Method for determining data filter for detecting particles of sample and system and method using same

Abstract

Aspects of the present disclosure include methods for determining and applying a data signal filter for detecting particles (e.g., small particles such as extracellular vesicles) in a particle analyzer. A method according to certain embodiments includes: detecting light from particles in a flowing stream using a light detection system; generating a data signal waveform in response to the detected light from the particles in the flow stream; determining the characteristics of the data signal waveform; and calculating a data signal filter from the determined characteristics of the data signal waveform. In some embodiments, the method includes determining a trigger indicator for detecting particles of the sample based on the filtered data signal waveform. Systems and integrated circuit devices (e.g., field programmable gate arrays) for implementing the subject methods are also described. A non-transitory computer-readable storage medium is also provided.

Description

[0001] Cross-reference to related applications

[0002] According to 35 USC 119(e), This application claims priority to U.S. Provisional Patent Application Serial No. 63 / 445,433, filed February 14, 2023; the disclosure of which is incorporated herein by reference in its entirety. Background Technology

[0003] Flow cytometry particle sorting systems (such as sorting flow cytometers) are used to sort particles in a fluid sample based on at least one measured property of the particles. Flow cytometers use fluorescence or scattered light to measure the physical and chemical properties of individual cells. In a flow cytometry particle sorting system, particles in a suspension (such as molecules, microbeads bound to analytes, or individual cells) flow in a stream through a detection zone where a sensor detects particles of the type to be sorted contained in the stream. When the sensor detects particles of the type to be sorted, a sorting mechanism is triggered that selectively separates the particles of interest.

[0004] Particle sensing is typically achieved by flowing a fluid through a detection region where particles are exposed to illumination from one or more lasers, and the light scattering and fluorescence properties of the particles are measured. Detection is performed using one or more photoelectric sensors to independently measure the fluorescence of each different fluorescent dye. Flow cytometry has recently been used to study small biological particles such as extracellular vesicles (EVs) due to its high throughput and multi-parameter analysis capabilities. EVs have been found to play a crucial role in intercellular signal transduction. However, their small size results in weak scattering and fluorescence signals, making them difficult to separate from noise levels and reliably identify. In flow cytometry, fluctuations in background noise and system settings can cause variations in light detection. Data analysis in flow cytometry treats noise, as well as variations in light illumination and detector settings, as static and constant values ​​during the experiment. Summary of the Invention

[0005] This disclosure includes methods for determining and applying data signal filters for detecting particles (e.g., small particles such as extracellular vesicles) in a particle analyzer. According to some embodiments, the method includes: detecting light from particles in a flowing stream using a photodetector system; generating a data signal waveform in response to the detected light from the particles in the flowing stream; determining characteristics of the data signal waveform; and calculating a data signal filter from the determined characteristics of the data signal waveform. In some embodiments, the method includes determining a trigger index for detecting particles in a sample based on the filtered data signal waveform. Systems and integrated circuit devices (e.g., field-programmable gate arrays) for implementing the methods of this subject matter are also described. A non-transitory computer-readable storage medium is also provided.

[0006] In this embodiment, features of the data signal waveform are used to calculate a data signal filter, for example, to optimize triggering performance for small particle detection using a particle analyzer. In some cases, the features of the data signal waveform include a width parameter. In others, the width parameter includes the ratio of waveform area to waveform height. In still others, the data signal waveform has a Gaussian distribution.

[0007] In some embodiments, the calculated data signal filter generates a data signal with the maximum signal-to-noise ratio when applied to a data signal from a photodetector system. In some cases, the data signal filter is matched to the waveform of the actual data signal generated in response to detected light. In certain cases, the data signal filter is calculated according to the following formula:

[0008]

[0009] in, It is the core of the data signal filter; It is the noise component of the data signal; It is the data signal waveform generated by the optical detection system; It represents the standard deviation. In some cases, the numerator of the data signal filter kernel is a function of the maximum data signal waveform after filtering. In other cases, the denominator of the data signal filter kernel is the noise amplitude of the data signal waveform after filtering.

[0010] In some embodiments, the data signal filter is an estimate of the actual data signal waveform. In some cases, the method includes calculating a linear analog data signal filter from determined characteristics of the data signal waveform. In some cases, the linear analog data signal filter is a finite impulse response filter. In other cases, the linear analog data signal filter is an infinite impulse response filter. In some cases, the method includes calculating a data signal filter from determined characteristics of the data signal waveform, the filter comprising one or more of the following: Butterworth filter, Chebyshev filter, elliptic Caul filter, Bessel filter, Gaussian filter, optimal L-filter, Ringquiz-Ryley filter, ideal filter, and matched filter.

[0011] In some embodiments, the data signal filter is based on a certain aspect of the particles in the flow. In some cases, the data signal filter is based on the width of the particles. In some embodiments, the particles of interest have a diameter of 1000 nm or less, such as a diameter between 50 nm and 800 nm. In some embodiments, the particles are extracellular vesicles. In some embodiments, the generated data signal waveform is independent of the particle size. In some embodiments, the size of the particles (e.g., determined by the width of the particles) is smaller than the profile of the illumination beam from the light source.

[0012] In some embodiments, the method includes applying a data signal filter to a data signal waveform generated by an optical detection system. In these embodiments, the method may include: detecting light from particles of a sample in a flowing stream using the optical detection system; generating a data signal waveform in response to the detected light; and applying a calculated data signal filter to the generated data signal waveform, wherein the data signal filter is calculated based on determined characteristics of the data signal generated by the optical detection system. In some cases, a triggering index for detecting particles in the flowing stream by the optical detection system is determined based on the filtered data signal waveform. In some cases, the triggering index is the ratio of the data signal amplitude to a noise component of the data signal waveform. In some cases, the noise component is the root mean square value of the noise in the data signal waveform.

[0013] In some embodiments, the method includes illuminating particles in a flowing stream with a light source. In some cases, the light source includes one or more lasers. In some cases, the light is detected using a light detection system having multiple photodetectors. In some embodiments, the one or more photodetectors are photomultiplier tubes. In some embodiments, the one or more photodetectors are photodiodes (e.g., avalanche photodiodes, APDs). In some embodiments, the light detection system includes a photodetector array, such as a photodetector array having multiple photodiodes or charge-coupled devices (CCDs).

[0014] This disclosure also includes systems for implementing the methods of this subject matter. A system according to certain embodiments includes: a light source configured to illuminate particles in a flowing stream; a light detection system having a plurality of photodetectors; and a processor with a memory operatively coupled thereto, wherein the memory stores instructions thereon that, when executed by the processor, cause the processor to generate a data signal waveform in response to detected light from particles in the flowing stream, determine characteristics of the data signal waveform, and calculate a data signal filter from the determined characteristics of the data signal waveform. In some embodiments, the memory includes instructions for determining a width parameter of the data signal waveform. In some cases, the memory includes instructions for determining one or more of a waveform area, a waveform height, and a ratio of waveform area to waveform height. In some cases, the data signal processed by the system has a Gaussian distribution.

[0015] In some embodiments, the memory contains instructions for calculating a data filter based on a certain aspect of particles in the flow stream. In some cases, the data filter is based on the width of the particles. In some embodiments, the memory contains instructions for calculating a data filter based on parameters of particles in the flow stream with a diameter of 1000 nm or smaller (e.g., a diameter of 50 nm to 800 nm).

[0016] In some embodiments, the memory includes instructions for calculating a data signal filter that, when applied to a data signal from a light detection system, generates a data signal with a maximum signal-to-noise ratio. In some cases, the memory includes instructions for matching the data signal filter to a real data signal waveform generated in response to detected light. In certain cases, the memory includes instructions for calculating the data signal filter according to the following formula:

[0017]

[0018] in It is the core of the data signal filter; It is the noise component of the data signal; It is the data signal waveform generated by the optical detection system; It represents the standard deviation. In some cases, the numerator of the data signal filter kernel is a function of the maximum data signal waveform after filtering. In other cases, the denominator of the data signal filter kernel is the noise amplitude of the data signal waveform after filtering.

[0019] In some embodiments, the memory contains instructions for calculating a data signal filter, which is an estimate of the actual data signal waveform. In some cases, the memory contains instructions for calculating a linear analog data signal filter from determined characteristics of the data signal waveform. In some cases, the linear analog data signal filter is a finite impulse response filter. In other cases, the linear analog data signal filter is an infinite impulse response filter. In some cases, the memory contains instructions for calculating a data signal filter from determined characteristics of the data signal waveform, the filter including one or more of the following: Butterworth filter, Chebyshev filter, elliptic Caul filter, Bessel filter, Gaussian filter, optimal L-filter, Ringquiz-Ryley filter, ideal filter, and matched filter.

[0020] In some embodiments, the system includes a memory storing instructions thereon for applying a data signal filter to a data signal waveform generated by a photodetector system. In these embodiments, the system may include: a light source configured to illuminate particles of a sample in a flowing stream; a photodetector system having a plurality of photodetectors; and a processor having a memory operatively coupled to a processor, wherein the memory stores instructions thereon that, when executed by the processor, cause the processor to generate a data signal waveform in response to detected light and apply a data signal filter to the generated data signal waveform, wherein the data signal filter is calculated based on determined characteristics of the data signal generated by the photodetector system. In some cases, the memory includes instructions for determining a trigger index for detecting sample particles based on the filtered data signal waveform. In some cases, the trigger index is the ratio of the data signal amplitude to a noise component of the data signal waveform. In some cases, the noise component is the root mean square value of the noise in the data signal waveform.

[0021] An integrated circuit device programmed to apply a data signal filter to detect particles in a flowing stream is also provided. According to some embodiments, the integrated circuit is programmed to determine characteristics of a data signal waveform generated in response to light detected from irradiated particles in a sample of the flowing stream, and to calculate a data signal filter from the determined characteristics of the data signal waveform. In some embodiments, the integrated circuit is programmed to determine a width parameter of the data signal waveform. In some cases, the integrated circuit is programmed to determine one or more of a waveform area, a waveform height, and a ratio of waveform area to waveform height. In some cases, the data signal processed by the system has a Gaussian distribution.

[0022] In some embodiments, the integrated circuit is programmed to compute a data filter based on a certain aspect of particles in the flow. In some cases, the data signal filter is based on the width of the particles. In some embodiments, the integrated circuit is programmed to compute a data filter based on parameters of particles in the flow with a diameter of 1000 nm or smaller (such as particles with a diameter from 50 nm to 800 nm).

[0023] In some embodiments, the integrated circuit is programmed to compute a data signal filter that, when applied to a data signal from a light detection system, generates a data signal with the maximum signal-to-noise ratio. In some cases, the integrated circuit is programmed to match the data signal filter to the waveform of the actual data signal generated in response to detected light. In other cases, the integrated circuit is programmed to compute the data signal filter according to the following formula:

[0024]

[0025] in It is the core of the data signal filter; It is the noise component of the data signal; It is the data signal waveform generated by the optical detection system; It represents the standard deviation. In some cases, the numerator of the data signal filter kernel is a function of the maximum data signal waveform after filtering. In other cases, the denominator of the data signal filter kernel is the noise amplitude of the data signal waveform after filtering.

[0026] In some embodiments, the integrated circuit is programmed to compute a data signal filter that is an estimate of the actual data signal waveform. In some cases, the integrated circuit is programmed to compute a linear analog data signal filter from determined characteristics of the data signal waveform. In some cases, the linear analog data signal filter is a finite impulse response (FIR) filter. In other cases, the linear analog data signal filter is an infinite impulse response (IOR) filter. In some cases, the integrated circuit is programmed to compute a data signal filter from determined characteristics of the data signal waveform, the filter comprising one or more of the following: Butterworth filter, Chebyshev filter, elliptic Caul filter, Bessel filter, Gaussian filter, optimal L-filter, Ringquiz-Ryley filter, ideal filter, and matched filter.

[0027] In some embodiments, the integrated circuit is programmed to apply a data signal filter to a data signal waveform generated by a photodetector system. In these embodiments, the integrated circuit is programmed to generate a data signal waveform in response to detected light and to apply a data signal filter to the generated data signal waveform, wherein the data signal filter is calculated based on determined characteristics of the data signal generated by the photodetector system. In some cases, the integrated circuit is programmed to determine a trigger index for detecting sample particles based on the filtered data signal waveform. In some cases, the trigger index is the ratio of the data signal amplitude to the noise component of the data signal waveform. In some cases, the noise component is the root mean square value of the noise in the data signal waveform.

[0028] A non-transitory computer-readable storage medium is also described, having instructions including an algorithm for determining a data signal filter for detecting particles in a particle analyzer. According to some embodiments, the non-transitory computer-readable storage medium has an algorithm for determining characteristics of a data signal waveform generated in response to light detected from particles irradiated from a sample in a flowing stream and calculating a data signal filter from the determined characteristics of the data signal waveform. In some embodiments, the non-transitory computer-readable storage medium includes an algorithm for determining a width parameter of the data signal waveform. In some cases, the non-transitory computer-readable storage medium includes an algorithm for determining one or more of a waveform area, a waveform height, and a ratio of waveform area to waveform height. In some cases, the data signal processed by the system has a Gaussian distribution.

[0029] In some embodiments, the non-transitory computer-readable storage medium includes an algorithm for calculating a data filter based on a certain aspect of particles in a flowing stream. In some cases, the data signal filter is based on the width of the particles. In some embodiments, the non-transitory computer-readable storage medium includes an algorithm for calculating a data filter based on particle parameters in a flowing stream with a diameter of 1000 nm or smaller (such as diameters from 50 nm to 800 nm).

[0030] In some embodiments, the non-transitory computer-readable storage medium includes an algorithm for calculating a data signal filter that generates a data signal with a maximum signal-to-noise ratio when applied to a data signal from a light detection system. In some cases, the non-transitory computer-readable storage medium includes an algorithm for matching the data signal filter to a real data signal waveform generated in response to detected light. In some cases, the non-transitory computer-readable storage medium includes an algorithm for calculating the data signal filter according to the following formula:

[0031]

[0032] in It is the core of the data signal filter; It is the noise component of the data signal; It is the data signal waveform generated by the optical detection system; It represents the standard deviation. In some cases, the numerator of the data signal filter kernel is a function of the maximum data signal waveform after filtering. In other cases, the denominator of the data signal filter kernel is the noise amplitude of the data signal waveform after filtering.

[0033] In some embodiments, the non-transitory computer-readable storage medium contains an algorithm for calculating a filter for a data signal, the filter being an estimate of a real data signal waveform. In some cases, the non-transitory computer-readable storage medium contains an algorithm for calculating a linear analog data signal filter from determined characteristics of the data signal waveform. In some cases, the linear analog data signal filter is a finite impulse response filter. In other cases, the linear analog data signal filter is an infinite impulse response filter. In some cases, the non-transitory computer-readable storage medium contains an algorithm for calculating a data signal filter from determined characteristics of the data signal waveform, the filter including one or more of the following: Butterworth filter, Chebyshev filter, elliptic Caul filter, Bessel filter, Gaussian filter, optimal L-filter, Ringquiz-Ryley filter, ideal filter, and matched filter.

[0034] In some embodiments, the non-transitory computer-readable storage medium includes an algorithm for applying a data signal filter to a data signal waveform generated by an optical detection system. In these embodiments, the non-transitory computer-readable storage medium includes an algorithm for generating a data signal waveform in response to detected light and applying a data signal filter to the generated data signal waveform, wherein the data signal filter is calculated based on determined characteristics of the data signal generated by the optical detection system. In some cases, the non-transitory computer-readable storage medium includes an algorithm for determining a trigger index for detecting sample particles based on the filtered data signal waveform. In some cases, the trigger index is the ratio of the data signal amplitude to a noise component of the data signal waveform. In some cases, the noise component is the root mean square value of the noise in the data signal waveform. Attached Figure Description

[0035] The invention can be better understood through the following detailed description when read in conjunction with the accompanying drawings. The drawings include the following figures:

[0036] Figure 1A The waveform of a data signal generated in response to light detected from irradiated particles, according to certain embodiments, is depicted.

[0037] Figure 1BThe waveforms of data signals generated for particles of different widths according to certain embodiments are depicted.

[0038] Figure 2 A flowchart is depicted according to certain embodiments for calculating a data signal filter and applying it to a data signal waveform.

[0039] Figure 3A An image-enabled particle sorter according to certain embodiments is described. Figure 3B A method for supporting image particle sorting data processing according to certain embodiments is described.

[0040] Figure 4A A functional block diagram of a particle analysis system according to certain embodiments is depicted. Figure 4B A flow cytometer according to certain embodiments is shown.

[0041] Figure 5 A functional block diagram of an example particle analyzer control system according to certain embodiments is depicted.

[0042] Figure 6A A schematic diagram of a particle sorting system according to certain embodiments is depicted.

[0043] Figure 6B A schematic diagram of a particle sorting system according to certain embodiments is depicted.

[0044] Figure 7 A block diagram of a computing system according to certain embodiments is depicted. Detailed Implementation

[0045] This disclosure includes methods for determining and applying data signal filters for detecting particles (e.g., small particles such as extracellular vesicles) in a particle analyzer. According to some embodiments, the method includes: detecting light from particles in a flowing stream using a photodetector system; generating a data signal waveform in response to the detected light from the particles in the flowing stream; determining characteristics of the data signal waveform; and calculating a data signal filter from the determined characteristics of the data signal waveform. In some embodiments, the method includes determining a trigger index for detecting particles in a sample based on the filtered data signal waveform. Systems and integrated circuit devices (e.g., field-programmable gate arrays) for implementing the methods of this subject matter are also described. A non-transitory computer-readable storage medium is also provided.

[0046] Before describing the invention 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 the terminology used herein is for the purpose of describing specific embodiments only and is not intended to be limiting, as the scope of the invention is limited only by the appended claims.

[0047] When a numerical range is provided, it should be understood that, unless the context explicitly specifies otherwise, every intermediate value between the upper and lower limits of the range (accurate to one-tenth of the lower limit unit), as well as any other specified or intermediate value within the range, is covered by this invention. The upper and lower limits of these smaller ranges may be independently included within the smaller range and are also covered by this invention, but must comply with any explicitly excluded limits within the range. When the range contains one or two limits, the range excluding one or both limits is also covered by this invention.

[0048] Certain ranges presented in this article are preceded by the term "approximately". The term "approximately" is used here to provide literal support for the exact number it refers to, and also to provide literal support for numbers that are close to or approximate to the number preceding the term. In determining whether a number is close to or approximate to a particular enumerated number, an unenumerated close or approximate number may be a number that is substantially equivalent to the particular enumerated number in its context.

[0049] 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 invention pertains. Although any methods and materials similar to or equivalent to those described herein may be used to practice or test the invention, only representative illustrative methods and materials are described here.

[0050] All publications and patents referenced in this specification are incorporated herein by reference as if each publication or patent were expressly and individually designated to be incorporated herein by reference, and to disclose and describe the methods and / or materials relating to the cited publication. References to any publication are based on its disclosure prior to the filing date and should not be construed as an admission that the present invention is not entitled to a prior invention prior to the disclosure date of that publication. Furthermore, the publication dates provided may differ from the actual publication dates and may require separate verification.

[0051] It should be noted that, as used herein and in the appended claims, the singular forms “a,” “an,” and “the” all include plural references unless the context clearly specifies otherwise. It should also be noted that the drafting of the claims may exclude any optional elements. Therefore, this statement is intended as a prior basis for using exclusive terms such as “only,” “merely,” or the use of “negative” when stating elements of the claims.

[0052] As will be apparent to those skilled in the art upon reading this disclosure, each embodiment described and illustrated herein has independent components and features that can be readily separated from or combined with features of any of the other embodiments without departing from the scope or spirit of the invention. Any of the described methods may be performed in the order of the events described or in any other logically feasible order.

[0053] Although the apparatus and method have been described or will be described for the sake of grammatical fluency and functional interpretation, it must be clearly understood that, unless expressly formulated in accordance with 35 USC §112, the claims should not be construed as necessarily limited to any manner of construction by “apparatus” or “step”, but should be given the full meaning and scope of equivalents provided by the claims in accordance with the doctrine of equivalents, and where the claims are expressly formulated in accordance with 35 USC §112, should be given the full legal equivalents specified in 35 USC §112.

[0054] As described above, this disclosure provides a method for determining and applying a data signal filter for detecting particles in a particle analyzer (e.g., a flow cytometer). In further describing embodiments of this disclosure, methods for determining the data signal filter are first described in more detail, such as by matching a calculated filter to a real waveform generated from detection light from irradiated particles in a sample, or by calculating a data signal filter as an estimate of the real data signal waveform. Next, systems and integrated circuit devices programmed to implement the methods of this subject matter are described. A non-transitory computer-readable storage medium is then provided.

