Flow cytometry dynamic range visualization

Abstract

The present disclosure provides methods of visualizing the dynamic range of a flow cytometer. Methods of interest include: detecting light from particles in a sample in a flow stream using a light detection system comprising a photodetector; generating one or more data signals in response to the detected light; generating a cytometry data plot for the sample, wherein the plot is generated by: converting the data signals to quantitative intensity units so as to be represented on an axis of the plot in quantitative units; determining a minimum intensity value and a maximum intensity value on the quantitative units axis for the detection range of the photodetector, the minimum and maximum values corresponding to a lowest intensity level and a highest intensity level defined by a bit depth of the photodetector; and indicating the minimum intensity value and the maximum intensity value of the detection range on the quantitative units axis of the plot; and displaying the plot of cytometry data generated for the sample on a visual display.

Description

Technical Field

[0001] This invention relates to the visualization of the dynamic range of flow cytometers. Background Technology

[0002] Characterization of analytes in biofluids has become an important part of biological research, medical diagnostics, and overall patient health and wellness assessment. Detection of analytes in biofluids (such as human blood or blood-derived products) can provide results that can play a role in determining treatment options for patients with a variety of diseases.

[0003] Flow cytometry is a technique used to characterize biological materials (such as cells in a blood sample or particles of interest in another type of biological or chemical sample) and is often used to sort such materials. A flow cytometer typically includes a sample reservoir for receiving a fluid sample (e.g., a blood sample) and a sheath fluid reservoir containing sheath fluid. The flow cytometer transports particles (including cells) in the fluid sample as a flow stream to a flow cell, while simultaneously guiding the sheath fluid into the flow cell. To characterize the composition of the flow stream, light is used to illuminate it. Changes in the material within the flow stream (e.g., the presence of morphology or fluorescent tags) can cause changes in the observed light, and these changes allow for characterization and separation. To characterize the components in the flow stream, light must act on the flow stream and be collected. The light source in a flow cytometer can be varied and may include one or more broad-spectrum lamps, light-emitting diodes, and single-wavelength lasers. The light source is aligned with the flow stream, and the optical response from the illuminated particles is collected and quantified.

[0004] Biological particle separation is achieved by adding sorting or collection capabilities to flow cytometers. Particles detected in the separation stream and possessing one or more desired characteristics are individually separated from the sample stream by mechanical or electrostatic removal. Common flow sorting techniques use droplet sorting, where a flow containing linearly separated particles is broken down into droplets. The droplet containing the particle of interest is charged and deflected through an electric field into a collection tube. Typically, linearly separated particles in the flow are characterized as they pass through an observation point located directly below the nozzle tip. Once a particle is identified as meeting one or more desired criteria, the time it will reach the droplet break-off point and detach from the flow as a droplet can be predicted. Ideally, a brief charge is applied to the fluid flow shortly before the droplet containing the selected particle detaches from the flow, and then grounded immediately after the droplet detaches. The droplet to be sorted remains charged when it detaches from the fluid flow, while all other droplets are uncharged.

[0005] The ability of a flow cytometer to produce a consistent output signal daily for the same input sample depends on a number of factors, including temperature and optomechanical alignment, both of which can fluctuate over time. To maintain performance, manufacturers have traditionally relied on daily quality control (QC) procedures to establish detector gain settings. These procedures typically involve adjusting the detector gain to move the output signal of the reference bead on an arbitrary unit scale, thereby ensuring that its mean fluorescence intensity (MFI) remains consistent over time. However, with the increasing need for standardized flow cytometry, real-time calibration and data normalization methods have gained attention. One promising approach is quantitative scaling, which enables photodetector data to be represented in standardized quantitative units. The use of quantitative scaling offers users the potential to optimize signal-to-noise ratio (SNR) while maintaining consistent performance over time, thereby enhancing overall data quality. Summary of the Invention

[0006] The inventors have recognized that the workflow for calibrating flow cytometers and normalizing flow cytometry data can be improved. In particular, it has been recognized that while conventional calibration methods (e.g., those implementing arbitrary unit scaling) intuitively allow users to determine whether one or more sample populations in an experiment are within the detector's optimal dynamic detection range (i.e., by visually examining the relative position of each population between the top and bottom of an arbitrary unit scale), cytometry data scaled and displayed via quantitative unit scaling is independent of the bit depth of a given flow cytometer system. This makes it difficult to determine the relative position of one or more populations within the detector's dynamic detection range, potentially negatively impacting detector sensitivity, population resolution, and the overall accuracy and reproducibility of experimental results. Therefore, the inventors recognize the need for methods and techniques to intuitively provide users with the dynamic detection range of photodetectors (e.g., during instrument calibration). Specifically, automated workflows are needed to update and display the photodetector's detection window in real time, for example, when acquiring cytometry data and adjusting detector settings. Embodiments of this disclosure meet these needs and expectations.

[0007] In one aspect, a method is provided for displaying cytological data to a user, the method including, for example, displaying the dynamic range of a flow cytometer used to generate the cytological data. This aspect of the method includes: detecting light from particles in a sample in a flowing stream using a light detection system including a photodetector; generating one or more data signals in response to the detected light; generating a plot of cytological data for the sample, wherein the plot is generated by: converting the data signals to quantitative intensity units for representation on an axis of the plot in quantitative units; determining a minimum and maximum intensity value of the detection range of the photodetector on the quantitative unit axis, the minimum and maximum values ​​corresponding to a minimum and maximum intensity level defined by the bit depth of the photodetector; and indicating the minimum and maximum intensity values ​​of the detection range on the quantitative unit axis of the plot; and displaying the plot of cytological data generated for the sample on a visual display. In some embodiments, the quantitative intensity units are independent of the photodetector settings.

[0008] In some embodiments, one or more data signals correspond to the pulse height of the particle. In some embodiments, one or more data signals correspond to the pulse area of ​​the particle. In these cases, the minimum and maximum intensity values ​​of the detection range can be determined using the ratio of pulse area to height. In some embodiments, the method further includes calculating the pulse area to height ratio by: generating a data signal based on light detected from an irradiated reference particle; determining the pulse area based on the generated data signal; determining the pulse height based on the generated data signal; and calculating the pulse area to height ratio by dividing the pulse area by the pulse height. In some embodiments, the reference particle comprises a multispectral fluorescent bead.

[0009] In some embodiments, a scaling factor is used to convert one or more data signals of sample particles into quantitative intensity units, wherein the scaling factor includes the detector gain of the photodetector. In these embodiments, the minimum and maximum intensity values ​​of the detection range are determined using the scaling factor. In some embodiments, the scaling factor includes a calibration factor, and one or more data signals are converted into quantitative intensity units by: normalizing the data signals with the detector gain to generate a gain-normalized data signal; and adjusting the gain-normalized data signal with the calibration factor to generate a calibration data signal.

[0010] In some embodiments, the method further includes calculating a calibration factor by adjusting a gain-normalized data signal generated from light detected from an irradiated reference particle to a predetermined average fluorescence intensity (MFI). For example, the calibration factor can be calculated by: determining a linear gain based on a photodetector voltage; determining a gain corresponding to a predetermined MFI of the data signal generated from light detected from the irradiated reference particle; and calculating a calibration factor to adjust the generated gain-normalized reference data signal to the predetermined MFI. In some embodiments, the method further includes determining a linear gain based on a photodetector voltage by: irradiating the photodetector with a light source at multiple different intensities; detecting light from the light source at multiple different intensities at multiple different photodetector voltages; and determining a detector gain setting for the photodetector sufficient to generate an MFI that increases linearly with the detector gain.

[0011] In some embodiments, the method further includes adjusting the settings of a photodetector. For example, the settings of the photodetector can be adjusted by: receiving an adjustment to the photodetector, wherein the adjustment includes changing the gain of the photodetector to an adjusted gain; adjusting the gain of the photodetector to the adjusted gain; and rescaling the minimum and maximum intensity values ​​of the detection range using the change in the gain of the photodetector. In some embodiments, the adjustment is received from a user. In some embodiments, the settings of the photodetector are adjusted to maximize the signal-to-noise ratio (SNR) of the sample. In some embodiments, the method further includes, after adjusting the photodetector settings, including cytological data generated for particles of the sample on a graph by: generating a data signal in response to light detected from irradiated particles of the sample after adjusting the photodetector settings; converting the data signal to quantitative intensity units using the change in the gain of the photodetector; and plotting the converted data signal on a graph.

[0012] In some embodiments, the minimum and maximum intensity values ​​of the detection range are indicated by visual indicators that mark the quantitative unit axis of the graph at the minimum and maximum intensity values. In these cases, the visual indicators may include a first visual indicator and a second visual indicator, the first visual indicator including a line perpendicular to the quantitative unit axis at the minimum intensity value, and the second visual indicator including a line perpendicular to the quantitative unit axis at the maximum intensity value. In some embodiments, the minimum and maximum intensity values ​​of the detection range are indicated by shading the region of the graph between the minimum and maximum intensity values ​​along the quantitative unit axis. In some embodiments, the minimum and maximum intensity values ​​of the detection range are indicated by shading the regions of the graph corresponding to values ​​below the minimum intensity value and above the maximum intensity value along the quantitative unit axis.

[0013] In some embodiments, the graph is a histogram representing fluorescence intensity values ​​in quantitative intensity units on a first axis and corresponding particle counts on a second axis. In other embodiments, the graph is a dot plot comprising: a first axis representing fluorescence intensity values ​​obtained using a data signal generated using light detected by a photodetector in quantitative intensity units; and a second axis representing fluorescence intensity values ​​obtained using a data signal generated using light detected by a second photodetector. In some embodiments, the graph of cytology data is generated and displayed in real time. In these embodiments, the method may further include updating the displayed graph of cytology data in real time. For example, the displayed graph of cytology data may be updated to reflect adjustments to photodetector settings or to include cytology data generated for additional particles in the sample.

[0014] On the other hand, a flow cytometer configured to display the dynamic range of the cytometer's light detection system is provided, for example, according to any of the methods described above and herein. The flow cytometer of interest includes: a light source configured to illuminate a sample comprising particles in a flowing stream; a light detection system including a photodetector for detecting light from the illuminated particles; and a processor including a memory operatively coupled to the processor, wherein the memory includes instructions stored thereon that, when executed by the processor, cause the processor to perform the following operations: generate one or more data signals in response to detected light; generate a graph of cytological data for the sample, wherein the graph is generated by: converting the data signals into quantitative intensity units for representation on an axis of the graph in quantitative units; determining a minimum and maximum intensity value of the detection range of the photodetector on the quantitative unit axis, the minimum and maximum values ​​corresponding to a minimum and maximum intensity level defined by the bit depth of the photodetector; and indicating the minimum and maximum intensity values ​​of the detection range on the quantitative unit axis of the graph; and displaying the graph of the cytological data generated for the sample on a visual display. In some embodiments, the flow cytometer further includes a display device operatively connected to the processor and configured to display graphs of cytological data. In some cases, the flow cytometer also includes an operator input device operatively connected to the processor and configured to receive adjustments to the settings of the photodetector from a user.

[0015] On the other hand, systems are provided for performing methods of displaying cytological data to a user, such as those described above and herein. Furthermore, non-transitory computer-readable storage media including system memory instructions are provided, as well as kits including one or more system components and / or non-transitory computer-readable storage media. Attached Figure Description

[0016] This disclosure can be best understood by reading in conjunction with the accompanying drawings, which include the following detailed description:

[0017] Figure 1A A flowchart is depicted illustrating a method for practicing a light detection system for visualizing a flow cytometer, according to certain embodiments. Figure 1B A display of cytological data is depicted, showing the dynamic range of a flow cytometer used to generate cytological data according to certain embodiments. Figure 1C A flowchart is depicted for a method of calibrating a flow cytometer in practice, according to certain embodiments.

[0018] Figure 2 A flow cytometer system according to certain embodiments is shown.

[0019] Figure 3 An image-enabled particle sorter according to certain embodiments is described.

[0020] Figure 4 A functional block diagram of a particle analysis system according to certain embodiments is depicted.

[0021] Figure 5 A functional block diagram of an example control system according to certain embodiments is depicted.

[0022] Figures 6A-6B A schematic diagram of a particle sorting system according to certain embodiments is depicted.

[0023] Figure 7 Aspects of a computer control system according to certain embodiments are described. Detailed Implementation

[0024] This disclosure provides a method for visualizing the dynamic range of a flow cytometer. The method of interest includes: detecting light from particles in a sample in a flowing stream using a light detection system including a photodetector; generating one or more data signals in response to the detected light; generating a graph of cytological data for the sample, wherein the graph is generated by: converting the data signals into quantitative intensity units for representation on an axis of the graph in quantitative units; determining a minimum and maximum intensity value of the detection range of the photodetector on the quantitative unit axis, the minimum and maximum values ​​corresponding to a minimum and maximum intensity level defined by the bit depth of the photodetector; and indicating the minimum and maximum intensity values ​​of the detection range on the quantitative unit axis of the graph; and displaying the graph of the cytological data generated for the sample on a visual display. This subject matter method can be implemented automatically by a computer. A flow cytometer, system, and non-transitory computer-readable storage medium for performing this subject matter method are also provided.

[0025] Before describing this disclosure in more detail, it should be understood that the invention is not limited to the specific embodiments described, as these embodiments can certainly be varied. It should also be understood that, since the scope of this disclosure will be limited only by the appended claims, the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting.

[0026] Where a range of values ​​is provided, it should be understood that, unless the context explicitly specifies otherwise, every intermediate value (to one-tenth of the lower limit unit) between the upper and lower limits of the range, as well as any other specified value or intermediate value within the range, is included in this disclosure. The upper and lower limits of these smaller ranges may be independently included within the smaller range and also within this disclosure, subject to any specific exclusions within the range. Where the range includes one or both of the included limits, the range excluding one or both of those included limits is also included in this disclosure.

[0027] This article provides certain ranges whose numerical values ​​are preceded by the term "approximately". The term "approximately" is used in this article to provide textual support for the exact number that follows it, as well as for numbers that are close to or approximate to the number that follows the term. In determining whether a number is close to or approximate to a specifically listed number, an unlisted number that is close to or approximate can be a number that provides a basic equivalent to the specifically listed number in the context in which it appears.

[0028] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains. Although any methods and materials similar to or equivalent to those described herein can be used in the practice or testing of this disclosure, representative illustrative methods and materials are described here.

[0029] All publications and patents referenced in this specification are incorporated herein by reference, as if each individual publication or patent were expressly and individually indicated to be incorporated herein by reference to disclose and describe the methods and / or materials relating to the referenced publication. Any reference to a publication refers to a publication prior to the filing date and should not be construed as an admission that this disclosure has no priority over such publication due to prior art. Furthermore, the publication dates provided may differ from the actual publication dates and may require independent verification.

[0030] It should be noted that, unless the context clearly indicates otherwise, the use of an element in this document and the appended claims without a defined quantity implies the presence of at least one such element. It should also be noted that claims may be drafted to exclude any optional elements. Therefore, this statement is intended as a preliminary basis for the use of exclusive terms such as "unique," "only," etc., when referencing claim elements or using the "negative" limitation.

[0031] As will be apparent to those skilled in the art upon reading this disclosure, each individual embodiment described and illustrated herein has discrete components and features that can be readily separated from or combined with features of any of the other several embodiments without departing from the scope or spirit of this disclosure. Any enumerated methods may be performed in the order of the enumerated events or in any other logically possible order.

[0032] Although the system and method have been or will be described for grammatical fluency and functional interpretation, it should be clearly understood that, unless expressly provided in 35 U.SC §112, the claims should not be construed as necessarily being bound by “means” or “steps,” but rather should be given the full range of meaning and equivalents provided by the definition of the claims in accordance with the doctrine of judicial equivalence, and if the claims are expressly provided in 35 U.SC §112, they should be given the full range of legal equivalents in accordance with 35 U.SC §112.

[0033] Methods for visualizing dynamic range

[0034] As described above, a method for displaying cytological data to a user, such as the dynamic range of a flow cytometer used to generate the cytological data, is provided. Aspects of this method include: detecting light from particles in a sample in a flowing stream using a light detection system including a photodetector; generating one or more data signals in response to the detected light; generating a graph of the cytological data for the sample, wherein the graph is generated by: converting the data signals into quantitative intensity units for representation on an axis of the graph in quantitative units; determining a minimum and maximum intensity value of the detection range of the photodetector on the quantitative unit axis, the minimum and maximum values ​​corresponding to a minimum and maximum intensity level defined by the bit depth of the photodetector; and indicating the minimum and maximum intensity values ​​of the detection range on the quantitative unit axis of the graph; and displaying the graph of the cytological data generated for the sample on a visual display. In some embodiments, the quantitative intensity units are independent of the photodetector settings.

[0035] As used herein, “bit depth” refers to the number of bits used to digitize an analog signal (e.g., converting detected light into a discrete digital signal). Thus, the bit depth of a system (e.g., a light detection system) or a particular component of it (e.g., a photodetector) defines the number of discrete intensity levels or channels that can be represented by that system. For example, an 18-bit system would have 2… 18Or, the bit depth is 262,144 discrete intensity levels or channels. In other words, the bit depth determines the resolution of a given optical detection system or its photodetector. Therefore, the lowest intensity level of the bit depth corresponds to the smallest electrical signal output from the photodetector that is quantized by the system's analog-to-digital converter (ADC), or the "first" channel of the bitmap (i.e., the lowest measurable signal above "no signal" or channel zero). Similarly, the highest intensity level of the bit depth corresponds to the largest analog input signal (i.e., the largest electrical signal output from the photodetector) that the ADC can accurately digitize without saturation (i.e., the upper limit of the analog input voltage range that the ADC is configured to process). However, since any signal exceeding this maximum input will also be assigned to the highest intensity level, the highest intensity level of the bit depth typically indicates saturation.

