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The application of on-chip optofluidic microscopy for imaging
Giardia lamblia
trophozoites and cysts
Lap Man Lee
1
,
Xiquan Cui
2
, and
Changhuei Yang
1,2
1
Department of Bioengineering (MC138-78), California Institute of Technology, Pasadena, CA,
91125
2
Department of Electrical Engineering (MC 136-93), California Institute of Technology, Pasadena,
CA, 91125
Abstract
The optofluidic microscope (OFM) is a lensless, low-cost and highly compact on-chip device that
can enable high-resolution microscopy imaging. The OFM performs imaging by flowing/scanning
the target objects across a slanted hole array; by measuring the time-varying light transmission
changes through the holes, we can then render images of the target objects at a resolution that is
comparable to the holes' size. This paper reports the adaptation of the OFM for imaging
Giardia
lamblia
trophozoites and cysts, a disease-causing parasite species that is commonly found in poor-
quality water sources. We also describe our study of the impact of pressure-based flow and DC
electrokinetic-based flow in controlling the flow motion of
Giardia
cysts – rotation-free translation
of the parasite is important for good OFM image acquisition. Finally, we report the successful
microscopy imaging of both
Giardia
trophozoites and cysts with an OFM that has a focal plane
resolution of 0.8 microns.
Keywords
Optofluidic microscopy; Microfluidics; On-chip imaging; Water quality monitoring; DC
electrokinetics
1. Introduction
The optical microscope is an important analytical tool in biomedicine and bioscience.
Optofluidic microscopy (OFM) [Heng et al. 2006a] is a new type of microscopy imaging
method which integrates microfluidic technology and aperture-based optics technique to
conduct high resolution, low cost microscopic imaging on a chip. This method does not
require the use of bulk lenses and other optical elements, which are typically found in a
conventional optical microscope, and instead perform imaging by translating/scanning the
target biological specimen over an array of small holes that was patterned onto the metal-
coated floor of a microfluidic channel.
We recently developed a complete on-chip OFM system that was tailored to image
Caenorhabditis elegans
. Using the acquired images, we further demonstrated that the OFM
can be used to identify different
C. elegans
phenotypes autonomously. Additionally, we
implemented a DC electrokinetic-driven OFM system that was suited for imaging spheroid
objects, such as cells and pollen spores [Cui et al. 2008].
lmlee@caltech.edu.
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Published in final edited form as:
Biomed Microdevices
. 2009 October ; 11(5): 951–958. doi:10.1007/s10544-009-9312-x.
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Giardia lamblia
is a water-borne parasite present in untreated or improperly treated water
sources. When contracted by humans, this flagellated protozoan can colonize and reproduce
in the small intestine, causing giardiasis. Symptoms include diarrhea, bloating, nausea,
abdominal cramping and malaise. Severe weight loss is often a consequence. Proper
treatment requires an appropriate antibiotic for days to relieve the symptoms and cure the
disease. Several microfluidic-based filtering techniques have been developed to effectively
trap and concentrate microbial cells [Zhu et al. 2004; Lay et al. 2008]. We believe that the
result of this initial demonstration study suggests that the OFM can potentially function as a
secondary identification tool if the technology is integrated with filtering techniques. The
OFM system can also be used as a point-of-care diagnostic tool for giardiasis.
In this paper, we report our recent adaptation of the OFM for
Giardia lamblia
trophozoites
and cysts. This study provides us an opportunity to demonstrate that the optofluidic
microscope's application range extends beyond potential bioscience and biomedical
research, and that the technology can potentially be useful as an autonomous, low-cost and
highly-compact method for environmental and food/water supply monitoring and
diagnostics [Lay and Liu 2007; Zhang et al. 2006; Sakamoto et al. 2007; Yager et al. 2006;
Chin et al. 2007].