[0055] Methods for determining and applying data signal filters for detecting particles in a flowing stream

[0056] Various aspects of this disclosure include methods for determining a data signal filter for detecting particles (e.g., small particles such as extracellular vesicles) in a particle analyzer. As described in more detail below, the methods of this subject matter improve the sensitivity and accuracy of data signal measurements in an optical detection system. In some cases, the methods described herein are used to calculate a data signal filter that can be used to improve the triggering performance of small particle detection, including without changing the hardware components of the particle analyzer system (e.g., photodetectors). In some cases, determining the data signal filter for sample particles can improve the sensitivity of data signal measurements (e.g., improve the signal-to-noise ratio) by 5% or more, such as 10% or more, such as 15% or more, such as 25% or more, such as 50% or more, such as 75% or more, and including 99% or more. In some embodiments, the calculated data signal filter can be used to adjust and optimize the threshold of a trigger indicator for detecting sample particles. In some cases, the methods described herein can improve the amplitude-based threshold of the trigger indicator by 5% or more, such as 10% or more, such as 15% or more, such as 25% or more, such as 50% or more, such as 75% or more, and including 99% or more.

[0057] In some embodiments, the present invention method can improve the accuracy of detecting small particles in a flowing stream, such as particles with diameters of 1000 nm or less, such as 900 nm or less, such as 800 nm or less, such as 700 nm or less, such as 600 nm or less, such as 500 nm or less, such as 400 nm or less, such as 300 nm or less, and including particles with diameters of 200 nm or less. In some cases, the diameter of the particle of interest is smaller than the width of the beam profile illuminated by the light source. In some cases, the present invention method can perform multi-parameter analysis, identification, and classification of extracellular vesicles, which is generally unreliable in flow cytometry because such particles generate high noise levels due to weak scattering and low fluorescence intensity signals.

[0058] In implementing the methods of this subject matter, a sample containing particles is illuminated with a light source, and the light from the sample is detected by a light detection system having multiple photodetectors. In some embodiments, the sample is a biological sample. The term "biological sample" in its conventional sense refers to a whole organism, plant, fungus, or a subset of animal tissue, cells, or components, which in some cases may be present in blood, mucus, lymph, synovial fluid, cerebrospinal fluid, saliva, bronchoalveolar lavage fluid, amniotic fluid, amniotic sac blood, urine, vaginal secretions, and semen. Thus, "biological sample" refers both to a protist or a subset of its tissues and to homogenates, lysates, or extracts prepared from such an organism or a subset of its tissues, including but not limited to, for example, plasma, serum, cerebrospinal fluid, lymph, skin sections, respiratory tract, gastrointestinal tract, cardiovascular and genitourinary tract sections, tears, saliva, breast milk, blood cells, tumors, and organs. Biological samples can be any type of biological tissue, including healthy tissue and diseased tissue (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., wherein in some cases, the sample is a blood sample, including whole blood, such as blood obtained from venipuncture or finger prick (wherein the blood may or may not be mixed with any reagents, such as preservatives, anticoagulants, etc., before the assay).

[0059] In some embodiments, the sample source is "mammal" or "milk," terms that are broadly 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 cases, the subject is human. The method can be applied to samples obtained from both sexes and human subjects at any developmental stage (i.e., newborns, infants, young children, adolescents, and adults), wherein in some embodiments, the human subject is a young child, adolescent, or adult. While the invention can be applied to samples from human subjects, it should be understood that the method can also be applied to samples from other animal subjects (i.e., "non-human subjects"), such as, but not limited to, birds, mice, rats, dogs, cats, livestock, and horses.

[0060] In implementing the methods of this subject matter, a sample containing particles is illuminated with light from a light source (e.g., in a flow stream of a flow cytometer). In some embodiments, the light source is a broadband light source that emits light with a wide wavelength range, such as spanning 50 nm or longer, such as 100 nm or longer, such as 150 nm or longer, such as 200 nm or longer, such as 250 nm or longer, such as 300 nm or longer, such as 350 nm or longer, such as 400 nm or longer, and including spanning 500 nm or longer. For example, a suitable broadband light source emits light with wavelengths from 200 nm to 1500 nm. Another example of a suitable broadband light source includes a light source that emits light with wavelengths from 400 nm to 1000 nm. When the method includes illumination with a broadband light source, the broadband light source protocols of interest may include, but are not limited to, halogen lamps, deuterium arc lamps, xenon arc lamps, stable fiber-coupled broadband light sources, broadband LEDs with a continuous spectrum, superluminescent diodes, semiconductor light-emitting diodes, broadband LED white light sources, multi-LED integrated white light sources, and other broadband light sources or any combination thereof.

[0061] In other embodiments, the method includes illumination using a narrowband light source that emits a specific wavelength or a narrow wavelength range, such as a light source emitting light in a narrow wavelength range, for example, a range of 50 nanometers or less, such as a range of 40 nanometers or less, such as a range of 30 nanometers or less, such as a range of 25 nanometers or less, such as a range of 20 nanometers or less, such as a range of 15 nanometers or less, such as a range of 10 nanometers or less, such as a range of 5 nanometers or less, such as a range of 2 nanometers or less, and including light sources that emit a specific wavelength (i.e., monochromatic light). When the method includes illumination using a narrowband light source, the narrowband light source protocol of interest may include, but is not limited to, narrow-wavelength LEDs, laser diodes, or broadband light sources coupled to one or more optical bandpass filters, diffraction gratings, monochromators, or any combination thereof.

[0062] In some embodiments, the method includes irradiating the sample with one or more lasers. As described above, the type and number of lasers will vary depending on the sample and the desired acquisition light, and may be gas lasers such as helium-neon lasers, argon lasers, krypton lasers, xenon lasers, nitrogen lasers, carbon dioxide lasers, carbon monoxide lasers, argon-fluorine (ArF) excimer lasers, krypton-fluorine (KrF) excimer lasers, xenon-chlorine (XeCl) excimer lasers, or xenon-fluorine (XeF) excimer lasers, or combinations thereof. In other cases, the method includes irradiating the flow with dye lasers (such as stilbene, coumarin, or rhodamine lasers). In still other cases, the method includes irradiating the flow with 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 method includes irradiating the flow with a solid-state laser, such as a ruby ​​laser, an Nd:YAG laser, an NdCrYAG laser, an Er:YAG laser, an Nd:YLF laser, an Nd:YVO4 laser, an Nd:YCa4O(BO3)3 laser, an Nd:YCOB laser, a Ti:sapphire laser, a thulium YAG laser, a ytterbium YAG laser, a ytterbium₂O₃ laser, or a cerium-doped laser, or combinations thereof.

[0063] The sample can be illuminated by one or more of the aforementioned light sources, such as two or more light sources, three or more light sources, four or more light sources, five or more light sources, and including ten or more light sources. The light sources can include any type of combination of light sources. For example, in some embodiments, the method includes illuminating the sample in the flowing stream with an array of lasers, such as an array having one or more gas lasers, one or more dye lasers, and one or more solid-state lasers.

[0064] The sample can be illuminated with wavelengths ranging from 200 nm to 1500 nm, such as 250 nm to 1250 nm, such as 300 nm to 1000 nm, such as 350 nm to 900 nm, and including 400 nm to 800 nm. For example, when the light source is a broadband light source, the sample can be illuminated with wavelengths ranging from 200 nm to 900 nm. In other cases, when the light source comprises multiple narrowband light sources, the sample can be illuminated with specific wavelengths in the range of 200 nm to 900 nm. For example, the light source can be multiple narrowband LEDs (1 nm–25 nm), each emitting light independently in the wavelength range of 200 nm to 900 nm. In other embodiments, the narrowband light source comprises one or more lasers (such as a laser array), and the sample is illuminated with specific wavelengths ranging from 200 nm to 700 nm, such as using a laser array having gas lasers, excimer lasers, dye lasers, metal vapor lasers, and solid-state lasers as described above.

[0065] If more than one light source is used, the sample can be illuminated simultaneously or sequentially by the light sources or in combination thereof. For example, the sample can be illuminated simultaneously by each light source. In other embodiments, the flow stream is illuminated sequentially by each light source. If more than one light source is used to sequentially illuminate the sample, the duration for which each light source illuminates the sample can be independently 0.001 microseconds or longer, such as 0.01 microseconds or longer, such as 0.1 microseconds or longer, such as 1 microsecond or longer, such as 5 microseconds or longer, such as 10 microseconds or longer, such as 30 microseconds or longer, and including 60 microseconds or longer. For example, the method may include illuminating the sample with a light source (e.g., a laser) for a duration ranging from 0.001 microseconds to 100 microseconds, such as from 0.01 microseconds to 75 microseconds, such as from 0.1 microseconds to 50 microseconds, such as from 1 microsecond to 25 microseconds, and including from 5 microseconds to 10 microseconds. In embodiments where the sample is sequentially illuminated by two or more light sources, the duration for which the sample is illuminated by each light source can be the same or different.

[0066] The time interval between illuminations from each light source can vary as needed, independently spaced by delays of 0.001 microseconds or longer, such as 0.01 microseconds or longer, such as 0.1 microseconds or longer, such as 1 microsecond or longer, such as 5 microseconds or longer, such as 10 microseconds or longer, such as 15 microseconds or longer, such as 30 microseconds or longer, and including 60 microseconds or longer. For example, the range of time intervals between illuminations from each light source can be from 0.001 microseconds to 60 microseconds, such as from 0.01 microseconds to 50 microseconds, such as from 0.1 microseconds to 35 microseconds, such as from 1 microsecond to 25 microseconds, and including from 5 microseconds to 10 microseconds. In some embodiments, the time interval between illuminations from each light source is 10 microseconds. In embodiments where the sample is sequentially illuminated by more than two (i.e., three or more) light sources, the delay between illuminations from each light source can be the same or different.

[0067] The sample may be illuminated continuously or at discrete intervals. In some cases, the method involves illuminating the sample continuously with a light source. In other cases, the sample is illuminated with a light source at discrete intervals, such as every 0.001 milliseconds, every 0.01 milliseconds, every 0.1 milliseconds, every 1 millisecond, every 10 milliseconds, every 100 milliseconds (and including every 1000 milliseconds) or some other interval.

[0068] Depending on the light source, the illumination distance of the sample can vary, such as 0.01 mm or more, such as 0.05 mm or more, such as 0.1 mm or more, such as 0.5 mm or more, such as 1 mm or more, such as 2.5 mm or more, such as 5 mm or more, such as 10 mm or more, such as 15 mm or more, such as 25 mm or more, and including 50 mm or more. Furthermore, the illumination angle can also vary, ranging from 10° to 90°, such as from 15° to 85°, such as from 20° to 80°, such as from 25° to 75°, and including from 30° to 60°, for example, illumination at a 90° angle.

[0069] In some embodiments, the method includes irradiating a sample with two or more frequency-shifted light beams. As described above, a beam generator assembly may be employed, having a laser and an acousto-optic device for frequency-shifting the laser. In these embodiments, the method includes irradiating the acousto-optic device with a laser. Depending on the desired wavelength of light generated in the output laser beam (e.g., for irradiating a sample in a flowing stream), the laser may have a specific wavelength ranging from 200 nm to 1500 nm, such as from 250 nm to 1250 nm, such as from 300 nm to 1000 nm, such as from 350 nm to 900 nm, and including from 400 nm to 800 nm. The acousto-optic device may be irradiated with one or more lasers, such as two or more lasers, such as three or more lasers, such as four or more lasers, such as five or more lasers, and including ten or more lasers. The lasers may include any type of laser combination. For example, in some embodiments, the method includes irradiating the acousto-optic device with an array of lasers, such as an array having one or more gas lasers, one or more dye lasers, and one or more solid-state lasers.

[0070] When using more than one laser, the acousto-optic device can be irradiated simultaneously, sequentially, or in combination with the laser. For example, the acousto-optic device can be irradiated simultaneously with each laser. In other embodiments, the acousto-optic device can be irradiated sequentially with each laser. When the acousto-optic device is irradiated sequentially with more than one laser, the duration of irradiation by each laser can be independently 0.001 microseconds or longer, such as 0.01 microseconds or longer, such as 0.1 microseconds or longer, such as 1 microsecond or longer, such as 5 microseconds or longer, such as 10 microseconds or longer, such as 30 microseconds or longer, and including 60 microseconds or longer. For example, the method may include irradiating the acousto-optic device with lasers for durations ranging from 0.001 microseconds to 100 microseconds, such as from 0.01 microseconds to 75 microseconds, such as from 0.1 microseconds to 50 microseconds, such as from 1 microsecond to 25 microseconds, and including from 5 microseconds to 10 microseconds. In embodiments where the acousto-optic device is irradiated sequentially with two or more lasers, the duration of irradiation by each laser can be the same or different.

[0071] The time interval between each laser irradiation can also vary as needed, independently spaced 0.001 microseconds or longer, such as 0.01 microseconds or longer, such as 0.1 microseconds or longer, such as 1 microsecond or longer, such as 5 microseconds or longer, such as 10 microseconds or longer, such as 15 microseconds or longer, such as 30 microseconds or longer, and including 60 microseconds or longer. For example, the range of the time interval between each light source irradiation can be from 0.001 microseconds to 60 microseconds, such as from 0.01 microseconds to 50 microseconds, such as from 0.1 microseconds to 35 microseconds, such as from 1 microsecond to 25 microseconds, and including from 5 microseconds to 10 microseconds. In some embodiments, the time interval between each laser irradiation is 10 microseconds. In embodiments where the acousto-optic device is sequentially irradiated by more than two (i.e., three or more) lasers, the delay between each laser irradiation can be the same or different.

[0072] The acousto-optic device can be continuously irradiated or irradiated at discrete intervals. In some cases, the method involves continuously irradiating the acousto-optic device with a laser. In other cases, the acousto-optic device is irradiated with a laser at discrete intervals, such as every 0.001 milliseconds, every 0.01 milliseconds, every 0.1 milliseconds, every 1 millisecond, every 10 milliseconds, every 100 milliseconds (and including every 1000 milliseconds), or at some other interval.

[0073] Depending on the type of laser, the illumination distance of the acousto-optic device can vary, such as 0.01 mm or more, such as 0.05 mm or more, such as 0.1 mm or more, such as 0.5 mm or more, such as 1 mm or more, such as 2.5 mm or more, such as 5 mm or more, such as 10 mm or more, such as 15 mm or more, such as 25 mm or more, and including 50 mm or more. Furthermore, the illumination angle can also vary, ranging from 10° to 90°, such as from 15° to 85°, such as from 20° to 80°, such as from 25° to 75°, and including from 30° to 60°, for example, illuminating at a 90° angle.

[0074] In an embodiment, the method includes applying radio frequency (RF) drive signals to an acousto-optic device to generate an angle-deflected laser beam. Two or more RF drive signals may be applied to the acousto-optic device to generate an output laser beam having a desired number of angle-deflected laser beams, such as three or more RF drive signals, such as four or more RF drive signals, such as five or more RF drive signals, such as six or more RF drive signals, such as seven or more RF drive signals, such as eight or more RF drive signals, such as nine or more RF drive signals, such as ten or more RF drive signals, such as fifteen or more RF drive signals, such as 25 or more RF drive signals, such as 50 or more RF drive signals, and including 100 or more RF drive signals.

[0075] The intensity of each angle-deflected laser beam generated by the radio frequency (RF) drive signal is based on the amplitude of the applied RF drive signal. In some embodiments, the method includes applying an RF drive signal with an amplitude sufficient to produce an angle-deflected laser beam of the desired intensity. In some cases, each applied RF drive signal independently has an amplitude of about 0.001 V to about 500 V, such as about 0.005 V to about 400 V, such as about 0.01 V to about 300 V, such as about 0.05 V to about 200 V, such as about 0.1 V to about 100 V, such as about 0.5 V to about 75 V, such as about 1 V to 50 V, such as about 2 V to 40 V, such as 3 V to about 30 V, and including about 5 V to about 25 V. In some embodiments, each applied radio frequency drive signal has a frequency from about 0.001 MHz to about 500 MHz, such as from about 0.005 MHz to about 400 MHz, such as from about 0.01 MHz to about 300 MHz, such as from about 0.05 MHz to about 200 MHz, such as from about 0.1 MHz to about 100 MHz, such as from about 0.5 MHz to about 90 MHz, such as from about 1 MHz to about 75 MHz, such as from about 2 MHz to about 70 MHz, such as from about 3 MHz to about 65 MHz, such as from about 4 MHz to about 60 MHz, and including from about 5 MHz to about 50 MHz.

[0076] In these embodiments, the angle-deflected laser beams in the output laser beam are spatially separated. Depending on the applied RF drive signal and the desired illumination profile of the output laser beam, the angle-deflected laser beams can be separated by 0.001 μm or greater, such as 0.005 μm or greater, such as 0.01 μm or greater, such as 0.05 μm or greater, such as 0.1 μm or greater, such as 0.5 μm or greater, such as 1 μm or greater, such as 5 μm or greater, such as 10 μm or greater, such as 100 μm or greater, such as 500 μm or greater, such as 1000 μm or greater, and including 5000 μm or greater. In some embodiments, the angle-deflected laser beams overlap 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 the overlap of beam points) can be 0.001 μm or greater, such as 0.005 μm or greater, such as 0.01 μm or greater, such as 0.05 μm or greater, such as 0.1 μm or greater, such as 0.5 μm or greater, such as 1 μm or greater, such as 5 μm or greater, such as 10 μm or greater, and including 100 μm or greater.

[0077] In some cases, the flow stream is illuminated with multi-beam frequency-shifted light, and cells in the flow stream are imaged using fluorescence imaging with radio frequency labeled emission (FIRE) to generate frequency-coded images, such as those described by Diebold et al. in Nature Photonics, 7(10), 806-810 (2013), and in U.S. Patent Nos. 9,423,353, 9,784,661, 9,983,132, 10,006,852, 10,078,045, 10,036,699, 10,222,316, 10,288,546, 10,324,019, and 10,408. The disclosures of those described in U.S. Patent Publications 758, 10,451,538, 10,620,111, and those described in U.S. Patent Publications 2017 / 0133857, 2017 / 0328826, 2017 / 0350803, 2018 / 0275042, 2019 / 0376895, and 2019 / 0376894 are incorporated herein by reference.

[0078] As described above, in some embodiments, light from the irradiated sample is transmitted to a photodetector system (described in more detail below) and measured by multiple photodetectors. In some embodiments, the method includes measuring light collected within a wavelength range (e.g., 200 nm–1000 nm). For example, the method may include collecting the spectrum of light within one or more wavelength ranges in the 200 nm–1000 nm wavelength range. In other embodiments, the method includes measuring collected light at one or more specific wavelengths. For example, the collected light may be measured at one or more of the following wavelengths: 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, the method includes measuring the wavelength of light corresponding to the fluorescence peak wavelength of the fluorophore. In some embodiments, the method includes measuring the collected light across the entire fluorescence spectral range for each fluorophore in the sample.

[0079] The collected light can be measured continuously or at discrete intervals. In some cases, the method involves measuring the light continuously. In others, the light is measured at discrete intervals, such as every 0.001 milliseconds, every 0.01 milliseconds, every 0.1 milliseconds, every 1 millisecond, every 10 milliseconds, every 100 milliseconds, and including every 1000 milliseconds or at some other interval.

[0080] During the method described herein, measurements of light collection may be performed once or multiple times, such as two or more times, three or more times, five or more times, and including ten or more times. In some embodiments, light propagation is measured two or more times, wherein the data are averaged in some cases.

[0081] Light from a sample can be measured at one or more of the following wavelengths: such as 5 or more different wavelengths, such as 10 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 including measuring collected light at 400 or more different wavelengths.

[0082] In embodiments, the method includes generating a data signal waveform in response to light detected from particles in a flowing stream. In some cases, the data signal waveform is generated by one or more fluorescent photodetectors, such as two or more, three or more, four or more, five or more, six or more, eight or more, twelve or more, sixteen or more, twenty-four or more, thirty-two or more, sixteen or more, and including 128 or more fluorescent photodetectors. In some cases, light from irradiated particles is detected in one or more photodetector channels, such as two or more, four or more, eight or more, sixteen or more, thirty-two or more, sixteen or more, and including 128 or more photodetector channels. In some embodiments, the data signal waveform includes data components acquired (or derived) from light from other detectors, such as detected light absorption or detected light scattering. In some cases, one or more data components of the data signal waveform are generated from light absorption detected from a sample, such as from a bright-field light detector. In other cases, one or more data components of the data signal waveform are generated by light scattering detected from the sample (such as from a side-scatter detector, a forward-scatter detector, or a combination of a side-scatter detector and a forward-scatter detector).

