Senior Design 2010-2011
Point-of-care diagnostic device
for monitoring CD4 levels of
HIV patients in resource-poor
settings
Lina M. Aboulmouna
Peter F. DelNero
Parker A. Gould
Rosalynne R. Korman
Christopher M. Madison
Stephen R. Schumacher
Advisor: Dr. Kevin T. Seale
Abstract
The goal of this project is to design a point-of-care device that quickly and cost-effectively
determines the CD4 count of an HIV-positive patient. This count is essential in determining a
patient’s suitability for antiretroviral treatment. The device is comprised of a microfluidic
platform for immunology and cell trap-based separation of white blood cells, coupled with a
CCD camera to capture and quantify fluorescent signals from tagged CD4 cells. This device is
designed to facilitate a simple, quick diagnosis of a patient’s stage in the HIV/AIDS progression,
which is crucial in the resource-poor medical setting found in many developing countries. The
design parameters include a per-test cost of under $2, minimal power requirements, simple
operation by minimally-trained technicians, and same-day test results. The motivation for this
project stems from the Gates Foundation CD4 Initiative for a low-cost, point-of-care device to
replace flow cytometry for accurate CD4 cell counting in under-developed regions.
Introduction
Acquired immunodeficiency syndrome (AIDS) is a disease caused by the human
immunodeficiency virus (HIV). Not everyone who is HIV-positive has AIDS; only when HIV
has depleted CD4 T helper lymphocytes beyond the given threshold of 200 cells per microliter of
whole blood is the patient considered to have AIDS. There is an inverse relationship between the
replication of HIV-1 and the destruction of lymphocytes. As HIV progresses, more and more
1
HIV-1 RNA circulates in the bloodstream while fewer and fewer CD4 cells are left. CD4
lymphocyte counts are predictive of progression to AIDS and, eventually, death.1
The World Health Organization has declared finding an affordable and effective way to obtain
CD4 lymphocyte counts in resource poor areas a high priority.2 Similarly, the Gates Foundation
has identified low-cost HIV diagnostics as one of its Grand Challenges in Global Health.3 CD4
counts provide important information to an attending physician on the current stage of the
disease, when to initiate antiretroviral treatment, how the patient is responding to treatment, and
when to consider modifying the current treatment regimen. Flow cytometry is the traditional
method for obtaining CD4 counts. However, flow cytometry is generally limited to developed
countries because of its requirements of expensive instrumentation and a trained staff.4 Lacking
the financial and technical means to obtain these CD4 counts, HIV/AIDS treatment in poor
countries is often started too soon or too late, which can result in poor clinical outcomes,
unnecessary burdens on the patient, and imprudent or inefficient use of the limited resources
available.
Along with other signs and symptoms, CD4 lymphocyte counts are used to stage the progression
of HIV infection according to standards set by the Centers for Disease Control and Prevention
(CDC). Patients with HIV who have CD4 counts above 500 cells/µL are in stage 1 infection,
O’Brien, WA, Hartigan, PM, Daar, ES, Simberkoff, MS, and Hamilton, JD. Changes in plasma HIV RNA levels
and CD4þ lymphocyte counts predict both response to antiretroviral therapy and therapeutic failure, VA Cooperative
Study Group on AIDS. Ann Intern Med 126: 939–945 (1997).
1
2
http://www.who.int/hiv/pub/guidelines/artadultguidelines.pdf
3
http://www.nature.com/nm/journal/v13/n10/full/nm1007-1131.html
Rodriguez, WR, et al. A Microchip CD4 Counting Method for HIV Monitoring in Resource-Poor Settings, PLoS
Medicine, July 2005, Volume 2, Issue 7.
4
2
CD4 counts between 500 cells/µL and 200 cells/µL are in stage 2, and CD4 counts of 200
cells/µL and below are in stage 3 and are classified as having AIDS.5
Both the World Health Organization (WHO) and the CDC recognize the importance of CD4
counts in deciding when to initiate antiretroviral treatments and when to adjust treatments. These
organizations have provided guidelines for making these decisions based on the CD4 count for a
particular patient.6
There are other methods of quantifying the progression of HIV and AIDS, such as CD4/CD8
ratios and nucleic acid amplification tests. Based on the CDC’s standards for the stages of HIV
and AIDS, as well the work of others in the field, we have decided to focus this project on
obtaining accurate CD4 counts.
