy in the form of electromagnetic radiation, and generating fluorescence. The specific fluorescence can be directly observed by a fluorescence microscope, can also be received by a photoelectric detector and converted into an electric signal to be further processed, can accurately, sensitively and quickly position and detect certain trace or ultra-trace substances, and is widely applied to a plurality of fields of medicine, biology, environmental protection and the like.
The immunochromatography detection technology is an immunoassay technology combining a chromatography technology and antigen-antibody specific reaction. The fluorescence immunochromatography quantitative detection technology is characterized in that on the basis of immunochromatography, a fluorescence marker is used for generating fluorescence under the irradiation of ultraviolet light, and the concentration of an object to be detected is measured according to a quantitative algorithm. The fluorescence immunochromatographic assay and the colloidal gold immunochromatographic assay have the characteristics of high stability, strong specificity, capability of quantitatively reacting the concentration of a substance to be detected and the like, and the fluorescence immunochromatographic assay has higher sensitivity and larger dynamic detection range than the colloidal gold immunochromatographic assay.
In the process of determining the retention value, chromatographic analysis is easily influenced by various factors such as temperature, flow rate, stationary phase properties, sample solution impurities and the like, the higher the chromatographic speed, the less antigen captured by the antibody, the lighter the color development, and the lower the sensitivity of the reagent, i.e. the chromatographic speed is inversely related to the sensitivity. The current fluorescent immune test strip quantitative detection technology is greatly influenced by temperature, and the binding reaction of antigen and antibody is mainly influenced. At higher temperatures, the chances of collision of the antigen-antibody complex increase, and the chances of the complex continuing to increase in volume increase also increase, so that the reaction phenomenon is accelerated. If the environmental temperature is too high, the combined antigen and antibody can be dissociated and denatured; the reaction rate becomes slow at too low a temperature. In addition, as the temperature of the solution rises, the viscosity of the medium becomes small, thereby increasing the chance of collision quenching of fluorescent molecules with solvent molecules.
The detector not only gives out voltage and current signals representing the measured object in the photoelectric conversion process, but also accompanies fluctuation noise voltage and current signals, and the fluctuation noise determines the capacity of the detector. All the elements with power resistors have thermal noise, and the temperature affects the noise of the detector and further affects the measurement result.
In conclusion, the temperature has a great influence on the quantitative detection of the fluorescence immunoassay strip, the influence factors are complex, the uniform mathematical model is difficult to represent, and the temperature stability is usually controlled by adding a temperature controller in the current quantitative detection process of the fluorescence immunoassay strip, so that the influence of the temperature on the quantitative detection of the fluorescence immunoassay strip is reduced.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a fluorescent immune test strip quantitative detection test signal temperature correction method based on known measurement data of different temperatures and different concentrations.
According to the requirement of the fluorescent immune test strip for quantitative detection on temperature correction, the temperature correction of the measured value is carried out by analyzing the final measured value and the physical quantity to be measured and utilizing the existing measured data with different concentrations at different temperatures. The whole correction function is determined through the processes of determining an ideal correction form, determining a correction index, determining a correction target, determining a correction characteristic value, designing a correction mathematical model, determining a correction parameter, correcting the correction parameter and the like, and the correction function is finally obtained.
In a first aspect of the present invention, a method for correcting temperature of a fluorescence quantitative detection test signal is provided, the method comprising the following steps:
(1) providing data:
providing fluorescence quantitative detection numerical data and temperature data;
(2) temperature correction:
carrying out temperature correction on the quantitative detection data in the step (1); comprising the following substeps:
(a) determining an ideal correction model of the optical fiber,
(b) determining a correction index;
(c) determining a correction target;
(d) determining a correction characteristic value;
(e) designing a correction mathematical model;
(f) preliminarily determining correction parameters to obtain preliminary correction parameters;
(3) judging the correction effect;
substituting the primary correction parameters obtained in the step (f) into the correction mathematical model designed in the step (e) to obtain a primary correction equation 1, judging the correction effect of the primary correction result according to the correction indexes determined in the step (b), and controlling the process according to the judgment result;
and (4) when the correction effect is judged not to meet the standard, performing correction parameter correction, wherein in the correction parameter correction step, parameter correction is performed on the obtained correction equation 1 by using (c), and a correction characteristic value (d) which is a correction result is added to the correction equation 1 through a correction mathematical model (e) in the following formula to complete parameter correction:
y＝g(T)x+h(T)+t(T) (A)
wherein g (T) is a coefficient function, h (T) is an intercept function, t (T) is a correction function, and an accurate correction equation 2 is obtained in a self-adaptive manner to a certain extent by continuously reducing the correction range;
when the correction effect is judged to reach the standard, the correction parameter correction step (4) is not carried out;
(5) outputting a correction equation 2;
and outputting the correction equation 2 to the measuring system, so that the system can correct the measured value according to the measured temperature information.
