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Ultrabright Polymer-Dot Transducer Enabled Wireless Glucose Monitoring via a Smartphone Kai Sun, Yingkun Yang, Hua Zhou, Shengyan Yin, Weiping Qin, Jiangbo Yu, Daniel T. Chiu, Zhen Yuan, Xuanjun Zhang, and Changfeng Wu ACS Nano, Just Accepted Manuscript • DOI: 10.1021/acsnano.8b02188 • Publication Date (Web): 25 Apr 2018 Downloaded from http://pubs.acs.org on April 25, 2018

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Ultrabright Polymer-Dot Transducer Enabled Wireless Glucose Monitoring via a Smartphone Kai Sun†, Yingkun Yang†, Hua Zhou†, Shengyan Yin†, Weiping Qin†, Jiangbo Yu§, Daniel T. Chiu§, Zhen Yuan||, Xuanjun Zhang||, and Changfeng Wu‡,* †

State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun, Jilin 130012, China.

‡

Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen 518055, China.

§

Department of Chemistry and Bioengineering, University of Washington, Seattle, Washington 98195, United States.

||

Faculty of Health Science, University of Macau, Taipa, Macau SAR China.

* To whom correspondence should be addressed E-mail: [email protected] Phone: +86-755-8801-5150 Fax: +86-755-8801-0724

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ABSTRACT

Optical methods such as absorptiometry, fluorescence, and surface plasmon resonance have long been explored for sensing glucose. However, these schemes have not had the clinical success of electrochemical methods for point-of-care testing because of the limited performance of optical sensors and the bulky instruments they require. Here, we show that an ultrasensitive optical transducer can be used for wireless glucose monitoring via a smartphone. The optical transducer combines oxygen-sensitive polymer dots (Pdots) with glucose oxidase that sensitively detect glucose when oxygen is consumed in the glucose oxidation reaction. By judicious design of the Pdots with ultra-long phosphorescence lifetime, the transducer exhibited a significantly enhanced sensitivity by one order of magnitude as compared to the one in previous study. As a result, the optical images of subcutaneous glucose level obtained with the smartphone camera could be utilized to clearly distinguish between euglycemia and hyperglycemia. We further developed an image processing algorithm and a software application that was installed on a smartphone. Realtime dynamic glucose monitoring in live mice was demonstrated with the smartphone and the implanted Pdot transducer.

KEYWORDS diabetes, continuous glucose monitoring, semiconducting polymer dots, fluorescence imaging, smartphone


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Diabetes severely threatens human health because it can cause numerous complications in heart, kidney, retina, and neural system.1 The global increase in the number of diabetic patients has posed a substantial impact on economic and social development, and has become one of the major health concerns of the 21st century.2,3

Tight glycemic control, along with regular

moderate exercise, strict diet management, and hypoglycemic drug treatments, is crucial for reducing pernicious morbidity and preventing diabetic complications.4,5 Therefore, reliable and continuous detection of blood glucose level is essential to manage diabetes progression and treatment.6,7

Over the past decades, various glucose monitoring technologies have been

developed, which detect glucose levels in the blood or interstitial fluid.8,9 Continuous glucose monitoring (CGM) is preferable to traditional single-point detection methods because continuous monitoring provides more detailed information about blood glucose fluctuations and results in substantial improvement in the management of diabetes.5 Electrochemical sensors are used in most current monitoring systems in clinical practice.

These sensors utilize a needle-like,

enzyme-coated electrode, which is implanted subcutaneously to measure the glucose concentration via the oxidation of glucose through enzymatic reactions.10-12

However, the

electrochemical sensors have several drawbacks, including in vivo sensor degradation, poor response at low glucose concentrations, pain of insertion, and risk of infection from the electrodes.13-15

Optical methods for glucose sensing have the potential to overcome the

limitations of electrochemical sensors.16 Sensor platforms based on fluorescent hydrogel beads and fibers have been developed for in vivo glucose monitoring.17,18 Despite many efforts,16-22 the clinical application of optical glucose sensors is severely limited by their inability to meet the required sensitivity and accuracy for transdermal detection.17,19 Another important aspect for practical application is the availability of inexpensive and portable devices for glucose


