U.S. patent application number 16/007658 was filed with the patent office on 2018-10-11 for methods and systems for identifying a particle using dielectrophoresis.
The applicant listed for this patent is MICHIGAN TECHNOLOGICAL UNIVERSITY. Invention is credited to Tayloria N.G. ADAMS, Jeana L. COLLINS, Kaela M. LEONARD, Adrienne Robyn MINERICK.
Application Number | 20180292352 16/007658 |
Document ID | / |
Family ID | 52779226 |
Filed Date | 2018-10-11 |
United States Patent
Application |
20180292352 |
Kind Code |
A1 |
MINERICK; Adrienne Robyn ;
et al. |
October 11, 2018 |
METHODS AND SYSTEMS FOR IDENTIFYING A PARTICLE USING
DIELECTROPHORESIS
Abstract
A system for identifying a particle. The system includes a
microfluidic device; a microelectrode array including a plurality
of electrodes, the microelectrode array disposed within the
microfluidic device; a plurality of particles suspended in a
solution and delivered to the micro-electrode array using the
microfluidic device; a signal generator operatively coupled to the
microelectrode array; a particle detector adjacent to the
microelectrode array; and a controller in operative communication
with the signal generator and the particle detector. The controller
is configured to apply an oscillating voltage signal to the
microelectrode array between a low frequency and a high frequency
at a sweep rate, wherein the sweep rate is no more than a maximum
sweep rate, and determine a distribution of the plurality of
particles relative to the microelectrode array at a plurality of
frequency levels between the low frequency and the high
frequency.
Inventors: |
MINERICK; Adrienne Robyn;
(Houghton, MI) ; COLLINS; Jeana L.; (Houghton,
MI) ; LEONARD; Kaela M.; (Braintree, MA) ;
ADAMS; Tayloria N.G.; (Chassell, MI) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
MICHIGAN TECHNOLOGICAL UNIVERSITY |
Houghton |
MI |
US |
|
|
Family ID: |
52779226 |
Appl. No.: |
16/007658 |
Filed: |
June 13, 2018 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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15027014 |
Apr 4, 2016 |
10012613 |
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PCT/US14/59332 |
Oct 6, 2014 |
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16007658 |
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61887178 |
Oct 4, 2013 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G01N 15/1031 20130101;
G01N 2015/0073 20130101; G01N 27/44791 20130101; B03C 5/005
20130101; G01N 2015/1006 20130101; G01N 33/48707 20130101 |
International
Class: |
G01N 27/447 20060101
G01N027/447; G01N 33/487 20060101 G01N033/487; G01N 15/10 20060101
G01N015/10; B03C 5/00 20060101 B03C005/00 |
Goverment Interests
STATEMENT REGARDING FEDERALLY-SPONSORED RESEARCH OR DEVELOPMENT
[0002] The present invention was conceived while performing work
under CBET 0644538, CBET 1041338, and IIP 1340126, each of which
has been awarded by the National Science Foundation. The government
has certain rights in the invention.
Claims
1. A system for identifying a plurality of particles suspended in a
solution, the system comprising: a microfluidic device to receive
the solution including the plurality of particles; a microelectrode
array comprising a plurality of electrodes, the microelectrode
array disposed within the microfluidic device and in vicinity of
the received solution, the microelectrode array including a first
plurality of electrodes to provide a first charge and a second
plurality of electrodes to provide a second charge, the second
charge being different than the first charge, and the second
plurality of electrodes being in a nonparallel relationship with
the first plurality of electrodes; a signal generator operatively
coupled to the microelectrode array; a particle detector adjacent
to the microelectrode array; and a controller in operative
communication with the signal generator and the particle detector,
the controller being configured to apply an oscillating voltage
signal to the microelectrode array at a plurality of frequency
levels varying continuously between a low frequency and a high
frequency, the plurality of frequency levels being applied at a
sweep rate, wherein the sweep rate is no more than a maximum sweep
rate and is no less than a minimum sweep rate, the applying of the
oscillating voltage signal to the microelectrode array resulting in
a spatially non-uniform field, and determine a distribution of the
plurality of particles relative to the microelectrode array at the
plurality of frequency levels varying continuously between the low
frequency and the high frequency.
2. The system of claim 1, wherein the solution has a conductivity
and wherein the maximum sweep rate is a function of the
conductivity.
3. The system of claim 2, wherein the conductivity is 0.10 S/m and
the maximum sweep rate is less than 0.0026 MHz/s.
4. The system of claim 2, wherein the conductivity is 1.0 S/m and
the maximum sweep rate is less than 0.0031 MHz/s.
5. The system of claim 1, wherein the low frequency is 0.01 MHz and
the high frequency is 2.0 MHz.
6. The system of claim 1, wherein the particle detector comprises
an image detector and an image analysis system and wherein the
controller, to determine the distribution of the plurality of
particles relative to the microelectrode array, is further
configured to collect an image of the microelectrode array using
the image detector and determine a spatially resolvable
concentration of the plurality of particles relative to the
microelectrode array using the image analysis system at each of the
plurality of frequency levels.
7. The system of claim 1, wherein, to determine the distribution of
the plurality of particles relative to the microelectrode array,
the controller is further configured to use an image analysis
system to determine a first spatial distribution of the plurality
of particles and a second spatial distribution of the plurality of
particles at a second location at each of the plurality of
frequency levels.
8. The system of claim 7, wherein, to determine the first spatial
distribution of the plurality of particles at a first location, the
controller is further configured to use the image analysis system
to determine an intensity of the plurality of particles at the
first location.
9. The system of claim 7, wherein, to determine the second spatial
distribution of the plurality of particles at the second location,
the controller is further configured to use the image analysis
system to determine an intensity of the plurality of particles at
the second location.
10. The system of claim 1, wherein the microelectrode array is a
quadrapole microelectrode array.
11. The system of claim 1, wherein the plurality of particles
comprise red blood cells.
12. The system of claim 1, wherein the sweep rate is no less than
the minimum sweep rate.
13. The system of claim 12, wherein the minimum sweep rate is
0.0008 MHz/s.
14-30. (canceled)
31. The system of claim 1, wherein the system comprises a handheld
device, the handheld device including the microfluidic device, the
microelectrode array, the signal generator, the particle detector,
and the controller.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application claims priority to co-pending U.S.
Provisional Patent Application No. 61/887,178 filed on Oct. 4,
2013, the entire content of which is incorporated herein by
reference.
INTRODUCTION
[0003] The present invention relates to identification of particles
based on dielectrophoretic responses.
SUMMARY OF THE INVENTION
[0004] In one embodiment, a system for identifying a particle
includes a microfluidic device; a microelectrode array including a
plurality of electrodes, the microelectrode array disposed within
the microfluidic device; a plurality of particles suspended in a
solution and delivered to the microelectrode array using the
microfluidic device; a signal generator operatively coupled to the
microelectrode array; a particle detector adjacent to the
microelectrode array; and a controller in operative communication
with the signal generator and the particle detector. The controller
is configured to apply an oscillating voltage signal to the
microelectrode array between a low frequency and a high frequency
at a sweep rate, wherein the sweep rate is no more than a maximum
sweep rate, and determine a distribution of the plurality of
particles relative to the microelectrode array at a plurality of
frequency levels between the low frequency and the high
frequency.
[0005] In another embodiment, a method of identifying a particle.
The method includes the steps of: placing a plurality of particles
adjacent a microelectrode array, the microelectrode array including
a plurality of electrodes; applying an oscillating voltage signal
to the microelectrode array, the oscillating voltage signal varying
between a low frequency and a high frequency at a sweep rate,
wherein the sweep rate is no more than a maximum sweep rate; and
determining a distribution of the plurality of particles relative
to the microelectrode array at a plurality of frequency levels
between the low frequency and the high frequency.