[0036] During the calibration of a given instrument (e.g., an optical detection system or its photodetector), the discrete intensity levels or channels of the instrument's bit depth (or more specifically, its ADC) are bound or mapped to values ​​on a unit scale (e.g., an arbitrary unit scale or a quantitative unit scale as described above). When using an arbitrary unit scale, it is typically created or adjusted such that the lowest and highest intensity levels of the photodetector's bit depth are inherently located near or close to the beginning and end of the arbitrary unit scale, respectively. In other words, since the minimum and maximum values ​​of the arbitrary unit scale are inherently bound to or associated with the lowest and highest intensity levels of the photodetector's bit depth, the arbitrary unit scale itself can be considered a proxy for the dynamic range of the photodetector. This allows users to visually understand whether the particles in the sample optimally fall within the dynamic detection range of the photodetector. However, when using a quantitative unit scale (as in the case of the method of this topic), the scaling of the data signal is no longer related to the bit depth of the photodetector. Therefore, before the minimum and maximum intensity values ​​of the photodetector's detection range are indicated on the quantitative unit axis (i.e., as described above and in this paper), users cannot intuitively determine whether the particles in the sample fall within the optimal range of the photodetector's dynamic detection range—which actually makes calibration more difficult and negatively impacts detector sensitivity, population resolution, and the overall accuracy and repeatability of experimental results.

[0037] In some embodiments, the generated data signal is a digital signal generated by an ADC, for example, as described above. In other words, in some cases, the generated data signal corresponds to or directly represents discrete intensity levels or channels of the bit depth (or, for example, their sum in the case of pulse area, as described below). In these cases, the same transformation applied to the data signal (i.e., to represent the data signal on the quantitative unit axis) can be applied to the lowest and highest intensity levels of the bit depth to determine the minimum and maximum intensity values ​​of the photodetector's detection range on the quantitative unit axis.

[0038] As described above, embodiments of this method include generating one or more data signals in response to light detected by a light detection system (and, for example, its photodetector) from sample particles in a flowing stream. In some embodiments, one or more data signals correspond to the pulse height of the particle. In other words, in certain cases, one or more data signals may correspond to the peak or maximum amplitude of an electrical signal generated by the photodetector in response to light emitted or scattered by the particle, for example, when it passes through the detection region (i.e., the highest channel of bit depth reached or reached by the particle).

[0039] In some embodiments, one or more data signals correspond to the pulse area of ​​the particle. That is, in some cases, one or more data signals correspond to the integral value of the electrical signal generated by the photodetector over time as the particle passes through the laser beam (i.e., the sum of all signal amplitudes of the photodetector during, for example, the period while the particle is in the detection region), representing the total light detected from the particle, or, i.e., the sum of the bit depth channels sampled for the particle. In these cases, the minimum and maximum intensity values ​​of the detection range can be determined using the ratio of pulse area to height. For example, the minimum and maximum intensity values ​​can be determined by dividing the lowest and highest intensity levels defined by the bit depth of the photodetector by the ratio of pulse area to height before applying a quantitative scaling transformation to each quotient. In some embodiments, the method further includes calculating the pulse area to height ratio by: generating a data signal based on the light detected from the irradiated reference particle; determining the pulse area based on the generated data signal; determining the pulse height based on the generated data signal; and calculating the pulse area to height ratio by dividing the pulse area by the pulse height.

[0040] In some instances, the reference particle comprises a multispectral fluorescent bead. In these instances, the multispectral fluorescent bead may include a fluorescent dye component covalently bonded to the particle. In some embodiments, the particle is a bead, for example, a structure having a diameter in the nanometer to micrometer range, such as a diameter of 0.01 micrometers to 1000 micrometers, or a diameter of 0.1 micrometers to 100 micrometers, and including diameters of 1 micrometer to 100 micrometers, and, for use in flow cytometry, including diameters of about 1 micrometer to 10 micrometers. Such a particle can be of any shape, approximating spherical in some instances.

[0041] In some embodiments, the particles (i.e., multispectral fluorescent beads) may be made of any suitable material (or combination thereof), including but not limited to polymers such as polystyrene; polystyrene containing other copolymers such as divinylbenzene; polymethyl methacrylate (PMMA); polyvinyl toluene (PVT); copolymers such as styrene / butadiene, styrene / vinyl toluene; latex; glass; or other materials such as silica (e.g., SiO2). In some embodiments, particles with low or no self-fluorescence are of interest, such as beads, for example glass beads. In some embodiments, the beads are a metal-organic polymer matrix, such as an organic polymer matrix having a main chain structure containing metals such as aluminum, barium, antimony, calcium, chromium, copper, erbium, germanium, iron, lead, lithium, phosphorus, potassium, silicon, tantalum, tin, titanium, vanadium, zinc, or zirconium. In some instances, the porous metal-organic matrix is ​​an organosiloxane polymer, including but not limited to polymers of methyltrimethoxysilane, dimethyldimethoxysilane, tetraethoxysilane, methacryloxypropyltrimethoxysilane, bis(triethoxysilane)ethane, bis(triethoxysilane)butane, bis(triethoxysilane)pentane, bis(triethoxysilane)hexane, bis(triethoxysilane)heptane, bis(triethoxysilane)octane, and combinations thereof.

[0042] The reference particles of interest may be porous or non-porous. In some embodiments, the particles are non-porous. In other embodiments, the particles are porous, for example, having pores in diameter ranging from 0.01 nm to 1000 nm (e.g., 0.05 nm to 750 nm, 0.1 nm to 500 nm, 0.5 nm to 250 nm, 1 nm to 100 nm, 5 nm to 75 nm), and including particles having pores in diameter ranging from 10 nm to 50 nm. In some cases, fluorescently labeled beads of interest include, but are not limited to, fluorescently labeled polystyrene beads, fluorescein beads, Rhodamine beads, and other beads labeled with fluorescent dyes. Further examples of fluorescently labeled beads are described in U.S. Patent Nos. 6,350,619, 7,738,094, and 8,248,597, the disclosures of which are incorporated herein by reference in their entirety.

[0043] In some embodiments, a scaling factor is used to convert one or more data signals of sample particles into quantitative intensity units (MFIs), where the scaling factor includes the detector gain of the photodetector. In these cases, the scaling factor can account for (i.e., normalize) the real-time gain of the photodetector as it generates an analog (i.e., electrical) signal based on the detected light (the analog signal is converted to digital data by the ADC). In other words, the scaling factor allows the sample quantitative intensity unit (e.g., MFI) to be maintained regardless of the gain setting, such that the quantitative intensity scale used (e.g., for representing the MFI) corresponds to the true intensity of the input signal. In some embodiments, the scaling factor divides one or more data signals by the gain of the photodetector. In some embodiments, the scaling factor is used to determine the minimum and maximum intensity values ​​of the detection range.

[0044] In some embodiments, the scaling factor includes a calibration factor, and one or more data signals are converted to quantitative intensity units by: normalizing the data signals with detector gain to generate gain-normalized (i.e., gain-independent) data signals; and adjusting the gain-normalized data signals with a calibration factor to generate calibration data signals. In some embodiments, the method further includes calculating (i.e., of the scaling factor) a calibration factor by adjusting a gain-normalized data signal generated from light detected from an irradiated reference particle to a predetermined average fluorescence intensity (MFI). For example, the calibration factor can be calculated by: determining a linear gain based on a photodetector voltage; determining a gain corresponding to a predetermined MFI of the data signal generated from light detected from an irradiated reference particle; and calculating a calibration factor that adjusts the generated gain-normalized reference data signal to the predetermined MFI.

[0045] In some embodiments, the calibration factor is calculated at multiple different time points, for example, periodically. For example, for a given instrument (e.g., a light detection system and its photodetector), the calibration factor may be calculated over a set number of days or uses to account for system offset. In some embodiments, the linear gain can be derived from a lookup table. In some embodiments, the reference particle may include multispectral fluorescent beads (e.g., as described above). In some embodiments, the method further includes determining the linear gain based on the photodetector voltage by: illuminating the photodetector with a light source at multiple different intensities; detecting light from the light source at multiple different intensities at multiple different photodetector voltages; and determining a detector gain setting sufficient to generate an MFI (Mean Function Index) for the photodetector that increases linearly with the detector gain.

[0046] In some embodiments, the method further includes adjusting the settings of the photodetector. For example, the settings of the photodetector can be adjusted by: receiving an adjustment to the photodetector, wherein the adjustment includes changing the gain of the photodetector to an adjusted gain; adjusting the gain of the photodetector to an adjusted gain; and rescaling the minimum and maximum intensity values ​​of the detection range using the change in the gain of the photodetector. In some embodiments, this adjustment (i.e., the adjustment to the photodetector) is received from a user. In some embodiments, the settings of the photodetector are adjusted to maximize the signal-to-noise ratio (SNR) of the sample. For example, when calibrating a photodetector system, a user may see from the minimum and maximum intensity values ​​of the photodetector's detection range indicated on the quantitative unit axis (i.e., as described above and herein) that the data signal represented on that axis (i.e., corresponding to particles in the sample) does not optimally fall within the dynamic detection range of the photodetector, such that the entire dynamic detection range of the photodetector is not effectively utilized. In these cases, the user can adjust the gain of the photodetector to make effective use of a larger dynamic detection range, and / or to ensure that there is sufficient space between the data signal represented on the axis (i.e., after conversion) and the detection threshold (i.e., the lower limit of detection) and / or the saturation point of the photodetector.

[0047] In some embodiments, the method further includes, after adjusting the settings of the photodetector, including cytological data generated from particles of the sample on a graph by: generating a light-generating data signal detected from particles of the irradiated sample in response to adjusting the settings of the photodetector; converting the data signal into quantitative intensity units using a change in the gain of the photodetector; and plotting the converted data signal on a graph. This allows the user to continuously adjust the photodetector (e.g., by multiple incremental changes in the photodetector gain) until the signal-to-noise ratio (SNR) has been effectively optimized. In some embodiments, the method includes adjusting the gain setting of the photodetector by 0.01 dB or more, such as 0.05 dB or more, 0.1 dB or more, 0.5 dB or more, 1 dB or more, 2 dB or more, 3 dB or more, 5 dB or more, or 10 dB or more.

[0048] In some embodiments, the minimum and maximum intensity values ​​of the detection range are indicated by visual indicators that mark the quantitative unit axis of the graph at the minimum and maximum intensity values. In these cases, the visual indicators may include a first visual indicator and a second visual indicator, the first visual indicator including a line perpendicular to the quantitative unit axis at the minimum intensity value, and the second visual indicator including a line perpendicular to the quantitative unit axis at the maximum intensity value. In some embodiments, the minimum and maximum intensity values ​​of the detection range are indicated by shading the region of the graph between the minimum and maximum intensity values ​​along the quantitative unit axis. In some embodiments, the minimum and maximum intensity values ​​of the detection range are indicated by shading the regions of the graph corresponding to values ​​below the minimum intensity value and above the maximum intensity value along the quantitative unit axis.

[0049] The shading described above can be any color or hue. In some embodiments, the shading color and hue are configured to form a direct contrast with the unshaded areas of the graph. In some embodiments, the shading color and hue are configured to form a direct contrast with the cytological data (i.e., the data signal represented in the graph) shown in the graph.

[0050] In some embodiments, the visual indicator may include marks placed directly on a marker axis of the quantitative axis at the minimum and maximum intensity values. The marker axis refers to a line with regularly spaced scale marks and numerical marks indicating the scale of the axis. In some embodiments, the visual indicator marks may include, but are not limited to, stars, triangles, squares, circles, or any other shape, for visually indicating to the user the upper and lower limits of the dynamic detection range of the photodetector. Similarly, the visual indicator marks may be of any color or hue.

[0051] As described above, the lowest intensity level of the bit depth corresponds to the minimum electrical signal output by the photodetector and quantized by the system's ADC, while the highest intensity level of the bit depth corresponds to the maximum analog input signal that the ADC can accurately digitize without saturation. The minimum and maximum intensity values ​​of the photodetector's detection range correspond to the lowest and highest intensity levels defined by the bit depth. In some embodiments, the minimum and maximum intensity values ​​directly represent the lowest and highest intensity levels defined by the bit depth on the unit of measurement axis. In other embodiments, the minimum and maximum intensity values ​​represent values ​​near the lowest and highest intensity levels defined by the bit depth on the unit of measurement axis. For example, in some cases, the gain setting of the photodetector can be adjusted so that the first few intensity levels or channels of the bit depth reflect background noise. In these cases, the minimum intensity value can be directly associated with (i.e., it can represent) the first intensity level or channel of the bit depth that is distinguishable from background noise. Thus, the minimum and maximum intensity values ​​can be configured to more accurately reflect the available detection range of the photodetector.

[0052] In some embodiments, the graph is a histogram representing fluorescence intensity values ​​in quantitative intensity units on a first axis and corresponding particle counts on a second axis. In other embodiments, the graph is a dot plot, comprising: a first axis representing fluorescence intensity values ​​obtained using data signals generated from light detected by a photodetector in quantitative intensity units; and a second axis representing fluorescence intensity values ​​obtained using data signals generated from light detected by a second photodetector. In some embodiments, the second axis is represented in quantitative intensity units. In these cases, the method may include: minimum and maximum intensity values ​​indicating the detection range of the photodetector on the first quantitative unit axis; and minimum and maximum intensity values ​​indicating the detection range of the second photodetector on the second quantitative unit axis (i.e., as described above and herein).

[0053] In some embodiments, the graph of cytological data is generated and displayed in real time. In some embodiments, the method further includes updating the displayed graph of cytological data in real time. For example, the displayed graph of cytological data may be updated to reflect adjustments to the photodetector settings, or to include cytological data generated for other particles in the sample.

[0054] Figure 1AA flowchart is depicted for a method (e.g., as described above) for visualizing the dynamic range of a flow cytometer's optical detection system. In step 101, light from particles in a sample in a flowing stream is detected using an optical detection system including a photodetector. In step 102, one or more data signals are generated in response to the detected light. The data signals may directly reflect the digital data signal, intensity level, or channel of the ADC output of the photodetector. In step 103, a graph of cytological data for the sample is generated by performing steps 103A-103C. In step 103A, the data signals are converted to quantitative intensity units for representation on the axes of the graph in quantitative units. This conversion may be linear or non-linear (e.g., exponential) and may include (e.g., when the data signals directly reflect the intensity level or channel of the ADC output) selecting the largest data signal corresponding to a sample particle (i.e., pulse height) or summing all data signals corresponding to the sample particle (i.e., pulse area). In other cases, the largest data signal has already been selected before the conversion, or the data signals have already been summed before the conversion (i.e., the conversion converts the sum of the data signals to quantitative intensity units). In step 103B, the minimum and maximum intensity values ​​of the detection range of the photodetector are determined on the quantitative unit axis, where the minimum and maximum values ​​correspond to the lowest and highest intensity levels defined by the bit depth of the photodetector. In other words, the positions of the minimum electrical signal output by the photodetector, quantized by the photodetector's ADC, and the positions of the maximum electrical signal output by the photodetector, which the ADC can accurately digitize without saturation, are both located on the quantitative unit axis of the graph. In some embodiments, this includes using the same conversion for the data signals representing the first and last (i.e., the highest and lowest) channels of the bit depth as for converting the data signals generated in response to the light of detected particles (e.g., see step 103A). In step 103C, the minimum and maximum intensity values ​​of the detection range are indicated on the quantitative unit axis of the graph. In step 104, a graph of the cytological data generated for the sample is displayed on a visual display. In some embodiments, steps 101-104 may be performed again each time light from other particles is detected and / or each time the settings of the photodetector (e.g., gain settings) are adjusted. In this way, the dynamic range of the photodetector is continuously updated on the display, allowing users to visually determine at any point in time (e.g., during instrument calibration or experiments) where a particle in the sample falls within the dynamic detection range of the photodetector.

[0055] Figure 1BThis diagram depicts a display of cytological data indicating the dynamic range of the flow cytometer used to generate cytological data. Figure A (left) illustrates how the relative position of a sample population between the top and bottom of an arbitrary unit scale (e.g., a gain-dependent unit scale) allows a user to visually determine whether the sample population falls within the optimal dynamic detection range of the photodetector. As shown in Figure A, the bit depth of the photodetector is inherently tied to the arbitrary unit scale (regardless of detector setting), allowing the user to quickly determine whether the SNR is effectively optimized for the sample population based solely on its relative position on the arbitrary unit scale. Figure B (right) illustrates how the relative position of a sample population between the top and bottom of a quantitative unit scale (e.g., a gain-independent unit scale) does not provide the user with any information about where the sample population falls within the dynamic detection range of the photodetector. By shading the region between the minimum and maximum intensity values ​​along the quantitative unit axis of the diagram (e.g., according to the methods described above and herein), the user can quickly determine whether the SNR is effectively optimized for the sample population based on its relative position within the visualized dynamic detection range of the photodetector.

[0056] Figure 1C A step-by-step illustration of generating scaled gain-normalized data according to certain embodiments is depicted. In step 120, a lookup table is generated to ensure that changes in average fluorescence intensity are linear with changes in detector settings (e.g., gain settings). At the periodic quality control shown at step 121 (e.g., daily), the detector gain setting is increased so that the average fluorescence intensity of the reference particles (e.g., multispectral beads) equals the target gain. A calibration factor for adjusting the user gain is calculated using the target gain and the target MFI. At step 122, gain-normalized data is generated by dividing the data signal by the scaling factor (i.e., linear gain), resulting in gain-normalized data (as shown in step 122, where the multispectral bead data exhibits the same MFI regardless of detector settings). This scaling factor allows the scaling of the MFI to remain consistent (regardless of detector settings) rather than calculating an offset applied to a saved setting and updated only after quality control. This can be done independently of the detector settings. In some embodiments, the periodic gain setting (e.g., daily gain setting) can be optimized to ensure consistency in sensitivity, resolution, or dynamic range. In some cases, the gain setting remains unchanged.

