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Chapter 13

Electrochemical Biosensors for Real-Time Monitoring of Reactive Oxygen and Nitrogen Species Xiaobo Liu, Eduard Dumitrescu, and Silvana Andreescu* Department of Chemistry & Biomolecular Science, Clarkson University, 8 Clarkson Avenue, Potsdam, New York 13699-5810 *E-mail: [email protected]

Oxidative and nitrosative stress has been associated with the pathophysiology and development of many diseases. Reactive oxygen and nitrogen species (ROS/RNS) have important physiological functions and play a critical role in redox regulation and oxidative and nitrosative stress. Quantification of ROS/RNS is essential for studying oxidative and nitrosative stress. This chapter provides a critical overview of the various electrochemical biosensors which can be used for in vivo and in vitro measurements of four primary ROS/RNS species: superoxide radicals, nitric oxide, hydrogen peroxide and peroxynitrite. The design, operational principle and applications of these sensors are described. Challenges and opportunities for real-time measurements of ROS/RNS species in biological systems and the translational aspects of this technology from chemistry and engineering laboratories to biology and clinical settings are discussed.

Introduction Oxidative and nitrosative stress is involved in the development of aging (1), carcinogenesis (2), neurodegenerative disorders, such as Alzheimer’s disease and Parkinson’s disease (3, 4), and some other health-related conditions (5–8). Under this physiological state, the generation of reactive oxygen/nitrogen species (ROS/ RNS) overwhelms the limitation of the cells’ antioxidant defense system (9, 10). © 2015 American Chemical Society In Oxidative Stress: Diagnostics, Prevention, and Therapy Volume 2; Hepel, et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


The deleterious impact of these conditions are a consequence of the high level of stress. Severe damage, including necrosis and apoptosis, is observed in cells exposed to oxidative stress conditions. Excessive ROS/RNS has been considered a sign of oxidative stress, while minor levels of oxidative and nitrosative stress merely trigger protective effects in the cell (11). Figure 1 shows the primary ROS and RNS and the interconversions between these species. Among ROS/ RNS, hydroxyl (HO•), superoxide (O2•-) and nitric oxide (NO) have been the most extensively studied. Hydrogen peroxide (H2O2) and peroxynitrite (ONOO-) are not free radicals by themselves, but they can generate free radicals through various chemical reactions (12).

Figure 1. Primary reactive oxygen and nitrogen species (ROS/RNS) derived from the biological conversion of oxygen into superoxide ion (O2•-) and nitric oxide (NO). (Reprinted with permissions from Reference (13, 14). Reference (13) Copyright 2008 American Chemical Society; Reference (14) Copyright 2013 Nature Publishing Group.)

Quantification of ROS/RNS species is critical for the study and understanding of oxidative and nitrosative stress. Most ROS/RNS species are difficult to detect due to their high reactivity and short life time. Various analytical methods, such as UV/Vis spectroscopy, fluorescence spectrometry and gas or liquid chromatography have been developed to quantify these species (15). However, most of these methods involve indirect quantification routes, require long assay time and do not provide a concentration profile of ROS/RNS species at their production site. These drawbacks limit the usefulness of such measurements. Customized microelectrodes or microbiosensors have demonstrated potential for real-time measurements in biological cells and tissues with high sensitivity and spatial resolution (16). Such devices can facilitate the study of the mechanism of action and role of ROS/RNS. Specifically designed microbiosensors can be used 302 In Oxidative Stress: Diagnostics, Prevention, and Therapy Volume 2; Hepel, et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


in the biological and biomedical field to study how oxidative and nitrosative stress and ROS/RNS affect biological species and disease conditions. Compared to other transduction methods, electrochemical biosensors have attracted significant interest (17). Their advantages include: (1) high selectivity, (2) high sensitivity and low detection limit, (3) small size making these probes suitable for in vivo measurements and (4) inexpensiveness and relative ease of preparing and use (18). Electrochemical biosensors have been applied to quantify several essential biomolecules and ROS/RNS in vitro and in vivo (19–22). This chapter reviews the recent advances in electrochemical biosensors for the detection of ROS/RNS species and assessment of oxidative stress status, with a focus on the suitability and/or adaptability of these devices for real-time measurements in biological systems.

Electrochemical Sensors for the Detection of Nitric Oxide (NO) From its initial discovery as an endothelial-derived relaxing factor (23–25), nitric oxide (NO) attracted a great deal of attention in biology and medicine. Studies carried out in the last 25 years linked this small molecule with many physiological processes. NO readily diffuses into cells where it can react with molecular targets. Compared to other ROS/RNS, NO by itself is not highly reactive. However, NO can interact with O2•- and form highly reactive oxidants like peroxynitrite (ONOO−), nitrite (NO2−), and nitrate (NO3−) (26, 27) that can cause damage to DNA, enzymes, proteins, lipids, etc. (28, 29). It has been shown that the concentration of NO plays an important role in cardiovascular disease (30, 31), hypertension (32, 33), neuronal disease (34, 35), respiratory disease (36), cancer (37) and diabetes (38). Due to its relevance in biological processes, analytical methods which provide fast, sensitive, selective and real-time quantification of NO in biological samples are of great interest. Several challenges need to be considered when designing NO detection methodologies. First, the NO concentration is usually very low. While some studies estimated a concentration of NO at μM level (39), others showed that the NO concentration could be as low as 100 pM (40), which requires improved detection sensitivity. Secondly, it is well-known that the stability of NO in biological media is reduced. The half-life of NO in tissues is in the order of seconds and can be as low as 0.1 seconds (41). Therefore, NO detection methods should have a short response time and provide a rapid, real-time measurement. Several conventional methods have been used to measure NO, including the Griess assay (42), electron spin resonance (ESR) (43), quantum cascade laser (44), spectrophotometry (45, 46), chemiluminescence (47) and fluorescence (48, 49). The Griess assay is one of the common methods used to determine NO with a limit of detection of about 1 µM. The method, however, has limited applicability in complex biological matrices (50). Other methods such as quantum cascade laser based detection has been used for gaseous NO assessment (44), while chemiluminescence and spectrophotometric assays have been traditionally used 303 In Oxidative Stress: Diagnostics, Prevention, and Therapy Volume 2; Hepel, et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