[0006] Other features and aspects of the invention will become
apparent by consideration of the following detailed description and
accompanying drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
[0007] FIG. 1 shows (a) Dielectric relaxation mechanism for PS
beads showing cases when i) particle polarization occurs at a
static frequency, ii) .tau..sub.MW is shorter than the slow
frequency sweep rate (.tau..DELTA..sub.FS) allowing the bead
interface time to polarize in response to the non-uniform AC field,
and iii) .tau..sub.MW is longer than the .tau..DELTA..sub.FS for
fast frequency sweep rates and the bead interface does not have
time to fully polarize. (b) Schematic of the quadrapole electrodes
micro patterned onto a glass slide, and (c) microdevice with PDMS
fluidic layer bonded above the quadrapole electrodes silver-epoxied
to copper leads.
[0008] FIG. 2 shows (a) nDEP behavior of 6 .mu.m PS beads suspended
in E-pure H.sub.2O 2.5.times.10.sup.-4 S/m and 250V.sub.pp/cm
0.0063, 0.056 and 0.17 MHz/s sweep rates from 0.010 MHz to 1.0 MHz.
(b) Raw intensity (arbitrary units) profile of PS beads in the
center nDEP region (boxes shown at 0.20 MHz) at 0.0063 MHz/s sweep
rate. Inset is a calibration of intensity per bead. (c)
Clausius-Mossotti factor for the PS beads from 0.010 MHz to 2.0 MHz
at three conductivities of 2.5.times.10.sup.-4,
1.0.times.10.sup.-3, and 1.0 S/m. PS bead assembly at slower
frequency sweep rates track static frequency responses while 0.056
MHz/s illustrates transitional behavior and frequency sweeps above
0.17 MHz/s substantially lag the true static frequency DEP
responses.
[0009] FIG. 3 shows (a) 6 .mu.m PS beads nDEP intensity profiles
for 0.00080, 0.0063, and 0.056 MHz/s and static steady state (SS)
measurements (black diamonds). Intensity analysis captures bead
assembly to the quadrapole center with transient and SS regions.
The slowest frequency sweep rate of 0.00080 MHz/s best predicts the
static DEP responses. (b) Bead assembly intensity (arbitrary units)
profiles for 0.0063 (n=8) and 0.17 MHz/s (n=7) with 95% confidence
upper and lower limits shown as dashed lines. (c) Transient slope
comparison for static frequencies (0 MHz/s) as well as frequency
sweeps. (d) Comparison of static frequency and frequency sweep PS
bead velocities from 0 to 50 s. 0.00080 MHz/s results are
consistently similar to the static frequency results.
[0010] FIG. 4 shows (a) nDEP behavior of RBCs suspended in 0.1 S/m
dextrose buffer and 250V/cm at 0.00080 MHz/s, 0.0063 MHz/s and
0.056 MHz/s sweep rates from 0.010 MHz to 0.50 MHz. (b) RBCs nDEP
intensity (arbitrary units) profiles for 0.00080, 0.0063, and 0.056
MHz/s and static measurements. (c) 0.00080 and 0.056 MHz/s RBC
assembly intensity (arbitrary units) profiles n=8, with 95%
confidence interval upper and lower limits shown as dashed
lines.
[0011] FIG. 5 shows an image comparison of the nDEP and pDEP
behavior of A+ red blood cells suspended in 0.10 S/m dextrose
solution and 1000V.sub.pp/cm at 0.00080, 0.0016, and 0.0028 MHz/s
sweep rates from 0.010 MHz to 1.0 MHz. (1) Denotes red blood cells
nDEP behavior and (2) denotes red blood cell pDEP behavior. The red
blood cells' DEP behavior at slower frequency sweep rates
correlates well with the static frequency response (top row).
[0012] FIG. 6 illustrates (a) nDEP and (b) pDEP intensity profiles
for 0.00080, 0.0016, and 0.0028 MHz/s and static steady state
measurements (solid circle). The intensity (arbitrary units)
analysis captures the RBCs assembly toward the electrode center
(nDEP) and near the electrodes (pDEP). 0.00080 MHz/s is the slowest
and 0.0016 MHz/s is the fastest sweep rate to best predict RBCs'
static DEP response.
[0013] FIG. 7 illustrates (a) RBC static images (top row) compared
to RBCs response using 0.0024 MHz/s (middle and bottom row). R1 and
R2 arc two different repeats completed for this measurement. (b)
nDEP and (c) pDEP intensity (arbitrary units) profiles for 0.0024
MHz/s with RBC static steady state measurements (circles). The
images and intensity profiles show the threshold frequency sweep
rate at which agreement with static measurements is acceptable, but
begins to falter. Sweep rates less than 0.0024 MHz/s agree well.
Each test was completed with A+ blood in 0.10 S/m at
1000V.sub.pp/cm.
[0014] FIG. 8 illustrates (a) RBC static images (top row) compared
to RBCs response using 0.0025 MHz/s (middle and bottom row). R1 and
R2 are two different repeats completed for this measurement. (b)
nDEP and (c) pDEP intensity profiles for 0.0025 MHz/s with RBC
static steady state measurements (circles). The images and
intensity profiles show poor agreement with static measurements.
Each test was completed with A+ blood in 0.10 S/m at
1000V.sub.pp/cm.
[0015] FIG. 9 illustrates (a) RBC static images (top row) compared
to RBCs response using 0.0026 MHz/s (middle and bottom row). R1 and
R2 are two different repeats completed for this measurement. (b)
nDEP and (c) pDEP intensity profiles for 0.0026 MHz/s with RBC
static steady state measurements (circles). The images show poor
agreement and intensity profiles show good agreement with static
measurements. Each test was completed with A+ blood in 0.10 S/m at
1000V.sub.pp/cm.
[0016] FIG. 10 illustrates (a) RBC static images (top row) compared
to the response of RBCs using a sweep rate of 0.0028 MHz/s (middle
and bottom row). R1 and R2 are two different repeats completed for
this measurement. Panels (b) nDEP and (c) pDEP show intensity
profiles for 0.0028 MHz/s with RBC static steady state measurements
(circles). The images show poor agreement and intensity profiles
illustrate the lack of reproducibility of agreement with static
measurements. Each test was completed with A+ blood in 0.10 S/m at
1000V.sub.pp/cm.
[0017] FIG. 11 illustrates (a) A- RBC static images (top row)
compared to A- RBCs response using 0.0024 MHz/s (bottom row). (b)
nDEP and (c) pDEP intensity profiles for 0.0024 MHz/s with RBC
static steady state measurements (circles). The images and
intensity profiles show good agreement with static measurements.
Each test was completed in 0.10 S/m at 1000V.sub.pp/cm.
[0018] FIG. 12 illustrates (a) O+ RBC static images (top row)
compared to O+ RBCs response using 0.0024 MHz/s (bottom row). (b)
nDEP and (c) pDEP intensity profiles for 0.0024 MHz/s with RBC
static steady state measurements (circles). The images and
intensity profiles show good agreement at 0.70 MHz and fair
agreement at 0.80 MHz. Each test was completed in 0.10 S/m at
1000V.sub.pp/cm.
[0019] FIG. 13 illustrates (a) B+ RBC static images (top row)
compared to OB+ RBCs response using 0.0024 MHz/s (bottom row). (b)
nDEP and (c) pDEP intensity profiles for 0.0024 MHz/s with RBC
static steady state measurements (circles). The images and
intensity profiles show good agreement over the tested frequency
range 0.60-0.84MHz. Each test was completed in 0.10 S/m at
1000V.sub.pp/cm.
[0020] FIG. 14 shows a plot of sweep rate (MHz/s) as a function of
conductivity of a solution. The plot points are a sweep rate at
which the results for a given conductivity were no longer accurate.
The plotted curve defines a threshold sweep rate. Thus, sweep rates
above the threshold sweep rate for a given concentration are too
fast, and any sweep rate below the curve may be used accurately and
reliably. This aids in determining the fastest sweep rates that may
be used for a solution with a given concentration in order to
decrease the overall time needed for the procedure.