History and Context
Previous work
Rodriguez et al. previously fabricated a microchip similar to our proposed device for HIV
diagnostics.4 However, our device differs significantly in the manner by which a whole blood
sample is tagged and filtered. Also, due to the pumping mechanism we have utilized, our device
is significantly less expensive to fabricate and use.
5
6
http://www.aids-ed.org/aidsetc?page=cm-105_disease#S1X
http://www.who.int/hiv/pub/guidelines/artadultguidelines.pdf
3
Methodology
Microfabrication of device components
Two microfluidic platforms connected by PEEK tubing (150µm inner diameter, 360µm outer
diameter) comprise the HIV test platform. These components are fabricated by PDMS soft
lithography using an SU-8 mold according to protocols developed at the Vanderbilt Institute for
Integrative Biosystems Research and Education (VIIBRE). The protocol is briefly outlined
below, and in Figure 1. The microfluidic device patterns were designed using Autodesk’s
AutoCAD software package. These patterns were reproduced to scale by selectively etching a
chrome-plated glass mask. Master molds were then fabricated on three-inch silicon wafers using
MicroChem SU-8 photoresist and the chrome masks, in accordance with the standard
photolithographic protocol practiced in the VIIBRE cleanrooms. Sylgard 184 PDMS (DowCorning) prepolymer was mixed with the corresponding curing agent at a 10:1 mass ratio, cast
onto the mold, degassed in a vacuum chamber for 20 minutes, and then cured at 70°C for four
hours. The PDMS was then carefully peeled from the mold and inlet/outlet holes were punched
using sharpened Luer-Lock syringe tips.
4
Figure 1: Step-by-step procedures for photolithography and replica molding.
The patterned PDMS and a glass coverslip were then exposed to an oxygen plasma for 30
seconds, and then placed in contact with one another, causing a hydrolysis reaction and a
permanent bond between the PDMS and glass. The microfluidic peristaltic pump was fabricated
using a similar replica molding-based protocol. An SU-8 patterned silicon wafer was spun with
a thin layer of uncured PDMS, and then cured cubes of PDMS were placed above the inlet/outlet
hole patterns. These cubes serve to provide structural stability for the inlet/outlet tubing
connections. This two-layer PDMS device was then allowed to cure at 70°C for 4 hours, along
with a flat, unpatterned, 1 mm thick layer of PDMS in a separate petri dish. After curing, the
two-layer patterned PDMS device (both layers now sealed together) was removed from the
silicon master, and inlet/outlet holes were punched. The device was then bonded to the
concurrently prepared 1 mm thick layer of PDMS using an oxygen plasma.
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Blood Sample Preparation
Whole blood samples were acquired via finger stick from volunteers using the procedure
established by the Vanderbilt University Institutional Review Board. Samples were obtained
using a standard CVS brand finger-stick device. A 75 mm Fischer microhematocrit tube was
used to collect approximately 35L of whole blood. Whole blood was aspirated directly from the
hematocrit tube into the device through PEEK tubing.
Pumping
The peristaltic pump operates by compressing a microfluidic track with ring of ball bearings. The
motor is automatically controlled through a microchip using Arduino software. The pump is also
capable of manual control by rotating the shaft. The flow rate is determined by the diameter of
the microfluidic track, which can be tailored to optimize sample loading.
Figure 2: Hand-crankable peristaltic pump. A novel microfluidic pump was designed which allows
manual pumping of inputs through the device. The pump’s rotation forces fluid through the device, and
the hand-crank mechanism allows for the pump to be operated with no electrical power input. The device
is composed of inlet ports for the various inputs, mixer elements to insure proper mixing, and the circular
array of channels to allow pump action.
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White blood cell trapping
White blood cells were captured using a trap device developed in SyBBURE/VIIBRE. Cells are
captured in the array of U-shaped traps as demonstrated in Figure 3. While red blood cells are
small and flexible enough to squeeze through the gaps in each trap, white blood cells remain
confined. The downstream flow prevents cells from escaping. In order to extract the maximum
number of cells from a volume of blood, the outlet tube was connected to the inlet port and the
sample was recirculated through the device.
Figure 3: Microfluidic trap device. An array of U-shaped structures captures cells as they flow through
the device. (Inset) Magnified diagram is of a cell trap containing two cells (green). Inset by K. Seale.
