Assessing and enhancing biological analyzer functionality through particle staining

Abstract

Staining functionality of a blood analysis instrument may be assessed using control particles which are stained using the instrument's staining functionality. This may be done using a method which comprises providing a control sample comprising control particles, applying a staining process to result in a stained control sample, capturing images of control samples from the stained control sample, and assessing a staining function using the captured images.

Description

ASSESSING AND ENHANCING BIOLOGICAL ANALYZER FUNCTIONALITYTHROUGH PARTICLE STAININGCROSS REFERENCE TO RELATED APPLICATIONS

[0001] This claims the benefit of, and is related to, U.S. provisional patent application 63 / 651,583 filed with the United States patent office on May 24, 2024, the disclosure of which is hereby incorporated by reference in its entirety.BACKGROUND

[0002] Blood cell analysis is a commonly performed medical test for providing an overview of a patient's health status. A blood sample can be drawn from a patient's body and stored in a test tube containing an anticoagulant to prevent clotting. A whole blood sample normally comprises three major classes of blood cells including red blood cells (erythrocytes), white blood cells (leukocytes) and platelets (thrombocytes). Each class can be further divided into subclasses of members. For example, five major types or subclasses of white blood cells (WBCs) have different shapes and functions. White blood cells may include neutrophils, lymphocytes, monocytes, eosinophils, and basophils. There are also subclasses of the red blood cell types. The appearances of particles in a sample may differ according to pathological conditions, cell maturity and other causes. Red blood cell subclasses may include reticulocytes and nucleated red blood cells.

[0003] To evaluate and document whether an analyzer is able to effectively perform its tasks, such as, but not limited to, analysis of blood samples, it may be provided with a control sample having known characteristics, and the results of analysis by the analyzer compared with what would be expected based on the control samples’ known characteristic(s). Currently, the state of the art uses material that is the same as or similar to blood as a control, for example, using human red blood cells as a control for the detection of red blood cells. However, such approaches have many problems. For example, certain blood based control particles may have a very short shelf life and / or require refrigerated transport or other special handling. These obstacles may beaddressed through fixing cells with fixing chemicals (e.g., an aldehyde formulation such as glutaraldehyde or formaldehyde), but this may cause changes (e.g., decreases in cell membrane permeability) which can render control samples with fixed control particles unsuitable for certain types of assessments. For example, conventional fixation techniques can result in cells being unable to take on stain (or if they were stained before fixation, being stained permanently), thereby rendering a control sample with such fixed cells unsuitable for assessing an analyzer’s staining functionality. As a result, there is a need for improved staining evaluation technology which may not be dependent on the use of control particles, as well as for improved control technology which can allow control samples to be shipped and stored at higher temperatures (e.g., room temperature) and stored for longer periods (e.g., 30 days or more).BRIEF SUMMARY

[0004] The present disclosure relates to technology for evaluating and enhancing analyzer functionality through particle staining. For example, in some aspects the disclosed technology may be used to implement a method which comprises providing a sample comprising particles, applying a staining process to result in a stained sample, obtaining images of particles from the stained sample which are stained in the staining process, and then assessing a staining function of a biological analyzer using the images of particles from the stained sample which are stained in the staining process.

[0005] The disclosed technology may also be implemented in other manners, such as in the form of systems or computer readable media programmed to performed methods such as described above, or control samples which may be used in such methods. Accordingly, the above description of a method which may be implemented based on this disclosure should be understood as being illustrative only, and should not be treated as limiting.BRIEF DESCRIPTION OF THE DRAWINGS

[0006] While the specification concludes with claims which particularly point out and distinctly claim the invention, it is believed the present invention will be better understood from the following description of certain examples taken in conjunction with the accompanying drawings, in which like reference numerals identify the same elements and in which:

[0007] FIG. 1 is a schematic illustration, partly in section and not to scale, showing operational aspects of an exemplary flowcell which may be used in an analyzer configured to capture and analyze images.

[0008] FIG. 2A illustrates a perspective view of an exemplary preparation module for mixing a staining and / or lysing agent with a sample to form a sample mixture, and for incubating the sample mixture, showing the lamination of ferromagnetic sheets to a housing of the preparation module.

[0009] FIG. 2B illustrates a perspective view of the preparation module of FIG. 2A, showing the wrapping of the ferromagnetic sheets to the housing with adhesive tape.

[0010] FIG. 2C illustrates a perspective view of the preparation module of FIG. 2A, showing the winding of a heating coil of the preparation module about the housing.

[0011] FIG. 3 illustrates a method which may be performed to assess staining functionality of a biological analyzer.

[0012] FIG. 4 illustrates acts which may be performed in assessing an analyzer’s staining function.

[0013] FIG. 5 illustrates acts which may be performed in assessing an analyzer’s staining function using absorbance statistics.

[0014] FIG. 6 illustrates steps which may be performed to determine if a particular imaged cell was under-stained.

[0015] FIG. 7 illustrates a potential distribution of cells from a stained sample.

[0016] FIG. 8 illustrates a potential method of using an analyzer’s staining function in analyzing a sample.

[0017] FIG. 9 illustrates a method which may be used to determine optimized channels for subsequent staining assessment.

[0018] The drawings are not intended to be limiting in any way, and it is contemplated that various embodiments of the invention may be carried out in a variety of other ways, including those not necessarily depicted in the drawings. The accompanying drawings incorporated in and forming a part of the specification illustrate several aspects of the present invention, and together with the description serve to explain the principles of the invention; it being understood, however, that this invention is not limited to the precise arrangements shown.DETAILED DESCRIPTION

[0019] The present disclosure relates to evaluating the effectiveness of analyzers. In some aspects, the analyzers may be visual analyzers comprising processors to facilitate automated conversion and / or analysis of images. Such analyzers may be useful, for example, in characterizing particles in biological fluids, such as detecting and quantifying erythrocytes, reticulocytes, nucleated red blood cells, platelets, and white blood cells, including white blood cell differential counting, categorization and subcategorization and analysis. Other similar uses such as characterizing blood cells from other fluids (serum, bone marrow, lavage fluid, effusions, exudates, cerebrospinal fluid, pleural fluid, peritoneal fluid, and amniotic fluid) are also contemplated.

[0020] Turning now to the drawings, FIG. 1 schematically shows an exemplary flowcell 22 which may be used in an analyzer for conveying a sample fluid through a viewing zone 23 of a high optical resolution imaging device 24 (e.g., a camera) in a configuration for imaging microscopic particles in a sample flow stream 32 using digital image processing. Flowcell 22 is coupled to a source 25 of sample fluid which may have been subjected to processing, such as contact with a particle contrast agent composition and heating.Flowcell 22 is also coupled to one or more sources 27 of a particle and / or intracellular organelle alignment liquid (PIO AL) / sheath fluid, such as a clear glycerol solution having a viscosity that is greater than the viscosity of the sample fluid, an example of which is disclosed in U.S. Pat. Nos. 9,316,635 and 10,451,612, the disclosures of which are hereby incorporated by reference in their entirety.