[0057] Flow cytometry method

[0058] In some instances, the samples analyzed by this method are biological samples. The term "biological sample," used in its conventional sense, refers to a subset of tissues, cells, or components of an organism, plant, fungus, or animal, and in some instances can be found in blood, mucus, lymph, synovial fluid, cerebrospinal fluid, saliva, bronchoalveolar lavage fluid, amniotic fluid, amniotic cord blood, urine, vaginal fluid, and semen. Therefore, "biological sample" refers both to a subset of a natural organism or its tissues and to homogenates, lysates, or extracts prepared from a subset of an organism or its tissues, including but not limited to, plasma, serum, cerebrospinal fluid, lymph, skin sections, respiratory tract, gastrointestinal tract, cardiovascular and genitourinary tract, tears, saliva, breast milk, blood cells, tumors, and organs. Biological samples can be any type of biological tissue, including both healthy and diseased tissues (e.g., cancerous tissue, malignant tissue, necrotic tissue, etc.). In some embodiments, the biological sample is a liquid sample, such as blood or its derivatives, such as plasma, tears, urine, semen, etc. In some instances, the sample is a blood sample, including whole blood, such as blood obtained by venipuncture or finger prick (where the blood may or may not be bound to any reagents such as preservatives, anticoagulants, etc. before testing).

[0059] In some embodiments, the source of the sample is "mammal" or "milk animal," terms that are widely used to describe organisms within the class Mammalia, including carnivores (e.g., dogs and cats), rodents (e.g., mice, guinea pigs, and rats), and primates (e.g., humans, chimpanzees, and monkeys). In some instances, the subject is a human. The method can be applied to samples obtained from human subjects of both sexes and at any developmental stage (i.e., newborns, infants, adolescents, teenagers, and adults), wherein in some embodiments, the human subject is an adolescent, teenager, or adult. While this disclosure can be applied to samples from human subjects, it should be understood that the method can also be performed on samples from other animal subjects (i.e., "non-human subjects") (e.g., but not limited to birds, mice, rats, dogs, cats, livestock, and horses).

[0060] Cells of interest can be targeted to characterize them according to various parameters, such as phenotypic features identified by attaching specific fluorescent labels to the cells of interest. In some embodiments, the system is configured to deflect analytical droplets identified as including target cells. A wide variety of cells can be characterized using the methods of this subject matter. Target cells of interest include, but are not limited to, stem cells, T cells, dendritic cells, B cells, granulocytes, leukemia cells, lymphoma cells, viral cells (e.g., HIV cells), NK cells, macrophages, monocytes, fibroblasts, epithelial cells, endothelial cells, and erythroid cells. Target cells of interest include cells with readily available cell surface markers or antigens that can be captured or labeled by readily available affinity agents or conjugates thereof. For example, target cells may include cell surface antigens such as CD11b, CD123, CD14, CD15, CD16, CD19, CD193, CD2, CD25, CD27, CD3, CD335, CD36, CD4, CD43, CD45RO, CD56, CD61, CD7, CD8, CD34, CD1c, CD23, CD304, CD235a, T cell receptor α / β, T cell receptor γ / δ, CD253, CD95, CD20, CD105, CD117, CD120b, Notch4, Lgr5 (N-terminal), SSEA-3, TRA-1-60 antigen, disialotetrahexosylganglioside GD2, and CD71. In some embodiments, target cells are selected from HIV-containing cells, Treg cells, antigen-specific T cell populations, tumor cells, or hematopoietic progenitor cells (CD34+) derived from whole blood, bone marrow, or umbilical cord blood.

[0061] When implementing the methods described in this article, an initial fluid sample is injected into the flow cytometer. The sample volume injected into the particle sorting module can vary, for example, ranging from 0.001 mL to 1000 mL, such as 0.005 mL to 900 mL, 0.01 mL to 800 mL, 0.05 mL to 700 mL, 0.1 mL to 600 mL, 0.5 mL to 500 mL, 1 mL to 400 mL, 2 mL to 300 mL, including samples from 5 mL to 100 mL.

[0062] The method according to embodiments of this disclosure includes counting and optionally sorting labeled particles (such as target cells) in a sample. In implementing this subject matter method, a fluid sample containing particles is first introduced into a flow nozzle of the system. After exiting the flow nozzle, the particles pass substantially one-by-one through a sample detection region, where each particle is illuminated by a light source, and measurements of light scattering parameters for each particle are recorded individually. In some instances, fluorescence emission measurements are also recorded as needed (e.g., two or more light scattering parameter measurements and one or more fluorescence emission measurements). Depending on the characteristics of the detected flow, regions of 0.001 mm or longer in the flow may be illuminated, such as 0.005 mm or longer, 0.01 mm or longer, 0.05 mm or longer, 0.1 mm or longer, 0.5 mm or longer, including regions of 1 mm or longer in the flow that may be illuminated. In some embodiments, the method includes illuminating a planar cross-section of the flow in the sample detection region, for example, using a laser (as described above). In other embodiments, the method includes irradiating a predetermined length region of the flow in the sample detection region, for example, corresponding to the irradiation profile of a diffuse laser beam or lamp.

[0063] In some embodiments, the method includes irradiating the flow at or near the flow tank nozzle orifice. For example, the method may include irradiating the flow at a location approximately 0.001 mm or more from the nozzle orifice, such as 0.005 mm or more, 0.01 mm or more, 0.05 mm or more, 0.1 mm or more, 0.5 mm or more, including a location 1 mm or more from the nozzle orifice. In some embodiments, the method includes irradiating the flow at a location immediately adjacent to the flow nozzle orifice.

[0064] In embodiments of this method, detectors, such as photomultiplier tubes (PMTs), are used to record light passing through each particle (in some cases referred to as forward scattering), light reflected orthogonally to the flow direction of the particle through the detection zone (in some cases referred to as orthogonal or lateral scattering), and fluorescence emitted from the particle as it passes through the detection zone and is illuminated by energy, if the particle is labeled with a fluorescent marker. Each of forward scattering (FSC), lateral scattering (SSC), and fluorescence emission includes a separate parameter for each particle (or each "event"). Thus, for example, two, three, or four parameters can be collected (and recorded) from particles labeled with two different fluorescent markers. The data recorded for each particle is analyzed in real time as needed or stored in a data storage and analysis device, such as a computer.

[0065] In some embodiments, particles are detected and uniquely identified by exposing them to excitation light and measuring the fluorescence of each particle in one or more detection channels as needed. The fluorescence emitted in the detection channels, used to identify particles and the binding complexes associated with them, can be measured after excitation using a single light source, or separately after excitation using different light sources. If separate excitation sources are used to excite the particle markers, the markers can be selected such that all markers can be excited by each excitation source used.

[0066] In some embodiments, the method also includes data acquisition, analysis, and recording (e.g., using a computer), where multiple data channels record light scattering and fluorescence data emitted by each particle as it passes through the sample detection area of ​​a particle sorting module from each detector. In these embodiments, the analysis includes classifying and counting particles such that each particle exists as a set of digitized parameter values. The subject system can be configured to trigger on selected parameters to distinguish particles of interest from background and noise. "Trigger" refers to a preset threshold for the detection parameter, which can be used as a means of detecting particles passing through the light source. Detecting an event exceeding the selected parameter threshold triggers the acquisition of light scattering and fluorescence data for that particle. Data for particles or other components in the analyzed medium that elicit a response below the threshold are not acquired. The trigger parameter could be the detection of forward scattered light caused by particles passing through the light beam. Flow cytometry then detects and collects the light scattering and fluorescence data of the particles.

[0067] The specific subpopulations of interest are then further analyzed by "gating" based on data collected for the entire population. To select an appropriate gate, the data is plotted to obtain the best possible subpopulation separation. This process can be performed by plotting forward light scattering (FSC) and lateral (i.e., orthogonal) light scattering (SSC) on a two-dimensional dot plot. The granular subpopulations (i.e., those cells within the gate) are then selected, and granules not within the gate are excluded. If needed, gates can be selected by drawing lines around the desired subpopulation on the computer screen using a cursor. Those granules within the gate are then further analyzed only by plotting other parameters of these granules (e.g., fluorescence). If necessary, the above analysis can be configured to generate counts of granules of interest in the sample.

[0068] Methods of interest may also include the use of particles in research, laboratory testing, or treatment. In some embodiments, the subject method includes obtaining single cells prepared from a target fluid or tissue biological sample. For example, the subject method includes obtaining cells from a fluid or tissue sample for use as a research or diagnostic specimen for diseases such as cancer. Similarly, the subject method includes obtaining cells from a fluid or tissue sample for therapeutic purposes. Cell therapy protocols are those that can prepare living cellular materials, including, for example, cells and tissues, and introduce them into a subject for therapeutic treatment. Situations where treatment can be performed by applying samples sorted by flow cytometry include, but are not limited to, blood disorders, immune system disorders, organ damage, etc.

[0069] A typical cell therapy protocol may include the following steps: sample collection, cell isolation, gene modification, in vitro culture and expansion, cell harvesting, sample volume reduction and washing, biopreservation, storage, and introduction of cells into a subject. The protocol can begin by collecting live cells and tissues from the subject's source tissue to produce a sample of cells and / or tissues. Samples can be collected using any suitable procedure, including, for example, administration of cell mobilizing agents to the subject, drawing blood from the subject, or extracting bone marrow from the subject. After sample collection, cells can be enriched using several methods, including, for example, centrifugation-based methods, filter-based methods, elutriation, magnetic separation methods, fluorescence-activated cell sorting (FACS), etc. In some instances, the enriched cells can be gene-modified using any convenient method, such as nuclease-mediated gene editing. Genetically modified cells can then be cultured, activated, and expanded in vitro. In some instances, cells are preserved, for example, cryopreserved, and stored for future use, where the cells are thawed and then administered to the patient, for example, cells can be infused into the patient.

[0070] Flow cytometer equipment and systems

[0071] This disclosure also includes flow cytometer apparatus and systems for practicing the methods of this subject matter, such as methods for visualizing the dynamic range of a flow cytometer's light detection system, as described above and herein. A flow cytometer of interest includes: a light source configured to illuminate a sample comprising particles in a flowing stream; a light detection system including a photodetector for detecting light from the illuminated particles; and a processor including a memory operatively coupled to the processor, wherein the memory includes instructions stored thereon that, when executed by the processor, cause the processor to perform the following operations: generate one or more data signals in response to detected light; generate a graph of cytological data for the sample, wherein the graph is generated by: converting the data signals into quantitative intensity units for representation on an axis of the graph in quantitative units; determining a minimum and maximum intensity value of the detection range of the photodetector on the quantitative unit axis, the minimum and maximum values ​​corresponding to a minimum and maximum intensity level defined by the bit depth of the photodetector; indicating the minimum and maximum intensity values ​​of the detection range on the quantitative unit axis of the graph; and displaying the graph of the cytological data generated for the sample on a visual display. In some embodiments, the flow cytometer further includes a display device operatively connected to the processor and configured to display graphs of cytological data. In some cases, the flow cytometer also includes an operator input device operatively connected to the processor and configured to receive adjustments to the settings of the photodetector from a user.

[0072] In some embodiments, a flow cytometer includes a flow cell. The flow cell of interest includes a cuvette configured to deliver particles in a flow stream. As discussed herein, a “flow cell” generally refers to an assembly containing a flow channel for delivering particles in a sheath fluid. The cuvette of interest has a passageway (i.e., a flow channel) running through it. The flow stream configured in the flow channel may include a liquid sample injected from a sample tube. In some cases, the flow cell includes a light-accessible flow channel. The cuvette may be made of, for example, quartz, glass, transparent plastic, etc. In some embodiments, the cuvette is formed of silica, for example, fused silica. In some cases, the flow cell is configured to be illuminated with light from a light source at one or more detection points. A “detection point” discussed herein refers to an area within the flow cell where particles are illuminated by light from a light source, for example, for analysis. The size of the detection point can be varied as needed. For example, when 0µm represents the optical axis of the light emitted by the light source, the detection point range can be from -50µm to 50µm, such as from -25µm to 40µm, and includes from -15µm to 30µm. Depending on certain considerations (e.g., the number and arrangement of lasers), multiple irradiation points can exist within the flow cell.

[0073] In some embodiments, the flow cell includes or is configured to be used with a sample injection port, which is configured to provide a sample to the flow cell. In embodiments, the sample injection system is configured to provide a suitable sample flow into the flow cell cavity (i.e., the flow channel). Depending on the desired flow characteristics, the sample rate delivered from the sample injection port to the flow cell can be 1 µL / min or more, for example 2 µL / min or more, for example 3 µL / min or more, for example 5 µL / min or more, for example 10 µL / min or more, for example 15 µL / min or more, for example 25 µL / min or more, for example 50 µL / min or more, and includes 100 µL / min or more. In some cases, the sample rate delivered from the sample injection port to the flow cell is 1 µL / sec or more, for example 2 µL / sec or more, for example 3 µL / sec or more, for example 5 µL / sec or more, for example 10 µL / sec or more, for example 15 µL / sec or more, for example 25 µL / sec or more, for example 50 µL / sec or more, and includes 100 µL / sec or more.

[0074] The sample injection port can be an orifice located in the inner wall of the lumen or a conduit located proximal to the lumen. When the sample injection port is an orifice located in the inner wall of the lumen, the orifice can be of any suitable shape. Cross-sectional shapes of interest include, but are not limited to: linear cross-sectional shapes, such as squares, rectangles, trapezoids, triangles, hexagons, etc.; curved cross-sectional shapes, such as circles, ellipses, etc.; and irregular shapes, such as parabolic bottoms coupled to a flat top. In some embodiments, the sample injection port has a circular orifice. The size of the sample injection port orifice can vary depending on its shape. In some cases, the opening size is 0.1 mm to 5.0 mm, for example 0.2 to 3.0 mm, for example 0.5 mm to 2.5 mm, for example 0.75 mm to 2.25 mm, for example 1 mm to 2 mm, and includes 1.25 mm to 1.75 mm, for example 1.5 mm.

[0075] In some cases, the sample injection port is a conduit located proximal to the flow cell cavity. For example, the sample injection port may be a conduit positioned so that its orifice is aligned with the flow cell orifice. When the sample injection port is a conduit aligned with the flow cell orifice, the cross-sectional shape of the sample injection tube can be any suitable shape, including but not limited to: straight cross-sectional shapes such as squares, rectangles, trapezoids, triangles, hexagons, etc.; curved cross-sectional shapes such as circles, ellipses, etc.; and irregular shapes, such as parabolic bottoms coupled to a flat top. The orifice of the conduit can vary depending on its shape; in some cases, the orifice opening is 0.1 mm to 5.0 mm, for example 0.2 to 3.0 mm, for example 0.5 mm to 2.5 mm, for example 0.75 mm to 2.25 mm, for example 1 mm to 2 mm, and includes 1.25 mm to 1.75 mm, for example 1.5 mm. The shape of the tip of the sample injection port may be the same as or different from the cross-sectional shape of the sample injection tube. For example, the orifice of the sample injection port may include a beveled tip with a bevel angle of 1° to 10°, such as 2° to 9°, such as 3° to 8°, such as 4° to 7°, and including a 5° bevel.

[0076] In some embodiments, the flow cell further includes a sheath fluid injection port configured to supply sheath fluid to the flow cell. In embodiments, the sheath fluid injection system is configured to supply a flow of sheath fluid into the flow cell cavity, for example, in combination with a sample to generate a laminar flow of sheath fluid around the sample flow. Depending on the desired flow characteristics, the rate of sheath fluid delivered to the flow cell cavity can be 25 µL / sec or more, for example 50 µL / sec or more, for example 75 µL / sec or more, for example 100 µL / sec or more, for example 250 µL / sec or more, for example 500 µL / sec or more, for example 750 µL / sec or more, for example 1000 µL / sec or more, and includes 2500 µL / sec or more.

[0077] In some embodiments, the sheath fluid injection port is an orifice located in the inner wall of the cavity. The sheath fluid injection port orifice can be of any suitable shape, with cross-sectional shapes of interest including but not limited to: straight cross-sectional shapes, such as squares, rectangles, trapezoids, triangles, hexagons, etc.; curved cross-sectional shapes, such as circles, ellipses, etc.; and irregular shapes, such as parabolic bottoms coupled to flat tops. The size of the sheath fluid injection port orifice can vary depending on the shape, and in some cases, the opening is 0.1 mm to 5.0 mm, for example 0.2 mm to 3.0 mm, for example 0.5 mm to 2.5 mm, for example 0.75 mm to 2.25 mm, for example 1 mm to 2 mm, and includes 1.25 mm to 1.75 mm, for example 1.5 mm.