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However, the optical approaches typically require bulky and expensive

instruments, which are obstacles in their wide spread applications. Advances in nanotechnology are creating opportunities for early diagnosis, staging and monitoring of disease progression in diabetic patients.6 The technologies offer solutions to overcome the problems with current glucose monitoring devices. As promising fluorescent materials, semiconductor polymer dots (Pdots) have attracted considerable attention for their applications in biological imaging and biosensors because of their high brightness, excellent stability, and biocompatibility.23-28 We have recently developed an optically bright Pdot oxygen transducer that consists of an oxygen-consuming enzyme for sensitive detection of smallmolecule substrates.29

The transducer−enzyme assembly after subcutaneous implantation

provides a strong luminescence signal that is transdermally detectable and continuously responsive to blood glucose fluctuations.

Despite the reliable performance of the Pdot

transducer, several challenges remain, including enhancing the sensitivity of the transducer and simplifying the monitoring instrument for practical applications.

In particular, instrument

miniaturization is an important consideration in the design and development of glucose monitoring devices. With the rapid development of communication, computation, and sensing capabilities of mobile devices, smartphone has become an indispensable device that can be carried in our pockets. By operating a variety of software applications (APP), smartphones largely fulfill most people's needs for a telephone, digital camera, media player, GPS navigation, and cloud services. Smartphones have shaped all aspects of our lifestyle, and have even become a very powerful and flexible platform for scientific research.30 Recently, with the expansion of attachments and software applications, smartphones have been used as portable detection and analysis instruments for monitoring many physiological parameters such as pulse, breath, body


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temperature, and blood pressure.31-34

Smartphone with CCD detectors has also been

demonstrated for disease diagnosis,35,36 fluorescence imaging,37,38 molecular detection,39,40 and colorimetric assays.41 Here, we developed an ultrasensitive polymer-dot transducer for wireless glucose monitoring via a smartphone.

First, we explored a series of oxygen responsive dyes with variable

phosphorescence lifetimes to develop an ultrasensitive Pdot transducer. Because palladium porphyrin complexes have more than 10 times longer lifetimes than platinum complexes, the resulting Pdot transducer exhibits a significantly higher sensitivity in both in vitro and in vivo glucose detection. With the ultrasensitive transducer, optical images of subcutaneous glucose obtained with smartphone cameras can be utilized to clearly distinguish between euglycemia and hyperglycemia.

We further developed an image-processing algorithm to decompose the

luminescence image via the RGB model, in which the red-to-blue intensity ratio was used to quantitatively calculate the blood glucose concentrations. Based on the algorithm, a software application was developed and installed on a smartphone. We demonstrated a wireless dynamic glucose monitoring in live mice by using the implanted transducer and the smartphone. RESULTS AND DISCUSSION Principle and development of the polymer-dot transducer.

The principle of glucose

detection is based on the surface conjugation of glucose oxidase (GOx) with a Pdot oxygen transducer, which behaves as a nanoreactor that depletes its internal oxygen reservoir in the presence of glucose.29 As a result, the sensitivity of glucose detection is largely determined by the performance of the oxygen responsive dye. The Pdot transducer in our previous report consisted of poly(9,9-dihexylfluorenyl-2,7-diyl) (PDHF) doped with an oxygen-sensitive dye


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platinum(II) octaethylporphine (PtOEP).27 With GOx bioconjugation, the PtOEP doped Pdots showed three times enhancement in luminescence intensity from euglycemia (5 mM glucose) to hyperglycemia (20 mM glucose). The sensitivity of the previous Pdot transducer is not sufficient for observation by unaided eyes or smartphone cameras. Therefore, we investigated several oxygen-sensitive dyes in order to significantly enhance the performance of the transducer. The oxygen sensing properties of phosphorescent porphyrin complexes can be characterized by the Stern-Volmer equation,42

I0 / I = τ0 / τ =1+ k q τ0PO2

………………… (1)

where I0 and I are the luminescence intensities in the absence and presence of oxygen, respectively. τ0 and τ are the related decay time constants, kq is the bimolecular quenching rate constant, and PO2 is the oxygen partial pressure. The product of kq and τ0 is the Stern-Volmer quenching constant, KSV.