[0083] In some embodiments, the resulting data signal waveform is plotted as a function of signal strength over time. In some cases, the data signal waveform is collected within time frames of 0.000001 ms or longer, such as 0.000005 ms or longer, such as 0.00001 ms or longer, such as 0.00005 ms or longer, such as 0.0001 ms or longer, such as 0.0005 ms or longer, such as 0.001 ms or longer, such as 0.005 ms or longer, such as 0.01 ms or longer, such as 0.05 ms or longer, such as 0.1 ms or longer, such as 0.5 ms or longer, such as 1 ms or longer, such as 2 ms or longer, such as 3 ms or longer, such as 4 ms or longer, such as 5 ms or longer, such as 6 ms or longer, such as 7 ms or longer, such as 8 ms or longer, such as 9 ms or longer, such as 10 ms or longer, and time frames including 100 ms or longer. In some embodiments, the data signal waveform is collected within time frames of 0.000001 ms to 10 ms, such as from 0.00001 ms to 9.5 ms, such as from 0.0001 ms to 9 ms, such as from 0.001 ms to 8.5 ms, such as from 0.01 ms to 8 ms, and including from 0.1 ms to 7.5 ms.

[0084] In some cases, the data signal exhibits a signal peak with a width parameter of 0.000001 ms or longer, such as 0.000005 ms or longer, such as 0.00001 ms or longer, such as 0.00005 ms or longer, such as 0.0001 ms or longer, such as 0.0005 ms or longer, such as 0.001 ms or longer, such as 0.005 ms or longer, such as 0.01 ms or longer, such as 0.05 ms or longer, such as 0.1 ms or longer, such as 0.5 ms or longer, such as 1 ms or longer, such as 2 ms or longer, such as 3 ms or longer, such as 4 ms or longer, such as 5 ms or longer, such as 6 ms or longer, such as 7 ms or longer, such as 8 ms or longer, such as 9 ms or longer, such as 10 ms or longer, and a width parameter including 100 ms or longer. For example, the width parameter of the data signal waveform can range from 0.000001 ms to 10 ms, such as from 0.00001 ms to 9.5 ms, such as from 0.0001 ms to 9 ms, such as from 0.001 ms to 8.5 ms, such as from 0.01 ms to 8 ms, and includes a range from 0.1 ms to 7.5 ms.

[0085] In some embodiments, the data signal waveform includes a noise component. The term "noise" is used herein in its conventional sense to refer to a signal measurement generated by a photodetector that is attributable to a component independent of the light from the detected irradiated particles, and may include thermal noise, shot noise, dark current noise, electronic noise, or other random variations in the detector signal. In some cases, the noise component is calculated as the root mean square of the data signal outside the signal peak region of the data signal waveform.

[0086] In some embodiments, the data signal waveform includes measurement variance. Measurement variance refers to the variance generated during the data acquisition process, such as the variance of light detection, data signal generation, or sample illumination. In some cases, measurement variance includes the variance of photodetector gain in one or more photodetectors of the light detection system. In some cases, measurement variance includes the variance of the trigger threshold of one or more photodetectors of the light detection system. In some cases, measurement variance includes the variance of the light detection duration for each particle by each photodetector. In some cases, measurement variance includes the variance of photon shot noise detected by each photodetector for each particle.

[0087] In some embodiments, the data signal waveform includes a signal peak having a height and a width. In some cases, the height of the signal peak is the intensity or amplitude of the data signal above the root mean square of the noise component. In other cases, the height of the signal peak is the intensity or amplitude of the data signal above a predetermined position within the root mean square of the noise component, for example, above the midpoint within the root mean square of the noise component. Figure 1A The waveform of the data signal generated in response to detection light from the irradiated particle is depicted, and this waveform is plotted as a function of signal intensity or amplitude versus time. Figure 1A In the data signal waveform generated in response to detection light from the irradiated particles, a signal peak 101 with a peak height 102, a peak width 103, and a peak area 104 is included. The data signal waveform also includes a noise component 105. In some cases, the noise component is characterized by the root mean square (RMS) 106 of the noise. In some cases, the signal peak height 102 of the data signal waveform 101 is determined by the upper limit of the RMS of the noise to the peak amplitude of the data signal waveform 101. In some cases, the signal peak height 102 of the data signal waveform 101 is determined by a predetermined position within the RMS of the noise, such as the midpoint within the RMS of the noise.

[0088] In some cases, the method includes determining one or more of the following: the height of a data signal waveform, the width of a data signal waveform, the area of ​​a data signal waveform, a combination thereof, or a ratio of one or more of the width, height, and area of ​​a data signal waveform. In some cases, the method includes determining a width parameter of the data signal waveform. In some embodiments, the width parameter is the ratio of the waveform area to the waveform height. In some embodiments, the data signal waveform has a Gaussian distribution. In other embodiments, the data signal waveform has a super-Gaussian distribution.

[0089] In some embodiments, the data signal filter is calculated from defined features of the data signal waveform. In certain cases, this feature is one or more of the following: the height of the data signal, the width of the data signal, the area of ​​the data signal waveform, or a ratio of one or more of the width, height, and area of ​​the data signal waveform. In some embodiments, the data signal filter is determined based on the ratio of the area to the height of the data signal waveform.

[0090] In some embodiments, the data signal filter determined based on the width parameter of the data signal waveform is a filter that matches the actual waveform generated by the optical detection system. In some cases, the matched filter is a calculated data signal filter that, when applied to the data signal from the optical detection system, generates a data signal with the maximum signal-to-noise ratio. In other words, the matched filter generates the optimal signal-to-noise ratio in the presence of any additive random noise. In some cases, the matched filter has the same functional form as the actual signal. In some embodiments, the data signal filter is a linear filter that maximizes the trigger index, as described in more detail below.

[0091] In some embodiments, the data signal filter takes additive noise into account. It is calculated using the corrupted time series signal x(t). ,in It is the underlying real signal generated by the optical detection system. In some cases, the data signal filter is calculated through function optimization according to the following formula:

[0092]

[0093] in It is the core of the data signal filter; It is the noise component of the data signal; It is the data signal waveform generated by the optical detection system; It represents the standard deviation. In some cases, the numerator of the data signal filter kernel is a function of the maximum data signal waveform after filtering. In other cases, the denominator of the data signal filter kernel is the noise amplitude of the data signal waveform after filtering.

[0094] In some embodiments, the method includes calculating an estimated data signal filter as a matched filter. In some cases, the method includes calculating a linear analog data signal filter from determined features of the data signal waveform (e.g., a width parameter). In some cases, the linear analog data signal filter includes a finite impulse response filter. In other cases, the linear analog data signal filter includes an infinite impulse response filter. In some embodiments, the method includes calculating a data signal filter from determined features of the data signal waveform, the data signal filter being selected from the group consisting of Butterworth filters, Chebyshev filters, elliptic Caul filters, Bessel filters, Gaussian filters, optimal L-filters, Ringquiz-Ryley filters, ideal filters, and matched filters.

[0095] In some embodiments, the data signal filter is calculated based on a certain aspect of the particle. In some cases, the data signal filter is based on the spatial data of the particle. In some cases, the spatial data includes the horizontal size scale of the particle, the vertical size scale of the particle, the particle size ratio along two different dimensions, and the size ratio of particle components (e.g., the ratio of the horizontal scale of the cell nucleus to the horizontal scale of the cytoplasm). In some cases, the data signal filter is calculated based on the width of the particle. In some cases, the particle is an extracellular vesicle. In some embodiments, the particles have a horizontal scale of 2000 nm or less, such as 1900 nm or less, such as 1800 nm or less, such as 1700 nm or less, such as 1600 nm or less, such as 1500 nm or less, such as 1400 nm or less, such as 1300 nm or less, such as 1200 nm or less, such as 1100 nm or less, such as 1000 nm or less, such as 900 nm or less, such as 800 nm or less, such as 700 nm or less, such as 600 nm or less, such as 500 nm or less, such as 400 nm or less, such as 300 nm or less, and include a horizontal scale of 250 nm or less. In some embodiments, the particles have a vertical scale of 2000 nm or less, such as 1900 nm or less, such as 1800 nm or less, such as 1700 nm or less, such as 1600 nm or less, such as 1500 nm or less, such as 1400 nm or less, such as 1300 nm or less, such as 1200 nm or less, such as 1100 nm or less, such as 1000 nm or less, such as 900 nm or less, such as 800 nm or less, such as 700 nm or less, such as 600 nm or less, such as 500 nm or less, such as 400 nm or less, such as 300 nm or less, and include a vertical scale of 250 nm or less.

[0096] In some embodiments, the particle size is smaller than the size of the illumination beam from the light source (i.e., the beam profile along the horizontal axis). In other words, the beam profile (e.g., the beam profile of a laser light source) illuminates the entire particle. In some cases, the beam profile is 5% or more larger than the particle size, for example, 10% or more, 15% or more, 20% or more, 25% or more, 50% or more, 75% or more, 90% or more, 95% or more, and including 99% or more. In some cases, the beam profile is 1.5 times or more, for example, 2 times or more, 3 times or more, 4 times or more, and including 5 times or more of the particle size.

[0097] In some embodiments, the generated data signal waveform is independent of particle size. In certain cases, the generated data signal waveform is independent of particle size when the particles have a vertical or horizontal scale that is below a predetermined threshold compared to the beam profile of the light source. For example, the generated data signal waveform may be independent of particle size when one or more of the horizontal or vertical scales are smaller than the beam profile of the light source, such as when the horizontal or vertical scale of the particles is 1% or more, for example 2% or more, for example 3% or more, for example 4% or more, for example 5% or more, for example 10% or more, for example 15% or more, for example 20% or more, and includes cases where the horizontal or vertical scale of the particles is 25% or more smaller than the beam profile of the light source. Figure 1B The data signal waveforms generated for particles of different widths according to certain embodiments are depicted. Figure 1B In this study, particles of 200 nm and 800 nm were illuminated using a light source with a beam profile greater than 800 nm. For example... Figure 1B As shown, the generated data signal waveform is independent of the particle size.

[0098] An aspect of the method disclosed herein also includes applying a data signal filter to a data signal waveform generated by a photodetector system. As described above, in some embodiments, applying a data signal filter to a data signal waveform generated by a photodetector system can improve the sensitivity of the data signal measurement by 5% or more, for example, by 10% or more, for example, by 15% or more, for example, by 25% or more, for example, by 50% or more, for example, by 75% or more, and including by 99% or more. In some embodiments, the method includes detecting light from particles of a sample in a flowing stream using a photodetector system, generating a data signal waveform in response to the detected light, and applying a calculated data signal filter to the generated data signal waveform.

[0099] In some cases, the method includes calculating a trigger index for detecting particles in a flowing stream using a calculated data signal filter. In some embodiments, the trigger index is the ratio of the amplitude of the data signal waveform to the noise component of the data signal waveform. In some embodiments, this ratio is the ratio of the maximum value of the data signal waveform to the noise component. In some embodiments, the noise component is calculated as the root mean square value of the noise in the data signal waveform.

[0100] In some embodiments, the trigger threshold changes based on a calculated trigger indicator (e.g., used to identify positive events in the raw data waveform). For example, the trigger threshold may be reduced by 0.0001% or more, such as 0.0005% or more, such as 0.001% or more, such as 0.005% or more, such as 0.01% or more, such as 0.05% or more, such as 0.1% or more, such as 0.5% or more, such as 1% or more, and includes cases where the trigger threshold is reduced by 2% or more. In some cases, the trigger threshold is increased by 0.0001% or more, such as increasing by 0.0005% or more, such as increasing by 0.001% or more, such as increasing by 0.005% or more, such as increasing by 0.01% or more, such as increasing by 0.05% or more, such as increasing by 0.1% or more, such as increasing by 0.5% or more, such as increasing by 1% or more, and includes increases of 2% or more.

[0101] In some embodiments, one or more measurement parameters of the photodetector system are changed based on a calculated trigger index. In some cases, the photodetector duration may vary based on the calculated trigger index, for example, by 0.0001 μs or more, for example, by 0.0005 μs or more, for example, by 0.001 μs or more, for example, by 0.005 μs or more, for example, by 0.01 μs or more, for example, by 0.05 μs or more, for example, by 0.1 μs or more, for example, by 0.5 μs or more, for example, by 1 μs or more, for example, by 2 μs or more, for example, by 3 μs or more, for example, by 4 μs or more, for example, by 5 μs or more, for example, by 10 μs or more, for example, by 50 μs or more, for example, by 100 μs or more, for example, by 500 μs or more, and including variations of 1000 μs or more. For example, the light detection duration can increase by 0.0001% or more, such as 0.0005% or more, such as 0.001% or more, such as 0.005% or more, such as 0.01% or more, such as 0.05% or more, such as 0.1% or more, such as 0.5% or more, such as 1% or more, and includes cases where the light detection duration increases by 2% or more. In some cases, the light detection duration decreases by 0.0001% or more, such as a decrease of 0.0005% or more, such as a decrease of 0.001% or more, such as a decrease of 0.005% or more, such as a decrease of 0.01% or more, such as a decrease of 0.05% or more, such as a decrease of 0.1% or more, such as a decrease of 0.5% or more, such as a decrease of 1% or more, and includes cases where the light detection duration decreases by 2% or more.

[0102] The calculated trigger index can be applied to data signal waveforms generated in one or more photodetector channels (e.g., fluorescence detector channels), such as 5% or more of the photodetector channels in a photodetector system, for example, 10% or more, 20% or more, 30% or more, 40% or more, 50% or more, 60% or more, 70% or more, 80% or more, and including 99% or more of the photodetector channels in a photodetector system. In some cases, the calculated trigger index can be applied to data signal waveforms in all photodetector channels of a photodetector system.

[0103] Figure 2 A flowchart illustrating the calculation of a data signal filter and its application to a data signal waveform according to certain embodiments is described. In step 201, a sample containing particles (e.g., cells or extracellular vesicles) in a flow stream is illuminated with a light source. Light from the illuminated particles is detected in multiple photodetector channels (step 202), for example, in one or more fluorescence photodetector channels. In step 203, a data signal waveform having signal and noise components is generated in each photodetector channel. Characteristics of the data signal waveform (step 204) (e.g., the width component of the data signal) are used to calculate the data signal filter. In some cases, the data signal filter is calculated by matching an optimization algorithm to the actual waveform (step 205). In some cases, the data signal filter is an approximation of a matched filter, for example, by calculating a linear analog data signal filter. In step 206, in some embodiments, the data signal filter may be applied to the data signal waveform, where, in certain cases, it is used to determine trigger indicators for detecting positive event data from the light from the illuminated particles in the sample.

[0104] In some embodiments, the method further includes sorting particles of the sample in the flowing stream. In some cases, methods for sorting components of a sample include sorting particles (e.g., cells in a biological sample) using a particle sorting module with deflection plates, as described in, for example, U.S. Patent 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 (e.g., cells) of the sample, as described in, for example, U.S. Patent Publication No. 2020 / 0256781, the disclosure of which is incorporated herein by reference. In some embodiments, the subject matter system includes a particle sorting module with deflection plates, as described in, for example, U.S. Patent Publication No. 2017 / 0299493, filed March 28, 2017, the disclosure of which is incorporated herein by reference.

[0105] A system for determining and applying data signal filters to detect particles in a flowing stream.

[0106] Aspects of this disclosure include methods for determining a data signal filter for detecting particles (e.g., small particles such as extracellular vesicles) in a particle analyzer. A system according to some embodiments includes: a light source configured to illuminate particles in a flowing stream; a light detection system having a plurality of photodetectors; and a processor with a memory operatively coupled thereto, wherein the memory stores instructions thereon that, when executed by the processor, cause the processor to generate a data signal waveform in response to detected light from particles in the flowing stream, determine characteristics of the data signal waveform, and calculate a data signal filter from the determined characteristics of the data signal waveform. In some embodiments, the memory includes instructions for determining a width parameter of the data signal waveform.

[0107] In one embodiment, the system includes a light source configured to illuminate a sample containing particles in a flowing stream. In another embodiment, the light source can be any suitable broadband or narrowband light source. Depending on the composition of the sample (e.g., cells, beads, non-cellular particles, etc.), the light source can be configured to emit light with varying wavelengths, ranging 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. For example, the light source can include a broadband light source emitting light with wavelengths from 200 nm to 900 nm. In other cases, the light source can include a narrowband light source emitting wavelengths ranging from 200 nm to 900 nm. For example, the light source can be a narrowband LED (1 nm–25 nm) emitting wavelengths between 200 nm and 900 nm. In some embodiments, the light source is a laser. In some cases, the system of interest includes gas lasers, such as helium-neon lasers, argon lasers, krypton lasers, xenon lasers, nitrogen lasers, carbon dioxide lasers, carbon monoxide lasers, argon-fluorine (ArF) excimer lasers, krypton-fluorine (KrF) excimer lasers, xenon-chlorine (XeCl) excimer lasers, or xenon-fluorine (XeF) excimer lasers, or combinations thereof. In other cases, the system of interest includes 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 subject system includes 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.

[0108] In other embodiments, the light source is a non-laser light source, such as a lamp, including but not limited to halogen lamps, deuterium arc lamps, xenon arc lamps, and light-emitting diodes (e.g., broadband LEDs with continuous spectrum, superluminescent LEDs, semiconductor light-emitting diodes, broadband LED white light sources, and multi-LED integrated light sources). In some cases, the non-laser light source can be a stable fiber-coupled broadband light source, a white light source, other light sources, or any combination thereof.

[0109] The light source can be positioned at any suitable distance from the sample (e.g., the flow stream in a flow cytometer), such as 0.001 mm or more, 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, 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 illuminates the sample at any suitable angle (e.g., relative to the vertical axis of the flow stream), such as at angles ranging from 10° to 90°, from 15° to 85°, from 20° to 80°, from 25° to 75°, and including angles ranging from 30° to 60°, such as at a 90° angle.

[0110] The light source can be configured to illuminate the sample continuously or at discrete intervals. In some cases, the system includes a light source configured to continuously illuminate the sample, such as using a continuous-wave laser to continuously illuminate the flow stream at the interrogation point in a flow cytometer. In other cases, the system of interest includes a light source configured to illuminate the sample at discrete intervals, such as every 0.001 milliseconds, every 0.01 milliseconds, every 0.1 milliseconds, every 1 millisecond, every 10 milliseconds, every 100 milliseconds, and including every 1000 milliseconds or some other interval. When the light source is configured to illuminate the sample at discrete intervals, the system may include one or more additional components to allow intermittent illumination of the sample using the light source. For example, the subject system in these embodiments may include one or more laser beam choppers, manually or computer-controlled beam blocks for blocking the sample and exposing the sample to the light source.

[0111] In some embodiments, the light source is a laser. Lasers of interest may include pulsed lasers or continuous-wave lasers. For example, the laser may be: a gas laser, such as a helium-neon laser, an argon laser, a krypton laser, a xenon laser, a nitrogen laser, a carbon dioxide laser, a carbon monoxide 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; a dye laser, such as a stilbene, coumarin, or rhodamine laser; or a metal vapor laser, such as a helium-cadmium (HeCd) laser, a helium-mercury (HeHg) laser, a helium-selenium (HeSe) laser, a helium-silver (HeAg) laser, or a strontium laser. Lasers, including neon-copper (NeCu) lasers, copper lasers, or gold lasers and combinations thereof; 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; semiconductor diode lasers, optically pumped semiconductor lasers (OPSL), or frequency doubling or third harmonics of any of the above lasers.

[0112] In some embodiments, the light source is a beam generator configured to generate two or more beams of frequency-shifted light. In some cases, the beam generator includes a laser, an RF generator configured to apply an RF drive signal to an acousto-optic device to generate two or more angle-deflected laser beams. In these embodiments, the laser may be a pulsed laser or a continuous-wave laser. For example, the laser in the beam generator of interest may be: a gas laser, such as a helium-neon laser, an argon laser, a krypton laser, a xenon laser, a nitrogen laser, a carbon dioxide laser, a carbon monoxide 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; a dye laser, such as a stilbene, coumarin, or rhodamine laser; or a metal vapor laser, such as a helium-cadmium (HeCd) laser, a helium-mercury (HeHg) laser, or a helium-fluorine (HFC) laser. Selenium (HeSe) lasers, helium-silver (HeAg) lasers, strontium lasers, neon-copper (NeCu) lasers, copper lasers, or gold lasers, and combinations thereof; 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.