[0078] The flow cytometer disclosed herein includes a light source configured to illuminate particles in a flow stream at a detection point within the flow cell. The number of light sources in the flow cytometer can vary. In some embodiments, the flow cytometer includes a single light source. Alternatively, in some cases, the flow cytometer may include multiple light sources. In some such cases, the number of light sources ranges from 2 to 10, for example, 2 to 5, including 2 to 4. Any convenient light source can be used as the light source described herein. In some embodiments, the light source is a laser. In embodiments, the laser can be any convenient laser, such as a continuous wave laser. For example, the laser can be a diode laser, such as an ultraviolet diode laser, a visible diode laser, and a near-infrared diode laser. In other embodiments, the laser can be a helium-neon (HeNe) laser. In some cases, the laser is a gas laser, such as a helium-neon laser, an argon laser, a krypton laser, a xenon laser, a nitrogen laser, a CO2 laser, a CO laser, an argon-fluorine (ArF) excimer laser, a krypton-fluorine (KrF) excimer laser, a xenon-chlorine (XeCl) excimer laser, or a xenon-fluorine (XeF) excimer laser, or a combination thereof. In other cases, the flow cytometers of this subject include dye lasers, such as stilbene, coumarin, or rhodamine lasers. In still other cases, lasers of interest include metal vapor lasers, such as helium-cadmium (HeCd) lasers, helium-mercury (HeHg) lasers, helium-selenium (HeSe) lasers, helium-silver (HeAg) lasers, strontium lasers, neon-copper (NeCu) lasers, copper lasers, or gold lasers, or combinations thereof. In other cases, the flow cytometers of this subject include solid-state lasers, such as ruby ​​lasers, Nd:YAG lasers, NdCrYAG lasers, Er:YAG lasers, Nd:YLF lasers, Nd:YVO4 lasers, Nd:YCa4O(BO3)3 lasers, Nd:YCOB lasers, Ti:sapphire lasers, thulium YAG lasers, ytterbium YAG lasers, ytterbium₂O₃ lasers, or cerium-doped lasers and combinations thereof.

[0079] The laser source according to some embodiments may also include one or more optical adjustment components. In some embodiments, the optical adjustment components are located between the light source and the flow cell and may include any means capable of changing the spatial width of the illumination or some other characteristics of the illumination from the light source (e.g., illumination direction, wavelength, beam width, beam intensity, and focal spot). The optical adjustment scheme may include any suitable device for adjusting one or more characteristics of the light source, including but not limited to lenses, mirrors, filters, optical fibers, wavelength splitters, pinholes, slits, collimation schemes, and combinations thereof. In some embodiments, the flow cytometer of interest includes one or more focusing lenses. In one example, the focusing lens may be a reducing lens. In other embodiments, the flow cytometer of interest includes optical fibers.

[0080] The light source can be positioned at any suitable distance from the flow cell, for example, 0.005 mm or more, such as 0.01 mm or more, 0.05 mm or more, 0.1 mm or more, 0.5 mm or more, 1 mm or more, 5 mm or more, 10 mm or more, 25 mm or more, and including distances of 100 mm or more. Furthermore, the light source can be positioned relative to the flow cell at any suitable angle, such as within the angle range of 10° to 90°, such as from 15° to 85°, such as from 20° to 80°, such as from 25° to 75°, including from 30° to 60°, and such as at 90°.

[0081] In some embodiments, the light source of interest includes a plurality of lasers configured to provide laser light for discrete illumination of the flowing stream. The plurality of lasers can be, for example, two or more lasers, three or more lasers, four or more lasers, five or more lasers, ten or more lasers, or even fifteen or more lasers configured to provide laser light for discrete illumination of the flowing stream. Depending on the wavelength of the light required to illuminate the flowing stream, each laser may have a specific wavelength varying from 200 nm to 1500 nm, for example from 250 nm to 1250 nm, for example from 300 nm to 1000 nm, for example from 350 nm to 900 nm, and including wavelengths from 400 nm to 800 nm. In some embodiments, the lasers of interest can include one or more of 405 nm, 488 nm, 561 nm, and 635 nm lasers.

[0082] In some embodiments, the light source is a beam generator configured to generate two or more frequency-shifted beams. In some cases, the beam generator includes a laser or a radio frequency (RF) generator configured to apply an RF drive signal to the acousto-optic device to generate two or more angle-deflected laser beams. In these embodiments, the laser can be a pulsed laser or a continuous-wave laser. For example, the lasers in the beam generator of interest include those listed above.

[0083] The acousto-optic device can be any suitable acousto-optic scheme configured to frequency-shift a laser using applied acoustic waves. In some embodiments, the acousto-optic device is an acousto-optic deflector. The acousto-optic device in this subject matter system is configured to generate an angle-deflected laser beam from light from a laser and an applied radio frequency (RF) drive signal. The RF drive signal can be applied to the acousto-optic device using any suitable RF drive signal source, such as a direct digital synthesizer (DDS), arbitrary waveform generator (AWG), or electrical pulse generator.

[0084] In an embodiment, the controller is configured to apply radio frequency drive signals to the acousto-optic device to generate a laser beam with a desired number of angular deflections in the output laser beam. For example, it is configured to apply three or more radio frequency drive signals, such as four or more radio frequency drive signals, such as five or more radio frequency drive signals, such as six or more radio frequency drive signals, such as seven or more radio frequency drive signals, such as eight or more radio frequency drive signals, such as nine or more radio frequency drive signals, such as ten or more radio frequency drive signals, such as fifteen or more radio frequency drive signals, such as 25 or more radio frequency drive signals, such as 50 or more radio frequency drive signals, and includes being configured to apply 100 or more radio frequency drive signals.

[0085] In some cases, in order to generate an intensity distribution of an angle-deflected laser beam in the output laser beam, the controller is configured to apply an amplitude-varying radio frequency drive signal, such as from about 0.001V to about 500V, for example from about 0.005V to about 400V, for example from about 0.01V to about 300V, for example from about 0.05V to about 200V, for example from about 0.1V to about 100V, for example from about 0.5V to about 75V, for example from about 1V to 50V, for example from about 2V to 40V, for example from 3V to about 30V, and including from about 5V to about 25V. In some embodiments, each applied radio frequency drive signal has a frequency from about 0.001 MHz to 500 MHz, for example from about 0.005 MHz to about 400 MHz, for example from about 0.01 MHz to about 300 MHz, for example from about 0.05 MHz to about 200 MHz, for example from about 0.1 MHz to about 100 MHz, for example from about 0.5 MHz to about 90 MHz, for example from about 1 MHz to about 75 MHz, for example from about 2 MHz to about 70 MHz, for example from about 3 MHz to about 65 MHz, for example from about 4 MHz to about 60 MHz, and including from about 5 MHz to about 50 MHz.

[0086] In some embodiments, the controller has a processor with a memory operatively coupled to the processor, such that the memory includes instructions stored thereon that, when executed by the processor, cause the processor to produce an output laser beam with angled deflections having a desired intensity distribution. For example, the memory may include instructions to produce two or more laser beams with the same intensity, such as three or more, four or more, five or more, ten or more, 25 or more, or 50 or more, and the memory may include instructions to produce 100 or more laser beams with the same intensity. In other embodiments, the memory may include instructions to produce two or more laser beams with different intensities, such as three or more, four or more, five or more, ten or more, 25 or more, or 50 or more, and the memory may include instructions to produce 100 or more laser beams with different intensities.

[0087] In some embodiments, the controller has a processor having a memory operatively coupled to the processor, such that the memory includes instructions stored thereon that, when executed by the processor, cause the processor to generate an output laser beam with increasing intensity along a horizontal axis from the edge to the center. In these examples, the intensity of the angle-deflected laser beam at the center of the output beam along the horizontal axis can be from 0.1% to about 99%, for example from 0.5% to about 95%, for example from 1% to about 90%, for example from about 2% to about 85%, for example from about 3% to about 80%, for example from about 4% to about 75%, for example from about 5% to about 70%, for example from about 6% to about 65%, for example from about 7% to about 60%, for example from about 8% to about 55%, and includes about 10% to about 50%. In other embodiments, the controller has a processor having a memory operatively coupled to the processor, such that the memory includes instructions stored thereon that, when executed by the processor, cause the processor to generate an output laser beam with increasing intensity along a horizontal axis from the edge to the center. In these cases, the intensity of the angle-deflected laser beam at the edge of the output laser beam along the horizontal axis can be from 0.1% to about 99%, for example from 0.5% to about 95%, for example from 1% to about 90%, for example from about 2% to about 85%, for example from about 3% to about 80%, for example from about 4% to about 75%, for example from about 5% to about 70%, for example from about 6% to about 65%, for example from about 7% to about 60%, for example from about 8% to about 55%, and includes about 10% to about 50%. In other embodiments, the controller has a processor having a memory operatively coupled to the processor, such that the memory includes instructions stored thereon that, when executed by the processor, cause the processor to produce an output laser beam with a Gaussian intensity distribution along the horizontal axis. In still other embodiments, the controller has a processor having a memory operatively coupled to the processor, such that the memory includes instructions stored thereon that, when executed by the processor, cause the processor to produce an output laser beam with a top hat intensity distribution along the horizontal axis.

[0088] In embodiments, the beam generator of interest can be configured to generate spatially separated angle-deflected laser beams within the output laser beam. Depending on the applied radio frequency drive signal and the desired illumination distribution of the output laser beam, the angle-deflected laser beams can be spaced 0.001 μm or greater, for example, 0.005 μm or greater, for example, 0.01 μm or greater, for example, 0.05 μm or greater, for example, 0.1 μm or greater, for example, 0.5 μm or greater, for example, 1 μm or greater, for example, 5 μm or greater, for example, 10 μm or greater, for example, 100 μm or greater, for example, 500 μm or greater, for example, 1000 μm or greater, including 5000 μm or greater. In some embodiments, the system is configured to generate overlapping angle-deflected laser beams within the output laser beam, for example, overlapping with adjacent angle-deflected laser beams along the horizontal axis of the output laser beam. The overlap between adjacent angle-deflected laser beams (such as spot overlap) can be 0.001 μm or larger, for example, 0.005 μm or larger, such as 0.01 μm or larger, 0.05 μm or larger, 0.1 μm or larger, 0.5 μm or larger, 1 μm or larger, 5 μm or larger, 10 μm or larger, including 100 μm or larger.

[0089] In some cases, beam generators configured to generate two or more frequency-shifted beams include, for example, U.S. Patent Nos. 9,423,353, 9,784,661, 9,983,132, 10,006,852, 10,036,699, 10,078,045, 10,222,316, 10,288,546, 10,324,019, 10,408,758, 10,451,538, 10,620,111, and 10,684,2 The laser excitation modules described in patents 11, 10,845,295, 10,935,482, 10,935,485, 11,105,728, 11,280,718, 11,327,016, 11,366,052, 11,371,937, 11,692,926, 11,630,053, 11,774,343, 11,940,369 and 11,946,851; the disclosures of these patents are incorporated herein by reference.

[0090] Furthermore, the flow cytometer includes detectors configured to collect light emitted by irradiated particles. The photodetectors are configured to detect particle-modulated light transmitted by an fiber optic light collecting element and generate a signal based on the characteristics of that light, such as intensity. For example, one or more particle-modulated photodetectors may include one or more side-scatter photodetectors for detecting side-scattered light wavelengths (i.e., light refracted and reflected from the surface and internal structure of the particle). In some embodiments, the flow cytometer includes a single side-scatter photodetector. In other embodiments, the flow cytometer includes multiple side-scatter photodetectors, such as two or more, three or more, four or more, and five or more.

[0091] The side-scattering light detector described herein can use any suitable detector for detecting the collected light. Detectors of interest can include, but are not limited to, optical sensors or detectors such as active pixel sensors (APS), avalanche photodiodes, image sensors, charge-coupled devices (CCDs), enhancement-mode charge-coupled devices (ICCDs), photon counters, calorimeters, photoresistors, photodiodes, photomultiplier tubes (PMTs), phototransistors, quantum dot photoconductors, or combinations thereof, and other detectors. In some embodiments, the collected light is measured using a charge-coupled device (CCD), a semiconductor charge-coupled device (CCD), an active pixel sensor (APS), a complementary metal-oxide-semiconductor (CMOS) image sensor, or an N-type metal-oxide-semiconductor (NMOS) image sensor. In some embodiments, the detector is a photomultiplier tube, for example, with an effective detection surface area per region ranging from 0.01 cm². 2 Up to 10 cm 2 Photomultiplier tubes, for example, from 0.05 cm 2 Up to 9 cm 2 For example, from 0.1 cm 2 Up to 8 cm 2 For example, from 0.5 cm 2 Up to 7 cm 2 and including from 1 cm 2 Up to 5 cm 2 .

[0092] In one embodiment, the flow cytometer of this subject also includes a fluorescence detector configured to detect light at one or more fluorescence wavelengths. In other embodiments, the flow cytometer includes a plurality of fluorescence detectors, such as two or more, three or more, four or more, five or more, ten or more, fifteen or more, and including twenty or more.

[0093] Any suitable detector for detecting the collected light can be used in conjunction with the fluorescence detector described herein. Detectors of interest can include, but are not limited to, optical sensors or detectors such as active pixel sensors (APS), avalanche photodiodes, image sensors, charge-coupled devices (CCDs), enhancement-mode charge-coupled devices (ICCDs), photon counters, calorimeters, photoresistors, photodiodes, photomultiplier tubes (PMTs), phototransistors, quantum dot photoconductors, or combinations thereof, and other detectors. In some embodiments, the collected light is measured using a charge-coupled device (CCD), a semiconductor charge-coupled device (CCD), an active pixel sensor (APS), a complementary metal-oxide-semiconductor (CMOS) image sensor, or an N-type metal-oxide-semiconductor (NMOS) image sensor. In some embodiments, the detector is a photomultiplier tube, for example, with an effective detection surface area per region ranging from 0.01 cm². 2 Up to 10 cm 2 Photomultiplier tubes, for example, from 0.05 cm 2 Up to 9 cm 2 For example, from 0.1 cm 2 Up to 8 cm 2 For example, from 0.5 cm 2 Up to 7 cm 2 and including from 1 cm 2 Up to 5 cm 2 .

[0094] When the flow cytometer of this subject includes multiple fluorescence detectors, each fluorescence detector can be identical, or the collection of fluorescence detectors can be a combination of detectors of different types. For example, when the flow cytometer of this subject includes two fluorescence detectors, in some embodiments, the first fluorescence detector is a CCD-type device and the second fluorescence detector (or imaging sensor) is a CMOS-type device. In other embodiments, both the first and second fluorescence detectors are CCD-type devices. In still other embodiments, both the first and second fluorescence detectors are CMOS-type devices. In still other embodiments, the first fluorescence detector is a CCD-type device and the second fluorescence detector is a photomultiplier tube (PMT). In still other embodiments, the first fluorescence detector is a CMOS-type device and the second fluorescence detector is a photomultiplier tube. In still other embodiments, both the first and second fluorescence detectors are photomultiplier tubes.

[0095] In embodiments of this disclosure, the fluorescence detector of interest is configured to measure collected light at one or more wavelengths, such as two or more wavelengths, such as five or more different wavelengths, such as ten or more different wavelengths, such as 25 or more different wavelengths, such as 50 or more different wavelengths, such as 100 or more different wavelengths, such as 200 or more different wavelengths, such as 300 or more different wavelengths, and includes measuring light emitted by a sample in the flow stream at 400 or more different wavelengths. In some embodiments, two or more detectors in the module described herein are configured to measure collected light at the same or overlapping wavelengths.

[0096] In some embodiments, the fluorescence detector of interest is configured to measure collected light within a wavelength range (e.g., 200 nm to 1000 nm). In some embodiments, the detector of interest is configured to collect a spectrum within a wavelength range. For example, a flow cytometer can include one or more detectors configured to collect a spectrum within one or more wavelength ranges from 200 nm to 1000 nm. In other embodiments, the detector of interest is configured to measure light emitted by a sample in a flowing stream at one or more specific wavelengths. For example, the module can include one or more detectors configured to measure light at 450 nm, 518 nm, 519 nm, 561 nm, 578 nm, 605 nm, 607 nm, 625 nm, 650 nm, 660 nm, 667 nm, 670 nm, 668 nm, 695 nm, 710 nm, 723 nm, 780 nm, 785 nm, 647 nm, 617 nm, and any combination thereof. In some embodiments, one or more detectors can be configured to pair with a specific fluorophore, such as a fluorophore used with the sample in a fluorescence assay.

[0097] Flow cytometers can include one or more suitable mechanisms for providing sheath fluid and sample flow to the sample fluid input coupler and the sheath fluid input coupler. For example, the sample fluid input coupler can be fluidly connected to a sample fluid line (e.g., tubing) fluidly connected to a sample fluid reservoir. Similarly, the sheath fluid input coupler can be fluidly connected to a sheath fluid line fluidly connected to a sheath fluid reservoir. Similarly, flow cytometers can include one or more suitable mechanisms for managing waste from the flow stream. A fluid output coupler can be fluidly connected to a waste flow line fluidly connected to a waste reservoir. U.S. Patent Application Publication No. 2022 / 0341838 provides a fluid management system applicable to the flow cytometers of the present invention, the disclosure of which is incorporated herein by reference in its entirety.

[0098] Suitable flow cytometry systems may include, but are not limited to, Ormerod (ed.), Flow Cytometry: A Practical Approach, Oxford Univ. Press (1997); Jaroszeski et al. (eds.), FlowCytometry Protocols, Methods in Molecular Biology No. 91, Humana Press (1997); Practical Flow Cytometry, 3rd ed., Wiley-Liss (1995); Virgo et al. (2012) Ann Clin Biochem. Jan;49(pt 1):17-28; Linden et al., Semin Throm Hemost. 2004 Oct;30(5):502-11; Alison et al. J Pathol, 2010 Dec; 222(4):335-344; and Herbig et al. (2007) Crit Rev Ther Drug Carrier Syst. The public content described in 24(3):203-255 is incorporated herein by reference.In some cases, flow cytometry systems of interest include the BD Biosciences FACSCanto™ flow cytometer, BD Biosciences FACSCanto™ II flow cytometer, BD Accuri™ flow cytometer, BD Accuri™ C6 Plus flow cytometer, BD Biosciences FACSCelesta™ flow cytometer, BD Biosciences FACSLyric™ flow cytometer, BD Biosciences FACSVerse™ flow cytometer, BD Biosciences FACSymphony™ flow cytometer, BD Biosciences LSRFortessa™ flow cytometer, BD Biosciences LSRFortessa™ flow cytometer, BD Biosciences LSRFortessa™ X-20 flow cytometer, BD Biosciences FACSPresto™ flow cytometer, BD Biosciences FACSVia™ flow cytometer, and BD Biosciences FACSCalibur™ cell sorter, BD Biosciences FACSCount™ cell sorter, BD Biosciences FACSLyric™ cell sorter, BD Biosciences Via™ cell sorter, and BD... Biosciences Influx™ Cell Sorter, BD Biosciences Jazz™ Cell Sorter, BD Biosciences Aria™ Cell Sorter, BD Biosciences FACSAria™ II Cell Sorter, BD Biosciences FACSAria™ III Cell Sorter, BD Biosciences FACSAria™ Fusion Cell Sorter, BD Biosciences FACSMelody™ Cell Sorter, BD Biosciences FACSymphony™ S6 Cell Sorter, BD Biosciences FACSDiscover™ Cell Sorter, or similar products.

