Information processing method and system for flow cytometer and flow cytometer
By obtaining and separating different parts of the blank noise signal in a flow cytometer and calculating their standard variance to determine the blank detection limit, the problem of difficulty in accurately determining the blank detection limit in the prior art is solved, and the ability to distinguish between background noise and sample signals is improved.
Patent Information
- Application Number
- CN202311470346.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-11-07
- Publication Date
- 2025-05-09
AI Technical Summary
The prior art is difficult to accurately determine the blank detection limit of flow cytometry, resulting in difficult distinction between background noise and sample signals.
By acquiring the blank noise signal without fluid flow, the first part whose signal intensity is less than the predetermined signal intensity and the second part whose signal intensity is greater than or equal to the predetermined signal intensity are separated, the standard variance of the second part is calculated, and the blank detection limit of the flow cytometer is determined based on this.
More accurate determination of blank detection limits is achieved, which reduces the misjudgment of background noise and improves the recognition accuracy of sample signals.
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Figure CN119959112A_ABST
Abstract
Description
Technical Field
[0001] The present disclosure relates to the technical field of flow cytometry detection, and in particular to an information processing method and system for a flow cytometer and a flow cytometer. Background Art
[0002] For flow cytometry, determining the limit of blank is important to determine background noise and sample signal. Summary of the invention
[0003] A brief overview of the disclosure is given below in order to provide a basic understanding of certain aspects of the disclosure. However, it should be understood that this overview is not an exhaustive overview of the disclosure. It is not intended to identify the key or important parts of the disclosure, nor is it intended to limit the scope of the disclosure. Its purpose is simply to give certain concepts of the disclosure in a simplified form as a prelude to a more detailed description given later.
[0004] In view of the above, an object of the present disclosure is to provide an improved information processing method and system for a flow cytometer and a flow cytometer, so as to determine the blank detection limit of the flow cytometer, etc.
[0005] According to one aspect of the present disclosure, there is provided an information processing method for a flow cytometer, comprising: obtaining a blank noise signal in the absence of fluid flow, the blank noise signal comprising a first part and a second part, the signal intensity of the first part being less than a predetermined signal intensity, and the signal intensity of the second part being greater than or equal to the predetermined signal intensity; obtaining a standard deviation of the second part; and determining a blank detection limit of the flow cytometer based on the standard deviation. The predetermined signal intensity is the signal intensity corresponding to the peak value of the distribution of the blank noise signal in a logarithmic coordinate system.
[0006] According to another aspect of the present disclosure, an information processing system for a flow cytometer is provided, comprising a processing unit, configured to: obtain a blank noise signal in the absence of fluid flow, the blank noise signal comprising a first part and a second part, the signal intensity of the first part being less than a predetermined signal intensity, and the signal intensity of the second part being greater than or equal to the predetermined signal intensity; obtain a standard deviation of the second part; and determine a blank detection limit of the flow cytometer based on the standard deviation. The predetermined signal intensity is the signal intensity corresponding to the peak value of the distribution of the blank noise signal in a logarithmic coordinate system.
[0007] According to yet another aspect of the present disclosure, a flow cytometer including the above-mentioned information processing system is provided.
[0008] According to other aspects of the present disclosure, a computer program code and a computer program product for implementing the information processing method according to the present disclosure are also provided, as well as a computer-readable storage medium having the computer program code for implementing the method according to the present disclosure recorded thereon.
