Phenylboronic acids have emerged as synthetic receptors that can reversibly bind to cis-diols of glucose molecules. The incorporation of phenylboronic acids in hydrogels offers exclusive attributes; for example, the binding process with glucose induces Donnan osmotic pressure resulting in volumetric changes in the matrix. However, their practical applications are hindered because of complex readout approaches and their time-consuming fabrication processes. Here, we demonstrate a microimprinting method to fabricate densely packed concavities in phenylboronic acid functionalized hydrogel films. A microengineered optical diffuser structure was imprinted on a phenylboronic acid based cis-diol recognizing motif prepositioned in a hydrogel film. The diffuser structure engineered on the hydrogel was based on laser-inscribed arrays of imperfect microlenses that focused the incoming light at different focal lengths and direction resulting in a diffused profile of light in transmission and reflection readout modes. The signature of the dimensional modulation was detected in terms of changing focal lengths of the microlenses due to the volumetric expansion of the hydrogel that altered the diffusion spectra and transmitted beam profile. The transmitted optical light spread and intensity through the sensor was measured to determine variation in glucose concentrations at physiological conditions. The sensor was integrated in a contact lens and placed over an artificial eye. Artificial stimulation of variation in glucose concentration allowed quantitative measurements using a smartphone's photodiode. A smartphone app was utilized to convert the received light intensity to quantitative glucose concentration values. The developed sensing platform offers low cost, rapid fabrication, and easy detection scheme as compared to other optical sensing counterparts. The presented detection scheme may have applications in wearable real-time biomarker monitoring devices at point-of-care settings.
Phenylboronic acids have emerged as synthetic receptors that can reversibly bind to cis-diols of glucose molecules. The incorporation of phenylboronic acids in hydrogels offers exclusive attributes; for example, the binding process with glucose induces Donnan osmotic pressure resulting in volumetric changes in the matrix. However, their practical applications are hindered because of complex readout approaches and their time-consuming fabrication processes. Here, we demonstrate a microimprinting method to fabricate densely packed concavities in phenylboronic acid functionalized hydrogel films. A microengineered optical diffuser structure was imprinted on a phenylboronic acid based cis-diol recognizing motif prepositioned in a hydrogel film. The diffuser structure engineered on the hydrogel was based on laser-inscribed arrays of imperfect microlenses that focused the incoming light at different focal lengths and direction resulting in a diffused profile of light in transmission and reflection readout modes. The signature of the dimensional modulation was detected in terms of changing focal lengths of the microlenses due to the volumetric expansion of the hydrogel that altered the diffusion spectra and transmitted beam profile. The transmitted optical light spread and intensity through the sensor was measured to determine variation in glucose concentrations at physiological conditions. The sensor was integrated in a contact lens and placed over an artificial eye. Artificial stimulation of variation in glucose concentration allowed quantitative measurements using a smartphone's photodiode. A smartphone app was utilized to convert the received light intensity to quantitative glucose concentration values. The developed sensing platform offers low cost, rapid fabrication, and easy detection scheme as compared to other optical sensing counterparts. The presented detection scheme may have applications in wearable real-time biomarker monitoring devices at point-of-care settings.
Glucose sensors based on various
optical phenomena have been extensively explored. Optical glucose
sensors can be classified into four groups according to the optical
transducer/phenomena: surface plasmon resonance (SPR), fluorescent,
Surface Enhanced Raman Scattering (SERS), and the photonic band gap
sensors. For instance, plasmonic sensors were investigated for glucose
sensing due to their high sensitivity to the change in the surrounding
dielectric constant. The readout of these sensors depended on detecting
the change in the resonant absorbed wavelength with glucose concentrations.
An enzyme responsive plasmonic nanoshell system was reported to sense
glucose through enzyme complexation.[1] Aggregation
and dissociation of gold nanoparticles coated with dextran were also
utilized to sense glucose. The nanoparticles aggregate with concanavalin
A induced by glucose led to a change in plasmonic absorption.[2]SERS surfaces were adopted for glucose
sensing as it enhanced the
scattered Raman signal by molecular adsorption and the enhancement
factor can reach up to 1011 fold.[3] The intensity of Raman spectra can be used to quantify the concentration
of glucose. For example, a template of mercaptophenyl boronic acid
(MBA) and silver/gold nanoparticles with graphene oxide nanomaterial
was developed to enzymatically sense glucose.[4] Gold nanostar silica core–shell nanoparticles were prepared
with glucose oxidase as a SERS substrate for label-free glucose detection.[5] In-situ gold nanoparticles were created in porous
and stable metal–organic framework and this system was decorated
with glucose and lactate oxidases for in vivo detection
of glucose and lactate via SERS.[6] However, the fabrication of SERS and SPR glucose sensors
require high vacuum and advanced technologies such as atomic layer
deposition and e-beam deposition, making the process costly and complicated.