[0099] In some embodiments, the subject system is a flow cytometry system, such as the system described in the following U.S. patents: 10,663,476, 10,620,111, 10,613,017, 10,605,713, 10,585,031, and 10,578,542. 10,578,469, 10,481,074, 10,302,545, 10,145,793, 10,113,967, 10,006,852, 9,952,076, 9,933,341, 9,726,527, 9,453,789, 9,200,334, 9,097,640, 9,095,494, 9,092,034, 8,975,595, 8,753,573, 8,233,1 The disclosures of the following patents are incorporated herein by reference in their entirety: 46, 8,140,300, 7,544,326, 7,201,875, 7,129,505, 6,821,740, 6,813,017, 6,809,804, 6,372,506, 5,700,692, 5,643,796, 5,627,040, 5,620,842, 5,602,039, 4,987,086, and 4,498,766.

[0100] In some embodiments, the flow cytometer is configured as an imaging flow cytometer. For example, in some cases, the subject system is a flow cytometry system configured to image particles in a flowing stream using fluorescence imaging with radio frequency labeled emission (FIRE), such as those described by Diebold et al. in Nature Photonics, Vol. 7 (10); those described in 806-810 (2013); and U.S. Patent Nos. 9,423,353, 9,784,661, 9,983,132, 10,006,852, 10,036,699, 10,078,045, 10,222,316. The disclosures of those listed in 10,288,546, 10,324,019, 10,408,758, 10,451,538, 10,620,111, 10,684,211, 10,845,295, 10,935,482, 10,935,485, 11,105,728, 11,280,718, 11,327,016, 11,366,052, 11,371,937, 11,692,926, 11,630,053, 11,774,343, 11,940,369, and 11,946,851 are incorporated herein by reference. In some embodiments, the flow cytometer is a particle sorter, and the particle sorter is an image-enabled particle sorter. Image-enabled particle sorters are described in the following U.S. Patent Nos. 10,324,019, 10,620,111, 11,105,728, and 11,774,343, and in 18 / 537,103, 18 / 657,618, 18,657,623, and 18 / 657,633, the disclosures of which are incorporated herein by reference in their entirety.

[0101] Figure 2 A flow cytometry system 200 according to an exemplary embodiment of the present disclosure is shown. The system 200 includes a laser 201 configured to irradiate particles 211 in a flow stream 214 at a detection point 215 within a flow cell 210. Although Figure 2 The example shows a single laser, but it should be understood that multiple lasers can also be used. The laser beam from laser 201 is directed to focusing lens 202, which focuses the laser beam onto the region of the fluid flow containing sample particles 211 within flow cell 210. Flow cell 210 is part of a fluid system that directs particles (typically one at a time) in the flow to the focused laser beam for detection. Alternatively, in the case of a flow cytometer that is an airflow cytometer, a nozzle tip can be used.

[0102] like Figure 2As shown, flow cell 210 is fluidly connected to a sheath fluid reservoir 203 containing sheath fluid and a sample fluid reservoir 204 containing sample fluid. Sheath fluid from sheath fluid reservoir 203 is supplied to at least one sheath fluid injection port 208 via a conduit (i.e., a sheath fluid line) 207. Furthermore, a sample flow containing particles 211 from sample fluid reservoir 204 is supplied to sample injection port 206 via a conduit (i.e., a sample fluid line) 205. Sample injection port 206 is fluidly connected to a sample injector 213 (e.g., a sample injection needle), configured to introduce particles 211 into the interior of flow cell 210. Particles 211 are hydrodynamically focused via the sheath fluid entering from sheath fluid injection port 208, such that a flow stream 214 is formed downstream of the tapered portion 212 of flow cell 210. Particles emitted at the distal end of flow cell 210 can be processed or collected by any suitable method, such as collection at the distal end of flow cell 210, depending on the type of flow cytometry performed, for example, via a waste line. Alternatively, the particles can be sorted.

[0103] Light from one or more laser beams interacts with particles 211 in the sample through diffraction, refraction, reflection, scattering, and absorption, and is then re-emitted at various wavelengths, depending on the particle's characteristics, such as its size, internal structure, and the presence of one or more fluorescent molecules attached to or naturally present on or within the particle. The emitted fluorescent light, as well as the diffracted, refracted, reflected, and scattered light, can be directed to one or more detectors. Specifically, forward scattered light (FSC) is directed to a forward scattered light detector 223. The forward scattered light detector 223 is located slightly off-center from the axis of the direct beam passing through the flow cell 210 and is configured to detect diffracted light, i.e., excitation light that passes primarily forward or surrounds the particle. The intensity of the light detected by the forward scattered light detector 223 depends on the overall size of the particle, and the forward scattered light detector may include, for example, a photodiode. Between the forward scattered light detectors 223 are a filter 221a and a scattering baffle 222. The filter 221a can be configured to filter out non-FSC light of at least one wavelength, and the scattering baffle 222 can be configured to prevent incident light (i.e. non-scattered light) from the laser 201 from being detected by the forward scattering detector 223.

[0104] Furthermore, side-scattered light (SSC) is detected by side-scattered light detector 224. In other words, side-scattered light detector 224 is configured to detect refracted and reflected light from the surface and internal structure of particle 211, which tends to increase with increasing structural complexity of the particle. Figure 2In the example, the flow cytometer 200 includes a dichroic mirror 220a configured to reflect SSC light to a side-scatter light detector 224 while allowing non-SSC (e.g., fluorescence) light to pass through. A filter 221b is configured to block at least one wavelength of non-SSC light from being detected by the side-scatter light detector 224. A plurality of fluorescence detectors 225a-225c are also shown in the figure, each configured to detect fluorescence at a different wavelength. For example, the dichroic mirror 220b can be configured to reflect fluorescence (FL) corresponding to a first wavelength (or wavelength range) to the fluorescence detector 225a while allowing light of other wavelengths to pass through. The filter 221c can be configured to block the fluorescence detector 225a from detecting light of at least one wavelength that does not correspond to the first wavelength (or wavelength range). Similarly, the dichroic mirror 220c is configured to reflect FL light corresponding to a second wavelength (or wavelength range) to the fluorescence detector 225b while allowing light of a third wavelength (or wavelength range) to pass through for detection by the fluorescence detector 225c. Filter 221d is configured to prevent fluorescence detector 225 from detecting light of at least one wavelength that does not correspond to the second wavelength (or wavelength range), while filter 221e is configured to prevent fluorescence detector 225c from detecting light of at least one wavelength that does not correspond to the third wavelength (or wavelength range).

[0105] Those skilled in the art will recognize that the flow cytometers according to embodiments of this disclosure are not limited to... Figure 2 The flow cytometer shown is not limited to any flow cytometer known in the art. For example, a flow cytometer can have any number of lasers, beam splitters, filters, and detectors in various wavelengths and configurations. For example, although... Figure 2 The example shown has three fluorescence detectors for illustrative purposes, but it should be understood that any suitable number of fluorescence detectors can be used.

[0106] During operation, the cytometer is controlled by a controller / processor 290. Measurement data from the detectors can be stored in memory 295 and processed by the controller / processor 290. Although not explicitly shown, the controller / processor 290 is coupled to the detectors to receive output signals from them and can also be coupled to the electrical and electromechanical components of the flow cytometer to control the laser 201, fluid flow parameters, etc. The system is also capable of providing input / output (I / O) capabilities 297. Memory 295, controller / processor 290, and I / O 297 can be provided entirely as integral components of the flow cytometer. In such embodiments, a display can also be provided as part of the I / O function 297 for displaying experimental data to the user of the cytometer 200. Alternatively, some or all of the memory 295, controller / processor 290, and I / O capabilities can be part of one or more external devices (e.g., a general-purpose computer). In some embodiments, some or all of the memory 295 and controller / processor 290 are capable of wireless or wired communication with the flow cytometer. The controller / processor 290, combined with memory 295 and I / O 297, can be configured to perform various functions related to the preparation and analysis of flow cytometry experiments.

[0107] In a flow cytometry experiment, different fluorescent molecules in the fluorophore panel will emit light within their respective characteristic wavelengths. Specific fluorescent labels used in the experiment and their associated fluorescence emission bands can be selected to approximately coincide with the filter window range of the detector. I / O 297 can be configured to receive data related to a flow cytometry experiment having a set of fluorescent labels and multiple cell populations with multiple markers, each cell population having a subset of multiple markers. I / O 297 can also be configured to receive biological data assigning one or more markers to one or more cell populations, marker density data, emission spectral data, data assigning labels to one or more markers, and flow cytometry configuration data. Flow cytometry experiment data, such as label spectral characteristics and flow cytometry configuration data, can also be stored in memory 295. Controller / processor 290 can be configured to evaluate one or more assignment schemes for label assignment to markers.

[0108] In some embodiments, the subject matter system is a particle sorting system configured to sort particles using closed particle sorting modules, such as those described in U.S. Patent Application Publication No. 2017 / 0299493, filed March 28, 2017, the disclosure of which is incorporated herein by reference. In some embodiments, a sorting decision module having multiple sorting decision units is used to sort particles (such as cells) in a sample, such as those described in U.S. Patent Application Publication No. 2020 / 0256781, filed December 23, 2019, the disclosure of which is incorporated herein by reference. In some embodiments, a system for sorting components of a sample includes a particle sorting module with deflection plates, such as those described in U.S. Patent Application Publication No. 2017 / 0299493, filed March 28, 2017, the disclosure of which is incorporated herein by reference.

[0109] In some embodiments, the system is an image-enabled particle sorter that uses radio frequency markers to emit fluorescence imaging, for example... Figure 3As shown, the particle sorter 300 includes an illumination assembly 300a, which includes a light source 301 (e.g., a 488 nm laser) that generates an output beam 301a. This output beam 301a is split into beams 302a and 302b by a beam splitter 302. Beam 302a propagates through an acousto-optic device 303 (e.g., an acousto-optic deflector (AOD)) to generate an output beam 303a with one or more angled deflections. In some examples, the output beam 303a generated from the acousto-optic device 303 includes a local oscillator beam and multiple radio frequency comb beams. Beam 302b propagates through an acousto-optic device 304 (e.g., an acousto-optic deflector (AOD)) to generate an output beam 304a with one or more angled deflections. In some examples, the output beam 304a generated from the acousto-optic device 304 includes a local oscillator beam and multiple radio frequency comb beams. Output beams 303a and 304a, generated by acousto-optic devices 303 and 304 respectively, are combined by beam splitter 305 to produce output beam 305a, which is transmitted through optical component 306 (e.g., objective lens) to illuminate particles in flow cell 307. In some embodiments, acousto-optic device 303 (AOD) splits a single laser beam into an array of small beams, each with a different optical frequency and angle. A second AOD 304 tunes the optical frequency of a reference beam, which is then overlapped with the array of small beams at beam combiner 305. In some embodiments, the light illumination system having a light source and acousto-optic devices may also include those described in Schraivogel et al., “High-speed fluorescence image-enabled cell sorting”, Science (2022), 375(6578): 315-320, and U.S. Patent Publication No. 2021 / 0404943, the disclosure of which is incorporated herein by reference in its entirety.

[0110] Output beam 305a irradiates sample particles 308 (e.g., together with sheath fluid 309) propagating through flow cell 307 at irradiation region 310. As shown in irradiation region 310, multiple beams (e.g., RF offset beams with angular deflection appearing as dots on irradiation region 310) overlap with the reference local oscillator beam (appearing as a shadow line on irradiation region 310). Due to their different optical frequencies, the overlapping beams exhibit beat frequency behavior, resulting in each small beam carrying a different frequency f. 1-n Sine modulation.

[0111] Light from the illuminated sample is transmitted to a light detection system 300b comprising multiple photodetectors. The light detection system 300b includes a forward-scattering photodetector 311 for generating a forward-scattering image 311a and a side-scattering photodetector 312 for generating a side-scattering image 312a. The light detection system 300b also includes a bright-field photodetector 313 for generating a light loss image 313a. In some embodiments, the forward-scattering detector 311 and the side-scattering detector 312 are photodiodes (e.g., avalanche photodiodes, APDs). In some cases, the bright-field photodetector 313 is a photomultiplier tube (PMT). Fluorescence from the illuminated sample is also detected by fluorescence photodetectors 314-317. In some cases, photodetectors 314-317 are photomultiplier tubes. Light from the illuminated sample is directed by a beamsplitter 320 to the side-scattering detection channel 312 and the fluorescence detection channels 314-317. The optical detection system 300b includes bandpass optical components 321, 322, 323, and 324 (e.g., dichroic mirrors) for propagating light of a predetermined wavelength to photodetectors 314-317. In some cases, optical component 321 has a 534 nm / 40 nm bandpass. In some cases, optical component 322 has a 586 nm / 42 nm bandpass. In some cases, optical component 323 has a 700 nm / 54 nm bandpass. In some cases, optical component 324 has a 783 nm / 56 nm bandpass. The first number indicates the center of the spectral band. The second number provides the range of the spectral band. Therefore, the 510 / 20 filter extends 10 nm on each side of the center of the spectral band, or from 500 nm to 520 nm.

[0112] Data signals generated in response to light detected by scattered light detection channels 311, 312, 313, and 314-317 are digitally processed in real time by processors 350 and 351. Images 311a-317a can be generated in each light detection channel based on the data signals generated by processors 350 and 351. Image-enabled sorting is performed in response to a sorting signal generated in sorting trigger 352. Sorting assembly 300c includes deflection plate 331 for deflecting particles into sample container 332 or waste stream 333. In some cases, sorting assembly 300c is configured to sort particles using a closed particle sorting module, such as those described in U.S. Patent Publication No. 2017 / 0299493, filed March 28, 2017, the disclosure of which is incorporated herein by reference in its entirety. The sorting component 300c includes a sorting decision module having multiple sorting decision units, such as those described in U.S. Patent Publication No. 2020 / 0256781, the disclosure of which is incorporated herein by reference in its entirety.

[0113] In some embodiments, the system is a particle analyzer, wherein the particle analysis system 401 ( Figure 4 It can be used to analyze and characterize particles, whether or not the particles are physically sorted into a collection container. Figure 4 A functional block diagram of a particle analysis system for computation-based sample analysis and particle characterization is shown. In some embodiments, particle analysis system 401 is a fluid system. Particle analysis system 401 includes fluid system 402. Fluid system 402 may include or be coupled to sample tube 405 and a fluid column moving within the sample tube, wherein particles 403 (e.g., cells) in the sample move along a common sample path 409.

[0114] The particle analysis system 401 includes a detection system 404 configured to collect signals from each particle as it passes through one or more detection stations along a common sample path. Detection station 408 generally refers to a monitoring area 407 along the common sample path. In some embodiments, detection may include detecting light or one or more other characteristics of particle 403 as it crosses the monitoring area 407. Figure 4 The image shows a detection station 408 with a monitoring area 407. Some embodiments of the particle analysis system 401 may include multiple detection stations. Furthermore, some detection stations can monitor more than one area.

[0115] Each signal is assigned a signal value to form a data point for each particle. As described above, this data is referred to as event data. The data points can be multi-dimensional data points, including numerical values ​​of various characteristics measured for the particle. The detection system 404 is configured to collect a series of such data points within a first time interval.

[0116] The particle analysis system 401 may also include a control system 406. The control system 406 may include one or more processors, amplitude control circuitry, and / or frequency control circuitry. The illustrated control system may be operationally associated with the fluid system 402. The control system may be configured to generate a calculated signal frequency for at least a portion of the first time interval based on the number of data points collected by the detection system 404 during the first time interval. The control system 406 may also be configured to generate an experimental signal frequency based on the number of data points in that portion of the first time interval. The control system 406 may also additionally compare the experimental signal frequency with a calculated signal frequency or a predetermined signal frequency.

[0117] Figure 5 A functional block diagram of an example particle analyzer control system (e.g., analysis controller 500) for analyzing and displaying biological events is shown. Analysis controller 500 can be configured to implement various processes for controlling the graphical display of biological events.

[0118] The particle analyzer or sorting system 502 is configured to acquire biological event data. For example, a flow cytometer can generate flow cytometry event data. The particle analyzer 502 can be configured to provide the biological event data to the analysis controller 500. A data communication channel can be included between the particle analyzer or sorting system 502 and the analysis controller 500. The biological event data can be provided to the analysis controller 500 via the data communication channel.

[0119] Analysis controller 500 may be configured to receive biological event data from particle analyzer or sorting system 502. The biological event data received from particle analyzer or sorting system 502 may include flow cytometry event data. Analysis controller 500 may be configured to provide a graphical display to display device 506 including a first graph containing the biological event data. For example, analysis controller 500 may also be configured to render regions of interest as gates around the cluster of biological event data shown on display device 506, for example, overlaid on the first graph. In some embodiments, a gate may be a logical combination of one or more graphical regions of interest plotted on a single-parameter histogram or bivariate graph. In some embodiments, the display device may be used to display particle parameters or saturation detector data.