[0009] Other aspects of the embodiments of the present disclosure are given in the following description, wherein the detailed description is used to fully disclose the preferred embodiments of the embodiments of the present disclosure without imposing limitations thereon. BRIEF DESCRIPTION OF THE DRAWINGS
[0010] The present disclosure may be better understood by referring to the detailed description given below in conjunction with the accompanying drawings, wherein the same or similar reference numerals are used throughout the drawings to represent the same or similar components. The accompanying drawings, together with the following detailed description, are included in and form a part of the present specification to further illustrate the preferred embodiments of the present disclosure and to explain the principles and advantages of the present disclosure. Among them:
[0011] Figure 1 is a flowchart showing an example of the process of an information processing method for a flow cytometer according to an embodiment of the present disclosure;
[0012] Figure 2A and Figure 2B is a diagram showing an example of distribution of a blank noise signal;
[0013] Figure 3 is a block diagram showing a configuration example of an information processing system for a flow cytometer according to an embodiment of the present disclosure; and
[0014] Figure 4 : is a block diagram showing an example structure of a personal computer that can be employed in the embodiments of the present disclosure. DETAILED DESCRIPTION
[0015] Exemplary embodiments of the present disclosure will be described below in conjunction with the accompanying drawings. For the sake of clarity and conciseness, not all features of the actual implementation are described in the specification. However, it should be understood that many implementation-specific decisions must be made in the process of developing any such actual implementation in order to achieve the developer's specific goals, such as meeting those constraints related to the system and business, and these constraints may vary from implementation to implementation. In addition, it should be understood that although the development work may be very complex and time-consuming, it is only a routine task for those skilled in the art who benefit from the content of this disclosure.
[0016] It should be understood that although the terms "first", "second", etc. may be used to describe various elements in this article, these elements should not be limited by these terms. These terms are only used to distinguish one element from another element. For example, without departing from the scope of the present disclosure, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element.
[0017] It is also necessary to explain here that in order to avoid obscuring the present disclosure due to unnecessary details, only the device structure and / or processing steps closely related to the scheme according to the present disclosure are shown in the accompanying drawings, while other details that are not closely related to the present disclosure are omitted.
[0018] The embodiments according to the present disclosure are described in detail below with reference to the accompanying drawings.
[0019] First, refer to Figure 1 An implementation example of an information processing method for a flow cytometer according to an embodiment of the present disclosure is described. Figure 1 is a flowchart showing an example of the flow of an information processing method 100 for a flow cytometer according to an embodiment of the present disclosure.
[0020] like Figure 1 As shown, the information processing method 100 according to an embodiment of the present disclosure may start at the start step S102 and end at the end step S110 .
[0021] According to an embodiment of the present disclosure, the information processing method 100 may include: acquiring a blank noise signal (step S104) in the absence of fluid flow (i.e., neither the sheath fluid nor the sample fluid flows); obtaining the standard deviation of the second part included in the blank noise signal (step S106); and determining the blank detection limit of the flow cytometer based on the standard deviation (step S108).
[0022] The blank noise signal acquired in step S104 may include a second part and a first part. The signal strength of the first part may be less than a predetermined signal strength. The signal strength of the second part may be greater than or equal to the predetermined signal strength. The predetermined signal strength is the signal strength corresponding to the peak value of the distribution of the blank noise signal in the logarithmic coordinate system. For example, Figure 2B In the distribution example of the blank noise signal shown, the first part may be located on the left side of the peak value P, and the second part may be located on the right side of the peak value P (including the peak value). For example, the signal strength corresponding to the peak value P may be the signal strength at the peak value P, or may be the signal strength within a predetermined range including the signal strength at the peak value P, for example, Figure 2B As shown by the dotted line in .
[0023] The inventors of the present application converted the blank signal noise obtained through the experiment from the linear coordinate system to the logarithmic coordinate system and found that the distribution of the signal on the left side of the peak in the logarithmic coordinate system is completely different from the distribution of the signal on the right side of the peak. The distribution of the signal on the left side of the peak is uneven, while the distribution of the signal on the right side of the peak is closer to the normal distribution. For example, see Figure 2B , which shows the Figure 2A The blank noise signal distribution example of the linear coordinate system shown in the figure is converted into the blank noise signal distribution in the logarithmic coordinate system. Based on this discovery, the inventors proposed a method for determining the blank detection limit using a portion of the blank noise signal (i.e., the signal or portion thereof located on the right side of the peak). The blank detection limit obtained by this method is less affected by the irregular distribution on the left side of the peak and is therefore more accurate.