In addition, the readout methods of both systems require a customized
setup of high-cost optical fibers or a Raman spectrometer.Fluorescent
sensors for continuously monitoring of glucose have
also been reported. For example, PBA containing fluorophores was employed
in a wearable device for continuous glucose monitoring. The employed
charge transfer mechanism induced spectral changes in the presence
of glucose. The fluorescence wavelength and the intensity shift with
glucose complexation.[7] Fluorescent sensors
suffer from photobleaching of the fluorophore and variations in the
illumination source causes over/underestimation of the glucose concentrations.Hydrogels of integrated photonic band gap (PBG) structures have
been functionalized and designed to undergo a reversible change in
their physical dimension in response to external stimuli such as glucose,
pH, ionic strength, temperature, humidity, solvent composition, and
biomolecule binding.[8−19] The photonic band gap of the hydrogel sensors are sensitive to hydrogel’s
volumetric change and convert this change into readable optical information.
The hydrogel photonic sensors can be classified into three types according
to the dimensions of the refractive index periodicity: 1D, 2D, and
3D photonic bandgap sensors. In such sensors, the reading out can
be recorded by colorimetric, and spectral shift measurements.[20−27]Phenylboronic acid functionalized hydrogel is a glucose-responsive
system due to their affinity to diol-containing molecules.[8,24] The complexation of PBA immobilized in the hydrogel matrix with
glucose molecules causes volumetric change (Figure ). Self-assembly methods have been utilized
for the formation of 3D-PBG structure and 3D inverse opal (IO) PBG
structure combined with PBA modified hydrogel for glucose sensing.[28] The PBA functionalized 3D-PBG (IO) hydrogel
sensors based on the polymerized acrylamide around 3D sacrificial
charged polystyrene particles, have been shown to sense the glucose
concentration obeying Bragg’s law.[29] Due to their intrinsic periodicity, these 3D-PBG sensors diffract
light of certain wavelengths at specific incident angles. Thereby,
at a particular point in space, spectral shifts are observed because
of the change in the lattice size and periodicity induced by the swelling
(or shrinking) of hydrogel sensing the external stimuli.
Figure 1
Schematic illustration
of glucose-induced swelling of the phenylboronic
acid functionalized hydrogel matrix. (a) Molecular illustration of
the glucose-binding process that causes swelling of the hydrogel matrix.
(b) Illustration of volumetric transition upon glucose introduction
into or depletion from the glucose-sensitive hydrogel matrix.
Schematic illustration
of glucose-induced swelling of the phenylboronic
acid functionalized hydrogel matrix. (a) Molecular illustration of
the glucose-binding process that causes swelling of the hydrogel matrix.
(b) Illustration of volumetric transition upon glucose introduction
into or depletion from the glucose-sensitive hydrogel matrix.The construction of such 3D-PBG
hydrogel sensors requires nonionic
hydrogel precursors to avoid disordering in the charge-stabilized
3D polystyrene particles.[24] These 3D crystalline
colloidal array particles were fabricated by self-assembly and this
process lasts 2 weeks which is time-consuming. 3D-IOs structure from
templates have also been transferred to the hydrogel during the polymerization
of monomers–once polymerized, the 3D-IOs were removed by chemical
etching, yielding a periodic porous polymer.[30] The 3D-IO method also suffers from the high defect density and prone
to damage during template etching. A limited range of detection is
also a significant drawback of 3D-PBG hydrogel sensors.1D-PBG
hydrogel glucose sensors have been fabricated based on the
diffusion of the silver nanoparticle in the glucose-responsive hydrogels,
followed by laser treatment to form composite layers separated by
hydrogel layers modulating the refractive index in one dimension.[31] The fabrication of the 1D-PBG sensor process
requires many stages and these sensors also have a limited field of
view, making readouts very complicated. 2D-PBG sensors based on colloidal
crystal arrays (CCA) have also been realized.[14] Although these sensors were sensitive to glucose in the physiological
concentration range, they had limitations in their fabrication.[32] These sensors require a well-ordered monolayer
of particles, demanding optimization, and functionalization with phenylboronic
acid postpolymerization.[10] In addition,
readout requires setups of expensive optical fibers fixed on rotating
stages, dark rooms and spectrophotometers connected to a computer.