[0021] The sample fluid is injected through a flattened opening at a distal end 28 of a sample feed tube 29, and into the interior of the flow cell 22 at a point where the PIOAL flow has been substantially established resulting in a stable and symmetric laminar flow of the PIOAL around / surrounding (e.g., circumferentially in a circular cross-sectional arrangement, or surrounding a plurality of sides of in a non-circular (e.g., rectangular) cross-sectional arrangement) the ribbon-shaped sample stream. The sample and PIOAL streams may be supplied by precision metering pumps that move the PIOAL with the injected sample fluid along a flowpath that narrows substantially. The PIOAL envelopes and compresses the sample fluid in the zone 21 where the flowpath narrows. Hence, the decrease in flowpath thickness at zone 21 can contribute to a geometric focusing of the sample stream 32. The sample fluid ribbon 32 is enveloped and carried along with the PIOAL downstream of the narrowing zone 21, passing in front of, or otherwise through the viewing zone 23 of, the high optical resolution imaging device 24 where images are collected, for example, using a charge couple device (CCD) 48. In this way, flow imaging is performed where images from the flowing sample stream and the cellular material contained therein are collected. Processor 18 can receive, as input, pixel data from CCD 48. The sample fluid ribbon flows together with the PIOAL to a discharge 33.

[0022] As shown here, the narrowing zone 21 can have a proximal flowpath portion 21a having a proximal thickness PT and a distal flowpath portion 21b having a distal thickness DT, such that distal thickness DT is less than proximal thickness PT. The sample fluid can therefore be injected through the distal end 28 of sample tube 29 at a location that is distal to the proximal portion 21a and proximal to the distal portion 21b. Hence, the sample fluid can enter the PIOAL envelope as the PIOAL stream is compressed by the zone 21. wherein the sample fluidinjection tube has a distal exit port through which sample fluid is injected into flowing sheath fluid, the distal exit port bounded by the decrease in flowpath size of the flow cell.

[0023] The digital high optical resolution imaging device 24 with objective lens 46 is directed along an optical axis that intersects the ribbon-shaped sample stream 32. The relative distance between the objective 46 and the flow cell 33 is variable by operation of a motor drive 54, for resolving and collecting a focused digitized image on a photosensor array. Additional information regarding the construction and operation of an exemplary flow cell such as shown in FIG. 1 is provided in U.S. Patent 9,322,752, entitled “Flow cell Systems and Methods for Particle Analysis in Blood Samples,” filed on March 17, 2014, the disclosure of which is hereby incorporated by reference in its entirety. Descriptions of approaches which may be used for focusing in an imaging system such as shown in FIG. 1 are provided in Published App. No. 2024 / 0357232 titled “Focus Quality Determination through Multi-Layer Processing,” filed on June 11, 2024, U.S. Patent 9,857,361 titled “Flowcell, Sheath fluid, and Autofocus Systems and Methods for Particle Analysis in Urine Samples”, filed on March 17, 2014, U.S. Patent 10,705,008 titled “Autofocus Systems and Methods for Particle Analysis in Blood Samples”, filed on March 17, 2014, U.S. Patent 10,705,011, titled “Dynamic Focus System and Methods”, filed October 5, 2017, and international application W02023 / 150064 titled “Measure Image Quality of Blood Cell Images”, filed January 27, 2023, the disclosures of each of which are hereby incorporated by reference in their entirety.

[0024] In addition to a flowcell such as that shown in FIG. 1, an analyzer which may be used for blood cell analysis may also include additional components, such as a staining and / or lysing component which can be used to prepare a sample for analysis. An example of such a component is provided in FIGS. 2A-2C, which depict a preparation module 400 which may be used to both mix a sample with a staining agent and / or a lysing agent (e.g., a combined staining and lysing agent) and to incubate the sample mixture via heating prior to the cells withing the sample mixture being imaged by a camera such as described in the context of FIG. 1. For example, preparation module 400 may be incorporated in place of the source 25 shown in FIG. 1 or between the source 25 and the sample feed tube 29 shown in FIG. 1, to facilitate mixingof the sample with the staining and / or lysing agent and incubation of the sample mixture prior to capturing of images of the sample by the high optical resolution imaging device 24. The staining and / or lysing agent may include any suitable composition. For example, it may be composed in accordance with any one or more teachings of U.S. Pat. No. 9,279,750, entitled “Method and Composition for Staining and Sample Processing,” issued on March 8, 2016, the disclosure of which is hereby incorporated by reference in its entirety; and / or U.S. Pat. No. 9,322,753, entitled “Method and Composition for Staining and Processing a Urine Sample,” issued on April 26, 2016, the disclosure of which is hereby incorporated by reference in its entirety; and / or US Pub. No. 2021 / 0108994, entitled “Method and Composition for Staining and Sample Processing,” published on April. 15, 2021, the disclosure of which is hereby incorporated by reference in its entirety.

[0025] In the example of FIGS. 2A-2C, the preparation module 400 includes a housing 410, a pair of ferromagnetic sheets 412, and a heater in the form of a heating coil 414 (FIG. 2C). Heating coil 414 can comprise a resistive coil, or alternatively an inductive coil. As best shown in FIG. 2A, the housing 410 includes a plurality of (e.g., four) sidewalls 420 which collectively define an interior chamber 422 (also referred to as a sample reservoir) for receiving the agent and the sample, mixing the agent and the sample to form a sample mixture, and incubating the sample mixture. The housing 410 also includes a top wall 424 and a port 426 extending through the top wall 424 to the interior chamber 422. The port 426 may permit a stain / lyse dispenser (not shown) to deliver the agent to the interior chamber 422, and / or may permit a sample dispenser (not shown) to deliver the sample to the interior chamber 422 so as to be added to the agent.

[0026] The housing 410 may comprise a metallic material having relatively high thermal conductivity, such as aluminum, in order to promote uniform heating of the housing 410 and likewise uniform heating of the contents of the interior chamber 422. In the example of FIGS. 2A-2C, the sidewalls 420 of the housing 410 are laminated with respective ferromagnetic sheets 412 to improve the efficiency of the heating (e.g., resistive heating, or alternatively inductive heating) performed by preparation module 400 (e.g., due to the relatively low ferromagnetic properties of aluminum). More particularly, each ferromagnetic sheet 412 is secured to theouter surfaces of a corresponding pair of sidewalls 420. It will be appreciated that any suitable number of ferromagnetic sheets 412 may be used to laminate the sidewalls 420. In the example of FIGS. 2A-2C a thermally conductive compound 430 is deposited on the outer surfaces of the sidewalls 420 for adhering the ferromagnetic sheets 412 to the sidewalls 420. As best shown in FIG. 2B, an adhesive tape 432 is tightly wrapped about the ferromagnetic sheets 412 to securely engage the inner surfaces of the ferromagnetic sheets 412 with the outer surfaces of the sidewalls 420.

[0027] As best shown in FIG. 2C, the heating coil 414 includes a wire 440 wound about the sidewalls 420 of the housing 410 (and about ferromagnetic sheets 412). The wire 440 may comprise a metallic material having relatively high electrical conductivity, such as copper. The wire 440 may have any suitable cross-sectional area and / or thickness, and may be wound to define any suitable number of turns for the heating coil 414. The heating coil 414 may functions as an inductor or induction coil, and is operatively coupled to a power unit 450, which may be configured to drive the heating coil 414 to a frequency at which the heating coil 414 behaves as a resonant circuit that under excitation produces an alternating current thereby producing an alternating magnetic field at or near the heating coil 414. This field may generate an electromagnetic field (EMF) on the outer surfaces of the sidewalls 420, which may in turn cause an alternating current. This current, in conjunction with the resistivity of the housing 410, may yield power dissipation and heat up the outer surfaces of the sidewalls 420. Such heat may be transferred to the contents of the chamber 422, such as the agent and / or the sample. It will be appreciated that such induction heating may be performed using relatively low input power, and / or may achieve homogeneous heating of the contents of the chamber 422 and thereby improve staining and / or lysing performance. In this regard, exciting the circuit at the resonant frequency may deliver maximum power, and exciting the circuit at an increasing frequency may effectively adjust the power delivery. Alternatively, in some cases a resistive heater / resi stance heating coil may be used for the heater coil 414.