for in vitro NO tests. These assays can also be adapted for measurements in cell cultures (45) and other biological samples (47). Electron spin resonance (43) and fluorescence with organic chromophores (51) allow investigation of NO concentration, but have limited temporal and spatial resolution and are not easy to use for quantitative analysis, especially in complex samples (52). Electrochemical methods using microelectrodes represent a powerful alternative to conventional methodologies for NO detection in biological systems. Electrochemistry is the only method that can provide real-time kinetic determination of NO at the production site and be adapted for in vivo measurements (52, 53). Conventional strategies to fabricate NO selective electrochemical microsensors developed over the last 20 years have been reviewed (52–60). While significant advances in electrode materials and design characteristics have facilitated development of sensitive electrochemical probes, most NO measurements in biological systems still make use of “classical strategies.” The first example of a NO selective sensor was reported in 1990 by K. Shibuki (61), who used the initial O2 sensor design reported by L. Clark (62), with a platinum wire working electrode and a thin gas-permeable rubber membrane. Electrode materials that are typically used to fabricate NO electrodes include platinum and its alloys (63, 64), gold (65) and carbon fibers (22, 66). Enhanced performances can be achieved on electrodes modified with different materials to increase surface area, catalytic properties and improve selectivity. For example, platinization improved the sensitivity of platinum electrodes by increasing the effective surface area (67). Deposition of platinum black particles on carbon fibers combined the properties of both materials, improving NO measurement capabilities (66, 68). The electrochemical oxidation of NO takes place at a high potential (> 0.8 V), where other electrochemically active species that are present in the biological system respond. Therefore, electrochemical NO sensors based on direct oxidation of NO may suffer from selectivity problems. To ensure selectivity, many NO electrodes are modified with a hydrophobic membrane permeable to NO, but impermeable to usual interfering compounds in biological matrix such as ascorbate, nitrite, uric acid, H2O2 and serotonin (59). A common approach is to use multiple sequential layers, each with a different property for blocking interferences (22). The commonly used membranes are Nafion (22, 63, 64, 69), o-phenylenediamine (o-PD) (22, 70) or m-phenylenediamine (m-PD) (63), poly-phenol and poly-eugenol (65, 70), resorcinol (63), chitosan (71) and aniline (70). A platinum-iridium alloy disk electrode modified with Nafion was used for in vivo NO detection in the prefrontal cortex and nucleus accumbens of freely moving rats (72). Interference studies confirmed the ability of Nafion to eliminate ascorbic acid signals. A similar microelectrode configuration was used for investigation of NO in the prefrontal cortex in an animal model of Schizophrenia in freely moving rats (69). We used single carbon fiber electrodes modified with Nafion and o-PD to determine zebrafish intestinal NO (22). The small dimension of carbon fibers (≈ 5 µm diameter) allowed a convenient implantation of the probe in the zebrafish intestine and enabled direct NO measurements with a detection limit of 1.43 nM. Figure 2 shows an example of NO measurements in the intestine of zebrafish using this electrode. 304 In Oxidative Stress: Diagnostics, Prevention, and Therapy Volume 2; Hepel, et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


Figure 2. Typical differential pulse voltammogram (DPV) response of intestinal NO in a 5 dpf zebrafish embryo using a single carbon fiber NO selective sensor (A). Images showing a single carbon fiber NO selective sensor (B) and the implantation of the sensor in the middle section of zebrafish intestine (C).

Other strategies to fabricate NO microelectrodes involve catalytic oxidation of NO via electron mediators deposited directly on the electrode surface or incorporated within a membrane. The mediator is used to enhance the electrochemical signal and to further minimize the interferences from electroactive species by selectively catalyzing the oxidation or reduction of the NO (55). On the other hand, their catalytic activity also increases the electrochemical signal of interfering substances that are oxidized at or below the holding potential. Hence, these types of NO sensors may also suffer from reduced selectivity (73). To provide selectivity, catalytic layers can be used in conjunction with permselective membrane. Conventional mediators used for NO sensors are metalloporphyrins (74–77) and metallophtalocyanines (78–80). Other materials, such as salen complexes (81) and Meldola blue (71) are also used for the same purpose. The interaction of nitric oxide with porphyrins and phtalocyanines was intensively studied (82–84). While many electrochemical sensors based on porphyrins have been reported, their sensing mechanism for NO is still largely unknown (53). Most studies attribute the enhanced measurement capabilities to their affinity for NO and resistance to degradation (55). It was shown that other mediators might have comparable efficiency. J. Njagi, et al. used Meldola blue, a recognized mediator for NADH and H2O2 oxidation (85), to develop a sensitive sensor for NO monitoring in brain slices (71). The platinum-based electrode modified with Meldola blue, o-PD and chitosan exhibited a low detection limit of 1 nM, a broad linear range and good stability when used for measurements in brain slices. Figure 3 shows a general schematic representation of a metal-based sensor modified with a mediator and one or more permselective membranes. 305 In Oxidative Stress: Diagnostics, Prevention, and Therapy Volume 2; Hepel, et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


Figure 3. General design for a metal-based sensor modified with a mediator and blocking layer(s).

Giving the high interest for NO measurements in biological media, it is expected that new directions will be explored in order to expand the applicability of these probes into other areas in biology and medicine. Electrode designs are continuously improving with the use of new materials and probe configurations. In the last five years, there has been an exponential increase in the use of nanomaterials to improve the sensitivity of NO probes. These include carbon based materials (86–88) such as graphene (89–93) and carbon nanotubes (94–97), as well as metal nanoparticles (98). These materials have good electrical conductivity, a high surface to volume ratio and electrocatalytic properties which make them suitable for electrochemistry applications (86, 87). A combination of multi-walled carbon nanotubes with cobalt porphyrin showed improved electrocatalytic activity towards NO oxidation (99). Wang, L. et al. developed a sensor using multi-walled carbon nanotubes functionalized with a polymeric film of ethylenediamine (EDA) (97). The sensor was used to monitor NO release from rat liver samples. Other sensors make use of the electrocatalytic properties of metal and metal oxide nanoparticles (98) such as nickel oxide (94) and ferric oxide (100). The use of gold nanoparticles incorporated in a sol-gel film (101) or deposited on a multi-walled carbon nanotubes film (102, 103) has also been reported. Electrochemical sensors offer an effective way for measuring NO in different biological samples. Figure 2 showed an example of measurement in zebrafish embryo. Figure 4 shows an example of electrochemical profiling of NO in cortical and hypocampal areas of the brain. This work demonstrated the potential of NO microelectrodes for studying NO release in diverse biological systems (104). Although many NO probes have been developed and some are commercially available, their implementation as routine measurement devices in biological and biomedical settings and in clinical diagnosis has not been fully realized. This might be due to problems related to electrode passivation, difficulties in calibration, cross-reactivity with other reactive species and biocompatibility of the probes. These issues, among with other translational aspects, will be discussed in the last section of this chapter. 306 In Oxidative Stress: Diagnostics, Prevention, and Therapy Volume 2; Hepel, et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


Figure 4. Electrochemical profiling of NO in cortical and hypocampal areas in different areas of the brain, showing penetration and monitoring site. (Reprinted with permission from Reference (104). Copyright 2011 Elsevier Ireland Ltd.)

Electrochemical Detection of Hydrogen Peroxide (H2O2) H2O2 is an important molecule in molecular biology, pharmaceutical industry, biochemistry, food industry and clinical field (105). Quantification of H2O2 and understanding the mechanism of release are of particular importance in biomedical research (106). H2O2 is one of the most stable ROS. Moreover, H2O2 is also a side product of some biochemical reactions catalyzed by oxidase enzymes, such as glucose oxidase (GOx), alcohol oxidase (AlOx), lactate oxidase (LOx), urate oxidase (UOx), cholesterol oxidase (ChoOx), glutamate oxidase (GlOx), lysine oxidase (LyOx), etc. These features make the detection of H2O2 attractive in academic research and industrial applications. Conventional methods, including UV-Vis spectrophotometry (107, 108) and fluorescence (109–111) methods have been the most widely used for the detection of H2O2, but have limitations when applied to biological systems. In vivo monitoring and real-time measurements are hard to achieve by these methods. Alternatively, electrochemical sensors are suitable candidates and can provide direct in situ measurements. Due to its versatility, electrochemical detection of H2O2 has been widely investigated. H2O2 can be detected electrochemically at its oxidation potential, between ~ 0.6 to 0.8 V vs standard Ag/AgCl reference electrode. The preferred working 307 In Oxidative Stress: Diagnostics, Prevention, and Therapy Volume 2; Hepel, et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


electrode material is platinum. Monitoring H2O2 reduction is also possible, but this approach suffers from overlapping signals from molecular oxygen (112).