In another preferred example, the correction equation 2 is a final parameter correction equation 2 obtained through one or more (3) correction effect determinations and/or one or more (4) correction parameter corrections.
In another preferred embodiment, the fluorescent quantitative detection is a fluorescent immune test strip quantitative detection.
In another preferred embodiment, the determined ideal correction form is:
y＝g(T)×f(x)+h(T) (B)
wherein x represents the original measured value, y represents the corrected measured value, and is the output result of the correction function, wherein g is the coefficient function, h is the intercept function, and f is the measured value conversion function.
In another preferred embodiment, the final determination takes the actually measured original signal value x as 400 as the function boundary point, where g (t) + h (t) is a quadratic function, and f (x) is a linear function.
In another preferred embodiment, different parameters are used for correction when x ≦ 400 and x > 400, respectively.
In another preferred embodiment, when x ≦ 400, the low value correction function y is used1Correcting for g (t) × f (x) + h (t); when x is more than 400, high-value correction function y is used2Correction is performed for g (t) (x) × f (x) + h (t).
In another preferred example, the correction index is a physical quantity capable of describing a degree of dispersion of the measured values.
In another preferred embodiment, the corrective measure is the standard deviation, variance, mean deviation and/or range of the measured value (Δ max-min).
In another preferred embodiment, the correction index is preferably very poor.
In a further preferred embodiment, a fictive or standard temperature T is used0The mean value of the single analyte level measurement values at different temperature points is used as the hypothetical temperature T in the established model0The corrected target is established and the measured results of the actual temperature levelsThe correction function of (2).
In another preferred embodiment, the correction characteristic value is determined by analyzing the complexity influence of the temperature on the characteristic value according to the measured characteristic value and determining the feasibility according to a mathematical model.
In another preferred example, the correction characteristic value is a physical quantity that combines the measurement line area Ta and the quality control line area Ca.
In another preferred embodiment, a mathematical model for correcting the correction characteristic value in (d) is determined according to the ideal correction form in (a), and the mathematical model for determining temperature correction is as follows:
y＝(anTn+…+a1T+a0)×x+(bnTn+…+b1T+b0) (C)
wherein x is the original measurement value, y is the corrected measurement value, T is the temperature, ai，bi(i ═ 0.. n) is a polynomial fitting parameter.
In another preferred embodiment, a preliminary determination of the correction parameter is made on the basis of measurements of different concentrations at different temperatures according to (e) said correction (function) mathematical model.
In another preferred embodiment, the parameter fitting is performed under the requirements of the Akamer's law to finally obtain the complete correction function parameters.
In a second aspect of the present invention, there is provided a fluorescence quantitative detection test signal temperature correction device, comprising:
a memory for storing computer executable instructions; and the number of the first and second groups,
a processor for implementing the steps of the method according to any one of the first aspect of the invention when executing the computer executable instructions.
In a third aspect of the present invention, there is provided a computer-readable storage medium comprising:
the computer-readable storage medium has stored therein computer-executable instructions which, when executed by a processor, implement the steps of the method according to any one of the first aspects of the invention.
It is to be understood that within the scope of the present invention, the above-described features of the present invention and those specifically described below (e.g., in the examples) may be combined with each other to form new or preferred embodiments. Not to be reiterated herein, but to the extent of space.
Other features, objects and advantages of the present invention will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, with reference to the accompanying drawings.
Drawings
Fig. 1 is a flow chart of a correction method according to a preferred embodiment of the present invention.
Fig. 2 is a schematic diagram of a modification of the measurement method according to a preferred embodiment of the present invention.