Fluorescent CD4 labeling with FITC
FITC-conjugated CD4 antibodies were used to label both CD4 Jurkat T lymphocytes and CD4
cells from whole blood. Cells were captured in the trap device, after which fluorescent antibodies
were pumped through. Finally, the traps were rinsed with PBS solution to remove excess
antibodies. Fluorescent images were captured using a Zeiss microscope equipped with a FITC
filter. Off-chip labeling was accomplished by mixing antibody solution in a 1:5 ratio with cells
and incubating for 30 minutes prior to loading the trap chambers.
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Time-resolved fluorescent imaging
Latex beads containing europium were conjugated to anti-CD4 antibodies according to the
protocol developed with the aid of Dr. Robert Buck of Gauge Scientific:
1. Suspend antibodies and CMEUs (carboxylate-modified europium nanoparticles) at 30 g
IgG/mg CMEU in the coating buffer: 10mM NaPO4 pH 8.0 .
2. Allow the antibodies to coat the CMEUs for 1-2 hours, with gentle shaking.
3. After the coating, spin down the CMEUs, remove supernatant, and resuspend in blocking
buffer: either 10 mg/ml BSA in buffer, or 5% PEG in buffer.
4. Wash 2 or 3 times: Spin down the CMEUs at 10,000-12000g, remove supernatant,
resuspend in blocking buffer.
5. Spin down CMEUs, remove supernatant, resuspend in Conjugate Dilution Buffer
(obtained from Gauge Scientific).
The Vanderbilt Reader, purchased from Gauge Scientific and shown in Figure 4, enables
microsecond resolution of digital image acquisition, allowing autofluorescent noise to diminish
before collecting images of the europium signal, as shown in Figure 5.
Figure 4: The Vanderbilt Reader. A portable, point-of-care time resolved fluorescence (TRF) platform.
This imaging device connects to a laptop via a USB connection.
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Figure 5: TRF imaging generates a fluorescent excitation but does not capture an image until after a short
time delay. This time delay allows cellular auto-fluorescence and background fluorescence (blue line) to
decay to minimal levels, while the fluorescence from europium nanoparticles (red line) remains strong.
Results and Discussion
The microfluidic peristaltic pump was able to induce precise and reliable flow rates in the cell
trap device. Manual operation was capable of controlling nanoliter volumes. Each revolution of
the bearing yields approximately 200 nL of flow. In addition, the feasibility of direct trap loading
and cell labeling on chip via aspiration of whole blood directly from a microhematocrit tube was
confirmed experimentally: this result is summarized in Figure 6. This ability to perform all of
the required mixing on chip represents a significant reduction in the difficulty of operation,
thereby eliminating the need for pipets and trained technicians. By rinsing the pump device with
buffer solution (and replacing the cell trap device), a second test can be performed immediately
using the same blood sample. A second test provides significant confirmation to the outcome of
the first test, which allows for more confident diagnosis. Flushing the pump with ethanol
immediately prepares the device for the next patient.
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Figure 6: FITC-CD4 antibodies identify CD4 cells in whole blood. Although the CD4 cells are initially
indistinguishable in a sea of red blood cells (A), they become discrete when illuminated with fluorescence
(B). As whole blood is flowed through the device, red blood cells pass through while some white blood
cells are trapped. DIC (C) and FITC (D) images were taken at t = 0 sec, 6 sec, and 6 min. FITC images
were thresholded (E) and overlayed on top of the corresponding DIC images (F). The number of trapped
CD4 cells increases over time from 1 to 2 to 4, suggesting that the number of trapped CD4 cells will
continue to increase as the whole blood is recirculated through the device.
The multitrap nanophysiometer captured white blood cells (WBC) from whole blood.
Recirculation of the blood helps to increase the cell trapping efficiency, which is crucial to
producing a reliable diagnosis of CD4 cells per microliter. Fluorescent microscopy images show
accumulation of CD4 cells over time in a localized field of view due to trapping, as seen in
Figure 6. Alternative trap layouts with increased density and offset patterning were fabricated on
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chrome masks to optimize WBC capture. The trap device is disposable and affordable, costing
approximately $0.15 per chip.
On-chip fluorescent labeling of WBCs from whole blood samples was performed with FITCconjugated anti-CD4 antibodies. Images were acquired from the Zeiss optical microscope and
the ImageJ software suite was used for image analysis: several representative images are
displayed in Figure 7. The labeling demonstrated selective binding to CD4 cells in whole blood
with significant signal output after rinsing with buffer. This demonstrated that the only manual
sample preparation required will be the original finger prick and loading a new trap device.