[0021] FIG. 15 shows RBC static images (top row) compared to RBCs
response using 0.0024 MHz/s (bottom row). Each test was completed
with A+ blood in 0.10 S/m at 1000V.sub.pp/cm. This illustrates the
visual similarity between the static response and response at this
sweep rate at the solution conductivity of 0.10 S/m.
[0022] FIG. 16 shows RBC static images (top row) compared to RBCs
response using 0.0024 MHz/s (bottom row). Each test was completed
with A+ blood in 0.50 S/m at 1000V.sub.pp/cm. This illustrates the
visual similarity between the static response and response at this
sweep rate at the solution conductivity of 0.50 S/m.
[0023] FIG. 17 shows RBC static images (top row) compared to RBCs
response using 0.0024 MHz/s (bottom row). Each test was completed
with A+ blood in 1.00 S/m at 1000V.sub.pp/cm. This illustrates the
visual similarity between the static response and response at this
sweep rate at the solution conductivity of 1.0 S/m.
[0024] FIG. 18 shows pDEP and nDEP plots of scaled intensity versus
frequency for A+ blood in 0.25 S/m at 1000V.sub.pp/cm. This plot
generally shows the 0.0027 MHz/s sweep rates near the threshold
sweep rate for this concentration match the static frequency data
well, but the 0.0028 MHz/s sweep rate begins to falter.
[0025] FIG. 19 shows RBC static images (top row) compared to RBCs
response using 0.0027 MHz/s and 0.0028 Mhz/s (middle and bottom
row). Each test was completed with A+ blood in 0.25 S/m at
1000V.sub.pp/cm. This illustrates the visual similarity between the
static response and the response at a sweep rate near the threshold
sweep rate for the given conductivity of the solution.
[0026] FIG. 20 shows pDEP and nDEP plots of scaled intensity versus
frequency for A+ blood in 0.5 S/m at 1000V.sub.pp/cm. This plot
generally shows the 0.0029 MHz/s sweep rates near the threshold
sweep rate for this concentration match the static frequency data
well, but the 0.0030 MHz/s sweep rate begins to falter.
[0027] FIG. 21 shows RBC static images (top row) compared to RBCs
response using 0.0029 MHz/s and 0.0030 Mhz/s (middle and bottom
row). Each test was completed with A+ blood in 0.50 S/m at 1000
V.sub.pp/cm. This illustrates the visual similarity between the
static response and the response at a sweep rate near the threshold
sweep rate for the given conductivity of the solution.
[0028] FIG. 22 shows pDEP and nDEP plots of scaled intensity versus
frequency for A+ blood in 1.0 S/m at 1000V.sub.pp/cm. This plot
generally shows the 0.0030 MHz/s sweep rates near the threshold
sweep rate for this concentration match the static frequency data
well, but the 0.0030 MHz/s sweep rate begins to falter.
[0029] FIG. 23 shows RBC static images (top row) compared to RBCs
response using 0.0030 MHz/s and 0.0031 MHz/s (middle and bottom
row). Each test was completed with A+ blood in 1.00 S/m at 1000
V.sub.pp/cm. This illustrates the visual similarity between the
static response and the response at a sweep rate near the threshold
sweep rate for the given conductivity of the solution.
[0030] FIG. 24 shows RBC static images (top row) compared to RBCs
response using a sweep rate of -0.0024 MHz/s (bottom row). Each
test was completed with A+ blood in 0.10 S/m at 1000
V.sub.pp/cm.
[0031] FIG. 25 shows pDEP and nDEP plots of scaled intensity versus
frequency for A+ blood in 0.10 S/m at 1000 V.sub.pp/cm using the
reverse sweep method as illustrated by the images in FIG. 24.
[0032] FIG. 26 shows RBC static images (top row) compared to RBCs
response using 0.0024 MHz/s (bottom row). Each test was completed
with A+ blood in 0.10 S/m at 1000 V.sub.pp/cm.
[0033] FIG. 27 shows pDEP and nDEP plots of scaled intensity versus
frequency for A+ blood in 0.10 S/m at 1000 V.sub.pp/cm using the
reverse sweep method as illustrated by the images in FIG. 26.
DETAILED DESCRIPTION
[0034] Before any embodiments of the invention are explained in
detail, it is to be understood that the invention is not limited in
its application to the details of construction and the arrangement
of components set forth in the following description or illustrated
in the following drawings. The invention is capable of other
embodiments and of being practiced or of being carried out in
various ways. Also, it is to be understood that the phraseology and
terminology used herein is for the purpose of description and
should not be regarded as limiting.
[0035] Alternating current (AC) dielectrophoresis (DEP) experiments
for biological particles in microdevices have typically been
applied at fixed frequencies. Reconstructing the DEP response curve
from static frequency experiments is laborious, but is important
for ascertaining differences in dielectric properties of biological
particles. The disclosed systems and methods, on the other hand,
employ the novel concept of sweeping the frequency as a function of
time to rapidly determine the DEP response curve from fewer
experiments. Homogeneous 6.08 .mu.m polystyrene (PS) beads were
initially used as a model system to determine whether sweeping the
frequency would be a viable method for generating DEP responses and
then to identify an optimal sweep rate. Subsequent experiments were
performed using the sweep rate approach with -7 .mu.m red blood
cells (RBC) to verify that this approach would also work with
biological samples. A Au/Ti quadrapole electrode microfluidic
device was used to separately subject particles and cells to
10V.sub.pp AC electric fields at frequencies ranging from 0.010-2.0
MHz over sweep rates from 0.00080 to 0.17 MHz/s. PS beads exhibited
negative DEP assembly over the frequencies explored, likely due to
Maxwell-Wagner interfacial polarizations. Results demonstrate that
frequency sweep rates must be slower than particle polarization
timescales; in some embodiments, sweep rates near 0.00080 MHz/s
yielded DEP behaviors very consistent with static frequency DEP
responses for both PS beads and RBCs, although higher sweep rates
may also be employed.
[0036] Accordingly, disclosed herein are systems and methods for
identifying a particle using dielectrophoresis (DEP). Embodiments
of the methods and systems disclosed herein may be used to
distinguish between different types of particles based on
differences in dielectric properties of the particles. In various
embodiments, the particles that are analyzed may include
polystyrene beads (e.g. for testing purposes) or cells such as
blood cells; in particular, different subtypes of red blood cells
(e.g. A+, A-, O+, O-, etc.) may be distinguished based on the
surface charge differences of the red blood cell subtypes (e.g. due
to differing antigens on the cell surfaces). In general, the
particles may range in size from about 1-50 .mu.m and should be
detectable (e.g. through optical or electrical means) using the
particle detector (e.g. an imaging system).
[0037] A system according to embodiments of the invention may
include a microfluidic device (which in some embodiments may
include an enclosed microfluidic chamber) having a microelectrode
array disposed in the fluid path of the microfluidic device. In
various embodiments, particles are delivered to the vicinity of the
microelectrode array using the microfluidic device prior to data
collection. In certain embodiments, data collection is performed in
a "batch-wise" manner, i.e. a group of particles is delivered to
the microelectrode array and fluid movement is then stopped before
data collection begins so that particle movements that are observed
are due to dielectrophoresis.