Detailed Description
Through intensive and thorough research, the inventor develops a method for completing correction of measurement data by acquiring temperature data for the first time. The method comprises the following steps: (1) providing data; (2) correcting the temperature; (3) judging the correction effect; optionally (4) correction parameter modification; and (5) output correction equation 2. The method of the invention further reduces the influence of the temperature on the measurement result by the temperature correction method on the basis of the temperature control system. More excellent, some current measuring systems are not provided with a temperature control system, and the temperature correction method can greatly improve the stability of the measuring system and the accuracy of the measuring result. On the basis of this, the present invention has been completed.
The invention is realized by the following technical scheme:
the method comprises the following steps:
1) determination of ideal correction form
The temperature correction requirement of the test signal is quantitatively detected based on the fluorescence immunoassay strip, and an ideal expected correction form is determined according to the input and output form, so that a basic basis is provided for the subsequent correction equation determination process. Through comprehensive consideration of data coupling, parameter determination difficulty, implementability and the like, the finally determined ideal correction form is as follows:
y＝g(T)×f(x)+h(T)
wherein x represents the original measured value, y represents the corrected measured value, and is the output result of the correction function, wherein g is the coefficient function, h is the intercept function, f is the measured value conversion function, and T is the actual measured value of the temperature. The coefficient function, the intercept function and the measured value conversion function are nth-order polynomial functions, and the specific form of the functions is determined by the subsequent steps.
2) Correction index determination
The correction index is determined based on the problems existing in the current actually measured measurement result, and the correction effect can be obviously and quantitatively shown through the correction index. And finally, selecting the range difference (delta max-min) as a correction index according to the effect of the influence on the actual measurement result.
3) Corrective objective determination
Instead of selecting a measured value at a particular temperature as the calibration target, the present invention uses a hypothetical temperature T to calculate the calibration target using the current measured value and a function0Then, the mean value of the measured values at different temperatures is taken as the measured value at the virtual temperature as the correction target, and the measured values at any known temperature in a certain range are finally corrected to the virtual temperature T through the correction function0The following accurate measurement values.
4) Corrective feature value determination
According to the measured characteristic value, the complexity influence of the temperature on the characteristic value is analyzed, and then the physical quantity corresponding to the improved characteristic extraction function Tap on the basis of the ratio of the area Ta of the measurement line to the area Ca of the quality control line is finally determined as a correction characteristic value according to the feasibility established by the mathematical model.
5) Design of corrective mathematical model
Determining a correction mathematical model of the correction characteristic value in the pair 4) according to the ideal correction form in the step 1), and finally determining the mathematical model for temperature correction according to information such as dimension relation of parameters in the mathematical model, wherein the mathematical model for temperature correction is as follows:
y＝(anTn+…+a1T+a0)×x+(bnTn+…+b1T+b0)
in the formula (I), the compound is shown in the specification,x is the original measurement, y is the corrected measurement, T is the temperature, ai，bi(i ═ 0.. n) is a polynomial fitting parameter.
6) Preliminary determination of correction parameters
And according to 5) the mathematical correction function model, carrying out preliminary determination on correction parameters on the basis of the measured values of different concentrations at different temperatures. Firstly, the measured values of different concentrations at the same temperature are used for obtaining the slope and intercept values at different temperatures, then the fitting of the slope and intercept to the temperature is carried out on the basis of the Aomu's law, and finally the a) in the step 5) is obtainedi，biFunctional form and parameters of (i ═ 0.. n).
7) Correction effect determination
Substituting the initial correction parameters obtained by 6) into the correction mathematical model designed by 5) to finally obtain an initial correction equation, judging the correction effect of the initial correction result according to the correction indexes determined by 2), turning to 9) to output the correction equation when the judgment result meets certain standards, and turning to 8) to correct the correction parameters when the judgment result does not meet certain standards.
8) Correction parameter modification
And when the correction effect judgment of 7) does not meet the standard, performing parameter correction on the obtained correction equation by using the current correction equation and the correction target value of 3) and the known original measurement values with different concentrations at different temperatures. Obtaining a correction function by limiting a correction range and adding the correction function to a correction equation to finish parameter correction according to the following formula:
y＝g(T)x+h(T)+t(T)
where g (T) is a coefficient function, h (T) is an intercept function, and t (T) is a correction function. The final correction parameters are more accurate by continuously reducing the correction range, and an accurate correction equation is finally obtained.