This paper is divided into the following sections. In the next section, we briefly explain the
OFM imaging principle and describe the design modifications required to adapt our OFM
systems for
Giardia lamblia
imaging. The required changes are few and minor as the
primary OFM design is sufficiently robust and flexible. In the third section, we report on our
findings regarding the flow control of
Giardia lamblia
trophozoites and cysts under pressure-
driven and DC electrokinetic driven flow. The extent of rotation under flow motion is of
particular interest to us as it directly impacts on the OFM's ability to perform imaging. We
report the results of a detailed sub-study into this issue. This sub-study is of broad relevance
as it can inform us on our design choices regarding our future OFM systems that are tailored
for other target types. Next, we present OFM images of
Giardia lamblia
trophozoites and
cysts and discuss the features that we can discern in the images. Finally, we conclude by
summarizing our findings.
2. Design and fabrication
2.1 On-chip optofluidic microscope design
One simple way to implement on-chip imaging is through the use of direct light projection
imaging [Lange et al. 2005; Ozcan and Demirci 2008; Seo et al. 2009]. This strategy works
by transmitting light through a target sample and detecting the resulting shadow with an
underlying sensor grid. In this situation, the best raw image resolution achievable is limited
by the size of the sensor pixels, which is typically larger than 2.2
μ
m. Aliasing artifact can
also degrade the raw image quality. At present, this imaging approach has inferior resolution
when compared with conventional microscopy methods. Current efforts in this research
direction are generally focused on eliciting morphological information indirectly from the
acquired images.
The OFM imaging approach circumvents the sensor-pixel based resolution limitation to
perform on-chip microscopy imaging by employing an array of submicron apertures to scan
the target sample. In brief, an OFM device consists of a sensor chip that is coated an opaque
metal layer. The geometry of an OFM device is illustrated in Figure 1(a). An array of
submicron apertures is patterned onto the metal layer in such a way that each aperture
transmits light to a single sensor pixel – this implies that the aperture-to-aperture separation
is equal to the sensor pixel length. A microfluidic channel is emplaced on top of the aperture
array such that the array spans the channel width diagonally. The entire device is then
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illuminated from the top. As a target sample flows through the microfluidic channel, it
interrupts light transmission through the apertures. As such, the time varying transmission
through each aperture effectively represents a line scan across the target. By compiling the
line scans collected by the entire array appropriately, we can then create a transmission
microscopy image of the object in which the focal-plane resolution is approximately equal to
the aperture size. The diagonal arrangement of the aperture array with respect to the channel
is required to ensure full sampling of the target. We encourage interested readers to refer to
[Heng et al. 2006a; Cui et al. 2008] for a more detailed and complete explanation of the
OFM method.
For our current study, the array consists of 120 apertures and the microfluidic channel's
dimensions are 40
μ
m in width, 9.7
μ
m in height and 2.5mm in length. The microfluidic
substrate is poly(dimethylsiloxane) (PDMS). The apertures are 500nm in size and are
fabricated at the center of every alternate square pixel (5.2
μ
m in length) underneath with a
separation of 10.4
μ
m. The tilt angle
θ
of the array with respect to the channel's flow axis is
2°. The separation of the apertures in the direction perpendicular to the channel's flow axis is
330 nm. The channel height is chosen to be comparable to the size of the
Giardia
samples
that we would be imaging. This ensures that the targets will flow across the aperture array
with close proximity. The OFM aperture array is patterned in the middle segment of the
microfluidic channel so that the target can flow across this rotation-free region steadily and
free from entrance effect. The planar view of the OFM device is shown in Figure 1(a). The
cross-sectional view of the OFM device is shown in Figure 1(b).
The flow speed of each target is calculated by dividing the channel length spanned by the
aperture array by the transit time of the object across the entire array. The percentage error
of the computed flow speed is found to be less than 4% for most of the biological samples
we examined in this study.
The OFM device is effectively a fixed focal plane microscope where we can expect obtain
the highest acuity at the floor of the flow channel (level of the aperture array). Based on our
previous OFM resolution study [Heng et al. 2006b], the focal plane resolution of this OFM
device is 800nm.
Finally, the achieved image resolution along the flow direction is set by the larger of the
two: the focal plane resolution (related to the aperture size) or the image smear extent. This
second parameter deserves more explanation. Our current system collects signal from each
relevant sensor pixel at a rate of 2000 s
-1
. If the target translates across the apertures too
quickly, the acquired image will appear smeared. We can define the threshold speed as the
speed when smearing artifacts become significant. The threshold speed equals the product of
aperture size and pixel readout rate. For our current system, this speed equals 1 mm/s.