[0120] The analysis controller 500 can be further configured to display the biological event data inside the door on the display device 506 in a manner different from other biological event data outside the door. For example, the analysis controller 500 can be configured to display the biological event data contained inside the door in a different color than the biological event data outside the door. The display device 506 can be a monitor, tablet computer, smartphone, or other electronic device configured to display a graphical interface.

[0121] The analysis controller 500 can be configured to receive a door selection signal from a first input device to identify a door. For example, the first input device can be implemented as a mouse 510. The mouse 510 can initiate a door selection signal to the analysis controller 500 to identify a door to be displayed or manipulated via the display device 506 (e.g., by clicking the door or its interior when the cursor is positioned on the desired door). In some embodiments, the first device can be implemented as a keyboard 508 or other means for providing input signals to the analysis controller 500, such as a touchscreen, stylus, optical detector, or voice recognition system. Some input devices may include multiple input functions. In these embodiments, each input function can be considered an input device. For example, such as... Figure 5 As shown, the mouse 510 can include a right mouse button and a left mouse button, and each button can generate a trigger event.

[0122] Triggering events may cause the analysis controller 500 to change the way data is displayed, the portion of data actually displayed on the display device 506, and / or provide input for further processing, such as selecting groups of interest for particle sorting.

[0123] In some embodiments, the analysis controller 500 may be configured to detect when the mouse 510 initiates gate selection. The analysis controller 500 may also be configured to automatically modify the drawing visualization to facilitate the gating process. This modification may be based on a specific distribution of the biological event data received by the analysis controller 500.

[0124] The analysis controller 500 can be connected to a storage device 504. The storage device 504 can be configured to receive and store biological event data from the analysis controller 500. The storage device 504 can also be configured to receive and store flow cytometry event data from the analysis controller 500. The storage device 504 can also be configured to allow the analysis controller 500 to retrieve biological event data, such as flow cytometry event data.

[0125] Display device 506 can be configured to receive display data from analysis controller 500. This display data may include graphs of biological event data and gates outlining portions of the graphs. Display device 506 can also be configured to change the presented information based on input received from analysis controller 500 and from particle analyzer 502, storage device 504, keyboard 508, and / or mouse 510.

[0126] In some embodiments, the analysis controller 500 may generate a user interface to receive sample events for sorting. For example, the user interface may include controls for receiving sample events or sample images. The sample events, images, or sample gates may be provided before collecting event data for the samples, or based on an initial set of events from a portion of the samples.

[0127] Figure 6A This is a schematic diagram of a particle sorting system 600 (e.g., a particle analyzer or sorting system 502) according to one embodiment presented herein. In some embodiments, the particle sorting system 600 is a cell sorting system. Figure 6AAs shown, a droplet-forming transducer 602 (e.g., a piezoelectric oscillator) is coupled to a fluid conduit 601, which can be coupled to a nozzle 603, and may include or be a nozzle 603. Within the fluid conduit 601, a sheath fluid 604 hydrodynamically aggregates a sample flow 606 containing particles 609 into a moving fluid column 608 (e.g., a stream). Within the moving fluid column 608, particles 609 (e.g., cells) are arranged in a single file to pass through a monitoring area 611 (e.g., a laser-stream intersection) irradiated by an irradiation source 612 (e.g., a laser). Vibration of the droplet-forming transducer 602 causes the moving fluid column 608 to break into multiple droplets 610, some of which contain particles 609.

[0128] In operation, a detection station 614 (e.g., an event detector) identifies when a particle (or cell) of interest crosses a monitoring area 611. The detection station 614 is fed into a timing circuit 628, which in turn feeds into a flash charge circuit 630. At the droplet break point, notified by a timed droplet delay (Δt), a flash charge can be applied to a moving fluid column 608, causing the droplet of interest to carry a charge. The droplet of interest may include one or more particles or cells to be sorted. The charged droplet can then be sorted by activating a deflection plate (not shown) to deflect the charged droplet into a container, such as a collection tube or a porous or microporous sample plate, where the droplet of interest can be associated with a pore or micropore. Figure 6A As shown, the droplets can be collected in the discharge container 638.

[0129] A detection system 616 (e.g., a droplet boundary detector) is used to automatically determine the phase of the droplet drive signal as a particle of interest crosses the monitoring region 611. An exemplary droplet boundary detector is described in U.S. Patent No. 7,679,039, the entire contents of which are incorporated herein by reference. The detection system 616 enables the instrument to accurately calculate the position of each detected particle within the droplet. The detection system 616 may be fed an amplitude signal 620 and / or a phase signal 618, which are then fed (via amplifier 622) to an amplitude control circuit 626 and / or a frequency control circuit 624. The amplitude control circuit 626 and / or the frequency control circuit 624 further control the droplet forming transducer 602. The amplitude control circuit 626 and / or the frequency control circuit 624 may be included in a control system.

[0130] In some embodiments, sorting electronics (e.g., detection system 616, detection station 614, and processor 640) may be coupled to a memory configured to store detected events and sorting decisions based thereon. The sorting decisions may be included in the event data of the particles. In some embodiments, detection system 616 and detection station 614 may be implemented as a single detection unit or communication coupling, such that event measurements can be collected by one of detection system 616 or detection station 614 and provided to non-collection elements.

[0131] Figure 6B This is a schematic diagram of a particle sorting system according to an embodiment of the present document. Figure 6B The particle sorting system 600 shown includes deflection plates 652 and 654. Charge can be applied via a stream-charging wire in the barbs. This generates a droplet stream 610 containing particles 610 for analysis. The particles can be illuminated with one or more light sources (e.g., lasers) to produce light scattering and fluorescence information. The particle information is processed by, for example, sorting electronics or other detection systems. Figure 6B (Not shown in the image) is analyzed. Deflection plates 652 and 654 can be independently controlled to attract or repel charged droplets, thereby guiding the droplets to a destination collector (e.g., one of 672, 674, 676, or 678). Figure 6B As shown, deflector plates 652 and 654 can be controlled to allow particles to enter container 674 along a first path 662 or along a second path 668. If the particles are not of interest (e.g., do not exhibit scattering or illumination information within a specified sorting range), the deflector plates can allow the particles to continue flowing along flow path 664. Such uncharged droplets can be introduced into a waste container via, for example, a suction device 670.

[0132] It can include sorting electronics to initiate the collection of measurement results, receive the fluorescence signal of the particles, and determine how to adjust the deflection plate to sort the particles. Figure 6B An example implementation of the illustrated embodiment includes the BD FACSAria™ series flow cytometer, commercially available from Becton Dickinson, Inc. (Franklin Lake, New Jersey).

[0133] The system may include a display and an operator input device. The operator input device may be, for example, a keyboard, mouse, or similar device. The processing module includes a processor that can access memory storing instructions for performing the steps of the method of the present invention. The processing module may include an operating system, a graphical user interface (GUI) controller, system memory, storage devices, input / output controllers, cache memory, data backup units, and many other devices. The processor may be a commercially available processor or other existing or future-available processors. The processor executes an operating system, which interacts with firmware and hardware in a known manner to assist the processor in coordinating and executing the functions of various computer programs written in a variety of programming languages ​​known in the art, such as Java, Perl, C++, Python, other high-level or low-level languages, or combinations thereof. The operating system typically works with the processor to coordinate and execute the functions of other computer components. The operating system also provides scheduling, input / output control, file and data management, storage management, and communication control and related services according to known techniques. In some embodiments, the processor includes analog electronic components that provide feedback control, such as negative feedback control.

[0134] System memory can be any of a variety of known or future memory storage devices. Examples include any common random access memory (RAM), magnetic media (such as internal hard disks or magnetic tapes), optical media (such as rewritable optical discs), flash memory devices, or other storage devices. Memory storage devices can be any of a variety of known or future devices, including optical disc drives, magnetic tape drives, or floppy disk drives. Such storage devices typically read from and / or write to program storage media (not shown, such as optical discs). Any such program storage media, or other existing or future-developed media, can be considered a computer program product. As those skilled in the art will recognize, these program storage media typically store computer software programs and / or data. Computer software programs (also known as computer control logic) are typically stored in system memory and / or program storage devices used in conjunction with memory storage devices.

[0135] In some embodiments, a computer program product is described, comprising a computer-usable medium storing control logic (computer software program, including program code). When a computer processor executes the control logic, the control logic causes the processor to perform the functions described in this disclosure. In other embodiments, some functions are implemented primarily in hardware, such as using a hardware state machine. How to implement a hardware state machine to perform the functions described in this disclosure will be apparent to those skilled in the art.

[0136] The memory can be any suitable device in which a processor can store and retrieve data, such as magnetic, optical, or solid-state storage devices (including disks, optical discs, magnetic tapes, RAM, or any other suitable fixed or portable devices). The processor can include a general-purpose digital microprocessor appropriately programmed from a computer-readable medium carrying the necessary program code. Programming can be provided to the processor remotely via a communication channel or pre-stored in a computer program product using any of these devices connected to the memory, such as memory or other portable or fixed computer-readable storage media. For example, a disk or optical disc can carry the programming and can be read by a disk reader / writer. The systems of this disclosure also include writing algorithms (e.g., in the form of a computer program product) to practice the methods described above. Programming according to this disclosure can be recorded on a computer-readable medium, such as any medium that can be directly read and accessed by a computer. Such media include, but are not limited to: magnetic storage media (such as floppy disks, hard disk storage media, and magnetic tape), optical storage media (such as CD-ROMs), electrical storage media (such as RAM and ROMs), portable flash drives, and mixtures of these categories (such as magnetic / optical storage media).

[0137] The processor can also access communication channels to communicate with users in remote locations. Remote locations mean that users do not have direct contact with the system, but instead relay input information from external devices to the input manager. External devices can be computers connected to a wide area network (WAN), telephone network, satellite network, or any other suitable communication channel, including mobile phones (i.e., smartphones).

[0138] In some embodiments, the system described herein may be configured to include a communication interface. In some embodiments, the communication interface includes a receiver and / or transmitter for communicating with a network and / or another device. The communication interface may be configured for wired or wireless communication, including but not limited to radio frequency (RF) communication (e.g., radio frequency identification (RFID)), Zigbee communication protocol, Wi-Fi, infrared, wireless universal serial bus (USB), ultra-wideband (UWB), Bluetooth® communication protocol, and cellular communication (such as code division multiple access (CDMA) or Global System for Mobile Communications (GSM)).

[0139] In one embodiment, the communication interface is configured to include one or more communication ports (e.g., physical ports or interfaces such as USB ports, USB-C ports, RS-232 ports, or any other suitable electrical connection ports) to allow data communication between the subject system and other external devices (e.g., computer terminals in a doctor's office or hospital environment) configured for similar complementary data communication.

[0140] In one embodiment, the communication interface is configured as infrared communication, Bluetooth® communication, or any other suitable wireless communication protocol to enable the subject system to communicate with other devices, such as computer terminals and / or networks, communication-enabled mobile phones, personal digital assistants, or any other communication devices that the user may use in conjunction with them.

[0141] In one embodiment, the communication interface is configured to provide connectivity for data transmission using the Internet Protocol (IP) via a mobile phone network, short message service (SMS), a wireless connection to a personal computer (PC) on a local area network (LAN) connected to the Internet, or a Wi-Fi connection to the Internet at a Wi-Fi hotspot.

[0142] In one embodiment, the subject system is configured to communicate wirelessly with a server device via a communication interface, such as using common standards like 802.11 or the Bluetooth® RF protocol, or the IrDA infrared protocol. The server device may be other portable devices, such as smartphones, personal digital assistants (PDAs), or laptops, or larger devices, such as desktop computers, appliances, etc. In some embodiments, the server device has a display (such as a liquid crystal display (LCD)) and input devices (such as buttons, keyboards, mice, or touchscreens).

[0143] In some embodiments, the communication interface is configured to automatically or semi-automatically enable data stored in the subject system (e.g., data in an optional data storage unit) to communicate with a network or server device using one or more of the communication protocols and / or mechanisms described above.

[0144] The output controller may include a controller for any of a variety of known display devices used to present information to a user (whether human or machine, local or remote). If one of the display devices provides visual information, this information is typically logically and / or physically organized as an array of image pixels. The graphical user interface (GUI) controller may include any of a variety of known or future software programs for providing a graphical input / output interface between the system and the user and for processing user input. Functional elements of the computer may communicate with each other via a system bus. In alternative embodiments, some of these communications may be implemented via a network or other types of remote communication. The output manager may also provide information generated by the processing module to a user at a remote location, such as via the Internet, telephone, or satellite network, according to known technologies. The way the output manager presents data may be implemented according to a variety of known technologies. For example, the data may include SQL, HTML, or XML documents, emails, or other files, or other forms of data. The data may include Internet URLs, allowing the user to retrieve more SQL, HTML, XML, or other documents or data from a remote source. One or more platforms present in the subject system may be any type of known computer platform or type to be developed in the future, although they generally fall into the category of computers commonly referred to as servers. However, they may also be host computers, workstations, or other computer types. They can be connected via any known or future cable or other communication system, including wireless systems, whether networked or otherwise. They can be located in the same place or physically separated. Various operating systems can be deployed on any computer platform, depending on the type and / or model of the chosen platform. Suitable operating systems include Windows® NT®, Windows® XP, Windows® 7, Windows® 8, Windows® 10, iOS®, macOS®, Linux®, Ubuntu®, Fedora®, OS / 400®, i5 / OS®, IBMi®, Android™, SGIIRIX®, Oracle Solaris®, and others.

[0145] Figure 7 The overall architecture of an example computing device 700 according to a particular embodiment is described. Figure 7The overall architecture of the computing device 700 shown includes computer hardware facilities and software components. However, for the sake of providing a feasible disclosure, it is not necessary to show all of these generally conventional components. As shown, the computing device 700 includes a processing unit 710, a network interface 720, a computer-readable media drive 730, an input / output device interface 740, a display 750, and an input device 760, all of which can communicate with each other via a communication bus. The network interface 720 provides connectivity to one or more networks or computing systems. The processing unit 710 can thus receive information and instructions from other computing systems or servers via the network. The processing unit 710 can also communicate to / from memory 770 and further provide output information to an optional display 750 via the input / output device interface 740. For example, analysis software (e.g., data analysis software or programs, such as FlowJo®, etc.) stored as executable instructions in the non-temporary memory of the analysis system can display flow cytometry event data to a user. The input / output device interface 740 can also accept input from optional input devices 760, such as keyboards, mice, digital pens, microphones, touch screens, gesture recognition systems, voice recognition systems, game controllers, accelerometers, gyroscopes, or other input devices.

[0146] Memory 770 may include computer program instructions (grouped into modules or components in some embodiments) that processing unit 710 executes to implement one or more embodiments. Memory 770 typically includes RAM, ROM, and / or other persistent, auxiliary, or non-transitory computer-readable media. Memory 770 may store an operating system 772 that provides computer program instructions to processing unit 710 in the routine management and operation of computing device 700. Data may be stored in data storage device 790. Memory 770 may also include computer program instructions and other information for implementing aspects of this disclosure.

[0147] kit

[0148] This disclosure also includes kits, which include storage media such as magneto-optical disks, CD-ROMs, CD-Rs, magnetic tapes, non-volatile memory cards, ROMs, DVD-ROMs, Blu-ray discs, solid-state drives, and network-attached storage. Any of these program storage media, or other media currently in use or that may be developed in the future, can be included in this subject kit. In embodiments, the program storage media includes instructions (e.g., as described above and herein) for visualizing (e.g., automatically) the dynamic range of the light detection system of a flow cytometer. In embodiments, the instructions included on a computer-readable medium provided in this subject kit, or a portion thereof, can be implemented as a software component of software for analyzing data. In these embodiments, the computer control system according to this disclosure can be implemented as an existing software package (e.g., FlowJo...).® It runs as a software "plugin".

[0149] In addition to the components described above, the theme kit may also include (in some embodiments) instructions, such as instructions for installing plugins into existing software packages. These instructions may exist in a variety of forms within the theme kit, with one or more forms present. One form of these instructions is as printed information on a suitable medium or substrate, such as a sheet or more of paper with the information printed on it, the kit's packaging, a packaging insert, etc. Another form of these instructions is as a computer-readable medium, such as a floppy disk, optical disc (CD), portable flash drive, etc., on which the information is recorded. Yet another form of these instructions is as a URL that can be used to access information from a remote site via the Internet.

[0150] practicality

[0151] The methods, systems, and computer systems described herein can be applied to a variety of applications requiring calibration or optimization of optical detection systems (e.g., optical detection systems in flow cytometers). For example, this disclosure can facilitate the calibration of flow cytometers, optimize the SNR of photodetectors, and enable continuous visual monitoring of the quality of data obtained from flow cytometry. In some embodiments, the methods, systems, and computer systems of this disclosure allow users to quickly and easily determine whether one or more sample populations in an experiment are within the optimal dynamic detection range of the detector. In turn, this disclosure allows for effective and continuous enhancement of detector sensitivity and population resolution while ensuring the overall accuracy and reproducibility of experimental results.

[0152] The embodiments of this disclosure can be used in applications where it is desirable to prepare cells from biological samples for research, laboratory testing, or treatment. In some embodiments, the methods and apparatus of this subject matter can facilitate the preparation of single cells from a target fluid or tissue biological sample. For example, the methods and systems of this subject matter facilitate the preparation of cells from fluid or tissue samples for use as research or diagnostic samples for diseases such as cancer. Similarly, the methods and systems of this subject matter can facilitate the preparation of cells from fluid or tissue samples for therapeutic purposes.