9) Correction equation output
Finally, the final parameter correction equation is finally obtained through the multiple correction effect judgment of 7) and the multiple correction parameter correction of 8), and then the correction equation is output to the measurement system, so that the system can finish the correction of the measured value according to the measured temperature information.
The main advantages of the invention are:
compared with the prior art, the invention has the following beneficial effects:
1) the invention introduces the temperature correction of the algorithm on the basis of the existing simple measurement quantity extraction and then the calculation of the physical quantity to be measured, reduces the discrete degree of the signal to be measured to a certain extent, and improves the measurement accuracy of the physical quantity to be measured;
2) the temperature correction mode can weaken the hardware requirement and excessive dependence of the measurement precision on the measurement equipment, and reduce the control requirement of the measurement equipment on temperature control;
3) on the basis of the existing temperature-controlled measuring equipment, the measuring precision and the measuring accuracy of the measuring equipment can be further improved;
4) the invention particularly provides a method for correcting the measurement data by an algorithm and parameter correction, provides a guide basis and an idea for the influence of other environmental parameters, and enables the correction of multi-environmental parameters of the fluorescent immune test strip for quantitatively detecting the test signal to be possible;
5) by "fictive temperature T0"OR" standard temperature T0"it is proposed that the calibration function can be obtained during the course of the study, i.e.the calibration curve is corrected to the" fictive temperature T "during the subsequent reagent calibration0"OR" standard temperature T0"calibration curve under such that the measured value at a certain temperature is taken into the" fictitious temperature T "after being corrected by the same function in the actual measurement0"OR" standard temperature T0"the calibration curve under the condition obtains more accurate report value, thereby avoiding the complex work of calibrating each batch of reagent at each temperature.
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the invention, but are not intended to limit the invention in any way. It should be noted that variations and modifications can be made by persons skilled in the art without departing from the spirit of the invention. All falling within the scope of the present invention.
As shown in fig. 2, an improved schematic diagram of a measurement method is obtained by integrating a temperature measurement value of a current measurement process obtained by a temperature sensor based on a measurement value obtained by a data processing method such as filtering and feature extraction of a previous data processing algorithm and a correction equation obtained by a temperature correction method based on measurement result values of different temperatures and different concentrations as a correction function into a measurement value and a temperature value, further obtaining a corrected measurement value, and obtaining a final physical quantity to be measured by using a corresponding function of the measurement value and the physical quantity.
As shown in fig. 1, a method for correcting the temperature of a test signal quantitatively detected by a fluorescent immune test strip, the method comprising the steps of:
1) determination of ideal correction form
The temperature correction requirement of the test signal is quantitatively detected based on the fluorescence immunoassay strip, and an ideal expected correction form is determined according to the input and output form, so that a basic basis is provided for the subsequent correction equation determination process.
The most initial temperature and measurement correction function is of the form:
y＝f(x，T)
wherein x represents the original measured value, y represents the corrected measured value, and is the output result of the correction function. Such a correction function is meaningless because of the coupling terms of the measured values and the temperature uncertainty in the form of such a correction function.
The complexity of the ideal correction function is improved, the degree of freedom of the ideal correction function is reduced, and the improved correction function has the form:
y＝g(T)×f(x)+h(T)
wherein x represents the original measured value, y represents the corrected measured value, and is the output result of the correction function, wherein g is the coefficient function, h is the intercept function, and f is the measured value conversion function.
2) Correction index determination
The correction index is determined based on the problems existing in the current actually measured measurement result, and the correction effect can be obviously and quantitatively shown through the correction index.
The influence on the measurement result in the current actual measurement is mainly expressed in the linearity between the current measurement value and the physical quantity, the dispersion degree of the current measurement value, the error between the current measurement value and the target value, and the like. At present, in the actual measurement process, the actual inaccurate measurement caused by the overlarge dispersion degree of the measured value along with the temperature change is mainly caused, so the dispersion degree of the measured value is taken as a correction index.
Physical quantities that can describe the degree of dispersion of the measured values are the standard deviation, variance, mean deviation and range (Δ max-min) of the measured values. For the accuracy of the measurement, the range is the one that best represents the maximum difference, and therefore the range, i.e. the span of the interval between the maximum observed value (Δ max) and the minimum observed value (Δ min) of the measured values, is chosen as the correction indicator.
