JP2003512605A - Temporary dynamic flow cytometer analysis system - Google Patents

Abstract

(57) Abstract: A flow cell measuring device (1) and a method for processing information associated with particles or cells entrained in a sheath fluid stream, whereby a moving speed is high. It allows for the examination, differentiation, assignment, and separation of such particles or cells. The first signal processor (18), individually or in combination with at least one further signal processor (17), performs a compensating conversion on the data from the signal (15). The compensating transform can complex transform data from at least one signal (15) to compensate for one or more operational parameters. The compensated parameters are returned to the first signal processor (18) to provide information about the compensated parameters, to define the particles (3) and to distinguish them from other particles.

Description

Detailed Description of the Invention

I. Field of the Invention In particular, a flow system for processing information associated with particles or cells entrained in a sheath fluid stream that allows for rapid assessment, identification, assignment and separation of particles or cells. A metrology device and method.

II. Background Flow cytometry is a field that has existed for many years. Basically, flow cytometry systems operate to position small amounts of material within the sheath fluid.
By hydrodynamic focusing and laminar flow, substances are separated into individual particles, cells, etc. In many applications, for analysis, the sheath fluid exits the nozzle in a jet and free fall with entrained material, or is carried in an optically clear path. The sheath fluid is based on the identified particle property assignments
Droplets may be formed that contain individual particles that are separated and collected.

This type of analysis requires uniform conditions within the jet, very precise timing, and consistent comparative parameters associated with entrained material to accurately separate such materials. In addition, there is a concerted commercial and public sector demand for faster flow cytometry, the need to identify materials based on more complex and multi-parameter analyzes, and the need for higher purity separations. Unfortunately, there are still variations in device behavior, sheath fluid stream dynamics, or observed particle properties, which are exacerbated by increasing the speed at which entrained material is jetted. Thus, there is a need to compensate for such variations in order to provide accurate analysis and separation of entrained material in the sheath fluid stream.

An overview of some attempts to understand and address fluid stream and droplet mechanics is provided in US Pat. Nos. 4,317,520, 4,318,480, and 4,318,481.
See 4318482, 4318483, and 4325483. Each of these patents is incorporated herein by reference. As the above patents describe, the conventional approach has been to calculate the signal and act immediately on such information. Also, some of the recognized practical problems are the fact that there is a limited amount of space and time to perform detection and analysis. It may be desirable to have the optical system as small as possible, as Japanese Patent No. 2024535 also recognizes only with respect to the detection system.

As can be appreciated, the substantial problem can be that the data generated from an occurrence must be detected and reacted in a very short time. Given the speed of microprocessors and the like, this may seem achievable at first glance. The challenge of this unique flow symmetry situation is that the initial or raw signal data may not be sub-optimal and may even be unusable. Thus, if unique flow cymetry is used, it must be further processed to achieve further analysis or decision making. This process is complicated,
Faster processing speeds and performance may be required beyond what is available on today's fastest computer systems as well as typical commercial systems. Moreover, the desire for faster processing frequencies can be exacerbated as the desire is sought. One extreme example of speed is shown in US Pat. No. 4,361,400. This patent is incorporated herein by reference. In the above patent, droplet formation frequencies in the range of 300 to 800 kilohertz have been achieved. Most practical droplet flow cytometry operates in the 10 kHz to 50 kHz range. Although the problem of analysis speed has been known for many years, it was clearly a generally accepted idea that prior to the present invention, digital analysis in the flow cymetric context would not be achievable. The present invention proves that this conjecture is not true.
As a result of the present invention, with appropriate data correction etc., now 50-100
Droplet formation speeds of up to ~ 200 kHz are possible.

However, at any of these speeds, there seemed to be expectations that analog analysis would be the only practical way of performing the analysis and compensating for fluid dynamics, particle properties, and instrument variations. To some extent, these expectations are so prevalent that quality control, good manufacturing practices, regulatory approvals and other issues are pushed aside, vanished or even compromised. Existing technology dominates the utility of this area.

Another important issue with conventional analysis of flow cymetry and correction of variables may be the preservation of the initial signal data resulting from the incidents associated with the fluid stream prior to subsequent processing steps. It is possible that the initial signal data could not be saved or stored until now because the amount of time to analyze or correct the initial signal is short. Thus, it is possible to sacrifice all or part of the original or raw signal data to increase the efficiency of the analysis and provide the feedback correction event. Discarding the initial raw data prevents data analysis to improve quality control, establish good manufacturing practices, and obtain processing thresholds for certain regulatory or legal requirements. obtain.

However, another problem with conventional analysis is that it cannot handle high-speed sequential generation, cannot correct multiple parameters, cannot perform complex operations, cannot provide conversion correction of the first data, or parameters that are corrected. May not be applicable. Conventional analysis can be limited by the amount of information that can be processed and returned between successive events that can occur at a rate of at least 10,000 per second.

The first aspect of the above-noted impossibility may involve the nature of conventional signal processors used with flow cymetry. Traditional flow cymetry signal processors often cannot handle large amounts of signal information because they are analog, cannot operate on poor quality signal information, and are actually complex transform operations (such as transform operations using algebraic formulas or structures). Is not actually achieved, or only a reflexive feedback operation is performed, rather than a sequential or multivariate analysis with subsequent parameter correction.

A second aspect of the impossibility described above may involve conventional data processing infrastructure. In part, traditional infrastructures cannot address how information flows are distributed, allocated, and coordinated. Conventional processing of flow cymetry information obtained from generation associated with a fluid stream is treated as an originally isolated feedback loop. Thus, as the number of feedback loops increases, it may be more difficult to co-ordinate various aspects of flow symmetry operation. Moreover, these feedback loops can be completely separated. For example, stream parameters such as droplet break-off position
It can be completely decoupled from different analysis of particles and separation of particles within the fluid stream being corrected.

A third aspect of the above impossibility may be a lack of symmetry reduction in the application of transformed data. Once again, analog analysis can prevent or minimize symmetry reductions in the complex analysis of sequential or parallel multivariate analysis. Run time increases due to lack of symmetry reduction or inability to apply symmetry reduction to the analysis conditions.

As mentioned above, the use of correction parameters resulting from complex signal conversions for a long time, real-time analysis with correction parameters, or the storage of the first signal data is a fluid stream, Although it has been considered necessary to have devices and methods that accompany changes in equipment or environmental changes, this need has not been met. The present invention addresses each of the above problems with practical solutions.
To the extent the person skilled in the art has taken a direction away from the technical direction pursued in the present invention, the solution does not appear to have been achieved. This is either a result of the fact that the person of ordinary skill in the art did not really understand the nature of the problem, or the fact that the person of ordinary skill in the art was misguided by some of the expectations and assumptions regarding the type of system that could be considered. Can result from The present invention uses digital signal processing (DSP) technology to compose information from the incidents associated with flow cymetry operations to perform complex transformation, correction, or analysis operations to meet these long sought after goals. To achieve.

(III. Disclosure of the Invention) The present invention relates to high-speed sequential generation, or multi-parameter analysis of generation, or
In order to solve the problems caused by doing the two individually or in combination, a flow symmetry with DSP technology is disclosed. While specific examples have been provided in the context of flow cytometry applications to describe the present invention, this is not intended to limit the scope of the present invention to the field or application within flow cytometry. The present invention may have numerous applications per se, as well as in various fields. For example, detecting defects in products disclosed in US Pat. No. 4,074,809 and US Pat. No. 4,501,366, field flow fractionation disclosed in US Pat. No. 5,503,994, liquid chromatography. , Or electrophoresis, such as computed tomography, gamma cameras, or time-of-flight devices, as disclosed in US Pat. No. 5,880,457.
Each of the above patents is incorporated herein by reference. The basic concept of the present invention is
It is not only applied in the area of flow cymetry, but may be applied in each of the above fields or in other fields. Other areas are parameters such as light generation signals between successive occurrences with a high incident light flux or between successive occurrences that generate data on multiple parameters, or between generations that generate a very large number of signals in a short time. This is an area where detection and analysis of small differences that occur may be necessary or desirable. Furthermore, the present invention can be divided into numerous embodiments that can be combined in various permutations and combinations. Of course, as a result of some of these different, potentially independent aspects of the invention,
The objects of the invention are considerably diversified.

