Microsphere intelligent analysis method and device
By analyzing the central overlap between the microspheres and the spot in the flow cytometer and screening the preferred microspheres, the problem of inaccurate detection results caused by insufficient overlap between the microspheres and the spot is solved, and the accuracy of the flow cytometer detection results is improved.
Patent Information
- Application Number
- CN202510155557.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-02-12
- Publication Date
- 2025-05-02
AI Technical Summary
In flow cytometry, the overlap between the microsphere and the center of the spot is insufficient, which affects the accuracy of the detection result data, especially when the single-cell fluid fluctuates greatly.
By obtaining the microsphere correlation information during the light spot of each microsphere, analyzing the center overlap between the microsphere and the light spot, and screening out the preferred microspheres with higher overlap for analysis to improve the accuracy of the detection results.
By screening the preferred microspheres, the impact of single-cell flow fluctuations on the detection results can be eliminated to a certain extent, thereby improving the accuracy of the flow cytometry detection results data.
Smart Images
Figure CN119915705A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of flow cytometry, and in particular to a microsphere intelligent analysis method and device. Background Art
[0002] The working principle of flow cytometer is to make the cells or other biological particles to be tested pass through the liquid flow system to form a single-cell liquid flow, and through the irradiation of the laser beam, it produces scattered light and fluorescence. These light signals will be captured by the optical system and converted into electrical signals, and then amplified and digitized by the electronic system. Finally, the data processing system will analyze these data to obtain information on the physical and biological characteristics of cells or other biological particles, such as cell size, shape, DNA content, protein expression, etc.
[0003] During the operation of the flow cytometer, the laser beam will be focused in the single-cell liquid flow to form a light spot. Ideally, when the microspheres in the single-cell liquid flow pass through the light spot, the center of the microspheres should overlap with the center of the light spot to ensure better excitation of the microspheres, which is beneficial to improve the accuracy of the test results. Summary of the invention
[0004] The present application provides a microsphere intelligent analysis method and device, which can analyze the microspheres in a flow cytometer, which is beneficial to improving the accuracy of the flow cytometer detection result data.
[0005] In a first aspect, the present application provides a microsphere intelligent analysis method. The method comprises: Acquire microsphere-related information of each microsphere when it passes through the light spot, wherein the microsphere-related information includes one or more of forward scattered light, side scattered light, and microsphere fluorescence value; Analyze the center overlap between each microsphere and the light spot based on the microsphere association information; Based on the center overlap, preferred microspheres are determined among all microspheres, and the preferred microspheres are used for analysis to obtain detection result data.
[0006] By adopting the above technical scheme, the center overlap degree of the microsphere and the light spot can be determined based on the microsphere association information of each microsphere in the process of passing through the light spot, so as to screen out the preferred microspheres with better overlap. Using the preferred microspheres to analyze the test result data is beneficial for the test result data to avoid the influence of single-cell liquid flow fluctuations to a certain extent, thereby helping to improve the accuracy of the flow cytometer test result data.
[0007] Further, analyzing the center overlap between each microsphere and the light spot based on the microsphere association information includes: Analyze the first scattered light distribution data of the forward scattered light of each microsphere in the process of passing through the light spot; The first sub-overlap is determined according to the first scattered light distribution data, the center overlap is positively correlated with the first sub-overlap, and the first sub-overlap is positively correlated with the distribution stability, and / or distribution symmetry, and / or distribution predictability of the first scattered light distribution data.
[0008] Further, determining the first sub-overlap degree according to the first scattered light distribution data includes: Determine the forward spectrum peak value, the forward spectrum valley value, the forward spectrum peak width, the forward spectrum coefficient of variation, the forward spectrum distribution skewness, the forward spectrum distribution mean, the microsphere forward passage time and the forward spectrum sudden change moment of the forward scattered light according to the first scattered light distribution data; Assume that the forward spectrum peak is The forward spectrum valley is , the forward spectrum peak width is , the coefficient of variation of the forward spectrum is , the forward spectral distribution skewness is , the mean of the front spectral distribution is , the forward transit time of the microsphere is , the forward spectrum suddenly changes at , the first sub-overlap degree is ,but ; ; ; ; ; ; ; In the formula, is the expected forward spectrum mean of the i-th preset coded microsphere, is the expected time for the i-th preset coded microsphere to pass through the light spot, are the start time and end time of the current microsphere passing through the light spot, All are pre-acquired preset calculation weights greater than zero.