3) Corrective objective determination
The present invention uses the current measured value to calculate the correction target through a certain function, and uses the fictitious temperature to calculate the function value as the correction target, and the correction target is set at the fictitious temperature T0The following steps. The objective function may select a mean, a temperature weighted mean, and a median. Finally, the nonlinearity of the median is too strong to be uniform, the temperature weighted mean value enables the temperature correction target to be coupled with the temperature, and the mean value is finally selected as the target function.
4) Corrective feature value determination
After the initial fluorescence curve is obtained, four basic parameters can be obtained through feature extraction: measurement line area Ta, measurement line amplitude Ty, quality control line area Ca, and quality control line amplitude Cy. Because the four basic parameters are influenced by temperature complicatedly, and the temperature correction of a single parameter is difficult to be represented by a mathematical model, an integrated feature extraction value is required to be used as a correction feature value, the feature extraction value is a feature extraction function Tap improved on the basis of the ratio of a measurement line area Ta and a quality control line area Ca in the basic parameters, the influence of the temperature on the features can be eliminated to a certain extent on the basis of the function, the complexity of the relation between the feature value and the temperature is reduced, and the design of the mathematical model is facilitated.
5) Design of corrective mathematical model
Determining a correction mathematical model for the correction characteristic value in 4) according to the ideal correction form in 1), wherein the common mathematical model comprises a polynomial model, an exponential model, a logarithmic model and the like. Since the inputs and outputs are measured values, except for one at the actual temperature and one at the fictive temperature, the existence between the two should be more biased towards a polynomial model, in which the model parameters should be only a temperature dependent function, the mathematical model being as follows:
y＝gn(T)xn+…+gi(T)xi+…+g1(T)x1+g0(T)，i＝1，2，3...n
in particular, since the physical dimensions of the measured value x and the corrected output value y are the same, the higher-order terms in the polynomial equation can be ignored, and thus the above equation can be simplified as follows:
y＝g(T)x+h(T)
similarly, the coefficient function g (t) and the intercept function h (t) are also set to be polynomial functions, so the final overall mathematical model is:
y＝(anTn+…+a1T+a0)×x+(bnTn+…+b1T+b0)
6) preliminary determination of correction parameters
And according to 5) the mathematical correction function model, carrying out preliminary determination on correction parameters on the basis of the measured values of different concentrations at different temperatures. Firstly, selecting measured values of different concentrations at the same temperature as independent variables, taking the correction target in 3) as a dependent variable, and carrying out straight line fitting according to the correction mathematical model in 5) to obtain the slope k and the intercept b of the fitted straight line of the measured values and the correction target at different temperatures. And then, taking the temperature as an independent variable, and respectively taking the slope k and the intercept b of the fitting straight line as dependent variables to perform polynomial fitting, wherein in order to ensure the robustness of the correction function, the polynomial degree of the correction function is required to be less than or equal to three, and the polynomial degree which is as small as possible is used when the fitting judgment coefficient is large enough according to the law of the Akamer razor. And finally obtaining the primary correction parameters.
7) Correction effect determination
Substituting the initial correction parameters obtained in the step 6) into the correction mathematical model designed in the step 5) to finally obtain an initial correction equation, and judging the correction effect of the initial correction result according to the correction indexes determined in the step 2). And carrying out flow control according to the judgment result, entering a process of finally determining an output by using a correction equation shown in 9) if the correction effect reaches the standard, and carrying out a correction process of 8) the correction parameter if the correction effect does not reach the standard. And whether the correction effect reaches the standard or not is determined by taking the percentage of the difference between the range of the original measured values at different temperatures at the same concentration and the range of the corrected measured value results at different temperatures at the same concentration obtained after correction in the original range as an evaluation value, and when the evaluation value is greater than a certain value, the standard is met.
8) Correction parameter correction
And when the correction effect judgment of 7) does not meet the standard, performing parameter correction on the obtained correction equation by using the current correction equation and the correction target value of 3) and the known original measurement values with different concentrations at different temperatures.