One broad purpose of one embodiment of the present invention is to transform an initial signal that occurs associated with an environment, equipment, or fluid stream, including but not limited to analog and digital signals. Can be. One aspect of this object of the invention may be to harmonize a plurality of different types of signals into a newly digitized data stream for processing. Another aspect of this object of the invention may be the conversion of other low quality or unusable signal data into usable quality signal data. In this regard, the first signal may relate to one or multiple properties of a single particle, such as cells in a fluid stream. Alternatively, the first signal may relate to one property or multiple properties of a series of particles in the fluid stream. A large number of signals themselves are detected for simultaneous occurrences (parallel occurrences), or for occurrences that occur discontinuously over time (sequential occurrences) that also represent one, two, or any number of additional parameters. Can be generated from Occurrence rate detected is about 10,000 per second
It can vary from 0 occurrences to about 800,000 or more occurrences per second. For example,
Changes in the fluid dynamics of the jet or nozzle, variations in the performance of the device itself (
(Such as changes in the baseline electronic signal from the photomultiplier tube) or changes in the performance of the instrument due to changes in external conditions such as temperature or pressure. For each of the above, even when occurring at a high rate, for a limited period of time, or even in a sub-optimal manner, the occurrence can be detected, converted to an initial signal, and digitized.

Another broad object of the practice of the invention is to provide a compensated parameter,
It may be to perform a compensating transformation on the original signal. One aspect of this purpose is the first
A compensation conversion to the processed data from the first signal incident to the first occurrence to compensate for the parameter (s) shared by the occurrence of the first occurrence and by the at least one additional occurrence. , And then applying a compensating transform to the processed data from the at least one further signal incident to the one or more occurrences. A second aspect of the present purpose may be compensation of the parameter (s), which shares the characteristic (s), so that "crosstalk" is eliminated or minimized. obtain. Elimination or minimization of crosstalk provides an improved ability to distinguish the first occurrence from the second or more occurrence (s). The identified outbreaks are then assigned to a class, separated, and retrieved.

Another object of embodiments of the present invention is to provide a hardware or software infrastructure to allocate, align, or coordinate the data generated from the original signals described above. One aspect of this objective may be to provide a plurality of signal processors that can operate in parallel to increase their ability to process signal data. The present invention can utilize at least two parallel signal processors, but many parallel signal processors. A parallel signal processor can be remotely located hardware or hardware connected together via an Ethernet or Internet connection.
A second aspect of the invention, for this purpose, may be to assign different functions to different parallel signal processors in order to optimize the processing speed. A third aspect of the invention, for this purpose, is to use linear assembler and register processing to enhance and coordinate the parallel operation of specialized functions performed by at least two signal processors. Can be. A fourth aspect of this purpose may be to provide software that optimizes the use of parallel processing of digital code. A fifth aspect of this object of the invention may be to provide a symmetrical reduction in the sequential conversion operation in order to reduce the processing execution time.

Another object of embodiments of the present invention may be to perform the composite operation on the original signal described above. Complex actions are due to the speed with which actions must be performed sequentially or in parallel, the number of parameters involved, the use of algebraic formulas or algebraic structures, the use of complex numbers to define variables or the like. It may be an action that was not possible or impractical before the invention. Each of these aspects can be an individual complex or a combined complex.

Another object of embodiments of the present invention may be to store the original signal in a memory device or memory storage device. One aspect of the invention may be to preserve the original signal without changing the original quality or the original quantity of the original signal. this is,
It may be necessary or desirable for quality control issues or to meet regulatory or statutory requirements. Another aspect of this purpose may be to duplicate the original signal for analysis during operation of the cytometer, or duplicate the signal for future re-analysis.

Another object of embodiments of the present invention may be to provide software for implementing various applications based on DSP technology. The first aspect of this purpose may provide an exemplary compensating conversion operation. This may include bimodal compensation, trimodal compensation, as well as compensating transforms of higher order compensation sets. A second aspect of this purpose may be to provide an exemplary compensation matrix and its various properties. A third aspect of this purpose may be to provide exemplary symmetric reduction in various aspects of software notation. A fourth aspect may be to provide an exemplary program of subtraction of pairs or groups of fluorescence signals in order to orthogonalize the color sensitivity of each signal.

However, another object of embodiments of the present invention is to provide an amplified photomultiplier tube (P
MT) output analog-to-digital converter. Since the emission spectra of fluorescent antibody labels are broadband, they can overlap with the passbands of up to eight photomultiplier filters. Therefore, the digitized PMT output from the even one antibody label may contain as many effects as eight antibody labels. S
"Practical Flow Cytometry" by hapiro 1
See pages 7-19, 163-166 (19), which is incorporated herein by reference. This feature may allow color sensitivity to be orthogonalized to the respective signals, and in particular may allow applications associated with MoFlo® blood flow meters.

However, another object of embodiments of the present invention is the ability to simultaneously or interchangeably latch multiple parameters, particularly the maximum value of any 64 MoFlo® blood flowmeter parameters. It may be to provide the ability to latch as an input.

Another object of embodiments of the present invention may be to provide cross-beam time alignment to perform enhanced compensation between a pair of parameters. One aspect of this purpose is that the apparent beam-to-beam transition time appears to be less than 1/3000 or appears to exceed the actual capabilities of analog circuit design, in billionths of a second between compensated beams. Can be reduced to less "time jitter".

Another object of embodiments of the present invention may be to provide digital error compensation. Digital subtraction is attractive because it avoids signal alignment problems, but significant digitization errors can occur. For example, if a bright signal is compensated over a large dynamic range, the apparent compensation density (populatio)
Digitized errors may occur, where the picket-fence roughness of n) may be discernible. Digital error compensation can minimize these errors and thus improve the quality of digital information.

Another object of embodiments of the present invention may be to provide logarithmic amplifier optimization. Logarithmic amplifiers usually do not match the ideal logarithmic behavior over the entire range.
For example, some logarithmic amplifiers have a variable of 0.4db. That is, for any given input, the ratio of the actual output signal from the logarithmic amplifier above the value expected for the full logarithmic function is expressed in db as:

[0025]   Error = 0.4db = 20log10 (Vout / Video) Optimization of logarithmic amplifiers can provide values that more closely approximate the ideal amplifier.

Another object of embodiments of the present invention is off-loading binning (off-lo).
Advising). For example, the particle density characteristics can be stored in the memory of an additional signal processor that uses a binning transform. These density statistical properties, such as mean, standard deviation, distortion and separation, can be sent to a separate processor, thus offloading this task, and thus the performance of the first and partitioned processors. improves.

Of course, further independent objects of the invention are disclosed throughout the other parts of the specification.

V. Modes for Carrying Out the Invention In particular, enhanced blood flow meters utilize DSP techniques and methods to process raw or original signal information associated with various parameters during operation. Environment parameters,
Including, but not limited to, instrument parameters or parameters entrained in the sheath fluid flow, or parameters associated with the cell, even if the blood flow meter of those particles or cells is operated at high speed. , Composite evaluation, identification,
Allows allocation and separation. Generally, data acquisition, data transformation, parameter compensation, and compensated parameter utilization systems for separating multiple parallel or sequential events may be useful in various fields and applications.

In describing these aspects of the invention, MoFlo (R) (Cytoma
blood flow meter systems, and Su of those systems.
The performance of Mmit (R) (also a trademark of Cytomation, Inc) may be mentioned. Each of these systems represents state of the art blood flow meter performance and is not only a very fast and practical blood flow measurement system, but is also well known to those skilled in the art.

Referring now to FIG. 1, a preferred embodiment of the present invention may be shown in detail. A blood flow meter (1) with a fluid source (2) can establish a fluid flow and particles (3) can be suspended therein. The source of particles (4) may sometimes insert particles such that at least one particle is suspended in the flow and is hydrodynamically concentrated in the flow. The oscillator (5), which is responsive to the fluid flow, vigorously agitates the fluid flow. Jet or fluid flow (6) composed of fluid flow (2) and particles (3)
) May then be established below the tip of the blood flow meter nozzle (7). The flow is established under steady state conditions such that a droplet (8) enclosing a single particle results and leaves the continuous portion of the flow. Once the flow is established in this steady manner, a stable droplet break-off point can be established. Below the droplet break-off point (9) there may be a free fall area (10). This free fall area exemplifies the area where the droplets leave the continuous portion of the stream and the droplets move. A sensor (12), such as a laser and receiver combination (or separate), can be used to monitor particle flow. The sensor can sense the occurrence and generate a signal (15). For example, a coherent beam of light directed at the fluid flow by the sensor (12) will block in the flow (6),
Thereafter, fluorescent or scattered light may be emitted. The emitted fluorescence can be captured by a receiver such as a photomultiplier tube to produce a signal (15). Based on analysis of the signal generated by the sensor from fluorescence generation, the particle (s) can be identified and assigned to a class. Droplets that fill location (11) may be present at points along the free fall area. Based on the particle allocation, the droplets can be actively filled, passively filled, or left unfilled.

