Non-Equilibrium Diffusion Controlled Ion-Selective Optical Sensor for

Xinfeng Du† and Xiaojiang Xie†. † Department of Chemistry, Southern University of Science and Technology, Shenzhen, 518055, P. R. China. ACS Sen...
0 downloads 12 Views 2MB Size
Letter pubs.acs.org/acssensors

Non-Equilibrium Diffusion Controlled Ion-Selective Optical Sensor for Blood Potassium Determination Xinfeng Du† and Xiaojiang Xie*,† †

Department of Chemistry, Southern University of Science and Technology, Shenzhen, 518055, P. R. China S Supporting Information *

ABSTRACT: Blood electrolyte measurements play important roles in clinical diagnostics. Optical ion sensors as simple and elegant as a mercury thermometer are in high demand. We present here an analytical method to quantify potassium ions in undiluted human blood and plasma by measuring the distance or the rate of the color propagation. The sensor was composed of K+-selective nanospheres embedded in an agarose hydrogel where mass transport was diffusion controlled. The sensor’s color-changing rate and the distance of color propagation depended linearly on the logarithm of K+ activity. A theoretical model was established and fully supported the experimental findings. This work lays the foundation of a new family of optical ion sensors for direct determination of common blood electrolytes. KEYWORDS: distance, sensors, blood electrolytes, ion selective optodes, hydrogels lood electrolyte (typically K+, Na+, Ca2+, Cl−, and so on) measurements have become routine in clinical laboratories to help diagnose a wide variety of acute and chronic illnesses.1 Blood potassium level fluctuations including hyperkalemia and hypokalemia can indicate acute renal failure, hypoaldosteronism, and rhabdomyolysis.2−4 Generally, advanced sensing technology for blood electrolyte detection is in high demand. An ideal ion sensor should be robust, fast, inexpensive, and easy to operate. Inspired by the state-of-art measuring tools such as the mercury thermometer, sensing concepts to determine blood electrolytes based on simple parameters (e.g., distance and time) could be of great value. Indeed, distance as a simple analytical measure has attracted the attention of many researchers to be integrated into chemical and biological sensors.5−10 Yang et al. recently developed several point-of-care microfluidic chips based on various substrates such as PMMA and polyacrylamide hydrogel.6−8 Henry et al. reported paper-based analytical devices for glucose, nickel, and glutathione using enzymatic reactions, metal complexation, and nanoparticle aggregation as the detection chemistries.9 A distance-based Cu2+ sensor on paper was also proposed.10 Ionophore-based ion-selective optodes (ISOs) are considered the alternative of ISEs which have created great impact since the integration into the clinical laboratory for automated testing of physiological samples.11 Typical ISOs are composed of hydrophobic sensing components embedded in lipophilic materials, and the sensing process involves ion-exchange (for cations) or coextraction (for anions). The absorbance or the fluorescence intensity of ISOs was recorded after the sensor and the sample reached equilibrium. ISOs are compatible with microplate readers, suitable for noninvasive remote sensing,

B

© XXXX American Chemical Society

easily miniaturized, and free from electromagnetic interferences and the cumbersome reference electrodes. In addition to conventional light absorption and fluorescence, recent emergency of photoacoustic measurements on ISOs have also rendered them highly valuable tools for in vivo monitoring.12,13 Ion-selective optodes are more than 25 years old, but due to certain limitations,14 they had no significant breakthrough in the field of clinical applications. Recently, Lindner and Pinkhassik and co-workers reported molecular indicators encapsulated in liposomes and poly(vinyl alcohol) with diffusion limited response times. 15,16 Meyerhoff et al. demonstrated paper-based plasticizer-free ion-selective sensors for sodium and anions to allow camera phone as a detector and buffers to be impregnated into the optode device.17,18 Ionophore-based titration reagents for serum samples were reported by Bakker et al.19,20 The same group also made progress to overcome of the pH cross-response of ISOs by replacing the chromoionophores with solvatochromic dyes or with exhaustive sensing mode.21−23 Optical sensors measuring spectrum intensity become difficult to apply when the sample is strongly colored, turbid, or fluorescent. Therefore, optical ion sensors functioning directly in undiluted human blood are rarely reported. However, direct measurement in whole blood without sample pretreatment is most clinically relevant for diagnostics. Near infrared (NIR) dyes and upconverting nanomaterials could mitigate the spectrum-overlapping problem.24−26 UnfortuReceived: August 25, 2017 Accepted: September 25, 2017

