U.S. patent number RE46,559 [Application Number 15/438,423] was granted by the patent office on 2017-09-26 for enhancing flow cytometry discrimination with geometric transformation.
This patent grant is currently assigned to Beckman Coulter, Inc.. The grantee listed for this patent is Beckman Coulter, Inc.. Invention is credited to Kenneth Michael Evans, George C. Malachowski, Paul Barclay Purcell, Edward Allan Stanton.
United States Patent |
RE46,559 |
Malachowski , et
al. |
September 26, 2017 |
Enhancing flow cytometry discrimination with geometric
transformation
Abstract
In flow cytometry, particles (2) can be distinguished between
populations (8) by combining n-dimensional parameter data, which
may be derived from signal data from a particle, to mathematically
achieve numerical results representative of an alteration (48). An
alteration may include a rotational alteration, a scaled
alteration, or perhaps even a translational alteration. Alterations
may enhance separation of data points which may provide real-time
classification (49) of signal data corresponding to individual
particles into one of at least two populations.
Inventors: |
Malachowski; George C.
(Melbourne, AU), Purcell; Paul Barclay (Ouray,
CO), Stanton; Edward Allan (Longmont, CO), Evans; Kenneth
Michael (College Station, TX) |
Applicant: |
Name |
City |
State |
Country |
Type |
Beckman Coulter, Inc. |
Brea |
CA |
US |
|
|
Assignee: |
Beckman Coulter, Inc. (Brea,
CA)
|
Family
ID: |
1000002634146 |
Appl.
No.: |
15/438,423 |
Filed: |
February 21, 2017 |
PCT
Filed: |
July 27, 2005 |
PCT No.: |
PCT/US2005/026673 |
371(c)(1),(2),(4) Date: |
July 16, 2009 |
PCT
Pub. No.: |
WO2006/015056 |
PCT
Pub. Date: |
February 09, 2006 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
Issue Date |
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60591957 |
Jul 27, 2004 |
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Reissue of: |
11632870 |
Jul 27, 2005 |
9134220 |
Sep 15, 2015 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G01N
15/1436 (20130101); G01N 15/1475 (20130101); G01N
15/1468 (20130101); G01N 15/1429 (20130101); G01N
33/5005 (20130101); G01N 15/1468 (20130101); G01N
33/5005 (20130101); G01N 15/1475 (20130101); G01N
2015/149 (20130101); G01N 2015/0065 (20130101); G01N
2015/1006 (20130101) |
Current International
Class: |
G01N
33/00 (20060101); G01N 15/14 (20060101); G05B
21/00 (20060101); G01N 33/50 (20060101); G01N
31/00 (20060101); G01N 33/48 (20060101) |
References Cited
[Referenced By]
U.S. Patent Documents
Foreign Patent Documents
|
|
|
|
|
|
|
19549015 |
|
Mar 1997 |
|
DE |
|
025296 |
|
Mar 1981 |
|
EP |
|
0160201 |
|
Nov 1985 |
|
EP |
|
0468100 |
|
Jan 1992 |
|
EP |
|
0781985 |
|
Jul 1997 |
|
EP |
|
0786079 |
|
May 2003 |
|
EP |
|
2699678 |
|
Dec 1992 |
|
FR |
|
61139747 |
|
Jun 1986 |
|
JP |
|
61159135 |
|
Jul 1986 |
|
JP |
|
2024535 |
|
Jan 1990 |
|
JP |
|
4-126066 |
|
Apr 1992 |
|
JP |
|
4-126081 |
|
Apr 1992 |
|
JP |
|
4126064 |
|
Apr 1992 |
|
JP |
|
1056008 |
|
Nov 1983 |
|
SU |
|
1260778 |
|
Sep 1986 |
|
SU |
|
WO96/12172 |
|
Apr 1996 |
|
WO |
|
WO99/44037 |
|
Feb 1999 |
|
WO |
|
WO0032542 |
|
Jun 2000 |
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WO |
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WO01/28700 |
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Apr 2001 |
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WO |
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Other References
Mann et al, "The Use of Projections for Dimensionality Reduction of
Flow Cytometric Data," Cytometry, 5:304-307, (1984). cited by
examiner .
Denk, W., et al (1995). Two-photon molecular excitation in laser
scanning microscopy. Handbook of Biological Conical Microscopy. J.
B. Pawley, ed., Plenum Press, New York, pp. 444-458. cited by
applicant .
Garner, D. L. et al; Quantification of the X- and Y-
Chromosome-Bearing Spermatozoa of Domestic Animals by Flow
Cytometry.sup.1, Biology of Reproduction 28, pp. 312-321, (1983).
cited by applicant .
Goppert-Mayer, M. 1931,. Uber Elementarakte mit zwei
Quantensprungen nnalen der Physik, pp. 273-294. cited by applicant
.
Johnson, Lawrence A. Sex Preselection by Flow Cytometric Separation
of X and Y Chromosome-bearing Sperm based on NA Difference: a
Review, Reprod. Fertil. Dev., 1995, 7, pp. 893-903. cited by
applicant .
Manni, Jeff; (1996). Two-Photon Excitation Expands the Capabilities
of Laser-Scanning Microscopy, Biophotonics International, pp.
44-52. cited by applicant .
Melamed et al, An Historical Review of the Development of Flow
Cytometers and Sorters,, 1979, pp. 3-9. cited by applicant .
Piston. D. W., et al (1994). Two-photon-excitation fluorescence
imaging of three-dimensional calcium ion activity. Applied Optics
33: 662-669. cited by applicant .
Piston, D. W., et al. (1995). Three-dimensionally resolved NAD(P)H
cellular metabolic redox imaging of the in-situ cornea with
two-photon excitation laser scanning microscopy. J of Microscopy
178: 20-27. cited by applicant .
Skogen-Hagenson, M. J. et al; "A High Efficiency Flow Cytometer,"
The Journal of Histochemistry and Cytochemistry, vol. 25, No. 7,
pp. 784-789, 1977, USA. cited by applicant .
Van Dilla et al. (Eds.)Flow Cytometry: Instrumentation and Data
Analysis,, "Overview of Flow Cytometry: Instrumentation and Data
Analysis" by Martin Van Dilla, 1985, pp. 1-8. cited by applicant
.
Williams, R. M. et al. (1944). Two photon molecular excitation
provides intrinsic 3-dimensional resolution for laser-based
microscopy and microphotochemistry. FASEB J. 8: 804-813. cited by
applicant .
McLeod, J., Eastman Kodak Company, Hawk-Eye Works, Rochester, NY,
Journal of the Optical Society of America; vol. 44, No. 8, Sep.
1953, pp. 592-597. cited by applicant .
Pinkel, D., "Flow Chambers and Sample Handling," Flow Cytometry:
Instrumentation and Data Analysis, pp. 77-128 (1985). cited by
applicant.
|
Primary Examiner: Diamond; Alan
Attorney, Agent or Firm: K&L Gates LLP Cullman; Louis
C.
Parent Case Text
CROSS-REFERENCES TO RELATED APPLICATIONS
This application is the United States National Stage of
International Application PCT/US2005/026673, filed 27 Jul. 2005,
which claims the benefit of the filing date of and right of
priority to U.S. Provisional Application No. 60/591,957, filed 27
Jul. 2004, both such applications hereby incorporated by reference
in their entirety.