Figure 7: CD4 cells can be labeled on chip. FITC-CD4 antibodies were flowed into a device containing
Jurkat T cells. The excess antibodies were rinsed from the device, revealing the presence of newly-labeled
CD4 Jurkat cells. A series of fluorescent pictures (A) is given, as well as the overlay of the fluorescent
and DIC images (B). This is proof of concept that CD4 cells can be labeled on chip.
Attempted conjugation of anti-CD4 antibodies to carboxylate-modified europium chelate
nanoparticles did not yield detectable binding to CD4 cells. A reliable conjugation and labeling
protocol has been investigated in collaboration with Dr. Buck of Gauge Scientific and Dr. Jay
Dickerson of the Vanderbilt Physics Department. The detection threshold using the Vanderbilt
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Reader portable TRF device was approximately 1:25 dilution from the original nanoparticle
concentration (1% solids). These detection threshold test images are displayed in Figure 8.
1:1
1:10
1:25
1:50
1:100
Figure 8: TRF images of cell traps. Europium nanoparticles were pumped into a trap array, and a TRF
images were taken. This figure demonstrates that europium phosphorescence can be detected at dilutions
as low as 1:25. Also, the resolution of the TRF image was high enough to illustrate the microscale
structure of the trap array, which promises to aid diagnosis by allowing trap-by-trap image analysis
instead of less precise macroscale analysis.
Healthy and immuno-suppressed data were simulated by combining measurements from the
FITC-labeled whole blood with accepted concentrations of CD4 lymphocytes. Cell size and
signal intensity data were used to calculate the relative signal ratio in healthy versus diseased
patients. The absolute quantification of CD4 cells per microliter of blood is a function of the total
signal intensity in the Vanderbilt Reader and the fraction of CD4 cells captured during
recirculation. The signal intensity of the europium-chelate nanoparticles was used to estimate a
minimum threshold of trapped cells needed to obtain a detectable signal in the Vanderbilt
Reader, and from this threshold the minimum number of recirculation passes was calculated.
Assuming the europium fluorescence of a particular labeled cell is equivalent to the fluorescent
intensity observed in the device from the conjugated europium solution, calculations suggest that
6.8% of the device area must be illuminated to reach the detection threshold. However, this
assumption depends on the concentration of CD4 receptors on the lymphocytes, which must be
12
determined experimentally with europium conjugated particles. According to these results,
approximately 22700 cells must be captured; a finger-stick equivalent of 40% of CD4 WBCs in
healthy patients and 150-250% in an AIDS patients. Therefore, unless the actual signal strength
of europium-labeled cells is higher than the original diluted signal, a magnifying lens of at least
10x power should be added to the TRF detection system.
Detection Threshold Calculations
We performed a theoretical analysis of the fluorescent behavior of cells the trap device. The
variables defined below are used in Equation 1.
s =
n =
n+ =
f+ =
p =
ℓ =
number of pixels in the field of view (FOV) of the image of the trap device
number of white blood cells in FOV
number of CD4 cells in FOV
fraction of white blood cells that are CD4
number of pixels that are lit due to fluorescence of a single tagged CD4 cell
fraction of FOV that is illuminated
The total number of pixels in FOV that are lit is given by (n+)(p), which is equal to (f+)(n)(p).
Therefore, the luminance ℓ is given by Equation 1
ℓ=
𝑓+ 𝑛𝑝
(1)
𝑠
This value is exact if the cells in the trap device can be resolved by the imaging device (i.e. a
single cell’s size is multiple pixels, or, more precisely, the fluorescence of a tagged cell is
multiple pixels). However, this resolution constraint requires a powerful microscope and is
therefore unsuitable for a point-of-care product. Another analysis, based on the illumination of
the device as a whole, is needed. For this analysis, we define the following variables.