[0028] In some cases, a preparation module 400 such as shown in FIGS. 2A-2C may include a temperature sensor such as a thermistor (not shown) which is configured to continuously sensethe temperature of the contents of the chamber 422. The temperature sensor may be configured to send feedback signals indicative of the sensed temperatures to a controller (not shown) which may in turn be configured to send control signals to the power unit 450 for selectively driving the heating coil 414. In this manner, the controller may cease heating of the contents of the chamber 422 upon reaching a threshold temperature. In one example, the controller utilizes heating control algorithms and the feedback signals are incorporated into elements of the algorithms or computer-driven instructions provided to the power unit 450 and / or heating coil 414 to optimally regulate temperature. In some embodiments, the controller may be configured to send control signals to a maintenance heater (not shown) for maintaining the contents of the chamber 422 at the threshold temperature.

[0029] In some analyzers which may be assessed using the disclosed technology, there may be a plurality of preparation modules, each utilizing the structure of FIGS. 2A-2C (i.e., a plurality of structural elements 400). In this way, a plurality of samples can be stained, incubated, or otherwise prepared at a similar time. In some cases, each staining module may have its own unique heating element. Similarly, in some case, a preparation module may have a plurality of chambers 422, each capable of receiving a sample, and a common heating structure connected to the entire module (e.g., a single housing 410 with a plurality of chambers 422 and a common heating coil 414 surrounding housing 410). Other configurations for preparing a sample for analysis, such as those described in U.S. published patent application 2024- 0027310, filed on July 21, 2023 for “Biological Sample Staining Module and Biological Analysis Systems And Methods,” the disclosure of which is incorporated by reference in its entirely, may also be used either in addition to, or in combination with, the preparation module of FIGS. 2A-2C. Accordingly, the above discussion of components which may be used for staining and / or lysing a sample should be understood as being illustrative only, and should not be treated as limiting.

[0030] To assess staining functionality of an analyzer which includes components such as described in the context of FIGS. 1 and 2A-2C the disclosed technology may be used to implement a method such as illustrated in FIG. 3. As shown in that figure, assessing staining functionalitymay begin with providing 301 a sample comprising particles. This may be done by, for example, loading a control sample into the analyzer and initiating a control run in which the control sample would be processed to provide data that could be used to assess the analyzer’s performance. However, the method of FIG. 3 may also be used with non-control samples, such as a whole blood sample being analyzed for the purpose of diagnosing a patient.

[0031] The following disclosure shall discuss control particle compositions which are used as part of a control sample. In some examples, the terms: a) “soft fixed” and “partially stabilized” can be used synonymously, b) “hard fixed” and “fully stabilized” can be used synonymously, and c) “unfixed,” “not stabilized,” and “unstabilized” can be used synonymously - where element a) refers to particles or cells that are exposed to a limited amount of fixative agent so as to still retain some native cellular characteristics (such as ability to uptake stain) element b) refers to particles or cells that are exposed to a greater amount of fixative agent so as to limit some native cellular characteristics (such as inability to uptake stain), and element c) refers to particles or cells that are either not exposed to any fixative agent or exposed to a limited amount of fixative agent but still retain substantial native cell characteristics (such as shrinkage or crenation when kept at room temperature, or shrinking when not stored in a refrigerated state). It should be understood that, while there are examples set forth here using the terminology of fixation, methods employing fixation can be replaced with stabilization in such examples, and the converse is also true.

[0032] In some examples, a control sample may require refrigeration to maintain cell integrity for certain analytical control processes (e.g., control processes that require size such as volumetric information, or morphological-related information). In some examples, at least a portion of the control sample does not require refrigeration because the control procedure relates to a parameter (e.g., count) where in-depth data such as size, volume, or morphological related information is not needed. Other examples may involve stabilization of the biological control such that refrigeration is not required (e.g., the biological controls can be kept at room temperature).

[0033] Stabilization can involve techniques to keep morphological features of control parti cles / cells intact for an extended period of time, particularly at room temperature. For example, stabilization of control particles at room temperature may be maintained for days, for at least a week or for longer than a week, or for as long as a month, or for a month or longer. Such techniques would utilize one or more stabilization agents during the preparation process to help stabilize the cells. In some examples, stabilization involves utilizing a stabilization agent which comprises nourishing media during the control cell preparation process to help stabilize the cells by expanding the timeframe that degradation of the cells occurs, or other techniques known to one skilled in the art. By example, suitable stabilizing agents can be an aqueous solution including a cell nutrient (e.g., lactose or AMP) and contain one or more of the following: a cell nutrient (e.g., lactose, AMP), a fungicide (e.g., methyl paraben, ethyl paraben, propyl paraben), an antimicrobial (e.g., kanamycin sulfate, neomycin sulfate, sodium penicillin, gentamicin sulfate), a surfactant (e.g., Pluronic F60, Pluronic 25R8, Pluronic F127, Kolliphor P188), a plasma protein (e.g., albumin, lipoproteins, globulins, fibrinogens and mixtures thereof), a buffer (e.g., citrate, EDTA), an agent to maintain tonicity (potassium chloride, sodium phosphate monobasic) and combinations thereof.

[0034] In some examples, stabilization utilizes a fixation process and a fixative agent, wherein cells are exposed to a fixative agent (e.g., an aldehyde, such as glutaraldehyde, formaldehyde, and the like) which chemically cross-links the cell membrane to stabilize it. Additional information on stabilization and stabilization agents can be found in, for example: US 7,393,688, US 4,213,876, US 4,299,726, US 6,569,682, US 5320,964, and US 4,358,394, the contents of which are hereby incorporated by reference in their entirety. \

[0035] A sample which may be provided 301 in such a method may comprise blood derived control particles, for example, human cells or animal derived analogs of human cells which have been fixed with a fixative agent - examples include aldehyde agents such as glutaraldehyde and formaldehyde, and can include any fixative agent known to one of ordinary skill in the art. However, to facilitate the assessment of an analyzer’s staining functionality while avoiding the need for refrigerated storage and transport, blood derived control particles used inimplementing the disclosed technology may be soft fixed or partially stabilized, rather than subjected to fixation used in conventional control creation. Specifically, in this example, the soft fixed control particles may be control particles which are subjected to only partial or reduced fixation so that they can still uptake the stain used by the analyzer in its preparation process. For example, in the case of fixation with glutaraldehyde, if a blood derived control particle were to be conventionally fixed using a 2-6% glutaraldehyde solution, then that blood derived control particle may be soft fixed using a solution with a glutaraldehyde concentration of 1% or less.

