A method for interpreting results of nucleic acid amplification based on multi-dimensional chromaticity analysis

Abstract

The present application relates to a kind of nucleic acid amplification result interpretation method based on multidimensional chroma analysis, belong to nucleic acid detection and machine vision technical field, comprising the following steps: S1: before nucleic acid amplification reaction starts, the environmental reflection RGB value of blank reaction cavity or reference area is collected, and environmental background noise compensation model is established;S2: the initial RGB value of sample to be tested before reaction is collected, and the initial RGB value is corrected according to environmental background noise compensation model, obtains sample initial chroma benchmark;S3: after nucleic acid amplification reaction and cooling to room temperature, the end point RGB value after reaction is collected, is corrected using the same background model, obtains sample end chroma;S4: calculate the multidimensional chroma change feature vector of sample from initial to end point;S5: based on multidimensional feature vector and environmental compensation data, calculate comprehensive evaluation score and adaptive dynamic threshold, and according to comprehensive evaluation score and adaptive dynamic threshold, judge sample negative and positive.

Description

Technical Field

[0001] This invention belongs to the field of nucleic acid detection and machine vision technology, and relates to a method for interpreting nucleic acid amplification results based on multidimensional colorimetric analysis. Background Technology

[0002] Loop-mediated isothermal amplification (LAMP) has become the preferred method for rapid pathogen detection in resource-constrained environments due to its advantages of not requiring thermal cycling and its ease of operation. Regarding result interpretation, colorimetric LAMP utilizes metal ion indicators such as calcein to determine positive or negative results by observing the color change of the solution before and after the reaction (e.g., from orange to yellow-green).

[0003] Existing portable nucleic acid rapid diagnostic devices typically use a TCS34725 color sensor combined with a standard white light source for colorimetric readings. However, limited by algorithm design, existing interpretation methods mainly rely on single-channel color difference analysis and fixed empirical thresholds. For example, calculating the percentage change in the green channel (G channel) reading before and after the reaction. and compare it with a preset fixed threshold (such as The results are compared to determine the outcome.

[0004] This single threshold interpretation method has the following technical problems in practical field applications: 1. Weak anti-interference ability and poor robustness: This method does not establish a compensation model for changes in ambient light, the reflective properties of polymethyl methacrylate chip material, and batch attenuation of the light source. When ambient background light noise is superimposed or there are scratches on the chip surface, the background noise will cause the subtle color shift of weak positive samples to be submerged, resulting in missed detection.

[0005] 2. Low utilization of chromaticity information: Only the green channel variation is extracted. This approach discards information about the coupling changes between the red (R) and blue (B) channels during the reaction process, as well as the shift characteristics of hue and saturation. This makes it difficult for the algorithm to distinguish non-specific color fluctuations caused by metal ion precipitation or microbubbles.

[0006] 3. Lack of dynamic baseline correction capability: Fixed thresholds cannot adapt to the initial color differences caused by different reagent batches, nor can they compensate for color temperature drift caused by light source aging after long-term use, resulting in the need for frequent hardware white balance calibration of the equipment. Summary of the Invention

[0007] In view of this, the purpose of this invention is to provide a method for interpreting nucleic acid amplification results based on multidimensional colorimetric analysis. Based on the existing technology, by constructing a multidimensional colorimetric feature vector, introducing a white reference calibration model and an adaptive dynamic threshold algorithm, the detection accuracy of weak positive samples and the anti-interference ability of the device in complex lighting environments are significantly improved without increasing hardware costs.