H
A
V
Ac
ac
=
=
=
=
=
height of the trap chamber
area of the trap chamber (as viewed from above)
volume of the trap chamber
area of the trap chamber occupied by CD4 cells (as viewed from above)
cross-sectional area of a CD4 cell
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N+ = total number of CD4+cells trapped in the trap chamber
Using these variables, we can define the macroscopic luminance as
ℓ𝑚 =
𝐴𝑐
𝐴
=
𝑎𝑐 𝑁+
𝐴
(2)
Finally, assuming that during a test, we flow in enough blood to exactly fill the trap chamber,
then the CD4 count is exactly N+/V, i.e. the number of CD4 cells per volume of blood. But N+ is
equal to Ac/ac, and V is equal to the area of the trap chamber times its height. Therefore, the CD4
count is given by
𝑁+
𝑉
=
𝐴𝑐
𝑎𝑐
=
𝐻𝐴
ℓ𝑚
𝑎𝑐 𝐻
(3)
Then, since the average cross-sectional area of a CD4 cell is about 40 µm2,7 and the height of the
trap chamber is set by the production process (typically between 11 and 15 m) all that is
required to determine the CD4 count is a measurement of the luminance.
However, this macroscopic luminance is no longer an exact, pixel-by-pixel value. A correlation
between the microscopic luminance ℓ and the macroscopic luminance ℓ𝑚 is necessary. In order
to accomplish this, experiments are needed which measure the two luminances from a single trap
device to calibrate the macroscopic luminance to its microscopic counterpart.
A final consideration concerning the detection of CD4 cells in this device is how to achieve the
requisite concentration of cells in the trap chamber for the imaging device to make a reliable
measurement of the CD4 count in a sample. Our initial experiments suggest that it is necessary to
recirculate the blood sample through the trap device in order to reach a high enough
concentration of cells. Once again, we define variables for analysis of recirculation:
7
Abbas AK and Lichtman AH (2003). Cellular and Molecular Immunology (5th ed.). Saunders, Philadelphia.
ISBN 0-7216-0008-5.
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Vs = volume of whole blood sample
Nt,i = number of CD4 cells remaining in the whole blood sample at the
beginning of the sample’s ith pass through the trap
Nr,i = number of CD4 cells captured in the trap after the sample’s ith pass
through the trap
fi = fraction of entering CD4 cells which were captured on pass i
Using the definitions of fi, Nt,i, and Nr,i, we can write a recursive equation for fi:
𝑓𝑖 =
𝑁𝑟,𝑖
𝑁𝑡,𝑖−1 −𝑁𝑟,𝑖−1
=
𝑁𝑟,𝑖
𝑁𝑡,𝑖−1 −𝑁𝑡,𝑖−1 𝑓𝑖−1
=
𝑁𝑟,𝑖
𝑁𝑡,𝑖−1 (1−𝑓𝑖−1 )
(4)
Next, assuming that the trap fraction fi is approximately constant—i.e. that trapping cells does
not significantly affect the trap’s performance—then fi = fi-1 = f. Performing the recursion of
Equation 4 yields
𝑓(1 − 𝑓)𝑖−1 =
𝑁𝑟,𝑖
(5)
𝑁𝑡,1
The total number of CD4 cells trapped after n passes of the sample through the device is the sum
of the cells trapped by each pass.
𝑁𝑡𝑟𝑎𝑝𝑝𝑒𝑑 = ∑𝑛𝑖=1 𝑁𝑟,𝑖 = ∑𝑛𝑖=1 𝑁𝑡,1 𝑓 (1 − 𝑓)𝑖−1 = 𝑁𝑡,1 (1 − (1 − 𝑓)𝑛 )
(6)
Modifying Equation 2 so that that N+ is replaced by the total number of cells trapped, we can
relate the macroscopic luminance to the right-side of Equation 6:
𝑁𝑡,1 (1 − (1 − 𝑓)𝑛 ) =
𝐴ℓ𝑚
𝑎𝑐
(7)
Rearranging yields
𝑁𝑡,1
𝑉𝑠
=
𝐴ℓ𝑚
𝑎𝑐 𝑉𝑠 (1−(1−𝑓)𝑛 )
(8)
Therefore, the CD4 cell count of a sample of blood is given in terms of the area of the trap
chamber (A), the cross-sectional area of a CD4+ cell (ac), the trapping efficiency of the device
(f), the number of recirculation passes (n), and the macroscopic luminance (ℓ𝑚 ). A and ac are
known quantities, n is determined by the duration of recirculation, ℓ𝑚 is measured by the
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experiment, leaving only f to be determined experimentally. It seems plausible that f is
approximately constant, but only for small values of n.
Cost Considerations
The cost of the CD4 counter per test is given by the detailed breakdown presented in Table 2.