[0038] The microelectrode array in one embodiment is a quadrapole
arrangement as shown, for example, in FIGS. 1, 2, 4, and 5. In this
arrangement four electrodes are arranged in an "X" with a gap in
the center (FIG. 5). Other possible arrangements of electrodes
include interdigitated electrodes, V-shaped electrodes, circular
electrodes, and T-shaped electrodes. In various embodiments, the
electrodes are arranged so that oppositely charged electrodes are
not parallel to one another, as this would create uniform fields
whereas other, non-parallel geometries create non-uniform electric
fields. In general, the electrodes are arranged so that they create
a spatially non-uniform field. The electrodes are attached to the
bottom of the microfluidic device and the particles that are
delivered to the device are initially distributed in the vicinity
of the electrodes in a random arrangement (e.g. see upper left
panel of FIG. 2a) before any electrical signal is applied. The
microelectrode array may be made by depositing metal strips onto a
glass slide with a cover having a microfluidic channel being bonded
on top of the glass slide (FIG. 1c). As shown in FIG. 1c, opposing
pairs of electrodes may be electrically coupled using copper wires,
as shown, with the leads (i.e. ground and "hot" AC signal) of a
signal generator being connected to the copper wires. In various
embodiments, pairs of electrodes may be electrically coupled as
shown in FIG. 1c so that, upon stimulation, each electrode is
90.degree. out of phase from the others to create a traveling wave
signal.
[0039] Once particles have been delivered to the microelectrode
array, a signal generator is used to deliver an oscillating voltage
to the electrodes. In various embodiments, the voltage is applied
at a peak-to-peak amplitude of 0.1V.sub.pp, 1V.sub.pp, 10V.sub.pp,
100V.sub.pp, or other suitable amplitude. In various embodiments,
the oscillating voltage is applied at frequencies of at least about
0.001 MHz, at least about 0.005 MHz, at least about 0.01 MHz, at
least about 0.05 MHz, at least about 0.1 MHz, at least about 0.5
MHz, or at least about 1.0 MHz. In other embodiments, the
oscillating voltage is applied at frequencies of no more than about
10.0 MHz, no more than about 5.0 MHz, no more than about 2.0 MHz,
no more than about 1.0 MHz, or no more than about 0.5 MHz.
[0040] In particular embodiments, the frequency of the oscillating
voltage is varied, for example from a low frequency to a high
frequency, in order to collect data at a variety of different
frequencies, a process referred to as "sweeping" the frequency. In
various embodiments, comparable results are obtained when the
frequency is swept from a high frequency to a low frequency.
Sweeping the oscillating voltage using a continuously varying
frequency permits a relatively large amount of data to be gathered
in a short period of time. The rate at which the frequency sweep,
i.e. the "sweep rate," may vary from 0.00001 MHz/s to 0.1 MHz/s. In
certain embodiments, the continuously varying frequency may be
approximated by a series of discrete, step-wise changes in
frequency with an increment ranging from about 10 nHz to about 10
Hz. As discussed herein, the optimum sweep rate may depend on
conditions such as the conductivity of the solution in which the
particles are suspended. The present inventors have found that when
the frequency is swept above a certain maximum sweep rate the
frequency changes too quickly, such that the particles do not have
sufficient time to respond to the voltage signal at a given
frequency before the signal changes to the next frequency. If the
oscillating voltage signal is varied too quickly, i.e. above the
maximum sweep rate, the observed particle movements and
distributions will be inaccurate and could lead to an inconclusive
or erroneous particle identification. Thus, in certain embodiments
the maximum sweep rate is no more than about 0.003 MHz/s, no more
than about 0.0029 MHz/s, no more than about 0.0028 MHz/s, no more
than about 0.0027 MHz/s, no more than about 0.0026 MHz/s, no more
than about 0.0025 MHz/s, no more than about 0.0020 MHz/s, no more
than about 0.0015 MHz/s, no more than about 0.0010 MHz/s, no more
than about 0.0008 MHz/s, or no more than about 0.0005 MHz/s. In
various embodiments, a minimum sweep rate of at least about 0.00005
MHz/s, at least about 0.0001 MHz/s, at least about 0.00015 MHz/s,
at least about 0.0002 MHz/s, at least about 0.0004 MHz/s, at least
about 0.0005 MHz/s, at least about 0.00075 MHz/s, or at least about
0.0010 MHz/s may be used.
[0041] While the oscillating voltage is being applied to the
microelectrode array at varying frequencies, data may be collected
to determine the spatial distribution of the particles within the
microfluidic device, particularly the particles in the vicinity of
the electrodes, as a function of time. Particle detection may be
carried out with systems which are capable of identifying the
spatial distributions of the particles with sufficient temporal
(e.g. operating at 0.1-10 Hz) and spatial (e.g. capable of
resolving 0.1 .mu.m.times.0.1 .mu.m areas) resolution.
[0042] In some embodiments, images are collected at regular
intervals (e.g. at video rates of 30 frames/sec or at other, slower
rates such as 1 image or frame/sec) while sweeping the oscillating
voltage. The images may be processed (for example several
sequential video-rate frames may be averaged together) and the
images or subregions thereof may be analyzed to characterize
particle distribution and behavior at one or several frequencies.
The analyses may include one or more of determining the particles'
intensity profiles, transient responses, and velocities. Analyses
may be conducted at one or more discrete locations within the
images including along one or more lines, e.g. lines running
between electrode tips. Analysis patterns for a sample which
includes an unknown particle may be compared to patterns generated
under equivalent conditions using known particles to determine the
identity of the unknown particle. In certain embodiments in which
only a few (e.g. 2-3) types of particles need to be distinguished,
it may be sufficient to analyze only two subregions of the particle
distribution in order to reliable distinguish the particle types
from one another. In other embodiments in which a larger number of
particle types are possible it may be necessary to analyze more
subregions in order to reliably distinguish among particle types.
For example, in order to distinguish among the eight red blood cell
subtypes (A+, A-, B+, B-, O+, O-, AB+, and AB-) it may be necessary
to analyze at least 4 different subregions of the particle
distribution, and greater accuracy would be achieved by including
more of the particle distribution in the analysis. In general,
regions and patterns on the substrate are selected for analysis
based on the areas that are expected to have the greatest change in
electric field patterns and hence the greatest change in particle
distribution at different frequencies, so as to provide the most
information for distinguishing between particle types. Additional
methods for analyzing DEP behavior of particles are disclosed in
Salmanzadeh et al. (2012), Rozitsky et al. (2013), and An et al.
(2014), each of which is incorporated herein by reference.
[0043] A system for carrying out embodiments of the invention may
include a controller for carrying out or more of the procedures
disclosed herein. The controller may be in operative communication
with one or more of the signal generator (which in turn is in
communication with the microelectrode array) and the particle
detector (e.g. imaging system). The controller may be a part of or
in communication with a computer system. The computer system may be
part of an existing computer system (e.g. on a smartphone, desktop
computer, on-board computer, etc.) or may be implemented as a
separate, standalone unit that is in local or remote communication
with other components. The computer system(s) may be in wired or
wireless communication with other systems through a combination of
local and global networks including the Internet. Each computer
system may include one or more input device, output device, storage
medium, and processor (e.g. a microprocessor). Input devices may
include a microphone, a keyboard, a computer mouse, a touch pad, a
touch screen, a digital tablet, a track ball, and the like. Output
devices include a cathode-ray tube (CRT) computer monitor, an LCD
or LED computer monitor, touch screen, speaker, and the like.
[0044] The computer system may be organized into various modules
including an acquisition module and an output module along with the
controller, where the controller is in communication with the
acquisition module and the output module. The various modules for
acquiring and processing data and for returning a result may be
implemented by a single computer system or the modules may be
implemented by several computer systems which are in either local
or remote communication with one another.
[0045] Storage media include various types of local or remote
memory devices such as a hard disk, RAM, flash memory, and other
magnetic, optical, physical, or electronic memory devices. The
processor may be any known computer processor for performing
calculations and directing other functions for performing input,
output, calculation, and display of data in accordance with the
disclosed methods. In various embodiments, implementation of the
disclosed invention includes generating sets of instructions and
data that are stored on one or more of the storage media and
operated on by a controller, where the controller may be configured
to implement various embodiments of the disclosed invention.
[0046] Some embodiments the system may be in the form of a portable
or handheld device which may be self-contained, including the
microfluidic device, microelectrode array, the controller, and
additional components such as a power supply and input/output
capabilities.