During our experiments, we typically operate with target flow speeds that are substantially
lower than this speed to preserve good resolution in the flow direction.
2.2 OFM device fabrication
We use a combination of nanofabrication technology and standard soft lithography
technique to fabricate our compact OFM devices. We use a monochrome CMOS imaging
sensor (Micron Tech, MT9M001C12STM) as our starting substrate. This sensor chip
contains a 2D array of 1280×1024 square pixels. We note that the fabricated OFM device
will only make use of a couple of lines of pixels on this sensor chip for sensing and, as such,
we could have used a linear array sensor chip in place of this particular chip type.
We prep this sensor chip by spin coating a 400 nm layer of poly(methyl methacrylate)
(PMMA) layer onto the chip's surface to planarize it. Next, we coat a 15 nm chromium seed
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layer and a 300 nm thick gold layer onto the PMMA surface by thermal evaporation (AVC
1000, Veeco). We next use a focused ion beam machine (Nova200, FEI Company) to mill a
line array of circular apertures into the metal layer. Then, we passivate the gold surface with
a 400 nm thick PMMA layer. The choice of the layer thickness represents a compromise
between passivation robustness and the need to optimize object and aperture array proximity
for good image resolution.
We next emplace a transparent PDMS block containing a microfluidic channel onto the
modified sensor chip. The PDMS microfluidic channel is formed by standard soft
lithography which defines its planar geometry and the channel height. The emplacement is
performed with the aid of a contact aligner (Karl Suss, MJB3). Finally, we solder the OFM
device onto an evaluation board (SILICON VIDEO® 9M001 from Epix, Inc.), which allows
us to interface the OFM device with a computer.
2.3 Surface treatment
To facilitate smooth flow of our biological samples in the device and to prevent debris
adhesion to the microfluidic channel walls, we condition the channel walls through the
following process. First, the microfluidic channel is filled up and flushed with a 10%
poly(ethylene glycol) (PEG) solution, 0.5 mM NaIO4, and 0.5% (by weight) benzyl alcohol.
The OFM device is then placed under a UV light source for 1 hour to promote PEG
deposition onto the channel walls. This process is similar to the one developed by [Hu et al.
2002]. The PEG grafted surface prevents nonspecific adsorption with biological entities and
lubricates the object flow. The device is then rinsed with deionized water, dried, and stored
under ambient condition.
2.4 Sample preparation
The suspensions of
G. lamblia
cysts and trophozoites (H3 isolate) are purchased from
WaterBorne, Inc., USA. They are fixed and preserved in 5% Formalin / PBS at pH 7.4 /
0.01% Tween 20. The
G. lamblia
cyst has an oval shape, about 7–10
μ
m in width and 8–13
μ
m in length [Zhu et al. 2004] while its trophozoite form has a particular pear shape and is
approximately 10-20
μ
m in dimension. Before use, the suspensions were sonicated and
filtered with a 40
μ
m cell strainer (BD Falcon, USA). The number concentration of targets in
the suspensions is approximately 10
6
per ml.
2.5 Image acquisition process
During testing and evaluations, we mount the on-chip OFM device on a conventional
microscope (BX41, Olympus) and illuminated uniformly under a white light source (100W
halogen lamp through a 5 × objective) from the top. The incident light intensity is 20 mW/
cm
2
, which is comparable to the intensity of sunlight. The conventional microscope simply
serves as a platform for cross-verifications and is not an integral part of the OFM device. We
reprogram the associated data-readout software so that we can readout the relevant lines of
the sensor pixels rather than the entire sensor grid. This modification allows us to achieve a
line readout rate of 2000 lines per second. We choose an exposure time window of 0.5 ms
between each readout.
We introduce the sample solution into the OFM device by injecting the solution into the
input port (Figure 1(a)). The solution automatically fills the entire microfluidic channel by
capillary force.