[0036] While a sample which may be provided 301 in a method such as shown in FIG. 3 may include soft fixed or partially stabilized blood derived control particles, it should be understood that methods such as shown in FIG. 3 are not limited to samples which include only such soft fixed particles. For instance, in some cases, a control sample may also include blood derived control particles which are hard fixed or fully stabilized - e.g. fixed so that they are no longer able to uptake the stain used in sample preparation. These hard fixed particles may be used for assessing different features of the analyzer than the soft fixed particles (e.g., soft fixed particles may be used in assessing the analyzer’s ability to prepare a sample, while the hard fixed particles could be used in assessing the analyzer’ s ability to determine a cell’ s volume), though in some cases hard and soft fixed particles may be used together in assessing particular features (e.g., hard and soft fixed particles may be used together in assessing the analyzer’s ability to prepare samples). In another example, hard fixed or fully stabilized cells can be used to act as a control or analogue for a pre-stained white blood cells, for example, the cells can be stained then exposed to a fixative agent to retain the stained state and then act as a control or analogue for a specific stained white blood cell type.

[0037] It is also possible that a control sample may include blood derived control particles which are not fixed or stabilized (e.g., not exposed to a fixative agent) at all. For example, in some cases a control sample may include non-fixed human red blood cells (RBCs) and / or hemoglobin (HGB) which may be used to assess the analyzer’s ability to enumerate RBCs and / or HGB (e.g., the ability to provide an RBC count and / or HGB level), assuming such enumeration wasperformed in a manner which would not be impacted by the type of morphological changes associated with room temperature storage (e.g., shrinking over time without refrigeration). Thus, while a control sample based on this disclosure may consist of soft fixed blood derived particles, other types of control samples (e.g., a control sample comprising soft fixed human white blood cells or soft fixed animal cells which are analogous to human white blood cells, along with unfixed human red blood cells and / or hemoglobin) are also possible, and so the exemplary control particles described above should be understood as being illustrative only, and should not be treated as limiting.

[0038] While control formulations are used with imaging systems, currently available control formulations generally require refrigeration, which can introduce logistical challenges and added cost. Thus, a shelf-stable control formulation is desired. Disclosed is a roomtemperature stable control particle formulation for use in blood imaging analyzers. The disclosed control particle formulations may be used with the disclosed blood imaging platforms for accurate cell identification and quality control across a range of blood cell types.

[0039] In aspects, the room-temperature stable control formulations comprise a mixture of biological particles that serve as analogs for various blood cell types, including human red blood cells (RBCs), human white blood cells (WBCs), human nucleated red blood cells (NRBCs), and human platelets. The room-temperature stable control formulations may be used in conjunction with the disclosed analyzers to identify cells in a blood sample obtained from an individual. In aspects, the analogs of the room -temperature stable control formulation are fixed using a chemical agent such as glutaraldehyde. Fixation of the analog preserves morphology and staining characteristics, enabling long-term storage without refrigeration.

[0040] In aspects, the room-temperature stable control particle formulation for a blood imaging analyzer comprises a plurality of white blood cell analogs. In aspects, each of the plurality of white blood cell analogs represents a white blood cell subtype. In aspects, each of the white blood cell analogs comprises a biological particle exposed to a fixative agent, wherein at least one of the plurality of white blood cell analogs is capable of receiving astaining composition. The plurality of white blood cell analogs may comprise a first white blood cell subtype, a second white blood cell subtype, a third white blood cell subtype, and a fourth white blood cell subtype. For example, in aspects, the first white blood cell subtype is a neutrophil, the second white blood cell subtype is a lymphocyte, the third white blood cell subtype is a monocyte, and the fourth white blood cell subtype is an eosinophil.

[0041] In aspects, the room-temperature stable control particle formulation for a blood imaging analyzer may further comprise a plurality of red blood cell analogs, and a plurality of platelet analogs.

[0042] In aspects, at least a portion of the room-temperature stable control particle formulation comprises fixed animal cells, in which each fixed animal cell is selected or engineered to mimic a specific blood cell subtype. In further aspects, at least a portion of the room-temperature stable control particle formulation comprises animal cells that have not been fixed. In further aspects, the room-temperature stable control particle formulation comprises a mixture of cell analogs comprising cells that are not fixed, fixed and / or partially fixed.

[0043] Cell analogs may be obtained via exposure of an animal cell to a fixation solution. Fixation may be achieved via contact of the animal cells with one or more treatment solutions. In one aspect, the treatment solution is a glutaraldehyde-buffered solution. In one aspect, the treatment solution is an isotonic glutaraldehyde solution. In one aspect, the treatment solution is a hypotonic glutaraldehyde solution. In one aspect, the treatment solution is, sequentially, at least two of an isotonic glutaraldehyde solution, a hypertonic glutaraldehyde solution and a hypotonic glutaraldehyde solution. In further aspects, a second treatment solution comprising a surfactant (for example, Ecosurf EH-0, Tergitol 15-S-9, Triton X-100, Igepal CA-630, Arquad 2C-75, or the like) can be used.

[0044] The fixation parameters (e.g., concentration, duration, osmolarity) are selected based on the desired analog to be obtained. Fixation can include one or more of exposure of a cell to a treatment solution selected from an isotonic glutaraldehyde solution, a hypotonic glutaraldehyde solution, or a hypertonic glutaraldehyde solution for a period of time of fromabout two hours to about 36 hours, or about 3 hours to 24 hours, or about 4 hours to about 18 hours, or about 5 hours to about 12 hours. In further aspects, fixation can include exposure of a cell, sequentially, to one or more of an isotonic glutaraldehyde solution, a hypotonic glutaraldehyde solution, and / or a hypertonic glutaraldehyde solution, the exposure periods being, individually, or collectively, for a period of time of from about two hours to about 36 hours, or about 3 hours to 24 hours, or about 4 hours to about 18 hours, or about 5 hours to about 12 hours. The duration of the contact with the fixation solution is dependent on the desired cell type that the analog will be used for. Following the contact with the treatment solution, a second treatment can be carried out. In aspects, the second treatment comprises contacting the cell to a surfactant, for example, Ecosurf EH-0, Tergitol 15-S-9, Triton X-100, Igepal CA-630, Arquad 2C-75, or the like, for further differentiation of the analogs. In aspects, the surfactant treatment is conducted at a temperature of about X°C to Y°C, for a duration of about X minutes to Y hours, with gentle agitation (e.g., 100-300 rpm). The treatment solution may be buffered to a pH of about 6.8 to 7.4 to maintain cell integrity. In a further aspect, any of the aforementioned treatment solutions can comprise cholesterol.

[0045] By way of example, the analogs of the room-temperature control formulation may be obtained as follows: a first animal cell is fixed in a hypertonic glutaraldehyde fixation solution sufficient to produce an analog cell that corresponds to a first human cell type. In aspects, the same animal cell type is fixed in a hypotonic glutaraldehyde fixation solution further comprising cholesterol to produce an analog cell that corresponds to a second human cell type. The resulting room-temperature control formulation, in this exemplary aspect, comprises two different analogs corresponding to two different human cell types due to the different treatment conditions, but which are derived from the same animal cell type. Thus, in aspects, the same cell type from a given animal can be modified via contact with different fixation solutions sufficient to cause the animal cell to form a blood cell analog that corresponds to a cell type in a human sample. Due to the fixation treatment, the resulting analogs are stable at room temperature.

[0046] Further by way of example, in general, the cell analogs are obtained via collection of blood from a selected animal species in an anticoagulant infused container. Whole blood is centrifuged, and the top layer (buffy coat) is removed. The cells are then washed with a buffered isotonic solution (such as PBS). The wash steps may vary, and the determination of sufficiency, duration, and number of wash steps will be readily determined by one of ordinary skill in the art. The cells are then resuspended in a fixation solution as described above (e.g., a glutaraldehyde solution with or without cholesterol), and incubated for a first treatment period. The first treatment period alters the cell characteristics from a natural value to a target value. Fixed cells are then separated from the treatment solution by centrifugation or gravity and washed, using a buffered isotonic solution. Initially treated cells may be further modified with a different treatment solution (e.g., surfactant) as described above. Multiple cell analogs may be combined and stored as a single room-temperature stable control formulation.