[0008] To achieve the above objectives, the present invention provides the following technical solution: A method for interpreting nucleic acid amplification results based on multidimensional colorimetric analysis includes the following steps: S1: Before the nucleic acid amplification reaction begins, collect the RGB values ​​of the ambient reflection in the blank reaction chamber or reference area, and establish an ambient background noise compensation model. S2: Collect the initial RGB value of the sample to be tested before the reaction, and correct the initial RGB value according to the environmental background noise compensation model to obtain the initial colorimetric reference of the sample. S3: After performing the nucleic acid amplification reaction and cooling to room temperature, collect the endpoint RGB value after the reaction, and use the same background model for correction to obtain the endpoint colorimetry of the sample; S4: Calculate the multidimensional chromaticity change feature vector of the sample from the initial to the end point. The feature vector includes the normalized change rate of the green channel, the CIE color difference value, and the change rate of the red-green ratio. S5: Based on the multidimensional feature vector and environmental compensation data, calculate the comprehensive evaluation score and adaptive dynamic threshold, and determine the positive or negative status of the sample based on the comprehensive evaluation score and adaptive dynamic threshold.

[0009] Furthermore, the environmental background noise compensation model described in step S1 is corrected using the following formula:

[0010] in, For the original readings, The environmental reflection noise component of the polymethyl methacrylate interface under the current environment. The calibration constant is for the standard black and white card.

[0011] Furthermore, the normalized rate of change of the green channel mentioned in step S4 The calculation is as follows:

[0012] in and The first measurement R , G , B Value and the second measurement obtained R , G , B value.

[0013] Furthermore, the CIE color difference value calculation steps in step S4 are as follows: The corrected RGB values ​​( Convert to CIE XYZ tristimulus values

[0014] Where M is obtained based on the spectral response of the .TCS34725 sensor and calibration using a standard light source. Transformation matrix; Convert XYZ to Uniform color space:

[0015]

[0016]

[0017] in The coordinates of the white point of the standard illuminator; function Defined as:

[0018] Calculate the color difference ΔE before and after the reaction: .

[0019] Furthermore, the formula for calculating the rate of change of the red-green ratio in step S4 is as follows:

[0020] in The values ​​of the red and green channels before the reaction were corrected. These are the red and green channel values ​​after the calibrated reaction.

[0021] Furthermore, the comprehensive evaluation score mentioned in step S5 is combined with... and Constructing a weighted scoring system:

[0022] in These are empirical weighting coefficients. , .

[0023] Furthermore, the adaptive dynamic threshold algorithm in step S5 is based on the distribution of historical detection data, and uses K-means clustering or the maximum inter-class variance method to learn the score distribution of negative control and weak positive control samples online; the environmental compensation data includes environmental background reflection noise components and / or initial brightness features before the reaction; when the comprehensive evaluation score in the multidimensional composite feature vector exceeds the adaptive dynamic threshold, it is judged as positive, otherwise it is judged as negative.

[0024] The beneficial effects of this invention are as follows: (1) By introducing a background noise compensation model for polymethyl methacrylate material and light source, environmental reflection interference is effectively eliminated, so that the equipment can still maintain high accuracy in non-dark room and strong reflective conditions, and improve the robustness of result interpretation and environmental adaptability.

[0025] (2) Using a multidimensional color space (including changes in brightness, hue and saturation) to replace the single green channel for judgment effectively captures subtle color shifts that are difficult to detect by the naked eye and traditional single-channel algorithms, improves the sensitivity of weak positive detection, and reduces the false negative rate of low-concentration samples.

[0026] (3) The dynamic threshold algorithm is used to replace the fixed threshold of the existing technology, which solves the reference drift problem caused by the aging and decay of the light source or the color development difference of different batches of calcium chlorophyll reagent, and significantly extends the calibration-free maintenance cycle of the equipment.

[0027] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0028] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein: Figure 1 This is a schematic diagram illustrating the detection principle of a nucleic acid amplification result interpretation method based on multidimensional colorimetric analysis. Figure 2 This is a flowchart of a method for interpreting nucleic acid amplification results based on multidimensional colorimetric analysis. Detailed Implementation

[0029] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0030] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0031] In the following description, numerous details are explored to provide a more thorough explanation of embodiments of the invention. However, it will be apparent to those skilled in the art that embodiments of the invention may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring embodiments of the invention.