A

DOI: 10.1021/acssensors.7b00614 ACS Sens. XXXX, XXX, XXX−XXX

Letter

ACS Sensors

Figure 1. Schematic illustration of the K+ sensing hydrogel and the two interrogation modes based on distance and absorbance decay rate.

and K+ ionophore (valinomycin, L). The nanosensors were prepared according to our previously established protocols (see Supporting Information for details).28 When K+ concentration (activity, strictly) is low, the gel appeared blue due to the high degree of protonation of C. The blue color of the gel eventually became reddish as the K+ concentration increased. However, this color change should not be fleeting to the human eyes because the mass transport of potassium ions near the solution/gel interface is diffusion limited. Therefore, the color propagation perpendicular to the potassium flux could be easily captured with a digital camera or even human eyes, while on the other hand, one could observe the color change in parallel to the flux. The choice of interrogation mode depends on the sample and instrumentation (vide inf ra). Figure 2a shows the time-dependent potassium ion concentration profiles across the solution/gel interface after adding 0.01 M of KCl solution to the hydrogel. The concentration profiles were numerically simulated every 4 s with a K+ diffusion coefficient of 1.93 × 10−5 cm2 s−1 in the aqueous solution and half that value in the hydrogel (please refer to the Supporting Information for more details). Future experimental confirmation of the concentration profiles is possible based on previous work on ion transport and diffusion coefficients with spectrophotometric and spectropotentiometric methods.29−31 Figure 2b shows the images of the hydrogel at various K+ concentrations. The gels were left overnight to reach equilibrium before the images were taken. The images were then analyzed by Wolfram Mathematica to extract the hue value (which reflects the color of the image in the HSB space) for each K+ concentration (Figure 2c).20 Combined with the concentration profiles shown in Figure 2a, the hue value at each

nately, such sensors for undiluted blood potassium measurements are still future promises. Xie et al. previously reported K+ selective ISOs incorporating NaYF4:Er,Yb upconverting nanorods, where blood samples still required at least 10 times dilution.24 On the other hand, most precedent ISOs operated under equilibrium mode.11,27 The kinetics of the sensing process of ISOs is normally mass transport limited, and in most cases, kinetic information is buried in the so-called “response time”. However, the response of the sensing system prior to reaching equilibrium contains rich and sample relevant information, and so far, it remains largely unexploited. Herein, we report a quantitative methodology to determine ion concentrations by simply analyzing the distance or the rate of the color propagation of ISOs. The sensor was operated in a diffusion controlled nonequilibrium mode and the kinetic information was utilized to analyze the sensor response. The hydrogel-trapped nanosensors enabled us to determine potassium concentrations in undiluted human blood without interference from the deeply colored background. To the best of our knowledge, such an optical sensor for blood electrolytes has not yet appeared. Figure 1 schematically illustrates the composition and the operating mode of the sensor. K+-selective nanosensors were trapped in a piece of agarose hydrogel. Agarose hydrogel was used because of its easy preparation, thermal reversibility, and low interference with the sensing process. The nanosensors, with ca. 100 nm hydrodynamic diameters, remained well trapped in the agarose hydrogels (0.5−2% w/w) without observable leakage over several days. The nanosensors functioned on the ion-exchange basis as conventional ISOs and contained chromoionophore (C), cation exchanger (R), B

DOI: 10.1021/acssensors.7b00614 ACS Sens. XXXX, XXX, XXX−XXX

Letter

ACS Sensors

Figure 3. (a) Analysis of an image (inset) to determine the distance of color propagation; gel (pixel position above 0), 1 mL of 10 mM KCl solution (pixel position below 0). (B) distance-based calibration line for blood potassium determination (black); red circle represents the undiluted human blood sample; inset pictures: K+ sensing gels 2 min after addition of standards with various concentrations of KCl (upper); a blank agarose hydrogel (1% w/w) 2 min after addition of undiluted human blood (lower left); K+ sensing gels 2 min after addition of 1 mL undiluted human blood (lower right).