Claims
We claim:
1. A method of operating a flow cytometry apparatus with at least n
detectors to analyze at least two populations of particles in the
same sample, the method comprising: (a) establishing a fluid stream
in the flow cytometry apparatus with at least n detectors, the at
least n detectors including a first detector and a second detector;
(b) entraining particles from the sample in the fluid stream in the
flow cytometry apparatus; (c) executing instructions read from a
computer readable memory with a processor, the processor being in
communication with the first detector in the flow cytometer, to
detect a first signal from the first detector based on individual
particles in the fluid stream; (d) executing instructions read from
the computer readable memory with the processor, the processor
being in communication with the second detector in the flow
cytometer, to detect a second signal from the second detector based
on the individual particles in the fluid stream; (e) executing
instructions read from the computer readable memory with the
processor to convert at least the first signal and the second
signal into n-dimensional parameter data for detected particles in
the sample, wherein the n-dimensional parameter data for particles
from the at least two populations overlap in at least one of the
dimensions; (f) executing instructions read from the computer
readable memory with the processor to rotationally alter the
n-dimensional parameter data so that spatial separation of the data
from the particles from the at least two populations in the at
least one dimension that is overlapped is increased; (g) executing
instructions read from the computer readable memory with the
processor to real-time classify each of the individual detected
particles into one of a first population and a second population of
the at least two populations based on at least the rotationally
altered n-dimensional parameter data; and (h) using the real-time
classification, sorting the individual particles with the flow
cytometer.
2. The method of claim 1, further comprising: (a) executing
instructions with the processor read from the computer readable
memory to create a first dimensional altered data point by
calculating a first 1st-dimensional alteration value times a 1
st-dimensional data point summed with a second 1 st-dimensional
alteration value times a 2nd-dimensional data point summed with a
third 1 st-dimensional alteration value times a 3rd-dimensional
data point; and (b) executing instructions with the processor read
from the computer readable memory to create a second dimensional
altered data point by calculating a first 2nd-dimensional
alteration value times the 1 st-dimensional data point summed with
a second 2nd-dimensional alteration value times the 2nd-dimensional
data point summed with a third 2nd-dimensional alteration value
times the 3rd-dimensional data point.
3. The method of claim 1, wherein the rotational alteration
increases discrimination between the first population and the
second population.
4. The method of claim 1, further comprising: (a) altering the
n-dimensional parameter data by scaling the n-dimensional parameter
data; and (b) real-time classifying the n-dimensional parameter
data of each of the individual particles into one of the at least
two populations based on at least the scaled n-dimensional
parameter data.
5. The method of claim 4, further comprising (a) executing
instructions with the processor read from the computer readable
memory to create a first dimensional altered data point by
calculating a first 1st-dimensional alteration value times a 1
st-dimensional data point summed with a second 1 st-dimensional
alteration value times a 2nd-dimensional data point summed with a
third 1 st-dimensional alteration value times a 3rd-dimensional
data point; and (b) executing instructions read from the computer
readable memory with the processor to create a second dimensional
altered data point by calculating a first 2nd-dimensional
alteration value times the 1 st-dimensional data point summed with
a second 2nd-dimensional alteration value times the 2nd-dimensional
data point summed with a third 2nd-dimensional alteration value
times the 3rd-dimensional data point.
6. The method of claim 5, wherein the alteration values are based
on a zoom and tracking element and the alteration increases
discrimination between the first population and the second
population in the n-dimensional parameter data.
7. The method of claim 4, further comprising: executing
instructions read from the computer readable memory with the
processor to simultaneously rotationally alter and scale the
n-dimensional parameter data.
8. The method of claim 1 or 4, further comprising: (a) executing
instructions read from the computer readable memory with the
processor to alter the n-dimensional parameter data by translating
the n-dimensional parameter data; and (b) executing instructions
read from the computer readable memory with the processor to
real-time classify each of the individual particles into one of
said the first population and the second population based on at
least the translated n-dimensional parameter data.
9. The method of claim 8, further comprising: (a) executing
instructions read from the computer readable memory with the
processor to create a first dimensional altered data point by
calculating a first 1st-dimensional alteration value times a 1
st-dimensional data point summed with a second 1 st-dimensional
alteration value times a 2nd-dimensional data point summed with a
third 1 st-dimensional alteration value times a 3rd-dimensional
data point; and (b) executing instructions read from the computer
readable memory with the processor to create a second dimensional
altered data point by calculating a first 2nd-dimensional
alteration value times the 1 st-dimensional data point summed with
a second 2nd-dimensional alteration value times the 2nd-dimensional
data point summed with a third 2nd-dimensional alteration value
times the 3rd-dimensional data point.
10. The method of claim 9, wherein the alteration values comprise
translating of the n-dimensional parameter data with respect to a
center point of rotation.
11. The method of claim 9, wherein the alteration values are based
on an operation selected from a group consisting of rotation in
x-axis, rotation in y-axis, rotation in z-axis, translation, scale,
and perspective operations.
12. The method of claim 8, further comprising: executing
instructions read from the computer readable memory with the
processor to simultaneously rotationally alter, scale, and
translate the n-dimensional parameter data.
13. The method of claim 1, further comprising: executing
instructions read from the computer readable memory with the
processor to cause a display device to display the n-dimensional
parameter data for each of the individual particles in relation to
the at least two populations.
14. The method of claim 1, further comprising: executing
instructions read from the computer readable memory with the
processor to cause a display device to display the n-dimensional
parameter data in a Cartesian coordinate system.
15. The method of claim 14, further comprising: executing
instructions read from the computer readable memory with the
processor to cause the display device to display: (a) the first
signal on a first axis; and (b) the second signal on a second
axis.
16. The method of claim 1, further comprising: executing
instructions read from the computer readable memory with the
processor to cause a display device to display a histogram of the
n-dimensional parameter data.
17. The method of claim 1, further comprising: executing
instructions read from the computer readable memory with the
processor to cause a display device to display: (a) elliptical
shaped populations of each of the first population and the second
population, the displayed elliptical shaped populations having
non-orthogonal angles of inclination to at least one axis; and (b)
the elliptical shaped populations orthogonal to at least one
axis.
18. The method of claim 1, wherein: (a) the particles include
sperm; and (b) the first population includes an X-bearing sperm
population; and (c) the second population includes a Y-bearing
sperm population.
19. The method of claim 1, wherein the first signal and the second
signal comprises fluorescence emitted from a light emitting element
coupled with the individual particles after passing through a laser
beam.
20. The method of claim 1, further comprising: identifying a point
situated between the first population and second population when
the n-dimensional parameter data for a first plurality of particles
from the first population and a second plurality of particles from
the second population is plotted on a Cartesian coordinate system,
such that the point is positioned so that the separation of the
first population and second population is increased with respect to
one axis of the Cartesian coordinate system when the n-dimensional
parameter data for the first and second plurality of particles is
rotated about the point, and wherein rotationally altering the
n-dimensional parameter data includes rotating the n-dimensional
parameter data about the point.
21. The method of claim 1, wherein the processor is a digital
signal processor.
22. The method of claim 21, wherein the digital signal processor is
a fixed point processor.
23. The method of claim 1 wherein the instructions are assembly
language code.