With appropriate modification on the electrode surface, the sensitivity, selectivity and detection limit of electrochemical H2O2 sensors can be significantly improved (113). The common electrode materials are electron mediators such as metal hexacyanoferrates (114), heme proteins (115) and transition metals and their oxides (116). With the rapid development of nanotechnology, incorporation of nanomaterials in the surface modification process is an emerging trend in the design of H2O2 sensors. Such examples include functionalized graphene/graphene oxide (117–119), silicon nanomaterials (120) and metal and metal oxide nanoparticles (117, 121–124). However, due to the large overpotential required for oxidation, where most other electroactive species (i.e., ascorbic acid, uric acid) are oxidized, direct measurement of H2O2 suffers from limited specificity (125). Thus, most sensors are functionalized with permselective membranes that allow passage of H2O2 while preventing the access of other molecules (126). These membranes eliminate interferences by controlling the pore dimensions. Different polymers, multilayers and mixed layers of varying dimensions, charges or polarities have been used to restrict the access of some electroactive interfering compounds present in the sample. The use of such membranes, however, may decrease the response time of the sensor by inducing diffusion limitations, e.g. increasing the time to establish an equilibrium of the diffusional mass transport (127). Permselective membranes are, in general, polymeric non-conductive films (127). Electropolymerized coatings have also been used and have shown reduced susceptibility to biofouling (128). Films obtained by electropolymerization include over-oxidized polypyrrole (129–131), polyphenylenediamine (132–135) and polyion complex layer (i.e., poly-L-lysine and poly-4-styrenesulfonate) (136). Although electropolymerized films show excellent permselectivity, they are relatively unstable when used for long periods of time and their performance tends to fail rapidly when they are operated at 37 °C (137). Several works have reported that the maintenance of high permselectivity with repeated use is difficult for electropolymerized films (138–140). Other types of membranes reject interferences through an electrostatic repulsion mechanism. A widely used approach is to use negatively charged membranes of sulfonate type (Nafion or Eastman Kodak AQ pefluorinatedionomer, a negatively charged polymer coating that can eliminate interferences from negatively charged species (141–143)), or cellulose acetate (144), which can eliminate interferences from acetaminophen, ascorbate and urate. Hamdi and collaborators (131) have shown that the selectivity of Pt electrodes coated with electrodeposited over-oxidized polypyrrole and polyphenylenediamine films display H2O2 selectivity relative to ascorbic acid of ≥130 and ≥240 respectively, and relative to dopamine of ≥100 and 80 respectively. By comparison, Nafion- and polyaniline-coated electrodes give inferior selectivity performance. Similarly, Hu et al (145) coated the electrode 308 In Oxidative Stress: Diagnostics, Prevention, and Therapy Volume 2; Hepel, et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


with layers of polypyrrole and Nafion, acting both as size and charge exclusion membranes. Brown and Lowry (146) have systematically investigated different coating procedures for depositing Nafion onto Pt microelectrodes and have found that the elimination of interference from ascorbic and uric acid was more effective by using a thermally annealing procedure involving 5 pre-coats and 2 subsequent dip-bake layers. This procedure was also successful in completely eliminating the response from the neurotransmitter dopamine and did not affect the permeability for oxygen. However, the sensitivity of the sensor for the detection of H2O2 also reduced after the deposition of membranes. In addition to chemical sensors based on direct oxidation or reduction of H2O2, other strategies involving proteins, in their wide majority heme proteins possessing peroxidase activity, have been developed. These devices have attained extraordinary levels of sensitivity with detection limits in the nM range, enabling measurements of the release of H2O2 by mitochrondria. A horseradish peroxidase (HRP)-based H2O2 sensor with the enzyme crosslinked in a polymer matrix was used to monitor H2O2 bursts from isolated mitochondria at an operating potential of 0 V vs standard Ag/AgCl reference electrode (147). Another example of measurements from isolated mitochondria is a sensor based on carbon–maghemite nanocompsites (124). A successful application of these sensors has been demonstrated for measurements of H2O2 released from hepatocytes (148). The accurate measurement of H2O2 released from alcohol-injured hepatocytes demonstrates the potential of these probes in biological and clinical fields. This experimental setup is illustrated in Figure 5.

Electrochemical Detection of Superoxide (O2•-) O2•- is a short-lived reactive oxygen intermediate resulting from the one-electron reduction of oxygen and one of the primary components of ROS. O2•- is one of the most abundant radicals produced in biological systems and the precursor of most other ROS species. Due to its central role as a major contributor to oxidative stress, the measurement of O2•- is of significant importance. However, detection of O2•- is complicated due to its very short lifetime (i.e., in the order of miliseconds), high diffusion rate from the production site and the very low and variable concentration level. Moreover, in aqueous solution, O2•- will undergo a fast disproportionation to H2O2. This disproportionation makes it particularly difficult to differentiate signals and biological effects between the two species. Conventional methods used to quantify O2•- in vitro include spectrometry (149), liquid chromatography-mass spectrometry (LC-MS) combined with electron paramagnetic resonance (EPR) (150), fluorescence (151) and EPR (152, 153). These methods can provide qualitative information, but they are not small enough to be used in situ at cell or tissue locations where suproxide is produced. Therefore, these methods do not provide a real-time concentration profile. Most biological studies to investigate O2•- are performed using ROS specific dyes. However, the specificity of these dyes has been questioned and such measurements have limited temporal and spatial resolution (154, 155). 309 In Oxidative Stress: Diagnostics, Prevention, and Therapy Volume 2; Hepel, et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


Figure 5. (A) PDMS covered sensing chip containing eight micropatterned Au electrodes (four in each working channel). (B) An image of a PEG−HRP polymerized Au electrode. (C) Microfluidic device for on-chip electrochemical experiments containing flow-through Ag/AgCl as reference (connected to the outlet), Pt wire as counter (in the inlet), and patterned Au as working electrodes. (Reprinted with permission from Reference (148). Copyright 2013 American Chemical Society.)