[0047] In aspects, the animal cell used to form the cell analog is selected from one or more of a goat cell, sheep cell, turkey cell, goose cell, rooster cell, emu cell, ostrich cell, or human cell. For example, the animal cell may be selected from goat red blood cell, sheep red blood cell, turkey red blood cell, goose red blood cell, rooster red blood cell, emu red blood cell, ostrich red blood cell or human red blood cell. The animal cell may be modified, via fixation, to serve as an analog to a unique blood cell type selected from a red blood cell, platelet, eosinophil, neutrophil, monocyte, lymphocyte, nucleated red blood cell (NRBC), or reticulocyte. Each cell type is treated with a diverse process to create a cell analog that can be differentiated from other cell types. In aspects, the room-temperature stable control formulation comprises a cell that serves as an analog for reticulocytes and as an anchor for determining mean corpuscular volume (MCV). Because human RBCs swell over time at room temperature, human RBCs are used primarily for hemoglobin quantification and RBC count. The analog, being fixed and size-stable, provide a reliable reference for MCV calculations, enabling the analyzer to report high, low, and normal MCV values

[0048] In aspects, certain blood cell types are not directly represented by analogs. Rather, rare subtypes such as basophils or immature granulocytes may be inferred throughmathematical transformations from more abundant analog populations (e.g., neutrophils), which simplifies the formulation while maintaining diagnostic utility. In aspects, the roomtemperature stable control formulation does not contain an analog for basophils or immature granulocytes. Rare subtypes may be inferred through mathematical transformation from more abundant cell types such as neutrophils.

[0049] In further aspects, an animal-derived cell may be used as an analog for reticulocytes and as an anchor for mean corpuscular volume (MCV) determination. Because human RBCs swell over time at room temperature, they are used primarily for hemoglobin quantification and RBC count. An animal cell analog that is fixed and size-stable is used to provide a reliable reference for MCV calculations, allowing the analyzer to report MCV values.

[0050] In further aspects, the room-temperature stable control formulation may be provided in the form of a kit, which comprises, in a room-temperature stable solution, a plurality of white blood cell analogs, each representing a white blood cells subtype, and a plurality of red blood cell analogs, each representing a red blood cell type, and a plurality of platelet analogs.

[0051] Whatever type of sample is provided 301, in the method of FIG. 3, after the sample is provided 301, a staining process (e g., as described in the context of FIGS. 2A-2C) may be applied 302 to the sample, thereby providing a stained sample. Images of particles from the stained sample which are stained in the staining process may then be obtained 303, and those images may be used in assessing 304 a staining function of the biological analyzer (e.g., to determine whether to indicate the staining function of the analyzer requires servicing, and / or to determine if a sample result should be invalidated in the case of a whole blood sample or other patient sample). This assessment 304 may be done, for example, using an artificial intelligence model (e.g., a model comprising one or more convolution layers connecting to a dense network with one or more output nodes corresponding to potential assessment results, such as pass / fail, levels on a 1-5 scale, or a number between 0 and 1) trained to take images of stained control particles as input and provide the assessment result as an output. However,other approaches to these assessments are also possible. For example, in some cases the images may be analyzed to generate masks for isolating cells or various portions of the cells (e.g., the nucleus) so that characteristics of the cells and / or portions of the cells could be used for assigning the imaged cells to clusters corresponding to different populations (e.g., a neutrophil cluster, a basophil cluster, etc ). The actual characteristics of these clusters could then be compared with the characteristics the clusters would be expected to have if the staining was functioning properly. For instance, if the clusters had lower blueness values than expected, then this could be treated as indicating that the analyzer’s staining module was not operating as expected. As yet another example, in some cases, a control sample would include both soft fixed particles that would be stained in the process of FIG. 3, as well as particles which are stained in advance and then hard fixed, and the assessment 304 may comprise clustering the particles based on stain intensity (e g., blueness) and determining if the soft fixed cells could be identified as a cluster whose mean intensity was different enough from that of the hard fixed pre-stained cells as to indicate that the analyzer’s staining functionality was not operating as intended. Other approaches to image analysis based assessment of an instrument’s performance characteristics, such as described in international patent application WO2024 / 138139, filed December 22, 2023 for “Population Based Cell Classification,” the disclosure of which is hereby incorporated by reference in its entirety, are also possible and may be used in some implementations.

[0052] Using a method such as described, a control sample comprising soft fixed (and potentially hard fixed and / or unfixed) blood derived control particles may be used to assess a biological analyzer’s staining functionality, even after being stored in much more relaxed conditions (e.g., for a week or more in an unrefrigerated environment at room temperature, rather than in a refrigerated environment kept at no more than 8° Celsius). This can significantly simplify the identification if issues with such instruments, so that those issues can be remediated before they have the opportunity to impact the processing of patient samples.

[0053] Other approaches to assessing 304 an analyzer’s staining function are also possible. For example, as shown in FIG. 4, in some cases assessing 304 the staining function of a biologicalanalyzer may include determining a plurality of absorbance values by, for each of the stained particle images, calculating 401 an incident light intensity based on light intensities of a plurality of non-particle pixels to remove luminance non-uniformity across images, and then using that incident light intensity to determine a set of absorbance values for a cell depicted in that image. For example, in the case of a patch image depicting an individual cell, calculating 401 the incident light intensity for that image may be done by calculating the mean or median intensities of pixels on the border of the image. This incident light intensity can then be used to determine the absorbance of each pixel in the image using a calculation such as equation 1, below.AP= logZ(IOPX)IpEquation 1In that equation Apis the absorbance at pixel p, I0pis the intensity of incident light at pixel p (i.e., the value calculated 401 in the preceding step), and Ipis the value of transmitted light at pixel p.

[0054] With the absorbance values determined 402, those values may be used to assess 403 the staining functionality of the analyzer. As shown in FIG. 5, this may be done by generating 501 one or more absorbance statistics, and evaluating 502 the staining function of the analyzer using those statistics (e.g., comparing one of the statistics with a threshold which had been previously established as distinguishing analyzers whose staining function was working properly from analyzers which were under-staining samples). Examples of statistics which may be generated 501 for this purpose include those described below in table 1.Table 1

[0055] Other statistics which may be generated 501 in some cases could include color channel specific statistics. For example, in some cases statistics such as ABceii red (representing the total absorbance of a cell in the red color channel) and / or ABN2nucieus green (representing the area normalized value of the total absorbance in the green color channel of pixels depicting the cell nucleus) may be calculated. It is also possible that, in addition to cell level statistics such as those from table 1, there may also be sample level statistics generated 501 in some cases. Forinstance, in some cases, the total, mean, median, 90thpercentile, standard deviation, variance or other population statistics may be calculated for one or more of the cell level statistics (e.g., a MeanABcvtopiasm statistic may be calculated, representing the average value of total absorbance of cytoplasm pixels across the cell population). Such population statistics may be for an entire cell population (e.g., all white blood cells), or may be for specific subpopulations of cells (e.g., there may be population statistics calculated specifically for white blood cell subtypes such as lymphocytes, monocytes, neutrophils, eosinophils and basophils).