Consequently, the PBG sensors could not find their way into low-cost
mass production and point of care. Table S1 presentsa comparison of various types of glucose sensors summarizing
the working principle, advantages, disadvantages, and detection ranges.In this work, we developed a glucose sensor that achieves the crucial
need of fast and economical fabrication process and a simple readout
method. We introduced a transducer (holographic optical diffusing
microstructures) that was easy to imprint on the surface of the glucose-responsive
hydrogel through the UV gel curing process, facilitating and accelerating
the fabrication process. The volumetric change of the hydrogel in
response to various glucose concentrations modulated the dimensions
of the optical diffusing microstructures and hence the scattering
efficiency of the sensor. As a result, the beam profile and power
for the transmitted and reflected beams changed. The readouts were
taken using an optical powermeter and also with a smartphone app,
exploiting the smartphone’s ambient light sensor. Therefore,
this sensor offers advantages in terms of its fast and facile preparation
and simple readouts within physiological ranges.
Results and Discussion
A holographic diffuser was mirror replicated on the hydrogel network
during photopolymerization (Figure ). Optical microscopy images confirmed successful transfer
of the mirror-replicated structure on the hydrogel layer. Both the
holographic diffuser and hydrogel sensor were illuminated with broadband
white light and laser beam (λ = 532 nm). The holographic diffuser
exhibited a wider divergence/diffusion angles, Δθd ∼ 40° and 35° for both broadband white light
and monochromatic beams, respectively, as compared to the angles,
Δθd ∼ 20° and 15°, respectively,
obtained for the imprinted hydrogel matrix. In addition, the maximum
transmitted light intensity detected by using a photodetector for
the holographic diffuser was ∼2 times lower than that of the
imprinted hydrogel matrix. The holographic master had a higher divergence,
which allowed lesser light (luminance) to reach the photodetector
placed at the identical distance as compared to its mirror replica
of the hydrogel matrix. The difference in θd was
expected because of the difference in the selection of materials and
fabrication processes between the holographic diffuser and the imprinted
hydrogel matrix.
Figure 2
Microimprinting of holographic diffusers
in hydrogel films. (a)
Schematic for the fabrication process of hydrogel-based optical glucose
sensor: a diffuser master replica is drop-cast with a glucose-sensitive
solution which is polymerized using UV light. After polymerization,
the master stamp is removed, and the imprinted glucose-sensitive hydrogel
is obtained on the glass slide. (b–d) Microscopic images of
the master diffuser and hydrogel. (e) Theoretically obtained Fourier
transform of the diffuser giving the profile of the diffused light
spot after interacting with glucose molecules. (f) Diffused light
profile after the broadband white light is transmitted through the
sensor in ambient (40% humidity) and fully hydrated conditions.
Microimprinting of holographic diffusers
in hydrogel films. (a)
Schematic for the fabrication process of hydrogel-based optical glucose
sensor: a diffuser master replica is drop-cast with a glucose-sensitive
solution which is polymerized using UV light. After polymerization,
the master stamp is removed, and the imprinted glucose-sensitive hydrogel
is obtained on the glass slide. (b–d) Microscopic images of
the master diffuser and hydrogel. (e) Theoretically obtained Fourier
transform of the diffuser giving the profile of the diffused light
spot after interacting with glucose molecules. (f) Diffused light
profile after the broadband white light is transmitted through the
sensor in ambient (40% humidity) and fully hydrated conditions.The light dispersion properties of the imprinted
hydrogel matrix
weakened when it was exposed to the highly humid conditions. In fully
hydrated conditions, the hydrogel matrix exhibited a smaller θd angle and higher maximum transmitted power than that of 40%
relative humidity conditions (Figure f). The optical hydrogel matrix as a sensor swelled
upon partial or full hydration, causing an initial size increase in
the structural profile of the replicated microstructure. This change
decreased the sensor’s diffusive properties and, consequently,
the divergence angle. Furthermore, the index matching effect due to
the introduction of water on the surface decreased the roughness and
also waveguided the transmitted light inline to the direction of the
incident beam and reduced the beam divergence. Therefore, the decrease
in the spot size in the case of full hydration increased the intensity
maxima of the transmitted light when recorded at the center of the
spot. For subsequent experiments, the sensor’s reference was
set according to its fully hydrated condition. The scattering profile
of the holographic diffuser and the optical hydrogel sensor were similar
for the blue, green, and red laser beam illumination (Figure S3).Microimprinted hydrogel sensors
were tested in different glucose
concentrations in transmission mode using monochromatic light (Figure ). The sensing was