Electrochemistry is a powerful alternative that can provide rapid real-time measurements of ROS species in complex biological environments (19–21, 156, 157). Real-time measurements of the release kinetic of O2•- radicals can be conducted by using a cytochrome c biosensor (158). Two types of O2•biosensors have been reported in literature, based on either cytochrome c or superoxide dismutase (SOD) (159–162). The sensing strategies involve direct or biocatalytic oxidations at the electrode surface, typically mediated by redox proteins. Depending on the design, the electrode can be coated with permselective membranes, redox relays or redox hydrogels to promote the electron transfer. Sensors based on cytochrome c measure the reduction of the heme center of cytochrome c at the electrode surface by the O2•- radical. The reduced cytochrome c is then reoxidized at the electrode surface generating an anodic current which is correlated with the concentration of O2•-. To fabricate the biosensor, cytochrome c is electrically “wired” on the electrode surface. Electron transfer between the electrode and the redox protein, cytochrome c, is typically achieved on a gold wire via a packed layer of self-assembled monolayers (SAMs) (161, 163, 164). The detection principle is shown in Figure 6. Typically, short-chain 310 In Oxidative Stress: Diagnostics, Prevention, and Therapy Volume 2; Hepel, et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


thiols provide efficient electron transfer between cytochrome c and the electrode surface and are used in most configurations. However, short chain thiols are not effective agaist interferences. Electroactive interferences are significantly blocked by long-chain thiols used in SAM (161). Therefore, most cytochrome c-based sensors employ a mixed (long and short) SAM layer to achieve an efficient electron transfer and prevent interfering signals from the coexisting electroactive species. Other sensors are using multiple layers of cytochrome c immobilized between electroactive polymers. For example, a sensor fabricated by deposition of six cytochrome c/poly(aniline(sulfonic acid)) (PASA) layers on a gold electrode showed highest sensitivity among a series of sensors made of 2 to 15 layers (165). The reaction rate between the redox protein and the O2•- radicals is a determining factor in the sensitivity of cytochrome c-based biosensors. To increase the reaction rate, cytochrome c mutants prepared by site directed mutagenesis focusing on aminoacids near the heme edge were tested. The results indicated that the reaction rate, and therefore the sensitivity of the sensor, varies and can be modulated by using mutant forms of cytochrome c (166).

Figure 6. Design and sensing principle of cytochrome c-based O2•- biosensors based on self-assemble monolayer (SAM). While many configurations of cytochrome c biosensors have been developed, few applications of these sensors to measure O2•- production in ‘real’ biological systems have been reported. Scheller and colleagues used a SAM-cytochrome c biosensor to determine the level of O2•- in the gastrocnemius muscle of a rat under artificially induced ischemic condition (167, 168). Our group utilized a cytochrome c biosensor prepared from mixed thiols to determine O2•- radicals production from rat brain slice during ischemia (158). Figure 7 shows a typical current-time response of the biosensor showing continuous monitoring of O2•- in mouse hippocampal brain slice exposed to simulated ischemic conditions, created by exposing the slice to hypoglycemic, acidic and hypoxic conditions (glucose was lowered to 2 mM and the cell was bubbled with 15 % CO2 and 1% oxygen). These sensors also can be used to study cellular mechanisms involved during 311 In Oxidative Stress: Diagnostics, Prevention, and Therapy Volume 2; Hepel, et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


mitochondrial O2•- generation (169) and they enable such measurements at single cell level. Rahman and colleagues used a conducting polymer to immobilize cytochrome c and lipid molecules to stabilize the catalytic activity of the heme center. This sensor was utilized to measure O2•- in rat brain (170).

Figure 7. Real-time amperometric measurements of O2•- production in a brain slice model of cerebral ischemia. (Reprinted with permission from Reference (158). Copyright 2012 Elsevier Inc.) O2•- sensors based on SOD involve the dismutation of the O2•- radical to O2 and H2O2 catalyzed by SOD through a two electron transfer process. Several generations of this type of sensors have been designed (Figure 8). In the first generation, the enzymatically produced H2O2 is detected at the electrode surface at an applied potential corresponding to oxidation or reduction of H2O2. This type of sensors usually incorporates SOD immobilized on the electrode surface in a H2O2 permeable membrane (171, 172). This design has two main limitations which restrain the applicability for measurements in biological systems: (1) O2•- can undergo rapid spontaneous dismutation and (2) the high applied potential (> 0.5 V vs. Ag/AgCl) required for the oxidation of H2O2 will also oxidize other electroactive substances that are typically present in biological samples such as ascorbic acid, uric acid, etc. The use of H2O2-impermeable membranes (173), self-referencing sensors (174) and permselective membranes like poly-m-phenylenediamine (PPD) (175) are effective strategies to remove such interferences. The second generation of SOD-based (O2•-) biosensors is based on th use of electron transfer mediators (176) to enhance the electron transfer from SOD to the sensor surface. Immobilization of SOD on the electrode surface was achieved through SAM (177), sol-gel film (178) or through a genetically engineered cysteine (179, 180). Endo and colleagues have successfully used a SOD-based biosensor to measure tissue-O2•- radicals generated from the heart tissue of endotoxin administered Wistar Kyoto rat in a flow cell system (176). In another work, O2•- derived from zymosan treated macrophage cells was detected using a biosensor made of SOD/sodium alginate sol-gel film (178). The third generation of SOD sensors involve direct electron transfer between the redox 312 In Oxidative Stress: Diagnostics, Prevention, and Therapy Volume 2; Hepel, et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


active center of SOD and the electrode surface (181–183). A SOD modified gold electrode functioning as a third generation O2•- biosensor with the SOD immobilized via a SAM of cysteine allowed monitoring of both the oxidation of (O2•-) to O2 at -0.2 V and its reduction to H2O2 at 0.3 V in the concentration range from 13 to 130 mM/min with a detection limit of 6 nM/min (182). A miniaturized probe based on this strategy was fabricated on a carbon fiber functionalized with gold nanoparticles (181), demonstrating potential for miniaturization.

Figure 8. Sensing principle and evolvement of SOD-based O2•- biosensors. In addition to sensors based on biological receptors, the use of biomimetic materials that mimic SOD or cytochrome c activity are gaining increasing acceptance. For example, a polymeric iron porphyrin complex which mimics cytochrome c activity used as a biomimetic sensing material enabled sensitive detection of O2•-. The amperometric response was monitored at a potential of 0.5 V and showed a linear relationship with the O2•- concentration. Coordination of an imidazole ligand to the iron porphyrin complex enhanced selectivity against H2O2 (184, 185). Fujita and colleagues have applied a sensor coated with a polymeric porphyrin complex to measure O2•- in the right atria of endotoxemic rats generated in vivo (186). More advanced applications of O2•- sensors were demonstrated for single living cell analysis (13). Bare carbon and/or platinized carbon electrode have been used to determine ROS/RNS induced by physical stress in a single fibroblast (187–189), mitochondria (147) and in different types of macrophage (68, 190). Figure 9 shows an example of a single cell measurement conducted by Amatore and colleagues (191).

Electrochemical Detection of Peroxynitrite (ONOO-) ONOO- is the product of the reaction between O2•- and NO (192, 193) (Figure 1). ONOO- is highly active and has a short half-life time under physiological conditions. Peroxynitrite has been involved in several pathological conditions such as Parkinson’s disease (194), proteins and DNA damage (195), fatty liver disease (196) and acute ischemia-reperfusion injury (197), due to its nitration effect. Conventional methologies to study the role of ONOO- in biological systems involve fluorescence (198–200) and bioluminescence (201) probes. These methods provide a visual distribution of ONOO- in cells and tissues (202). However, they generally lack specificity and are unable to provide real-time quantitative assessment (48). 313 In Oxidative Stress: Diagnostics, Prevention, and Therapy Volume 2; Hepel, et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


Figure 9. Optical microscopic view and schematic side view showing a human fibroblast in a Petri dish and the positioning of a microelectrode (black shadow on right) which constitute together a semiartificial synapse. A glass micropipette (white shadow on left) was used to trigger the oxidative stress response. (Reprinted with permission from Reference (191). Copyright 2001 WILEY-VCH.)