[0056] Other types of statistics may also be generated in some cases. To illustrate, consider FIG. 6, which illustrates steps which may be performed to determine if a particular imaged cell was under-stained - information which could be used to generate 501 the population statistic of a percentage of cells which are under-stained. In the method of FIG. 6, initially an absorbance value for a cell’s nucleus would be determined 601 (e g., a value for ABnucieus which may be normalized or limited to a particular color channel would be determined). This value could then be compared 602 to a threshold to determine if the cell was or was not under-stained. When performing a method such as shown in FIG. 6, a variety of approaches may be used to determine the threshold which would be compared 602 with the absorbance for the cell’s nucleus. For example, in some cases, a predetermined threshold (e.g., a threshold of 0.94 for ABN2nUcieus red) defined using observed values for well-stained versus under-stained cells may be used. Alternatively, in some cases a threshold may be defined based on a distribution of absorbance values for a sample. For instance, in a case where values of ABnucieus red are distributed as shown in FIG. 7, it can be seen that there is a horizontal gap along Y = 0.8. in such a case, that horizontal gap (i.e., a value of 0.8 for ABnucieus red) can be used as a threshold to separate under-stained from well-stained cells in the sample under analysis.

[0057] It should be understood that, while statistics such as the cell and population level statistics described above may be used to assess an analyzer’s staining function, such statistics may also be used for other purposes. An example of how statistics such as described may be used for purposes in addition to assessing an analyzer’s staining functionality is shown in FIG. 8. In that figure, in addition to determining 401 absorbance values, there would be a calculation 801of the amount of stain available per cell (SAPC) (e.g., by dividing the volume of stain used in the staining process, by the number of cells in the sample). The ratio of this value to various absorbance statistics can then be used as a measure for how hard or easy it is to stain imaged cells, which, in turn, may be used to analyze 802 the sample, such as by classifying cells and / or diagnosing various disease states which may impact staining.

[0058] Another example of a potential use of absorbance statistics is shown in FIG. 9, which depicts a method which may be used to determine optimized channels for subsequent staining assessment (or disease diagnosis, or cell identification, or other application of staining information). As shown in FIG. 9, optimized channel optimization may begin with obtaining images of well-stained and under-stained cells 901 902. This may be done, for example, by using a human reviewer to examiner and classify images of cells as well-stained or understained, intentionally under-staining cells through reducing the amount of reagent used in the staining process, etc. Once the image have been obtained 901 902, they may be used to, for each absorbance statistic generated by the analyzer (e.g., ABNlceii, ABN 1 cytoplasm, etc.) calculate 903 904 two sets of values, a first set of values using the well-stained images and a second set of values using the under-stained images. These sets of values may each include one value for each channel of the pixels in the relevant images. For example, in an analyzer which captures images having values in red, green and blue color channels (e.g., RGB images) and which would calculate the cell level statistic ABNl nucieus, the first set of values may be ABN 1 nucleus red, ABNlnucieus green, and ABNlnucieus blue calculated based on the well-stained images, while the second set of values may be ABNlnucieus_red, ABN lnucieus_green, and ABN lnucieus blue calculated based on the under-stained images. Those values may then be used to determine 905 the coefficients which would maximize the difference between the well- stained and under-stained images for the relevant statistics in a weighted average of the channel values. Subsequently, once the optimized coefficients had been determined 905, they could be used to calculate absorbance statistics that may be better able to evaluate and / or apply an analyzer’s staining function. For instance, there may be a statistic such as ABN lnucieus optimized which COuld be calculated as ABNlnucieus red ai optimized + ABNlnucieus green * a2 optimized +ABN 1 nucleus blue * as optimized and which may be able to make finer grained distinctions than either the ABNlnucieus statistic or any of the channel specific versions of that statistic.

[0059] Note, descriptions for fixatives, fixation agents, stabilization, and stabilization agents have been included herein. Illustratively, references may be made to some of these concepts (e.g., fixatives or fixation agents) however such examples should not be construed as limiting and can extend to broader stabilization concepts to help stabilization of certain control cell types (e g., without need for refrigeration).

[0060] As a further illustration of potential implementations and applications of the disclosed technology, the following examples are provided of non-exhaustive ways in which the teachings herein may be combined or applied. It should be understood that the following examples are not intended to restrict the coverage of any claims that may be presented at any time in this application or in subsequent filings of this application. No disclaimer is intended. The following examples are being provided for nothing more than merely illustrative purposes. It is contemplated that the various teachings herein may be arranged and applied in numerous other ways. It is also contemplated that some variations may omit certain features referred to in the below examples. Therefore, none of the aspects or features referred to below should be deemed critical unless otherwise explicitly indicated as such at a later date by the inventors or by a successor in interest to the inventors. If any claims are presented in this application or in subsequent filings related to this application that include additional features beyond those referred to below, those additional features shall not be presumed to have been added for any reason relating to patentability.

[0061] Example 1

[0062] A method of assessing a staining functionality of a biological analyzer comprising: providing a control sample, the control sample comprising control particles; applying a staining process to the control sample to result in a stained control sample; capturing images of control particles from the stained control sample which are stained in the staining process; and assessing astaining function of the biological analyzer using the images of the control particles from the stained control sample which are stained in the staining process.

[0063] Example 2

[0064] The method of example 1, wherein the control particles which are stained in the staining process are capable of uptaking stain when the control sample is provided.

[0065] Example 3

[0066] The method of example 2, wherein a plurality of control particles which were not capable of uptaking stain are included in the control sample when the control sample is provided.

[0067] Example 4

[0068] The method of any of examples 1-3, wherein the control particles comprise stabilized particles.

[0069] Example 5

[0070] The method of example 4, wherein the stabilized particles comprise particles which are fixed with a fixative agent which cross link the cell membranes of the stabilized particles fixed with the fixative agent.

[0071] Example 6

[0072] The method of any of claims 4-5, wherein the stabilized control particles are stabilized with glutaraldehyde.

[0073] Example 7

[0074] The method of any of examples 4-6, wherein the control particles comprise particles which are unfixed.

[0075] Example 8

[0076] The method of example 7, wherein the particles which are unfixed comprise partiices which are unstabilized.

[0077] Example 9

[0078] The method of any of examples -8, wherein the method comprises providing a red blood cell count based on measurements of the control particles which are unfixed.

[0079] Example 10

[0080] The method of any of examples 1-9, wherein the control particles are blood-derived

[0081] Example 11

[0082] The method of any of examples 1-10, wherein the method further comprises storing the control sample without refrigeration for at least seven days.

[0083] Example 12

[0084] The method of any of examples 1-11, wherein assessing the staining function of the biological analyzer comprises determining a plurality of absorbance values by, for each of the images of stained control particles from the stained control sample which are stained in the staining process: calculating an incident light intensity value for that image based on light-intensities of a plurality of non-particle pixels; and determining a set of absorbance values for a control particle depicted in that image using the incident light intensity value for that image; and assessing the staining function using the plurality of absorbance values.

[0085] Example 13

[0086] The method of example 12, wherein assessing the staining function comprises: generating one or more absorbance statistics for the control sample based on one or more absorbance values for the images of control particles from the stained control sample which are stained in the staining process; determining an individual particle threshold based on a distribution ofabsorbance values in the images of control particles from the stained control sample which are stained in the staining process; and generating an under-stained percentage based on comparing absorbance values for the images of control particles from the stained control sample which are stained in the staining process with the individual cell threshold.