Firstly, determining a correction range, wherein the range needing to be corrected is not a correction target function in the whole temperature section or the whole concentration section, and relatively increasing the times of the polynomial, segmenting the function and more ensuring the robustness of the system and the difficulty of parameter determination and verification, so that the range of the correction function is determined firstly.
Then, a deviation value is obtained, after a function correction range is determined, the measured value in the range is substituted into the current correction equation to obtain an initial correction result, and the current correction result is subtracted from the correction target value in 3) to obtain the deviation value of the function.
The independent variable and the dependent variable of the correction fitting function are obtained, the function which is mainly related to temperature needs to be corrected, so that the independent variable of the correction function is temperature, the dependent variable is an offset value, and at the moment, one temperature corresponds to the offset value under a plurality of concentrations, the data integration of the dependent variable is needed, namely, the average value of the offset values under the temperature is obtained as the dependent variable, and the correction function t (T) is obtained after polynomial fitting.
The final modified polynomial function is:
y＝g(T)x+h(T)+t(T)
where g (T) is a coefficient function, h (T) is an intercept function, and t (T) is a correction function.
And after correction, the correction function is subjected to secondary correction effect judgment, and the aim of enabling the whole correction function to reach the standard is finally achieved by gradually reducing the correction range.
9) Correction equation output
Finally, the final parameter correction equation is finally obtained through the multiple correction effect judgment of 7) and the multiple correction parameter correction of 8), and then the correction equation is output to the measurement system, so that the system can finish the correction of the measured value according to the measured temperature information.
10) Corrective effect
The method of the present invention is used to establish a temperature correction function of a BNP (B-type brain natriuretic peptide) immunofluorescence assay kit, a calibration curve (T may be any temperature at which the calibration curve is drawn) is obtained at 25 ℃ when T ═ 25 ℃, and the correction function is established by the method of the present invention:
when the measured value is less than 400:
y＝(-0.00635T+1.2097)x+0.05644T2-2.03226T+4.32053
when the measured value is greater than 400:
y＝(-0.00635T+1.2097)x+0.39697T2-26.43979T+433.3316
the calibration curve at 25 ℃ is corrected to a "fictive temperature T0"OR" standard temperature T0"calibration curve under. As shown in table 1.
TABLE 1 comparative table of the improved range of a preferred embodiment of the present invention
Respectively fitting a calibration curve to obtain: the standard curve function before correction is:
y ═ a-D) [1+ (xC) ^ B ] + D, (where a ═ 3619.12724, B ═ 1.21371, C ═ 1216.73864,
D＝10.10068；R2＝0.99996)；
corrected "fictive temperature T0"the scaling curve function under:
y ═ a-D/[ 1+ (x/C) ^ B ] + D, (where a ═ 3799.01736, B ═ 1.21508, C ═ 1181.22648,
D＝28.13712；R2＝0.99991)
in the actual measurement process, the inventor tests BNP standard substance solutions at 100pg/ml and 1600pg/ml, records the measured values, the reported values under the original standard curve, the actual test temperature T and the corrected measured values of the function proposed by the method, and calculates the substitution of the corrected measured values into the' imaginary temperature T0"OR" standard temperature T0"lower calibration curve, as shown in tables 2 and 3.
TABLE 2 accuracy in determination of BNP calibrator (100pg/ml)
TABLE 3 accuracy in determination of BNP calibrator (1600pg/ml)
As can be seen from tables 2 and 3, the temperature after correction to the fictive temperature T0Thereafter, the accuracy of the reported values is greatly improved, and the deviation of the reported values of the calibrator at 100pg/ml is more than 15% for a plurality of times before correction, and the deviation of the reported values at 100pg/ml is considered to be clinically unavailable when the deviation is more than 20%, and the deviation is maintained below 15% after correction. Actual measurement of 1600pg/ml calibrator samples, correctedThe relative deviation of the reported values of (A) is kept below 10%. The improvement of the relative deviation is very significant for analytical tests, in particular for clinical use.