(ca. 7.5 μm in diameter and 2 μm thick) which constitute about 45% of the whole blood volume.33 Here, the agarose hydrogel matrix served simultaneously as a filter to block the red blood cells and other large biomolecules while allowing the potassium ions to diffuse through. As shown in the insets of Figure 3b, the dark red background of undiluted human blood was blocked by the hydrogel and unable to interfere with the detection. The images were taken 2 min after adding the blood. The potassium concentration in the undiluted blood was determined by standard calibration to be 3.7 ± 0.2 mM, which is in the normal concentration range and also close to the level determined in the blood plasma using ICP-MS (3.6 ± 0.2 mM). The relative error of the distance-based measurement was restricted to less than 4% and mainly came from the color boundary determination. Further improvements on image acquisition setup and the gel processing to obtain a sharper edge could even reduce the relative error. The sample addition could induce a small level of convection to the aqueous phase. However, the batch- to-batch experiments indicated that the influence on the reproducibility was not an issue. For ICP-MS measurements, the oversensitivity of the MS detection forced us to dilute the plasma samples 200 times. On the other hand, observation in parallel with the potassium ion flux allowed us to monitor the absorbance change of the gel over time using UV−visible absorption spectrometer. Here for simplicity, the agarose hydrogels with ca. 3 mm thickness were cast on the walls of disposable polystyrene cuvette. For this K+ sensor containing chromoionophore I (C), the absorbance at 665 nm which is sensitive to the protonation C was monitored. As shown in Figure 4a, plotting the absorbance of the gels against the square root of time resulted in a linear correlation. A linear fit was obtained between the decay rate at 665 nm and the logarithm of K+ activity. Clearly the decay became faster as the K+ concentration increased. Note that the gel thickness only affected the absolute absorbance values which were offset for better presentation. Figure 4b showed a linear calibration line from which the K+ activity in the blood plasma sample was determined to be 3.6 ± 0.1 mM. The measurement of the slope was highly reproducible with relative errors less than 1%. A theoretical modeling was also performed through numerical simulation and the theoretical response curves agreed very well with the experimental results over a larger concentration range

Figure 2. (a) Numerically simulated K+ concentration profiles at the hydrogel/solution boundary; arrows indicate the evolution every 4 s. (b) Picture of the K+ sensing hydrogel at equilibrium with 0.5 mL aqueous solutions containing various KCl. (c) Hue values extracted from b as a function of K+ activity. (d) Simulated color propagation of a hydrogel exposed to 10 mM KCl solution at various times (as indicated).

position across the interface was reconstructed and the color propagations at various time steps could be predicted (as shown in Figure 2d). According to the model, boundaries can be drawn to identify how far the color has propagated. Moreover, as shown in Figure S1, the absorption spectra for the sensing gels showed much higher scattering signals. Nevertheless, the response of the nanosensors in solutions and in the hydrogels showed little difference, indicating that the agarose gel matrix had little interference to the sensor response at equilibrium state. Although it is a convenient way to identify the color propagation with the naked eye, each individual could perceive the colors with subtle differences. To obtain more precise and standardized results, we performed RGB analysis on the acquired images. Figure 3a shows the results on an image 2 min after the addition of 10 mM KCl sample solution. The ratio of the red channel value (Figure S2a) to the blue channel value (Figure S2b) was plotted against the pixel position. The two transitions (indicated by the blue solid lines in Figure 3a) corresponding to the two boundaries were observed to help identify the propagated distance, and the boundaries identified in this way matched our visual perception very well. As shown in Figure 3b, a linear calibration was observed for the sensor in the K+ concentration range of 0.1 to 10 mM. Normal human blood potassium level is within the range of 3.5−5.0 mM, which is covered by the sensor. Because of the deeply colored and scattering background, it is very challenging to apply conventional optical ion sensors in undiluted blood. Molecular indicators for K+, for instance, despite their successful applications in cells and urine samples, are very difficult to use in undiluted blood samples.32 The deep color of blood mainly comes from the heme-containing red blood cells C