Description
TECHNICAL FIELD
The present invention includes in embodiments apparatus and methods
for real-time discrimination of particles while being sorted by
flow cytometry. Specifically, embodiments of the invention may
include application of various mathematical operations to
manipulate data in real-time resulting in enhanced discrimination
between populations of particles.
BACKGROUND
One of the most important developments over the last few years has
been the application of high speed jet-in-air sorters to
discriminate particles and cells that are only subtly different. As
but one example, flow cytometry can be used to separate X from Y
bearing sperm. While it is in this context that some properties are
discussed, it should be understood that this is only one example of
a broad range of applications. Sperm sorting has been applied now
to cattle, horses and pigs and may be used with various other
animals. In this one application, the intent may be to obtain
viable and motile sperm from semen or perhaps even be to guaranteed
the sex of off-spring that are created when a sexed sperm may be
inseminated into a female of a species. The requirement may be to
improve animal husbandry. For example, in cattle where dairy is the
main product, females may be preferred or even in beef, the male
may be the desirable selection.
Subtle differences can even be quantitative, for example, sperm may
not express surface antigens that are indicators of the presence of
X or Y chromosomes. However, X bearing sperm may have a larger mass
of genetic material. A dye, such as Hoechst, may have the property
of binding to DNA. As a consequence, light emitted by X bearing
sperm, when ignited by ultra-violet laser, may be slightly brighter
and this can be used as a discrimination to sort and separate the
sperm.
Subtle differences can also be due to flow cytometer geometries as
well. In the sperm example, mammalian sperm are generally paddle
shaped and when they pass through a flow cytometer they can have a
random orientation. This orientation may obscure the differential
light coming from the X and Y bearing cells. Consequently, a
cytometer may have a specialized orienting nozzle that can use a
hydrodynamic effect to orientate the cells to a reasonable
degree.
A bivariate histogram may be collected, the parameters may be a
forward and side angle fluorescence. A population may show the
effect of orientation. A slight separation of two populations may
make a drawing of a closed contour around each population
difficult. A contour may be needed to establish a region that can
be exclusively sorted.
DISCLOSURE OF THE INVENTION
Accordingly, it is desirable to provide enhanced discrimination
between particles during flow cytometry. An object of the present
invention, in embodiments, may include applying mathematical
operations to data to allow enhanced discrimination between
populations.
Another object of the invention in embodiments may include
performing a geometric perhaps 2-dimensional transformation of flow
cytometry data so that particles can be sorted.
It may be another object of the present invention to provide in
embodiments an alteration of flow cytometry data in order to
distinguish particles between populations. This may include
rotational alterations, translation alterations, scaling
alterations and the like in various embodiments.
Naturally, further objects, goals and embodiments of the inventions
are disclosed throughout other areas of the specification and
claims.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is an illustration of a sort overview in accordance with
some embodiments of the present invention.
FIG. 2 illustrates forward and side light detection systems in
accordance with some embodiments of the present invention.
FIG. 3 is an example of a histogram of sperm sorting data prior to
rotation.
FIG. 4 is an example of a histogram of sperm sorting data after
scaling.
FIG. 5 is an example of a histogram of sperm sorting data after
rotation.
FIG. 6 is an example of a histogram of sperm sorting data after
scaling and rotation.
FIG. 7 is a conceptual depiction of a system for analyzing detected
signal data in one embodiment.
MODE(S) FOR CARRYING OUT THE INVENTION
The present invention includes a variety of aspects, which may be
combined in different ways. The following descriptions are provided
to list elements and describe some of the embodiments of the
present invention. These elements are listed with initial
embodiments, however it should be understood that they may be
combined in any manner and in any number to create additional
embodiments. The variously described examples and preferred
embodiments should not be construed to limit the present invention
to only the explicitly described systems, techniques, and
applications. Further, this description should be understood to
support and encompass descriptions and claims of all the various
embodiments, systems, techniques, methods, devices, and
applications with any number of the disclosed elements, with each
element alone, and also with any and all various permutations and
combinations of all elements in this or any subsequent
application.
Embodiments of the invention may include various methods,
apparatus, systems and the like to distinguish particles during
flow cytometry. A fluid stream (1) may be established in a flow
cytometer in which particles (2) may be entrained. In an
embodiment, particles may be sperm; however other kinds of
particles are certainly possible and all are meant to be included
in this disclosure. Particles may be coupled with a light emitting
element, for example one embodiment may include a Hoechst dye. Each
individual particle may emit a first signal and perhaps even at
least one additional signal. A detector (42) may be placed so as to
detect signals from the particles as can be understood from FIGS. 1
and 2. In embodiments, a first signal detector may detect a first
signal affiliated with an individual particle and perhaps even at
least one additional signal detector may detect at least one
additional signal affiliated with an individual particle. This may
include any kind of signal that may be in association, perhaps even
close association with an individual particle such as but not
limited to fluorescence, radiance, and the like.
As an example, FIGS. 1 and 2 represent a flow cytometry sort
overview. A nozzle (32) may allow particles (2) entrained in a
fluid stream (1) to move through a laser beam (34) at an
interrogation point (33). A signal detector (42) such as a forward
scatter detector (30) and perhaps even a side scatter collection
objective (31) may be placed appropriately to collect signals
affiliated to a particle. It may also be desirable to provide
primary laser focusing optics (43). In embodiments, signals may
include fluorescence emitted from a light emitting particle coupled
with individual particles after passing through a laser beam.
Signals emitted from a particle may be passed through optics and
perhaps even a pinhole strip (44) to assist in collection of data.
A signal detector may be connected to a system, as discussed
hereafter, in which signal data indicative of the signals may be
processed and analyzed in order to determine a sort decision.
Computers, computer programming, hardware, software and the like
may assist in a sort decision. While a sort decision is being
determined, particles may pass through a drop delay (35). This time
frame may be very short. After a sort decision may have been made,
a pulse of charge (37) may be applied to a droplet (23) containing
a particle. Droplets may pass through charged deflection plates
(38) in order to sort particles into a desired sort receptacle (40)
having containers. A waste collection tube (39) may be included in
embodiments.
In order to distinguish particles, signal data may be analyzed.
Embodiments may include converting signals (e.g. a first signal and
at least one additional signal) affiliated with each individual
particle into n-dimensional parameter data. This may be done with a
signal processor responsive to the signals. A signal processor may
provide a conversion of a first signal and at least one additional
signal into n-dimensional parameter data. N-dimensional parameter
data may include one-dimensional or perhaps even multi-dimensional
(2-D, 3-D, 4-D, etc.) data which can be associated with each signal
detected. Signal data may be converted to relate each signal with a
coordinate, such as an intensity of a color, and the like and may
even be plotted in a Cartesian coordinate system.
Signals, perhaps even n-dimensional data, may be plotted on a graph
(13). Since differences between particles may vary slightly,
signals affiliated with the particles may also vary slightly. This
slight difference may be so small that when plotted, the
n-dimensional parameter data corresponding to the signals, may
place data points very close together. These may be so close that
it may be difficult to categorize the data points into a
population. Conventional technologies may have disregarded these
points that are so close together and may have decided to throw out
that particle because it could not have been distinguished. It may
be desirable in embodiments to reconfigure data to enhance
separation between data points.