carried out by measuring the transmitted light intensity and recording
the profile/diameter of the diffused light after passing through the
optical hydrogel sensor (Figure c–e). The sensor was equilibrated in PBS solution
(pH 7.4, ionic strength = 150 mM, 24 °C) for 2 h, and each measurement
for different glucose concentration (M) within the
range 0 ≤ M ≤ 100 mM was carried out
after 90 min to the last preceding sensing trial. An incident monochromatic
light beam of λ = 532 nm was used, and sensing measurements
were performed in the transmission mode. Figure a illustrates the schematic of the experimental
setup in sensing experiments. In addition to the swelling caused by
water diffusion inside the optical hydrogel sensor, glucose swelled
the sensor due to the formation of anionic boronate–glucose
1:1 complexation in the hydrogel matrix that increased the boronate
anions, leading to increasing Donnan osmotic pressure and, hence,
caused a positive volumetric shift. For low pH solutions (pH <
pKa), the phenylboronic acid existed in
uncharged trigonal configuration. It complexes with glucose-forming
boronate ester, which is far more acidic than the boronic acid.[33,34] The pKa of the boronic ester is less
than the pH of the solution (7.4), resulting in dissociation of the
boronic ester donating a proton forming a stable boronate anion. For
high pH solutions (pH > pKa) the PBA
existed
in a stable and charged tetrahedral configuration that complexes with
glucose to form boronate anion (Figure S4).[33,34] The dimensional shift in the imprinted microlenses
on the sensor’s surface altered the overall divergence of the
beam by changing the focal length of each individual microlens. Figure b shows the working
principle of the sensor. The changing optical parameters could be
correlated to the variation in the glucose concentration.
Figure 3
Quantification
of glucose concentrations with an imprinted differ
based hydrogel sensor. (a) Schematic of the monochromatic light transmission
setup used to measure the optical response of the hydrogel sensor
based on a diffuser structure when exposed to glucose. (b) Working
principle of the diffuser, which is based on arrays of distorted microlenses–glucose
binding alters the dimension of the microlenses and hence the profile
of the transmitted light. (c) Transmitted light power, P, behavior for the green laser beam versus the diffusion
angle for glucose concentration within the range 0 ≤ Μ ≤ 100 mM. (d) Peak transmitted light power, Pmax, as a function of glucose concentration
for 0 ≤ Μ ≤ 100 mM. (e) Normalized
transmitted light power for different glucose concentrations versus the diffusion angle showing the change in the diameter
of the diffused spot (captured on imaging screen). (f) Normalized PT–θd plot. (g) Exponential
fit for the fwhm and w conceived from (c). (h) Photographs
of diffused monochromatic light spots after passing through the sensor
submerged in different glucose concentration solutions. The diameter
was restricted at fwhm of the transmitted power.
Quantification
of glucose concentrations with an imprinted differ
based hydrogel sensor. (a) Schematic of the monochromatic light transmission
setup used to measure the optical response of the hydrogel sensor
based on a diffuser structure when exposed to glucose. (b) Working
principle of the diffuser, which is based on arrays of distorted microlenses–glucose
binding alters the dimension of the microlenses and hence the profile
of the transmitted light. (c) Transmitted light power, P, behavior for the green laser beam versus the diffusion
angle for glucose concentration within the range 0 ≤ Μ ≤ 100 mM. (d) Peak transmitted light power, Pmax, as a function of glucose concentration
for 0 ≤ Μ ≤ 100 mM. (e) Normalized
transmitted light power for different glucose concentrations versus the diffusion angle showing the change in the diameter
of the diffused spot (captured on imaging screen). (f) Normalized PT–θd plot. (g) Exponential
fit for the fwhm and w conceived from (c). (h) Photographs
of diffused monochromatic light spots after passing through the sensor
submerged in different glucose concentration solutions. The diameter
was restricted at fwhm of the transmitted power.Increasing glucose concentration initially increased the
maximum
transmitted light power, PTmax, and shrank
the diameter of the diffused light spot on the imaging screen (Figure d–h). Upon
increasing the glucose concentration, 0 ≤ M ≤ 100 mM, the maximum transmitted light power PTmax and the diameter underwent a slower corresponding
shift; the sensor response was saturated at high concentrations, below
which the response was fairly linear with percentage sensitivity of S ∼ 2.5% mM–1 (or ∼11 μW
mM–1) calculated using the slope of the P–M curve, given by S = ΔP/ΔM, where ΔP and ΔM are the change in the transmitted
optical power and change in glucose concentration, respectively. The
sensitivity of our diffuser-based sensor is around 18 times higher
than the recently reported work; for the glucose concentration range
of 0–100 mM, the diffuser sensor showed the change of 128%
in the transmitted power compared to the 7% attenuation of the transmitted
light in ref (35).