There are two ways by which we can actuate microfluidic flow and perform sample
scanning – pressure-based flow and electrokinetic-based translation. We describe our
implementation of both approaches in the next two sub-sections.
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2.5.1 Pressure-based microfluidic flow—
We generate a pressure differential in our
microfluidic channel through the use of surface tension. We accomplish this by adding an
additional drop of the sample solution onto the input port. As native PDMS is highly
hydrophobic, this liquid drop beads up to form a hemispherical shape with a radius of about
0.5 mm. The associated surface tension then creates a Young–LaPlace pressure of up to
several hundred Pa at the inlet [Walker and Beebe 2002]. This pressure difference between
the two ports then generates a mean fluid flow velocity with a magnitude of a few hundred
microns per second in our microfluidic channel configuration. This fluid velocity will drag
the targets to flow inside the microfluidic channel and the translation speed of our targets is
proportional to this flow speed and is measured by the method described in Section 2.1.
We find that the flow velocity as generated by this means is sufficiently constant for our
application, as the OFM image acquisition time for each target is fairly short – typically less
than 1.0 second. The flow speed may vary over time as fluid drains out of the beading drop
and alters the surface tension. However, this change occurs over a much longer timescale.
As long as we are able to measure the flow speed of each individual target independently,
this variation is unimportant.
Experimentally, we find that the average flow speeds of
G. lamblia
cysts and trophozoites
are both 600
μ
m/s for both species.
2.5.2 Electrokinetic-based microfluidic flow—
We have found that the use of DC
electrokinetics provides an alternate, simple and direct way to actuate microfluidic flow.
This method involves imposing an electric field along the microfluidic flow channel axis to
generate an electrosmotic flow, an electrophoretic force and an electro-orientation force on
the biological sample. We will discuss our experimental findings regarding the effects of
these forces on our
G. lamblia
cysts and trophozoites in Section 3.
To generate the requisite electric field in the channel, we insert a pair of external platinum
electrodes into the inlet and outlet. Next, we connect the electrodes to a low voltage power
supply (E3617A, HP). A multi-meter is also connected to the setup to measure the current
level. A constant voltage of 30 V (electric field strength is
E
= 10 V/mm) is applied to the
electrodes. No destruction and disruption of the PMMA protection layer is observed if the
applied voltage is kept below this voltage.
Experimentally, we find that the average flow speeds of
G. lamblia
cysts and trophozoites
are 400
μ
m/s and 150
μ
m/s, respectively, for this scheme.
2.5.3 Observations—
We note the following experimental observations.
First, the cell flow speed is substantially lower than the threshold speed of 1 mm/s for both
schemes. This assures that the OFM image quality along the flow direction is well-
preserved.
Second, we observe that the OFM device can typically operate for about 30 minutes before
debris accumulation begins to have an impact on the uniformity of the flow velocity. This
relatively long operational lifetime is attributable to the PEG coating treatment of the
microfluidic channel which reduces debris deposition. We are currently working on
techniques to further prolong channel-use lifetime.
Third, the microfluidic channel can be flushed and rinse with DI water via a vacuum pump.
The on-chip OFM device can then be stored under DI water and ready for repeated use.
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3. Results and discussion
3.1. Study of pressure and electrokinetic-based flow control for
G. lamblia
cysts and
trophozoites
During OFM image acquisition, the target has to translate across the aperture array with a
uniform speed and maintain the same orientation. Any significant deviations will introduce
distortions into the resulting image. In our previous work [Cui et al. 2008]; we briefly
studied the impact of pressure-based and electrokinetic-based flow on
Chlamydomonas
and
pollen spore imaging. In that study, we found that the non-uniform Poiseulle flow velocity
profile created by pressure difference generates a significant torque on the targets and,
thereby, causing the target to rotate. Electrokinetic-based flow allowed for better flow
control for a number of reasons: 1) the electroosmotic flow has a plug-like profile and, as
such, does not generate a significant torque on a target in the flow stream [Probstein 1992].