Embodiments may include distinguishing at least two populations (8)
of n-dimensional parameter data. A population differentiation
element may include a geometric transformation and may allow
n-dimensional parameter data to be categorized into one of at least
two populations. For example, a sperm may be categorized into a
X-bearing sperm population and a Y-bearing population. A geometric
two-dimensional transformation may be performed on flow cytometry
data such that particles or even cells may be sorted into separate
vials based on an appropriate property. In the sperm example, one
vial containing cells for male and one vial containing cells for
female. A transformation may include a matrix dot product of
various translation, scale, and perhaps even rotation operations
for discriminating male determining from female determining cells
and may even maintain proper cell type identification during signal
drift over time. The transformations may be combined into a single
transformation matrix so that the calculations can be performed
within the available signal processing time such as with a Digital
Signal Processor.
In embodiments, the present invention may include real-time
classifying n-dimensional parameter data of each of the individual
particles into one of at least two populations. A real-time
classification element may include classifying signal data into a
population, making a sort decision, and sorting a particle all
within the small amount of time it takes for the particle to move
through a flow cytometer. Accordingly, the present invention may
provide in embodiments, sorting individual particles based upon a
real-time classification.
The present invention may provide in embodiments, visually
distinguishing at least two populations of n-dimensional parameter
data. This may assist a user to ensure that a sorting may be
running properly. This may also allow for user input to assist in
discrimination between populations. Embodiments may include
graphically placing n-dimensional parameter data for each of the
individual particles in relation to at least two populations. For
example, it may be desirable to plot n-parameter data in a
Cartesian coordinate system. A first signal may be plotted on one
axis (14) and at least one additional signal may be plotted on at
least one additional axis (15), as can be seen in FIG. 3. In yet
other embodiments, a histogram (17) of the n-dimensional parameter
data may be provided.
Certain particles or cells may exhibit signals that can show
enhanced differences by translation or scaling effects. For
example, a male determining and female determining sperm cell may
not be discriminated from each other using a typical unaltered
light signal detected by a flow cytometer. Although a digitized
signal may have 12 bits of resolution, a sorting electronics may
have 8 bits of resolution possibly discarding the lower 4 bits. A
detected light from male determining and female determining sperm
cells may be so similar that the lower 4 bits may be required to
discriminate between them. Likewise, due to their similarity, the
cells may not effectively be discriminated in histogram data
analysis of the detected parameters possibly because histograms may
also degrade resolution.
Particles or sperm cells may occupy a small area of a histogram
(17). The variation of detected signals of cells or particles,
perhaps such as male determining sperm cells with respect to female
determining sperm cells may be small; as may be the variation
within cell or particles of the same type. The total range of
variation for both types of cells or particles may span less than
half the total available range. Therefore, the lower bits of
resolution may be important for discriminating between the cells or
particles and perhaps even the upper bits may not be necessary to
identify both types of cells or particles. The invention may
exploit this characteristic, in embodiments, by translating a
center of the total range of signal variation for both types of
cells or particles to an origin of a Cartesian coordinate system,
scaling the data about the origin effectively increasing the
variance between types, then translating back to its original
location. As a result, histogram data may show sufficient variation
for discriminating between two types of cells or particles while
even preserving enough information to identify both types from
instrument noise, dead or destroyed cells, other foreign particles,
and the like. This has particular applicability for sperm cell sex
discrimination.
N-dimensional parameter data may be combined, in embodiments, to
mathematically achieve numerical results representative of an
alteration. An alteration calculation may include any kind of
manipulation of data. For example, embodiments may provide
manipulating n-dimensional parameter data mathematically to achieve
a desired result. This may include a rotational alteration perhaps
with a rotational alteration calculation applied to n-dimensional
parameter data. Other embodiments may include a translation
alteration perhaps with a translational alteration calculation. In
yet other embodiments, n-dimensional parameter data may be combined
to mathematically achieve numerical results representative of a
scaling operation perhaps with a scaled alteration calculation. Of
course, other kinds of alterations and calculations may be used and
any alteration may be applied as a single operation or perhaps even
in combination with others. Classification of a particle may be
based upon numerical results representative of an alteration.
In embodiments, and as can be conceptually understood from FIG. 7,
a signal (45) associated with a particle may be detected by at
least one detector (46) in which signal data may be sent to a
signal processor (47). In a signal processor, signal data may be
converted into n-dimensional parameter data to which at least one
alteration (48) (e.g. rotational alteration, translation operation,
scaling operation, any combination of these and the like) may be
applied to the n-dimensional parameter data. Based on the
alteration, n-dimensional parameter data may be classified into one
of at least two populations providing a real-time classification
(49). A particle differentiation decision (50) may be made based
upon a real-time classification of the n-dimensional parameter data
to which directions may be sent to a flow cytometer (51) in order
to charge and sort the particles.
Certain particles or cells may exhibit signals that can show
enhanced differences by a rotational alteration of the data. For
example, in embodiments, the invention may involve rotating data to
increase a separation of data from male determining cells to female
determining cells. Two sources of light may be detected for each
cell. The range of light intensity from one source from male
determining cells may overlap the same light source range from
female determining cells. Employing a scale factor, as described
above, may increase the separation of the mean distribution of the
signal range but may not completely eliminate an overlap.
To eliminate the overlap in this particular example, the invention
may consider a shape of the signal distribution in two-dimensional
analysis where signals from perhaps both light sources may be
correlated in a two-dimensional Cartesian coordinate system.
Graphically, each of the populations such as cell types may have an
elliptical shaped population (18) with similar non-orthogonal
angles of inclination of a major axis and may even have a similar
length of a minor axis. The difference in Y-intercept of the
ellipse major axis for one cell type to the other type may be
greater than the length of the minor axis. Since the major axes may
be nearly parallel, it may be desirable to orient the elliptical
shaped populations orthogonal to at least one axis. A rotation
about a mid-point between the two major axes may orient each
ellipse orthogonal to the Y-axis possibly effectively eliminating
the Y-axis overlap.
Signals such as perhaps light intensity may vary with time, which
may preclude the setting of fixed regions by which sort decisions
may be based. During a long sort, populations may drift due to
physical changes to the detectors, absorption or degradation of
dye, and even other uncontrollable conditions. Consequently, sort
regions may need to be monitored and adjusted during the sort. This
may be tedious, labor intensive and even prone to error.
One embodiment of the present invention may hold a population in
its original location by employing a scale operation in the
transformation matrix. One possible scale factor could be a ratio
of an initial mean value of the signal range with respect to the
current mean; which may effectively scale the signal up or down
proportionately to the amount of drift from the initial mean.
As previously mentioned, a flow cytometer may be used to generate a
stream into which the cells or other particulates may be injected.
A detection point may be established which may cause a source of
laser light to strike the cells perhaps causing a dye that is
carried on genomic material to fluoresce. In one application, sperm
may be orientated by the hydrodynamics of the injection device, and
perhaps the fluorescence level could be proportional to the amount
of genomic mass. Thus, a differential between X and Y bearing sperm
can be detectable. Fluorescence may be detected by sensors
established forward of the detection point and possibly even to an
angle, such as 90 degrees, of this point as may be understood in
FIGS. 1 and 2. A sensory system can pass a pulse of light to an
electrical device which may convert a pulse level into binary
numbers suitable for manipulation by a Digital Signal Processor
("DSP").