DOI: 10.1021/acssensors.7b00614 ACS Sens. XXXX, XXX, XXX−XXX

Letter

ACS Sensors

composed of water, undiluted blood plasma, and diluted blood plasma exhibited very close slopes (−8.74 × 10−3, −8.33 × 10−3, and −8.34 × 10−3, respectively) in the kinetic measurements. The samples were spiked with the same level of KCl (0.1 M). In summary, a methodology to detect potassium ions has been developed based on hydrogel-trapped nanosensors. The distance or the color changing rate was utilized as the sensor response. While the mass transport in the hydrogel matrix was diffusion limited, allowing us to take full advantage of the kinetic information, the gel matrix served simultaneously as a filter for the analyte, blocking the optically interfering red blood cells and, hence, enabling the optical detection of K+ in undiluted human blood. Considering the choices of ionophores, this platform is in principle highly versatile. Sensors for other blood electrolytes including Na+, Ca2+, and Cl− based on this methodology are being continued in this laboratory. Both the distance-based image analysis and the decay rate measurement provided satisfactory analytical precision with the relative error below 4%. Future improvements on gel processing and instrumentation are envisioned. The hydrogels also could potentially be adapted for use on microfluidic devices and multiwell microplate readers to further reduce the sample volume requirement and increase the throughput.

Figure 4. (a) Absorbance decay at 665 nm of the K+ sensing gel after addition of KCl solutions (black) and undiluted human blood plasma (red). (b) Calibration lines using the decay rate as a function of logarithm activity of K+ (black) and the signal from the plasma sample (red circle). Error bars (n = 5) smaller than the plot markers and not shown.

(0.1 mM to 100 mM; see Figure S3 and S4). At high K+ concentration (e.g., 100 M) over long interrogation time, the deviation from linearity was due to the finite thickness of the gels. Compared with measuring the distance, monitoring the absorbance decay rate is attractive if UV−visible spectrometers or microplate readers are readily available. The hydrogels could be easily cast in commercial 96-well plates. Thus, the decay rate measurement could be more easily adapted to microplate readers for high throughput. To some extent, this detection mode was also compatible with colored samples (Figure S5) given that the sample background remained unchanging. We measured the K+ concentrations in undiluted human blood plasma and a colored cell culture medium containing known potassium concentrations and the results agreed with ICP-MS measurements. However, measurements with undiluted human blood samples in this mode were unsuccessful due to the deeply colored and scattering background. Reducing the sample thickness or using NIR chromoionophores could potentially enable this detection mode but it could also increase the instrumentation and sample preparation requirements. ISOs containing chromoionophores are known to suffer from the pH dependence. To overcome this problem, Bakker and coworkers previously proposed to use solvatochromic dyes as the replacement of chromoionophore, or operating ISOs in the exhaustive sensing mode.21−23 Here, the agarose hydrogel matrix allowed us to overcome the cross-response from sample pH changes simply by adding pH buffers to the sensing gel. To evaluate the stability of the pH within the gel, organosilica particles surface-modified with fluorescein (a pH sensitive indicating dye) were trapped in the gels and the absorbance of the gels were monitored upon exposing to samples with pH 3.0, 5.0, 7.0, 9.0, and deionized water (nonbuffered). As shown in Figure S6, within the detection time window of the sensor, the absorbance change was very little even with pH 3.0 in the sample, indicating that the hydrogel was indeed well buffered. Figure S7 shows that the responses of the gels to 1 mM KCl sample at pH 5.0, 7.0, and 9.0 were identical when the gels were filled with 5 mM phosphate buffer. In addition, the use of valinomycin as potassium ionophore ensured the selectivity of the sensor. As shown in Figure S8, very close decay rates (slopes) were observed for sample solutions without and with 100 mM NaCl, 1 mM MgCl2, and 1 mM CaCl2. The innate viscosity of the blood plasma had little influence on the optical kinetics. As shown in Figure S9, samples



ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acssensors.7b00614. Description of experimental methods including the preparation of the nanosensors and hydrogels, numerical simulations, supplementary figures including spectra and calibrations for the K+ response of the nanosensors and the gel at equilibrium mode, selectivity and response at various pH conditions (PDF)



AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. ORCID

Xiaojiang Xie: 0000-0003-2629-8362 Notes

The authors declare no competing financial interest.