Few publications reported the development of electrochemical sensors for the detection of ONOO-. Most sensors are based on the use of chemically modified electrodes containing catalytic materials. Manganese phthalocyanine (203, 204) and manganese porphyrin (205) are commonly used as electrochemical mediators in these sensor designs. A sensor based on manganese-[poly-2,5-di-(2-thienyl)-1H-pyrrole)-1-(p-benzoicacid)] has been used to monitor ONOO- produced from phorbolmyristate acetate (PMA)-stimulated YPEN-1 glioma cells (206). A poly(cyanocobalamin) modified sensor provided suitable sensitivity and selectivity for the detectin of ONOO(207). More recently, cobalt phthalocyanine tetracarboxylic acid modified reduced graphene oxide was used as en electrocatalyst for the detection of ONOOand H2O2 demonstrating very low detection limits of 1.7 nM for ONOO- and 60 μM for H2O2 (208). 314 In Oxidative Stress: Diagnostics, Prevention, and Therapy Volume 2; Hepel, et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


Figure 10. Example of simultaneous detection of NO and ONOO− by two amperometric measurements at +0.8 and −0.1 V vs Ag/AgCl using a multiplex array. (Reprinted with permission from Reference (209). Copyright 2011 Royal Society of Chemistry.) While highly sensitive, these platforms suffer from reduced selectivity from the reduction of molecular oxygen or the oxidation of H2O2 and other electroactive analytes. Amatore and colleagues used a platinized carbon-fiber microelectrode to perform direct measurement of ONOO- in a single cell (191). A manganese phthalocyanine modified carbon fiber microelectrode has also been used to quantify ONOO- at single cell level (203).

Miniaturized and Multiplexed Platforms for ROS/RNS Sensing Simultaneous detection of multiple ROS/RNS is of great biological interest. Multidetection combined with real-time kinetic analysis would allow study of the cross-reactivity of individual species and their interrelated processes, including production, chemical transformation and degradation pathways. Such measurements could provide a more comprehensive understanding of the contribution of individual radicals and their effects in biological systems. An interesting on-chip multiplexed platform was reported by Quinton and collab. This platform allows simultaneous amperometric detection of NO and ONOO- released by cultured cells (209). The device includes a set of gold ultramicroelectrodes (UMEs) of 50 µm diameter, Ag/AgCl reference electrode and gold counter electrode. The NO electrodes were electrochemically modified with poly(eugenol) and poly(phenol) to provide selectivity for NO. The detection was performed amperometrically at 0.8 V vs Ag/AgCl in PBS. The ONOO− electrodes were uncoated gold electrodes used without further chemical modification of the surface. Detection was performed at -0.1 V vs Ag/AgCl to 315 In Oxidative Stress: Diagnostics, Prevention, and Therapy Volume 2; Hepel, et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


measure the reduction of ONOOH. The low applied potential eliminated most electroactive interferences. Figure 10 shows an example of dual NO and ONOO− measurement on the multiplexed microfabricated platform. The methodology was adapted by the same group to disposable UMEs (210) to increase sensitivity and allow detection of low concentrations of NO and ONOO− released by PMA (phorbol-12-myristate-13-acetate)-induced HL60 cells. These platforms were integrated within cell culture wells. Such devices have potential broad applicability in cell biology for studying real-time oxidative stress in cell cultures.

Translational Aspects: Measurement Challenges and Opportunities in Biological Systems The studies summarized in the previous sections demonstrate the potential of electrochemical sensors as viable tools for measuring the temporal and spatial accumulation of ROS/RNS. These devices provide important information regarding the role of oxidative stress and facilitate quantitation of these species in biological systems. Advantages of this method include real-time detection at low cost with high spatial resolution, high sensitivity, inexpensive equipment and minimum disturbance of the sample. However, while a large number of electrochemical sensors have been reported in literature for the detection of ROS/RNS, few of these sensors have been actually used for measurements in “real” biological samples. Most reported studies are performed under “ideal” laboratory conditions in standard solutions of laboratory generated radicals. Translation of this technology to biological and biomedial labs is still challenging and has been hampered by several limitations. Many of the reported sensors still require miniaturization, full functionality in the biological environment (e.g. cell cuture medium, tissues), high sensitivity and selectivity as well as biocompatibility with minimum perturbation of the environment. The most critical issues are: ■

The non-specific adsorption in biological environments remains problematic and requires engineering of more effective materials and electrode coatings to prevent biofouling. The complexity of the biological environment may compromise the integrity of the sensor surface, resulting in a decrease of response after in vivo measurements. This decrease introduces potential measurement errors (71, 170). The post calibration can decrease by up to 40 % of the pre-measurement signal (211). Electrode fouling due to the non-specific adsorption of proteins has been identified as the main cause for this decrease (212). While several approaches have been reported to address this issue with varying degree of success (e.g. electrode coating with natural proteins such as bovine serum albumin (BSA) or with antifouling polymers such as polyethylene glycol (PEG)), biofouling is still problematic (71). By carefully designing the sequence of layers and the type of membrane material, it is possible to achieve pre- and post-calibration with a 5% deviation in the post-measurement calibration (132). 316 In Oxidative Stress: Diagnostics, Prevention, and Therapy Volume 2; Hepel, et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.

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Elimination of interferences and overlapping signals from the many electroactive molecules requires better design of the electrode surface to incorporate separation membranes while still enabling detection of the target with high sensitivity. When this is not possible, pattern recognition techniques could be used to discriminate signals (213, 214). Achieve and demonstrate selectivity of measurements for ROS/RNS. The various types of ROS/RNS species coexisting in the system are short lived and highly reactive, being involved in dynamically changing reactions. Validation of sensor response with other methods or biological manipulation to selectively suppress, enhance or overexpress the level of these species should be performed to define the nature of the ROS/RNS and confirm the identity of the observed signals. For example, specificity of O2•- measurements should be confirmed with addition of SOD. Biological manipulations can also be made to enhance NO release. Oxidative and nitrosative stress take place simultaneously and species like O2•- and NO coexist. O2•- is converted to peroxynitrate in the presence of NO, which may lead to errors in the determination of individual species. Simultaneous detection of multiple ROS/RNS species should be addressed in the future to study the individual roles, interrelated processes, the kinetics of release and inactivation of the various reactive species. Needle like and planar disk shape electrodes enabling detection of multiple species have been developed as preliminary attempts to build an automated multi-target analytical platform (205, 215–217). Moreover, variation in the oxygen level, medium composition (e.g. some cell culture media may contain antioxidants), environmental conditions, temperature or pH may affect electrochemical signals. Careful evaluation of these variables and testing of interferences in real conditions is necessary before implementation of the device as an analytical tool for biological measurements. Many electrodes are still too bulky to be adapted to cell cultures or inserted in tissues. These probes, even if they showed excellent selectivity and sensitivity performance, still need further miniaturization. Nanostructured materials can be implemented in microsensor designs to enlarge the surface area and facilitate miniaturization.