[0047] Without being limited as to theory, DEP enables
phenotypically similar biological cells to be discriminated based
on dielectric properties including the conductivity and
permittivity of the membrane, cytoplasm, and other structurally
relevant organelles. Cell components and structure contribute to a
cell's signature dielectric dispersion. A particle's complex
permittivity is frequency dependent and characterized by dielectric
dispersion regions (y, .beta., and .alpha., where
w.sub..alpha.<w.sub..beta.<w.sub.y) specific to an applied
frequency. Certain embodiments of this work to illustrate sweep
rates uses frequencies in the range of 0.010 to 2.0 MHz in the
.beta.-dispersion region because the Clausius-Mossotti factor,
which governs sign and polarization strength, for polystyrene beads
is nearly constant over this range. Maxwell-Wagner theory describes
the polarization mechanism of particles in the .beta.-dispersion
region as interfacial polarization where moving charges build
around the interface of a charged or charge-neutral particle and
exchange ions with the suspending medium. Interfacial particle
polarization creates an induced dipole moment such that the
particle experiences disproportionate forces in each half cycle of
the alternating current (AC) field resulting in net particle
movement.
[0048] Polarized particles can exhibit either positive
dielectrophoresis (pDEP) or negative dielectrophoresis (nDEP) as a
consequence of the frequency-dependent polarizability of the
particle in the surrounding medium. Particles that exhibit pDEP
move to high electric field regions and particles that exhibit nDEP
move to low electric field regions. This motion up and down
electric field gradients is described by the Clausius-Mossotti
factor for spherical particles.
f cm = ~ p - ~ m ~ p + 2 ~ m , ~ i = ~ i + .sigma. i .omega. j ,
##EQU00001##
[0049] where {tilde over ( )}.sub.i is the complex permittivity of
the particle (i=p) and of the medium (i=m), which are both
functions of conductivity (.sigma.), permittivity ( ), and angular
frequency (.omega.).
[0050] Polarization is not an instantaneous event; charge transport
into the interface takes a few microseconds in response to the
electric field. Maxwell-Wagner dielectric relaxation is a physical
phenomenon related to the transport delay of cation and anion
alignment in and around the interface of the dielectric particle.
At lower frequencies (<.about.10 MHz), particle polarization is
driven by this conductive polarization. At higher AC frequencies,
charges do not have enough time to move into and around the
interface double layer, so particles experience polarization lag
time as a result of the rapidly modulating field and do not reach
maximum polarization.
[0051] Maxwell-Wagner dielectric relaxation is characterized by a
time constant, .tau..sub.MW, which is unique to each particle or
cell due to the time constant's dependence on the cell dielectric
properties. The time required for a particle to reach maximum
polarization is given by Eq. (3) (see Morgan et al. (2003), p. 27;
see also Grosse et al. (2010) and Mittal et al. (2008), each of
which is incorporated herein by reference):
.tau. TW = ( p + 2 m ) 0 .sigma. p .+-. 2 .sigma. m .
##EQU00002##
[0052] Typical relaxation times for particle polarization vary from
pico- to microseconds (see Morgan et al. (2003), p. 27; see also
Grosse et al. (2010) and Mittal et al. (2008)), and the calculated
.tau..sub.MW for polystyrene (PS) beads in our Epure H.sub.2O
medium at 2.5.times.10.sup.-4 S/m is 3.5 las. Thus, a single AC
cycle is on the order of 0.01 to 2.mu.s; the time delay in ion
transport within a static frequency field of 0.010 to 2.0 MHz is
such that 2 to 350 AC cycles must be completed before the particle
experiences full polarization.
[0053] The Maxwell-Wagner dielectric timescale for charge transport
into and around the interface becomes important when the frequency
is swept, i.e. changes as a function of time. FIG. 1a highlights
the Maxwell-Wagner particle polarization at the interface under
static frequency as well as slow and fast frequency sweep rates. At
a static frequency in the .beta.-dispersion region, the particle
experiences a constant frequency field such that the relaxation
time is not a factor and the particle fully polarizes. A particle
in a field with a slowly changing frequency sweep has a relaxation
time, .tau..sub..DELTA.FS, that is less than .tau..sub.MW and thus
the particle interface fully polarizes. Tn contrast, a particle in
a fast frequency sweep has a relaxation time, .tau..sub..DELTA.FS,
that is larger than .tau..sub.MW and the particle interface does
not have time to fully polarize in the field. PS beads are lossy
dielectric particles treated as homogeneous spheres and are thus an
idealized particle to examine new techniques, devices, or
approaches to dielectrophoretic characterizations. Our system is
easily able to discern pDEP and nDEP transitional behavior and
adaptable to new frequency sweep techniques. The homogeneous
spherical DEP polarization model for PS beads ( =2.5 and
.sigma.=9.4.times.10.sup.-5 S/m) suspended in Epure H.sub.2O
displays only nDEP behavior over 0.010 to 2.0 MHz.
[0054] Thus, microfluidic and dielectrophoretic (DEP) technologies
enable a wide variety of particle polarizations with nonuniform
electric fields on microchips to achieve particle manipulation,
concentration, separations, and property-based identification.
Particles can include bioparticles (e.g. DNA, viruses, or proteins)
as well as cells (e.g. blood cells, cancer cells, stem cells, and
yeast). The advantages to coupling DEP with microfluidics are small
sample size (on the order of microliters), rapid analysis
(approximately minutes to achieve results), minimal sample
preparation, and minimal waste production. Traditionally, DEP
experiments are completed at static, fixed frequencies such that
maximum particle polarization can be achieved and measured.
Multiple experiments are conducted, each at discrete frequencies
over the range of interest to stitch together DEP response spectra;
this is a labor-intensive approach. Further disadvantages are that
extended field exposure times at fixed frequencies can change
particle properties or cell viability. As disclosed herein, it is
demonstrated that frequency can be swept with time in the
.beta.-dispersion region thus enabling interrogation of cells at
multiple frequencies within a short time period. The benefits of
using a frequency sweep technique are that nearly continuous DEP
response curves, when coupled with automated response analysis, can
be compiled in near real time and the number of experiments needed
to obtain particle DEP spectra are greatly reduced.
[0055] Traditional DEP measurements are completed at single static
frequencies in order to compile frequency by frequency, the DEP
spectrum for a particle or cell system. This method is laborious
and, as disclosed herein, requires time for particles to fully
polarize for accurate observed DEP responses. The present
disclosure describes the use of frequency sweeps as a means to more
efficiently interrogate multiple frequencies in a single
experimental run and systematically compared the responses to the
nDEP response at fixed frequencies between 0.010 and 2.0 MHz. It
was observed that frequency sweep rates influence the DEP response
of PS beads and RBCs and further, the permissible frequency sweep
rate is particle or cell dependent. The underlying mechanism
appears to be the same. At slower sweep rates, particles have more
time to polarize in the electric field and therefore a more
accurate and reproducible DEP spectrum can be obtained. At faster
frequency sweep rates, the particles are unable to achieve maximum
interfacial polarization because of the dielectric relaxation time
scale so the observed DEP response does not match the true DEP
behavior of the particle.
[0056] For polystyrene beads at frequency sweep rates below 0.0063
MHz/s, responses correlate closely with dielectric responses of
particles subjected to a static frequency potential. In the PS bead
system, 0.056 MHz/s is the transitional sweep rate where the
particle dielectric relaxation is approximately the same order of
magnitude as the shifts in frequency within the sweep. Dielectric
responses continue to track the static frequency responses,
although reproducibility is diminished. However as this sweep rate
is increased further, conductivity dominated interfacial
polarizations cannot be established and the PS bead frequency sweep
data does not coincide with static frequency measurements.