The charged droplets can pass through the electrostatic field (12) as they fall into the free fall zone.
When the droplets are charged by positive or negative charges, the electric field established between these electrostatic plates reflects the charged droplets, the trajectory of the reflected droplets (13) and the neutral droplets. The orbit of can serve to separate one type of particle class from another type of particle class. These separated particles are then placed in a container (s).
May be collected within (14). Moreover, allocation and separation of multiple classes of particles can be achieved using other techniques, such as utilizing different amounts of charge. The rate of separating or classifying the classes of particles can be at least 1000 per second.

Monitoring or sensing may be performed using the sensor (12) and then various parameters (16) related to the operation of flow cytometry or a number of other instruments (used individually or in combination). ) May be supplemented or generated by the signal (15) associated with As mentioned above, the raw or original signal (s) may be single particles (3) that may be cells carried by the fluid stream (2).
) May be associated with a single property or multiple properties. Alternatively, the original signal may be associated with a single property or multiple properties of cells within the series of particles (3) or fluid stream (2). As explained further above, co-occurrence sensing, or discrete occurrence.
Sensing of s over time can generate a number of signals representing one, two, or any number of other parameters (at least 64 parameters in MoFlo® flow cytometry). The rate of perceived outbreaks can vary between several outbreaks per second, or can be from about 10,000 outbreaks per second to about 800,000 outbreaks per second, or higher. The original signal may also be due to changes in hydrodynamics at the jet or nozzle, changes in the performance of the device itself (eg changes in the reference electron signal from the photomultiplier), or changes in external conditions such as temperature or pressure. It may represent a change in the performance of the device due to doing. Specifically, as shown in FIG. 1, the parameters can be various aspects associated with the fluorescence emission of fluorescein isothiocyanate (FITC) when excited,
Includes pulse width, forward scatter, side scatter, FITC raw information, raw PE, raw PECYS, etc. Naturally, numerous other parameters may also be monitored, and these particular examples are intended to be used as a guide rather than a comprehensive list.

The MoFlo® system, for example, monitors some of the traditional 12-bit parameters, which are pulse width, analog-to-digital converter (ADC), channel output, timer output, look-up table (LUT). Output, and classifier output.
Users of MoFlo® may have the need or desire to calculate another parameter, which compensates the ADC output for unwanted side effects of broadband fluorescence emission, calculates the speed of the ADC channel, and , Calculating whether the ADC parameters fall within or outside a region of relatively high dimension above 3D.
To develop the performance of equipment such as MoFlo® systems, other types of flow cytometry systems, or other types of equipment, the present invention uses at least one additional signal processor (17) to A compensation operation is applied to the processed data from the first signal and the processed data from the second or more signals. This is the first
Can occur in parallel with or concurrently with the data processing of the signal processor (18). A compensating output from another signal processor for at least one of the parameters shared by the signal (or the generation that generated the signal) is a combination of the first signal and the second signal based on the compensating parameter (s). Allows for enhanced differentiation between. The compensation data can then be combined, for example, with the data governing the function of the first signal processor and applied to classify and separate the occurrences.

Passing, Transforming, and Returning Referring again to FIG. 1, as described above, the data emerging from flow cytometry may utilize at least one other signal processor, which may , A parallel digital signal processor (17) that can be used simultaneously with the first signal processor, for example. The original raw data or a portion of the original raw data from each signal produced by flow cytometry is
It can be assembled as a table with 32 or more 16-bit data words. First
16 data words can be the raw data output resulting from the generation of fluorescence emission from an excited fluorochrome used as a surface or internal marker. First one
The 6 data words may pass through another signal processor and the converted output is then
It may be presented in the second (or more) 16 data words. The final compensation parameters are returned to the first signal processor, combined with the output of the first signal processor, and then presented or displayed. This is often referred to as the pass and return digital signal path.

Inevitably, the numeric data formats for a particular application need to be matched. For example, 12-bit MoFlo (R) unprocessed data is 12
． It can be considered as an unsigned fixed-point integer in 0 format, that is, there are 12 integer bits to the left of the fixed point and 0 fractional bits to the right of the fixed point. This results in the range 0x000 (0) to 0xFFF (4095). The compensation parameter output from the second signal processor (17) may need to be in the same format. The internal data manipulations may be modified as needed to execute the required algorithms. Possible internal data formats that can be used are, for example, two's complement, signed integers, signed or unsigned fractional fixed point numbers, or floating point decimals. Various CPLD / FPGA or digital signal processing von Neumann or Harvard programs, data and I / O architectures may be used as needed to implement the algorithms. The algorithm and parameter coefficient for compensation parameters are
It can be changed while operating the device. If desired, for example, in a MoFlo® system, within the operating time, from the first computer of the system, for example, M
It has to be able to be downloaded via the FIO Rev B Control Word Bus using the same programming conventions.

Another signal processor (s) used in parallel is a large number of signals,
It can provide compensation parameters fast enough that the data from the channels, or parameters, are simultaneously compensatively transformed. The speed of operation on the first group of 16 data words may occur before the second group of 16 data words becomes available. Each data word may pass through another signal processor at a rate of at least every 150 nanoseconds. Therefore, another signal processor may perform all operations on the 16 allocated data words in a maximum of approximately 2410 nanoseconds.

Thus, performing compensatory transformation operations on the data from the signal (s) can provide compensation parameters for differentiating development during the flow cytometry operation. In such real-time operation of flow cytometry or other equipment, another signal processor (s) was chosen, even if the rate of development that differentiated was 1000 to 800,000 developments per second. Compensation conversion operations may be performed on the parameters. Naturally, this other signal processor (s) may also apply the compensating transform operation to low speed generation.

The compensation parameters generated by another signal processor (s) are then returned to the first signal processor. In this way, the first signal processor may manage data for different tasks than another signal processor (s). In one embodiment of the present invention, a first signal processor may perform the tasks of data management and display and another signal processor, among others,
Performs a compensation conversion function on the original signal. Therefore, the separation of tasks of data management and display and parametric compensation transformation can be important requirements for achieving accurate and reliable function.

By way of example only using the invention, a compensating transformation involving complex manipulations, with or without another signal processor (s), emits fluorescent antibody labels that overlap the pass band of the 8PMT filter. It may be performed in the spectrum. The compensation conversion operation may be of the following form, which may be the preferred configuration, but a wide variety of alternative embodiments are possible.

(Bidirectional Compensation) Two linear signals of 0 to 1000 mv are logarithmic and linear voltage (linear).
voltage) is converted into a log signal in a related manner as follows.

V ¹ _log = A. log (V ¹ _lin / V _th )
(1) V ² _log = A. log (V ² _lin / V _th ).
(2) Here, A = 10000 / log (10000 / _Vth ). V / _th is typically 1 millivolt. This formula is 1 millivolt to 100
Input of 00 millivolts is 0 millivolts to 100 using 2.5 volts every 10
Guaranteed to generate a log signal of 00 millivolts. The compensation parameter is a parameter obtained by removing the crosstalk between the two parameters. This is obtained by

V ^1c _lin = V ¹ _lin (1-C ₁₂ ) ^ V ² _lin / V ¹ _lin (3) V ^2c _lin = V ² _lin (1-C ₂₁ ) ^ V ¹ _lin / V ² _lin (4) ) To recover V ¹ _lin and V ² _lin from logarithmic values,
The inverse function of (1) and (2) can be determined.

V ¹ _lin = V _th exp (V ¹ _log / A) (5) V ² _lin = V _th exp (V ² _log / A) (6) These linear values are then given by (3) above. And (4) and can be transformed into logarithms by reapplying (1) and (2).

In practice, this calculation has a linear range of 0-4095 (
Digitalized) and the threshold is 4095. Performed on a digital value that is /10000.0.

Three-Way Compensation This is a mathematically the same process, except that the equations for the compensation sets are as follows, as well as for higher order compensation sets.