[0087] Example 14

[0088] The method of any of examples 12-13, wherein each of the images of control particles from the stained control sample which are stained in the staining process comprise values in each of a plurality of channels; and assessing the staining function comprises: generating one or more absorbance statistics for the stained control sample based on one or more absorbance values for the images of control particles from the stained control sample which are stained in the staining process; and for each of the one or more absorbance statistics, generating that absorbance statistic comprises calculating an optimized sum, wherein the optimized sum is a sum of, for each of the plurality of channels, a value for that absorbance statistic in that channel, multiplied by a corresponding coefficient from a plurality of optimized coefficients.

[0089] Example 15

[0090] A system comprising one or more processors and a non-transitory computer readable medium having stored thereon instructions for performing the method of any of examples 1-14.

[0091] Example 16

[0092] A non-transitory computer readable medium having stored thereon instructions for performing the method of any of examples 1-14.

[0093] Example 17

[0094] A control sample for assessing a staining functionality of a biological analyzer, the control sample comprising a plurality of partially stabilized blood derived control particles.

[0095] Example 18

[0096] The control sample of example 17, wherein the plurality of partially stabilized blood derived control particles are capable of uptaking stain.

[0097] Example 19

[0098] The control sample of example 18, wherein the control sample comprises, in addition to the plurality of partially stabilized blood derived control particles which are capable of uptaking stain, a plurality of fully stabilized blood derived control particles which are not capable of uptaking stain.

[0099] Example 20

[0100] The control sample of any of examples 17-19, wherein the control sample comprises, in addition to the plurality of partially stabilized blood derived control particles, a plurality of unstabilized blood derived control particles.

[0101] Example 21

[0102] The control sample of example 20, wherein the plurality of partially stabilized blood derived control particles comprise white blood cell control particles, and wherein the plurality of unstabilized blood derived control particles comprise red blood cell control particles.

[0103] Example 22

[0104] The control sample of any of examples 17-21, wherein the control sample is shelf stable at room temperature for at least seven days.

[0105] Example 23

[0106] The control sample of any of examples 17-22, wherein the plurality of partially stabilized blood derived control particles are partially stabilized with glutaraldehyde.

[0107] Example 24

[0108] A method of assessing a staining functionality of a biological analyzer comprising: providing the control sample of any of examples 17-23; applying a staining process to the control sample to result in a stained control sample; obtaining images of control particles from the stained control sample which are stained in the staining process; and assessing the staining function of the biological analyzer using the images of the control particles from the stained control sample which are stained in the staining process.

[0109] Example 25

[0110] A system comprising: a processor; and a non-transitory computer readable medium having stored thereon instructions for performing a method of assessing a staining functionality of a biological analyzer using the control sample of any of examples 17-23.

[0111] Example 26

[0112] A biological analyzer comprising: a staining module configured to apply a staining process to a control sample to result in a stained control sample; an image capture device configured to capture images of control particles from the stained control sample; a processor; and a non- transitory computer readable medium having stored thereon instructions operable to, when executed by the processor, perform an assessment method comprising, obtaining images of control particles from the stained control sample; and assessing a staining functionality of the biological analyzer using the images of the control particles from the stained control sample.

[0113] Example 27

[0114] The biological analyzer of example 26, wherein assessing the staining functionality of the biological analyzer using the images of the control particles from the stained control sample comprises assessing the staining functionality of the biological analyzer using images of a plurality of stained partially stabilized control particles.

[0115] Example 28

[0116] The biological analyzer of example 27, wherein the assessment method comprises: capturing images of unstabilized control particles from the stained control sample; and assessing an enumeration functionality of the biological analyzer using the images of the unstabilized control particles from the stained control sample.

[0117] Example 29

[0118] The biological analyzer of any of examples 26-28, wherein assessing the staining functionality of the biological analyzer comprises determining a plurality of absorbance values by, for each of the images of control particles from the stained control sample: calculating an incident light intensity value for that image based on light-intensities of a plurality of nonparticle pixels; and determining a set of absorbance values for a control particle depicted in that image using the incident light intensity value for that image; and assessing the staining function using the plurality of absorbance values.

[0119] Example 30

[0120] The biological analyzer of example 29, wherein assessing the staining functionality comprises: generating one or more absorbance statistics for the control sample based on one or more absorbance values for the images of control particles from the stained control sample; determining an individual particle threshold based on a distribution of absorbance values in the images of control particles from the stained control sample; and generating an understained percentage based on comparing absorbance values for the images of control particles from the stained control sample with the individual cell threshold.

[0121] Example 31

[0122] The biological analyzer of any of examples 29-30, wherein each of the images of control particles from the stained control sample comprise values in each of a plurality of channels; and assessing the staining functionality comprises: generating one or more absorbance statistics for the stained control sample based on one or more absorbance values for the imagesof control particles from the stained control sample; and for each of the one or more absorbance statistics, generating that absorbance statistic comprises calculating an optimized sum, wherein the optimized sum is a sum of, for each of the plurality of channels, a value for that absorbance statistic in that channel, multiplied by a corresponding coefficient from a plurality of optimized coefficients.

[0123] Example 32

[0124] A method comprising performing the set of assessment acts the instructions stored on the non-transitory computer readable medium of the analyzer of any of examples 26-31 are to perform when executed.

[0125] Example 33

[0126] A non-transitory computer readable medium having stored thereon instructions for performing the set of assessment acts the non-transitory computer readable medium of the analyzer of any of examples 26-31 are to perform when executed.

[0127] All patents, patent publications, patent applications, journal articles, books, technical references, and the like discussed in the instant disclosure are incorporated herein by reference in their entirety for all purposes.

[0128] Different arrangements of the components depicted in the drawings or described above, as well as components and steps not shown or described are possible. Similarly, some features and sub-combinations are useful and may be employed without reference to other features and sub-combinations. Embodiments of the invention have been described for illustrative and not restrictive purposes, and alternative embodiments will become apparent to readers of this patent. In certain cases, method steps or operations may be performed or executed in differing order, or operations may be added, deleted or modified. It can be appreciated that, in certain aspects of the invention, a single component may be replaced by multiple components, and multiple components may be replaced by a single component, to provide an element orstructure or to perform a given function or functions. Except where such substitution would not be operative to practice certain embodiments of the invention, such substitution is considered within the scope of the invention. Accordingly, the claims should not be treated as limited to the examples, drawings, embodiments and illustrations provided above, but instead should be understood as having the scope provided when their terms are given their broadest reasonable interpretation as provided by a general -purpose dictionary, except that when a term or phrase is indicated as having a particular meaning under the heading Explicit Definitions, it should be understood as having that meaning when used in the claims.

[0129] Explicit Definitions

[0130] It should be understood that, in the above examples and the claims, a statement that something is “based on” something else should be understood to mean that it is determined at least in part by the thing that it is indicated as being based on. To indicate that something must be completely determined based on something else, it is described as being “based EXCLUSIVELY on” whatever it must be completely determined by.

[0131] It should be understood that, in the above examples and claims, “room temperature” should be understood as meaning ambient indoor temperature, typically from 20-22° Celsius.

[0132] It should be understood that, in the above examples and claims, the term “set” should be understood as one or more things which are grouped together.