A signal processor, for example a Digital Signal Processor may
contain highly optimized algorithms that can perform a
specialization transformation of at least two signal values. This
transformation may cause a resulting population of signal to adopt
a form, such as where a separation of X and Y bearing sperm may be
delineated. Clarity of delineation may allow each population to be
selected more accurately than in any other separation system.
The selection of which population is to be sorted can be made by an
electronic system such as by controlling a droplet break-off of a
standard flow cytometer. There may be a delay between a detection
of a fluorescence and a particle falling into a last breaking drop
(36). This time may be known. Thus an electronic system can apply
an electric charge to the drop containing the particle of interest.
High voltage plates below the breaking drops may cause the drop to
move and be placed into a collection vial. In this fashion, a high
level of selected particles, perhaps such as pure sperm cells can
be collected as may be understood in FIG. 1.
A Digital Signal Processor may control the position of the
populations. Flow cytometers may have variability in the pointing
accuracy of a laser beam which can cause an intensity of
fluorescence from each cell to shift. A DSP may act as a sensory
device to monitor a shifting of light intensity and may even
perform a correcting scale to ensure that the populations residing
in the fluorescence bivariate remain in the same position. This may
ensure that the correct sperm are sorted. The process of
transformation, zooming and perhaps even control may be imbedded in
one geometric transform. Multiple transformation and zoom could be
incorporated perhaps even with non-linear, logarithmic, table look
up, or even discretely unique data portion transformations.
Transformation may uniquely supply the accuracy required to provide
highly pure particle separation.
One method of gaining spatially separated data may be to use
compensation algorithms as those skilled in the art could
appreciate. Rotation of the data (forward scatter vs. side scatter)
may be a more accurate mechanism to do this. In addition to
rotation, it has been found that there may be a need for tracking
and zooming of the data. These combinations can be significant, for
example sex selection may not be optimally achieved by any other
method, hence the importance of this invention.
By rotating a bivariate histogram in which two populations may be
present but overlapping in one dimension, a better spatial
separation in the dimension that is overlapped may be created.
Rotated data can be used as a parameter in sort decisions and
perhaps even in any other histograms. If data has been properly
rotated, a univariate histogram of the parameter of interest can
contain gaps in the populations. In embodiments, a rotation
function may be utilized to set the X and Y populations on a
bivariate to be horizontal.
Because the populations of interest may typically be close
together, it may be desirable--either alone or in combination with
other aspects--to zoom in on a region in order to exaggerate a
distinction between the populations. This may be another mechanism
to allow separation of the populations. Further, the long sorts
typical of sperm sorting or the like may cause data to shift over
time. Shifts may be fixed by setting a tracking region and using
this region in a newly computed parameter. In embodiments, an
automatic region setting algorithm may be implemented. In other
embodiments, regions may be set according to a desired purity
level.
In order to rotate and sort data, a rotation could be done using
hardware that can access the data in an acquisition rack and may
have a capability to modify an event frame prior to a sort decision
being made. Rather than design new hardware, it may be desirable to
implement this in a DSP perhaps by using a rotation algorithm. This
may include an ability to do compensation on data when rotating it.
In addition to rotation, a user can specify a region to zoom in
on.
In embodiments, the present invention may provide specification of
a center point of a rotation. This may allow a finer control of the
rotation in order to achieve maximum separation.
Embodiments of the present invention may include providing a
n-dimensional space alteration function having at least:
a first 1st-dimensional alteration value, a second 1st-dimensional
alteration value, and a third 1st-dimensional alteration value;
a first 2nd-dimensional alteration value, a second 2nd-dimensional
alteration value, and a third 2nd-dimensional alteration value, and
the like.
This may be representative of a matrix, as one skilled in the art
can appreciate and can be understood by the various examples given
herein.
N-dimensional space alteration functions may be combined with a
vector having data points so as to alter the n-dimensional
parameter data. In an embodiment, a combination of a function and
data points may include, but is not limited to: calculating a first
1st-dimensional alteration value times a 1st-dimensional data point
summed with a second 1st-dimensional alteration value times a
2nd-dimensional data point summed with a third 1st-dimensional
alteration value times a 3rd-dimensional data point to thereby
create a first dimensional altered data point; and calculating a
first 2nd-dimensional alteration value times a 1st-dimensional data
point summed with a second 2nd-dimensional rotational value times a
2nd-dimensional data point summed with a third 2nd-dimensional
alteration value times a 3rd-dimensional data point to thereby
create a second dimensional altered data point.
In other embodiments, a n-dimensional space alteration function may
include a first 3rd-dimensional alteration value, a second
3rd-dimensional alteration value and a third 3rd-dimensional
alteration value. Further, a combination of data may include
calculating a first 3rd-dimensional alteration value times a
1st-dimensional data point summed with a second 3rd-dimensional
rotational value times a 2nd-dimensional data point summed with a
third 3rd-dimensional alteration value times a 3rd-dimensional data
point to thereby create a third dimensional altered data point.
Many different types of data manipulation values that may be used
as an alteration value. For example, a rotational alteration may
include alteration values based upon an angle of rotation allowing
altered data points to increase discrimination of at least two
populations of n-dimensional data. In other embodiments, a scaled
alteration may include alteration values are based upon a zoom and
tracking element allowing altered data points to increase
discrimination of at least two populations of n-dimensional data.
In yet other embodiments, a translation alteration may include
alteration values which may translate n-parameter data with respect
to a center point of rotation.
The following are examples of matrices that may be used in order to
do rotation about a given center point and even zoom or tracking on
a region and the like.
Translate data:
.function. ##EQU00001## Rotate the data:
.times..times..theta..times..times..theta..times..times..theta..times..ti-
mes..theta..times..times..times..theta. ##EQU00002## Scale the data
(Zoom and Tracking):
.function. ##EQU00003## These can be combined with the
variables:
Res=Resolution/2
Z=Zoom amount
RC=Rotation Center
Tr=Tracking constant
ZC=Tracking center
.THETA.=Angle of rotation
into a single transformation produced by the product of any or all
of the following linear operations:
T(Res.sub.x, Res.sub.y)
S(Z.sub.x, Z.sub.y)
T(-ZC.sub.x, -ZC.sub.y)
S(Tr.sub.x, Tr.sub.y)
T(RC.sub.x, RC.sub.y)
R.theta.
T(-RC.sub.x, -RC.sub.y)
The equation, T(-RC.sub.x, -RC.sub.y), may translate an event to an
origin and then the opposite in order to translate it back to a
proper coordinate system. This may be done with all listmode data
in the first quadrant.
When zooming, the data that is being zoomed may be centered in a
histogram. This may be why that data could be translated to half
(1/2) the resolution rather than back to a center point of a zoomed
region.
Other examples of translation alterations may be based upon an
operation such as rotation in x-axis, rotation in y-axis, rotation
in z-axis, translation, scale, perspective, higher order and the
like operations. Some examples include the following 3-D
algorithms:
Rotation in X-Axis:
.function..theta..function..theta..function..theta..function..theta..func-
tion..theta. ##EQU00004## Rotation in Y-Axis:
.function..theta..function..theta..function..theta..function..theta..func-
tion..theta. ##EQU00005## Rotation in Z-Axis:
.function..theta..function..theta..function..theta..function..theta..func-
tion..theta. ##EQU00006##
Translation:
.function. ##EQU00007##
Scale:
.function. ##EQU00008## Of course other algorithms may be used and
all are meant to be included in this disclosure. The examples
provided herein are not meant to be limiting.