Palladium complexes of porphyrins and related structures have

significantly longer excited-state lifetimes (about 1 ms in the absence of oxygen) in comparison with corresponding platinum complexes (< 100 µs), while the biomolecular quenching constant remains the same owing to their very similar structures. It is therefore possible to achieve a significantly higher sensitivity to glucose by using Pd-porphyrins and semiconducting polymer to develop the transducer. The oxygen-sensitive Pdots were prepared by the reprecipitation method described in previous reports.29,43 The semiconducting polymer PDHF was chosen as the light harvesting host. As shown in Figure 1, four types of phosphorescent dyes as dopants (doping concentration of 10 wt% relative to the PDHF polymer), namely Pt(II) octaethylporphine (PtOEP, D1), Pt(II) mesotetra (pentafluorophenyl) porphine (PtTFPP, D2), Pd(II) octaethylporphine (PdOEP, D3) and


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Figure 1. (a) Molecular structures of PDHF, PSMA, PtOEP, PtTFPP, PdOEP, and PdTFPP. (b) Schematic diagram of real-time glucose monitoring by optical transducer based on oxygenresponsive polymer dots.

Pd(II) meso-tetra (pentafluorophenyl) porphine (PdTFPP, D4), were used to prepare four types of Pdots. A small amount of functional polymer poly(styrene-co-maleic anhydride) (PSMA, 10 wt% relative to the PDHF polymer) was used to functionalize the Pdots with surface carboxyl groups that allow for subsequent bioconjugation. Glucose oxidase (GOx) was conjugated to the four types of Pdots to form glucose transducers, which are Pt-porphyrin based transducers (PD1Gx, PD2Gx) and Pd-porphyrin based transducers (PD3Gx, PD4Gx). The dynamic light


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scattering (DLS) results showed that the conjugation of glucose oxidase caused a slight increase in the hydrodynamic diameter (Figure 2a). For example, the average hydrodynamic diameter of PD4Gx increased from 18 to 25 nm, and the surface ζ-potential changed from −29 to −18 mV, indicating successful GOx conjugation to the Pdots. The Pdot-GOx transducer showed spherical morphology and relatively monodispersed particle size distribution, as measured by transmission electron microscopy (TEM) (Figure 2b).

Figure 2. Luminescence response of PD4Gx to glucose. (a) Hydrodynamic diameters of PD4 with and without GOx coating. (b) Representative TEM image of PD4Gx transducer. (c) Luminescence spectra of PD4Gx transducer in PBS (pH 7.4) with increasing glucose concentrations. (d) A plot of the emission ratio (I672/I425) as a function of glucose concentration. The curve shows a good linear relationship (R2>0.99) in the physiologically relevant range (6-18 mM). (e) Time-dependent luminescence intensity of PD4Gx transducer at 672 nm after adding glucose to the PBS solution of the transducer. (f) The mean luminescence intensities of PD4Gx transducer in the presence of glucose and various carbohydrate analytes (20 mM). Error bars represent the standard deviations of the three measurements.


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Optical characterizations of the polymer-dot transducer. Spectroscopic measurements were performed to investigate the glucose sensing properties of the Pdot transducers. The absorption and emission spectra of the four types of Pdots are shown in Figure S1. As seen from the spectra, each of the Pdot transducers exhibited a dominant UV absorption band from PDHF polymer and a weak absorption peak from the porphyrin complex. Upon UV excitation, the Pdots showed blue fluorescence from the PDHF polymer and a red phosphorescence from the porphyrin complex. As an example, Figure 2c shows the emission spectra of PD4Gx at various glucose concentrations, indicating the superior response of the transducer to glucose.