[0113] The acousto-optic device can be any convenient acousto-optic protocol configured to frequency-shift a laser with applied acoustic waves. In some embodiments, the acousto-optic device is an acousto-optic deflector. The acousto-optic device in this subject system is configured to generate an angle-deflected laser beam using light from a laser and an applied radio frequency (RF) drive signal. The RF drive signal can be applied to the acousto-optic device from any suitable RF drive signal source, such as a direct digital synthesizer (DDS), an arbitrary waveform generator (AWG), or an electrical pulse generator.

[0114] In an embodiment, the controller is configured to apply radio frequency drive signals to the acousto-optic device to generate a desired number of angle-deflected laser beams in the output laser beam, for example, to apply 3 or more radio frequency drive signals, such as 4 or more radio frequency drive signals, such as 5 or more radio frequency drive signals, such as 6 or more radio frequency drive signals, such as 7 or more radio frequency drive signals, such as 8 or more radio frequency drive signals, such as 9 or more radio frequency drive signals, such as 10 or more radio frequency drive signals, such as 15 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.

[0115] In some cases, in order to generate the intensity distribution of the angle-deflected laser beam in the output laser beam, the controller is configured to apply an RF drive signal having an amplitude that varies in the following ranges: for example, from about 0.001 V to about 500 V, for example, from about 0.005 V to about 400 V, for example, from about 0.01 V to about 300 V, for example, from about 0.05 V to about 200 V, for example, from about 0.1 V to about 100 V, for example, from about 0.5 V to about 75 V, for example, from about 1 V to 50 V, for example, from about 2 V to 40 V, for example, from 3 V to about 30 V, and including from about 5 V to about 25 V. In some embodiments, each applied radio frequency drive signal has a frequency from about 0.001 MHz to about 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 includes frequencies from about 5 MHz to about 50 MHz.

[0116] In some embodiments, the controller has a processor with a memory operatively coupled to the processor, such that the memory stores instructions thereon that, when executed by the processor, cause the processor to generate an output laser beam with angled deflections of a desired intensity distribution. For example, the memory may store instructions for generating two or more angled laser beams of equal 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 store instructions for generating 100 or more angled laser beams of equal intensity. In other embodiments, instructions may be included for generating two or more angled laser beams of 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 for generating 100 or more angled laser beams of different intensities.

[0117] 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 generate an output laser beam whose intensity gradually increases along a horizontal axis from the edge to the center. In these cases, the range of the intensity of the angularly deflected laser beam at the center of the output beam can be from 0.1% to about 99% of the intensity of the angularly deflected laser beam at the edge of the output laser beam along the horizontal axis, 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 from about 10% to about 50% of the intensity of the angularly deflected laser beam at the edge of the output laser beam along the horizontal axis. In other 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 generate an output laser beam whose intensity gradually increases along a horizontal axis from the edge to the center. In these cases, the range of the intensity of the angularly deflected laser beam at the edge of the output beam can be from 0.1% to about 99% of the intensity of the angularly deflected laser beam at the center of the output laser beam along the horizontal axis, 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 from about 10% to about 50% of the intensity of the angularly deflected laser beam at the center of the output laser beam along the horizontal axis. In other 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 generate an output laser beam with a Gaussian intensity distribution along a horizontal axis. In other 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 generate an output laser beam with a flat-topped intensity distribution along a horizontal axis.

[0118] In embodiments, the beam generator of interest can be configured to generate angle-deflected laser beams within spatially separated output laser beams. Depending on the applied radio frequency drive signal and the desired illumination profile of the output laser beams, the angle-deflected laser beams can be separated into sizes of 0.001 μm or greater, such as 0.005 μm or greater, 0.01 μm or greater, 0.05 μm or greater, 0.1 μm or greater, 0.5 μm or greater, 1 μm or greater, 5 μm or greater, 10 μm or greater, 100 μm or greater, 500 μm or greater, 1000 μm or greater, and including 5000 μm or greater. In some embodiments, the system is configured to generate angle-deflected laser beams within the output laser beams, which overlap, for example, with adjacent angle-deflected laser beams along the horizontal axis of the output laser beam. The overlap between adjacent angle-deflected laser beams (e.g., the overlap of beam points) can be 0.001 μm or greater, such as 0.005 μm or greater, such as 0.01 μm or greater, such as 0.05 μm or greater, such as 0.1 μm or greater, such as 0.5 μm or greater, such as 1 μm or greater, such as 5 μm or greater, such as 10 μm or greater, and includes 100 μm or greater overlap.

[0119] In some cases, beam generators configured to generate two or more frequency-shifted beams include laser excitation modules as described by Diebold et al. in Nature Photonics Vol. 7 (10), 806-810 (2013), and those described in U.S. Patent Nos. 9,423,353, 9,784,661, 9,983,132, 10,006,852, 10,078,045, 10,036,699, 10,222,316, 10,288,546, 10,324,019, and 10,4 The laser excitation modules described in U.S. Patent Publications 08,758, 10,451,538, 10,620,111 and 2017 / 0133857, 2017 / 0328826, 2017 / 0350803, 2018 / 0275042, 2019 / 0376895 and 2019 / 0376894, the disclosures of which are incorporated herein by reference.

[0120] In some embodiments, the system includes a light detection system with multiple photodetectors. The photodetectors of interest may include, but are not limited to, optical sensors such as active pixel sensors (APS), avalanche photodiodes (APDs), image sensors, charge-coupled devices (CCDs), enhancement-mode charge-coupled devices (ICCDs), light-emitting diodes, photon counters, calorimeters, pyroelectric detectors, photoresistors, photovoltaic cells, photodiodes, photomultiplier tubes, phototransistors, quantum dot photoconductors, or combinations thereof, as well as other photodetectors. In some embodiments, charge-coupled devices (CCDs), semiconductor charge-coupled devices (CCDs), active pixel sensors (APSs), complementary metal-oxide-semiconductor (CMOS) image sensors, or N-type metal-oxide-semiconductor (NMOS) image sensors are used to measure light from a sample.

[0121] In some embodiments, the optical detection system of interest includes multiple photodetectors. In some cases, the optical detection system includes multiple solid-state detectors, such as photodiodes. In some cases, the optical detection system includes a photodetector array, such as a photodiode array. In these embodiments, the photodetector array may include four or more photodetectors, such as ten or more photodetectors, such as 25 or more photodetectors, such as 50 or more photodetectors, such as 100 or more photodetectors, such as 250 or more photodetectors, such as 500 or more photodetectors, such as 750 or more photodetectors, and including 1000 or more photodetectors. For example, the detector may be a photodiode array having four or more photodiodes, such as ten or more photodiodes, such as 25 or more photodiodes, such as 50 or more photodiodes, such as 100 or more photodiodes, such as 250 or more photodiodes, such as 50 or more photodiodes, such as 100 or more photodiodes, such as 250 or more photodiodes, such as 500 or more photodiodes, such as 750 or more photodiodes, and including 1000 or more photodiodes.

[0122] Photodetectors can be arranged in any geometric shape as needed, with arrangements of interest including, but not limited to, square, rectangular, trapezoidal, triangular, hexagonal, heptagonal, octagonal, nonagonal, decagonal, dodecagonal, circular, elliptical, and irregularly patterned configurations. Photodetectors in the photodetector array can be oriented relative to each other (with reference to the XZ plane) at angles ranging from 10° to 180°, such as from 15° to 170°, from 20° to 160°, from 25° to 150°, from 30° to 120°, and including angles from 45° to 90°. The photodetector array can be any suitable shape, including linear shapes such as squares, rectangles, trapezoids, triangles, hexagons, etc.; curved shapes such as circles, ellipses; and irregular shapes such as parabolic shapes with bottom and top planes coupled. In some embodiments, the photodetector array has a rectangular effective surface.

[0123] Each photodetector (e.g., photodiode) in the array may have an effective surface with a width ranging from 5 μm to 250 μm, for example from 10 μm to 225 μm, for example from 15 μm to 200 μm, for example from 20 μm to 175 μm, for example from 25 μm to 150 μm, for example from 30 μm to 125 μm, and including 50 μm to 100 μm, and a length ranging from 5 μm to 250 μm, for example from 10 μm to 225 μm, for example from 15 μm to 200 μm, for example from 20 μm to 175 μm, for example from 25 μm to 150 μm, for example from 30 μm to 125 μm, and including 50 μm to 100 μm, wherein the surface area of ​​each photodetector (e.g., photodiode) in the array ranges from 25 μm. 2 Up to 10000 μm 2 For example, from 50 μm 2 Up to 9000 μm 2 For example, from 75 μm 2 Up to 8000 μm 2 For example, from 100 μm 2 Up to 7000 μm 2 For example, from 150 μm 2 Up to 6000 μm 2 And including from 200 μm 2 Up to 5000 μm 2 .

[0124] The size of a photodetector array can vary depending on the amount and intensity of light, the number of photodetectors, and the required sensitivity. Its length can range from 0.01 mm to 100 mm, for example, from 0.05 mm to 90 mm, from 0.1 mm to 80 mm, from 0.5 mm to 70 mm, from 1 mm to 60 mm, from 2 mm to 50 mm, from 3 mm to 40 mm, from 4 mm to 30 mm, and including 5 mm to 25 mm. The width of the photodetector array can also vary, ranging from 0.01 mm to 100 mm, for example, from 0.05 mm to 90 mm, from 0.1 mm to 80 mm, from 0.5 mm to 70 mm, from 1 mm to 60 mm, from 2 mm to 50 mm, from 3 mm to 40 mm, from 4 mm to 30 mm, and including 5 mm to 25 mm. Therefore, the effective surface area of ​​the photodetector array can range from 0.1 mm... 2 Up to 10000 mm 2 For example, from 0.5 mm 2 Up to 5000 mm 2 For example, from 1 mm 2 Up to 1000 mm 2 For example, from 5 mm 2 Up to 500 mm 2 And including from 10 mm 2 Up to 100 mm 2 .

[0125] The photodetector of interest is configured to measure light collected at one or more wavelengths, such as at two or more wavelengths, such as at five or more different wavelengths, such as at ten or more different wavelengths, such as at 25 or more different wavelengths, such as at 50 or more different wavelengths, such as at 100 or more different wavelengths, such as at 200 or more different wavelengths, such as at 300 or more different wavelengths, and includes measuring light emitted by a sample in a flowing stream at 400 or more different wavelengths.

[0126] In some embodiments, the photodetector is configured to measure light collected within a wavelength range (e.g., 200 nm–1000 nm). In some embodiments, the photodetector of interest is configured to collect a spectrum within a wavelength range. For example, the system may include one or more detectors configured to collect a spectrum within one or more wavelength ranges in the 200 nm–1000 nm wavelength range. In other embodiments, the photodetector of interest is configured to measure light from a sample in the flowing stream at one or more specific wavelengths. For example, the system may include one or more detectors configured to measure light at one or more of the following wavelengths: 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, the photodetector may be configured to pair with a specific fluorophore, such as a fluorophore used with the sample in fluorescence analysis. In some embodiments, the photodetector is configured to measure the light collected across the entire fluorescence spectrum of each fluorophore in the sample.

[0127] The light detection system is configured to measure light continuously or at discrete intervals. In some cases, the photodetector of interest is configured to continuously measure the collected light. In other cases, the light detection system is configured to measure at discrete intervals, such as every 0.001 milliseconds, every 0.01 milliseconds, every 0.1 milliseconds, every 1 millisecond, every 10 milliseconds, every 100 milliseconds, and including every 1000 milliseconds, or at some other interval.

[0128] In some embodiments, the system is configured to identify and classify particles in a sample. In some embodiments, the system is configured to sort identified or classified particles. In these embodiments, the system may include a computer control system, wherein the system also includes one or more computers for fully or partially automating the system for implementing the methods described herein. In embodiments, the system includes a computer having a computer-readable storage medium thereon storing a computer program, wherein the computer program, when loaded onto the computer, also includes instructions for determining characteristics of a data signal waveform. In some embodiments, the memory includes instructions for determining one or more of the following: the height of a data signal, the width of a data signal, the area of ​​a data signal waveform, a combination thereof, or a ratio of one or more of the width, height, and area of ​​a data signal waveform. In some embodiments, the memory includes instructions for determining a width parameter of a data signal waveform. In some embodiments, the width parameter is the ratio of the waveform area to the waveform height. In some embodiments, the data signal waveform has a Gaussian distribution. In other embodiments, the data signal waveform has a super-Gaussian profile.

[0129] In some embodiments, the memory includes instructions for calculating a data signal filter from defined features of a data signal waveform. In other cases, the memory includes instructions for calculating a data signal filter based on a ratio of one or more of the following: the height of the data signal, the width of the data signal, the area of ​​the data signal waveform, or a combination thereof. In some embodiments, the memory includes instructions for calculating a data signal filter based on the ratio of the area of ​​the data signal waveform to the height of the data signal waveform.

[0130] In some embodiments, the memory contains instructions for determining a data signal filter that matches a real waveform generated by the optical detection system. In some embodiments, the matched filter is a calculated data signal filter that, when applied to a data signal from the optical detection system, generates a data signal with the maximum signal-to-noise ratio. In some cases, the memory contains instructions for determining a matched filter that generates the optimal signal-to-noise ratio in the presence of any additive random noise. In some cases, the memory contains instructions for determining a matched filter that has the same functional form as the real signal. In some embodiments, the memory contains instructions for determining a data signal filter that is a linear filter that maximizes a trigger metric.

[0131] In some embodiments, the system includes a computer having a computer-readable storage medium on which a computer program is stored, wherein, when the computer program is loaded onto the computer, it also includes instructions for calculating a data signal filter that takes additive noise into account. Destroyed time series signals , ,in It is the underlying real signal generated by the optical detection system. In some cases, the memory contains instructions for optimizing the calculation of the data signal filter using a function according to the following formula:

[0132]

[0133] in It is the core of the data signal filter; It is the noise component of the data signal; It is the data signal waveform generated by the optical detection system; It represents the standard deviation. In some cases, the numerator of the data signal filter kernel is a function of the maximum data signal waveform after filtering. In other cases, the denominator of the data signal filter kernel is the noise amplitude of the data signal waveform after filtering.

[0134] In some embodiments, the memory contains instructions for calculating a data signal filter, which is an approximation of a matched filter. In some cases, the memory contains instructions for calculating a linear analog data signal filter from determined characteristics of the data signal waveform (e.g., a width parameter). In some cases, the linear analog data signal filter includes a finite impulse response filter. In other cases, the linear analog data signal filter includes an infinite impulse response filter. In some cases, the memory contains instructions for calculating a data signal filter from determined characteristics of the data signal waveform, the filter being selected from the group consisting of: Butterworth filter, Chebyshev filter, elliptic Caul filter, Bessel filter, Gaussian filter, optimal L-filter, Ringquiz-Ryley filter, ideal filter, and matched filter.

[0135] In some embodiments, the memory includes instructions for calculating a data signal filter based on a certain aspect of the particle. In some cases, the data signal filter is based on spatial data of the particle. In some cases, the spatial data includes the horizontal size scale of the particle, the vertical size scale of the particle, the particle size ratio along two different dimensions, and the size ratio of particle components (e.g., the ratio of the horizontal scale of the cell nucleus to the horizontal scale of the cytoplasm). In some cases, the data signal filter is calculated based on the width of the particle. In some cases, the particle is an extracellular vesicle.

[0136] In some embodiments, the memory includes instructions for generating data signal waveforms that are independent of particle size. In certain cases, the generated data signal waveform is independent of particle size when the vertical or horizontal scale of the particle is below a predetermined threshold compared to the beam profile of the light source. For example, the generated data signal waveform may be independent of particle size when one or more of the horizontal or vertical scales are smaller than the beam profile of the light source, such as when the horizontal or vertical scale of the particle is 1% or more, for example 2% or more, for example 3% or more, for example 4% or more, for example 5% or more, for example 10% or more, for example 15% or more, for example 20% or more, and includes cases where the horizontal or vertical scale of the particle is 25% or more smaller than the beam profile of the light source.

[0137] In some embodiments, the system includes a computer having a computer-readable storage medium thereon storing a computer program, wherein the computer program, when loaded onto the computer, further includes instructions for applying a data signal filter to a data signal waveform generated by the photodetector system. In some cases, the memory includes instructions for detecting light from sample particles in the flow stream using the photodetector system, instructions for generating a data signal waveform in response to the detected light, and instructions for applying a calculated data signal filter to the generated data signal waveform. In some cases, the memory includes instructions for calculating a trigger index for the photodetector system to detect particles in the flow stream based on the calculated data signal filter. In some embodiments, the trigger index is the ratio between the amplitude of the data signal waveform and a noise component of the data signal waveform. In some cases, the ratio is the ratio between the maximum value of the data signal waveform and a noise component. In some embodiments, the memory includes instructions for calculating a noise component, which is the root mean square value of the noise in the data signal waveform.

[0138] In some embodiments, the memory includes instructions for storing calculated trigger indicators that change the trigger threshold (e.g., for identifying positive events in the raw data waveform). In one example, the memory includes instructions for decreasing the trigger threshold by 0.0001% or more, such as decreasing by 0.0005% or more, such as decreasing by 0.001% or more, such as decreasing by 0.005% or more, such as decreasing by 0.01% or more, such as decreasing by 0.05% or more, such as decreasing by 0.1% or more, such as decreasing by 0.5% or more, such as decreasing by 1% or more, and including a decrease of 2% or more. In another example, the memory includes instructions for increasing the trigger threshold by 0.0001% or more, such as increasing by 0.0005% or more, such as increasing by 0.001% or more, such as increasing by 0.005% or more, such as increasing by 0.01% or more, such as increasing by 0.05% or more, such as increasing by 0.1% or more, such as increasing by 0.5% or more, such as increasing by 1% or more, and including an increase of 2% or more.

[0139] In some embodiments, the memory includes instructions for changing one or more measurement parameters of the light detection system based on a calculated trigger index. In some cases, the memory includes instructions for increasing or decreasing the light detection duration by 0.0001 μs or more based on the calculated trigger index, for example, increasing or decreasing by 0.0005 μs or more, for example, increasing or decreasing by 0.001 μs or more, for example, increasing or decreasing by 0.005 μs or more, for example, increasing or decreasing by 0.01 μs or more, for example, increasing or decreasing by 0.05 μs or more, for example, increasing or decreasing by 0.1 μs or more, for example, increasing or decreasing by 0.5 μs or more, for example, increasing or decreasing by 1 μs or more, for example, increasing or decreasing by 2 μs or more, for example, increasing or decreasing by 3 μs or more, for example, increasing or decreasing by 4 μs or more, for example, increasing or decreasing by 5 μs or more, for example, increasing or decreasing by 10 μs or more, for example, increasing or decreasing by 50 μs or more, for example, increasing or decreasing by 100 μs or more, for example, increasing or decreasing by 500 μs or more, and including increasing or decreasing by 1000 μs or more. For example, the light detection duration can increase by 0.0001% or more, such as 0.0005% or more, such as 0.001% or more, such as 0.005% or more, such as 0.01% or more, such as 0.05% or more, such as 0.1% or more, such as 0.5% or more, such as 1% or more, and includes cases where the light detection duration increases by 2% or more. In some cases, the light detection duration decreases by 0.0001% or more, such as a decrease of 0.0005% or more, such as a decrease of 0.001% or more, such as a decrease of 0.005% or more, such as a decrease of 0.01% or more, such as a decrease of 0.05% or more, such as a decrease of 0.1% or more, such as a decrease of 0.5% or more, such as a decrease of 1% or more, and includes cases where the light detection duration decreases by 2% or more.

[0140] In an embodiment, the memory includes instructions for applying a calculated trigger index to data signal waveforms generated in one or more photodetector channels (e.g., fluorescence detector channels), such as 5% or more of the photodetector channels in a light detection system, for example, 10% or more, 20% or more, 30% or more, 40% or more, 50% or more, 60% or more, 70% or more, 80% or more, and including 99% or more of the photodetector channels in the light detection system. In some cases, the memory includes instructions for applying the calculated trigger index to data signal waveforms in all photodetector channels of the light detection system.