[0009] Furthermore, analyzing the center overlap between each microsphere and the light spot based on the microsphere association information further includes: Analyze the second scattered light distribution data of the side scattered light of each microsphere when it passes through the light spot and the fluorescence distribution data of the fluorescence value of the microsphere; determining a scattered light ratio distribution curve by combining the second scattered light distribution data and the first scattered light distribution data; Analyzing the ratio distribution curve to determine a second sub-overlapping degree, wherein the second sub-overlapping degree is positively correlated to the stability of the ratio distribution curve; Analyzing the fluorescence distribution data to determine a third sub-overlapping degree, wherein the third sub-overlapping degree is positively correlated to the stability of the fluorescence distribution data; The center overlap is also positively correlated to the second sub-overlap and the third sub-overlap.
[0010] Further, analyzing the ratio distribution curve to determine the second sub-overlap degree includes: Obtain the coefficient of variation, maximum rate of change, and cumulative duration of the scattered light ratio distribution curve exceeding a preset ratio range; Assume that the coefficient of variation of the scattered light ratio distribution curve is , the maximum rate of change is , the cumulative duration exceeding the preset ratio range is , the second sub-overlap degree is ,but ; In the formula, All are pre-acquired preset calculation weights greater than zero.
[0011] Further, analyzing the fluorescence distribution data to determine the third sub-overlap degree includes: Obtain the coefficient of variation of fluorescence distribution data; The third sub-overlapping degree is determined according to the coefficient of variation of the fluorescence distribution data, and the third sub-overlapping degree is negatively correlated to the coefficient of variation of the fluorescence distribution data.
[0012] Furthermore, analyzing the center overlap between each microsphere and the light spot based on the microsphere association information further includes: Based on the pre-acquired sub-overlapping weights, a weighted average of the first sub-overlapping, the second sub-overlapping and the third sub-overlapping is calculated as the central overlap.
[0013] Further, the determining of the preferred microsphere among all microspheres based on the center overlap comprises: The microspheres whose center overlap is higher than a preset overlap threshold are determined as preferred microspheres.
[0014] In a second aspect, the present application provides a microsphere intelligent analysis device, which is used to perform any one of the methods described in the first aspect.
[0015] In summary, this application at least has the following beneficial effects: Provided is a microsphere intelligent analysis method and device, which can eliminate the influence of single-cell liquid flow fluctuation on flow cytometer detection results to a certain extent through an algorithm, thereby facilitating improving the accuracy of the detection results.
[0016] It should be understood that the contents described in the Summary of the Invention are not intended to limit the key or important features of the embodiments of the present application, nor are they intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS
[0017] The above and other features, advantages and aspects of the embodiments of the present application will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, wherein: Figure 1 A flow chart of a microsphere intelligent analysis method in an embodiment of the present application is shown. DETAILED DESCRIPTION
[0018] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.
[0019] In addition, the term "and / or" in this article is only a description of the association relationship between the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.
[0020] The present application provides a microsphere intelligent analysis method and device, which can screen and use microspheres that are less affected by single-cell fluid flow fluctuations to analyze test results, which is beneficial to improving the accuracy of flow cytometer test results.
[0021] In a first aspect, the present application discloses a microsphere intelligent analysis method, which can be performed by a flow cytometer and is targeted at a whole microsphere group. Generally speaking, a whole microsphere group corresponds to one detection or experiment.
[0022] Figure 1 A flow chart of a microsphere intelligent analysis method in an embodiment of the present application is shown.
[0023] Reference Figure 1 , the method specifically comprises: S110: Acquire microsphere association information of each microsphere when it passes through the light spot.
[0024] In the embodiment of the present application, the light spot refers to the light spot formed by the focusing of the laser beam in the flow cytometer, and the microsphere refers to the cell to be tested or other biological particles in the flow cytometer. The single-cell liquid flow can basically ensure that a single microsphere passes through the light spot in turn, and after being excited by the light spot of the laser beam, forward scattered light, side scattered light and fluorescence are generated. The forward scattered light, side scattered light and fluorescence can be captured by the optical system of the flow cytometer and converted into electrical signals.
[0025] In the method of this step, the microsphere-related information includes one or more of forward scattered light, side scattered light, and microsphere fluorescence. The forward scattered light, side scattered light, and microsphere fluorescence mentioned here are all converted electrical signals.
[0026] S120: Analyze the center overlap between each microsphere and the light spot based on the microsphere association information.
[0027] The method of this step specifically includes: analyzing the first scattered light distribution data of the forward scattered light of each microsphere passing through the light spot; determining the first sub-overlapping degree according to the first scattered light distribution data, the center overlap degree is positively correlated with the first sub-overlapping degree, and the first sub-overlapping degree is positively correlated with the distribution stability, and / or distribution symmetry, and / or distribution predictability of the first scattered light distribution data.