The

intensity ratio of the red-to-blue emission peaks (I672/I425) constructs a ratiometric glucose sensing with a good linear relationship in the physiologically relevant range from 6 to 18 mM (Figure 2d). As the sensitivity is defined as the slope of the linear part of the curve,44 PD4Gx exhibited an intensity change of 152% per millimolar, which is much more sensitive than the other three Pdot transducers (9% per millimolar for PD1Gx, 17% per millimolar for PD2Gx, 80% per millimolar for PD3Gx) (Figure S2). The Pdot transducers also show fast glucose response within a few minutes and high selectivity against other carbohydrate derivatives (Figure 2e and 2f). These results are consistent with the high specificity and catalytic activity of the GOx enzyme. Excess of hydrogen peroxide, which is a side product of the enzymatic reaction, is detrimental to cells and tissues.45 We show that the addition of catalase can deplete the concentration of hydrogen peroxide, yielding a transducer that is biocompatible with cellular environment (Figure S3). The sensitivity of the Pd-porphyrin based transducer was significantly enhanced as compared to the Pt-porphyrin based one because of the long excited-state lifetimes. Both state-state and time-resolved measurements were used to validate the superior sensitivity of the PD4Gx


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transducer. As shown in Figure 3a, glucose (20 mM) was quickly added to the air-saturated solutions of four different transducers, leading to increased red phosphorescence as the dissolved oxygen was depleted.

When compared to the starting point (before glucose addition), the

emission intensity of PD4Gx transducer after glucose addition (10 min) was significantly enhanced by ~84-fold, which is much higher than those for PD3Gx (~27 fold), PD2Gx (~6 fold), and PD1Gx (~4 fold) (Figure 3b). According to Eq. 1, the enhancement in phosphorescence intensity is closely correlated to the changes in the excited state lifetime. Figure 3c shows the phosphorescence decay curves of the four transducers in the presence of glucose (~20mM). A monoexponential fit to the decay curve yielded a lifetime of 803 µs for the PD4Gx transducer, which is ~85-fold longer than the lifetime (9.3 µs) of PD4Gx in the absence of glucose. In contrast, the lifetimes of PD3Gx, PD2Gx, and PD1Gx transducers in the presence of glucose were ~24-fold, ~4-fold, and ~3-fold longer, respectively, than that in the absence of glucose (Figure 3d). These lifetime results were in good agreement with the changes in emission intensity, indicating that the long excited-state times of Pd-porphyrin complexes indeed led to significant enhancement in the sensitivity of the transducer.

Table 1. Photophysical properties of Pdot transducers for glucose monitoring.


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Figure 3. Optical characterizations of different Pdot-GOx transducers. (a) Time dependent emission intensities of PDGx (PD1Gx (black), PD2Gx(red), PD3Gx(green), PD4Gx(blue)) in the presence of glucose (20 mM).

(b) Comparisons of phosphorescence intensities of PDGx

transducers in the absence (blue) and presence (orange) of glucose calculated from the spectroscopic data at 10 min. (c) Phosphorescence decay curves of PDGx (PD1Gx (black), PD2Gx(red), PD3Gx(green), PD4Gx(blue)) upon addition of excess glucose. The grey curve shows the instrumental response function (IRF). The scattered dots represent the experimental data, and the solid lines are fitting curves. (d) Comparisons of phosphorescence lifetimes of PDGx transudcers in the absence (blue) and presence (orange) of glucose. (e) Photostability of the PDGx (PD1Gx (black), PD2Gx (red), PD3Gx (green), PD4Gx (blue)) in the absence of glucose, showing the decreases of the emission intensities over 10 min under continous excitation of 380 nm. (f) Luminescence intensites from the initial and final emission spectra taken under continuous 380 nm illumination. Error bars represent the standard deviations of the three measurement.


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In addition, the photostabilities of the four transducers were investigated, as they are critical for long-term glucose monitoring. The photobleaching kinetics was found to vary substantially in the four types of Pdot transducers (Figure 3e). Under continuous illumination of a Xe lamp in a fluorometer, the PD2Gx and PD4Gx transducers (with the same TFPP ligand) showed much better photostability than PD1Gx and PD3Gx (with OEP ligand). Particularly, PD4Gx appears as the most photostable among the four transducers, as evidenced by minimum photobleaching under the same light irradiation (Figure 3f).