[0153] Notwithstanding the appended claims, this disclosure is also limited by the following provisions:

[0154] 1. A flow cytometer, comprising:

[0155] A light source configured to illuminate a sample including particles in a flowing stream;

[0156] A light detection system comprising a photodetector for detecting light from irradiated particles; and

[0157] A processor including memory operatively coupled to the processor, wherein the memory includes instructions stored thereon, which, when executed by the processor, cause the processor to:

[0158] Generate one or more data signals in response to detected light;

[0159] A graph of cytological data is generated for the sample, wherein the graph is generated in the following manner:

[0160] The data signal is converted into quantitative intensity units so that it can be represented on the axis of a graph expressed in quantitative units;

[0161] Determine the minimum and maximum intensity values ​​of the photodetector along the quantitative unit axis, the minimum and maximum values ​​corresponding to the lowest and highest intensity levels defined by the bit depth of the photodetector; and

[0162] The minimum and maximum intensity values ​​of the detection range are indicated on the quantitative unit axis of the figure; and

[0163] A graph of the cytological data generated for the sample is displayed on a visual display.

[0164] 2. The flow cytometer according to Clause 1, wherein the flow cytometer further comprises a display device operatively connected to the processor and configured to display graphs of the cytology data.

[0165] 3. The flow cytometer according to clause 1 or 2, wherein the quantitative intensity unit is independent of the photodetector setting.

[0166] 4. The flow cytometer according to any one of clauses 1-3, wherein the one or more data signals correspond to the pulse height of the particle.

[0167] 5. The flow cytometer according to any one of clauses 1-3, wherein the one or more data signals correspond to the pulse area of ​​the particle.

[0168] 6. The flow cytometer according to Clause 5, wherein the minimum and maximum intensity values ​​of the detection range are determined using the ratio of pulse area to height.

[0169] 7. The flow cytometer according to Clause 6, wherein the memory includes instructions for calculating the ratio of the pulse area to its height in such a manner as:

[0170] Data signals are generated based on the light detected from the irradiated reference particles;

[0171] Determine the pulse area based on the generated data signal;

[0172] The pulse height is determined based on the generated data signal; and

[0173] The ratio of pulse area to height is calculated by dividing the pulse area by the pulse height.

[0174] 8. The flow cytometer according to Clause 7, wherein the reference particle comprises multispectral fluorescent beads.

[0175] 9. A flow cytometer according to any one of clauses 1-8, wherein a scaling factor is used to convert one or more data signals of the sample particles into quantitative intensity units, wherein the scaling factor includes the detector gain of the photodetector.

[0176] 10. The flow cytometer according to Clause 9, wherein the scaling factor is used to determine the minimum and maximum intensity values ​​of the detection range.

[0177] 11. The flow cytometer according to Clause 10, wherein the scaling factor includes a calibration factor, and the one or more data signals are converted to quantitative intensity units in such a manner as follows:

[0178] The data signal is normalized using the detector gain to generate a gain-normalized data signal; and

[0179] The gain-normalized data signal is adjusted using the calibration factor to generate a calibration data signal.

[0180] 12. The flow cytometer according to Clause 11, wherein the memory includes instructions for calculating the calibration factor by adjusting a gain-normalized data signal generated from light detected from an irradiated reference particle to a predetermined average fluorescence intensity (MFI).

[0181] 13. The flow cytometer according to Clause 12, wherein the memory includes instructions for calculating the calibration factor in such a manner as:

[0182] The linear gain is determined based on the photodetector voltage.

[0183] Determine the gain corresponding to a predetermined MFI of the data signal generated by the light detected from the irradiated reference particle; and

[0184] The generated gain-normalized reference data signal is adjusted to the predetermined MFI calibration factor.

[0185] 14. The flow cytometer according to Clause 13, wherein the linear gain is derived from a lookup table and the reference particle comprises multispectral fluorescent beads.

[0186] 15. The flow cytometer according to clause 13 or 14, wherein the memory includes instructions for determining a linear gain based on the photodetector voltage in such a way as:

[0187] The photodetector is illuminated at multiple locations with different intensities using a light source;

[0188] Detecting light from a light source at multiple different intensities under multiple different photodetector voltages; and

[0189] Determine a detector gain setting sufficient to generate an MFI that increases linearly with the detector gain.

[0190] 16. The flow cytometer according to any one of clauses 9-15, wherein the memory includes instructions for adjusting the settings of the photodetector.

[0191] 17. The flow cytometer according to Clause 16, wherein the memory includes instructions for adjusting the settings of the photodetector in such a way as:

[0192] Receive an adjustment to the photodetector, wherein the adjustment includes changing the gain of the photodetector to the adjusted gain;

[0193] Adjust the gain of the photodetector to the adjusted gain; and

[0194] The minimum and maximum intensity values ​​of the detection range are rescaled using changes in the gain of the photodetector.

[0195] 18. The flow cytometer according to Clause 17, wherein the flow cytometer further includes an operator input device operatively connected to the processor and configured to receive the adjustments from a user.

[0196] 19. The flow cytometer according to Clause 17 or 18, wherein the settings of the photodetector are adjusted to maximize the signal-to-noise ratio (SNR) of the sample.

[0197] 20. The flow cytometer according to any one of clauses 17-19, wherein the memory includes instructions for including cytological data generated for particles of the sample on the graph after adjusting the settings of the photodetector in such a way as:

[0198] A data signal is generated in response to light detected from irradiated particles in the sample after the settings of the photodetector are adjusted.

[0199] The data signal is converted into the quantitative intensity unit using the gain change of the photodetector; and

[0200] The converted data signal is plotted on the graph.

[0201] 21. The flow cytometer according to any one of clauses 1-20, wherein the minimum and maximum intensity values ​​of the detection range are indicated by a visual indicator marking the quantitative unit axis of the graph at the minimum and maximum intensity values.

[0202] 22. The flow cytometer according to Clause 21, wherein the visual indicator comprises a first visual indicator and a second visual indicator, the first visual indicator comprising a line perpendicular to the quantitative unit axis at the minimum intensity value, and the second visual indicator comprising a line perpendicular to the quantitative unit axis at the maximum intensity value.

[0203] 23. The flow cytometer according to any one of clauses 1-22, wherein the minimum and maximum intensity values ​​of the detection range are indicated by shading the region of the graph between the minimum and maximum intensity values ​​along the quantitative unit axis.

[0204] 24. The flow cytometer according to any one of clauses 1-23, wherein the minimum and maximum intensity values ​​of the detection range are indicated by shading the regions of the graph corresponding to values ​​below the minimum and above the maximum intensity values ​​along the quantitative unit axis.

[0205] 25. A flow cytometer according to any one of clauses 1-24, wherein the graph is a histogram representing fluorescence intensity values ​​in quantitative intensity units on a first axis and corresponding particle counts on a second axis.

[0206] 26. The flow cytometer according to any one of clauses 1-24, wherein the plot is a dot plot, comprising:

[0207] The first axis represents, in quantitative intensity units, the fluorescence intensity value obtained using a data signal generated from light detected by the photodetector; and

[0208] The second axis represents the fluorescence intensity value obtained using the data signal generated by the light detected by the second photodetector.

[0209] 27. The flow cytometer according to any one of clauses 1-26, wherein the flow cytometer is configured to generate and display graphs of the cytology data in real time.

[0210] 28. The flow cytometer according to Clause 27, wherein the flow cytometer is configured to update the graph of the displayed cytology data in real time.

[0211] 29. The flow cytometer according to Clause 28, wherein the graph of the updated cytology data is used to reflect adjustments to the settings of the photodetector or to include cytology data generated for other particles in the sample.

[0212] 30. The flow cytometer according to any one of clauses 1-29, wherein the light source comprises a laser.

[0213] 31. The flow cytometer according to Clause 30, wherein the light source comprises a plurality of lasers.

[0214] 32. The flow cytometer according to any one of clauses 1-31, wherein the photodetector comprises a photomultiplier tube.

[0215] 33. A method for displaying cytological data to a user, the method comprising:

[0216] A light detection system including a photodetector is used to detect light from particles in a sample in a flowing stream.

[0217] In response to detected light, one or more data signals are generated;

[0218] A graph of cytological data is generated for the sample, wherein the graph is generated in the following manner:

[0219] The data signal is converted into quantitative intensity units so that it can be represented on the axis of a graph expressed in quantitative units;

[0220] Determine the minimum and maximum intensity values ​​of the photodetector along the quantitative unit axis, wherein the minimum and maximum values ​​correspond to the lowest and highest intensity levels defined by the bit depth of the photodetector; and

[0221] The minimum and maximum intensity values ​​of the detection range are indicated on the quantitative unit axis of the figure; and

[0222] A graph of the cytological data generated for the sample is displayed on a visual display.

[0223] 34. The method according to Clause 33, wherein the quantitative intensity unit is independent of the photodetector setting.

[0224] 35. The method according to any one of clauses 33-34, wherein the one or more data signals correspond to the pulse height of the particle.

[0225] 36. The method according to any one of clauses 33-35, wherein the one or more data signals correspond to the pulse area of ​​the particle.

[0226] 37. The method according to Clause 36, wherein the minimum and maximum intensity values ​​of the detection range are determined using the ratio of the pulse area to the height.

[0227] 38. The method according to Clause 37, wherein the method further comprises calculating the ratio of pulse area to height by: generating a data signal based on light detected from an irradiated reference particle; determining a pulse area based on the generated data signal; determining a pulse height based on the generated data signal; and calculating the ratio of pulse area to height by dividing the pulse area by the pulse height.

[0228] 39. The method according to Clause 38, wherein the reference particle comprises multispectral fluorescent beads.

[0229] 40. The method according to any one of clauses 33-39, wherein one or more data signals of the sample particles are converted into quantitative intensity units using a scaling factor, wherein the scaling factor includes the detector gain of the photodetector.

[0230] 41. The method according to Clause 40, wherein the minimum and maximum intensity values ​​of the detection range are determined using the scaling factor.

[0231] 42. The method according to Clause 41, wherein the scaling factor includes a calibration factor, and one or more data signals are converted to quantitative intensity units in such a manner as follows:

[0232] The data signal is normalized using the detector gain to generate a gain-normalized data signal; and the gain-normalized data signal is adjusted using the calibration factor to generate a calibration data signal. 43. The method according to claim 42, wherein the method further comprises calculating the calibration factor by adjusting a gain-normalized data signal generated from light detected from an irradiated reference particle to a predetermined MFI.

[0233] 44. The method according to clause 43, wherein the method further comprises calculating the calibration factor by: determining a linear gain based on a photodetector voltage; determining a gain corresponding to a predetermined MFI of a data signal generated from light detected from an irradiated reference particle; and calculating a calibration factor to adjust the generated gain-normalized reference data signal to the predetermined MFI.

[0234] 45. The method according to Clause 44, wherein the linear gain is derived from a lookup table, and the reference particle comprises multispectral fluorescent beads.

[0235] 46. ​​The method according to clause 44 or 45, wherein the method further comprises determining the linear gain based on the photodetector voltage in such a manner as follows:

[0236] The photodetector is illuminated by a light source at multiple different intensities; the light from the light source at multiple different intensities is detected at multiple different photodetector voltages; and a detector gain setting sufficient to generate an MFI that increases linearly with the detector gain is determined for the photodetector.

[0237] 47. The method according to any one of clauses 40-46, wherein the method further comprises adjusting the settings of the photodetector.

[0238] 48. The method according to clause 47, wherein the photodetector settings are adjusted in the following manner:

[0239] The adjustment to the photodetector includes changing the gain of the photodetector to an adjusted gain; adjusting the gain of the photodetector to achieve the adjusted gain; and rescaling the minimum and maximum intensity values ​​of the detection range using the change in the gain of the photodetector.

[0240] 49. The method according to Clause 48, wherein the adjustment is received from the user.

[0241] 50. The method according to clause 48 or 49, wherein the settings of the photodetector are adjusted to maximize the signal-to-noise ratio (SNR) of the sample.

[0242] 51. The method according to any one of clauses 48-50, wherein the method further comprises, after adjusting the settings of the photodetector, including cytological data generated for particles of the sample on the graph in such a way as:

[0243] A data signal is generated in response to light detected from irradiated particles in the sample after adjusting the settings of the photodetector; the data signal is converted into the quantitative intensity unit using a change in the gain of the photodetector; and the converted data signal is plotted on the graph.

[0244] 52. The method according to any one of clauses 33-51, wherein the minimum and maximum intensity values ​​of the detection range are indicated by a visual indicator marking the quantitative unit axis of the graph at the minimum and maximum intensity values.

[0245] 53. The method according to Clause 52, wherein the visual indicator comprises a first visual indicator and a second visual indicator, the first visual indicator comprising a line perpendicular to the quantitative unit axis at a minimum intensity value, and the second visual indicator comprising a line perpendicular to the quantitative unit axis at the maximum intensity value.

[0246] 54. The method according to any one of clauses 33-53, wherein the minimum and maximum intensity values ​​of the detection range are indicated by shading the region of the graph between the minimum and maximum intensity values ​​along the quantitative unit axis.

[0247] 55. The method according to any one of clauses 33-54, wherein the minimum and maximum intensity values ​​of the detection range are indicated by shading the regions of the graph corresponding to values ​​below the minimum intensity value and above the maximum intensity value along the quantitative unit axis.

[0248] 56. The method according to any one of clauses 33-55, wherein the graph is a histogram representing fluorescence intensity values ​​in quantitative intensity units on a first axis and corresponding particle counts on a second axis.

[0249] 57. The method according to any one of clauses 33-55, wherein the graph is a dot graph comprising: a first axis representing fluorescence intensity values ​​obtained using a data signal generated by light detected by the photodetector in quantitative intensity units; and a second axis representing fluorescence intensity values ​​obtained using a data signal generated by light detected by a second photodetector.

[0250] 58. The method according to any one of clauses 33-57, wherein the graph of the cytological data is generated and displayed in real time.

[0251] 59. The method according to Clause 58, wherein the method further comprises updating a graph of the displayed cytological data in real time.

[0252] 60. The method according to Clause 59, wherein the graph of the displayed cytological data is updated to reflect adjustments to the settings of the photodetector or to include cytological data generated for other particles in the sample.

[0253] 61. The method according to any one of clauses 33-60, wherein the light source comprises a laser.

[0254] 62. The method according to Clause 61, wherein the light source comprises a plurality of lasers.

[0255] 63. The method according to any one of clauses 33-62, wherein the photodetector comprises a photomultiplier tube.

[0256] 64. A system for displaying cytological data to a user, the system comprising:

[0257] A processor including memory operatively coupled to the processor, wherein the memory includes instructions stored thereon, which, when executed by the processor, cause the processor to:

[0258] Receive cytological data of a sample in a flowing stream, the cytological data including one or more data signals generated by a photodetector in response to light detecting particles in the sample;

[0259] A graph of the cytological data is generated, wherein the graph is generated in the following manner:

[0260] The data signal is converted into quantitative intensity units so that it can be represented on the axis of a graph expressed in quantitative units;

[0261] Determine the minimum and maximum intensity values ​​of the photodetector along the quantitative unit axis, the minimum and maximum values ​​corresponding to the lowest and highest intensity levels defined by the bit depth of the photodetector; and

[0262] The minimum and maximum intensity values ​​of the detection range are indicated on the quantitative unit axis of the figure; and

[0263] A graph of the cytological data generated for the sample is displayed on a visual display.

[0264] 65. The system according to Clause 64, wherein the system further comprises a display device operatively connected to the processor and configured to display a graph of the cytological data.

[0265] 66. The system according to clause 64 or 65, wherein the quantitative intensity unit is independent of the photodetector setting.

[0266] 67. The system according to any one of clauses 64-66, wherein one or more data signals correspond to the pulse height of the particle.

[0267] 68. The system according to any one of clauses 64-67, wherein one or more data signals correspond to the pulse area of ​​the particle.

[0268] 69. The system according to Clause 68, wherein the minimum and maximum intensity values ​​of the detection range are determined using the ratio of pulse area to height.

[0269] 70. The system according to clause 69, wherein the memory includes instructions for calculating the ratio of the pulse area to its height in such a manner as follows:

[0270] Data signals are generated based on the light detected from the irradiated reference particles;

[0271] Determine the pulse area based on the generated data signal;

[0272] The pulse height is determined based on the generated data signal; and

[0273] The ratio of pulse area to height is calculated by dividing the pulse area by the pulse height.

[0274] 71. The system according to Clause 70, wherein the reference particle comprises multispectral fluorescent beads.

[0275] 72. The system according to any one of clauses 64-71, wherein one or more data signals of the sample particles are converted into quantitative intensity units using a scaling factor, wherein the scaling factor includes the detector gain of the photodetector.

[0276] 73. The system according to Clause 72, wherein the minimum and maximum intensity values ​​of the detection range are determined using the scaling factor.

[0277] 74. The system according to Clause 73, wherein the scaling factor includes a calibration factor, and one or more data signals are converted to quantitative intensity units in such a manner as follows:

[0278] The data signal is normalized using the detector gain to generate a gain-normalized data signal; and

[0279] The gain-normalized data signal is adjusted using the calibration factor to generate a calibration data signal.

[0280] 75. The system according to Clause 74, wherein the memory includes instructions for calculating the calibration factor by adjusting a gain-normalized data signal generated from light detected from an irradiated reference particle to a predetermined MFI.

[0281] 76. The system according to clause 75, wherein the memory includes instructions for calculating the calibration factor in such a way as:

[0282] The linear gain is determined based on the photodetector voltage.

[0283] Determine the gain corresponding to a predetermined MFI of the data signal generated by the light detected from the irradiated reference particle; and

[0284] The generated gain-normalized reference data signal is adjusted to the predetermined MFI calibration factor.

[0285] 77. The system according to Clause 76, wherein the linear gain is derived from a lookup table, and the reference particle comprises multispectral fluorescent beads.