Programs may solve the particular equation used and may download
the result to the DSP. A DSP code may perform a simple matrix
multiplication using the matrices supplied by computer programs.
Further, a computer program may create zoom parameters such that a
mean of the zoomed signals may remain fixed. The mean may remain at
the same position within a tracking region. Software may allow a
user to designate regions bounds which a zoom function may utilize.
Software may send a center of a zoom, zoom value and even tracking
gain to a DSP.
In embodiments, zooming of a square region on a split of
populations (such as X and Y populations) may be shown on a
Forward-Fluorescence versus a Side-fluorescence bivariate
histogram. A zoom region may be a square or perhaps even non-square
with a maximum size which may be equal to a size of a bivariate. In
embodiments, it may be desirable to use a gain set at 1 and offset
at 0 on both parameters. A zoom region can be set as a fraction in
percentage of the bivariate range in linear units. As those skilled
in the art would recognize, 1/16 may offer a digital advantage. In
embodiments, software gain (distinct from a zoom gain) can be
altered. Because the DSP may be a fixed point processor, a highly
optimized assembly code may be used to do the floating point
math.
In order to achieve efficient calculations of data within the sort
time period of real time classifying, the present invention in
embodiments may include simultaneously processing two or more
alteration calculations. This may include simultaneously processing
n-dimensional parameter data to mathematically achieve numerical
results of both a rotational alteration and a scaled alteration.
Other embodiments may include simultaneously processing
n-dimensional parameter data to mathematically achieve numerical
results of a rotational alteration, a scaled alteration and perhaps
even a translation alteration. Of course, additional alterations
may be simultaneously or perhaps even sequentially processed as
well.
FIG. 3 may be an image of data prior to rotation. FIG. 4 shows an
image of data after scaling, FIG. 5 show an image of data after
rotation and FIG. 6 shows an image of data after scaling and
rotation. These may include one type of illustrations of data that
can be expected. It is also common to see these illustrations of
data from sperm sorting data. While rotating may allow a user to
gain spatially separated data, it may distort the relative values
of intensity and in embodiments, may not be used for any reason
other than gaining the space between distinct populations. It may
be possible to remove the values on the axis of the rotated data in
order to assure that users have a visual way of recognizing
this.
As can be easily understood from the foregoing, the basic concepts
of the present invention may be embodied in a variety of ways. It
involves both transformation techniques as well as devices to
accomplish the appropriate transformation. In this application, the
transformation techniques are disclosed as part of the results
shown to be achieved by the various devices described and as steps
which are inherent to utilization. They are simply the natural
result of utilizing the devices as intended and described. In
addition, while some devices are disclosed, it should be understood
that these not only accomplish certain methods but also can be
varied in a number of ways. Importantly, as to all of the
foregoing, all of these facets should be understood to be
encompassed by this disclosure.
The discussion included in this application is intended to serve as
a basic description. The reader should be aware that the specific
discussion may not explicitly describe all embodiments possible;
many alternatives are implicit. It also may not fully explain the
generic nature of the invention and may not explicitly show how
each feature or element can actually be representative of a broader
function or of a great variety of alternative or equivalent
elements. Again, these are implicitly included in this disclosure.
Where the invention is described in device-oriented terminology,
each element of the device implicitly performs a function.
Apparatus claims may not only be included for the device described,
but also method or process claims may be included to address the
functions the invention and each element performs. Neither the
description nor the terminology is intended to limit the scope of
the claims that will be included in any subsequent patent
application.
It should also be understood that a variety of changes may be made
without departing from the essence of the invention. Such changes
are also implicitly included in the description. They still fall
within the scope of this invention. A broad disclosure encompassing
both the explicit embodiment(s) shown, the great variety of
implicit alternative embodiments, and the broad methods or
processes and the like are encompassed by this disclosure and may
be relied upon when drafting the claims for any subsequent patent
application. It should be understood that such language changes and
broader or more detailed claiming may be accomplished at a later
date. With this understanding, the reader should be aware that this
disclosure is to be understood to support any subsequently filed
patent application that may seek examination of as broad a base of
claims as deemed within the applicant's right and may be designed
to yield a patent covering numerous aspects of the invention both
independently and as an overall system.
Further, each of the various elements of the invention and claims
may also be achieved in a variety of manners. Additionally, when
used or implied, an element is to be understood as encompassing
individual as well as plural structures that may or may not be
physically connected. This disclosure should be understood to
encompass each such variation, be it a variation of an embodiment
of any apparatus embodiment, a method or process embodiment, or
even merely a variation of any element of these. Particularly, it
should be understood that as the disclosure relates to elements of
the invention, the words for each element may be expressed by
equivalent apparatus terms or method terms--even if only the
function or result is the same. Such equivalent, broader, or even
more generic terms should be considered to be encompassed in the
description of each element or action. Such terms can be
substituted where desired to make explicit the implicitly broad
coverage to which this invention is entitled. As but one example,
it should be understood that all actions may be expressed as a
means for taking that action or as an element which causes that
action. Similarly, each physical element disclosed should be
understood to encompass a disclosure of the action which that
physical element facilitates. Regarding this last aspect, as but
one example, the disclosure of a "detector" should be understood to
encompass disclosure of the act of "detecting"--whether explicitly
discussed or not--and, conversely, were there effectively
disclosure of the act of "detecting", such a disclosure should be
understood to encompass disclosure of a "detector" and even a
"means for detecting." Such changes and alternative terms are to be
understood to be explicitly included in the description.
Any patents, publications, or other references mentioned in this
application for patent are hereby incorporated by reference. All
priority cases are also incorporated by reference. In addition, as
to each term used it should be understood that unless its
utilization in this application is inconsistent with such
interpretation, common dictionary definitions should be understood
as incorporated for each term and all definitions, alternative
terms, and synonyms such as contained in the 60 Random House
Webster's Unabridged Dictionary, second edition are hereby
incorporated by reference. Finally, all references listed in the
list of references below or other information statement filed with
the application are hereby appended and hereby incorporated by
reference, however, as to each of the above, to the extent that
such information or statements incorporated by reference might be
considered inconsistent with the patenting of this/these
invention(s) such statements are expressly not to be considered as
made by the applicant(s).
TABLE-US-00001 1. U.S. PATENT DOCUMENTS DOCUMENT NO. & PUB'N
DATE PATENTEE OR KIND CODE (if known) mm-dd-yyyy APPLICANT NAME
3,299,354 12/17/67 Hogg 3,661,460 05/09/72 Elking et al. 3,710,933
01/16/73 Fulwyler et al 3,761,941 09/25/73 Robertson 3,810,010
05/07/74 Thom 3,826,364 07/30/74 Bonner et al 3,833,796 11/03/74
Fetner et al 3,960,449 07/01/76 Carleton et al 3,963,606 06/15/76
Hogg 3,973,196 08/03/76 Hogg 4,014,611 03/29/77 Simpson et al
4,070,617 01/24/78 Kachel et al 4,074,809 2/21/2978 McMillin et al.