The photophysical parameters of the four

transducers are summarized in Table 1. The optical characteristics in the Table indicate that PD4Gx is the most suitable transducer for glucose monitoring because of its superior sensitivity and excellent photostability. In vivo glucose monitoring by smartphone and implanted transducer. We examined the performance of the PD4Gx transducer in real-time blood glucose monitoring in live mice. PD4Gx transducers were implanted in the subcutaneous tissue on the backs of live mice (8-week, Balb/c). Luminescence images of the mice were captured every 5 min using a small-animal biophotonic imaging system. After intraperitoneal (i.p.) infusion of glucose solution (200 µL, 1 M in 1x PBS, pH=7.4), an obvious transdermal red phosphorescent signal was observed because of the rise in blood glucose level (Figure 4a).

Furthermore, the phosphorescence signal

gradually decayed as the blood glucose concentration was reduced by the intraperitoneal infusion of insulin (100 µL, 0.5 U/mL, saline solution). For a comparison, the performance of PD1Gx transducer was also examined according to the same experimental protocol. As clearly seen from the data (Figure S4), the phosphorescence intensities of both PD1Gx and PD4Gx transducers consistently monitored the concentration changes induced by infusions of glucose


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Figure 4. In vivo glucose monitoring in hyperglycemia animal model. (a) In vivo biophotonic images of a live mouse with intraperitoneal administration of glucose and insulin over time. PD4Gx transducers were implanted in subcutaneous site of the mice.

(b) The magnified

luminescence images of the implanted PD4Gx and PD1Gx in euglycemic (~5mM) and hyperglycemic (~18mM) mice. (c) The mean luminescence intensities of PD4Gx and PD1Gx from the regions of interest in (b). (d) The luminescence intensity ratios of PD4Gx and PD1Gx versus blood glucose concentrations. The corresponding solid lines are fitting curve, showing the superior sensitivity of PD4Gx to PD1Gx . Error bars represent the standard deviations of three measurements.

and insulin. However, further image analysis indicated the superior sensitivity of the PD4Gx transducer as compared to PD1Gx. Assuming ~5 mM is the normal glucose level (euglycemia), and 18 mM is the high glucose level (hyperglycemia), we compared the intensity ratio of phosphorescence signals of hyperglycemia and euglycemia, which were obtained by using PD4Gx and PD1Gx and the imaging system (Figure 4b). The imaging results indicated that PD4Gx exhibited 12 times signal enhancement from euglycemia to glycemia, whereas PD1Gx showed only 2 times increase under the change in glucose levels (Figure 4c). Calibration curves


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of PD4Gx and PD1Gx transducers were plotted from the biophotonic images (Figure 4d). As estimated from the slopes of the calibration curves, the PD4Gx transducer in live animals showed approximately six times higher sensitivity than that of PD1Gx.

The performance

difference between PD4Gx and PD1Gx in live animals was somewhat lower than that obtained in aqueous solutions (20 times improvement) because in vivo monitoring is also dependent on the issues such as local microvascular perfusion, availability of tissue oxygen, and tissue penetration of the optical signals. In vivo reversible measurements and biodistribution of the Pdot transducer were performed to investigate whether PD4Gx was suitable for long-term glucose monitoring. After the Pdot transducer was implanted, reversible measurements were repeated for three times in one day. Because frequent blood sample collection may cause severe blood loss or even death of the mice, we choose to monitor the two points (hyperglycemia and euglycemia) in several up-and-down cycles. As shown in Figure S5, the response of the transducer remained unchanged for multiple repetitive measurements in one day. Subsequently, the measurements were repeated once a day for three days, and the luminescence intensity was also closely correlated with the glucose level in these measurements, indicating the potential of the Pdot transducer for long-term glucose monitoring.

In addition, the major organs and subcutaneous tissues were excised from

euthanized mice one-month post implantation for imaging and histological analysis.

The

luminescence images showed that strong emission was only observed from subcutaneous tissue, indicating the PD4Gx transducer reside at implantation site without migration to other organs (Figure S6a-b). We also evaluated whether there was an inflammation effect from possible color change, swelling, and scab of implantation site by using the method described in a previous study.18 The PD4Gx did not induce any inflammation for at least 30 days (Figure S6c).