The decrease in sensitivity and saturation at higher glucose concentrations
was due to the decrease in the available boronate binding sites and
decreasing elasticity of the hydrogel matrix that competed against
the volumetric swelling process. However, this nonlinear behavior
could be fit very accurately with an exponential trend with a correlation
coefficient of R2 = 0.99 and exponential
coefficient of ∼32.08 mM–1. The visual shift
of the diffused spectra was also very clear, which could be seen by
the naked eye (Figure h). For diabeticpatients, the required readout rate of the sensor
for the shift of glucose concentration from 8 to 15 mM is 0.078 mM·min–1.[35] According to swelling
kinetics of the sensor when it is immersed in glucose concentration
of 10 mM, the sensor provides a readout rate of 0.14 mM per min which
is higher than the required speed. The blood contains fructose and
lactate; both complex with PBA under physiological conditions.[33,34] However, the glucose concentrations in blood for healthy (3.9–6.9
mM) and diabetic (7.2–10 mM) people are much larger than fructose
concentrations (0.008 ± 0.001 and 0.012 ± 0.0036 mM) as
well as the lactate (0.36–0.75 mM) in both conditions, respectively.[35,36] Previous studies reported a minimal interference from fructose of
0.5% and 3.5% for lactate for the glucose sensor that is prepared
from same ingredients; PBA derivative and polymer matrix.[37]Glucose concentration within the range
of 0 ≤ M ≤ 100 mM was also measured
using broadband white light. Photographs
of the diffused spots on a screen 40 cm away from the sensors were
captured for visual detection. The divergence angle of the diffused
light was consistent with the previous experiments carried out using
the monochromatic light (Figure ). An increase in the glucose concentration decreased
the divergence angle and increased the power of the transmitted beam.
The sensor response was linear for glucose concentrations within 0
≤ M ≤ 50 mM, and the sensor’s
sensitivity in this range was 11.6 μW·mM–1. Parts f–h of Figure show the transmitted light spectra of the glucose sensor.
The sensor does not alter the spectral profile of the white light
over the entire visible range. This means that the glucose detection
can be performed reliably using any selective wavelength or the range
of the wavelength due to the monotonic positive shift in the optical
transmission against various glucose concentration. The diffuser-based
sensor was able to quantify glucose within a wider detection range
as compared to its other counterparts based on the visual detection
scheme (1D and 3D PBG sensors).
Figure 4
Quantification of glucose using the imprinted
hydrogel sensor with
a broadband light source for the concentration range of 0 ≤ Μ ≤ 100 mM. (a) P–θd trend of hydrogel sensor for different glucose concentrations.
(b) Pmax plotted against various glucose
concentrations, M. (c) Normalized transmitted power
of the broadband light versus the diffusion angle,
showing the change in the diffused spot diameter with increasing glucose
concentrations. (d) Exponential fit for the fwhm and w conceived from (c). (e) Photographs of diffused broadband light
spots after passing through the sensor submerged in different glucose
concentration solutions. The diameter was restricted at fwhm of the
transmitted power. (f) Transmission spectra of the sensor for varying
glucose concentration. (g) Absolute transmittance for increasing glucose
concentration. (h) Average transmission of the sensor over 450–800
nm in various glucose concentrations.
Quantification of glucose using the imprinted
hydrogel sensor with
a broadband light source for the concentration range of 0 ≤ Μ ≤ 100 mM. (a) P–θd trend of hydrogel sensor for different glucose concentrations.