[0141] According to some embodiments, the system may include a display and an operator input device. The operator input device may be, for example, a keyboard, a mouse, etc. The processing module includes a processor that can access memory on which instructions for performing steps of the methods of this subject are stored. The processing module may include an operating system, a graphical user interface (GUI) controller, system memory, memory storage devices, input / output controllers, caches, data backup units, and many other devices. The processor may be a commercial processor, or may be one of other existing or upcoming processors. The processor executes the operating system, which interfaces with firmware and hardware in a well-known manner and assists the processor in coordinating and executing the functions of various computer programs written in various programming languages, such as Java, Perl, C++, other high-level or low-level languages, and combinations thereof, as known in the art. The operating system typically cooperates with the processor to coordinate and execute the functions of other components of the computer. The operating system also provides scheduling, input / output control, file and data management, memory management, and communication control and related services, all based on known technologies. The processor may be any suitable analog or digital system. In some embodiments, the processor includes analog electronics that provide feedback control (e.g., negative feedback control).

[0142] System memory can be any known or future memory storage device. Examples include any common random access memory (RAM), magnetic media (such as resident hard disks or magnetic tapes), optical media (such as optical discs), flash memory devices, or other memory storage devices. Memory storage devices can be any known or future devices, including optical disc drives, magnetic tape drives, removable hard disk drives, or floppy disk drives. Such memory storage devices typically read from and / or write to program storage media (not shown), such as optical discs, magnetic tapes, removable hard disks, or floppy disks. Any of these program storage media, or other program storage media currently in use or that may be developed in the future, can be considered a computer program product. As should be understood, 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.

[0143] In some embodiments, a computer program product is described that includes a computer-usable medium storing control logic (a computer software program, including program code). When executed by a computer processor, the control logic causes the processor to perform the functions described herein. In other embodiments, some functions are implemented primarily in hardware, for example using a hardware state machine. It will be apparent to those skilled in the art that implementing a hardware state machine to perform the functions described herein will be readily apparent.

[0144] The memory can be any suitable device in which the 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 device). The processor can include a general-purpose digital microprocessor, which is appropriately programmed by a computer-readable medium carrying the necessary program code. The program can be provided to the processor remotely via a communication channel or pre-stored in a computer program product, such as memory or some other portable or fixed computer-readable storage medium, and used with any of these devices associated with the memory. For example, a disk or optical disc can carry the program and can be read by a disk writer / reader. The system of the present invention also includes a program for programming algorithms to implement the methods described above, for example in the form of a computer program product. The program according to the invention 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 ROM; portable flash drives; and hybrid media of these categories, such as magnetic / optical storage media.

[0145] The processor can also access communication channels to communicate with remote users. Remote means that the user does not directly interact with the system, but instead relays input information from external devices (such as computers connected to a wide area network (“WAN”), telephone network, satellite network, or any other suitable communication channel, including mobile phones (such as smartphones)) to the input manager.

[0146] In some embodiments, the system according to this disclosure 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., RFID, Zigbee communication protocol, WiFi, 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).

[0147] In one embodiment, the communication interface is configured to include one or more communication ports, such as physical ports or interfaces like USB ports, RS-232 ports, or any other suitable electrical connection ports, to allow the subject system to communicate data with other external devices (e.g., computer terminals (e.g., in a doctor's office or hospital environment)) configured to perform similar complementary data communications.

[0148] In one embodiment, the communication interface is configured for 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 can use in conjunction with them.

[0149] In one embodiment, the communication interface is configured to provide data transmission connectivity via a mobile network using Internet Protocol (IP), Short Message Service (SMS), a wireless connection to a personal computer (PC) on a local area network (LAN) connected to the Internet, or a WiFi connection to the Internet at a WiFi hotspot.

[0150] In one embodiment, the system is configured to wirelessly communicate with a server device via a communication interface, such as using a common standard, such as 802.11 or the Bluetooth® RF protocol, or the IrDA infrared protocol. The server device may be another portable device, such as a smartphone, personal digital assistant (PDA), or laptop; or a larger device, such as a desktop computer, home appliance, etc. In some embodiments, the server device has a display, such as a liquid crystal display (LCD), and input devices, such as buttons, a keyboard, a mouse, or a touchscreen.

[0151] In some embodiments, the communication interface is configured to automatically or semi-automatically transmit data stored in the subject system (e.g., optional data storage unit) to a network or server device using one or more of the communication protocols and / or mechanisms described above.

[0152] The output controller may include controllers for various 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 may typically be logically and / or physically organized as an array of picture elements. The graphical user interface (GUI) controller may include any of various known or future software programs for providing a graphical input and 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, one of these communications may be implemented using a network or other type of remote communication. The output manager may also provide information generated by the processing module to a remote user, for example, via the Internet, telephone, or satellite networks, according to known technologies. The presentation of data by the output manager may be implemented according to various known technologies. As some examples, the data may include SQL, HTML, or XML documents, emails or other files, or other forms of data. The data may contain Internet URL addresses so that the user can retrieve other 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 mainframes, workstations, or other computer types. They can be connected via any known or future type of cable or other communication system (including wireless systems), whether networked or otherwise. They can be co-located or physically separated. A variety of operating systems can be used on any computer platform, depending on the type and / or brand of the chosen platform. Suitable operating systems include Windows 10 and Windows NT. ® , Windows XP, Windows 7, Windows 8, iOS, Sun Solaris, Linux, OS / 400, Compaq Tru64 Unix, SGI IRIX, Siemens Reliant Unix, Ubuntu, Zorin OS, etc.

[0153] In some embodiments, the subject matter system includes one or more optical adjustment components for adjusting light, such as light incident on a sample (e.g., light from a laser) or light collected from a sample (e.g., scattered light, fluorescence). For example, optical adjustment can increase the size of the light, the focus of the light, or collimate the light. In some cases, optical adjustment is an amplification scheme to increase the size of the light (e.g., the beam point), such as increasing the size by 5% or more, such as increasing by 10% or more, such as increasing by 25% or more, such as increasing by 50% or more, and including increasing the size by 75% or more. In other embodiments, optical adjustment includes focusing the light to reduce the size of the light, such as reducing by 5% or more, such as reducing by 10% or more, such as reducing by 25% or more, such as reducing by 50% or more, and including reducing the size of the beam point by 75% or more. In some embodiments, optical adjustment includes collimating light. The term "collimating" is conventionally used to refer to optically adjusting the collinearity of light propagation, or reducing the divergence of light from the same propagation axis. In some cases, collimation includes reducing the spatial cross-section of the beam (e.g., reducing the beam profile of a laser).

[0154] In some embodiments, the optical adjustment component is a focusing lens with a magnification ranging from 0.1 to 0.95, for example, from 0.2 to 0.9, from 0.3 to 0.85, from 0.35 to 0.8, from 0.5 to 0.75, and including magnifications from 0.55 to 0.7, such as 0.6. For example, in some cases, the focusing lens is a biachromatic reducing lens with a magnification of approximately 0.6. The focal length of the focusing lens can vary, ranging from 5 mm to 20 mm, for example, from 6 mm to 19 mm, from 7 mm to 18 mm, from 8 mm to 17 mm, from 9 mm to 16 mm, and including focal lengths ranging from 10 mm to 15 mm. In some embodiments, the focal length of the focusing lens is approximately 13 mm.

[0155] In other embodiments, the optical adjustment component is a collimator. The collimator can employ any convenient collimation scheme, such as one or more mirrors or curved lenses, or combinations thereof. For example, in some cases, the collimator is a single collimating lens. In other cases, the collimator is a collimating mirror. In still other cases, the collimator comprises two lenses. In yet another case, the collimator comprises a mirror and a lens. When the collimator comprises one or more lenses, the focal length of the collimating lens can vary from 5 mm to 40 mm, for example from 6 mm to 37.5 mm, for example from 7 mm to 35 mm, for example from 8 mm to 32.5 mm, for example from 9 mm to 30 mm, for example from 10 mm to 27.5 mm, for example from 12.5 mm to 25 mm, and includes focal lengths ranging from 15 mm to 20 mm.

[0156] In some embodiments, the present invention system includes a flow cell nozzle having a nozzle orifice configured to allow flow through the flow cell nozzle. The flow cell nozzle has an orifice that delivers a fluid sample to a sample interrogation region, wherein in some embodiments, the flow cell nozzle includes a proximal cylindrical portion defining a longitudinal axis and a distal truncated conical portion terminating in a flat surface transverse to the longitudinal axis, having the nozzle orifice. The length (measured along the longitudinal axis) of the proximal cylindrical portion can vary from 1 mm to 15 mm, for example from 1.5 mm to 12.5 mm, for example from 2 mm to 10 mm, for example from 3 mm to 9 mm, and includes a range from 4 mm to 8 mm. The length (measured along the longitudinal axis) of the distal truncated conical portion can also vary from 1 mm to 10 mm, for example from 2 mm to 9 mm, for example from 3 mm to 8 mm, and includes a range from 4 mm to 7 mm. In some embodiments, the diameter of the flow pool nozzle may vary, ranging from 1 mm to 10 mm, for example from 2 mm to 9 mm, for example from 3 mm to 8 mm, and including from 4 mm to 7 mm.

[0157] In some cases, the nozzle chamber does not include a cylindrical portion, and the entire flow pool nozzle chamber is truncated conical. In these embodiments, the length of the truncated conical nozzle chamber (measured along the longitudinal axis transverse to the nozzle orifice) can range from 1 mm to 15 mm, for example from 1.5 mm to 12.5 mm, for example from 2 mm to 10 mm, for example from 3 mm to 9 mm, and includes 4 mm to 8 mm. The diameter of the proximal portion of the truncated conical nozzle chamber can range from 1 mm to 10 mm, for example from 2 mm to 9 mm, for example from 3 mm to 8 mm, and includes 4 mm to 7 mm.

[0158] In this embodiment, the sample flow exits from an orifice at the distal end of the flow cell nozzle. Depending on the desired flow characteristics, the flow cell nozzle orifice can be of any suitable shape, with cross-sectional shapes of interest including, but not limited to: linear cross-sectional shapes, such as squares, rectangles, trapezoids, triangles, hexagons, etc.; curved cross-sectional shapes, such as circles, ellipses; and irregular shapes, such as parabolic shapes where the bottom connects to the top of a plane. In some embodiments, the flow cell nozzle of interest has a circular orifice. In some embodiments, the nozzle orifice size can vary, ranging from 1 μm to 20,000 μm, for example from 2 μm to 17,500 μm, for example from 5 μm to 15,000 μm, for example from 10 μm to 12,500 μm, for example from 15 μm to 10,000 μm, for example from 25 μm to 7,500 μm, for example from 50 μm to 5,000 μm, for example from 75 μm to 1,000 μm, for example from 100 μm to 750 μm, and including 150 μm to 500 μm. In some embodiments, the nozzle orifice diameter is 100 μm.

[0159] In some embodiments, the flow cell nozzle includes a sample injection port configured to provide a sample to the flow cell nozzle. In some embodiments, the sample injection system is configured to provide a suitable sample flow rate to the flow cell nozzle chamber. Depending on the characteristics of the desired flow, the rate at which the sample delivered to the flow cell nozzle chamber through the sample injection port can be 1 μL / s or higher, for example, 2 μL / s or higher, for example, 3 μL / s or higher, for example, 5 μL / s or higher, for example, 10 μL / s or higher, for example, 15 μL / s or higher, for example, 25 μL / s or higher, for example, 50 μL / s or higher, for example, 100 μL / s or higher, for example, 150 μL / s or higher, for example, 200 μL / s or higher, for example, 250 μL / s or higher, for example, 300 μL / s or higher, for example, 350 μL / s or higher, for example, 400 μL / s or higher, for example, 450 μL / s or higher, and including 500 μL / s or higher. For example, the sample flow rate can range from 1 μL / sec to about 500 μL / sec, for example from 2 μL / sec to about 450 μL / sec, for example from 3 μL / sec to about 400 μL / sec, for example from 4 μL / sec to about 350 μL / sec, for example from 5 μL / sec to about 300 μL / sec, for example from 6 μL / sec to about 250 μL / sec, for example from 7 μL / sec to about 200 μL / sec, for example from 8 μL / sec to about 150 μL / sec, for example from 9 μL / sec to about 125 μL / sec, and includes from 10 μL / sec to about 100 μL / sec.

[0160] The sample injection port can be an orifice located in the wall of the nozzle chamber, or it can be a conduit located near the proximal end of the nozzle chamber. When the sample injection port is an orifice located in the wall of the nozzle chamber, the orifice can be of any suitable shape, wherein the 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 shapes where the bottom and top planes connect. In some embodiments, the sample injection port has a circular orifice. The size of the sample injection port orifice can vary depending on the shape, and in some cases, the opening ranges from 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 from 1 mm to 2 mm, and includes from 1.25 mm to 1.75 mm, for example 1.5 mm.

[0161] In some cases, the sample injection port is a conduit located proximal to the flow cell nozzle chamber. For example, the sample injection port may be a conduit positioned such that its orifice aligns with the flow cell nozzle orifice. When the sample injection port is a conduit positioned aligned with the flow cell nozzle 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; and irregular shapes, such as parabolic shapes where the bottom connects to the top of a plane. The orifice of the conduit can vary depending on its shape, and in some cases, its opening size ranges from 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 from 0.75 mm to 2.25 mm, for example from 1 mm to 2 mm, and includes sizes from 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 sample injection port may include a beveled tip with an angle ranging from 1° to 10°, such as from 2° to 9°, such as from 3° to 8°, such as from 4° to 7°, and including a bevel of 5°.

[0162] In some embodiments, the flow cell nozzle further includes a sheath fluid injection port configured to supply sheath fluid to the flow cell nozzle. In some embodiments, the sheath fluid injection system is configured to supply a sheath fluid flow to the flow cell nozzle chamber, for example, together with a sample, to generate a laminar flow of sheath fluid surrounding a sample flow. Depending on the desired characteristics of the flow flow, the rate at which the sheath fluid is delivered to the flow cell nozzle chamber can be 25 μL / s or higher, for example 50 μL / s or higher, for example 75 μL / s or higher, for example 100 μL / s or higher, for example 250 μL / s or higher, for example 500 μL / s or higher, for example 750 μL / s or higher, for example 1000 μL / s or higher, and includes 2500 μL / s or higher. For example, the sheath fluid flow rate can range from 1 μL / s to about 500 μL / s, for example from 2 μL / s to about 450 μL / s, for example from 3 μL / s to about 400 μL / s, for example from 4 μL / s to about 350 μL / s, for example from 5 μL / s to about 300 μL / s, for example from 6 μL / s to about 250 μL / s, for example from 7 μL / s to about 200 μL / s, for example from 8 μL / s to about 150 μL / s, for example from 9 μL / s to about 125 μL / s, and includes from 10 μL / s to about 100 μL / s.

[0163] In some embodiments, the sheath fluid injection port is an orifice located in the wall of the nozzle chamber. The sheath fluid injection port orifice can be of any suitable shape, with cross-sectional shapes of interest including, but not limited to: linear cross-sectional shapes, such as squares, rectangles, trapezoids, triangles, hexagons, etc.; curved cross-sectional shapes, such as circles, ellipses; and irregular shapes, such as parabolic shapes where the bottom and top planes connect. The size of the sample injection port orifice can vary depending on the shape, and in some cases, the opening ranges from 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.

[0164] In some cases, the system includes a sample interrogation region in fluid communication with the flow cell nozzle orifice. In these cases, the sample flow exits from an orifice at the distal end of the flow cell nozzle, and particles in the flow can be illuminated by a light source at the sample interrogation region. The size of the interrogation region can vary depending on the properties of the flow nozzle, such as the size of the nozzle orifice and the size of the sample inlet. In embodiments, the width of the interrogation region can be 0.01 mm or greater, for example 0.05 mm or greater, for example 0.1 mm or greater, for example 0.5 mm or greater, for example 1 mm or greater, for example 2 mm or greater, for example 3 mm or greater, for example 5 mm or greater, and including 10 mm or greater. The length of the inquiry area can also vary, and in some cases it is 0.01 mm or longer, such as 0.1 mm or longer, such as 0.5 mm or longer, such as 1 mm or longer, such as 1.5 mm or longer, such as 2 mm or longer, such as 3 mm or longer, such as 5 mm or longer, such as 10 mm or longer, such as 15 mm or longer, such as 20 mm or longer, such as 25 mm or longer, and including 50 mm or longer.

[0165] The interrogation region can be configured to facilitate the illumination of a planar cross-section of the outflowing flow, or it can be configured to facilitate the illumination of a diffuse field of a predetermined length (e.g., using a diffuse laser or lamp). In some embodiments, the interrogation region includes a transparent window that facilitates the illumination of a predetermined length of the outflowing flow, such as 1 mm or longer, 2 mm or longer, 3 mm or longer, 4 mm or longer, 5 mm or longer, and including 10 mm or longer. Depending on the light source used to illuminate the outflowing flow (described below), the interrogation region can be configured to transmit light ranging from 100 nm to 1500 nm, such as from 150 nm to 1400 nm, from 200 nm to 1300 nm, from 250 nm to 1200 nm, from 300 nm to 1100 nm, from 350 nm to 1000 nm, from 400 nm to 900 nm, and including from 500 nm to 800 nm.Therefore, the query area can be formed of any transparent material that passes through the desired wavelength range, including but not limited to optical glass, borosilicate glass, pyrex glass, ultraviolet quartz, infrared quartz, sapphire, and plastics such as polycarbonate, polyvinyl chloride (PVC), polyurethane, polyether, polyamide, polyimide, or copolymers of these thermoplastics, such as PETG (ethylene glycol-modified polyethylene terephthalate), and other polymeric plastic materials, including polyesters, wherein the polyester of interest may include, but is not limited to, poly(alkylene terephthalate), such as polyethylene terephthalate (PE). T), bottle-grade PET (a copolymer based on monoethylene glycol, terephthalic acid and other comonomers such as isophthalic acid, cyclohexenedimethyl alcohol, etc.), poly(butylene terephthalate) (PBT) and poly(hexamethylene terephthalate); poly(alkyl adipate), such as poly(ethylene adipate), poly(1,4-butanediol adipate and polyhexamethylene adipate; polyalkyl octanoate, such as poly(ethylene octanoate); polyalkyl sebacate, such as poly(ethylene sebacate); poly(ε-caprolactone and poly(β-propiolactone); polyalkyl isophthalate, such as polyethylene isophthalate; Poly(2,6-naphthalenedicarboxylate), for example, poly(2,6-naphthalenedicarboxylate); poly(alkylenesulfonyl-4,4′-dibenzoate), for example, poly(ethylenesulfonyl-4,4′-dibenzoate); poly(p-phenylene dicarboxylate), for example, poly(p-phenylene dicarboxylate); poly(trans-1,4-cyclohexanediyl dicarboxylate), for example, poly(trans-1,4-cyclohexanediyl dicarboxylate); poly(1,4-cyclohexane-dimethylenealkylene dicarboxylate), for example, poly(1,4-cyclohexane-dimethylene ethylene dicarboxylate); poly([2.2.2]-bicyclooctane -1,4-dimethylenealkylene dicarboxylate, such as poly([2.2.2]-bicyclooctane-1,4-dimethyleneethylene dicarboxylate); lactic acid polymers and copolymers, such as (S)-polylactide, (R,S)-polylactide, poly(tetramethylglycolic acid) and poly(lactide-co-glycolic acid); and polycarbonates of bisphenol A, 3,3'-dimethylbisphenol A, 3,3',5,5'-tetrachlorobisphenol A, and 3,3',5,5'-tetramethylbisphenol A; polyamides, such as poly(p-phenylene terephthalamide); polyesters, such as polyethylene terephthalate, such as Mylar. TMPolyethylene terephthalate; etc. In some embodiments, the subject matter system includes a cuvette located in the sample interrogation area. In embodiments, the cuvette may allow light in the range of 100 nm to 1500 nm to pass through, such as light from 150 nm to 1400 nm, such as light from 200 nm to 1300 nm, such as light from 250 nm to 1200 nm, such as light from 300 nm to 1100 nm, such as light from 350 nm to 1000 nm, such as light from 400 nm to 900 nm, and including light from 500 nm to 800 nm.