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Histological analysis indicated no obvious organ damage or inflammation in all the organs and tissue (Figure S7). The minimally invasive subcutaneous injection and good biocompatibility of the Pdot material efficiently alleviate the pain from the implantation process and reduce the inflammation owing to the negligible open wound. Therefore, the PD4Gx transducer holds great potential for in vivo glucose monitoring. Although optical methods have long been explored for glucose detection,16 nearly all optical methods involve the use of bulky optical instrumentation, such as microplate reader,22 spectroscopic equipment,20,21 and small-animal imaging system.17,18 As shown in Figure 2d the PD4Gx transducer displayed emission spectra which can be well decomposed into blue and red channels.

Correspondingly, the luminescence images of the aqueous solutions under UV

excitation showed apparent color evolution from blue to red by varying the glucose concentration from 2 to 20 mM (Figure 5a). It is well known that any true-color image can be split into three primary color images by the RGB model. Each of the primary color images can be digitized by using a MATLAB image-processing algorithm, yielding intensity values that are correlated with the glucose concentrations. To validate the above principle, we processed the luminescence images taken by a smartphone camera (Figure 5a). As illustrated with two glucose concentrations (0 mM and 20 mM), the respective images were decomposed by the RGB model, yielding blue-channel images with constant intensities and red-channel images with glucose-dependent intensities. The intensity ratio of the red-to-blue channels was used for calculation and quantification of the glucose concentrations. With the PD4Gx transducer and


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Figure 5. Image processing algorithm for in vitro glucose measurement. (a) Photographs of luminescent PD4Gx transducer at different glucose concentrations (0-20 mM). A customized digital-image processing algorithm was developed to decompose the original true-color image into the R (red), G (green), and B (blue) image channels. The intensity ratio was calculated from the pixel arrays of R and B channel images. (b) The mean R/B intenisty ratio in the absence and presence of glucose (0 mM and 20 mM). (c) The temporal change of luminescent PD4Gx transducer captured every minute over time after adding glucose of different concentrations (020 mM). The value of each point in the cuvre was calculated from the R/B intensity ratio between the pixel arrays of the R and B channel images. (d) The R/B intensity ratio as function of glucose, showing good linear relationship (R2>0.99) in the physiologically relevant glucose range (6-18 mM).

smartphone images, approximately 30-fold intensity enhancement was detected from aqueous solutions in the absence and presence of glucose (20 mM), indicating the feasibility of using smartphone images for blood glucose monitoring (Figure 5b).

Furthermore, luminescence

images were continuously captured over time for the samples with different glucose


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concentrations (0-20 mM). By using the image processing algorithm, we plotted the real-time glucose response curves (Figure 5c), which are in good agreement with the response curves obtained by the spectroscopic measurements. Figure 5d displayed the linear response (R2 > 0.99) of Red/Blue intensity ratio in the physiological blood glucose range of 6-18 mM with a sensitivity of approximately 60 % per millimolar. This sensitivity obtained by the smart-phone images was somewhat lower than that seen in the spectroscopic results (152 % per millimolar). However, these results indicated that the PD4Gx transducer combined with the smartphone provides a viable approach for glucose monitoring. Finally, we demonstrated real-time dynamic glucose monitoring by a smartphone system with a custom-built APP. PD4Gx transducers were implanted in the subcutaneous site of live mice, which were then imaged by the smartphone under a UV-lamp excitation (Figure 6a). The APP software consists of an image acquisition module, image processing module, image analysis module, and data service module (Figure 6b).

By installing the APP software on the

smartphone, we can determine the blood glucose concentrations in real-time by analyzing the optical image of the implanted transducer in live mice. Figure 6c shows the luminescence photographs of the transducer in live mice before and after intraperitoneal injection of glucose. Apparent changes in the emission color of the implanted transducer were identified by unaided eyes and smartphone camera.