Therefore, the invention designs a mathematical model by analyzing the characteristics and the requirements of the measured value, ensures the theoretical basis of temperature correction, improves the correction precision and creatively provides the 'hypothetical temperature T' by a self-adaptive parameter correction method at the same time of improving the correction precision0"OR" standard temperature T0"concept, by the method of the present invention, it is not necessary to perform calibration curve plotting under different temperature conditions individually for each batch of reagents and even for each individual analytical test system at each temperature point. After obtaining a certain calibration curve at a certain temperature, the calibration curve is corrected to the 'virtual temperature T' by using the method provided by the invention0Calibration curve under which the test value is corrected again to the "fictive temperature T" during the actual measurement0"is used herein. The relative deviation of the reported values due to the temperature-dominant cause in the actual test is significantly improved.
The implementation of the method of the invention can realize the temperature correction of the test signal of the quantitative detection of the fluorescence immunoassay strip by the method without the requirement of the hardware of the temperature control module, thereby not only reducing the hardware requirement of the system, but also improving the concise property of the system.
The foregoing description of specific embodiments of the present invention has been presented. It is to be understood that the present invention is not limited to the specific embodiments described above, and that various changes and modifications may be made by one skilled in the art within the scope of the appended claims without departing from the spirit of the invention.
Discussion of the related Art
Further, due to the above mentioned complexity factor, different batches of reagents, even different equipments, are affected by temperature and show different differences between the true values of the distance measurement when performing actual measurement, and it is usually necessary to draw different calibration curves of immunoreaction at different temperatures, and then select different calibration curves according to the collected ambient temperature or reagent reaction temperature during actual measurement, and calculate the concentration value according to the measured value. However, this method is time-consuming and labor-consuming, and is not practical.
In the work of the invention, the inventor creatively provides a 'virtual temperature T' in the process of correcting the measured value and the temperature of the reagent of the same type under a matched measuring system0"OR" standard temperature T0"is designed. That is, the inventor has established a temperature calibration function in the test study of reagents with different temperatures and different batches, and the method and the result of the function are established so that only one calibration curve of a certain batch of reagents at a certain temperature is needed to be obtained in the final actual measurement, and then the calibration curve at the temperature is calibrated into the 'hypothetical temperature T' through the calibration function established by the method provided by the invention0"OR" standard temperature T0"calibration curve under. In the actual analysis and test process, the real-time temperature is measured, and then the function determined by the method is corrected to obtain the' hypothetical temperature T0"OR" standard temperature T0The corrected measured value under "is substituted into the above" virtual temperature T0"OR" standard temperature T0"in the lower calibration curve, a relatively accurate back-calculated concentration value is obtained. The attenuation of deviation brought by temperature in the immunochromatography analysis process is realized, so that the immunoassay measurement value has higher accuracy.
All documents referred to herein are incorporated by reference into this application as if each were individually incorporated by reference. Furthermore, it should be understood that various changes and modifications of the present invention can be made by those skilled in the art after reading the above teachings of the present invention, and these equivalents also fall within the scope of the present invention as defined by the appended claims.
Claims (15)
1. A temperature correction method for a fluorescence quantitative detection test signal is characterized by comprising the following steps:
(1) providing data:
providing fluorescence quantitative detection numerical data and temperature data;
(2) temperature correction:
carrying out temperature correction on the quantitative detection data in the step (1); comprising the following substeps:
(a) determining an ideal correction model, wherein the determined ideal correction model is as follows:
y＝g(T)×f(x)+h(T) (B)
wherein x represents the original measured value, y represents the corrected measured value, and is the output result of the correction function, wherein g is the coefficient function, h is the intercept function, f is the measured value transfer function,
(b) determining a correction index, wherein the correction index is a physical quantity capable of describing the discrete degree of the measured value;
(c) determining the correction target by using a fictitious or standard temperature T0The mean value of the single analyte level measurement values at different temperature points is used as the hypothetical temperature T in the established model0A correction target;
(d) determining a correction characteristic value, wherein the influence of temperature on the complexity of the characteristic value is analyzed according to the measured characteristic value, and the correction characteristic value is further determined according to the feasibility established by a mathematical model;