(b) Pmax plotted against various glucose
concentrations, M. (c) Normalized transmitted power
of the broadband light versus the diffusion angle,
showing the change in the diffused spot diameter with increasing glucose
concentrations. (d) Exponential fit for the fwhm and w conceived from (c). (e) Photographs of diffused broadband light
spots after passing through the sensor submerged in different glucose
concentration solutions. The diameter was restricted at fwhm of the
transmitted power. (f) Transmission spectra of the sensor for varying
glucose concentration. (g) Absolute transmittance for increasing glucose
concentration. (h) Average transmission of the sensor over 450–800
nm in various glucose concentrations.The swelling dynamics of the sensor were studied for 10–50
mM glucose concentrations (Figure a–e). The spot profile and Pmax were recorded at 6 min intervals. Upon exposure to
glucose solution, the binding equilibrium reached to saturation in
less than 60 min. This time was half of that reported in previous
studies, where the saturation time for the 3PBA-modified PCCAs and
holographic sensors was around 2 h.[12] The
rapid response and quicker saturation time is an important step toward
the practical implementation of such sensors. The quick response was
due to the microengineered surface of the sensor that increases the
active surface area and improved the diffusion rate of the glucose
into the hydrogel matrix
Figure 5
Reusability and response
time of the imprinted optical glucose
sensor. (a) Transmitted light power versus the diffusion
angle recorded within the time span of 0 ≤ t ≤ 120 min for 10 mM glucose concentration. (b) Optical transmitted
power versus the diffusion angle recorded within
the time span of 0 ≤ t ≤ 120 min for
50 mM glucose concentration. (c) Peak power of the transmitted light versus 10, 30, and 50 mM glucose concentration over 120
min. (d, e) Time coefficients and slopes
calculated using exponential fit (for at all data points) and linear
fit for shorter span (over 40 min), respectively. (f) Switching of
the sensor for various cycles against introduction or depletion of
glucose (10 mM). (g) pH sensitivity of the hydrogel sensor for various
glucose concentration at different pH values. (h) Schematic illustration
of glucose sensing using a mobile phone. Microimprinted optical glucose
sensor integrated on a contact lens. The light illuminated on the
glucose sensor reflects back and alters the diffused light profile
upon different glucose concentration exposures. (i) Experimental setup:
photograph of an artificial eye with attached contact lens and sensor
and schematic of the construction of contact lens. (j) Quantification
of glucose sensing using a smartphone camera taken at a distance of
10 cm.
Reusability and response
time of the imprinted optical glucose
sensor. (a) Transmitted light power versus the diffusion
angle recorded within the time span of 0 ≤ t ≤ 120 min for 10 mM glucose concentration. (b) Optical transmitted
power versus the diffusion angle recorded within
the time span of 0 ≤ t ≤ 120 min for
50 mM glucose concentration. (c) Peak power of the transmitted light versus 10, 30, and 50 mM glucose concentration over 120
min. (d, e) Time coefficients and slopes
calculated using exponential fit (for at all data points) and linear
fit for shorter span (over 40 min), respectively. (f) Switching of
the sensor for various cycles against introduction or depletion of
glucose (10 mM). (g) pH sensitivity of the hydrogel sensor for various
glucose concentration at different pH values. (h) Schematic illustration
of glucose sensing using a mobile phone. Microimprinted optical glucose
sensor integrated on a contact lens. The light illuminated on the
glucose sensor reflects back and alters the diffused light profile
upon different glucose concentration exposures. (i) Experimental setup:
photograph of an artificial eye with attached contact lens and sensor
and schematic of the construction of contact lens. (j) Quantification
of glucose sensing using a smartphone camera taken at a distance of
10 cm.The stability and reusability of the
sensor were investigated by
recording the response of the sensor for four complete cycles (Figure f). The sensor’s
response for glucose concentrations was measured for ∼100 min,
followed by the reset using an acetate buffer of pH 4.6 for ∼10
s and then for ∼60 min in PBS buffer before commencing the
next cycle for 10 mM glucose concentration. The increasing trend of Pmax remained identical throughout experiments
with the same saturation values for all the cycles. Similarly, the
switching off behavior returned to the initial value quickly; the
trend was unchanged throughout all the cycles. These results are important
as our sensor exhibited reusability, no signal hysteresis or drift
after each cycle, and identical sensitivity for each cycle. The effect
of pH on the glucose detection was studied (Figure g). As shown in Figure , the sensitivity of the sensor increased
with increasing pH. The highest sensitivity was recorded for pH 8,
while at the physiological pH (7.4), a relatively lower glucose sensitivity
was observed, consistent with the previous studies.[38,39] To explain the higher sensitivity of the sensor at higher pH values,
the effect of pH on the sensor was examined (Figure S11). We found that upon increasing the pH from 4 to 6, the
hydrogel slightly swells and consequently a slight increase in the
transmitted power was recorded, indicating an inconsequential increase
in the anionic boronate ions. The sensor exhibited a linear and higher