[0032] Example 1: like Figure 1-2 As shown, this invention provides a method for interpreting nucleic acid amplification results based on multidimensional colorimetric analysis. In this embodiment, it is applied to an integrated nucleic acid diagnostic device comprising a TCS34725 color sensor, a white reference light source, a microprocessor, and a polymethyl methacrylate reaction chamber, and includes the following steps: Step 1: Before the nucleic acid amplification reaction starts, the microprocessor controls the TCS34725 sensor to acquire the initial environmental reflectance RGB values ​​of the blank reaction chamber or the pre-placed silicone reference area. A background noise model was established. This model was used to remove the fixed bias caused by reflection of the light source at the polymethyl methacrylate interface.

[0033] Step 2: Before the sample is injected and isothermal amplification begins, collect the first RGB value of the mixed solution in the reaction chamber. The background noise model is used to perform homomorphic filtering correction on the first RGB value to obtain the corrected reference chromaticity coordinates characterizing the initial true color of the solution. ).

[0034] Step 3: After the isothermal amplification reaction is completed and cooled to room temperature, collect the second RGB value of the solution in the reaction chamber. ), and use the background noise model to perform correction according to the same rules to obtain the corrected endpoint chromaticity coordinates ( ).

[0035] Step 4: Calculate the corrected colorimetric change. , , .

[0036] Construct a multidimensional composite feature vector, which includes: Main sensitivity characteristic: Normalized rate of change of green channel The main characteristics used to capture the calcein response; main sensitivity characteristics The calculations include:

[0037] Auxiliary discrimination feature: Color difference value in CIE color space Used to quantify color distance perceived by the human eye; The calculation of color difference formula includes the following sub-steps: The corrected RGB values ​​( Convert to CIE XYZ tristimulus values

[0038] Where M is obtained based on the spectral response of the .TCS34725 sensor and calibration using a standard light source. The transformation matrix, the specific values ​​of which are obtained from factory calibration or white balance calibration.

[0039] Convert XYZ to Uniform color space

[0040]

[0041]

[0042] in The coordinates of the white point of the standard illuminator are given; the function f(t) is defined as:

[0043] Calculate the color difference ΔE before and after the reaction.

[0044] Suppression of interference characteristics: rate of change of red-green ratio This is used to identify false brightness changes caused by the reflection of polymethyl methacrylate (PMMA). The rate of change in red-green ratio. Calculate using the following formula:

[0045] in The values ​​of the red and green channels before the reaction were corrected. These are the corrected red and green channel values ​​after the reaction. This indicator quantifies the relative decrease in the red / green ratio: in a positive reaction, red weakens and green strengthens, resulting in a decrease in the R / G ratio. The value is positive; however, the overall brightness change caused by the reflection or bubbles of polymethyl methacrylate does not significantly alter the R / G ratio. The value approaches 0, thus effectively suppressing false positive interference.

[0046] Step 5: The microprocessor executes an adaptive threshold algorithm. This algorithm is based on the initial brightness features obtained in Step 2 ( ) and ambient light reference value ( The positive / negative threshold for this test is dynamically calculated using a preset mapping function. When the comprehensive evaluation score in the multidimensional composite feature vector exceeds the dynamic threshold, it is judged as positive; otherwise, it is judged as negative.

[0047] The comprehensive evaluation score is combined with and Constructing a weighted scoring system:

[0048] in These are empirical weighting coefficients. , .

[0049] The adaptive dynamic threshold algorithm, based on historical detection data distribution, uses K-means clustering or the maximum inter-class variance method to learn the score distribution of negative and weakly positive control samples online. This algorithm can adjust the threshold based on the current light source illuminance level (as determined by...). (Characteristics) Automatically adjust the segmentation threshold: When the ambient light is dim, the threshold is automatically lowered to prevent weak positives from being missed; when the chip reflection is strong, the threshold is automatically raised to suppress false positives.