[0046]   V^1c _lin= V¹ _lin(1-C₁₂) ^ V^Two _lin/ V¹ _lin(1-C _Thirteen ) ^ V^Three _lin/ V¹ _lin． ． ．                 (7)   V^2c _lin= V^Two _lin(1-C₂₁) ^ V¹ _lin/ V^Two _lin(1-C ₂₃ ) ^ V^Three _lin/ V^Two _lin． ． ．                 (8)   V^3c _lin= V^Three _lin(1-C₃₁) ^ V¹ _lin/ V^Three _lin(1-C ₃₂ ) ^ V^Two _lin/ V^Three _lin． ． ．                 (9) Using a look-up table, N color compensation can be done in the following manner. Conversion related
According to this note, N color compensation can be decomposed into N-1 2D lookups
Is clear. For example, the compensation output of three colors when performing from the antilogarithm to the logarithm is
, Can be:

V ^1c _log = V ¹ _log −exp (V ² _log −V ¹ _log ). log (1
_{^{-C 12) -exp (V 3 log}} -V 1 log). log (1-c ₁₃ ) The first two terms together with the last term in this equation are equivalent to:

[0048]   V^1c _log= LUT (V¹ _log, V^Two _log) -LUT (V¹ _log, V ^Three _log )   (Apply transformation)   An 8 × 8 compensation matrix is described using the following notational conventions. When n = 0 to 7, p_ncIs the compensation output. When n = 0 to 7, p_nIs the input log signal. C_jkBut-. 999-. If the fractional compensation value is in the range of 999, c_jkIs the complement
Number = -A^*log (1-C_jk). e (p_n-P_m) = Exp ((p_n-P_m) / A) A = 4095.0 / log (10000) = 444.6 The compensation matrix may be as follows:

[0049]

[Equation 1] c _jk is positive or negative, the parameters are along the diagonal of the matrix,
Note that other values are subtracted from that parameter.

[0050] (Characteristics) diagonal around is symmetrical, _{e (p} j -p _k) term on one side of the diagonal is the reciprocal of the term on the opposite side. However, this is not a useful symmetry because division is a time consuming operation in integer arithmetic DSP devices. The function e (p _j −p _k ) may be in the range exp (−4095 / A) to exp (4095 / A), as _pn is always positive and may be in the range 0-4095. This is in the range of 8 digits for every 10 of 1 / 10000-10000. In order to perform integer arithmetic quickly, preferably the computation of e (p _j −p _k ) should be done using a 16-bitmap to conserve memory space. However, 1.
Values in the relatively low range of less than 0 are incorrectly represented. This is the accuracy of the calculations, which means that not be maintained over the mapped all values were of e (p k _{-p k).} It may be necessary to have two maps (one for the positive independent variable and one for the negative independent variable of e ()) in order to maintain accuracy. These constraints allow us to calculate the number of operations that may be needed to solve this matrix.

[0051]

[Equation 2] The 6201 DSP operates in 5 ns clock cycles. Therefore, this calculation of non-optimal execution would be 5 ^* 708 = 3540 ns. The MoFlo (R) parameter bus operates at 150 ns per frame word, so the number of MoFlo (R) data words is:

3540/150 = 23.6 The last compensation parameter is in slot 10. Output is data word 16
Need to be ready in. Element e (p _j −p _k ) off the diagonal
It is not possible to do a computational matrix each time we encounter each MoFlo (R) parameter, since can be a mixture of all parameters. DSP pipelining and parallel architecture can substantially reduce this computation time.

This set may be reduced symmetrically to reduce run time. One can multiply the above equation by e (p _n ) to move the diagonal term to the left.

[0054]

[Equation 3]

[0055]

[Equation 4] The execution time of this matrix is 2660 ns, MoFlo (R) frame words = 2660/150 = 17.7 MoFlo (R) data words.

Using parallel assembler and register usage optimization to improve parallel operation, it is possible to obtain parallel code as described in Appendix A, which is incorporated herein by reference. This program and the examples above are not intended to limit the invention to the particular hardware, software, algorithms, applications or configurations, but in the generation and use of the invention, which may take the form of various embodiments. Provided as a guide to. A particular embodiment of the invention may be as follows, in the context of a flow cytometer or otherwise.

In a particular application, it is possible to separate the occurrences in time. The temporally separated occurrences can be different original or raw signals generated for the same particle, for example, as the particle travels through various flow cytometric processes in the context of the flow cytometer. As mentioned above, these flow cytometer processes include entrainment into the fluid stream, excitation of boundary fluorochromes, assignment to classes and separation of particles into assigned classes. Time-separated generation may also include particles labeled with several different fluorochromes, where each type of fluorochrome is excited at different time points. Again, the temporally separated occurrences are a series of discrete occurrences each monitored for the same parameter, such as the emission of a fluorescent dye from a series of labeled cells, or the emission of the fluorescent dye is attenuated. It may be a single occurrence monitored in discrete time periods, such as the emission characteristics of the fluorescent dyes seen in Of course, it is possible to provide many other examples with temporally separated occurrences. Due to these spatially separated occurrences,
The output of the original signals, separated in time, results. With pass-through, compensating transforms and returns, using a further signal processor (s), this temporal separation can be eliminated. In some cases, this allows specific applications not previously possible, such as using multiple separation lasers to excite multiple fluorochromes over time, while in other cases, The original signal makes it possible, even during the operation of the instrument, to carry out the compensating transformation applied between the occurrences and the more accurate method of distinction between the occurrences. . Because it is difficult to eliminate temporal isolation by similar circuitry, it is often impossible to perform operations with similar tolerances, such as operations that are less tolerant of “time-varying”.

In certain applications, “cross talk” between the same or different parameters may occur. “Crosstalk” between the same or different parameters associated with the same or different occurrences due to compensatory transformations in the original or raw signal, different occurrences associated with the same parameter,
The "crosstalk" associated with or may be eliminated. As mentioned above, "crosstalk" between the emission of different types of fluorochromes was compensated. The compensating transform allows the raw original fluorescence signal, or compensates for many other types of signals, so that the resulting, compensated parameters actually eliminate crosstalk. , Correctly position the blank reference level. This is especially the detection of defects in products as disclosed by US Pat. Nos. 4,074,809 and 4,501,366; as disclosed by US Pat. No. 5,503,994. Flow field fractionation, liquid chromatography or electrophoresis; US Pat. No. 5,880
, Tomography, gamma cameras or time-of-flight instruments as disclosed by U.S. Pat. No. 5,135,759, and by U.S. Pat. App. No. 60/2103089 for bright fluorescence values. May be relevant to other types of applications, such as a flow cytometer. Each of these documents is incorporated herein by reference. This type of compensating transform can be performed simultaneously on many channels (at least eight channels in the above embodiment) and provides orthogonalized data that can be returned to the first signal processor.

In certain applications, multiple color compensation is required. The compensation transform for multi-color compensation can take the format described above, allowing for at least 8 color compensation implemented by a 64-element matrix of operation. The transformation may operate on linear format data or orthogonal format data. Inevitably, higher order sets can be used to provide N color compensation, as described.

In certain applications, it is necessary to analyze parametric dynamics or parametric ratios. The ratio between two signals over time is an important measure in studies of cell dynamics. Once the original signal is compensated, the ratio can be used to provide a measure of the absolute difference between the signals. For example, calcium release can be an important measure in studies of cell dynamics. To measure calcium release, the ratio of the two fluorescence emission signals may be needed. These fluorescence emission signals can be subjected to a compensating transformation to provide a compensated fluorescence emission signal for comparison at the appropriate time frame needed to maintain accuracy. It is possible to implement multiple ratios. Time can be an essential parameter for kinetic measurements and can be provided by a built-in clock. The built-in clock can have a time range from microseconds to years, allowing sufficient flexibility in time-stamped data streams.

Certain applications require subpopulation discrimination and tracking. The flow cytometer relies on the stability of various parameters, including but not limited to environmental parameters, instrumental parameters, developmental parameters, for analyzing and defining the mean and width of a population of particles. Unfortunately, these parameters can always be dynamically unstable. By compensating the original signal from these various parameters, it is possible to control the stability. Alternatively,
With a compensating transformation, it is possible to track drift within these parameters. Compensating and transforming the original signal information, among other uses, parameters for decomposing or distinguishing subpopulations, parameters for choosing the level of decomposition maintained between individual subpopulations, and individual subpopulations. Parameters for selecting thresholds for allocation and separation, parameters for enabling continuous distinction and allocation of individuals from subgroups to various networks, for tracking subgroups such as parameter drift It may be possible to select parameters for evaluating the purity of individual pools separated without re-analysis.

In this respect, a two-dimensional population of particles, a three-dimensional population of particles, or a higher-dimensional population of particles can be distinguished and assigned to different subpopulations, and can be multidimensional. Regions can be used to separate subpopulations when using the present invention. It provides a powerful and direct method for separating previously unavailable multidimensional subpopulations on flow cytometers and other types of instruments, as well as in other disciplines of applications. provide.

Another aspect in which the identification of subpopulations is closely associated with the overlapping subpopulations is enumerated by dynamically characterizing the duplications using compensatory transformations that can be designed to detect the percentage of duplications. It is possible. The exact proportions, averages, widths and separations of multi-functional subpopulations can also be characterized by the present invention. A wide population of particles with a small sub-population of interest can be narrowed and maintained for dynamic amplification or transformation of amplification parameters so that a sub-population of interest can be defined, placed, analyzed and separated. It is possible to squeeze through compensation. Without conversion compensation, such an exact description may not be possible.