response between the pH values of 6 and 9, as the concentrations of
boronate ions increased significantly. Therefore, the higher sensitivity
at higher pH glucose solutions might be due to an increase in the
concentration of the anionic boronate ions which have high affinity
to complexes with glucose forming a stable boronate anion. The sensitivity
of the glucose sensor is not only affected by the pH of the glucose
solution, but also by the ionic strength of the solution. It has been
found that increasing the ionic strength of the aqueous solution increases
the charged PBA in the polymer matrix raising up the Donnan potential,
leading to the improved swelling response of the sensor.[22]The thickness of the prepared glucose
sensor was ∼350 μm
(Figure S2) as measured under an optical
microscope. We could not use samples of thickness <350 μm
as handling limitations of our free-standing sensors became more severe
below this thickness. It is known that thicker sensors provide higher
sensitivity on account of the response and saturation times, which
become longer.[39] We believe that reducing
the thickness of the sensor to nanoscale would candidate the sensor
for real-time monitoring as the response and saturation times of the
sensor would be within a few seconds. The transduction mechanism used
to monitor the volumetric modulation is also an important factor that
affects the sensitivity; for example, a 2.5 D photonic structure based
sensor showed a quick response time, but the transduction mechanism
posed the lowest sensing limit to ∼10 mM.[40]The effect of glucose complexation with the immobile
PBA in the
hydrogel matrix on the mechanical properties has been studied (Figure S9). The elasticity/Young’s modulus
for the sensor in absence of glucose was ∼175 kPa and increased
to ∼218 kPa for the glucose concentration of 50 mM. The stiffness
of the sensor increased from ∼0.49 to 0.61 N/m, indicating
a decrease in the flexibility. Increasing the sensor stiffness with
glucose complexing may also explain the decreased sensitivity of the
sensor at high glucose concentrations.To show the utility of the sensor,
we attached it on a small reflective
sheet and incorporated on a contact lens (Figure h–j). Light intensity measurements
were obtained in the reflection mode (with the incident and reflection
angles of 45° with respect to the normal) using a smartphone
photodiode. The inbuilt light sensor in the smartphone was utilized
to capture the backscattered light (at a distance of 12 cm) and record
its luminance. For this purpose, we used the “Smart Tools”
android app which is freely available from the Google app store. Upon
continuous application of different glucose solutions on the sensor
surface, the changing luminance against varying glucose concentration
(0–50 mM) was measured. The sensor was sensitive to the glucose
concentration in the range of 5 mM and upward. The sensitivity of
such sensors and thickness are inversely proportional. We anticipate
that the sensitivity will improve to work in the tear range (0.26–0.9)
with further optimization to the sensor’s thickness and decreasing
the resolution of the diffusing microstructures. These modifications
can improve the sensor’s active surface area and as a result,
minimal swelling of the sensor will alter the transmitted and reflected
beam profile.[41] Although, tear constituents
such as fructose and lactate may interfere with the glucose measurements,
this can be resolved by developing a highly glucose-selective bis-boronic
acid functionalized hydrogel.We anticipate no harm of illuminating
the eyes for few seconds
with a white light source as the ophthalmologists examine the patient’s
eyes by ophthalmoscopes that are provided by light pointers. The data
file can be stored in ASCII format for global recognition and can
be remotely sent to the physician for better health and care facilities.
In contrast to other sophisticated electrochemical sensing schemes
for glucose sensing, optical sensors incorporated in contact lenses
do not require an electrical powersupply, significantly simplifying
the operation and readout system with already available CMOS photodiode
light sensors in smartphones.[42]
Conclusion
We have demonstrated an optical glucose sensor based on a diffuser
architecture in a contact lens. The diffuser structure was initially
mirror-replicated onto a glucose-sensitive hydrogel. The structure
of the diffuser was based on microengineered lens arrays that exhibited
a focal length modulation in response to the overall size modification
of the hydrogel upon exposure to different glucose concentrations.
Consequently, the changing focal lengths changed the diffused light
profile being transmitted or reflected from the surface of the sensor,
thereby changing the light intensity of the diffused spot within a
given transmission area. This change was measured as a function the
glucose concentration with the range of 0 to 100 mM. The sensor was
sensitive to glucose well within the physiological conditions. More
importantly, this optical sensor can be adapted as a minimally invasive
real-time measurement method as important when finger prick blood
sampling in glucose measurements at point-of-care settings is associated
low patient compliance. The developed sensor was also reversible and
reusable and exhibited no signal drift and hysteresis over multiple
cycles or glucose concentration increase and depletion. We have successfully
demonstrated such sensing using a hydrogel diffuser-based glucose
sensor embedded in a contact lens and tested it on an artificial eye.