2) The net electric charge on a biological target interacts with the imposed electric field to
pull the target towards the oppositely charged pole (electrophoretic force). This interaction
acts as a net body force on the cell and should not cause any rotation. 3) The non-uniform
electric charge distribution (dipole moments) on a target interacts with the imposed electric
field to reorient the target to achieve the lowest potential energy state. This electro-
orientation effect effectively locks the target into a single orientation during the entire flow
duration [Hughes 2003].
Our current study provides us an opportunity to examine a number of issues: 1)
G. lamblia
trophozoites are pear-shaped. How do they fare in pressure-based flow OFM imaging? 2)
Do targets rotate under pressure-based flow with the same angular velocities or is the
angular velocity broadly distributed? 3) What proportions of the
G. lamblia
cysts translating
under pressure-based and electrokinetic-based flows have sufficiently well-controlled flow
motions that they can be imaged with the OFM device. 4) How fast does a
G. lamblia
cyst
lock into its steady-state orientation during electrokinetic-based flow?
For this sub-study, we fabricate a number of microfluidic devices based on the description
given in Section 2. Glass slides are used in place of sensor chips as the substrate, as this
allows us to examine the exact flow motions of targets in the channels under a conventional
inverted microscope (IX71, Olympus). The region of interest is chosen to be 300
μ
m in
length and located in the middle of the microfluidic channel. This distance is equivalent to
the length of OFM array to image a
G. lamblia
cyst (10
μ
m in width).
Experimentally, we observe that
G. lamblia
trophozoites can flow without significant
rotations under pressure-based flow (experimental parameters as described in section 2.5.1).
Given its particular pear or relatively elongated shape, the trophozoite can either balance
itself in the parabolic velocity profile flowing steadily along the microfluidic channel
without rotation or it is dragged to the side wall and the side wall restricts them from
rotation. We did not observe any significant rotation event for all of the
Giardia
trophozoites
observed. This indicates that pressured-based flow is a viable flow strategy for
G. lamblia
trophozoite imaging.
On the other hand, we find that the more spherical
G. lamblia
cysts rotate significantly under
pressure-based flow. The cysts rotate with opposite orientations (clockwise versus counter-
clockwise) when it is flowing along the upper and lower half of the microfluidic channel
while driven by pressure as illustrated in Figure 3(a). In general, we observed that the typical
Giardia
cyst tends to rotate more and translate slower when it is flowing closer to a side
wall.
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To study the impact of electrokinetic-based microfluidic flow on
G. lamblia
cysts, we set up
an experiment as per the description in section 2.5.2. Both the
G. lamblia
cysts [Erlandsen
and Meyer 1984], and the microfluidic channel walls carry net negative charges at neutral
pH values. This implies that the resulting electrophoretic and electroosmostic forces act in
opposite directions. We observe that the net electrokinetic flow of the cysts is opposite to the
direction of applied electric field; this indicates that the electrophoretic force is stronger than
the electroosmotic flow in our experiment. In addition, we observe that most
Giardia
cysts
settle into their final flow orientation by electro-orientation before flowing more than 200
μ
m in the microfluidic channel. The relatively small electric field strength (E = 10 V/mm) is
sufficiently strong to create an electro-orientation force to hold most cells at a constant
orientation during flow. This strength is much lower than the critical value that would cause
cell lysis.
We study the statistical distribution of cell rotation events during flow by driving 100
lamblia
cysts each in a microfluidic channel under pressure-based and electrokinetic-based
flow. Figure 3(a) and (b) show a typical
Giardia
cyst flowing in the channel under these two
conditions. Figure 3 (c) plots the number of cysts versus the extent of the rotation (over a
flow distance of 300
μ
m). We can see from the plot that, under pressure-based flow, the cyst
rotation is significant and broadly distributed. In comparison, the extent of cyst rotation
under electrokinetic-based flow is small. In the context of this current OFM design, a
rotation of 5° during the passage of the cyst across the aperture array does not create
significant image distortions. Experimentally, we find that 70% of the cysts experienced
rotations under pressure-based flow while only 5% of the cysts experienced significant
rotations under electrokinetic-based flow. This indicates the DC electrokinetics is an
effective way to suppress rotational motion of cells in OFM systems.