4,162,282 07/24/79 Fulwyler et al 4,230,558 10/28/80 Fulwyler
4,302,166 11/24/81 Fulwyler et al 4,317,520 03/02/82 Lombardo et al
4,318,480 03/09/82 Lombardo et al 4,318,481 03/09/82 Lombardo et al
4,318,482 03/09/82 Barry et al 4,318,483 03/09/82 Lombardo et al
4,325,483 04/20/82 Lombardo et al 4,341,471 07/27/82 Hogg et al
4,350,410 09/21/82 Minott 4,361,400 11/30/82 Gray et al 4,395,676
07/26/83 Hollinger et al 4,400,764 08/23/83 Kenyon 4,487,320
12/11/84 Auer 4,498,766 02/12/85 Unterleitner 4,501,336 02/26/1985
Kemp et al. 4,515,274 05/07/85 Hollinger et al 4,523,809 06/18/85
Toboada et al 4,538,733 11/03/85 Hoffman 4,598,408 07/01/86 O'Keefe
4,600,302 07/15/86 Sage, Jr. 4,631,483 12/23/86 Proni et al
4,673,288 06/16/87 Thomas et al 4,691,829 09/08/87 Auer 4,702,598
10/27/87 Bohmer 4,744,090 05/10/88 Freiberg 4,758,729 07/19/88
Monnin 4,794,086 01/27/88 Kasper et al 4,818,103 04/04/89 Thomas et
al 4,831,385 05/16/89 Archer et al 4,845,025 07/04/89 Lary et al
4,877,965 10/31/89 Dandliker et al 4,942,305 07/17/90 Sommer
4,981,580 01/01/91 Auer 4,983,038 01/08/91 Ohki et al 4,987,539
01/22/91 Moore, et al. 5,005,981 04/09/91 Schulte et al 5,007,732
04/16/91 Ohki et al 5,030,002 07/09/91 North, Jr. 5,034,613
07/23/91 Denk et al 5,079,959 01/14/92 Miyake et al 5,098,657
03/24/92 Blackford et al 5,101,978 04/07/92 Marcus 5,199,576
04/06/93 Corio, et al. 5,127,729 07/07/92 Oetliker et al 5,135,759
08/04/1992 Johnson 5,144,224 09/01/92 Larsen 5,150,313 09/22/92 Van
den Engh et al 5,159,397 10/27/92 Kosaka et al 5,159,403 10/27/92
Kosaka 5,167,926 12/01/92 Kimura et al 5,180,065 01/19/93 Touge et
al 5,182,617 01/26/93 Yoneyama et al 5,199,576 04/06/93 Corio et al
5,215,376 06/01/93 Schulte et al 5,247,339 09/21/93 Ogino 5,259,593
11/09/93 Orme et al 5,260,764 11/09/93 Fukuda et al 5,298,967
03/29/94 Wells 5,359,907 11/01/94 Baker et al 5,367,474 11/22/94
Auer, et al. 5,370,842 12/06/94 Miyazaki et al 5,412,466 05/02/95
Ogino 5,452,054 09/19/95 Dewa et al 5,466,572 11/14/95 Sasaki, et
al 5,467,189 11/14/95 Kreikebaum et al 5,471,294 11/28/1995 Ogino
5,483,469 01/09/96 Van den Engh et al 5,503,994 04/02/1996 Shear et
al. 5,523,573 06-04-96 Hanninen et al 5,558,998 09/24/96 Hammond,
et al 5,596,401 01/21/97 Kusuzawa 5,601,235 02/11/97 Booker et al
5,602,039 02/11/97 Van den Engh 5,602,349 02/11/97 Van den Engh
5,641,457 07/24/97 Vardanega, et al 5,643,796 07/01/97 Van den Engh
et al 5,650,847 07/22/97 Maltsev et al 5,672,880 09/30/97 Kain
5,675,401 10/07/97 Wangler et al 5,700,692 12/23/97 Sweet 5,707,808
01/13/98 Roslaniec et al 5,726,364 03/10/98 Van Den Engh 5,759,767
06/02/98 Lakowicz et al 5,777,732 06/07/98 Hanninen et al 5,786,560
07/28/98 Tatah et al 5,796,112 08/18/98 Ichie 5,815,262 09/29/98
Schrof et al 5,824,269 10/20/1998 Kosaka et al. 5,835,262 11/10/98
Iketaki et al 5,880,457 03/09/1999 Tomiyama et al. 5,912,257
06/15/99 Prasad et al 5,916,449 06/29/1999 Ellwart et al. 6,589,792
07/08/2003 Malachowski 6,248,590 06/19/2001 Malachowski 4,361,400
11/30/1982 Gray et al.
TABLE-US-00002 II. FOREIGN PATENT DOCUMENTS Foreign Patent Document
PUB'N Country Code, Number, DATE PATENTEE Kind Code (if known)
mm-dd-yyyy OR APPLICANT NAME DE19549015 03-04-97 Ellwart et al. EP
0781985 A2 07-02-97 Karls et al. EP0160201 A2 11/06/85 Sage et al.
EP025296 A2 03/18/81 Lombardo et al. EP0468100 A1 01/29/92 Kosaka,
Tokihiro EP0786079 B1 05/21/2003 Van Den Engh FR2699678-Al 12/23/92
MERLU BENOIT JP 4-126066 04/27/92 SAKAMOTO KAZUCHIKA, et al. JP
4-126081 04/27/92 SAKAMOTO KAZUCHIKA, et al. JP2024535 01/26/90
MIYAMOTO MORITOSHI, et al. JP4126064 (A) 04/27/92 SHIOMIATSUSHI, et
al. JP4126066 (A) 04/27/92 SAKAMOTO KAZUCHIKA, et al. JP4126081 (A)
04/27/92 SAKAMOTO KAZUCHIKA et al. JP61139747 (A) 06/27/86 ITO YUJI
JP61159135 (A) 07/18/86 ITO YUJI SU1056008 11/23/83 TRETYAKOV
ALEKSANDR et al. SU1260778-A1 09/30/86 YAGUNOV ALEKSEJ et al
WO96/12172 A1 04/25/1996 Van Den Engh WO 99/44037 02/26/1999
Malachowski WO01/28700 A1 04/26/2001 Ellison, et al.
TABLE-US-00003 III. OTHER DOCUMENTS Axicon; Journal of the Optical
Society of America; Vol. 44, Company, Hawk-Eye Works, Rochester,
NY, Sep. 10, 1953, pp. 592-597 Ceruzzi, P., "Histoiy of Modern
Computing", MIT Press, Reference to Non-von Neumann. Denk, W., et
al (1995). Two-photon molecular excitation in laser scanning
microscopy. Handbook of Biological Conical Microscopy. J. B.