■ ■

ACKNOWLEDGMENTS The authors thank the start fund of SUSTC and the Thousand Talents Program of China for financial support. REFERENCES

(1) Leino, A.; Kurvinen, K. Interchangeability of blood gas, electrolyte and metabolite results measured with point-of-care, blood gas and core laboratory analyzers. Clin. Chem. Lab. Med. 2011, 49 (7), 1187−1191. (2) Manteaux, A. E.; Dali-Braham, I.; Ramont, L.; Maquart, F. X.; Oudart, J. B. Confusing hyperkalemia. Clin. Chem. 2017, 63 (7), 1305−1306. (3) Kieneker, L. M.; Eisenga, M. F.; Joosten, M. M.; de Boer, R. A.; Gansevoort, R. T.; Kootstra-Ros, J. E.; Navis, G.; Bakker, S. J. L. Plasma potassium, diuretic use and risk of developing chronic kidney disease in a predominantly White population. PLoS One 2017, 12 (3), e0174686.

D

DOI: 10.1021/acssensors.7b00614 ACS Sens. XXXX, XXX, XXX−XXX

Letter

ACS Sensors (4) Shajani-Yi, Z.; Lee, H. K.; Cervinski, M. A. Hyponatremia, hypokalemia, hypochloremia, and other abnormalities. Clin. Chem. 2016, 62 (6), 898−898. (5) Yamada, K.; Shibata, H.; Suzuki, K.; Citterio, D. Toward practical application of paper-based microfluidics for medical diagnostics: stateof-the-art and challenges. Lab Chip 2017, 17 (7), 1206−1249. (6) Huang, Y. S.; Ma, Y. L.; Chen, Y. H.; Wu, X. M.; Fang, L. T.; Zhu, Z.; Yang, C. J. Target-responsive DNAzyme cross-linked hydrogel for visual quantitative detection of lead. Anal. Chem. 2014, 86 (22), 11434−11439. (7) Zhu, Z.; Guan, Z. C.; Jia, S. S.; Lei, Z. C.; Lin, S. C.; Zhang, H. M.; Ma, Y. L.; Tian, Z. Q.; Yang, C. J. Au@Pt nanoparticle encapsulated target-responsive hydrogel with volumetric bar-chart chip readout for quantitative point-of-care testing. Angew. Chem., Int. Ed. 2014, 53 (46), 12503−12507. (8) Xie, Y.; Wei, X. F.; Yang, Q. Z.; Guan, Z. C.; Liu, D.; Liu, X.; Zhou, L. J.; Zhu, Z.; Lin, Z. Y.; Yang, C. Y. A Shake&Read distancebased microfluidic chip as a portable quantitative readout device for highly sensitive point-of-care testing. Chem. Commun. 2016, 52 (91), 13377−13380. (9) Cate, D. M.; Dungchai, W.; Cunningham, J. C.; Volckens, J.; Henry, C. S. Simple, distance-based measurement for paper analytical devices. Lab Chip 2013, 13 (12), 2397−2404. (10) Pratiwi, R.; Nguyen, M. P.; Ibrahim, S.; Yoshioka, N.; Henry, C. S.; Tjahjono, D. H. A selective distance-based paper analytical device for copper(II) determination using a porphyrin derivative. Talanta 2017, 174, 493−499. (11) Bakker, E.; Buhlmann, P.; Pretsch, E. Carrier-based ion-selective electrodes and bulk optodes. 1. General characteristics. Chem. Rev. 1997, 97 (8), 3083−3132. (12) Lee, C. H.; Folz, J.; Zhang, W.; Jo, J.; Tan, J. W. Y.; Wang, X.; Kopelman, R. Ion-selective nanosensor for photoacoustic and fluorescence imaging of potassium. Anal. Chem. 2017, 89 (15), 7943−7949. (13) Cash, K. J.; Li, C. Y.; Xia, J.; Wang, L. H. V.; Clark, H. A. Optical drug monitoring: photoacoustic imaging of nanosensors to monitor therapeutic lithium in vivo. ACS Nano 2015, 9 (2), 1692−1698. (14) Lindner, E.; Bordelon, D.; Kim, M. D.; Dergunov, S. A.; Pinkhassik, E.; Chaum, E. Ion-selective optodes in a sampling capillary for tear fluid analysis. Electroanalysis 2012, 24 (1), 42−52. (15) Dergunov, S. A.; Miksa, B.; Ganus, B.; Lindner, E.; Pinkhassik, E. Nanocapsules with ″invisible″ walls. Chem. Commun. 2010, 46, 1485−1487. (16) Kim, M. D.; Dergunov, S. A.; Lindner, E.; Pinkhassik, E. Dyeloaded porous nanocapsules immobilized in a permeable polyvinyl alcohol matrix: a versatile optical sensor platform. Anal. Chem. 2012, 84, 2695−2701. (17) Wang, X. W.; Qin, Y.; Meyerhoff, M. E. Paper-based plasticizerfree sodium ion-selective sensor with camera phone as a detector. Chem. Commun. 2015, 51 (82), 15176−15179. (18) Wang, X.; Zhang, Q.; Nam, C.; Hickner, M.; Mahoney, M.; Meyerhoff, M. E. An ionophore-based anion-selective optode printed on cellulose paper. Angew. Chem., Int. Ed. 2017, 56 (39), 11826− 11830. (19) Zhai, J. Y.; Xie, X. J.; Bakker, E. Ionophore-based ion-exchange emulsions as novel class of complexometric titration reagents. Chem. Commun. 2014, 50 (84), 12659−12661. (20) Zhai, J. Y.; Xie, X. J.; Cherubini, T.; Bakker, E. Ionophore-based titrimetric detection of alkali metal ions in serum. Acs Sens 2017, 2 (4), 606−612. (21) Xie, X. J.; Gutierrez, A.; Trofimov, V.; Szilagyi, I.; Soldati, T.; Bakker, E. Charged solvatochromic dyes as signal transducers in pH independent fluorescent and colorimetric ion selective nanosensors. Anal. Chem. 2015, 87 (19), 9954−9959. (22) Xie, X. J.; Zhai, J. Y.; Bakker, E. Potentiometric response from ion-selective nanospheres with voltage-sensitive dyes. J. Am. Chem. Soc. 2014, 136 (47), 16465−16468.