Conclusion and Future Trends In summary, electrochemical biosensors have demonstrated potential for rapid, sensitive and real-time measurements of a variety of ROS/RNS species. Given the wide range of physiological effects and their critical roles in redox regulation and oxidative stress, the development of fast and accurate methods for the detection of these species is of clinical importance. A variety of such sensors have been designed and some have been applied to biological relevant situations. Sensitive, dynamic and real-time measurement capabilities with possibilities for multiplexing and single cell detection are major advantages of the electrochemical methods over conventional spectrophotometric and fluorescent assays. Unlike 317 In Oxidative Stress: Diagnostics, Prevention, and Therapy Volume 2; Hepel, et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


optical methods, these sensors do not require addition of reagents for the detection of radicals, as the electron transfer is achieved by electrical means. They can also directly quantify ROS/RNS radicals with spatial resolution and can also be adapted for in vivo measurements. The main challenge for the future is to design more robust sensors that can be used in the complex biological environment and to enable translation of this technology from the sensing laboratories into the biology and clinical fields. An active cooperation between electroanalytical chemists, biologists and clinicians is needed to ensure successful translation of this technology into the biomedical field. Future sensors require development of new materials and innovative engineering design of specific membranes with enhanced antifouling properties. There is also a need to improve selectivity and sensitivity of these probes. Recently developed nanopipettes and nanosensors (218–220) can potentially be adapted for real time investigations of ROS/RNS in single cells and neurons. Micro-electrochemical sensing arrays consisting of various functionalized UMEs and nanoscale sensors can also be developed in the future to obtain broader mechanistic understanding of the release characteristics of individual ROS/RNS species in biological systems and to determine their contribution to the development of disease. Improved electrochemical sensors with enhanced performance for O2•-, H2O2 and ONOO- could also be obtained by the development of genetically engineered redox proteins (221) to enhance the molecular specificity and the electron transfer rate at the electrode surface. Based on the growing interest in the study of oxidative stress and the growing evidence linking oxidative stress with many diseases, we envision that in the next few years we will see increased research activities in the development of customized microelectrodes designed for measurements in specific biological conditions and sample types. A broader adoption of these sensors by the biomedical community will be promoted through close collaborations beween analytical chemists, biologists, engineers and medical professionals.

Acknowledgments This work was supported by NIH # R21NS078738-01 and NSF grants # 1200180, 1336493 and 0954919. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the funding agencies.

References 1. 2. 3. 4.

Finkel, T.; Holbrook, N. J. Nature 2000, 408, 239–247. Klaunig, J. E.; Kamendulis, L. M.; Hocevar, B. A. Toxicol. Pathol. 2010, 38, 96–109. Jomova, K.; Vondrakova, D.; Lawson, M.; Valko, M. Mol. Cell. Biochem. 2010, 345, 91–104. Uttara, B.; Singh, A. V.; Zamboni, P.; Mahajan, R. T. Curr. Neuropharmacol. 2009, 7, 65–74. 318 In Oxidative Stress: Diagnostics, Prevention, and Therapy Volume 2; Hepel, et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.

5. 6. 7.


8. 9. 10. 11.

12. 13. 14. 15. 16. 17. 18. 19.

20. 21. 22. 23.

24. 25. 26. 27. 28.

Reuter, S.; Gupta, S. C.; Chaturvedi, M. M.; Aggarwal, B. B. Free Radical Biol. Med. 2010, 49, 1603–1616. Higashi, Y.; Noma, K.; Yoshizumi, M.; Kihara, Y. Circ. J. 2009, 73, 411–418. Palmieri, B.; Sblendorio, V. Eur. Rev. Med. Pharmacol. Sci. 2007, 11, 383–399. Palmieri, B.; Sblendorio, V. Eur. Rev. Med. Pharmacol. Sci. 2007, 11, 27–54. Halliwell, B. Lancet 1994, 344, 721–724. Rahman, K. Clin. Interv. Aging 2007, 2, 219–236. Xia, T.; Kovochich, M.; Brant, J.; Hotze, M.; Sempf, J.; Oberley, T.; Sioutas, C.; Yeh, J. I.; Wiesner, M. R.; Nel, A. E. Nano Lett. 2006, 6, 1794–1807. Gilgun-Sherki, Y.; Melamed, E.; Offen, D. Neuropharmacology. 2001, 40, 959–975. Amatore, C.; Arbault, S.; Guille, M.; Lemaitre, F. Chem. Rev. 2008, 108, 2585–2621. Imlay, J. A. Nat. Rev. Microbiol. 2013, 11, 443–454. Prior, R. L.; Wu, X.; Schaich, K. J. Agric. Food Chem. 2005, 53, 4290–4302. Özel, R. E.; Liu, X.; Alkasir, R. S. J.; Andreescu, S. TrAC, Trends Anal. Chem. 2014, 59, 112–120. Mello, L. D.; Kubota, L. T. Talanta 2007, 72, 335–348. Kissinger, P. T. Biosens. Bioelectron. 2005, 20, 2512–2516. Andreescu, S.; Gheorghiu, M.; Özel, R. E.; Wallace, K. N. Methodologies for Toxicity Monitoring and Nanotechnology Risk Assessment. Biotechnology and Nanotechnology Risk Assessment: Minding and Managing the Potential Threats around Us; ACS Symposium Series; Ripp, S., Henry, T. B., Eds.; American Chemical Society: Washington, DC, 2011; Vol. 1079, pp 141−180. Özel, R. E.; Wallace, K. N.; Andreescu, S. Anal. Chim. Acta 2011, 695, 89–95. Özel, R. E.; Ispas, C.; Ganesana, M.; Leiter, J. C.; Andreescu, S. Biosens. Bioelectron. 2014, 52, 397–402. Özel, R. E.; Hayat, A.; Wallace, K. N.; Andreescu, S. RSC Adv. 2013, 3, 15298–15309. Khan, M. T.; Furchgott, R. F. Additional Evidence that Endothelium-Drived Relaxing Facotr is Nitric Oxide. In Pharmacology: Proceedings of the Xth International Congress of Pharmacology (IUPHAR), Sydney, Australia, August 23−29, 1987;Rand, M. J., Raper, C., Eds.; Elsevier: Amsterdam, 1987. Ignarro, L. J.; Buga, G. M.; Wood, K. S.; Byrns, R. E.; Chaudhuri, G. Proc. Natl. Acad. Sci. U. S. A. 1987, 84, 9265–9269. Palmer, R. M. J.; Ferrige, A. G.; Moncada, S. Nature 1987, 327, 524–526. Beckman, J. S.; Koppenol, W. H. Am. J. Physiol.: Cell Physiol. 1996, 271, C1424–C1437. Kelm, M. Biochim. Biophys. Acta, Bioenerg. 1999, 1411, 273–289. Knott, A. B.; Bossy-Wetzel, E. Diabetes, Obes. Metab. 2010, 12, 126–133. 319 In Oxidative Stress: Diagnostics, Prevention, and Therapy Volume 2; Hepel, et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