In an application using the flow cytometer, the population of various subjects (
It is possible to screen particles with one or more) / subpopulations to generate regions of interest that better delineate these populations. These areas can be automatically assigned to the sorting electronics of the flow cytometer so that the real-time physical separation of particles of interest can be sorted. This automated process can be important when separating high volumes of specific cell types for culturing, transfection, insemination, biochemical recombination, protein display, etc. using a flow cytometer. .

A binning transform can be used to store the population of particles in the memory of the additional signal processor (s). View data on statistical characteristics of these populations, such as mean, standard deviation, skewness and separation,
It is possible to return to the first signal processor, which can be a workstation for storage or retrieval. Therefore, offloading this task to additional signal processors may improve the performance of the workstation.

The method described above and in Appendix A may store raw signal data in a memory storage element. Cost considerations often preclude this feature on analog systems. Storing raw or original signal data also complies with Good Manufacturing Practices in that the original signal data can be retrieved if the transformed data is operated incorrectly.
Preserving the original signal data and replicating the original signal data for subsequent processing can preserve elements of the original raw signal data that may be lost by digital "roofing" or "flooring." This may allow the original signal to be retrieved and data backtracked for FDA requirements and signal reanalysis.

Referring now to FIG. 2, a preferred embodiment of the hardware is shown for application of the present invention with a MoFlo® flow cytometer. As can be appreciated, a further signal processor (17) can be located inside or outside the center of the instrument. Each compensating conversion operation (based on the example above) may require a minimum data memory size of 12 bits or wider, 56 kilowords. At a minimum, TBD kilowords of I / O memory space may also be required. Various CPLD / FPGA or digital signal processing Von N
Euman and Harvard programs, data, I / O architectures, etc. can be used to implement the compensation conversion algorithm as specified above.

An additional processor (17) helps to improve parallelism of operations,
This allows for speed conversions that were previously unattainable. This increased processing power enables algebraic and near transcendental behavior. Transcendental motions can be considered to be motions that require an infinite number of steps. However, extremely fast processing speeds may provide infinite approximations that are feasible and almost unchanged from exact calculations.

As can be readily understood from the above description, the basic idea of the invention can be implemented in various ways. The present invention relates to both signal processing techniques and devices for achieving proper signal processing. In the present application, processing techniques are disclosed as part of the illustrated results achieved by the various devices described and as steps specific to use. These processing techniques are simply the natural consequence of using the device as intended and described. Further, while disclosing some devices, it should be understood that they not only achieve a particular method, but can be modified in multiple ways. Importantly, with respect to all the above description, it should be understood that all these aspects are covered by this disclosure.

The disclosure contained in this provisional application is intended to serve as a basic description. The reader should be aware that a particular discussion may not explicitly describe all possible embodiments, and many changes are implied. Moreover, this particular discussion may not fully explain the generic nature of the invention, how each feature or element may actually be expanded into its broader function or many variations of another or equivalent element. It cannot be explicitly stated whether it can be represented. Again, these are implicitly included in this disclosure. In the present invention, which is described in function-oriented terms, each aspect of functionality is accomplished by a device, subroutine, or program. Not only may device claims be included for the devices described, but method claims or process claims may also be included to accomplish the functions performed by the invention and each element. obtain. Neither the description nor the terms are intended to limit the scope of the claims included herein.

Furthermore, it is possible to achieve each of the various elements of the invention and the claims in different ways. This disclosure includes each such modification, modification of one embodiment of any apparatus embodiment, embodiment of a method or process, or mere modification of any of these elements. Should be understood as a thing. In particular, since the disclosure is related to the elements of the invention, the words corresponding to each element-even if only the function or result obtained from that element-is the same-of the corresponding device. It should be understood that it may be represented by terms or method terms. Such equivalent, broader, and more general terms should be considered as included in the description of each element or action. Such terms may be used as alternatives to the implicit, broad terminology to which the invention is related when it is desired to clarify the terminology. It is to be understood that this is merely an example, and that all actions may be represented as a means of receiving the action or as an element causing the action. Similarly, each physical element in the disclosure should be understood to include the disclosure of the action facilitated by the physical element. By way of example only, for this last aspect, the disclosure of "processor" -whether or not explicitly mentioned-includes the disclosure of the term "processing." Should be understood as a thing. Conversely, where there is only disclosure of the work of "processing," such disclosure should be understood to encompass the disclosure of "processor" and "processing" means as well. Such modifications and alternative terms are to be understood as being expressly included in the description herein.

Moreover, various combinations and variations of all elements or applications can be generated and presented. All of these combinations and modifications can be made to optimize performance in a particular application.

Any enforcement of any law, statute, rule, or regulation mentioned herein for a patent, or any patent, published document, or other reference mentioned for a patent in this application is hereby incorporated by reference. Specifically, US patent application Ser. No. 60 / 160,719 is hereby incorporated by reference as if including all its drawings or appendices. Each of the references listed in the references table below is incorporated by reference.

[0074]

[Table 1]

[0075]

[Table 2]

[0076]

[Table 3] In addition, for each term used, unless the usage of each term in this application conflicts with that found in common dictionaries, the meaning of each term is its meaning and all definitions, alternative terms and synonyms (e.g., , Random House Webs
ter's Unmerged Dictionary, second e
The one described in the section. The dictionary is used for reference. ) Should be understood as including definitions found in common dictionaries. However, for each of the above, among such statements, the contents that are considered to be contradictory to the patent content of the present invention (singular or plural), or the information incorporated by reference as such references, It is not explicitly regarded as being made by the applicant (s) of this application. In addition, the term “comprise” or variations thereof (eg, “comprises” or “co”, unless the context implies otherwise).
"including" is intended to include an element or step or a group of elements or steps described and exclude any other element or step or group of elements or steps. Should be understood. Such terms should be construed in their broadest form so as to give the applicant the broadest inclusive scope permitted by law in countries such as Australia.

Applicant (s) should therefore be understood as having at least a basis for claiming: , I) each of the processing devices or subroutines disclosed and described herein, ii) the related methods disclosed and described, iii) each of these devices and methods similar, corresponding to, or even Of devices and methods of iv)
Alternative Designs to Achieve Each of the Disclosed and Described Functions; v) Alternative Designs and Alternative Methods to Achieve Each of the Disclosed and Illustrated Functions Shown Implicitly; Features, components and steps illustrated as inventions, vii) applications enhanced by the various disclosed systems or components, viii) products produced by such systems or components, ix) Methods and apparatus substantially as described herein above and in reference to any of the examples accompanying this specification, x) various combinations and permutations of each of the disclosed elements. , X
i) processes performed with or on the aid of the computer described elsewhere in the above description, xiii) programmable devices referred to everywhere in the above, xiii) digitally readable memory A memory encoded with data for issuing instructions to a processor, including means or elements that function as described anywhere above, xiv) a computer disclosed and described herein, xv) Individual or combined subroutines and programs disclosed and described herein, xvi) disclosed and related methods, xvii) similar and equivalent to each of these systems and methods, and even such A variant implying a system and method, xvii
i) an alternative design to achieve each of the disclosed and described functions, xix) an alternative design and alternative method to achieve each of the disclosed and implied functions illustrated. xx) each of the programmable functions, components, and steps presented as separate and independent inventions, and xxi)
Various combinations and permutations of each of the above.

[Brief description of drawings]

FIG. 1 shows a schematic cross-sectional view of a blood flow meter embodiment of the present invention showing various features combined.

[Fig. 2]   FIG. 2 schematically shows the hardware of the embodiment of the present invention.