After sequential injections of glucose and insulin, the

luminescence images were continuously taken by using the digital camera of a smartphone. By selecting a uniform color region (150×150 pixels) near the center of the images (Figure 6d), blood glucose concentrations were obtained by running the APP software, in which images were processed through sequential steps such as color decomposition and red/blue intensity


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Figure 6. In vivo continuous glucose monitoring in live mice using PD4Gx transducer and smartphone. (a) Photograph of glcuose measurement in live mice by a smartphone camera. (b) Image decomposition method for blood glucose monitoring using an APP in the smartphone. The images displayed on the smartphone show the testing home page (left) and the real-time data display page (right) of the APP. (c) Representative true-color photographs of the implanted PD4Gx transducer before and after glucose administration. (d) Magnified regions in the images taken by smartphone camera at different blood glucose levels. (e) Calibration curve using the Red/Blue intensity ratio as a function of glucose concentration. The fitting curve (solid line) showed an excellent linear relationship (R2 > 0.99). (f) Real-time dynamic glucose monitoring by the implanted PD4Gx transducer and smartphone (black).

By glucose and insulin

administration, the blood glucose levels showed an up-and-down fluctuation along the timeline. The red scattered points were measured by a commercial glucose meter using the tail blood.


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calculation. A calibration curve was established by comparing the Red/Blue intensity ratio with the glucose values measured by a commercial glucose meter (Figure 6e). By means of the calibration curve, the blood glucose can be continuously monitored by smartphone-based measurements through image recording and APP analysis. As shown in Figure 6f, the glucose measurement by the smartphone system clearly reflected the rise and fall of blood glucose levels in live mice with glucose and insulin infusions. For comparison, a few scattered points were detected by a commercial glucose meter. The scattered measurements by glucose meter were in good agreement with the continuously monitored data, indicating that the smartphone with the implanted transducer can quantitatively measure and continuously monitor blood glucose changes in living mice.

CONCLUSION In summary, we developed an ultrasensitive polymer-dot transducer for wireless glucose monitoring via a smartphone. By using the longer lifetime palladium porphyrin complexes, the Pdot transducer exhibited a significantly higher sensitivity in both in vitro and in vivo glucose detection. With the ultrasensitive transducer, it was possible to clearly differentiate between euglycaemia and hyperglycaemia using luminescence images taken with a smartphone camera. We further developed an image-processing algorithm to decompose the fluorescence image via the RGB model. Based on the algorithm, a software application was developed and installed on a smartphone. We demonstrated a wireless, real-time, dynamic glucose monitoring of blood glucose level by means of the implanted transducer and the smartphone. The miniaturisation of the optical monitoring platform can promote innovative development of optical monitoring


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approaches in diabetic healthcare. Furthermore, by taking advantage of the mobile platform, the blood glucose data can be stored and uploaded to a database for personal healthcare, and this can aid the understanding and prediction of public health status through big data analysis. Additionally, as a highly sensitive transducer, the platform can be used for assembly into a closed-loop artificial pancreas intelligent system for maintaining normoglycemia.

METHODS AND EXPERIMENTAL SECTION Materials. The polymers poly(9,9-dihexylfluorenyl-2,7-diyl) (PDHF, average Mw 55,000, polydispersity 2.7), poly(styrene-co-maleic anhydride) (PSMA, average Mw ~1,700, styrene content 68%), the phosphorescent dyes Platinum(II) octaethylporphine (PtOEP), Palladium(II) octaethylporphine (PdOEP), Platinum(II) meso-tetra (pentafluorophenyl) porphine (PtTFPP), Palladium(II) meso-tetra (pentafluorophenyl) porphine (PdTFPP), and tetrahydrofuran (THF) solvent were purchased from Sigma-Aldrich. . Preparation and characterizations of Pdots. Dye-doped polymer dots were prepared by a modified reprecipitation method.

Taking PtOEP-doped Pdots as an example, the PDHF

polymer, PSMA polymer, and PtOEP were first dissolved in THF solvent to prepare stock solutions (1 mg/mL), respectively. The stock solutions were further diluted in THF to produce solutions consisting of PDHF (100 µg/mL), PSMA (10 µg/mL), and PtOEP (10 µg/mL). Then, an aliquot of the solution mixture (2 mL) was added quickly to Milli-Q water (10 mL) in a bath sonicator, followed by additional 2 min of sonication. For removing the THF solvent, the solutions were heated on a 90 °C hotplate with nitrogen stripping. After removing, the solutions


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continued to be concentrated to 8 mL and filtrated through a 0.2 micron filter. The same method was used for preparing other Pdots doped with PdOEP, PtTFPP, and PdTFPP, respectively. The hydrodynamic diameter and surface potential of Pdot-GOx nanoparticles were characterized by dynamic light scattering (DLS) using a Malver Nano ZS instrument. The morphology and monodispersity Pdot-GOx were characterized by transmission electron microscopy (TEM). The samples for TEM measurements were prepared by drop casting the Pdot-GOx dispersion onto copper grids.