[0028] In one example, determining the first sub-overlap degree according to the first scattered light distribution data includes: determining the forward spectrum peak value, the forward spectrum valley value, the forward spectrum peak width (the width of the signal intensity distribution), the forward spectrum coefficient of variation, the forward spectrum distribution skewness, the forward spectrum distribution mean, the microsphere forward passage time and the forward spectrum sudden change moment of the forward scattered light according to the first scattered light distribution data; assuming that the forward spectrum peak value is The forward spectrum valley is , the forward spectrum peak width is , the coefficient of variation of the forward spectrum is , the forward spectral distribution skewness is , the mean of the front spectral distribution is , the forward transit time of the microsphere is , the forward spectrum suddenly changes at , the first sub-overlap degree is ,but ; ; ; ; ; ; ; In the formula, is the expected forward spectrum mean of the i-th preset coded microsphere, is the expected time for the i-th preset coded microsphere to pass through the light spot, are the start time and end time of the current microsphere passing through the light spot, All are pre-acquired preset calculation weights greater than zero.
[0029] The method of this step may also include: analyzing the second scattered light distribution data of the side scattered light of each microsphere passing through the light spot and the fluorescence distribution data of the microsphere fluorescence value; determining the scattered light ratio distribution curve by combining the second scattered light distribution data and the first scattered light distribution data; analyzing the ratio distribution curve to determine the second sub-overlapping degree, and the second sub-overlapping degree is positively correlated to the stability of the ratio distribution curve; analyzing the fluorescence distribution data to determine the third sub-overlapping degree, and the third sub-overlapping degree is positively correlated to the stability of the fluorescence distribution data; the center overlap is also positively correlated to the second sub-overlapping degree and the third sub-overlapping degree.
[0030] In one example, analyzing the ratio distribution curve to determine the second sub-overlap degree includes: obtaining the coefficient of variation, the maximum change rate, and the cumulative duration exceeding the preset ratio range of the scattered light ratio distribution curve; assuming that the coefficient of variation of the scattered light ratio distribution curve is , the maximum rate of change is , the cumulative duration exceeding the preset ratio range is , the second sub-overlap degree is ,but ; In the formula, All are pre-acquired preset calculation weights greater than zero.
[0031] In one example, analyzing the fluorescence distribution data to determine the third sub-overlapping degree includes: obtaining the coefficient of variation of the fluorescence distribution data; determining the third sub-overlapping degree according to the coefficient of variation of the fluorescence distribution data, wherein the third sub-overlapping degree is negatively correlated to the coefficient of variation of the fluorescence distribution data. Specifically, assuming that the third sub-overlapping degree is , the coefficient of variation of the fluorescence distribution data is ,but , where The calculated weight for prefetching that is greater than zero.
[0032] The method of this step specifically further includes: based on the pre-acquired sub-overlap weights, calculating a weighted average of the first sub-overlap, the second sub-overlap and the third sub-overlap as the central overlap.
[0033] It should be understood that in the above content, when determining the center overlap, the distribution stability (related parameters are the forward spectrum peak value, the forward spectrum valley value, and the forward spectrum variation coefficient) of the forward scattered light of the microspheres, the distribution symmetry (related parameters are the forward spectrum distribution skewness) and the distribution expectancy (related parameters are the forward spectrum distribution mean, the forward transit time of the microspheres, and the forward spectrum sudden change moment) are comprehensively considered, as well as the distribution stability of the ratio of the side scattered light to the forward scattered light, and the distribution stability of the microsphere fluorescence value. For the above factors, only one or a combination of several of them can be considered, or other parameters that reflect the distribution stability, distribution symmetry and distribution expectancy of the forward scattered light, side scattered light and fluorescence of the microspheres can also be considered. Other examples are not listed here one by one.
[0034] S130: Determine preferred microspheres among all microspheres based on the center overlap, and use the preferred microspheres for analysis to obtain detection result data.
[0035] The method of this step specifically includes: determining the microspheres with a central overlap higher than a preset overlap threshold as preferred microspheres. After determining the preferred microspheres, the preferred microspheres are used to analyze the test result data. The analysis process here is consistent with the analysis process using the entire microsphere group, so the analysis process is not described in detail. The test result data analyzed only using the preferred microspheres has statistical significance, can represent the entire microsphere group, and can eliminate the influence of single-cell flow fluctuations on the test results to a certain extent.
[0036] In summary, this method can analyze the center overlap between microspheres and light spots based on the self-developed microsphere screening model, and use the preferred microspheres, i.e., microspheres with higher center overlap, to analyze the test result data. It can not only represent the analysis results of the entire microsphere group, but also eliminate the influence of single-cell liquid flow fluctuations on the test result data, which is beneficial to improve the accuracy of flow cytometer test results.
[0037] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the embodiments of the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present application.
[0038] In a second aspect, the present application discloses a microsphere intelligent analysis device, which is used to perform any of the methods disclosed in the first aspect.