─────────────────────────────────────────────────── ─── Continuation of front page (51) Int.Cl. ⁷ Identification code FI theme code (reference) G01N 21/64 G01N 21/64 F 33/48 33/48 M (81) Designated country EP (AT, BE, CH, CY, DE, DK, ES, FI, FR, GB, GR, IE, IT, LU, MC, NL, PT, SE), OA (BF, BJ, CF, CG, CI, CM, GA, GN, GW, ML, MR, NE, SN, TD, TG), AP (GH, GM, KE, LS, MW, MZ, SD, SL, SZ, TZ, UG, ZW), EA (AM, AZ , BY, KG, KZ, MD, RU, TJ, TM), AE, AG, AL, AM, AT, AU, AZ, BA, BB, BG, BR, BY, BZ, CA, CH, CN, R, CU, CZ, DE, DK, DM, DZ, EE, ES, FI, GB, GD, GE, GH, GM, HR, HU, ID, IL, IN, IS, JP, KE, KG, KP , KR, KZ, LC, LK, LR, LS, LT, LU, LV, MA, MD, MG, MK, MN, MW, MX, MZ, NO, NZ, PL, PT, RO, RU, SD, SE, SG, SI, SK, SL, TJ, TM, TR, TT, TZ, UA, UG, US, UZ, VN, YU, ZA, ZW (72) Inventor Purcell, Paul Berkeley United States Colorado 80525, Foot Collins, Innovation Drive 4850, Sitemation, Incorporated (72) Inventor Malakowski, George United States Colorado 80525, Foot Collins, Innovation Drive 4850, Sitemation, Incorporated (72) Inventor Ottenberg, Matthias Jay. United States Colorado 80525, Photo Collins, Innovation Drive 4850, Sitemation, Incorporated F-term (reference) 2G043 AA03 AA04 BA16 CA03 CA06 DA02 EA01 EA14 GA07 GB19 KA09 LA02 NA05 NA06 2G045 CB01 FA11 FB12 JA01 JA20 2G059 A08 2G059 A08 DD12 EE02 GG01 KK01 MM09 MM10 PP04 4D054 GA01 GA10 GB06

Claims (155)