Pawley, ed., Plenum Press, New York, pp 444-458. Garner, D. L. et
al; "Quantification of the X- and Y- Chromosome- Bearing
Spermatozoa of Domestic Animals by Flow Cytometry", Biology of
Reproduction 28, pgs. 312-321, (1983) Goppert-Mayer, M. 1931,. Uber
Elementarakte mit zwei Quantensprungen nnalen der Physik, Pages
273-294 Johnson, Lawrence A. "Sex Preselection by Flow Cytometric
Separation of X and Y Chromosome-bearing Sperm based on NA
Difference: a Review, Reprod. Fertil. Dev., 1995, 7, pgs. 893-903
Manni, Jeff; (1996). Two-Photon Excitation Expands The Capabilities
of Laser-Scanning Microscopy, Biophotonics International, pp 44-52
Melamed et al, An Historical Review of the Development of Flow
Cytometers and Sorters, 1979, pp. 3-9 Piston. D. W., et al (1994).
Two-photon-excitation fluorescence imaging of three-dimensional
calcium ion activity. APPLIED OPTICS 33: 662- 669 Piston, D. W., et
al. (1995). Three-dimensionally resolved NAD(P)H cellular metabolic
redox imaging of the in-situ cornea with two-photon excitation
laser scanning microscopy. J OF MICROSCOPY 178: 20-27 Radbruch, A
Flow Cytometry and Cell Sorting,. (Ed.), "Operation of a Flow
Cytometer" by Gottlinger et al., 1992, p. 7-23 Sharpe, J., Thesis:
An Introduction to Flow Cytometry," pp 5-7 and pp 33-42 and page
55. Shapiro, H. M.D., "Practical Flow Cytometry", Third Edition,
John Wiley & Sons, Inc., Publication. Skogen-Hagenson, M. J. et
al; "A High Efficiency Flow Cytometer," The Journal of
Histochemistry and Cytochemistry, Vol. 25, No. 7, pp. 784-789,
1977, USA Van Dilla et al. (Eds.), Flow Cytometry: Instrumentation
and Data Analysis, "Flow Chambers and Sample Handling," by Pinkel
et al., 1985, pp. 77-128 Van Dilla et al. (Eds.)Flow Cytometry:
Instrumentation and Data Analysis. "Overview of Flow Cytometry:
Instrumentation and Data Analysis" by Martin Van Dilla, 1985, pp.
1-8 Williams, R. M. et al. (1944). Two photon molecular excitation
provides intrinsic 3-dimensional resolution for laser-based
microscopy and microphotochemistry. FASEB J. 8: 804-813. "An
Introduction to Flow Cytometry", pp 5-7 and pp 33-42 and page 55.
Gottlinger, C., et al, "Operation of a Flow Cytometer," Flow Cyto-
metry and Cell Sorting, pp. 7-23 (1982) McLeod, J., Eastman Kodak
Company, Hawk-Eye Works, Rochester, NY, Journal of the Optical
Society of America; vol. 44, no. 8, September 1953, pp. 592-597
Pinkel, D., "Flow Chambers and Sample Handling," Flow Cytometry:
Instrumentation and Data Analysis, pp. 77-128 (1985) U.S.
application 09/032,733, entitled "Method and Apparatus for Flow
Cytometry," filed on Feb. 27, 1998, 53 pages and 5 figures U.S.
application No. 60/591,957, entitled, "Geometric Transformation for
Enhanced Flow Cytometry Discrimination," filed Jul. 7, 2004, 19
pages.
Thus, the applicant(s) should be understood to have support to
claim and make a statement of invention to at least: i) each of the
transformation devices as herein disclosed and described, ii) the
related methods disclosed and described, iii) similar, equivalent,
and even implicit variations of each of these devices and methods,
iv) those alternative designs which accomplish each of the
functions shown as are disclosed and described, v) those
alternative designs and methods which accomplish each of the
functions shown as are implicit to accomplish that which is
disclosed and described, vi) each feature, component, and step
shown as separate and independent inventions, vii) the applications
enhanced by the various systems or components disclosed, viii) the
resulting products produced by such systems or components, ix) each
system, method, and element shown or described as now applied to
any specific field or devices mentioned, x) methods and apparatuses
substantially as described hereinbefore and with reference to any
of the accompanying examples, xi) the various combinations and
permutations of each of the elements disclosed, xii) each
potentially dependent claim or concept as a dependency on each and
every one of the independent claims or concepts presented.
In addition and as to computer aspects and each aspect amenable to
programming or other electronic automation, the applicant(s) should
be understood to have support to claim and make a statement of
invention to at least: xiii) processes performed with the aid of or
on a computer as described throughout the above discussion, xiv) a
programmable apparatus as described throughout the above
discussion, xv) a computer readable memory encoded with data to
direct a computer comprising means or elements which function as
described throughout the above discussion, xvi) a computer
configured as herein disclosed and described, xvii) individual or
combined subroutines and programs as herein disclosed and
described, xviii) the related methods disclosed and described, xix)
similar, equivalent, and even implicit variations of each of these
systems and methods, xx) those alternative designs which accomplish
each of the functions shown as are disclosed and described, xxi)
those alternative designs and methods which accomplish each of the
functions shown as are implicit to accomplish that which is
disclosed and described, xxii) each feature, component, and step
shown as separate and independent inventions, and xxiii) the
various combinations and permutations of each of the above.
With regard to claims whether now or later presented for
examination, it should be understood that for practical reasons and
so as to avoid great expansion of the examination burden, the
applicant may at any time present only initial claims or perhaps
only initial claims with only initial dependencies. Support should
be understood to exist to the degree required under new matter
laws--including but not limited to European Patent Convention
Article 123(2) and United States Patent Law 35 U.S.C. .sctn.132 or
other such laws--to permit the addition of any of the various
dependencies or other elements presented under one independent
claim or concept as dependencies or elements under any other
independent claim or concept. In drafting any claims at any time
whether in this application or in any subsequent application, it
should also be understood that the applicant has intended to
capture as full and broad a scope of coverage as legally available.
To the extent that insubstantial substitutes are made, to the
extent that the applicant did not in fact draft any claim so as to
literally encompass any particular embodiment, and to the extent
otherwise applicable, the applicant should not be understood to
have in any way intended to or actually relinquished such coverage
as the applicant simply may not have been able to anticipate all
eventualities; one skilled in the art, should not be reasonably
expected to have drafted a claim that would have literally
encompassed such alternative embodiments.
Further, if or when used, the use of the transitional phrase
"comprising" is used to maintain the "open-end" claims herein,
according to traditional claim interpretation. Thus, unless the
context requires otherwise, it should be understood that the term
"comprise" or variations such as "comprises" or "comprising", are
intended to imply the inclusion of a stated element or step or
group of elements or steps but not the exclusion of any other
element or step or group of elements or steps. Such terms should be
interpreted in their most expansive form so as to afford the
applicant the broadest coverage legally permissible.
Finally, any claims set forth at any time are hereby incorporated
by reference as part of this description of the invention, and the
applicant expressly reserves the right to use all of or a portion
of such incorporated content of such claims as additional
description to support any of or all of the claims or any element
or component thereof, and the applicant further expressly reserves
the right to move any portion of or all of the incorporated content
of such claims or any element or component thereof from the
description into the claims or vice-versa as necessary to define
the matter for which protection is sought by this application or by
any subsequent continuation, division, or continuation-in-part
application thereof, or to obtain any benefit of, reduction in fees
pursuant to, or to comply with the patent laws, rules, or
regulations of any country or treaty, and such content incorporated
by reference shall survive during the entire pendency of this
application including any subsequent continuation, division, or
continuation-in-part application thereof or any reissue or
extension thereon.
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