3.2. OFM imaging of
G. lamblia
cysts and trophozoites
We image a number of
G. lamblia
cysts and trophozoites with our completed OFM device.
Figure 2(a)-(d) and (h)-(k) are OFM images (focal plane resolution of 800 nm) of several
G.
lamblia
cysts and trophozoites respectively. Fig. 2(e)-(f) and Fig. 2(l)-(m) are standard
microscopy images of similar
G. lamblia
cysts and trophozoites acquired with an inverted
light transmission microscope (Olympus IX-71) under a 40 × objective. We can see that the
OFM images compare well with standard microscopy images. The subcellular content and
the trophozoites's flagella are clearly discernable in the OFM images.
We further compare the performance of our OFM device to the simple direct projection
imaging scheme. In this experiment, we place some
G. lamblia
cysts and trophozoites
directly onto a high density CMOS sensor chip (Micron Tech, MT9P001). With the sensor
pixel size of 2.2
μ
m, this is the highest pixel density sensor chip that is currently
commercially available. Representative images of the targets are shown in Figure 2(g) and
2(n). The relatively low quality of the images when compared with OFM images can be
attributed to a number of reasons. First, due to the planar design of CMOS sensor chip and
the fact that each sensor pixel's fill factor is necessarily less than unity, we expect these
images to be sparsely sampled. In comparison, the OFM method actually allows us to
oversample our targets by simply choosing a slower flow speed than the sensor frame rate
and by ensuring that the line scans associated with the apertures overlap spatially. The latter
can be accomplished by choosing a shallow tilt angle for the aperture array versus the
microfluidic channel. Second, the transparent protective coating on the sensor deteriorates
the achievable resolution. We estimate that this layer is 600 nm thick based on typical
manufacturing practices. As the highest resolution is achieved in direct projection imaging
by placing the targets as close to the sensor grid as possible, this relatively thick coating
deteriorates the achievable resolution significantly [Heng et al. 2006b]. Finally, we note that
while simple direct projection imaging, as implemented with currently available technology,
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fares worse than OFM imaging in the context of image resolution, promising direct
projection methods based on in-line holography [Seo et al. 2009] can potentially achieve
good resolution.
4. Conclusions
We demonstrate the use of an OFM device to perform microscopy imaging of
G. lamblia
cysts and trophozoites. We are able to clearly discern the subcellular content and the
trophozoites's flagella in the OFM images. The achieved focal plane resolution of this OFM
device is 800 nm. This study shows that the OFM technology can potentially be used to
create autonomous, cheap and highly compact water analysis systems for monitoring water
quality in rural environment and resource-poor countries.
Acknowledgments
The authors appreciate the generous help and discussions from Dr. Xin Heng, Guoan Zheng, Sean Pang and Dr.
Jigang Wu. This work is supported by DARPA Center for Optofluidic Integration (California Institute of
Technology), NIH R21EB008867-01, and Coulter Foundation Early Career Award. Lap Man Lee is thankful for the
financial support from the Croucher Foundation Scholarship (Hong Kong).
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Figure 1.
(a) The planar geometry and the aperture array arrangement of the on-chip OFM. (b) A
cross-sectional scheme of the OFM device. (c) A photo of the fabricated on-chip OFM
device. (A US dime is placed aside for size comparison and the red line represents the
microfluidic channel)
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Figure 2.
G. lamblia
images. Images taken from the on-chip OFM device of cysts (a–d), trophozoites
(h–k). Images taken from a conventional light transmission inverted microscope with a 40 ×
objective of cysts (e–f) and trophozoites (l–m). Direct projection images on a 2.2
μ
m CMOS
imaging sensor chip of cyst (g) and trophozoite (n). (Scale bars: 10
μ
m)
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Figure 3.
The microfluidic motion of a
Giardia
cyst when (a) driven by pressure and (b) driven by DC
electrokinetics at 30V (E = 10 V/mm). (c) A graph showing the distribution of sample
rotation under pressure-based and electrokinetic-based drive. The horizontal axis quantifies
the magnitude of rotation after 300
μ
m of travel in the microfluidic channel.
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