[0024] For flow cytometers, background noise includes noise caused by sample lines (e.g., particles, impurities, etc. in sample lines), noise caused by sheath fluid (e.g., particles, impurities, etc. in sheath fluid), noise caused by electronic components, etc. Existing carryover indicators can be used to determine specific sample carryover in flow cytometers, but specific sample carryover only contributes to a portion of the background noise and cannot represent the entire background noise. In addition, carryover indicators can only determine a specific sample carryover. CLSI-EP17-A provides a model for determining background noise, but the model has two defects. First, it relies on the assumption that the distribution of low-level and blank results is symmetrical and normally distributed. In addition, some parameter models make additional assumptions that repeated measurements of low-level samples have the same standard deviation as blank samples. A major drawback of this approach is that the model cannot distinguish between the apparent and true (or actual) concentrations of the analyte. Therefore, the model cannot be used for nanoparticle analyzer systems.
[0025] As described above, in the information processing method 100 according to the present disclosure, the blank detection limit is determined based on the standard deviation of the second part of the blank noise signal, thereby obtaining a more accurate blank detection limit, and a more accurate background noise can be obtained based on the obtained blank detection limit. In addition, the information processing method 100 according to the present disclosure can be applied to a nanoscale analysis system.
[0026] For example, in step S106, the standard deviation of the second part may be obtained by performing Gaussian fitting on the second part.
[0027] As an example, in step S108, the weighted sum of the signal intensity corresponding to the peak value and the standard deviation may be calculated as the blank detection limit.
[0028] As another example, in step S108, the mean or median (not shown) of the blank noise signal (including the first part and the second part) can be determined, and the blank detection limit can be determined based on the mean or median of the blank noise signal and the standard deviation obtained in step S106, thereby further improving the accuracy of the obtained blank detection limit. For example, the blank detection limit LoB can be calculated based on the following formula (1) or (2).
[0029] LoB = Mean B + n *σ B Formula (1)
[0030] LoB = Median B + n *σ B Formula (2)
[0031] In the above formulas (1) and (2), Mean B Represents the mean of the blank noise signal, Median B represents the median value of the blank noise signal, σ B represents the standard deviation obtained in step S106, and n is a coefficient about the standard deviation. Basically, the larger n is, the higher the LoB is, and the lower the probability that a true blank sample gives a value indicating the presence of an analyte is.
[0032] In some examples, n may be between 1 and 10 (inclusive). The inventors have found through experiments that n=9 is more sensitive to detecting background noise.
[0033] As an example, the information processing method 100 may also include: obtaining a first noise signal when no sample flows through a sample line of the flow cytometer and the sheath fluid flows; and determining the purity of the sheath fluid based on the first noise signal and the blank detection limit (not shown). For example, the more the first noise signal exceeds the blank detection limit, the more impurities there are in the sheath fluid and the lower the purity. For example, the purity of the sheath fluid can be monitored based on the first noise signal.
[0034] For example, the information processing method 100 may further include: obtaining a second noise signal when a pure medium flows through a sample line of the flow cytometer and a sheath fluid flows; and determining the sample line noise based on the second noise signal, a blank detection limit, and the purity of the sheath fluid. For example, the pure medium may be pure water, but is not limited thereto.
[0035] For example, background noise can be characterized by blank detection limit, purity of sheath fluid and sample line noise. The information processing method 100 of the present application can more accurately characterize background noise, thereby better distinguishing background noise from sample signals, and further obtaining more accurate sample signals.
[0036] The above has described the information processing method 100 for a flow cytometer according to an embodiment of the present disclosure. Corresponding to the embodiment of the above information processing method 100, the present disclosure further provides the following information processing system 300 for a flow cytometer.
[0037] Figure 3 : is a block diagram showing a configuration example of an information processing system 300 for flow cytometer according to an embodiment of the present disclosure.
[0038] like Figure 3 As shown, the information processing system 300 according to an embodiment of the present disclosure may include a processing unit 302. The processing unit 302 may be configured to: acquire a blank noise signal in the absence of fluid flow (i.e., both the sheath fluid and the sample fluid do not flow); obtain a standard deviation of the second part included in the blank noise signal; and determine a blank detection limit of the flow cytometer based on the standard deviation.
[0039] The blank noise signal acquired by the processing unit 302 may include a second part and a first part. The signal strength of the first part may be less than a predetermined signal strength. The signal strength of the second part may be greater than or equal to a predetermined signal strength. The predetermined signal strength is the signal strength corresponding to the peak value of the distribution of the blank noise signal in a logarithmic coordinate system.