(e) designing a corrective mathematical model, wherein a corrective mathematical model for said corrective characteristic values of (d) is determined from said ideal corrective model of (a), said corrective mathematical model for determining temperature correction being:
y＝(anTn+…+a1T+a0)×x+(bnTn+…+b1T+b0) (C)
wherein x is the original measurement value, y is the corrected measurement value, T is the temperature, ai，bi(i-0.. n) is a polynomial fitting parameter;
(f) preliminarily determining a correction parameter to obtain a preliminary correction parameter, wherein the substep (f) comprises the following parameter fitting steps: firstly, selecting measured values of different concentrations at the same temperature as independent variables, taking the correction target of (c) as a dependent variable, and carrying out linear fitting according to the correction mathematical model of (e) to obtain the slope k and the intercept b of the fitted straight line of the measured values and the correction target at different temperatures, then taking the temperature as the independent variable, and respectively taking the slope k and the intercept b of the fitted straight line as the dependent variables to carry out polynomial fitting;
(3) judging the correction effect;
substituting the primary correction parameters obtained in the step (f) into the correction mathematical model designed in the step (e) to obtain a primary correction equation 1, judging the correction effect of the primary correction result according to the correction indexes determined in the step (b), and controlling the process according to the judgment result;
and (4) when the correction effect is judged not to meet the standard, performing correction parameter correction, wherein in the correction parameter correction step, parameter correction is performed on the obtained correction equation 1 by using the correction parameter (c), and the correction characteristic value (d) which is the correction result is added to the correction equation 1 through a correction mathematical model (e) in the following formula to complete parameter correction:
y＝g(T)x+h(T)+t(T) (A)
wherein g (T) is a coefficient function, h (T) is an intercept function, t (T) is a correction function, and an accurate correction equation 2 is obtained in a self-adaptive manner to a certain extent by continuously reducing the correction range;
when the correction effect is judged to reach the standard, the correction parameter correction step (4) is not carried out;
(5) outputting a correction equation;
when the correction effect is judged to reach the standard, the correction equation 1 is output to the measuring system, and when the correction effect is judged not to reach the standard, the correction equation 2 is output to the measuring system, so that the system can finish the correction of the measured value according to the measured temperature information.
2. The method of claim 1, wherein the corrective equation 2 is a final parametric corrective equation 2 obtained through one or more (3) corrective effect determinations and/or one or more (4) corrective parameter corrections.
3. The method of claim 1, wherein the quantitative fluorescent test is a quantitative fluorescent immunoassay strip test.
4. The method of claim 1, wherein the final determination is performed by taking the actually measured original signal value x as 400 as a function boundary point, where g (t) + h (t) is a quadratic function, and f (x) is a linear function.
5. The method of claim 4, wherein the correction is performed using different parameters for x ≦ 400 and x > 400, respectively.
6. The method of claim 4, wherein the low value correction function y is used when x ≦ 4001Correcting for g (t) × f (x) + h (t); when x is more than 400, high-value correction function y is used2Correction is performed for g (t) (x) × f (x) + h (t).
7. The method of claim 1, wherein the corrective measure is a standard deviation of the measured values.
8. The method of claim 1, wherein the corrective measure is a standard deviation, variance, mean deviation, and/or range of measured values.
9. The method of claim 8, wherein the correction indicator is range.
10. The method of claim 1, wherein the calibration objective is used to establish a calibration function of the calibration objective and the actual temperature level measurements.
11. The method of claim 1, wherein the correction characteristic value is a physical quantity that combines a measurement line area Ta and a quality control line area Ca, wherein the physical quantity is a ratio of the measurement line area Ta and the quality control line area Ca.
12. A method according to claim 1, wherein the preliminary determination of the correction parameter is made based on measurements of different concentrations at different temperatures according to the corrective mathematical model of (e).
13. The method of claim 1, wherein sub-step (f) further comprises: and performing parameter fitting under the requirements of the Akahm razor law to finally obtain complete correction function parameters.
14. A fluorescent quantitative detection test signal temperature correction device, comprising:
a memory for storing computer executable instructions; and the number of the first and second groups,
a processor for implementing the steps of the method of any one of claims 1 to 13 when executing the computer-executable instructions.
15. A computer-readable storage medium, comprising:
the computer-readable storage medium has stored therein computer-executable instructions that, when executed by a processor, implement the steps of the method of any one of claims 1 to 13.
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| CN112432988B (en) * | 2020-11-25 | 2023-03-03 | 重庆迈联医疗科技有限公司 | Temperature correction method of electrochemical test system |
| EP4217743A1 (en) * | 2020-12-10 | 2023-08-02 | Waters Technologies Corporation | Devices and methods for temperature correction for lateral flow testing |
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