29. Thomas, D. D.; Ridnour, L. A.; Isenberg, J. S.; Flores-Santana, W.; Switzer, C. H.; Donzelli, S.; Hussain, P.; Vecoli, C.; Paolocci, N.; Ambs, S.; Colton, C. A.; Harris, C. C.; Roberts, D. D.; Wink, D. A. Free Radical Biol. Med. 2008, 45, 18–31. 30. Flammer, A.; Lüscher, T. Pfluegers Arch. 2010, 459, 1005–1013. 31. Förstermann, U. Pfluegers Arch. 2010, 459, 923–939. 32. Wilcox, C. S. Am. J. Physiol.: Regul., Integr. Comp. Physiol. 2005, 289, R913–R35. 33. Kuklinska, A. M.; Mroczko, B.; Musial, W. J.; Usowicz-Szarynska, M.; Sawicki, R.; Borowska, H.; Knapp, M.; Szmitkowski, M. Int. Heart J. 2009, 50, 341–351. 34. Calabrese, V.; Mancuso, C.; Calvani, M.; Rizzarelli, E.; Butterfield, D. A.; Giuffrida Stella, A. M. Nat. Rev. Neurosci. 2007, 8, 766–775. 35. Steinert, J. R.; Chernova, T.; Forsythe, I. D. Neuroscientist 2010, 16, 435–452. 36. Baptist, A. P.; Khan, F. I.; Wang, Y.; Ager, J. J. Asthma 2008, 45, 670–674. 37. Mocellin, S.; Bronte, V.; Nitti, D. Med. Res. Rev. 2007, 27, 317–352. 38. Pitocco, D.; Zaccardi, F.; Di Stasio, E.; Romitelli, F.; Santini, S. A.; Zuppi, C.; Ghirlanda, G. Rev. Diabet. Stud. 2010, 7, 15–25. 39. Kirino, T. J. Cereb. Blood Flow Metab. 2002, 22, 1283–1296. 40. Hall, C. N.; Garthwaite, J. Nitric Oxide 2009, 21, 92–103. 41. Thomas, D. D.; Liu, X.; Kantrow, S. P.; Lancaster, J. R. Proc. Natl. Acad. Sci. U. S. A. 2001, 98, 355–360. 42. Green, L. C.; Wagner, D. A.; Glogowski, J.; Skipper, P. L.; Wishnok, J. S.; Tannenbaum, S. R. Anal. Biochem. 1982, 126, 131–138. 43. Xu, Y. C.; Cao, Y. L.; Guo, P.; Tao, Y.; Zhao, B. L. Phytopathology 2004, 94, 402–407. 44. Wojtas, J.; Bielecki, Z.; Stacewicz, T.; Mikolajczyk, J.; Medrzycki, R.; Rutecka, B. Acta Phys. Pol., A. 2011, 120, 794–797. 45. Ridnour, L. A.; Sim, J. E.; Hayward, M. A.; Wink, D. A.; Martin, S. M.; Buettner, G. R.; Spitz, D. R. Anal. Biochem. 2000, 281, 223–229. 46. Spasojević, I.; Batinić-Haberle, I.; Fridovich, I. Nitric Oxide 2000, 4, 526–533. 47. Hausladen, A.; Rafikov, R.; Angelo, M.; Singel, D. J.; Nudler, E.; Stamler, J. S. Proc. Natl. Acad. Sci. U. S. A. 2007, 104, 2157–2162. 48. McQuade, L. E.; Lippard, S. J. Curr. Opin. Chem. Biol. 2010, 14, 43–49. 49. Miao, R.; Mu, L.; Zhang, H.; Xu, H.; She, G.; Wang, P.; Shi, W. J. Mater. Chem. 2012, 22, 3348–3353. 50. Sun, J.; Zhang, X.; Broderick, M.; Fein, H. Sensors 2003, 3, 276–284. 51. Yang, Y.; Seidlits, S. K.; Adams, M. M.; Lynch, V. M.; Schmidt, C. E.; Anslyn, E. V.; Shear, J. B. J. Am. Chem. Soc. 2010, 132, 13114–13116. 52. Xu, T.; Scafa, N.; Xu, L.-P.; Su, L.; Li, C.; Zhou, S.; Liu, Y.; Zhang, X. Electroanalysis 2014, 26, 449–468. 53. Bedioui, F.; Griveau, S. Electroanalysis 2013, 25, 587–600. 54. Christodoulou, D.; Kudo, S.; Cook, J. A.; Krishna, M. C.; Miles, A.; Grisham, M. B.; Murugesan, R.; Ford, P. C.; Wink, D. A. Methods Enzymol. 1996, 268, 69–83. 320 In Oxidative Stress: Diagnostics, Prevention, and Therapy Volume 2; Hepel, et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


55. Privett, B. J.; Shin, J. H.; Schoenfisch, M. H. Chem. Soc. Rev. 2010, 39, 1925–1935. 56. Trouillon, R. Biol. Chem. 2013, 394, 17–33. 57. Zhang, X. Front. Biosci. 2004, 9, 3434–3446. 58. Bedioui, F.; Villeneuve, N. Electroanalysis 2003, 15, 5–18. 59. Bedioui, F.; Quinton, D.; Griveau, S.; Nyokong, T. Phys. Chem. Chem. Phys. 2010, 12, 9976–9988. 60. Pekarova, M.; Lojek, A.; Hrbac, J.; Kuchta, R.; Kadlec, J.; Kubala, L. Folia Biol. 2014, 60, 8–12. 61. Shibuki, K. Neurosci. Res. 1990, 9, 69–76. 62. Severinghaus, J.; Astrup, P. J. Clin. Monit. Comput. 1986, 2, 125–139. 63. Huang, C.; Brisbois, E.; Meyerhoff, M. Anal. Bioanal. Chem. 2011, 400, 1125–1135. 64. Wynne, A. M.; Reid, C. H.; Finnerty, N. J. J. Electroanal. Chem. 2014, 732, 110–116. 65. Quinton, D.; Girard, A.; Thi Kim, L. T.; Raimbault, V.; Griscom, L.; Razan, F.; Griveau, S.; Bedioui, F. Lab Chip. 2011, 11, 1342–1350. 66. Wang, Y.; Noël, J.-M.; Velmurugan, J.; Nogala, W.; Mirkin, M. V.; Lu, C.; Collignon, M. G.; Lemaître, F.; Amatore, C. Proc. Natl. Acad. Sci. U. S. A. 2012, 109, 11534–11539. 67. Lee, Y.; Yang, J.; Rudich, S. M.; Schreiner, R. J.; Meyerhoff, M. E. Anal. Chem. 2003, 76, 545–551. 68. Amatore, C.; Arbault, S.; Koh, A. C. W. Anal. Chem. 2010, 82, 1411–1419. 69. Finnerty, N. J.; Bolger, F. B.; Pålsson, E.; Lowry, J. P. ACS Chem. Neurosci. 2013, 4, 825–831. 70. Quinton, D.; Porras-Gutiérrez, A. G.; Gutiérrez-Granados, S.; Griveau, S.; Bedioui, F. ECS Trans. 2010, 25, 39–46. 71. Njagi, J.; Erlichman, J. S.; Aston, J. W.; Leiter, J. C.; Andreescu, S. Sens. Actuators, B 2010, 143, 673–680. 72. Finnerty, N. J.; O’Riordan, S. L.; Palsson, E; Lowry, J. P. J. Neurosci. Methods 2012, 209, 13–21. 73. Ferreira, N. R.; Ledo, A.; Frade, J. G.; Gerhardt, G. A.; Laranjinha, J.; Barbosa, R. M. Anal. Chim. Acta 2005, 535, 1–7. 74. Brunet, A.; Privat, C.; Stepien, O.; David-Dufilho, M.; Devynck, J.; Devynck, M. A. Analusis 2000, 28, 469–474. 75. Diab, N.; Oni, J.; Schulte, A.; Radtke, I.; Blöchl, A.; Schuhmann, W. Talanta 2003, 61, 43–51. 76. Biesaga, M.; Pyrzyńska, K.; Trojanowicz, M. Talanta 2000, 51, 209–224. 77. Oliveira, T. I. S.; dos Santos, V. N.; Lomonaco, D.; Correia, A. N.; Mazetto, S. E.; de Lima-Neto, P. J. Electrochem. Soc. 2013, 160, B113–B118. 78. Vilakazi, S. L.; Nyokong, T. J. Electroanal. Chem. 2001, 512, 56–63. 79. Griveau, S.; Dumézy, C.; Séguin, J.; Chabot, G. G.; Scherman, D.; Bedioui, F. Anal. Chem. 2006, 79, 1030–1033. 80. Nyokong, T.; Vilakazi, S. Talanta 2003, 61, 27–35. 81. Mao, L.; Yamamoto, K.; Zhou, W.; Jin, L. Electroanalysis 2000, 12, 72–77. 82. Nguyen, T. Q.; Escaño, M. C. S.; Kasai, H. J. Phys. Chem. C 2010, 114, 10017–10021. 321 In Oxidative Stress: Diagnostics, Prevention, and Therapy Volume 2; Hepel, et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