[0040] Similar to the above-mentioned information processing method 100, the information processing system 300 can determine the blank detection limit based on the standard deviation of the second part of the blank noise signal, thereby obtaining a more accurate blank detection limit, and a more accurate background noise can be obtained based on the obtained blank detection limit. In addition, the information processing system 300 according to the present disclosure can be applied to a nanoscale analysis system.
[0041] For example, the processing unit 302 can determine the mean or median of the blank noise signal, and determine the blank detection limit based on the mean or median and the standard deviation of the blank noise signal, thereby further improving the accuracy of the obtained blank detection limit. For example, the processing unit 302 can calculate the blank detection limit based on the above formula (1) or (2).
[0042] As an example, the processing unit 302 may acquire a first noise signal when no sample flows through a sample line of the flow cytometer and the sheath fluid flows, and determine the purity of the sheath fluid based on the first noise signal and a blank detection limit.
[0043] For example, the processing unit 302 may obtain a second noise signal while allowing pure medium to flow through a sample line of the flow cytometer and sheath fluid to flow, and determine the sample line noise based on the second noise signal, the blank detection limit, and the purity of the sheath fluid.
[0044] For example, according to an embodiment of the present disclosure, a flow cytometer including the above-mentioned information processing system 300 may also be provided.
[0045] It should be pointed out that although the above describes the information processing method and information processing system for a flow cytometer and the functional configuration and operation of the flow cytometer according to the embodiments of the present disclosure, this is only an example and not a limitation, and those skilled in the art may modify the above embodiments according to the principles of the present disclosure, for example, the functional modules and operations in each embodiment may be added, deleted or combined, and such modifications shall fall within the scope of the present disclosure.
[0046] In addition, it should be pointed out that the system embodiment here corresponds to the above-mentioned method embodiment. Therefore, for the contents not described in detail in the system embodiment, please refer to the description of the corresponding parts in the method embodiment, and the description will not be repeated here.
[0047] In addition, the present disclosure also provides a storage medium and a program product. It should be understood that the machine-executable instructions in the storage medium and the program product according to the embodiments of the present disclosure can also be configured to execute the above-mentioned information processing method, so the contents not described in detail here can refer to the description of the previous corresponding parts, and will not be repeated here.
[0048] Accordingly, the storage medium for carrying the program product including the machine executable instructions is also included in the disclosure of the present invention, including but not limited to a floppy disk, an optical disk, a magneto-optical disk, a memory card, a memory stick, and the like.
[0049] In addition, it should be noted that the above series of processes and devices can also be implemented by software and / or firmware. In the case of being implemented by software and / or firmware, from a storage medium or a network to a computer with a dedicated hardware structure, such as Figure 4 The general-purpose personal computer 500 shown installs the programs constituting the software, and when the various programs are installed, the computer can execute various functions and the like.
[0050] exist Figure 4 In the embodiment, a central processing unit (CPU) 501 executes various processes according to a program stored in a read only memory (ROM) 502 or a program loaded from a storage section 508 to a random access memory (RAM) 503. In the RAM 503, data required when the CPU 501 executes various processes and the like is also stored as needed.
[0051] The CPU 501, the ROM 502, and the RAM 503 are connected to one another via a bus 504. An input / output interface 505 is also connected to the bus 504.
[0052] The following components are connected to the input / output interface 505: an input section 506 including a keyboard, a mouse, etc.; an output section 507 including a display such as a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN card, a modem, etc. The communication section 509 performs communication processing via a network such as the Internet.
[0053] A drive 510 is also connected to the input / output interface 505 as needed. A removable medium 511 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc. is mounted on the drive 510 as needed so that a computer program read therefrom is installed into the storage section 508 as needed.
[0054] In the case where the above-described series of processing is realized by software, a program constituting the software is installed from a network such as the Internet or a storage medium such as the removable medium 511 .