[Claims] 1. A method for measuring flow cells, comprising: a. Establishing a fluid stream, b. Introducing particles into the fluid stream, c. Agitating the fluid stream; d. Detecting a first occurrence associated with at least one particle, and e. Generating a first signal, f. Creating data from the first signal; g. Detecting at least one further occurrence associated with the at least one particle, and h. Generating at least one additional signal, i. Creating data from the at least one additional signal, j. Processing data from the first signal; k. Processing data from the at least one additional signal; l. Applying at least one transform operation to the processed data from the first signal; m. Applying at least one transform operation to the processed data from the at least one additional signal; n. Compensating for at least one parameter separated by the first occurrence and the at least one further occurrence; o. Distinguishing the first occurrence from the at least one further occurrence based on at least one compensated parameter; p. Assigning the at least one particle to a classification, q. Separating the assigned particles, r. Collecting the assigned particles by taxonomy. 2. The step of detecting a first occurrence associated with the at least one particle and the step of detecting at least one further occurrence associated with the at least one particle detect an occurrence associated with one particle. The method for measuring flow cells according to claim 1, comprising the step of: 3. The method of detecting a first occurrence associated with the at least one particle and detecting at least one further occurrence associated with the at least one particle comprises detecting an occurrence associated with at least two particles. The flow cytometric method according to claim 1, comprising a detecting step. 4. The flow cytometric method according to claim 2, wherein the step of detecting the occurrence associated with the one particle includes the step of detecting continuous occurrence. 5. The flow cytometry method of claim 3, wherein detecting the occurrence associated with the at least two particles comprises detecting continuous occurrence. 6. The flow cytometric method according to claim 4, wherein the step of detecting the occurrences associated with the one particle includes the step of detecting parallel occurrences. 7. The flow cytometric method of claim 5, wherein detecting occurrences associated with the at least two particles comprises detecting parallel occurrences. 8. The flow cytometric method of claim 2, wherein detecting the occurrence associated with the one particle comprises detecting occurrence associated with the same parameter. 9. The flow cytometric method of claim 2, wherein detecting the occurrence associated with the one particle comprises detecting occurrence associated with at least two parameters. 10. The flow cytometric method of claim 3, wherein detecting an incident associated with the at least two particles comprises detecting an incident associated with the same parameter. 11. The flow cytometric method of claim 3, wherein detecting the occurrence associated with the at least two particles comprises detecting occurrence associated with the at least two parameters. 12. The flow of claim 1, wherein the steps of generating data from the first signal and generating the at least one additional signal include generating a channel of information. Cell measurement method. 13. The flow of claim 1, wherein generating data from the first signal and generating the at least one additional signal comprises generating a plurality of channels of information. Cell measurement method. 14. The step of generating data from the first signal and the step of generating the at least one additional signal include the step of generating a signal at a rate of at least 10,000 per second. Item 1. The flow cell measurement method according to Item 1. 15. Separating the distinguished components from the substance comprises: a. Encapsulating the distinguished components in a droplet, b. Collecting the droplets having the distinguished classification of components in a container, the flow cytometric method according to claim 1. 16. The method of flow cytometry of claim 15, wherein the step of collecting the droplets having the differentiated component classifications in a container occurs at a rate of at least 1,000 per second. 17. The step of applying said compensation information to processed data from a first signal and processed data from at least one further signal,
The flow cytometry method of claim 1, comprising performing a complex number operation on the processed data from the first signal and the processed data from the second signal. 18. The method of claim 17, wherein performing the complex operation on the processed data from the first signal and the processed data from the second signal comprises performing an algebraic operation. Flow cell measurement method. 19. The step of performing the algebraic operation comprises: a. Applying a parameter-compensating transform to the first signal and the at least one further signal; b. Producing a first compensated signal and at least one further compensated signal, c. 19. A method of flow cytometry according to claim 18, comprising comparing the first compensated signal and the at least one further compensated signal. 20. The method of claim 19, wherein comparing the first compensated signal and the at least one further compensated signal comprises minimizing a parameterized characteristic. Flow cell measurement method. 21. Comparing the first compensated signal with the at least one further compensated signal comprises minimizing the at least two different parameterized characteristics. Item 21. The flow cell measurement method according to Item 19. 22. The method of flow cytometry according to claim 20, wherein the step of minimizing the characteristics separated by the same parameter includes the step of reducing spectral overlap. 23. The flow cytometric method of claim 21, wherein minimizing the at least two different parameterized characteristics comprises reducing spectral overlap. 24. The flow cytometric method of claim 22, wherein the step of minimizing the one parameterized characteristic comprises the step of substantially aligning successive events in time. 25. The method of claim 23, wherein the step of minimizing the at least two different parameter-separated properties comprises the step of substantially aligning successive events in time. . 26. The flow cytometry of claim 1, further comprising processing data from the first signal and data from the one additional signal with at least one additional signal processor. Method. 27. The method of claim 26, wherein using the at least one additional signal processor comprises using the at least one additional signal processor in parallel with the first signal processor. 28. The step of using at least one further signal processor in parallel with the first signal processor comprises the first signal processor and the second signal processor.
28. The flow cytometry method according to claim 27, comprising the step of simultaneously using the signal processor of. 29. The flow cytometry method according to claim 28, wherein the step of simultaneously using the first signal processor and the second signal processor includes the step of registering a usage of a parallel linear code. 30. The flow cytometric method according to claim 29, wherein the step of registering the usage of the parallel linear code includes the step of registering a digital parallel linear code. 31. The method of claim 3, further comprising applying a compensation matrix.
The method for measuring flow cells according to 0. 32. The flow cytometric method of claim 31, further comprising reducing execution time using compensation matrix symmetric reduction. 33. a. Assaying original data from the first signal and the at least one additional signal in a memory storage element; b. Deriving original data from the first signal and the at least one further signal stored in the memory storage element without modification, the flow cytometric method of claim 1. 34. a. Replicating the original data from the first signal and the at least one further signal; b. Processing the duplicate signal, c. 34. The method of claim 33, further comprising the step of translating the first occurrence and the at least one further occurrence using a processed replication signal. 35. The method of flow cytometry of claim 34, further comprising the step of populating information in said at least one additional signal processor. 36. a. A fluid stream, b. At least one particle contained in the fluid stream; c. An oscillator and d. A first sensor and e. At least one signal generator and f. Data from the signal generator associated with the first occurrence, g. Data from the signal generator associated with at least one further occurrence, h. A signal processor, i. A transform operation applied to at least a portion of the data from the signal generator associated with the first generation, j. A transform operation applied to at least a portion of the data from the signal generator associated with a second occurrence, k. A compensated parameter separated by the first occurrence and the second occurrence; l. A particle distinguishing element, n. A particle assignment element, and o. A particle separator, p. And at least one container in which the separated particles are collected. 37. The signal processor is at least a portion of the data from a signal generator associated with the first occurrence and at least a portion of the data from a signal generator associated with the second occurrence. The complex number conversion operation is performed on the.
Flow cytometer described in. 38. The flow cytometer of claim 37, further comprising at least one additional signal processor. 39. The at least one further signal processor includes at least a portion of the data from a signal generator associated with the first occurrence and the data from a signal generator associated with the second occurrence. 39. The flow cytometer of claim 38, wherein the complex transformation operation is performed on at least a portion of the flow cytometer. 40. The flow cytometer of claim 39, wherein the at least one additional signal processor is a digital signal processor. 41. The digital signal processor further comprises a responsive memory element, wherein original data from the signal generator may be stored.
Flow cytometer described in. 42. The flow cytometer of claim 41, further comprising an original data retrieval element. 43. The flow cytometer of claim 42, further comprising an original data replication element. 44. The flow cytometer of claim 43, further comprising a storage element. 45. A method for measuring flow cells, comprising: a. Establishing a fluid stream, b. Agitating the fluid stream; c. Detecting an incident associated with the fluid stream, d. Generating a signal from the generation, e. Processing the signal using a first signal processor; f. Processing the signal using at least one additional signal processor; g. Superimposing outputs from the first signal processor and the at least one further signal processor, h. Applying superposed outputs to classify the occurrences. 46. The method of claim 45, wherein processing the signal with at least one additional signal processor comprises using the at least one additional signal processor in parallel with the first signal processor. Flow cell measurement method. 47. The step of using at least one additional signal processor in parallel with the first signal processor processes at least a portion of the signal using the first signal processor and the second signal processor simultaneously. The flow cytometric method according to claim 46, which comprises steps. 48. The step of simultaneously processing at least a portion of the signal with the first signal processor and the second signal processor comprises registering parallel linear code usage. The method for measuring flow cells according to 1. 49. The flow cytometric method of claim 48, wherein the step of registering the usage of the parallel linear code comprises the step of registering the usage of the parallel digitized code. 50. a. Performing a compensating transformation on the signal;   b. Generating a compensated signal;   The flow cytometry method according to claim 49, further comprising: 51. The flow cytometry method of claim 50, wherein performing a compensatory transformation on the signal comprises compensating for signal parameters. 52. The flow cytometry method of claim 51, wherein compensating for the one parameter comprises compensating for an analog signal. 53. The flow cytometry method of claim 50, wherein compensating the analog signal comprises minimizing a variation selected from the group consisting of phase and shape. 54. The step of performing a compensating transformation on said signal comprises at least two.
51. The method of flow cytometry of claim 50, comprising compensating for two different parameters. 55. The flow cytometric method of claim 54, wherein compensating for the at least two different parameters comprises minimizing a characteristic separated by the at least two different parameters. 56. The flow cytometric method of claim 55, wherein the step of minimizing the at least two different parameter-separated characteristics comprises the step of reducing spectral overlap. 57. The flow cytometric method of claim 50, wherein the step of performing the compensation transformation comprises applying an algebraic operation. 58. The method of claim 5, further comprising applying a compensation matrix.
7. The flow cell measurement method according to 7. 59. The flow cytometry method of claim 58, further comprising using a symmetrical reduction in the compensation matrix to minimize the execution time of performing a compensation transformation on the signal. 60. The flow cytometric method of claim 45, wherein performing a compensatory transform on the signal comprises performing a compensatory transform on a signal generated from at least 10,000 occurrences per second. . 61. The method of flow cytometry of claim 45, further comprising the step of populating the information of said at least one additional signal processor. 62. a. Assaying the original data from the signal in a memory storage element, b. 47. The flow cytometry method of claim 45, further comprising deriving original data from the signal stored in the memory storage element without modification. 63. a. Replicating the original data from the signal,   b. Processing the duplicated signal,   c. Translating said occurrence using the processed duplicated signal;   The flow cytometry method according to claim 45, further comprising: 64. a. A fluid stream, b. A sensor responsive to development, c. At least one signal generator coupled to the sensor; d. A first signal processor for performing operations on the signal data; e. A second signal processor for performing an operation on the signal data; f. A compensated parameter output from the second signal processor returned to the first signal processor; g. A responsive particle discriminating element to the compensated parameter output. 65. a. A particle assignment element,   b. A particle separator,   c. At least one container in which the separated particles are collected   65. The flow cytometer of claim 64, further comprising: 66. A method of measuring flow cells, comprising: a. Establishing a fluid stream, b. Generating a first signal associated with the fluid stream, c. Generating at least one additional signal associated with the fluid stream; d. Applying a parametric compensation transform to the first signal and the at least one further signal; e. Generating a first compensated signal and at least one further compensated signal, f. Comparing the first compensated signal and the at least one further compensated signal; g. Classifying an occurrence based on a comparison of the first compensated signal and the at least one further compensated signal. 67. The flow cytometric method of claim 66, further comprising applying a compensation matrix to the output from the parameter compensation transform. 68. The flow cytometric method of claim 67, further comprising the step of using symmetrical reduction in the compensation matrix to reduce the execution time. 69. The flow cytometry method of claim 68, further comprising digitizing the first signal and the at least one additional signal. 70. The flow of claim 69, further comprising processing the first signal and the at least one additional signal with at least one additional signal processor in parallel with the first signal processor. Cell measurement method. 71. The step of using at least one additional signal processor in parallel with the first signal processor processes at least a portion of the signal using the first signal processor and the second signal processor simultaneously. 71. The method for measuring flow cytometry according to claim 70, which comprises steps. 72. The step of simultaneously processing at least a portion of the signal with the first signal processor and the second signal processor comprises registering a usage of a parallel digital linear code. 71. The method for measuring flow cells according to item 71. 73. The method of compensating transforming the first signal and the at least one additional signal comprises performing compensating transform at a rate of at least 10,0000 transforms per second. 68, 69, 70, 71