Table 2: Cost analysis of the point-of-care diagnostic device
Item
PDMS base and curing agent Sylgard
184
Anti-CD4 antibodies
Europium nanoparticles
Glass Slides
PEEK tubing
Photolithography (500k tests)
Pump (500k tests)
TRF Reader (500k tests)
Total
Amount
3g
Capital Cost
$0.31
Cost per test
$0.31
.3ug
10uL
1
$ 0.14
$1.07
$0.12
$0.14
$1.07
$0.12
20cm
1
1
1
--
$0.40
$10
$60
$1020
$1,092
$0.04
$0.01
$0.01
$0.01
$1.71
Note that the PDMS base and curing agent are used in the making of the trap device as well as
the pump. The costs of photolithography, the pump (motor and controls), and the TRF reader
become negligible when their capital costs are divided by the number of tests they are expected
to last: we estimate this to be about 500,000 tests. The price of the TRF reader estimated here is
for a production model, rather than the prototype model used in this project.
Conclusions, Recommendations, and Future Directions
Significant progress toward a functional prototype for a point-of-care HIV diagnostic system has
been accomplished. All of the components of the device were designed, fabricated, and tested for
application in CD4 counting from whole blood samples. Thus far, protocols for microfluidic
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pumping and recirculation, white blood cell trapping, on-chip fluorescent labeling of whole
blood, and time-resolved fluorescent imaging with europium nanoparticles have been developed.
With the exception of the TRF reader, current results indicate that each component of the pointof-care system is capable of meeting the design criteria proposed for a point-of-care diagnostic
instrument as an affordable alternative to clinical blood testing in low-resource settings.
Conjugation of europium nanoparticles to anti-CD4 antibodies and subsequent TRF analysis of
whole blood remain the final steps for direct point-of-care application. Based on calibration
images of nanoparticle solutions, this step may prove challenging with the current detection
system. Assuming the europium fluorescence of a particular labeled cell is equivalent to the
fluorescent intensity observed in the device from the conjugated europium solution, calculations
suggest that 6.8% of the device area should be illuminated to reach the detection threshold.
However, this assumption depends on the concentration of CD4 receptors on the lymphocytes,
which must be determined experimentally with europium conjugated particles. According to
these results, approximately 22700 cells must be captured; a finger-stick equivalent of 40% of
CD4 WBCs in healthy patients and 150-250% in an AIDS patients. Therefore, unless the actual
signal strength of europium-labeled cells is higher than the original diluted signal, a magnifying
lens of at least 10x power should be added to the TRF detection system. Alternative methods for
higher density WBC trapping have been proposed for future investigation but may still be
insufficient for TRF detection.
With an expected price of $1.71 per test, this platform is anticipated to match the target of $2 per
test stipulated by global health initiatives like the Gates Foundation Challenge. Non-recurring
engineering costs of the prototype system were distributed across their expected lifetime as
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shown in Table 2. Reagents and disposable trap cartridges comprised the majority of the cost per
test.
The only sample preparation step is the initial loading of the blood into the PEEK tubing.
Ultimately, operation with Lab-View and ImageJ will enable automated on-chip labeling and
image processing capabilities. The disposable trap cartridge with a re-useable pump and imaging
system is ideal for facile, affordable, point-of-care application. By containing hazardous
biological samples on-chip, disposal of used chips becomes the only device-specific safety
concern. Peripheral considerations for implementation of this diagnostic tool must be addressed.
These include transportation and storage of antibodies, disposal of finger-pricks and used
cartridges, and availability of reagents and finger-sticks.
Once a complete working TRF prototype has been fabricated, the device’s ability to measure
CD4 counts must be tested against conventional techniques like flow cytometry (R = 0.9).
Because the test affords immediate, facile test replication, the precision can be reduced to
R = 0.7 with a double positive as a clear diagnosis.
Acknowledgements
Our special thanks go to our project mentors Professor Kevin Seale and Professor John Wikswo,
of the Vanderbilt Institute for Integrative Biosystems Research and Education, for their efforts to
guide our work. In addition, we extend our sincere gratitude to Dan Morrow and Dr. Bob Buck
of Gauge Scientific for providing their technical expertise in time-resolved fluorescent imaging.
We also thank Loi Hoang for his help with pump operation and troubleshooting. Finally, we
thank Professor Paul King for his feedback and guidance in completing our project.
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