[0055] It should be understood by those skilled in the art that such storage media is not limited to Figure 4 The removable medium 511 shown has a program stored therein and is distributed separately from the device to provide the program to the user. Examples of the removable medium 511 include magnetic disks (including floppy disks (registered trademark)), optical disks (including compact disk read-only memory (CD-ROM) and digital versatile disks (DVD)), magneto-optical disks (including minidiscs (MD) (registered trademark)), and semiconductor memories. Alternatively, the storage medium may be a ROM 502, a hard disk included in the storage portion 508, or the like, in which the program is stored and distributed to the user together with the device containing them.
[0056] The preferred embodiments of the present disclosure are described above with reference to the accompanying drawings, but the present disclosure is certainly not limited to the above examples. Those skilled in the art may obtain various changes and modifications within the scope of the appended claims, and it should be understood that these changes and modifications will naturally fall within the technical scope of the present disclosure.
[0057] For example, a plurality of functions included in one unit in the above embodiments may be implemented by separate devices. Alternatively, a plurality of functions implemented by a plurality of units in the above embodiments may be implemented by separate devices, respectively. In addition, one of the above functions may be implemented by a plurality of units. Needless to say, such a configuration is included in the technical scope of the present disclosure.
[0058] In this specification, the steps described in the flowchart include not only the processing performed in time series in the order described, but also the processing performed in parallel or individually rather than necessarily in time series. In addition, even in the steps processed in time series, it goes without saying that the order can be appropriately changed.
Claims
1. An information processing method for a flow cytometer, comprising: Acquire a blank noise signal in the absence of fluid flow, the blank noise signal comprising a first part and a second part, the signal strength of the first part being less than a predetermined signal strength, and the signal strength of the second part being greater than or equal to the predetermined signal strength; Obtaining the standard deviation of the second part; as well as Determining the blank detection limit of the flow cytometer based on the standard deviation, The predetermined signal strength is the signal strength corresponding to the peak value of the distribution of the blank noise signal in a logarithmic coordinate system.
2. The information processing method according to claim 1, wherein: Determining the blank detection limit of the flow cytometer includes: The mean or median of the blank noise signal is determined, and the blank detection limit is determined based on the mean or median of the blank noise signal and the standard deviation.
3. The information processing method according to claim 2, comprising: Acquiring a first noise signal when no sample flows through a sample line of the flow cytometer and sheath fluid flows; as well as The purity of the sheath fluid is determined based on the first noise signal and the blank detection limit.
4. The information processing method according to claim 3, comprising: Acquiring a second noise signal while allowing a pure medium to flow through a sample line of the flow cytometer and a sheath fluid to flow; as well as A sample line noise is determined based on the second noise signal, the blank detection limit, and the purity of the sheath fluid.
5. An information processing system for a flow cytometer, comprising a processing unit configured to: Acquire a blank noise signal in the absence of fluid flow, the blank noise signal comprising a first part and a second part, the signal strength of the first part being less than a predetermined signal strength, and the signal strength of the second part being greater than or equal to the predetermined signal strength; Obtaining the standard deviation of the second part; as well as The blank detection limit of the flow cytometer is determined based on the standard deviation, wherein: The predetermined signal strength is the signal strength corresponding to the peak value of the distribution of the blank noise signal in a logarithmic coordinate system.
6. The information processing system according to claim 5, wherein: The processing unit is further configured to determine a mean or a median of the blank noise signal, and determine the blank detection limit based on the mean or the median of the blank noise signal and the standard deviation.
7. The information processing system according to claim 6, wherein: The processing unit is further configured to: Acquiring a first noise signal when no sample flows through a sample line of the flow cytometer and sheath fluid flows; and The purity of the sheath fluid is determined based on the first noise signal and the blank detection limit.
8. The information processing system according to claim 7, wherein: The processing unit is further configured to: Acquiring a second noise signal while allowing a pure medium to flow through a sample line of the flow cytometer and a sheath fluid to flow; and A sample line noise is determined based on the second noise signal, the blank detection limit, and the purity of the sheath fluid.
9. A flow cytometer comprising the information processing system according to any one of claims 5 to 8. 10 . A computer-readable storage medium storing instructions, which, when executed by a processor, cause the processor to perform the information processing method according to claim 1 .