[0050] Example 2: This embodiment uses LAMP amplification detection of African swine fever virus plasmid samples as an example, and the detection device is the INARDD portable nucleic acid diagnostic instrument described in the background paper. The hardware of this device includes: a TCS34725 color sensor, an STM32F103 microprocessor, a standard white light source, and a microfluidic chip made of polymethyl methacrylate (5mm thick cavity layer + 1mm cover plate layer).

[0051] Step 1: The microprocessor drives the TCS34725 sensor to read the pre-set blank calibration cavity on the microfluidic chip. It obtains the polymethyl methacrylate (PMMA) reflectance reference value under the current environment. For example, with conventional indoor lighting and a superimposed light source on, the measured environmental reflectance noise baseline is... The microprocessor stores this set of values ​​as the system noise floor.

[0052] Step 2: Add 10 μL of the sample to be tested and the amplification reagent into the reaction chamber. Before the heating module is activated, the color sensor reads the initial color value of the reaction solution. Assume the read value is... The solution appears orange. The microprocessor executes a background noise subtraction algorithm: (Assuming) ), to obtain the true initial chromaticity value.

[0053] Step 3: The temperature control module maintains a heating temperature of 55℃ for 50 minutes. After the reaction is complete, the color sensor reads the value again. If the sample is positive, the solution turns yellow-green due to the complexation of calcein and magnesium ions, and the reading is [value missing]. .

[0054] Step 4: The microprocessor calculates the change ratio for each channel. In addition to calculating the conventional... In addition to the changes, a comprehensive evaluation score was introduced. Empirical weighting coefficient Take values ​​of 0.6, 0.2, and 0.2 respectively.

[0055] Calculate the change in the proportion of green channels Approximately 32%; Calculate color difference Approximately 15; Calculate the rate of change of the red-green ratio Approximately 42%.

[0056] Overall evaluation score .

[0057] Step 5: Set the traditional fixed threshold method as follows If this fixed threshold is applied directly, in this embodiment... A value of only 32 will lead to missed detections (false negatives). In this invention, the microprocessor reads the current ambient light intensity (…). The algorithm determines that the current environment is low-light. Based on the score distribution (mean 15, standard deviation 3) of historical negative control samples under this lighting condition, the adaptive algorithm dynamically sets the judgment threshold to the mean + 3 times the standard deviation. =24.0, the adaptive algorithm automatically lowers the dynamic threshold to Since the comprehensive evaluation score calculated by this invention is 30.6, which is greater than the dynamic threshold of 24, the system accurately determines that the sample is positive and outputs the result on the display screen.

[0058] In summary, this invention, while retaining INARDD's existing mature and low-cost hardware architecture, solves the accuracy bottleneck of colorimetric LAMP under weak positive interpretation and ambient light interference through multi-dimensional colorimetric analysis and dynamic threshold compensation at the algorithm level, and significantly improves the reliability of rapid on-site diagnosis.

[0059] Example 3: An electronic device, comprising a memory and a processor; The memory is used to store computer programs; The processor is configured to implement the method described in Embodiment 1 when executing the computer program.

[0060] Example 4: A computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described in Embodiment 1.

[0061] Example 5: A computer program product includes a computer program that, when executed by a processor, implements the method described in Example 1.

[0062] In the above embodiments, the reference to "this embodiment" in the specification indicates that a specific feature, structure, or characteristic described in connection with the embodiment is included in at least some embodiments, but not necessarily all embodiments. Multiple appearances of "this embodiment" do not necessarily refer to the same embodiment.

[0063] In the above embodiments, although the invention has been described in conjunction with specific embodiments thereof, many substitutions, modifications, and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory structures (e.g., dynamic RAM (DRAM)) may be used with the embodiments discussed. The embodiments of the invention are intended to cover all such substitutions, modifications, and variations falling within the broad scope of the appended claims.