[0039] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the described device and flow cytometer can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.
[0040] In summary, this application at least has the following beneficial effects: Provided is a microsphere intelligent analysis method and device, which can eliminate the influence of single-cell liquid flow fluctuation on flow cytometer detection results to a certain extent through an algorithm, thereby facilitating improving the accuracy of the detection results.
[0041] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the aforementioned disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in this application (but not limited to) by each other to form a technical solution.
Claims
1. A microsphere intelligent analysis method, characterized in that: include: Acquire microsphere-related information of each microsphere when it passes through the light spot, wherein the microsphere-related information includes one or more of forward scattered light, side scattered light, and microsphere fluorescence value; Analyze the center overlap between each microsphere and the light spot based on the microsphere association information; Based on the center overlap, preferred microspheres are determined among all microspheres, and the preferred microspheres are used for analysis to obtain detection result data.
2. The method according to claim 1, characterized in that: Analyzing the center overlap between each microsphere and the light spot based on the microsphere association information includes: Analyze the first scattered light distribution data of the forward scattered light of each microsphere in the process of passing through the light spot; The first sub-overlap is determined according to the first scattered light distribution data, the center overlap is positively correlated with the first sub-overlap, and the first sub-overlap is positively correlated with the distribution stability, and / or distribution symmetry, and / or distribution predictability of the first scattered light distribution data.
3. The method according to claim 2, characterized in that Determining the first sub-overlapping degree according to the first scattered light distribution data comprises: Determine the forward spectrum peak value, the forward spectrum valley value, the forward spectrum peak width, the forward spectrum coefficient of variation, the forward spectrum distribution skewness, the forward spectrum distribution mean, the microsphere forward passage time and the forward spectrum sudden change moment of the forward scattered light according to the first scattered light distribution data; Assume that the forward spectrum peak is The forward spectrum valley value is , the forward spectrum peak width is , the coefficient of variation of the forward spectrum is , the forward spectral distribution skewness is , the mean of the front spectral distribution is , the forward passage time of the microsphere is , the forward spectrum suddenly changes at , the first sub-overlap degree is ,but ； ； ； ； ； ； ； In the formula, is the expected forward spectrum mean of the i-th preset coded microsphere, is the expected time for the i-th preset coded microsphere to pass through the light spot, are the start time and end time of the current microsphere passing through the light spot, All are pre-acquired preset calculation weights greater than zero.
4. The method according to claim 2, characterized in that: The analyzing the center overlap between each microsphere and the light spot based on the microsphere association information further includes: Analyze the second scattered light distribution data of the side scattered light of each microsphere when it passes through the light spot and the fluorescence distribution data of the fluorescence value of the microsphere; determining a scattered light ratio distribution curve by combining the second scattered light distribution data and the first scattered light distribution data; Analyzing the ratio distribution curve to determine a second sub-overlapping degree, wherein the second sub-overlapping degree is positively correlated to the stability of the ratio distribution curve; Analyzing the fluorescence distribution data to determine a third sub-overlapping degree, wherein the third sub-overlapping degree is positively correlated to the stability of the fluorescence distribution data; The center overlap is also positively correlated to the second sub-overlap and the third sub-overlap.
5. The method according to claim 4, characterized in that Analyzing the ratio distribution curve to determine the second sub-overlap degree comprises: Obtain the coefficient of variation, maximum rate of change, and cumulative duration of the scattered light ratio distribution curve exceeding a preset ratio range; Assume that the coefficient of variation of the scattered light ratio distribution curve is , the maximum rate of change is , the cumulative duration exceeding the preset ratio range is , the second sub-overlap degree is ,but ； In the formula, All are pre-acquired preset calculation weights greater than zero.
6. The method according to claim 4, characterized in that The analyzing the fluorescence distribution data to determine the third sub-overlapping degree comprises: Obtain the coefficient of variation of fluorescence distribution data; The third sub-overlapping degree is determined according to the coefficient of variation of the fluorescence distribution data, and the third sub-overlapping degree is negatively correlated to the coefficient of variation of the fluorescence distribution data.
7. The method according to any one of claims 4 to 6, characterized in that: The analyzing the center overlap between each microsphere and the light spot based on the microsphere association information further includes: Based on the pre-acquired sub-overlapping weights, a weighted average of the first sub-overlapping, the second sub-overlapping and the third sub-overlapping is calculated as the central overlap.
8. The method according to claim 1, characterized in that Determining the preferred microsphere among all microspheres based on the center overlap comprises: The microspheres whose center overlap is higher than a preset overlap threshold are determined as preferred microspheres.
9. A microsphere intelligent analysis device, characterized in that: Used to perform the method according to any one of claims 1 to 8.