(23) Xie, X. J.; Zhai, J. Y.; Bakker, E. pH independent nano-optode sensors based on exhaustive ion-selective nanospheres. Anal. Chem. 2014, 86 (6), 2853−2856. (24) Xie, L. X.; Qin, Y.; Chen, H. Y. Polymeric optodes based on upconverting nanorods for fluorescent measurements of pH and metal ions in blood samples. Anal. Chem. 2012, 84 (4), 1969−1974. (25) Xie, L. X.; Qin, Y.; Chen, H. Y. Direct fluorescent measurement of blood potassium with polymeric optical sensors based on upconverting nanomaterials. Anal. Chem. 2013, 85 (5), 2617−2622. (26) DeJong, S. A.; Lu, Z. Y.; Cassidy, B. M.; O’Brien, W. L.; Morgan, S. L.; Myrick, M. L. Detection limits for blood on four fabric types using infrared diffuse reflection spectroscopy in mid- and nearinfraredspectral windows. Anal. Chem. 2015, 87 (17), 8740−8747. (27) Mistlberger, G.; Crespo, G. A.; Bakker, E. Ionophore-based optical sensors. Annu. Rev. Anal. Chem. 2014, 7, 483−512. (28) Xie, X. J.; Mistlberger, G.; Bakker, E. Ultrasmall fluorescent ionexchanging nanospheres containing selective ionophores. Anal. Chem. 2013, 85 (20), 9932−9938. (29) Schneider, B.; Zwickl, T.; Federer, B.; Pretsch, E.; Lindner, E. Spectropotentiometry: a new method for in situ imaging of concentration profiles in ion-selective membranes with simultaneous recording of potential-time transients. Anal. Chem. 1996, 68, 4342− 4350. (30) Gyurcsanyi, R. E.; Lindner, E. Spectroscopic method for the determination of the ionic site concentration in solvent polymeric membranes and membrane plasticizers. Anal. Chem. 2002, 74, 4060− 4068. (31) Heng, L. Y.; Toth, K.; Hall, E. A. H. Ion-transport and diffusion coefficients of non-plasticized methacrylic-acrylic ion-selective membranes. Talanta 2004, 63, 73−87. (32) Song, G. J.; Sun, R. F.; Du, J. Q.; Chen, M. W.; Tian, Y. Q. A highly selective, colorimetric, and environment-sensitive optical potassium ion sensor. Chem. Commun. 2017, 53 (41), 5602−5605. (33) Barrett, K.; Brooks, H.; Boitano, S.; Barman, S. Ganong’s Review of Medical Physiology, 23 ed.; McGraw-Hill Companiesm 2010; p 727.

E

DOI: 10.1021/acssensors.7b00614 ACS Sens. XXXX, XXX, XXX−XXX