Our proof-of-concept technology may be vital for chronic diseases
cases, especially for type 1 diabetics, where continuous glucose monitoring
is an important necessity for blood glucose management at point-of-care
settings.
Methods
Acrylamide (AA), N,N′-methylenebis(acrylamide)
(BIS), 3-(acrylamido) phenylboronic acid (3-APBA), dimethyl sulfoxide
(DMSO), 2,2-diethoxyacetophenone (DEAP), β-d-(+)-glucose,
and phosphate-buffered saline (PBS) were purchased from Sigma-Aldrich
and used without further purification. The acrylamide hydrogel film
was synthesized by the free-radical polymerization utilizing DEAP
as the photoinitiator and BIS as the cross-linker. The monomer solution
was prepared from AA (78.5 mol %), BIS (1.5 mol %), 3-APBA (20 mol
%), DEAP, and DMSO. The suspended monomer solution was stir-mixed
for 10 min at 24 °C. Prepolymer solution (100 μL) was dropcast
directly onto a master stamp surface based on a laser microengineered
diffuser structure. A hydrophobic glass slide was placed on top the
solution to obtain a uniform thickness. A photopolymerization process
was initiated with a UV amp (Black Ray, 365 nm) for 5 min. A holographic
diffuser was mirror replicated on the hydrogel network during photopolymerization.
Subsequently, the resulting replica hydrogel was peeled off the master
stamp, washed with deionized water, and kept in the dry condition
prior to further experiments. One of the advantages of the diffuser
sensor is the one-step preparation–that is, acrylamide, the
cross-linker, and PBA are mixed together in the initiator solution
followed by a single UV-assisted cross-linking process. In this method,
the immobilized amount of PBA in the polymer is as same as the amount
we added to the monomer solution which was 20% mol of the mixed monomer.
The single-step method virtually gives a complete loading of the added
PBA. This strategy is different compared to other coupling methods,
where, polymerization of the acrylamide is carried out first, followed
by the attachment of PBA using EDC. In this method, the encapsulation
of poly acrylamide is done in the solution containing PBA and EDC
for certain time duration. The loaded amount of phenylboronic acid
to the polyacrylamide depends on the time span for the encapsulation
process and initial concentration of PBA in the solution.The
thickness and surface of the holographic diffuser and the prepared
hydrogel sensor were investigated using an optical microscope (Zeiss,
5× and 20× objective lens). For optical characterization,
the setup comprised of two inline rotational stages (Thorlab), one
containing a 3D translational stage (Thorlab) with a sample holder
and the other with the light source mount, and an optical power meter
located at 12 cm from the sensor, all fixed on an optical bench. The
master stamp and optical sensor were illuminated by monochromatic
and broadband light sources at their normal and the transmitted diffused
light spot were scanned by an optical power meter (Thorlabs, PM100A)
for different sample orientations. The beam profile of the transmitted
light was also studied using an imaging screen setup (by replacing
the optical power meter with an imaging screen). To measure the response
of the optical hydrogel sensor against the variation in glucose concentrations,
the hydrogel was equilibrated in PBS buffer (7.4 pH, 24 °C, ionic
strength = 150 mM) for 2 h, and optical transmission experiments were
repeated under physiological conditions for different glucose concentrations.
The sensing was also carried out on a sensor-integrated contact lens
on an artificial eye by obtaining readouts with a smartphone camera
and app, and results were compared with data recorded with the optical
power meter.
Authors: Ali K Yetisen; Yunuen Montelongo; Fernando da Cruz Vasconcellos; J L Martinez-Hurtado; Sankalpa Neupane; Haider Butt; Malik M Qasim; Jeffrey Blyth; Keith Burling; J Bryan Carmody; Mark Evans; Timothy D Wilkinson; Lauro T Kubota; Michael J Monteiro; Christopher R Lowe Journal: Nano Lett Date: 2014-05-20 Impact factor: 11.189
Authors: Joana Krämer; Rui Kang; Laura M Grimm; Luisa De Cola; Pierre Picchetti; Frank Biedermann Journal: Chem Rev Date: 2022-01-07 Impact factor: 60.622