[0166] In some embodiments, the optical detection system having multiple photodetectors as described above is part of or located within a particle analyzer (e.g., a particle sorter). In some embodiments, the subject system is a flow cytometry system that includes photodiodes and amplifier assemblies as part of an optical detection system for detecting light emitted by a sample in a flowing stream. Suitable flow cytometry systems may include, but are not limited to, those described in the following literature: Ormerod (ed.), Flow Cytometry: A Practical Approach, Oxford University Press (1997); Jaroszeski et al. (ed.), Flow Cytometry Protocols, Methods in Molecular Biology, Vol. 91, Humana Press (1997); Practical Flow Cytometry, 3rd Edition, Wiley-Liss (1995); Virgo et al. (2012) Ann Clin Biochem. Jan; 49 (Part 1): 17-28; Linden et al., Semin Throm Hemost. Oct. 2004; 30(5): 502-11; Alison et al., J Pathol, Dec. 2010; 222(4): 335-344; and Herbig et al. (2007) Crit Rev Ther Drug Carrier Syst. 24(3): 203-255; its publication is incorporated herein by reference. In some cases, flow cytometry systems of interest include BD Biosciences FACSCanto. TM Flow cytometer, BD Biosciences FACSCanto TM II flow cytometer, BD Accuri TM Flow cytometer, BD Accuri TMC6 Plus flow cytometer, BDBiosciences FACSCelesta TM Flow cytometer, BD Biosciences FACSLyric TM Flow cytometer, BDBiosciences FACSVerse TM Flow cytometer, BD Biosciences FACSymphony TM Flow cytometer, BDBiosciences LSRFortessa TM Flow cytometer, BD Biosciences LSRFortessa TM X-20 flow cytometer, BD Biosciences FACSPresto TM Flow cytometer, BD Biosciences FACSVia TM Flow cytometer and BD Biosciences FACSCalibur TM Cell sorter, BD Biosciences FACSCount TM Cell sorter, BDBiosciences FACSLyric TM Cell sorter, BD BiosciencesVia TM Cell sorters, including BD Biosciences Influxe, BD Biosciences Jazzc, BD Biosciences Ariac, BD Biosciences FACSAriac II, BD Biosciences FACSAriac III, BD Biosciences FACSAriac Fusion, BD Biosciences FACSMelodys, and BD Biosciences FACSymphony. TM S6 cell sorter, etc.

[0167] In some embodiments, the subject system is a flow cytometry system, such as those described in U.S. Patent Nos. 10,663,476, 10,620,111, 10,613,017, 10,605,713, 10,585,031, 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 The systems described in ,095,494, 9,092,034, 8,975,595, 8,753,573, 8,233,146, 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, the disclosures of which are incorporated herein by reference in their entirety.

[0168] In some embodiments, the present subject system is a particle sorting system configured to sort particles using a closed particle sorting module, such as the system described in U.S. Patent Publication No. 2017 / 0299493, which is incorporated herein by reference. In some embodiments, a sorting decision module having multiple sorting decision units is used to sort particles (e.g., cells) in a sample, such as the system described in U.S. Patent Publication No. 2020 / 0256781, which is incorporated herein by reference. In some embodiments, the present subject system includes a particle sorting module with deflection plates, such as the system described in U.S. Patent Publication No. 2017 / 0299493, filed March 28, 2017, which is incorporated herein by reference.

[0169] In some cases, the flow cytometry system of the present invention is 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), 806-810 (2013) and U.S. Patent Nos. 9,423,353, 9,784,661, 9,983,132, 10,006,852, 10,078,045, 10,036,699, 10,222,316, 10,288,546, 10,324,019, and 10,408,7 The disclosures of those described in U.S. Patent Publications 58, 10,451,538, 10,620,111; and those described in U.S. Patent Publications 2017 / 0133857, 2017 / 0328826, 2017 / 0350803, 2018 / 0275042, 2019 / 0376895, and 2019 / 0376894 are incorporated herein by reference.

[0170] In some embodiments, the present subject system is configured to sort one or more particles (e.g., cells) in a sample, which are identified based on the estimated abundance of fluorophores associated with the particles as described above. The term "sorting" is used herein in its conventional sense to refer to the separation of components (e.g., cells, non-cellular particles, such as biomacromolecules) from a sample and, in some cases, the delivery of the separated components to one or more sample collection containers. For example, the present subject system can be configured to sort samples having two or more components, such as three or more components, such as four or more components, such as five or more components, such as ten or more components, such as fifteen or more components, and including the sorting of samples having 25 or more components. One or more sample components can be separated from a sample and delivered to a sample collection container, for example, two or more sample components can be separated from a sample, such as three or more sample components, such as four or more sample components, such as five or more sample components, such as ten or more sample components, and including fifteen or more sample components, and delivered to a sample collection container.

[0171] In some embodiments, the particle sorting system of interest is configured to sort particles using a closed particle sorting module, such as the sorting module described in U.S. Patent Publication No. 2017 / 0299493, filed March 28, 2017, which is incorporated herein by reference. In some embodiments, a sorting decision module having multiple sorting decision units is used to sort particles (e.g., cells) in a sample, such as the sorting decision module described in U.S. Patent Publication No. 2020 / 0256781, which is incorporated herein by reference. In some embodiments, the system of interest includes a particle sorting module with deflection plates, such as the particle sorting module described in U.S. Patent Publication No. 2017 / 0299493, filed March 28, 2017, which is incorporated herein by reference.

[0172] In some embodiments, the system uses fluorescence imaging with a particle sorter that supports radio frequency tag emission imaging, such as... Figure 3AAs shown. The particle sorter 300 includes an illumination assembly 300a containing a light source 301 (e.g., a 488 nm laser) that generates an output beam 301a, which is split into beams 302a and 302b by a beam splitter 302. Beam 302a propagates through an acousto-optic device (e.g., an acousto-optic deflector, AOD) 303 to generate an output beam 303a with one or more angled deflections. In some cases, 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 (e.g., an acousto-optic deflector, AOD) 304 to generate an output beam 304a with one or more angled deflections. In some cases, 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 from acousto-optic devices 303 and 304 respectively, are combined by beam splitter 305 to generate output beam 305a, which is delivered through optical element 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 sub-beams, each sub-beam having a different optical frequency and angle. A second AOD 304 modulates the optical frequency of a reference beam, which is then overlapped with the sub-beam array at beam combiner 305. In some embodiments, the light illumination system having a light source and acousto-optic device may also include the system described by Schraivogel et al. in “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.

[0173] Output beam 305a irradiates sample particles 308 passing through flow cell 307 (e.g., with sheath fluid 309) at irradiation region 310. As shown in irradiation region 310, multiple beams (e.g., angle-deflected RF shift beams depicted as dots on irradiation region 310) overlap with a reference local oscillator beam (indicated by shaded lines on irradiation region 310). Due to their different optical frequencies, the overlapping beams exhibit beat frequency behavior, resulting in each sub-beam operating at a different frequency f. 1-n Perform sinusoidal modulation.

[0174] 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 using 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 optics 321, 322, 323, and 324 (e.g., dichroic mirrors) for propagating light of a predetermined wavelength to photodetectors 314-317. In some cases, optics 321 has a 534 nm / 40 nm bandpass. In some cases, optics 322 has a 586 nm / 42 nm bandpass. In some cases, optics 323 has a 700 nm / 54 nm bandpass. In some cases, optics 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. Thus, the 510 / 20 filter extends 10 nm on each side of the center of the spectral band, or from 500 nm to 520 nm.

[0175] Data signals generated in response to light detected in scattered light detection channels 311 and 312, bright field light detection channel 313, and fluorescence detection channels 314-317 are processed digitally in real time using processors 350 and 351. Images 311a-317a can be generated in each light detection channel based on the data signals generated in processors 350 and 351. Image-supporting 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 the module described in U.S. Patent Publication No. 2017 / 0299493, filed March 28, 2017, the disclosure of which is incorporated herein by reference. In some embodiments, 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 contents of which are incorporated herein by reference.

[0176] Figure 3B Image-supported particle sorting data processing is described according to certain embodiments. In some cases, image-supported particle sorting data processing is a low-latency data processing pipeline. Each photodetector generates a pulse with high-frequency modulation to encode an image (waveform). Fourier analysis is performed to reconstruct the image from the modulated pulse. The image processing pipeline produces a set of image features (image analysis), which are combined with features obtained from the pulse processing pipeline (event packets). Real-time sorting and classification electronics then classify the particles based on the image features, generating sorting decisions for selectively charging droplets.

[0177] In some embodiments, the system is a particle analyzer, wherein the particle analysis system 401 ( Figure 4A It can be used to analyze and characterize particles, whether or not the particles are physically sorted into collection containers. Figure 4A 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 flow system. Figure 4A The particle analysis system 401 shown can be configured to perform all or part of the methods described herein, for example. The particle analysis system 401 includes a fluid system 402. The fluid system 402 may include or be coupled to a sample tube 405 and a moving fluid column within the sample tube, in which particles 403 (e.g., cells) of the sample move along a common sample path 409.

[0178] 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 sampling path. Detection station 408 typically refers to a monitored area 407 of the common sampling path. In some implementations, detection may include detecting light or one or more other characteristics of a particle 403 as it passes through the monitored area 407. Figure 4A The diagram shows a detection station 408 and a monitored area 407. Some implementations of the particle analysis system 401 may include multiple detection stations. Furthermore, some detection stations can monitor more than one area.

[0179] Each signal is assigned a signal value to form a data point for each particle. As mentioned above, this data can be referred to as event data. The data point can be a multidimensional data point containing values ​​of individual attributes measured for each particle. The detection system 404 is configured to collect a series of such data points over a first time interval.

[0180] The particle analysis system 401 may also include a control system 306. The control system 406 may include one or more processors, amplitude control circuitry, and / or frequency control circuitry. The control system shown 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 a Poisson distribution and the number of data points collected by the detection system 404 within the first time interval. The control system 406 may be further configured to generate an experimental signal frequency based on the number of data points within a portion of the first time interval. The control system 406 may also compare the experimental signal frequency with a calculated signal frequency or a predetermined signal frequency.

[0181] Figure 4B A system 400 for flow cytometry according to an exemplary embodiment of the present invention is shown. The system 400 includes a flow cytometer 410, a controller / processor 490, and a memory 495. The flow cytometer 410 includes one or more excitation lasers 415a-415c, a focusing lens 420, a flow chamber 425, a forward scatter detector 430, a side scatter detector 435, a fluorescence collecting lens 440, one or more beam splitters 445a-445g, one or more bandpass filters 450a-450e, one or more long-pass (“LP”) filters 455a-455b, and one or more fluorescence detectors 460a-460f.

[0182] The excitation lasers 115a-115c emit light in the form of a laser beam. Figure 4B In the example system, the laser beams emitted from excitation lasers 415a-415c have wavelengths of 488 nm, 633 nm, and 325 nm, respectively. The laser beams are first guided through one or more beams splitters 445a and 445b. Beam splitter 445a transmits 488 nm light and reflects 633 nm light. Beam splitter 445b transmits ultraviolet light (wavelength range of 10 to 400 nm) and reflects both 488 nm and 633 nm light.

[0183] The laser beam is then directed to a focusing lens 420, which focuses the beam onto the flow stream portion containing the sample particles within a flow chamber 425. The flow chamber is part of a fluid system that guides particles (typically one at a time) in the flow stream toward the focused laser beam for interrogation. The flow chamber may include a flow cell in a benchtop cytometer or a nozzle head in a gas flow cytometer.

[0184] Light from the laser beam interacts with particles in the sample through diffraction, refraction, reflection, scattering, and absorption, and is re-emitted at various wavelengths depending on the characteristics of the particles (e.g., their size, internal structure, and the presence of one or more fluorescent molecules naturally present on or within the particles). The fluorescence emission, along with the diffracted, refracted, reflected, and scattered light, can be routed through one or more of beam splitters 445c-445g, bandpass filters 450a-450e, longpass filters 455a-455b, and fluorescence collecting lens 440 to one or more of forward scattering detector 430, side scattering detector 435, and one or more fluorescence detectors 460a-460f.

[0185] A fluorescence collecting lens 440 collects light emitted from the particle-laser beam interaction and directs the light to one or more beam splitters and filters. Bandpass filters (e.g., bandpass filters 450a-450e) allow a narrow range of wavelengths to pass through the filter. For example, bandpass filter 450a is a 510 / 20 filter. The first number indicates the center of the spectral band. The second number provides the range of the spectral band. Thus, a 510 / 20 filter extends 10 nm on each side of the center of the spectral band, or from 500 nm to 520 nm. Short-pass filters transmit light with wavelengths equal to or shorter than a specified wavelength. Long-pass filters (e.g., long-pass filters 455a-455b) transmit light with wavelengths equal to or longer than a specified wavelength. For example, long-pass filter 455a is a 670 nm long-pass filter that transmits light equal to or longer than 670 nm. Filters are typically selected to optimize the detector's specificity for a particular fluorescent dye. The filter can be configured such that the spectral band of the light transmitted to the detector is close to the emission peak of the fluorescent dye.

[0186] Beam splitters direct light of different wavelengths in different directions. Beam splitters can be characterized by filter properties such as short-pass and long-pass characteristics. For example, beam splitter 445g is a 620 SP beam splitter, meaning that beam splitter 445g transmits light with wavelengths of 620 nm or shorter and reflects light with wavelengths greater than 620 nm in different directions. In one embodiment, beam splitters 445a-445g may include optical mirrors, such as dichroic mirrors.

[0187] The forward scattering detector 430 is positioned slightly off-center from the axis of the direct beam passing through the flow cell and is configured to detect diffracted light, i.e., excitation light that primarily travels forward through or around the particle. The intensity of the light detected by the forward scattering detector depends on the overall size of the particle. The forward scattering detector may include a photodiode. The side scattering detector 435 is configured to detect refracted and reflected light from the particle surface and internal structure, increasing with the complexity of the particle structure. Fluorescence emission from fluorescent molecules associated with the particle can be detected by one or more fluorescence detectors 460a-460f. The side scattering detector 435 and the fluorescence detector may include photomultiplier tubes. The signals detected at the forward scattering detector 430, the side scattering detector 435, and the fluorescence detector can be converted into electronic signals (voltages) by the detectors. This data can provide information about the sample.

[0188] Those skilled in the art will recognize that the flow cytometer according to embodiments of the present invention is not limited to Figure 4B The flow cytometer shown may be any flow cytometer known in the art. For example, a flow cytometer may have any number of lasers, beam splitters, filters, and detectors, and may have various wavelengths and various different configurations.

[0189] During operation, the cytometer is controlled by a controller / processor 490, and measurement data from the detector can be stored in memory 495 and processed by the controller / processor 490. Although not explicitly shown, the controller / processor 490 is coupled to the detector to receive output signals from the detector and can also be coupled to the electrical and electromechanical components of the flow cytometer 410 to control the laser, flow parameters, etc. Input / output (I / O) functionality 497 may also be provided in the system. Memory 495, controller / processor 490, and I / O 497 may be provided as an integral part of the flow cytometer 410. In such an embodiment, a display may also form part of the I / O functionality 497 for presenting experimental data to the user of the cytometer 400. Alternatively, some or all of the memory 495 and controller / processor 490 and I / O functionality may be part of one or more external devices (e.g., a general-purpose computer). In some embodiments, some or all of the memory 495 and controller / processor 490 may communicate wirelessly or wired with the cytometer 410. The controller / processor 490, together with memory 495 and I / O 497, can be configured to perform various functions related to the preparation and analysis of flow cytometry experiments.

[0190] Figure 4BThe system shown includes six different detectors that detect fluorescence in six different wavelength bands (which may be referred to herein as “filter windows” for a given detector), defined by the configuration of filters and / or spectrometers in the beam path from flow cell 425 to each detector. Different fluorescent molecules used in flow cytometry experiments will emit light in their own characteristic wavelength bands. Specific fluorescent tags used in experiments and their associated fluorescence emission bands can be selected to roughly coincide with the filter windows of the detectors. However, as more detectors are provided and more tags are used, a perfect correspondence between filter windows and fluorescence emission spectra is impossible. Typically, although the peak of the emission spectrum of a particular fluorescent molecule may lie within the filter window of a particular detector, a portion of the emission spectrum of that tag may also overlap with the filter windows of one or more other detectors. This can be referred to as spillover. I / O 497 can be configured to receive data for a flow cytometry experiment having a set of fluorescent tags and multiple cell populations with multiple labels, each cell population having a subset of multiple labels. I / O 497 can also be configured to receive biological data, label density data, emission spectral data, data on tag assignment to one or more cell populations, and cytometer configuration data. Flow cytometry experimental data (e.g., tag spectral characteristics and flow cytometry configuration data) can also be stored in memory 495. Controller / processor 490 can be configured to evaluate one or more tag-to-label assignments.

[0191] 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.

[0192] The particle analyzer or sorting system 502 can be 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 biological event data to an analysis controller 500. A data communication channel may be included between the particle analyzer or analysis system 502 and the analysis controller 500. The biological event data can be provided to the analysis controller 500 via the data communication channel.

[0193] Analysis controller 500 is configurable to receive biological event data from a particle analyzer or analysis system 502. The biological event data received from the particle analyzer or analysis system 502 may include flow cytometry event data. Analysis controller 500 is configurable to provide a graphical display of a first graph including the biological event data to display device 506. Analysis controller 500 may be further configured to render regions of interest as gates around the cluster of biological event data displayed by display device 506, for example, overlaying them onto 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 may be used to display particle parameter or saturation detector data.

[0194] The analysis controller 500 can also be configured to display the biological event data inside the door on the display device 506 in a manner different from other events in the biological event data outside the door. For example, the analysis controller 500 can be configured to render the colors of the biological event data inside the door differently from the colors of the biological event data outside the door. The display device 506 can be implemented as a monitor, tablet computer, smartphone, or other electronic device configured to present a graphical interface.

[0195] The analysis controller 500 can be configured to receive a door selection signal from a first input device for identifying 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 on or manipulated via the display device 506 (e.g., by clicking the desired door when the cursor is over it). 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 such embodiments, each input function can be considered an input device. For example, such as... Figure 5 As shown, the mouse 510 may include a right mouse button and a left mouse button, and each button can generate a trigger event.

[0196] Triggering events can cause the analysis controller 500 to change how data is displayed, which parts of the data are actually displayed on the display device 506, and / or provide input for further processing, such as selecting a group of particles of interest for particle sorting.

[0197] In some embodiments, the analysis controller 500 may be configured to detect when the mouse 510 initiates a gate selection. The analysis controller 500 may be further configured to automatically modify the drawing visualization to facilitate the gating process. This modification may be based on the specific distribution of biological event data received by the analysis controller 500.

[0198] 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 be further configured to allow the analysis controller 500 to retrieve biological event data, such as flow cytometry event data.

[0199] Display device 506 can be configured to receive display data from analysis controller 500. The display data may include graphs of biological event data and gates outlining portions of the graphs. Display device 506 can be further configured to change the presented information based on input received from analysis controller 500 and input from particle analyzer 502, storage device 504, keyboard 508, and / or mouse 510.

[0200] In some implementations, the analysis controller 500 may generate a user interface to receive example events for sorting. For example, the user interface may include controls for receiving example events or example images. The example events, images, or example 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.

[0201] 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 described herein. In some embodiments, the particle sorting system 600 is a cell sorting system. Figure 6A As shown, a droplet-forming transducer 602 (e.g., a piezoelectric oscillator) is coupled to a fluid conduit 601, which may be coupled to, include, or be a nozzle 603. Within the fluid conduit 601, a sheath fluid 604 hydrodynamically focuses a sample fluid 606 containing particles 609 into a moving fluid column 608 (e.g., a stream). In the moving fluid column 608, particles 609 (e.g., cells) align in a line across a monitored area 611 (e.g., where laser streams intersect) and are irradiated by a radiation 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.

[0202] In operation, a detection station 614 (e.g., an event detector) identifies when a target particle (or target cell) crosses a monitored 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, a flash charge can be applied to a moving fluid column 608, charging the target droplet, by a timing droplet delay (Δt). The target droplet 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 droplet into a container (e.g., a collection tube or a porous or microporous sample plate) where a pore or micropore may be associated with a specific target droplet. Figure 6A As shown, the droplets can be collected in the discharge container 638.

[0203] A detection system 616 (e.g., a droplet boundary detector) is used to automatically determine the phase of the droplet drive signal as a target particle passes through the monitored area 611. An exemplary droplet boundary detector is described in U.S. Patent No. 7,679,039, which is incorporated herein by reference in its entirety. The detection system 616 allows the instrument to accurately calculate the position of each detected particle in the droplet. The detection system 616 may be fed an amplitude signal 620 and / or a phase signal 618, which in turn are fed (via amplifier 622) an amplitude control circuit 626 and / or a frequency control circuit 624. The amplitude control circuit 626 and / or the frequency control circuit 624, in turn, 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.

[0204] 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 on those events. 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 communicatively coupled, such that event measurements can be collected by one of detection system 616 or detection station 614 and provided to non-collecting elements.