TEM image were performed using a microscope

(Hitachi H-600, 120 kV). The UV−vis absorption spectra of Pdot-GOx were obtained by a scanning spectrophotometer (Shimadzu UV-2550), and the luminescence spectra of Pdot-GOx transducer

at

different

glucose

concentrations

were

recorded

by

a

fluorescence

spectrophotometer (Hitachi F-4600). GOx Bioconjugation with Pdots. The GOx enzyme was conjugated to the surface of Pdots by the EDC-catalyzed peptide formation. In the experimental protocol, 125 µL of glucose oxidase (10 µM in 20 mM HEPES) and 100 µL of EDC solution (freshly-prepared, 5 mg/mL of MilliQ water) were successively added to the Pdot solution (20 mM HEPES). The solution was well mixed on a vortex for 4 h at 25℃ (room temperature). Finally, free glucose oxidase molecules were separated by size-exclusion column using Sephacryl-300 gel media. In vivo glucose monitoring. Balb/c nude mice (Vital River Laboratories, Beijing, China) were used for in vivo glucose monitoring. Approximately 8-week-old female mice were used for all animal experiments, which were performed in compliance with the Guidelines for the Care and Use of Research Animals established by the Institutional Animal Care and Use Committee of Jilin University. The experimental group size was approved by the regulatory authorities for


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animal welfare. Before experiment, the mice were anesthetized with intraperitoneal injection of chloral hydrate (400 mg/kg) or inhalation of isoflurane (1.5 mL/h). 100 µL of PD4Gx (50 µg/mL) was implanted subcutaneously into the dorsal side of the mouse. After PD4Gx implantation, biophotonic images were recorded with a custom built optical imaging system. For blood glucose manipulation, the sterilized glucose solution (200 µL, 1 M) and insulin (100 µL, 0.5 U/mL) were sequentially administered via intraperitoneal infusion (with time interval of 15 min). The fluorescence imaging was continuously captured every 5 min with an excitation of 543 nm and emission at 672 nm. After fluorescence imaging, a tail blood sample was collected and measured by using a standard glucose meter (Accu-Chek, Roche Diagnostics), for determining the blood glucose level. ASSOCIATED CONTENT Supporting Information. The Supporting Information is available free of charge on the ACS Publications website. Additional figures of the spectroscopic characterizations, cell viability, and in vivo glucose monitoring. (PDF) The authors declare no competing financial interests. AUTHOR INFORMATION Corresponding Author *E-mail: [email protected] Author Contributions


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C.W. conceived the projects and designed the experiments. K.S. was primarily responsible for the experiments. J.Y. and D.T.C. contributed to the design of the Pdot transducer. Y.Y. and H.Z. performed the preparation and characterization of the polymer-dot transducer. K.S. and Y.Y. contributed to the spectroscopic studies and in vivo glucose monitoring. K.S. developed an image processing algorithm and a software application that was installed on a smartphone. S.Y., W.Q., Z.Y., and X.Z. provided input to the design of the experiments. K.S., D.T.C., and C.W. wrote the paper. All authors discussed the results and commented on the manuscript. ACKNOWLEDGMENT This work was supported by the grants from the National Natural Science Foundation of China (Grant No. 61335001; Grant No. 81771930), Shenzhen Science and Technology Innovation Commission (Grant No. JCYJ20170307110157501), and Open Project of the State Key Laboratory of Luminescence and Applications.

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TABLE OF CONTENTS GRAPHIC AND SYNOPSIS


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Ultrabright Polymer-Dot Transducer Enabled ... - ACS Publications

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