[0286] 78. The system according to clause 76 or 77, wherein the memory includes instructions for determining a linear gain based on the photodetector voltage in such a way as:

[0287] The photodetector is illuminated at multiple locations with different intensities using a light source;

[0288] Detecting light from a light source at multiple different intensities under multiple different photodetector voltages; and

[0289] Determine a detector gain setting sufficient to generate an MFI that increases linearly with the detector gain.

[0290] 79. The system according to any one of clauses 72-78, wherein the memory includes instructions for adjusting the settings of the photodetector.

[0291] 80. The system according to clause 79, wherein the memory includes instructions for adjusting the settings of the photodetector in such a way as:

[0292] Receive an adjustment to the photodetector, wherein the adjustment includes changing the gain of the photodetector to the adjusted gain;

[0293] Adjust the gain of the photodetector to the adjusted gain; and

[0294] The minimum and maximum intensity values ​​of the detection range are rescaled using changes in the gain of the photodetector.

[0295] 81. The system according to Clause 80, wherein the system further comprises an operator input device operatively connected to the processor and configured to receive adjustments from a user.

[0296] 82. The system according to clause 80 or 81, wherein the settings of the photodetector are adjusted to maximize the signal-to-noise ratio (SNR) of the sample.

[0297] 83. The system according to any one of clauses 80-82, wherein the memory includes instructions for including cytological data generated for particles of the sample on the graph after adjusting the settings of the photodetector in such a way as follows:

[0298] A data signal is generated in response to light detected from irradiated particles in the sample after the settings of the photodetector are adjusted.

[0299] The data signal is converted into the quantitative intensity unit using the gain change of the photodetector; and

[0300] The converted data signal is plotted on the graph.

[0301] 84. The system according to any one of clauses 64-83, wherein the minimum and maximum intensity values ​​of the detection range are indicated by a visual indicator marking the quantitative unit axis of the graph at the minimum and maximum intensity values.

[0302] 85. The system according to Clause 84, wherein the visual indicator includes a first visual indicator and a second visual indicator, the first visual indicator including a line perpendicular to the quantitative unit axis at a minimum intensity value, and the second visual indicator including a line perpendicular to the quantitative unit axis at the maximum intensity value.

[0303] 86. The system according to any one of clauses 64-85, wherein the minimum and maximum intensity values ​​of the detection range are indicated by shading the region of the graph between the minimum and maximum intensity values ​​along the quantitative unit axis.

[0304] 87. The system according to any one of clauses 64-86, wherein the minimum and maximum intensity values ​​of the detection range are indicated by shading the regions of the graph corresponding to values ​​below the minimum intensity value and above the maximum intensity value along the quantitative unit axis.

[0305] 88. The system according to any one of clauses 64-87, wherein the graph is a histogram representing fluorescence intensity values ​​in quantitative intensity units on a first axis and corresponding particle counts on a second axis.

[0306] 89. The system according to any one of clauses 64-87, wherein the graph is a dot graph comprising: a first axis representing fluorescence intensity values ​​obtained using a data signal generated by light detected by the photodetector in quantitative intensity units; and a second axis representing fluorescence intensity values ​​obtained using a data signal generated by light detected by a second photodetector.

[0307] 90. The system according to any one of clauses 64-89, wherein the system is configured to generate and display graphs of the cytological data in real time.

[0308] 91. The system according to Clause 90, wherein the system is configured to update the graph of the displayed cytological data in real time.

[0309] 92. The system according to Clause 91, wherein the graph of the updated cytological data is used to reflect adjustments to the settings of the photodetector or to include cytological data generated for other particles in the sample.

[0310] 93. The system according to any one of clauses 64-92, wherein the light source comprises a laser.

[0311] 94. The system according to Clause 93, wherein the light source comprises a plurality of lasers.

[0312] 95. The system according to any one of clauses 64-94, wherein the photodetector comprises a photomultiplier tube.

[0313] 96. A non-transitory computer-readable storage medium, including instructions stored thereon for displaying cytological data to a user by means of a method, the method comprising:

[0314] A light detection system including a photodetector is used to detect light from particles in a sample in a flowing stream.

[0315] In response to detected light, one or more data signals are generated;

[0316] A graph of cytological data is generated for the sample, wherein the graph is generated in the following manner:

[0317] The data signal is converted into quantitative intensity units so that it can be represented on the axis of a graph expressed in quantitative units;

[0318] Determine the minimum and maximum intensity values ​​of the photodetector along the quantitative unit axis, the minimum and maximum values ​​corresponding to the lowest and highest intensity levels defined by the bit depth of the photodetector; and

[0319] The minimum and maximum intensity values ​​of the detection range are indicated on the quantitative unit axis of the figure; and

[0320] A graph of the cytological data generated for the sample is displayed on a visual display.

[0321] 97. The non-transitory computer-readable storage medium as described in Clause 96, wherein the quantitative intensity unit is independent of the photodetector setting.

[0322] 98. The non-transitory computer-readable storage medium according to any one of clauses 96-97, wherein one or more data signals correspond to the pulse height of the particle.

[0323] 99. A non-transitory computer-readable storage medium according to any one of clauses 96-98, wherein one or more data signals correspond to the pulse area of ​​the particle.

[0324] 100. The non-transitory computer-readable storage medium according to Clause 99, wherein the minimum and maximum intensity values ​​of the detection range are determined using the ratio of the pulse area to its height.

[0325] 101. The non-transitory computer-readable storage medium according to clause 100, wherein the method further comprises calculating the ratio of the pulse area to its height by:

[0326] A data signal is generated based on the light detected from the irradiated reference particle; a pulse area is determined based on the generated data signal; a pulse height is determined based on the generated data signal; and the ratio of the pulse area to the height is calculated by dividing the pulse area by the pulse height.

[0327] 102. The non-transitory computer-readable storage medium according to Clause 101, wherein the reference particle comprises multispectral fluorescent beads.

[0328] 103. The non-transitory computer-readable storage medium according to any one of clauses 96-102, wherein one or more data signals of the sample particles are converted into quantitative intensity units using a scaling factor, wherein the scaling factor includes the detector gain of the photodetector.

[0329] 104. The non-transitory computer-readable storage medium according to Clause 103, wherein the minimum intensity value and the maximum intensity value of the detection range are determined using the scaling factor.

[0330] 105. The non-transitory computer-readable storage medium according to Clause 104, wherein the scaling factor includes a calibration factor, and one or more data signals are converted into quantitative intensity units in such a manner as follows:

[0331] The data signal is normalized using the detector gain to generate a gain-normalized data signal; and the gain-normalized data signal is adjusted using the calibration factor to generate a calibration data signal.

[0332] 106. The non-transitory computer-readable storage medium according to Clause 105, wherein the method further comprises calculating the calibration factor by adjusting a gain-normalized data signal generated from light detected from an irradiated reference particle to a predetermined MFI.

[0333] 107. The non-transitory computer-readable storage medium according to clause 106, wherein the method further comprises calculating the calibration factor by:

[0334] The linear gain is determined based on the photodetector voltage.

[0335] Determine the gain corresponding to a predetermined MFI of the data signal generated by the light detected from the irradiated reference particle; and

[0336] The generated gain-normalized reference data signal is adjusted to the predetermined MFI calibration factor.

[0337] 108. The non-transitory computer-readable storage medium according to Clause 107, wherein the linear gain is derived from a lookup table and the reference particle comprises multispectral fluorescent beads.

[0338] 109. The non-transitory computer-readable storage medium according to clause 107 or 108, wherein the method further comprises determining the linear gain based on the photodetector voltage in such a manner as follows:

[0339] The photodetector is illuminated at multiple locations with different intensities using a light source;

[0340] Detecting light from a light source at multiple different intensities under multiple different photodetector voltages; and

[0341] Determine a detector gain setting sufficient to generate an MFI that increases linearly with the detector gain.

[0342] 110. The non-transitory computer-readable storage medium according to any one of clauses 103-109, wherein the method further comprises adjusting the settings of the photodetector.

[0343] 111. The non-transitory computer-readable storage medium according to Clause 110, wherein the settings of the photodetector are adjusted by:

[0344] Receive an adjustment to the photodetector, wherein the adjustment includes changing the gain of the photodetector to the adjusted gain;

[0345] Adjust the gain of the photodetector to the adjusted gain; and

[0346] The minimum and maximum intensity values ​​of the detection range are rescaled using changes in the gain of the photodetector.

[0347] 112. The non-transitory computer-readable storage medium as described in Clause 111, wherein the adjustment is received from a user.

[0348] 113. The non-transitory computer-readable storage medium according to clause 111 or 112, wherein the settings of the photodetector are adjusted to maximize the signal-to-noise ratio (SNR) of the sample.

[0349] 114. The non-transitory computer-readable storage medium according to any one of clauses 111-113, wherein the method further comprises, after adjusting the settings of the photodetector, including cytological data generated for particles of the sample on the graph in such a way that:

[0350] In response to the light detected from the irradiated particles of the sample after adjusting the settings of the photodetector, a data signal is generated.

[0351] The data signal is converted into the quantitative intensity unit using the gain change of the photodetector; and

[0352] The converted data signal is plotted on the graph.

[0353] 115. A non-transitory computer-readable storage medium according to any one of clauses 96-114, wherein the minimum and maximum intensity values ​​of the detection range are indicated by a visual indicator marking the quantitative unit axis of the graph at the minimum and maximum intensity values.

[0354] 116. The non-transitory computer-readable storage medium according to Clause 115, wherein the visual indicator includes a first visual indicator and a second visual indicator, the first visual indicator including a line perpendicular to the quantitative unit axis at a minimum intensity value, and the second visual indicator including a line perpendicular to the quantitative unit axis at the maximum intensity value.

[0355] 117. A non-transitory computer-readable storage medium according to any one of clauses 96-116, wherein the minimum and maximum intensity values ​​of the detection range are indicated by shading the region of the graph between the minimum and maximum intensity values ​​along the quantitative unit axis.

[0356] 118. A non-transitory computer-readable storage medium according to any one of clauses 96-117, wherein the minimum and maximum intensity values ​​of the detection range are indicated by shading the regions of the graph corresponding to values ​​below the minimum intensity value and above the maximum intensity value along the quantitative unit axis.

[0357] 119. The non-transitory computer-readable storage medium according to any one of clauses 96-118, wherein the graph is a histogram representing fluorescence intensity values ​​in quantitative intensity units on a first axis and corresponding particle counts on a second axis.

[0358] 120. A non-transitory computer-readable storage medium according to any one of clauses 96-118, wherein the graph is a dot graph, comprising:

[0359] The first axis represents, in quantitative intensity units, the fluorescence intensity value obtained using a data signal generated from light detected by the photodetector; and

[0360] The second axis represents the fluorescence intensity value obtained using the data signal generated by the light detected by the second photodetector.

[0361] 121. The non-transitory computer-readable storage medium according to any one of clauses 96-120, wherein the graph of the cytology data is generated and displayed in real time.

[0362] 122. The non-transitory computer-readable storage medium as described in Clause 121, wherein the method further includes a graph of the displayed cytological data that is updated in real time.

[0363] 123. The non-transitory computer-readable storage medium as described in Clause 122, wherein the graph of the updated cytological data reflects adjustments to the settings of the photodetector or includes cytological data generated for other particles of the sample.

[0364] 124. The non-transitory computer-readable storage medium according to any one of clauses 96-123, wherein the light source includes a laser.

[0365] 125. The non-transitory computer-readable storage medium as described in Clause 124, wherein the light source comprises a plurality of lasers.

[0366] 126. The non-transitory computer-readable storage medium according to any one of clauses 96-125, wherein the photodetector comprises a photomultiplier tube.

[0367] Although the invention has been described in detail by way of illustrations and examples for the purpose of clarity, it will be apparent to those skilled in the art, based on the teachings of the invention, that certain changes and modifications may be made thereto without departing from the spirit or scope of the appended claims.

[0368] Therefore, the foregoing only illustrates the principles of the invention. It should be understood that those skilled in the art will be able to design various arrangements, which, although not explicitly described or shown herein, embody the principles of the invention and are included within its spirit and scope. Furthermore, all examples and conditional language listed herein are primarily intended to assist the reader in understanding the principles of the invention and the concepts contributed by the inventors to further developments in the field, and should be understood as not being limited to these specifically listed examples and conditions. Moreover, all statements herein referencing the principles, aspects, and embodiments of the invention, as well as specific examples thereof, are intended to cover their structural and functional equivalents. Additionally, such equivalents are contemplated to include both currently known equivalents and future-developed equivalents (i.e., any element developed that performs the same function, regardless of its structure). Furthermore, nothing disclosed herein is intended to be offered to the public, whether or not such disclosure is expressly stated in the claims.

[0369] Therefore, the scope of the invention is not intended to be limited to the exemplary embodiments shown and described herein. Rather, the scope and spirit of the invention are embodied in the appended claims. In the claims, with respect to the limitation in the claims, 35 USC §112(f) or 35 USC §112(6) is explicitly defined as being invoked only when such limitation in the claims begins to refer to the exact phrase “means for…” or the exact phrase “step for…”; if such an exact phrase is not used in the limitation in the claims, then 35 USC §112(f) or 35 USC §112(6) is not invoked.

Claims

1. A flow cytometer, comprising: A light source configured to illuminate a sample including particles in a flowing stream; A light detection system, comprising a photodetector for detecting light from irradiated particles; as well as A processor including memory operatively coupled to the processor, wherein the memory includes instructions stored thereon, which, when executed by the processor, cause the processor to: Generate one or more data signals in response to detected light; A graph of cytological data is generated for the sample, wherein the graph is generated in the following manner: The data signal is converted into quantitative intensity units so that it can be represented on the axis of a graph expressed in quantitative units; Determine the minimum and maximum intensity values ​​of the photodetector's detection range along the quantitative unit axis, the minimum and maximum intensity values ​​corresponding to the lowest and highest intensity levels defined by the photodetector's bit depth; and The minimum and maximum intensity values ​​of the detection range are indicated on the quantitative unit axis of the graph; and A graph of the cytological data generated for the sample is displayed on a visual display.

2. The flow cytometer according to claim 1, wherein, The flow cytometer also includes a display device operatively connected to the processor and configured to display graphs of the cytology data.

3. The flow cytometer according to claim 1 or 2, wherein, The quantitative intensity unit is independent of the photodetector settings.

4. The flow cytometer according to any one of claims 1-3, wherein, The one or more data signals correspond to the pulse height of the particle.

5. The flow cytometer according to any one of claims 1-3, wherein, The one or more data signals correspond to the pulse area of ​​the particle.

6. The flow cytometer according to any one of claims 1-5, wherein, A scaling factor is used to convert one or more data signals of the sample particles into quantitative intensity units, wherein the scaling factor includes the detector gain of the photodetector.

7. The flow cytometer according to any one of claims 1-6, wherein, The minimum and maximum intensity values ​​of the detection range are indicated by a visual indicator that marks the quantitative unit axis of the graph at the minimum and maximum intensity values.

8. The flow cytometer according to any one of claims 1-7, wherein, The minimum and maximum intensity values ​​of the detection range are indicated by shading the region of the graph between the minimum and maximum intensity values ​​along the quantitative unit axis.

9. The flow cytometer according to any one of claims 1-8, wherein, The minimum and maximum intensity values ​​of the detection range are indicated by shading the regions of the graph corresponding to values ​​below the minimum intensity value and above the maximum intensity value along the quantitative unit axis.

10. The flow cytometer according to any one of claims 1-9, wherein, The graph is a histogram that represents fluorescence intensity values ​​in quantitative intensity units on the first axis and the corresponding particle counts on the second axis.

11. The flow cytometer according to any one of claims 1-10, wherein, The graph is a dot graph, including: The first axis represents, in quantitative intensity units, the fluorescence intensity value obtained using the data signal generated by the light detected by the photodetector; and The second axis represents the fluorescence intensity value obtained using the data signal generated by the light detected by the second photodetector.

12. The flow cytometer according to any one of claims 1-11, wherein, The flow cytometer is configured to generate and display graphs of the cytology data in real time.

13. A method for displaying cytological data to a user, the method comprising: A light detection system including a photodetector is used to detect light from particles in a sample in a flowing stream. Generate one or more data signals in response to detected light; A graph of cytological data is generated for the sample, wherein the graph is generated in the following manner: The data signal is converted into quantitative intensity units so that it can be represented on the axis of a graph expressed in quantitative units; Determine the minimum and maximum intensity values ​​of the photodetector along the quantitative unit axis, wherein the minimum and maximum values ​​correspond to the lowest and highest intensity levels defined by the bit depth of the photodetector; and The minimum and maximum intensity values ​​of the detection range are indicated on the quantitative unit axis of the graph; and A graph of the cytological data generated for the sample is displayed on a visual display.

14. The method according to claim 13, wherein, The quantitative intensity unit is independent of the photodetector settings.

15. A system for displaying cytological data to a user, the system comprising: A processor including a memory operatively coupled to the processor, wherein the memory includes instructions stored thereon, which, when executed by the processor, cause the processor to: receive cytological data of a sample in a flowing stream, the cytological data including one or more data signals generated by a photodetector in response to light detecting particles from the sample; A graph of the cytological data is generated, wherein the graph is generated in the following manner: The data signal is converted into quantitative intensity units so that it can be represented on the axis of a graph expressed in quantitative units; Determine the minimum and maximum intensity values ​​of the photodetector along the quantitative unit axis, wherein the minimum and maximum values ​​correspond to the lowest and highest intensity levels defined by the bit depth of the photodetector; and The minimum and maximum intensity values ​​of the detection range are indicated on the quantitative unit axis of the graph; and A graph of the cytological data generated for the sample is displayed on a visual display.

Images