[0133] It should be understood that, in the above examples and claims, a statement that something is “shelf stable” should be understood as meaning suitable for its intended use (e g., assessing staining functionality) throughout and at the conclusion of the period for which the thing is identified as being shelf stable.

Claims

CLAIMSWhat is claimed is:

1. A method of assessing a staining functionality of a biological analyzer comprising: providing a control sample, the control sample comprising control particles; applying a staining process to the control sample to result in a stained control sample; obtaining images of control particles from the stained control sample which are stained in the staining process; and assessing the staining function of the biological analyzer using the images of the control particles from the stained control sample which are stained in the staining process.

2. The method of claim 1, wherein the control particles which are stained in the staining process are capable of uptaking stain when the control sample is provided.

3. The method of claim 2, wherein a plurality of control particles which were not capable of uptaking stain are included in the control sample when the control sample is provided.

4. The method of any of claims 1-3, wherein the control particles comprise stabilized particles.

5. The method of claim 4, wherein the stabilized particles comprise particles which are fixed with a fixative agent which cross link the cell membranes of the stabilized particles fixed with the fixative agent.

6. The method of any of claims 4-5, wherein the stabilized control particles are stabilized with glutaraldehyde.

7. The method of any of claims 4-6, wherein the control particles comprise particles which are unfixed.

8. The method of claim 7, wherein the particles which are unfixed comprise particles which are unstabilized.

9. The method of any of claims 7-8, wherein the method comprises providing a red blood cell count based on measurements of the control particles which are unfixed.

10. The method of any of claims 1-9, wherein the control particles are blood-derived.

11. The method of any of claims 1-10, wherein the method further comprises storing the control sample without refrigeration for at least seven days.

12. The method of any of claims 1-11, wherein assessing the staining function of the biological analyzer comprises determining a plurality of absorbance values by, for each of the images of stained control particles from the stained control sample which are stained in the staining process: calculating an incident light intensity value for that image based on light-intensities of a plurality of non-particle pixels; and determining a set of absorbance values for a control particle depicted in that image using the incident light intensity value for that image; and assessing the staining function using the plurality of absorbance values.

13. The method of claim 12, wherein assessing the staining function comprises: generating one or more absorbance statistics for the control sample based on one or more absorbance values for the images of control particles from the stained control sample which are stained in the staining process; determining an individual particle threshold based on a distribution of absorbance values in the images of control particles from the stained control sample which are stained in the stainingprocess; and generating an under-stained percentage based on comparing absorbance values for the images of control particles from the stained control sample which are stained in the staining process with the individual cell threshold.

14. The method of any of claims 12-13, wherein each of the images of control particles from the stained control sample which are stained in the staining process comprise values in each of a plurality of channels; and assessing the staining function comprises: generating one or more absorbance statistics for the stained control sample based on one or more absorbance values for the images of control particles from the stained control sample which are stained in the staining process; and for each of the one or more absorbance statistics, generating that absorbance statistic comprises calculating an optimized sum, wherein the optimized sum is a sum of, for each of the plurality of channels, a value for that absorbance statistic in that channel, multiplied by a corresponding coefficient from a plurality of optimized coefficients.

15. A system comprising one or more processors and a non-transitory computer readable medium having stored thereon instructions for performing the method of any of claims 1-14.

16. A non-transitory computer readable medium having stored thereon instructions for performing the method of any of claims 1-14.

17. A control sample for assessing a staining functionality of a biological analyzer, the control sample comprising a plurality of partially stabilized blood derived control particles.

18. The control sample of claim 17, wherein the plurality of partially stabilized blood derived control particles are capable of uptaking stain.

19. The control sample of claim 18, wherein the control sample comprises, in addition to the plurality of partially stabilized blood derived control particles which are capable of uptaking stain, a plurality of fully stabilized blood derived control particles which are not capable of uptaking stain.

20. The control sample of any of claims 17-19, wherein the control sample comprises, in addition to the plurality of partially stabilized blood derived control particles, a plurality of unstabilized blood derived control particles.

21. The control sample of claim 20, wherein the plurality of partially stabilized blood derived control particles comprise white blood cell control particles, and wherein the plurality of unstabilized blood derived control particles comprise red blood cell control particles.

22. The control sample of any of claims 17-21 wherein the control sample is shelf stable at room temperature for at least seven days.

23. The control sample of any of claims 17-22, wherein the plurality of partially stabilized blood derived control particles are partially stabilized with glutaraldehyde.

24. A method of assessing a staining functionality of a biological analyzer comprising: providing the control sample of any of claims 17-23; applying a staining process to the control sample to result in a stained control sample; obtaining images of control particles from the stained control sample which are stained in the staining process; and assessing the staining function of the biological analyzer using the images of the control particles from the stained control sample which are stained in the staining process.

25. A system comprising: a processor; anda non-transitory computer readable medium having stored thereon instructions for performing a method of assessing a staining functionality of a biological analyzer using the control sample of any of claims 17-23.

26. A biological analyzer comprising: a staining module configured to apply a staining process to a control sample to result in a stained control sample; an image capture device configured to capture images of control particles from the stained control sample; a processor; and a non-transitory computer readable medium having stored thereon instructions operable to, when executed by the processor, perform a set of assessment acts comprising, obtaining images of control particles from the stained control sample; and assessing a staining functionality of the biological analyzer using the images of the control particles from the stained control sample.

27. The biological analyzer of claim 26, wherein assessing the staining functionality of the biological analyzer using the images of the control particles from the stained control sample comprises assessing the staining functionality of the biological analyzer using images of a plurality of stained partially stabilized control particles.

28. The biological analyzer of claim 27, wherein the set of assessment acts comprises: obtaining images of unstabilized control particles from the stained control sample; and assessing an enumeration functionality of the biological analyzer using the images of the unstabilized control particles from the stained control sample.

29. The biological analyzer of any of claims 26-28, wherein assessing the staining functionality of the biological analyzer comprises determining a plurality of absorbance values by, for each of the images of control particles from the stained control sample:calculating an incident light intensity value for that image based on light-intensities of a plurality of non-particle pixels; and determining a set of absorbance values for a control particle depicted in that image using the incident light intensity value for that image; and assessing the staining function using the plurality of absorbance values.

30. The biological analyzer of claim 29, wherein assessing the staining functionality comprises: generating one or more absorbance statistics for the control sample based on one or more absorbance values for the images of control particles from the stained control sample; determining an individual particle threshold based on a distribution of absorbance values in the images of control particles from the stained control sample; and generating an under-stained percentage based on comparing absorbance values for the images of control particles from the stained control sample with the individual cell threshold.

31. The biological analyzer of any of claims 29-30, wherein each of the images of control particles from the stained control sample comprise values in each of a plurality of channels; and assessing the staining functionality comprises: generating one or more absorbance statistics for the stained control sample based on one or more absorbance values for the images of control particles from the stained control sample; and for each of the one or more absorbance statistics, generating that absorbance statistic comprises calculating an optimized sum, wherein the optimized sum is a sum of, for each of the plurality of channels, a value for that absorbance statistic in that channel, multiplied by a corresponding coefficient from a plurality of optimized coefficients.

32. A method comprising performing the set of assessment acts the instructions stored on the non-transitory computer readable medium of the analyzer of any of claims 26-31 are to performwhen executed.

33. A non-transitory computer readable medium having stored thereon instructions for performing the set of assessment acts the non-transitory computer readable medium of the analyzer of any of claims 26-31 are to perform when executed.

Images