[0064] As will be understood by those skilled in the art, the computer-readable storage medium described in this embodiment allows for the implementation of all or part of the steps in the above method embodiments by computer program-related hardware. The aforementioned computer program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0065] The electronic terminal provided in this embodiment includes a processor, a memory, a transceiver, and a communication interface. The memory and the communication interface are connected to the processor and the transceiver and complete communication between them. The memory is used to store computer programs, the communication interface is used to perform communication, and the processor and the transceiver are used to run the computer programs, so that the electronic terminal performs the steps of the above method.

[0066] In this embodiment, the memory may include random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device.

[0067] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0068] This invention can be used in a wide range of general-purpose or special-purpose computing system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices, etc.

[0069] This invention can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This invention can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0070] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for interpreting nucleic acid amplification results based on multidimensional colorimetric analysis, characterized in that: Includes the following steps: S1: Before the nucleic acid amplification reaction begins, collect the RGB values ​​of the ambient reflection in the blank reaction chamber or reference area, and establish an ambient background noise compensation model. S2: Collect the initial RGB value of the sample to be tested before the reaction, and correct the initial RGB value according to the environmental background noise compensation model to obtain the initial colorimetric reference of the sample; S3: After performing the nucleic acid amplification reaction and cooling to room temperature, collect the endpoint RGB value after the reaction, and correct it using the same background model to obtain the endpoint colorimetry of the sample; S4: Calculate the multidimensional chromaticity change feature vector of the sample from the initial to the end point. The feature vector includes the normalized change rate of the green channel, the CIE color difference value, and the change rate of the red-green ratio. S5: Based on the multidimensional feature vector and environmental compensation data, calculate the comprehensive evaluation score and adaptive dynamic threshold, and determine the positive or negative status of the sample based on the comprehensive evaluation score and adaptive dynamic threshold.

2. The method for interpreting nucleic acid amplification results based on multidimensional colorimetric analysis according to claim 1, characterized in that: The environmental background noise compensation model described in step S1 is corrected using the following formula: in, For the original readings, The environmental reflection noise component of the polymethyl methacrylate interface under the current environment. The calibration constant is for the standard black and white card.

3. The method for interpreting nucleic acid amplification results based on multidimensional colorimetric analysis according to claim 1, characterized in that: The normalized rate of change of the green channel mentioned in step S4 The calculation is as follows: in and The first measurement R , G , B Value and the second measurement obtained R , G , B value.

4. The method for interpreting nucleic acid amplification results based on multidimensional colorimetric analysis according to claim 3, characterized in that: The CIE color difference value calculation steps in step S4 are as follows: The corrected RGB values ​​( Convert to CIE XYZ tristimulus values Where M is obtained based on the spectral response of the .TCS34725 sensor and calibration using a standard light source. Transformation matrix; Convert XYZ to Uniform color space: in The coordinates of the white point of the standard illuminator; function Defined as: Calculate the color difference ΔE before and after the reaction: 。 5. The method for interpreting nucleic acid amplification results based on multidimensional colorimetric analysis according to claim 4, characterized in that: The formula for calculating the rate of change of the red-green ratio in step S4 is as follows: in The values ​​of the red and green channels before the reaction were corrected. These are the red and green channel values ​​after the calibrated reaction.

6. The method for interpreting nucleic acid amplification results based on multidimensional colorimetric analysis according to claim 5, characterized in that: The comprehensive evaluation score mentioned in step S5 is combined with... and Constructing a weighted scoring system: in These are empirical weighting coefficients. , .

7. The method for interpreting nucleic acid amplification results based on multidimensional colorimetric analysis according to claim 1, characterized in that: The adaptive dynamic threshold algorithm described in step S5 is based on the distribution of historical detection data and uses K-means clustering or the maximum inter-class variance method to learn the score distribution of negative control and weak positive control samples online; the environmental compensation data includes environmental background reflection noise components and / or initial brightness features before the reaction; when the comprehensive evaluation score in the multidimensional composite feature vector exceeds the adaptive dynamic threshold, it is judged as positive, otherwise it is judged as negative.

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