[0205] 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 current-charged wire in the barbs. This generates a droplet stream 610 containing particles 609 for analysis. The particles can be irradiated with one or more light sources (e.g., lasers) to generate light scattering and fluorescence information. This can be achieved through sorting electronics or other detection systems (…). Figure 6B(Not shown in the image) to analyze particle information. Deflection plates 652 and 654 can be independently controlled to attract or repel charged droplets, thereby guiding the droplets to a target collection container (e.g., one of 672, 674, 676, or 678). Figure 6B As shown, deflector plates 652 and 654 can be controlled to guide particles along a first path 662 toward container 674, or along a second path 668 toward container 678. If the particles are not the target (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, for example, via a suction device 670.

[0206] The sorting electronics may include a collection that initiates measurements, receives the fluorescence signal of the particles, and determines how to adjust the deflection plate to sort the particles. Figure 6B An example implementation of the embodiment shown includes the BD FACSAria™ series flow cytometer, commercially available from Becton, Dickinson and Company (Franklin Lakes, NJ).

[0207] Integrated circuit devices

[0208] This disclosure also includes integrated circuit devices programmed to perform the methods described herein, such as those for calculating and applying data signal filters to detect particles in a flowing stream. In some embodiments, the integrated circuit device of interest includes a field-programmable gate array (FPGA). In other embodiments, the integrated circuit device includes an application-specific integrated circuit (ASIC). In still other embodiments, the integrated circuit device includes a complex programmable logic device (CPLD).

[0209] According to some embodiments, the integrated circuit is programmed to determine characteristics of a data signal waveform generated in response to light detected from irradiated particles in a sample of a flowing stream, and to calculate a data signal filter from the determined characteristics of the data signal waveform. In some embodiments, the integrated circuit is programmed to determine a width parameter for the data signal waveform. In some cases, the integrated circuit is programmed to determine one or more of the waveform area, waveform height, and the ratio of waveform area to waveform height. In some cases, the data signal processed by the system has a Gaussian distribution.

[0210] In some embodiments, the integrated circuit is programmed to compute a data filter based on aspects of particles in the flow stream. In some cases, the data signal filter is based on the particle width. In some embodiments, the integrated circuit is programmed to compute a data filter based on parameters of particles in the flow stream with a diameter of 1000 nm or smaller (e.g., diameters from 50 nm to 800 nm).

[0211] In some embodiments, the integrated circuit is programmed to compute a data signal filter that generates a data signal with the maximum signal-to-noise ratio when applied to a data signal from a light detection system. In some cases, the integrated circuit is programmed to match the data signal filter to the waveform of the actual data signal generated in response to detected light. In other cases, the integrated circuit is programmed to compute the data signal filter according to the following formula:

[0212]

[0213] in It is the core of the data signal filter; It is the noise component of the data signal; It is the data signal waveform generated by the optical detection system; It represents the standard deviation. In some cases, the numerator of the data signal filter kernel is a function of the maximum data signal waveform after filtering. In other cases, the denominator of the data signal filter kernel is the noise amplitude of the data signal waveform after filtering.

[0214] In some embodiments, the integrated circuit is programmed to compute a data signal filter as an estimate of the actual data signal waveform. In some cases, the integrated circuit is programmed to compute a linear analog data signal filter based on determined characteristics of the data signal waveform. In some cases, the linear analog data signal filter is a finite impulse response (FIR) filter. In other cases, the linear analog data signal filter is an infinite impulse response (IOR) filter. In some cases, the integrated circuit is programmed to compute a data signal filter from determined characteristics of the data signal waveform, the filter comprising one or more of the following: Butterworth filter, Chebyshev filter, elliptic Caul filter, Bessel filter, Gaussian filter, optimal L-filter, Ringquiz-Ryley filter, ideal filter, and matched filter.

[0215] In some embodiments, the integrated circuit is programmed to apply a data signal filter to a data signal waveform generated by a photodetector system. In these embodiments, the integrated circuit is programmed to generate a data signal waveform in response to detected light and to apply a data signal filter to the generated data signal waveform, wherein the data signal filter is calculated based on determined characteristics of the data signal generated by the photodetector system. In some cases, the integrated circuit is programmed to determine a trigger index for detecting particles in a sample based on the filtered data signal waveform. In some cases, the trigger index is the ratio of the data signal amplitude to the noise component of the data signal waveform. In some embodiments, the noise component is the root mean square value of the noise in the data signal waveform.

[0216] Non-transitory computer-readable storage medium

[0217] This disclosure also includes non-transitory computer-readable storage media containing instructions for implementing the methods of this subject matter. The computer-readable storage medium can be used on one or more computers to enable full or partial automation of a system for implementing the methods described herein. In some embodiments, instructions according to the methods described herein can be encoded in the form of a “program” onto a computer-readable medium, wherein the term “computer-readable medium” as used herein refers to any non-transitory storage medium that participates in providing instructions and data to a computer for execution and processing. Examples of suitable non-transitory storage media include floppy disks, hard disks, optical disks, 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 (NAS), whether these devices are located inside or outside a computer. Files containing information can be “stored” on a computer-readable medium, where “stored” means recording information so that a computer can access and retrieve it later. The computer implementation methods described herein can be executed using programs that can be written in one or more of any number of computer programming languages. These languages ​​include, for example, Python, Java, JavaScript, C, C#, C++, Go, R, Swift, PHP, and many others.

[0218] According to some embodiments, a non-transitory computer-readable storage medium has algorithms for determining the characteristics of a data signal waveform generated in response to light detected from irradiated particles in a sample in a flowing stream, and for calculating a data signal filter from the determined characteristics of the data signal waveform. In some embodiments, the non-transitory computer-readable storage medium includes an algorithm for determining a width parameter of the data signal waveform. In some cases, the non-transitory computer-readable storage medium includes algorithms for determining one or more of a waveform area, a waveform height, and a ratio of waveform area to waveform height. In some cases, the data signal processed by the system has a Gaussian distribution.

[0219] In some embodiments, the non-transitory computer-readable storage medium includes an algorithm for calculating a data filter based on a certain aspect of particles in a flowing stream. In some cases, the data signal filter is based on the width of the particles. In some embodiments, the non-transitory computer-readable storage medium includes an algorithm for calculating parameters of a data filter based on particles in a flowing stream with a diameter of 1000 nm or smaller (e.g., a diameter from 50 nm to 800 nm).

[0220] In some embodiments, the non-transitory computer-readable storage medium includes an algorithm for calculating a data signal filter that generates a data signal with a maximum signal-to-noise ratio when applied to a data signal from a light detection system. In some cases, the non-transitory computer-readable storage medium includes an algorithm for matching the data signal filter to a real data signal waveform generated in response to detected light. In some cases, the non-transitory computer-readable storage medium includes an algorithm for calculating the data signal filter according to the following formula:

[0221]

[0222] in It is the core of the data signal filter; It is the noise component of the data signal; It is the data signal waveform generated by the optical detection system; It represents the standard deviation. In some cases, the numerator of the data signal filter kernel is a function of the maximum data signal waveform after filtering. In other cases, the denominator of the data signal filter kernel is the noise amplitude of the data signal waveform after filtering.

[0223] In some embodiments, the non-transitory computer-readable storage medium includes an algorithm for calculating a data signal filter as an estimate of a real data signal waveform. In some cases, the non-transitory computer-readable storage medium includes an algorithm for calculating a linear analog data signal filter from determined characteristics of the data signal waveform. In some cases, the linear analog data signal filter is a finite impulse response filter. In other cases, the linear analog data signal filter is an infinite impulse response filter. In some cases, the non-transitory computer-readable storage medium includes an algorithm for calculating a data signal filter from determined characteristics of the data signal waveform, the filter comprising one or more of the following: Butterworth filter, Chebyshev filter, elliptic Caul filter, Bessel filter, Gaussian filter, optimal L-filter, Ringquiz-Ryley filter, ideal filter, and matched filter.

[0224] In some embodiments, the non-transitory computer-readable storage medium includes an algorithm for applying a data signal filter to a data signal waveform generated by an optical detection system. In these embodiments, the non-transitory computer-readable storage medium includes an algorithm for generating a data signal waveform in response to detected light and applying a data signal filter to the generated data signal waveform, wherein the data signal filter is calculated based on determined characteristics of the data signal generated by the optical detection system. In some cases, the non-transitory computer-readable storage medium includes an algorithm for determining a trigger index for detecting sample particles based on the filtered data signal waveform. In some cases, the trigger index is the ratio of the data signal amplitude to a noise component of the data signal waveform. In some cases, the noise component is the root mean square value of the noise in the data signal waveform.

[0225] In some cases, non-transitory computer-readable storage media include instructions for generating sorting decisions based on particles identified in a sample.

[0226] Non-transitory computer-readable storage media may be used on one or more computer systems having a display and operator input devices. Operator input devices may be, for example, a keyboard, mouse, etc. The processing module includes a processor that can access memory storing instructions thereon for performing the steps of the methods of this subject. The processing module may include an operating system, a graphical user interface (GUI) controller, system memory, memory storage devices, input / output controllers, caches, data backup units, and many other devices. The processor may be a commercially available processor, or may be one of other existing or upcoming processors. The processor executes the operating system, which interfaces with firmware and hardware in a well-known manner and assists the processor in coordinating and executing the functions of various computer programs written in various programming languages ​​(such as those described above), other high-level or low-level languages, and combinations thereof, as is known in the art. The operating system typically cooperates with the processor to coordinate and execute the functions of other components of the computer. The operating system also provides scheduling, input / output control, file and data management, memory management, communication control, and related services, all of which are based on known technologies.

[0227] kit

[0228] This disclosure also includes kits, which contain one or more integrated circuits described herein. In some embodiments, the kit may also contain programming for the system of this subject matter, such as in the form of a computer-readable medium (e.g., a flash drive, USB storage device, optical disc, DVD, Blu-ray disc, etc.), or instructions for downloading the program from an Internet Protocol or cloud server. The kit may also contain instructions for implementing the methods of this subject matter. These instructions may exist in various forms within the subject matter kit, including one or more forms. These instructions may exist as information printed on a suitable medium or substrate, such as one or more sheets of paper containing printed information, in kit packaging, in packaging instructions, etc. Another form of these instructions is a computer-readable medium on which information is recorded, such as a floppy disk, optical disc (CD), portable flash drive, etc. Yet another form of these instructions may be a website address that can be used via the Internet to access information on a remote site.

[0229] practicality

[0230] The systems, methods, and computer systems described herein can be used in a variety of applications where it is necessary to analyze and sort the particulate composition of samples in a fluid medium, such as biological samples. In some embodiments, the systems and methods described herein can be used for flow cytometry characterization of biological samples labeled with fluorescent tags. In other embodiments, these systems and methods are used for spectral analysis of emitted light. Furthermore, the systems and methods described herein can also be used to enhance the available signal of light acquired from a sample (e.g., in a flowing stream). In some cases, this disclosure can be used to enhance the measurement of light acquired from a sample illuminated in a flowing stream in a flow cytometer. Embodiments of this disclosure may be used to provide a flow cytometer with higher cell sorting accuracy, enhanced particle collection, particle charging efficiency, more precise particle charging, and enhanced particle deflection during cell sorting.

[0231] Embodiments of this disclosure can also be used for applications where cells prepared from biological samples are desired for research, laboratory testing, or treatment. In some embodiments, the methods and apparatus of this subject matter can conveniently obtain individual cells from a target fluid or tissue biological sample. For example, the methods and systems of this subject matter can conveniently obtain 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 conveniently obtain cells from fluid or tissue samples for therapeutic purposes. Compared to conventional flow cytometry systems, the methods and apparatus of this disclosure can isolate and collect cells from biological samples (e.g., organs, tissues, tissue fragments, body fluids) with greater efficiency and lower cost.

[0232] Notwithstanding the appended claims, this disclosure is also defined by the following provisions:

[0233] 1. A method for determining a data signal filter for detecting particles in a particle analyzer, the method comprising:

[0234] Use a light detection system to detect light from particles in a flowing stream;

[0235] A data signal waveform is generated in response to light detected from particles in the flowing stream;

[0236] Determine the characteristics of the data signal waveform; and

[0237] Calculate the data signal filter from the defined characteristics of the data signal waveform.

[0238] 2. The method according to Clause 1, wherein the characteristics of the data signal waveform include the width parameter of the data signal waveform.

[0239] 3. The method according to Clause 2, wherein the width parameter includes the ratio of waveform area to waveform height.

[0240] 4. The method according to any one of Clauses 1 to 3, wherein the data signal waveform comprises a Gaussian distribution.

[0241] 5. The method according to any one of Clauses 1-4, wherein the calculated data signal filter, when applied to the data signal from the optical detection system, generates a data signal with the maximum signal-to-noise ratio.

[0242] 6. The method according to any one of clauses 1 to 5, wherein the data signal filter is calculated according to the following formula:

[0243]

[0244] in, It is the core of the data signal filter;

[0245] It is the noise component of the data signal;

[0246] It is the data signal waveform generated by the optical detection system; and

[0247] That is the standard deviation.

[0248] 7. The method according to Clause 6, wherein the numerator of the data signal filter kernel is a function of the maximum data signal waveform after filtering with the data signal filter.

[0249] 8. The method according to any one of Clauses 6 to 7, wherein the denominator of the data signal filter kernel is the noise amplitude of the data signal waveform after filtering with the data signal filter.

[0250] 9. The method according to any one of Clauses 1 to 8, wherein the method comprises calculating a linear analog data signal filter from determined characteristics of the data signal waveform.

[0251] 10. The method according to Clause 9, wherein the linear analog data signal filter includes a finite impulse response filter.

[0252] 11. The method according to Clause 9, wherein the linear analog data signal filter includes an infinite impulse response filter.

[0253] 12. The method according to any one of Clauses 9-11, wherein the method comprises calculating a data signal filter from determined characteristics of the data signal waveform, the data signal filter being selected from the group consisting of Butterworth filters, Chebyshev filters, elliptic Caul filters, Bessel filters, Gaussian filters, optimal L-filters, Linkütz-Ryley filters, ideal filters, and matched filters.

[0254] 13. The method according to any one of clauses 1 to 12, wherein the data signal filter is based on the aspect of particles.

[0255] 14. The method according to Clause 13, wherein the aspect is the width of the particle.

[0256] 15. The method according to any one of clauses 1-14, wherein the particles are extracellular vesicles.

[0257] 16. The method according to any one of Clauses 13 to 15, wherein the waveform of the generated data signal is independent of the particle size.

[0258] 17. The method according to any one of clauses 1-16, wherein the method further comprises illuminating the sample with a light source.

[0259] 18. The method according to Clause 17, wherein the size of the particles is smaller than the size of the illumination beam of the light source.

[0260] 19. The method according to any one of Clauses 1-18, wherein the method comprises applying a data signal filter to a data signal waveform generated by an optical detection system.

[0261] 20. The method of claim 19, wherein the method further comprises determining a triggering index for detecting particles in a sample based on the waveform of the filtered data signal.

[0262] 21. The method according to Clause 20, wherein the triggering metric includes the ratio of the data signal amplitude to the noise component of the data signal waveform.

[0263] 22. The method according to Clause 21, wherein the noise component includes the root mean square value of the noise of the data signal waveform.

[0264] 23. A method comprising:

[0265] A light detection system is used to detect light from particles in a sample flowing through a stream.

[0266] Generate a data signal waveform in response to detected light; and

[0267] A data signal filter is applied to the generated data signal waveform, wherein the data signal filter is calculated based on the defined characteristics of the data signal generated by the optical detection system.

[0268] 24. The method according to Clause 23, wherein the method further comprises determining a triggering index for detecting particles in a sample based on the filtered data signal waveform.

[0269] 25. The method according to Clause 24, wherein the triggering metric includes the ratio of the data signal amplitude to the noise component of the data signal waveform.

[0270] 26. The method according to Clause 25, wherein the noise component includes the root mean square value of the noise of the data signal waveform.

[0271] 27. The method according to any one of clauses 23 to 26, wherein the data signal filter is based on the aspect of particles.

[0272] 28. The method according to Clause 27, wherein the aspect is the width of the particle.

[0273] 29. The method according to any one of clauses 23-28, wherein the particles comprise extracellular vesicles.

[0274] 30. The method according to any one of clauses 24-28, wherein the particles comprise extracellular vesicles.

[0275] 31. The method according to any one of Clauses 27-29, wherein the waveform of the generated data signal is independent of the particle size.

[0276] 32. The method according to any one of clauses 23-31, wherein the method further comprises illuminating the sample with a light source.

[0277] 33. The method of claim 32, wherein the size of the particle is smaller than the size of the illumination beam of the light source.

[0278] 34. The method according to any one of clauses 23-33, wherein the characteristics of the data signal waveform include a width parameter of the data signal waveform.

[0279] 35. The method according to Clause 34, wherein the width parameter includes the ratio of waveform area to waveform height.

[0280] 36. The method according to any one of clauses 23-35, wherein the data signal waveform comprises a Gaussian distribution.

[0281] 37. The method according to any one of clauses 23-36, wherein the calculated data signal filter generates a data signal waveform with the maximum signal-to-noise ratio.

[0282] 38. The method according to any one of clauses 23-37, wherein the data signal filter is calculated according to the following formula:

[0283]

[0284] in, It is the core of the data signal filter;

[0285] It is the noise component of the data signal;

[0286] It is the data signal waveform generated by the optical detection system; and

[0287] That is the standard deviation.

[0288] 39. The method according to Clause 38, wherein the numerator of the data signal filter kernel is a function of the maximum data signal waveform after filtering with the data signal filter.

[0289] 40. The method according to any one of clauses 38-39, wherein the denominator of the data signal filter kernel is the noise amplitude of the data signal waveform after filtering with the data signal filter.

[0290] 41. The method according to any one of clauses 23-40, wherein the method comprises calculating a linear analog data signal filter from determined characteristics of the data signal waveform.

[0291] 42. The method according to Clause 41, wherein the linear analog data signal filter includes a finite impulse response filter.

[0292] 43. The method according to Clause 42, wherein the linear analog data signal filter includes an infinite impulse response filter.

[0293] 44. The method according to any one of clauses 41-43, wherein the method comprises calculating a data signal filter from determined characteristics of a data signal waveform, the data signal filter being selected from the group consisting of Butterworth filters, Chebyshev filters, elliptic Caul filters, Bessel filters, Gaussian filters, optimal L-filters, Linkütz-Ryley filters, ideal filters, and matched filters.

[0294] 45. A system comprising:

[0295] A light source configured to illuminate particles in a flowing stream;

[0296] An optical detection system comprising multiple photodetectors; and

[0297] A processor includes memory operatively coupled to the processor, wherein the memory includes instructions stored thereon that, when executed by the processor, cause the processor to:

[0298] A data signal waveform is generated in response to light detected from particles in the flowing stream;

[0299] Determine the characteristics of the data signal waveform; and

[0300] Calculate the data signal filter from the defined characteristics of the data signal waveform.

[0301] 46. ​​The system according to Clause 45, wherein the characteristics of the data signal waveform include a width parameter of the data signal waveform.

[0302] 47. The system according to Clause 46, wherein the width parameter includes the ratio of waveform area to waveform height.

[0303] 48. The system according to any one of clauses 45-47, wherein the data signal waveform comprises a Gaussian distribution.

[0304] 49. The system according to any one of clauses 45-48, wherein the calculated data signal filter, when applied to the data signal from the optical detection system, generates a data signal with the maximum signal-to-noise ratio.

[0305] 50. The system according to any one of clauses 45-49, wherein the memory includes instructions for calculating a data signal filter according to the following formula:

[0306]

[0307] in, It is the core of the data signal filter;

[0308] It is the noise component of the data signal;

[0309] It is the data signal waveform generated by the optical detection system; and

[0310] That is the standard deviation.

[0311] 51. The system according to Clause 50, wherein the numerator of the data signal filter kernel is a function of the maximum data signal waveform after filtering with the data signal filter.

[0312] 52. The system according to any one of clauses 50 to 51, wherein the denominator of the data signal filter core is the noise amplitude of the data signal waveform after filtering by the data signal filter.

[0313] 53. The system according to any one of clauses 45-52, wherein the memory includes instructions for calculating a linear analog data signal filter from determined features of the data signal waveform.

[0314] 54. The system according to Clause 53, wherein the linear analog data signal filter includes a finite impulse response filter.

[0315] 55. The system according to Clause 53, wherein the linear analog data signal filter includes an infinite impulse response filter.

[0316] 56. The system according to any one of clauses 53-55, wherein the method comprises calculating a data signal filter from determined characteristics of a data signal waveform, the data signal filter being selected from the group consisting of Butterworth filters, Chebyshev filters, elliptic Caul filters, Bessel filters, Gaussian filters, optimal L-filters, Ringquiz-Ryley filters, ideal filters, and matched filters.