[0057] For full utility in DEP experiments, this frequency sweep
rate methodology must be translatable to cell systems. Results
illustrated that only 0.00080 MHz/s accurately predicted the static
frequency DEP responses of human RBCs. Red blood cells are
substantially more morphologically and dielectrically complex than
polystyrene beads. Calculation of the dielectric relaxation time,
taking into account only the membrane permittivity and conductivity
of 4.4 and 10.sup.-7 S/m, respectively (Gascoyne et al. (2004),
incorporated herein by reference) yields a dielectric relaxation
time .about.4.6 .mu.s roughly corresponding to 0.21 MHz. This
relaxation time is larger than the PS bead relaxation time of 3.5
.mu.s, so the optimal frequency sweep rate for red blood cells
would be slower than that for PS beads. This result suggests that
for each new cell system of interest it is imperative to determine
the optimal frequency sweep rate for accurately and reproducibly
interrogating the behavior of that cell. This work outlines a
systematic technique to make comparisons between frequency sweep
rate and static frequency shown. For all cell systems, sweep rates
that are too fast will not allow the cell adequate time to polarize
and will result in inaccurate and less reproducible DEP responses.
An optimal frequency sweep rate can be estimated by calculating the
Maxwell-Wagner dielectric relaxation time for the particle/cell of
interest, provided the cell's permittivity and conductivity is
known. The frequency sweep rate chosen for the DEP study should
then remain at frequencies below the inverse dielectric relaxation
time (1/.tau..sub.MW) for 5-45 s (longer times spent below the
threshold give better DEP predictions).
[0058] Since the cell's permittivity and conductivity are
determined from the frequency dependent DEP spectrum, this presents
a cyclical situation. However, this work has demonstrated that
frequency sweep rates slower than 0.00080 MHz/s can yield accurate
DEP response of PS beads as well as RBCs. This sweep rate may
therefore be translatable to other cell systems. In addition, at
higher frequencies where the polarization mechanism is more heavily
influenced by charge permittivity effects through the membrane and
cell cytosol, it is possible that slow frequency sweep rates can
still accurately capture DEP response spectra. Lastly, this
frequency sweep rate technique will enable researchers to obtain
accurate and continuous DEP response spectra in shorter experiment
times.
[0059] The following non-limiting Examples are intended to be
purely illustrative, and show specific experiments that were
carried out in accordance with embodiments of the invention.
EXAMPLES
Example 1
[0060] In this Example, dielectrophoretic responses of PS beads
(model system) were quantified at both static frequencies and
frequency sweeps at rates ranging from 0.00080 to 0.17 MHz/s over
the .beta.-dispersion frequency range of 0.010-2.0 MHz. PS bead
motion in the electric field was imaged with video microscopy and
analyzed using three techniques: intensity profiles, transient
response, and particle velocities. Data shows that frequency sweep
rates impact particle polarization due to dielectric relaxation
limitations. This frequency sweep technique was further extended in
this Example to negatively charged biconcave red blood cells
(RBCs), which are an important cellular system for medical disease
diagnostics.
[0061] The microdevice shown in FIG. 1c was fabricated according to
previously published microfabrication techniques (Grom et al.
(2006), incorporated herein by reference), with the 100 .mu.m wide
electrodes spaced 200 .mu.m apart aligned at 90.degree. along the
bottom of a 70 pm deep by 1000 .mu.m wide microfluidic chamber as
shown in FIG. 1b. Polystyrene beads (Cat No. PP-60-10, Spherotech,
Lake Forest, Ill., USA), 6.08 .mu.m in diameter were centrifuged at
1300 min.sup.-1 for 5 mins to separate the beads from the liquid.
The PS beads were resuspended in Epure H.sub.2O (18 M.OMEGA. or
2.5.times.10.sup.-4 S/m) at a 1:10 (bead to water) volumetric
dilution ratio and vortexed. Microdevice was pre-rinsed with Epure
H.sub.2O and Alconox precision cleaner (Cat No. 1104, Alconox Inc,
White Plains, N.Y., USA) to prevent bead adhesion. PS beadEpure
H.sub.2O suspension was pumped to the microchamber using a syringe.
Time was allowed for inlet and outlet pressures to equalize and
flow to stop. The function generator (Agilent 33250A, Agilent,
Santa Clara, Calif., USA) was connected via copper leads to produce
a 10V.sub.pp AC sine wave with frequencies ranging from 0.010-2.0
MHz at specific frequency sweep rates 0.00080, 0.0011, 0.0030,
0.0063, 0.013, 0.021, 0.028, 0.042, 0.056, 0.083, and 0.17 MHz/s.
Frequency sweeps linearly increased the applied frequency as a
function of time. Greater than five (n>5) static frequency
experiments were completed at each frequency 0.010, 0.020, 0.030,
0.040, 0.050, 0.20, 0.40, 0.60, 0.80, 1.0, 1.2, 1.4, 1.6, 1.8, and
2.0 MHz by applying 10V.sub.pp for 90 s. These DEP static frequency
responses were compared to each frequency sweep rate DEP responses.
For the static and frequency sweep experiments, the PS bead
concentration was between 238-263 beads in the t=0 field of view.
Video recordings of experiments were taken at 30 fps at
640.times.480 pixels/image using LabSmith SVM Synchronized Video
Microscope with a 10.times. objective (LabSmith, Livermore, Calif.,
USA).
[0062] Video recordings of PS beads DEP behaviors were analyzed
with ImageJ (NIH, Bethesda, Md.) using intensity, transient slope,
and velocity measurements. Since PS beads only exhibit nDEP over
the frequency range of interest, intensity data acquisition from
images was completed by drawing a rectangular box at the device
center, I.sub.CTR, and background, I.sub.BK measured in a location
with no PS beads present (See FIG. 2a). ImageJ Z Project function
was used to average the pixel intensities in the specified boxed
region. The initial background, I.sub.BK(t=0) and center intensity,
I.sub.CTR(t=0) were subtracted from the center and background
intensity at each time, I.sub.CTR(t) and I.sub.BK(t), and then a
normalized intensity was calculated by dividing by the maximum
intensity experienced by the PS beads, (Eq. (4)):
I _ DEP , t = [ ( I CTR - I BK ) t + ( I BK - I CTR ) t = 0 ] [ ( I
CTR - I BK ) t + ( I BK - I CTR ) t = 0 ] MAX ##EQU00003##
[0063] This normalized intensity tracked the real-time magnitude of
the PS bead DEP response, which had two distinct regions: transient
where beads moved with nDEP toward the center, and steady-state
(SS) where beads achieved tight packing at the device center. These
two responses were analyzed separately via transient slope and
particle velocity.
[0064] The transient response of the PS beads was extracted from
the steady-state response via signal processing in which the delay
and rise time were quantified. The PS bead delay time, t.sub.d, was
characterized as the time required for the intensity response to
reach 50% of the final intensity response for the first time. The
rise time, t.sub.T, was determined as the time needed for the
intensity response to reach 100% of the final intensity response
for the first time (Ogata et al. (1978), pp. 517-518, incorporated
herein by reference). This allowed the transient response to be
segmented and a linear trend line was fit between t.sub.d and
t.sub.T where t.sub.d<t.sub.T. A comparison of the transient
slope for frequency sweep rates and static frequency measurements
is given in FIG. 3c. PS bead velocities were determined from the
original video by tracking the x-, y-pixel position of individual
PS beads from 0-50 s. PS bead located within 5 .mu.m of electrode
tips were selected to control for similar electric field gradients.
This procedure was repeated for at least 10 beads in each specific
frequency sweep rate and static experimental video.