Or the flow cell measuring method according to any one of 72. 74. The flow cytometric method of claim 73, further comprising the step of populating information in said at least one additional signal processor. 75. a. Analyzing original data from the first signal and the at least one further signal in a memory storage element; b. 75. The flow cytometry method of claim 74, further comprising: unaltering original data from the first signal and the at least one additional signal stored in the memory storage element. 76. a. Duplicating the original data from the first signal and the at least one further signal; b. Processing duplicate signals, c. The method of claim 75, further comprising translating the occurrence using the processed duplicated signal. 77. a. A fluid stream, b. A sensor responsive to the occurrence, c. At least one signal generator connected to the sensor; d. A first signal generated by the at least one signal generator; e. At least one additional signal generated by the at least one signal generator; f. A signal processor responsive to the first signal and the at least one additional signal; g. A transformation operation performed on the first signal and the at least one further signal; h. A compensated signal comparison element, i. A particle discrimination element responsive to the compensated signal comparison element. 78. a. Establishing a fluid stream,   b. Disrupting the fluid stream;   c. Detecting an incident associated with the fluid stream,   d. Generating a signal from the generation,   e. Performing a complex operation on the signal,   f. Performing flow cytometry using the output of the complex operation;   A method for measuring flow cells, comprising: 79. The flow cytometry method of claim 78, wherein the step of performing a complex operation on the signal includes the step of performing an algebraic operation on the signal. 80. The flow cytometry method according to claim 79, wherein the step of performing algebraic calculation on the signal includes a step of performing compensation conversion on the signal. 81. The flow cytometry method according to claim 80, wherein the step of performing compensation conversion on the signal includes the step of compensating one parameter. 82. The flow cytometry method of claim 81, wherein compensating for the one parameter comprises compensating for a serial analog signal. 83. The flow cytometry method of claim 80, wherein the step of compensating and transforming the signal comprises compensating for at least two parameters. 84. Compensating the at least two parameters
84. The flow cytometric method of claim 83, comprising compensating for at least two serial analog signals. 85. The flow cytometric method of claim 81 or 84, wherein compensating the serial analog signal comprises minimizing a variation selected from the group consisting of phase and shape. 86. The flow cytometric method of claim 80, wherein the step of performing the compensating transform comprises the step of minimizing common features. 87. The flow cytometric method of claim 80, wherein the step of minimizing the common feature comprises the step of reducing spectral overlap. 88. The flow cytometric method according to claim 80, wherein the step of performing the compensation transformation includes the step of substantially arranging temporally consecutive events. 89. The method of claim 80, further comprising using a compensation matrix.
The method for measuring flow cells according to 1. 90. The flow cytometric method of claim 89, further comprising reducing execution time using compensation matrix symmetry reduction. 91. The method of flow cytometry of claim 78, further comprising processing the data from the signal with at least one additional signal processor. 92. The flow cytometry method of claim 91, wherein the step of using the at least one additional signal processor comprises using the at least one additional signal processor in parallel with the first signal processor. 93. The step of using the at least one additional signal processor in parallel with the first signal processor comprises: using the first signal processor and the second signal processor.
93. The method of measuring flow cytometry according to claim 92, comprising the step of simultaneously using the signal processor of. 94. Simultaneously using the first signal processor and the second signal processor comprises recording parallel line code usage.
The flow cell measuring method according to claim 93. 95. The flow cytometric method of claim 94, wherein recording the usage of the parallel line code comprises recording a digital parallel line code. 96. a. Analyzing original data from the first signal and the at least one further signal in a memory storage element; b. 92. The flow cytometry method of claim 91, further comprising: unaltering original data from the first signal and the at least one additional signal stored in the memory storage element. 97. a. Duplicating the original data from the first signal and the at least one further signal; b. Processing duplicate signals, c. 97. The flow cytometric method of claim 96, further comprising: translating the first occurrence and the at least one further occurrence using a processed duplicated signal. 98. The flow cytometric method of claim 97, further comprising the step of populating information in said at least one additional signal processor. 99. a. A fluid stream, b. A sensor responsive to the occurrence, c. At least one signal generator connected to the sensor; d. A signal generated by the at least one signal generator; e. A signal processor responsive to the first signal and the at least one further signal; f. Complex operations used on the signal, g. A flow cytometer with a compensation signal. 100. a. Establishing a fluid stream,   b. Entraining substances in the fluid stream;   c. Disrupting the fluid stream;   d. Detecting an incident associated with the substance;   e. Generating a signal from the generation,   f. Digitizing the signal;   g. Translating the occurrence using the digital signal;   A flow cytometry method including 101. The flow cytometric method of claim 100, further comprising the step of detecting continuous occurrence. 102. The flow cytometric method of claim 100, further comprising detecting a plurality of parallel consecutive occurrences. 103. The method of flow cytometry according to claim 101 or 102, wherein the continuous generation is at a rate of at least 1,000 per second. 104. The flow cytometric method of claim 103, further comprising storing the digital signal in a memory storage element. 105. The flow cytometry method of claim 104, further comprising the step of duplicating the digital signals stored in the memory storage element. 106. The flow cytometry method of claim 105, further comprising processing the duplicate digital signal with a first signal processor. 107. The flow cytometry method of claim 106, further comprising processing the duplicate digital signal with at least one additional signal processor. 108. The step of using said at least one further signal processor in parallel with said first signal processor comprises simultaneously using said first signal processor and said second signal processor 108. The flow cytometry method of claim 107, comprising the step of treating at least a portion. 109. The step of simultaneously processing at least a portion of a digital signal using the first signal processor and the second signal processor comprises recording the usage of a digital parallel line code. 108. The flow cell measurement method according to 108. 110. The flow cytometric method of claim 109, further comprising the step of performing a complex operation on the digital signal. 111. The flow cytometric method of claim 110, wherein the step of performing a complex operation on the digital signal includes the step of performing an algebraic operation on the digital signal. 112. The flow cytometric method according to claim 111, wherein the step of performing algebraic calculation on the digital signal includes the step of performing compensation conversion on the signal. 113. The flow cytometry method according to claim 112, wherein the step of compensating and converting the signal includes the step of compensating one parameter. 114. The flow cytometry method of claim 113, wherein compensating for the one parameter comprises compensating for a serial analog signal. 115. The flow cytometric method of claim 114, wherein compensating the serial analog signal comprises minimizing a variation selected from the group consisting of phase and shape. 116. The flow cytometric method of claim 112, wherein the step of compensating transforming the signal comprises compensating for at least two different parameters. 117. The method of flow cytometry of claim 116, wherein compensating for the at least two different parameters comprises minimizing features common to the at least two different parameters. 118. The flow cytometric method of claim 117, wherein minimizing the features common to the at least two different parameters comprises reducing spectral overlap. 119. The flow cytometric method of claim 118, further comprising the step of generating a compensation signal. 120. The flow cytometric method of claim 119, further comprising the step of reprocessing the digital signal. 121. The flow cytometric method of claim 120, wherein the step of translating generation using the digital signal comprises the step of using the compensation signal to distinguish components of the substance. 122. The flow cytometric method of claim 121, further comprising the step of classifying the discriminating components. 123. The flow cytometric method of claim 122, further comprising the step of separating the distinguishing component from the substance. 124. Separating the distinguishing component from the substance comprises: a. Encapsulating the distinguishing component in a droplet, b. The step of collecting a droplet having a distinguishing component belonging to one class in a container, the flow cytometric method according to claim 123. 125. The flow cytometric method of claim 124, wherein the step of collecting the droplets having the distinguishing component belonging to one class in a container occurs at a rate of at least 1000 per second. 126. a. A fluid stream, b. Substances entrained in the fluid stream, c. A sensor responsive to an incidental occurrence of the entrained material in the fluid stream; d. At least one signal generator connected to the sensor; e. Signal data generated by the at least one signal generator; f. A signal data digitizer, g. A digital signal processor responsive to the digital signal. 127. a. Establishing a fluid stream,   b. Detecting an incident associated with the fluid stream,   c. Generating an original signal from the generation,   d. Storing the original signal in a memory storage element;   e. Duplicating the original signal,   f. Processing duplicate signals,   g. Translating the occurrence using the processed duplicate signal;   A method for measuring flow cells, comprising: 128. The flow cytometry method of claim 127, further comprising retrieving the original signal stored in the memory storage element without modification. 129. further comprising the step of reprocessing the duplicate signal.
The flow cell measuring method according to claim 128. 130. The flow cytometric method of claim 129, further comprising the step of reprocessing the extracted original signal. 131. The flow cytometry method of claim 130, further comprising entraining a substance within the fluid stream. 132. The flow of claim 131, wherein translating the occurrence with the processed duplicated signal comprises distinguishing a component of the substance using the processed duplicated signal. Cell measurement method. 133. The flow cytometric method of claim 132, further comprising the step of classifying the discriminating component. 134. The flow cytometric method of claim 133, further comprising the step of separating the distinguishing component from the substance. 135. Separating the distinguishing component from the substance comprises: a. Encapsulating the distinguishing component in a droplet, b. The step of collecting a droplet having a distinguishing component belonging to one class in a container, the flow cytometric method according to claim 134. 136. The flow cytometric method of claim 135, wherein the step of collecting the droplets having the distinguishing component belonging to one class in a container occurs at a rate of at least 1000 per second. 137. The flow cytometric method of claim 127, wherein detecting an incident associated with the fluid stream comprises detecting a continuous occurrence. 138. The flow cytometric method of claim 127, wherein detecting an incident associated with the fluid stream comprises detecting a plurality of parallel consecutive occurrences. 139. The flow cytometric method of claim 138, wherein the continuous occurrence has a rate of at least 10,000 per second. 140. The flow cytometric method of claim 127, further comprising digitizing the original data from the generation. 141. The flow cytometry method of claim 140, further comprising processing the duplicate digital signal with at least one additional signal processor. 142. The step of using the at least one further signal processor in parallel with the first signal processor comprises: simultaneously using the first signal processor and the at least one further signal processor of the overlapping digital signals. 144. The flow cytometry method of claim 141, comprising the step of treating at least a portion. 143. The step of simultaneously processing at least a portion of a duplicate digital signal using the first signal processor and at least one further signal processor comprises recording the usage of a digital parallel line code.
The flow cell measuring method according to claim 142. 144. The flow cytometric method of claim 141, further comprising the step of performing a complex operation on the duplicated digital signal. 145. The flow cytometric method of claim 144, wherein the step of performing a complex operation on the overlapping digital signal includes the step of performing an algebraic operation on the overlapping digital signal. 146. The flow cytometric method of claim 145, wherein the step of performing an algebraic operation on the overlapped digital signal includes the step of performing a compensation conversion on the overlapped digital signal. 147. The flow cytometric method of claim 146, wherein the step of performing compensatory conversion on the duplicated digital signal includes the step of compensating for one parameter. 148. The flow cytometric method of claim 147, wherein compensating for said one parameter comprises compensating for serial digital analog signals. 149. The method of flow cytometry of claim 148, wherein compensating for the serial analog signal comprises minimizing a variation selected from the group consisting of phase and shape. 150. The flow cytometric method of claim 146, wherein the step of compensating transforming the signal comprises compensating for at least two different parameters. 151. The flow cytometry method of claim 150, wherein compensating for the at least two different parameters comprises minimizing a feature common to the at least two different parameters. 152. The flow cytometric method of claim 151, wherein minimizing the features common to the at least two different parameters comprises reducing spectral overlap. 153. a. A fluid stream,   b. Occurrences associated with the fluid stream,   c. A sensor responsive to the occurrence associated with the fluid stream;   d. At least one signal generator connected to the sensor;   e. Signal data generated by the at least one signal generator;   f. A memory element for storing the signal data,   g. A stored signal data retrieval element,   h. A stored signal duplicator,   i. At least one signal processor responsive to duplicate signals and   A flow cytometer. 154. A method according to any of the embodiments substantially as set forth in claims 1-153 and attached. 155. Apparatus according to any of the embodiments substantially as set forth in claims 1-154 and attached.