[0317] 57. The system according to any one of clauses 45-56, wherein the data signal filter is based on the aspect of particles.

[0318] 58. The system according to Clause 57, wherein the aspect is the width of the particle.

[0319] 59. The system according to any one of clauses 45-58, wherein the particles are extracellular vesicles.

[0320] 60. The system according to any one of clauses 57-59, wherein the waveform of the generated data signal is independent of particle size.

[0321] 61. The system according to Clause 60, wherein the size of the particles is smaller than the size of the illumination beam of the light source.

[0322] 62. The system according to any one of clauses 45-61, wherein the memory includes instructions for applying a data signal filter to a data signal waveform generated by the optical detection system.

[0323] 63. The system according to Clause 62, wherein the memory includes instructions for determining a trigger index for detecting particles in a sample based on the filtered data signal waveform.

[0324] 64. The system according to Clause 63, wherein the triggering metric includes the ratio of the data signal amplitude to the noise component of the data signal waveform.

[0325] 65. The system according to Clause 64, wherein the noise component includes the root mean square value of the noise of the data signal waveform.

[0326] 66. A system comprising:

[0327] A light source configured to illuminate particles of a sample in a flowing stream;

[0328] An optical detection system comprising multiple photodetectors; and

[0329] A processor, comprising memory operatively coupled to the processor, wherein the memory includes instructions stored thereon that, when executed by the processor, cause the processor to:

[0330] Generate a data signal waveform in response to detected light; and

[0331] A data signal filter is applied to the generated data signal waveform, wherein the data signal filter is calculated based on the defined characteristics of the data signal generated by the optical detection system.

[0332] 67. The system according to Clause 66, wherein the memory includes instructions for determining a trigger index for detecting particles in a sample based on the filtered data signal waveform.

[0333] 68. The system according to Clause 67, wherein the triggering metric includes the ratio of the data signal amplitude to the noise component of the data signal waveform.

[0334] 69. The system according to Clause 68, wherein the noise component includes the root mean square value of the noise of the data signal waveform.

[0335] 70. The system according to any one of clauses 66-69, wherein the diameter of the particles is 1000 nm or less.

[0336] 71. The system according to Clause 27, wherein the diameter of the particles is from 50 nm to 800 nm.

[0337] 72. The system according to any one of clauses 66-71, wherein the particles comprise extracellular vesicles.

[0338] 73. The system according to any one of clauses 71 to 72, wherein the waveform of the generated data signal is independent of particle size.

[0339] 74. The system according to Clause 73, wherein the size of the particles is smaller than the size of the illumination beam of the light source.

[0340] 75. The system according to any one of clauses 66-74, wherein the characteristics of the data signal waveform include a width parameter of the data signal waveform.

[0341] 76. The system according to Clause 75, wherein the width parameter includes the ratio of waveform area to waveform height.

[0342] 77. The system according to any one of clauses 66-76, wherein the data signal waveform comprises a Gaussian distribution.

[0343] 78. The system according to any one of clauses 66-77, wherein the calculated data signal filter generates a data signal waveform with the maximum signal-to-noise ratio.

[0344] 79. The system according to any one of clauses 66-78, wherein the memory includes instructions for calculating a data signal filter according to the following formula:

[0345]

[0346] in, It is the core of the data signal filter;

[0347] It is the noise component of the data signal;

[0348] It is the data signal waveform generated by the optical detection system; and

[0349] That is the standard deviation.

[0350] 80. The system according to Clause 79, wherein the numerator of the data signal filter kernel is a function of the maximum data signal waveform after filtering with the data signal filter.

[0351] 81. The system according to any one of clauses 79-80, wherein the denominator of the data signal filter core is the noise amplitude of the data signal waveform after filtering by the data signal filter.

[0352] 82. The system according to any one of clauses 66-81, wherein the memory includes instructions for calculating a linear analog data signal filter from determined features of the data signal waveform.

[0353] 83. The system according to Clause 82, wherein the linear analog data signal filter includes a finite impulse response filter.

[0354] 84. The system according to any one of clauses 82-83, wherein the linear analog data signal filter comprises an infinite impulse response filter.

[0355] 85. The system according to any one of clauses 82-84, wherein the memory includes instructions for calculating a data signal filter from determined features of a data signal waveform, the data signal filter being selected from the group consisting of Butterworth filters, Chebyshev filters, elliptic Caul filters, Bessel filters, Gaussian filters, optimal L-filters, Ringquiz-Ryley filters, ideal filters, and matched filters.

[0356] 86. An integrated circuit for determining a data signal filter for particle detection in a particle analyzer, wherein the integrated circuit is programmed to:

[0357] Determine the characteristics of the data signal waveform generated in response to light detected from irradiated particles in a sample flowing through a stream; and

[0358] Calculate the data signal filter from the defined characteristics of the data signal waveform.

[0359] 87. The integrated circuit according to Clause 86, wherein the characteristics of the data signal waveform include a width parameter of the data signal waveform.

[0360] 88. The integrated circuit according to Clause 87, wherein the width parameter includes the ratio of waveform area to waveform height.

[0361] 89. The integrated circuit according to any one of clauses 86-88, wherein the data signal waveform comprises a Gaussian distribution.

[0362] 90. The integrated circuit according to any one of clauses 86-89, wherein the integrated circuit is programmed to calculate a data signal filter that generates a data signal waveform with the maximum signal-to-noise ratio.

[0363] 91. The integrated circuit according to any one of clauses 86-90, wherein the integrated circuit is programmed to calculate a data signal filter according to the following formula:

[0364]

[0365] in, It is the core of the data signal filter;

[0366] It is the noise component of the data signal;

[0367] It is the data signal waveform generated by the optical detection system; and

[0368] That is the standard deviation.

[0369] 92. The integrated circuit according to Clause 91, wherein the numerator of the data signal filter core is a function of the maximum data signal waveform after filtering with the data signal filter.

[0370] 93. The integrated circuit according to any one of clauses 91-92, wherein the denominator of the data signal filter core is the noise amplitude of the data signal waveform after filtering by the data signal filter.

[0371] 94. The integrated circuit according to any one of clauses 86-89, wherein the integrated circuit is programmed to calculate a linear analog data signal filter from determined characteristics of a data signal waveform.

[0372] 95. The integrated circuit according to Clause 94, wherein the linear analog data signal filter includes a finite impulse response filter.

[0373] 96. The integrated circuit according to Clause 94, wherein the linear analog data signal filter includes an infinite impulse response filter.

[0374] 97. The integrated circuit according to any one of clauses 94-95, wherein the integrated circuit is programmed to calculate a data signal filter from determined characteristics of a data signal waveform, the data signal filter being selected from the group consisting of Butterworth filters, Chebyshev filters, elliptic Caul filters, Bessel filters, Gaussian filters, optimal L-filters, Ringquiz-Ryley filters, ideal filters, and matched filters.

[0375] 98. The integrated circuit according to any one of clauses 86-97, wherein the integrated circuit is programmed to apply a data signal filter to a data signal waveform generated by a photodetector system.

[0376] 99. The integrated circuit according to Clause 98, wherein the integrated circuit is programmed to determine a trigger index for detecting particles in a sample based on a filtered data signal waveform.

[0377] 100. The integrated circuit according to Clause 99, wherein the triggering indicator includes the ratio of the data signal amplitude to the noise component of the data signal waveform.

[0378] 101. The integrated circuit according to Clause 100, wherein the noise component includes the root mean square value of the noise of the data signal waveform.

[0379] 102. An integrated circuit for applying a data signal filter to detect particles in a sample, wherein the integrated circuit is programmed to apply the data signal filter to a data signal waveform generated in response to light detected from irradiated particles in a sample in a flowing stream, wherein the data signal filter is calculated based on determined characteristics of the data signal generated by a photodetector system.

[0380] 103. The integrated circuit according to Clause 102, wherein the integrated circuit is programmed to determine a trigger index for detecting particles in a sample based on the filtered data signal waveform.

[0381] 104. The integrated circuit according to Clause 103, wherein the triggering indicator includes the ratio of the data signal amplitude to the noise component of the data signal waveform.

[0382] 105. The integrated circuit according to Clause 104, wherein the noise component includes the root mean square value of the noise of the data signal waveform.

[0383] 106. The integrated circuit according to any one of clauses 102-105, wherein the width parameter includes the ratio of waveform area to waveform height.

[0384] 107. The integrated circuit according to Clause 106, wherein the data signal waveform comprises a Gaussian distribution.

[0385] 108. The integrated circuit according to any one of clauses 102-107, wherein the integrated circuit is programmed to calculate a data signal filter that generates a data signal waveform with the maximum signal-to-noise ratio.

[0386] 109. The integrated circuit according to any one of clauses 102-108, wherein the integrated circuit is programmed to calculate a data signal filter according to the following formula:

[0387]

[0388] in, It is the core of the data signal filter;

[0389] It is the noise component of the data signal;

[0390] It is the data signal waveform generated by the optical detection system; and

[0391] That is the standard deviation.

[0392] 110. The integrated circuit according to Clause 109, wherein the numerator of the data signal filter core is a function of the maximum data signal waveform after filtering with the data signal filter.

[0393] 111. The integrated circuit according to any one of clauses 109-110, wherein the denominator of the data signal filter core is the noise amplitude of the data signal waveform after filtering by the data signal filter.

[0394] 112. The integrated circuit according to any one of clauses 102-108, wherein the integrated circuit is programmed to calculate a linear analog data signal filter from determined characteristics of the data signal waveform.

[0395] 113. The integrated circuit according to Clause 112, wherein the linear analog data signal filter includes a finite impulse response filter.

[0396] 114. The integrated circuit according to Clause 112, wherein the linear analog data signal filter includes an infinite impulse response filter.

[0397] 115. The integrated circuit according to any one of clauses 112-114, wherein the memory includes instructions for calculating a data signal filter from determined features of a data signal waveform, the data signal filter being selected from the group consisting of Butterworth filters, Chebyshev filters, elliptic Caul filters, Bessel filters, Gaussian filters, optimal L-filters, Linkütz-Ryley filters, ideal filters, and matched filters.

[0398] 116. A non-transitory computer-readable storage medium for determining a data signal filter for detecting particles in a particle analyzer, wherein the non-transitory computer-readable storage medium includes instructions stored thereon, the instructions being used to:

[0399] Determine the characteristics of the data signal waveform generated in response to light detected from irradiated particles in a sample flowing through a stream; and

[0400] Calculate the data signal filter from the defined characteristics of the data signal waveform.

[0401] 117. The non-transitory computer-readable storage medium as described in Clause 116, wherein the width parameter includes the ratio of waveform area to waveform height.

[0402] 118. The non-transitory computer-readable storage medium as described in Clause 117, wherein the data signal waveform comprises a Gaussian distribution.

[0403] 119. The non-transitory computer-readable storage medium according to any one of Clauses 116-118, wherein the non-transitory computer-readable storage medium includes an algorithm for calculating a data signal filter that generates a data signal waveform with a maximum signal-to-noise ratio.

[0404] 120. A non-transitory computer-readable storage medium according to any one of clauses 116-119, wherein the integrated circuit is programmed to calculate a data signal filter according to the following formula:

[0405]

[0406] in, It is the core of the data signal filter;

[0407] It is the noise component of the data signal;

[0408] It is the data signal waveform generated by the optical detection system; and

[0409] That is the standard deviation.

[0410] 121. The non-transitory computer-readable storage medium as described in Clause 120, wherein the numerator of the data signal filter kernel is a function of the maximum data signal waveform after filtering with the data signal filter.

[0411] 122. The non-transitory computer-readable storage medium according to any one of clauses 120-121, wherein the denominator of the data signal filter core is the noise amplitude of the data signal waveform after filtering with the data signal filter.

[0412] 123. The non-transitory computer-readable storage medium according to any one of clauses 116-122, wherein the non-transitory computer-readable storage medium includes an algorithm for calculating a linear analog data signal filter from determined features of a data signal waveform.

[0413] 124. The non-transitory computer-readable storage medium as described in Clause 123, wherein the linear analog data signal filter includes a finite impulse response filter.

[0414] 125. The non-transitory computer-readable storage medium as described in Clause 123, wherein the linear analog data signal filter includes an infinite impulse response filter.

[0415] 126. The non-transitory computer-readable storage medium according to any one of Clauses 124-125, wherein the non-transitory computer-readable storage medium includes an algorithm for calculating a data signal filter from determined features of a data signal waveform, the data signal filter being selected from the group consisting of Butterworth filters, Chebyshev filters, elliptic Caul filters, Bessel filters, Gaussian filters, optimal L-filters, Ringquiz-Ryley filters, ideal filters, and matched filters.

[0416] 127. The non-transitory computer-readable storage medium according to any one of clauses 116-126, wherein the non-transitory computer-readable storage medium includes an algorithm for applying a data signal filter to a data signal waveform generated by an optical detection system.

[0417] 128. The non-transitory computer-readable storage medium according to Clause 127, wherein the non-transitory computer-readable storage medium includes an algorithm for determining a trigger index for detecting particles in a sample based on a filtered data signal waveform.

[0418] 129. The non-transitory computer-readable storage medium as described in Clause 128, wherein the triggering indicator includes the ratio of the data signal amplitude to the noise component of the data signal waveform.

[0419] 130. The non-transitory computer-readable storage medium as described in Clause 129, wherein the noise component includes the root mean square value of the noise of the data signal waveform.

[0420] 131. A non-transitory computer-readable storage medium for a data signal filter for detecting particles in a particle analyzer, wherein the non-transitory computer-readable storage medium includes an algorithm stored thereon for applying the data signal filter to a data signal waveform generated in response to light detected from irradiated particles in a sample in a flowing stream, wherein the data signal filter is calculated based on determined characteristics of the data signal generated by a photodetector system.

[0421] 132. The non-transitory computer-readable storage medium according to Clause 131, wherein the non-transitory computer-readable storage medium includes an algorithm for determining a trigger index for detecting particles in a sample based on a filtered data signal waveform.

[0422] 133. The non-transitory computer-readable storage medium as described in Clause 132, wherein the triggering indicator includes the ratio of the data signal amplitude to the noise component of the data signal waveform.

[0423] 134. The non-transitory computer-readable storage medium as described in Clause 133, wherein the noise component includes the root mean square value of the noise of the data signal waveform.

[0424] 135. The non-transitory computer-readable storage medium according to any one of clauses 131-134, wherein the width parameter includes the ratio of waveform area to waveform height.

[0425] 136. The non-transitory computer-readable storage medium as described in Clause 135, wherein the data signal waveform comprises a Gaussian distribution.

[0426] 137. The non-transitory computer-readable storage medium according to any one of clauses 131-136, wherein the non-transitory computer-readable storage medium includes an algorithm for calculating a data signal filter that generates a data signal waveform with a maximum signal-to-noise ratio.

[0427] 138. The non-transitory computer-readable storage medium according to any one of clauses 131-137, wherein the non-transitory computer-readable storage medium includes an algorithm for calculating a data signal filter according to the following formula:

[0428]

[0429] in, It is the core of the data signal filter;

[0430] It is the noise component of the data signal;

[0431] It is the data signal waveform generated by the optical detection system; and

[0432] That is the standard deviation.

[0433] 139. The non-transitory computer-readable storage medium as described in Clause 138, wherein the numerator of the data signal filter kernel is a function of the maximum data signal waveform after filtering with the data signal filter.

[0434] 140. The non-transitory computer-readable storage medium according to any one of clauses 138-139, wherein the denominator of the data signal filter core is the noise amplitude of the data signal waveform after filtering with the data signal filter.

[0435] 141. The non-transitory computer-readable storage medium according to any one of clauses 131-140, wherein the non-transitory computer-readable storage medium includes an algorithm for calculating a linear analog data signal filter from determined features of a data signal waveform.

[0436] 142. The non-transitory computer-readable storage medium as described in Clause 141, wherein the linear analog data signal filter includes a finite impulse response filter.

[0437] 143. The non-transitory computer-readable storage medium as described in Clause 141, wherein the linear analog data signal filter includes an infinite impulse response filter.

[0438] 144. The integrated circuit according to any one of clauses 141-143, wherein the memory includes instructions for calculating a data signal filter from determined features of a data signal waveform, the data signal filter being selected from the group consisting of Butterworth filters, Chebyshev filters, elliptic Caul filters, Bessel filters, Gaussian filters, optimal L-filters, Linkütz-Ryley filters, ideal filters, and matched filters.

[0439] Although the invention has been described in detail by way of illustration and example for clarity, it will be readily apparent to those skilled in the art that some changes and modifications can be made to it without departing from the spirit or scope of the appended claims.

[0440] Therefore, the foregoing only illustrates the principles of the invention. It is understood that those skilled in the art will be able to design various arrangements that, while 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 described herein are primarily intended to help the reader understand the principles of the invention and the concepts contributed by the inventors to advance the technology, and should be interpreted as not being limited to these specifically described examples and conditions. Moreover, all statements herein, including the principles, aspects, and embodiments of the invention and their specific examples, are intended to cover their structural and functional equivalents. Furthermore, such equivalents are intended to include both currently known equivalents and those developed in the future, i.e., any elements developed that perform the same function, regardless of structure. Furthermore, nothing disclosed herein is intended to be offered to the public, whether or not such disclosure is expressly recited in the claims.

[0441] 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, reference to 35 USC §112(f) or 35 USC §112(6) is explicitly defined as a limitation in the claims only when the precise phrase “means for…” or the precise phrase “step for…” is used at the beginning of the limitation in the claims; if such a precise phrase is not used in the limitation in the claims, then 35 USC §112(f) or 35 USC §112(6) is not referenced.

Claims

1. A method for determining a data signal filter for detecting particles in a particle analyzer, the method comprising: Use a light detection system to detect light from particles in a flowing stream; A data signal waveform is generated in response to light detected from particles in the flow stream; Determine the characteristics of the data signal waveform; as well as Calculate the data signal filter from the defined characteristics of the data signal waveform.

2. The method according to claim 1, wherein, The characteristics of the data signal waveform include the width parameter of the data signal waveform.

3. The method according to claim 2, wherein, The width parameter includes the ratio of waveform area to waveform height.

4. The method according to any one of claims 1 to 3, wherein, The data signal waveform includes a Gaussian distribution.

5. The method according to any one of claims 1-4, wherein, When the calculated data signal filter is applied to the data signal from the optical detection system, it generates a data signal with the maximum signal-to-noise ratio.

6. The method according to any one of claims 1 to 5, wherein, The data signal filter is calculated according to the following formula: , in, It is the core of the data signal filter; It is the noise component of the data signal; The data signal waveform generated by the optical detection system; and That is the standard deviation.

7. The method according to claim 6, wherein, The numerator of the data signal filter kernel is a function of the maximum data signal waveform after filtering with the data signal filter.

8. The method according to any one of claims 6 to 7, wherein, The denominator of the data signal filter kernel is the noise amplitude of the data signal waveform after being filtered by the data signal filter.

9. The method according to any one of claims 1 to 8, wherein, The method includes calculating a linear analog data signal filter from determined features of the data signal waveform.

10. The method according to any one of claims 1 to 9, wherein, The data signal filter is based on aspects of the particles.

11. The method according to any one of claims 1-10, wherein, The particles are extracellular vesicles.

12. The method according to any one of claims 1 to 11, wherein, The method includes applying the data signal filter to the data signal waveform generated by the optical detection system.

13. A method comprising: A light detection system is used to detect light from particles in a sample flowing through a stream. It generates a data signal waveform in response to detected light; as well as A data signal filter is applied to the generated data signal waveform, wherein the data signal filter is calculated based on determined characteristics of the data signal generated by the optical detection system.

14. A system comprising: A light source configured to illuminate particles in a flowing stream; An optical detection system, which includes multiple photodetectors; as well as A processor, including memory operatively coupled to the processor, wherein the memory includes instructions stored thereon, the instructions causing the processor, when executed by the processor, to: A data signal waveform is generated in response to light detected from particles in the flowing stream; Determine the characteristics of the data signal waveform; and The data signal filter is calculated based on the definite characteristics of the data signal waveform.

15. A system comprising: A light source configured to illuminate particles of a sample in a flowing stream; An optical detection system, which includes multiple photodetectors; as well as A processor, including memory operatively coupled to the processor, wherein the memory includes instructions stored thereon, the instructions causing the processor, when executed by the processor, to: Generate a data signal waveform in response to detected light; and A data signal filter is applied to the generated data signal waveform, wherein the data signal filter is calculated based on the defined characteristics of the data signal generated by the optical detection system.

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