[0065] For experiments involving human RBCs, blood of the
appropriate type (e.g. O+, A+, etc.) was obtained from a single
donor and centrifuged at 1400 rpm for 5 mins to separate the packed
RBCs from the plasma and leukocytes. The packed RBCs were removed,
then resuspended at 1:75 v:v in 0.10 S/m isotonic dextrose buffer
doped with 0.75% BSA (Cat No. A7906, Sigma Aldrich, St. Louis, Mo.,
USA) to prevent cell/device adhesion. This RBC suspension was
syringe-pumped to the microchamber, with time being allowed for
flow to stop after pumping before the 10V.sub.pp signal was applied
over 0.010-0.50 MHz (range reduced to avoid pDEP behavior) at
frequency sweep rates of 0.00080, 0.0063 and 0.056 MHz/s (n=7). RBC
static frequency experiments were completed at 0.010, 0.10, 0.25
and 0.50 MHz at 10V.sub.pp for 90 s (n=7). Video microscopy at
25.times. and 1 fps was obtained with a Zeiss Axiovert Inverted
Light Microscope (Zeiss, Germany). The video images were analyzed
as described herein for the PS beads.
[0066] Frequency sweep rates ranging from 0.00080 to 0.17 MHz/s
were explored to see if the nDEP response of PS beads would vary
and/or correspond to static frequency measurements. The frequency
range was chosen for the relatively consistent Clausius-Mossotti
factor, Re(f.sub.CM) for a homogeneous lossy polystyrene sphere of
0.26 to 0.48 (see FIG. 2c) over the frequency range of 0.010 to 2.0
MHz. Static frequency experiments were completed at fixed values in
this same frequency range. FIG. 2a shows still images from both
static frequency experiments and the frequency sweeps at 0.20,
0.60, and 1.0 MHz. For static frequencies, the response 45 seconds
after field application is shown while for frequency sweeps of
0.0063, 0.056, and 0.17 MHz/s, the image is shown at the time stamp
when the specified frequency is reached. The electrodes are visible
as black shadows in the images and the PS beads assemble due to
nDEP forces at the central electric field gradient minima Data was
examined to determine the sweep rate that most closely approximated
the static frequency response. Frequency sweeps 0.00080 and 0.0063
MHz/s (shown) tracked static frequency, or true, DEP responses
while the slightly faster sweep of 0.056 MHz/s begins to lag the
true DEP responses and at 0.17 MHz/s and faster, particles were
unable to achieve sufficient polarization to respond sufficiently
in the electric field.
[0067] nDEP responses were quantified via intensity analysis as
described herein for all sweeps and all static frequency
experiments. FIG. 2b illustrates the frequency- (and time-)
dependent intensity for the 0.0063 MHz/s sweep rate images shown in
FIG. 2a. This quantification of the PS bead nDEP response was
correlated to total bead packing via the calibration shown in the
inset. The 188-bead count at the center deviates slightly from the
initial, field off, bead count of 245 because PS beads also move
down the electric field gradient to regions outside of the image
field of view.
[0068] Normalized intensities, Eq. (4), were compiled in FIG. 3a
for SS (i.e. 45 seconds) static frequency nDEP responses and
0.00080, 0.0063, 0.056 MHz/s frequency sweep rate nDEP responses.
The time for sweep responses to achieve the true nDEP static
response decreases as the sweep rate decreases. Frequency sweep
rates 0.00080 and 0.0063 MHz/s are within the 95% confidence
intervals (n=7) of the static steady-state (SS) responses. FIG. 3a
inset shows that the slowest 0.00080 MHz/s sweep rate more quickly
aligns closely with the static frequency responses. FIG. 3b
compares average 0.0063 MHz/s (n=8) to 0.17 MHz/s (n=7) with the
dashed lines signifying the upper and lower limits of the 95%
confidence intervals for I.sub.DEP. The confidence intervals around
the transient 0.0063 MHz/s sweeps are smaller than for 0.17 MHz/s
over much of the frequency range indicating greater reproducibility
at slower sweep rates. Faster sweep rates either do not reach SS or
have a lag before reaching SS (compare to FIG. 2a) suggesting the
bead interface does not fully polarized and thus displays
attenuated nDEP motion.
[0069] The transient behavior was quantified for all static
frequencies and frequency sweeps via a transient slope analysis as
compiled in FIG. 3c. Four static frequency measurements 0.010,
0.60, 1.0 and 2.0 MHz are shown compared to 0.00080, 0.0063, 0.028,
0.056, and 0.17 MHz/s frequency sweep rates. Static frequency
transient slopes range between 0.023-0.095 and are within the 95%
(p<0.05) confidence intervals of 0.00080, 0.0063, and 0.028
MHz/s frequency sweep transient slopes. These slower sweep rates
and 0.056 MHz/s differ at p<0.001 from the fastest sweep rate of
0.17 MHz/s, which is also significantly different at p<0.001
from the static measurements (except for 1.0.times.10.sup.4 Hz with
p<0.01).
[0070] Individual bead velocities were compiled for static as well
as frequency sweeps in FIG. 3d. PS bead velocity corroborates the
intensity profile and the slope analysis that 0.00080 MHz/s
frequency sweep rate closely tracks the bead velocity at static
frequencies. 0.056 MHz/s gives good estimations of static frequency
bead velocity at times greater than 20 s. Based on intensity,
transient slope, and velocity analysis, the slow frequency sweep
rate of 0.00080 MHz/s is most consistent with static frequency DEP
responses.
[0071] There is an observable inverse relationship between the
frequency sweep rate and particle polarization, where slower sweep
rates result in comparable particle polarization characteristics to
static frequency responses. Dielectric relaxation is the driving
force of this relationship; the calculated dielectric relaxation
time Eq. (3) for PS beads in E-pure H.sub.2O at 2.5.times.10.sup.-4
S/m is 3.5 ps, which corresponds to 0.28 MHz. There are two
timescales that influence this behavior: the frequency itself and
the change in frequency per time. The Maxwell-Wagner,
conductivity-driven interfacial polarization mechanism occurs below
.about.0.28 MHz; above this frequency threshold the interfacial
polarization of the PS beads gradually decreases and the particle
permittivity increasingly influences the DEP force. The
experimental frequencies tested were within the range dominated by
Maxwell-Wagner polarization such that maximum particle interfacial
polarization was possible.
[0072] The second timescale of interest is the frequency change per
time or frequency sweep rate, which determines how many consecutive
cycles a particle experiences a specific frequency. At slower sweep
rates, the PS beads experience a specific frequency for a large
number of cycles and thus the beads have time to polarize because
the timescale of the frequency change is slower than the dielectric
relaxation time. A particle must experience a single frequency
during the sweep for a minimum of 3.5 .mu.s for maximum interfacial
polarization to be achieved. Upon polarization, the particle, which
its current DEP force has to overcome inertia and Stokes drag to
achieve observable particle motion down the electric field
gradient. At static frequencies, it takes roughly 5 s for maximum
velocity to be attained (see FIG. 3d, AC field applied at t=5 s)
and as much as 45 s for final SS at the field gradient minima to be
reached. As the sweep rate increases, the dielectric relaxation
time and the rate of change of the frequency approach the same
order of magnitude. Results suggest that 0.056 MHz/s is a
transitional sweep rate because the DEP behavior roughly
corresponds to the static behavior of the PS beads. With further
increases in frequency sweep rates, the timescale for frequency
change surpasses the dielectric relaxation timescale such that
particles are unable to fully polarize resulting in an attenuated
DEP response as shown with data in FIGS. 2, 3a, and 3b. FIG. 3b
also demonstrates that the transient behavior of the PS beads is
more reproducible at slower frequency sweep rates, which can be
attributed to the interfacial polarization timescale of the beads.
Implications of the intensity, slope, and velocity analysis
compared with static frequencies are that slow frequency sweep
rates accurately predict the DEP response of PS beads because the
changes in frequency are slower than the characteristic
Maxwell-Wagner dielectric relaxation.
[0073] Thus, a frequency sweep approach can be utilized to attain
accurate DEP behavior of PS beads, provided the sweep rate is
slower than conductivity mediated interfacial polarization
timescale. This result is reliable over frequency ranges where
particle polarization is dominated by the conduction of free
charges from the media. The charges are moving around the PS beads
through the particle-liquid interface inducing a dipole, which
causes PS bead movement down the electric field gradient to the
electrode center. At different sweep rates the rate of movement of
the charges varies which varies the rate of the dipole being
induced, observed as dielectric relaxation. Each sweep rate has a
unique dielectric relaxation time and our results are consistent
with Maxwell-Wagner interfacial polarization theory. 0.00080 MHz/s
is the optimal sweep rate necessary to predict the true DEP
behavior of PS beads because it allows for full or partial (when
the frequency is above 0.28 MHz) polarization.
[0074] Given that the sweep methodology yielded accurate DEP
responses for the ideal system of PS beads, the same methodology
and frequency sweep rates were explored with human RBCs. The three
most successful PS bead frequency sweep rates were reproduced with
human red blood cells: 0.00080 MHz/s, 0.0063 MHz/s and 0.056 MHz/s.
Static frequency experiments were also performed at 0.010 MHz, 0.10
MHz, 0.25 MHz and 0.50 MHz. Seen in FIG. 4a are 25.times.
microscope images taken of the t=45 s final static frequency frames
aligned above the sweep time points that correspond to those four
static frequencies. Qualitatively, the only sweep rate that
accurately matches the static frequency behavior of the human RBCs
is 0.00080 MHz/s. This behavior was further verified by the same
intensity analysis as for PS beads. In FIG. 4b, the scaled
intensity is plotted for 0.00080, 0.0063 and 0.056 MHz/s
experiments (n=8) as compared to the static frequency intensities.
After the initial 10 s transition for the red blood cells to
polarize and overcome drag, the slowest frequency sweep of 0.00080
MHz/s accurately predicts the static frequency behavior and is
highly reproducible, with a very narrow 95% confidence interval
range (FIG. 4c). The fastest sweep rate of 0.056 MHz/s does not
predict the static behavior of the human RBCs and is much less
reproducible, as evidenced by the large 95% confidence interval in
FIG. 4c. From these experiments, we conclude that the optimal
frequency sweep for determining the accurate DEP behavior of RBCs
is 0.00080 MHz/s. Due to the complex dielectric properties of
cells, it is necessary to carefully compare frequency sweep rates
with static frequency behaviors to ascertain optimal frequency
sweep rates that accurately interrogate the cell of interest.
Example 2
[0075] Conditions for Example 2 are the same as described above for
Example 1 except where otherwise stated. FIGS. 5-13 show data
obtained from applying a sweeping oscillating voltage signal of
1000Vpp/cm to human red blood cells in a solution with conductivity
of 0.10 S/m. FIGS. 5-10 show data obtained from A+ RBCs while FIG.
11 shows data from A- RBCs, FIG. 12 shows data from O+ RBCs, and
FIG. 13 shows data from B+ RBCs.
[0076] FIG. 5 shows images of A+RBCs distributed in the vicinity of
quadrapole electrodes during application of an oscillating voltage
having frequencies ranging from 0.01 MHz to 1.0 MHz applied
statically or at sweep rates of 0.00080 MHz/s, 0.0016 MHz/s, or
0.0028 MHz/s. The notation "(1)" denotes RBCs demonstrating nDEP
behavior and "(2)" denotes RBCs demonstrating pDEP behavior. The
RBC's DEP behavior at slower frequency sweep rates (0.00080 MHz/s
and 0.0016 MHz/s) correlates well with the static frequency
response (top row), indicating that these are below the maximum
sweep rate for these conditions. FIG. 6 compares the nDEP (panel
(a)) and the nDEP (panel (b)) intensity profiles of the particles
for the statically applied oscillating voltage as well as at the
various sweep rates tested across the range of frequencies.
[0077] Panel (a) of each of FIGS. 7-13 shows images of particle
distributions at oscillating voltages of 0.70 MHz and 0.80 MHz
collected either with static application of the oscillating voltage
("0 MHz") or while sweeping at the indicated sweep rates. Panels
(b) and (c) of each of FIGS. 7-13 show nDEP (panels (b)) and pDEP
(panels (c)) intensity profiles throughout the frequency range
relative to intensity profiles obtained with statically-applied
oscillating voltages at 0.7 MHz and 0.8 MHz. FIGS. 7-10 include
results from two different experimental runs, R1 and R2.
[0078] Comparison of the images of particle distributions at
different sweep rates relative to distributions obtained with
statically applied oscillating voltages provides an indication of
whether or not the sweep rate is too fast, based on whether the
swept images match those obtained with statically applied
oscillating voltages at the same frequency.
[0079] The data in this example shows the applicability of the
disclosed methods and in particular the similarity in maximum sweep
rates for various blood types. The data also shows the dependence
of the maximum sweep rate on conductivity of the solution in which
the particles (RBCs) are suspended.
Example 3
[0080] Conditions for Example 3 arc the same as described above for
Examples 1 and 2 except where otherwise stated.
[0081] One factor which may affect the maximum sweep rate is the
conductivity of the solution in which the particles are suspended.
Accordingly, experiments were carried out to determine the extent
to which conductivity impacts the maximum sweep rate.
[0082] FIGS. 14-23 show the effect of changes in conductivity on
the maximum sweep rate using red blood cells. When using biological
material, and in particular cells such as red blood cells, it is
important when varying the conductivity of the solution to maintain
the overall tonicity of the solution within a limited range. For
the experiments in FIGS. 14-23, varying combinations of NaCl and
dextrose were combined to achieve the stated levels of conductivity
of 0.10 S/m, 0.25 S/m, 0.50 S/m, and 1.0 S/m while maintaining the
solution at approximately isotonic levels for human red blood
cells; increasing the amount of NaCl increases the conductivity and
proportionately less dextrose is used as NaCl is increased in order
to maintain a relatively constant tonicity (see An et al. 2014,
incorporated herein by reference).
[0083] As shown in FIG. 14, increasing conductance from 0.10 S/m to
1.0 S/m has the effect of increasing the maximum sweep rate that
can be used from less than 0.0026 MHz/s at 0.1 S/m to less than
0.0031 MHz/s at 1.0 S/m. As seen in FIGS. 15-23, using a sweep rate
below the maximum level generates particle distributions at various
frequencies that are equivalent to distributions that are obtained
with the application of an oscillating voltage at a static
frequency. Increasing the conductance permits the use of a faster
sweep rate, which in turn permits data to be collected at a faster
rate.
Example 4
[0084] Conditions for Example 4 are the same as described above for
Examples 1-3 except where otherwise stated.
[0085] The experiments of Example 4 demonstrate that particle DEP
behavior is independent of the `direction` of sweeping, i.e.
sweeping the oscillating voltage signal from a high frequency to a
low frequency generates equivalent results as when the oscillating
voltage is swept from a low frequency to a high frequency.
[0086] FIG. 24 shows RBC static images (top row) compared to RBCs
response using a sweep rate of -0.0024 MHz/s (bottom row). Each
test was completed with A+ blood in 0.10 S/m at 1000 V.sub.pp/cm.
FIG. 25 shows pDEP and nDEP plots of scaled intensity versus
frequency for A+ blood in 0.10 S/m at 1000 V.sub.pp/cm using the
reverse sweep method as illustrated by the images in FIG. 24.
[0087] FIG. 26 shows RBC static images (top row) compared to RBCs
response using 0.0024 MHz/s (bottom row). Each test was completed
with A+ blood in 0.10 S/m at 1000 V.sub.pp/cm. FIG. 27 shows pDEP
and nDEP plots of scaled intensity versus frequency for A+ blood in
0.10 S/m at 1000 V.sub.pp/cm using the reverse sweep method as
illustrated by the images in FIG. 26.
REFERENCES
[0088] Each of the following references is incorporated herein by
reference in its entirety:
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[0098] P. Gascoyne, J. Satayavivad, and M. Ruchirawat, Acta Tropica
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[0099] Various features of the invention are set forth in the
following claims.
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