83. Vilakazi, S.; Nyokong, T. Polyhedron 2000, 19, 229–234. 84. Cárdenas-Jirón, G. I.; Gonzalez, C.; Benavides, J. J. Phys. Chem. C 2012, 116, 16979–16984. 85. Vasilescu, A.; Noguer, T.; Andreescu, S.; Calas-Blanchard, C.; Bala, C.; Marty, J.-L. Talanta 2003, 59, 751–765. 86. Pumera, M.; Ambrosi, A.; Bonanni, A.; Chng, E. L. K.; Poh, H. L. TrAC, Trends Anal. Chem. 2010, 29, 954–965. 87. Yáñez-Sedeño, P.; Pingarrón, J. M.; Riu, J.; Rius, F. X. TrAC, Trends Anal. Chem. 2010, 29, 939–953. 88. Chen, D.; Feng, H.; Li, J. Chem. Rev. 2012, 112, 6027–6053. 89. Gan, T.; Hu, S. Microchim. Acta 2011, 175, 1–19. 90. Li, W.; Geng, X.; Guo, Y.; Rong, J.; Gong, Y.; Wu, L.; Zhang, X. ACS Nano 2011, 5, 6955–6961. 91. Guo, C. X.; Ng, S. R.; Khoo, S. Y.; Zheng, X.; Chen, P.; Li, C. M. ACS Nano 2012, 6, 6944–6951. 92. Jiang, S.; Cheng, R.; Wang, X.; Xue, T.; Liu, Y.; Nel, A.; Huang, Y.; Duan, X. Nat. Commun. 2013, 4. 93. Liu, Y. M.; Punckt, C.; Pope, M. A.; Gelperin, A.; Aksay, I. A. ACS Appl. Mater. Interfaces 2013, 5, 12624–12630. 94. Wang, F.; Chen, X. W.; Chen, Z. L. Microchim. Acta 2011, 173, 65–72. 95. Zhao, L.; Zhu, S.; Zhou, J. Sens. Actuators, B 2012, 171, 563–571. 96. Santos, R. M.; Rodrigues, M. S.; Laranjinha, J.; Barbosa, R. M. Biosens. Bioelectron. 2013, 44, 152–159. 97. Wang, L.; Hu, P.; Deng, X.; Wang, F.; Chen, Z. Biosens. Bioelectron. 2013, 50, 57–61. 98. Luo, X.; Morrin, A.; Killard, A. J.; Smyth, M. R. Electroanalysis 2006, 18, 319–326. 99. Yan, Y.; Yao, P.; Mu, Q.; Wang, L.; Mu, J.; Li, X.; Kang, S.-Z. Appl. Surf. Sci. 2011, 258, 58–63. 100. Zhang, L.; Ni, Y.; Wang, X.; Zhao, G. Talanta 2010, 82, 196–201. 101. Kannan, P.; John, S. A. Electrochim. Acta 2010, 55, 3497–3503. 102. Deng, X.; Wang, F.; Chen, Z. Talanta 2010, 82, 1218–1224. 103. Maluta, J. R.; Canevari, T. C.; Machado, S. A. S. J. Solid State Electrochem. 2014, 18, 2497–2504. 104. Jo, A.; Do, H.; Jhon, G. J.; Suh, M.; Lee, Y. Neurosci. Lett. 2011, 498, 22–25. 105. Chen, W.; Cai, S.; Ren, Q.-Q.; Wen, W.; Zhao, Y.-D. Analyst 2012, 137, 49–58. 106. Nauseef, W. M. Biochim. Biophys. Acta, Gen. Subj. 2014, 1840, 757–767. 107. Sellers, R. M. Analyst 1980, 105, 950–954. 108. Eisenberg, G. Ind. Eng. Chem., Anal. Ed. 1943, 15, 327–328. 109. Lin, V. S.; Dickinson, B. C.; Chang, C. J. Methods Enzymol. 2013, 526, 19–43. 110. Liu, Y. A.; Liao, X. Curr. Org. Chem. 2013, 17, 654–669. 111. Oh, W.-K.; Jeong, Y. S.; Kim, S.; Jang, J. ACS Nano 2012, 6, 8516–8524. 112. Wilson, G. S.; Hu, Y. B. Chem. Rev. 2000, 100, 2693–2704. 113. Ispas, C.; Njagi, J.; Cates, M.; Andreescu, S. J. Electrochem. Soc. 2008, 155, F169–F176. 322 In Oxidative Stress: Diagnostics, Prevention, and Therapy Volume 2; Hepel, et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


114. Zhang, Y.; Sun, X.; Zhu, L.; Shen, H.; Jia, N. Electrochim. Acta 2011, 56, 1239–1245. 115. Zhang, Q.; Qiao, Y.; Zhang, L.; Wu, S.; Zhou, H.; Xu, J.; Song, X.-M. Electroanalysis 2011, 23, 900–906. 116. Meng, F.; Yan, X.; Liu, J.; Gu, J.; Zou, Z. Electrochim. Acta 2011, 56, 4657–4662. 117. Huang, K.-J.; Niu, D.-J.; Liu, X.; Wu, Z.-W.; Fan, Y.; Chang, Y.-F.; Wu, Y.-Y. Electrochim. Acta 2011, 56, 2947–2953. 118. Liu, M.; Liu, R.; Chen, W. Biosens. Bioelectron. 2013, 45, 206–212. 119. Xi, F.; Zhao, D.; Wang, X.; Chen, P. Electrochem. Commun. 2013, 26, 81–84. 120. Yan, Q.; Wang, Z.; Zhang, J.; Peng, H.; Chen, X.; Hou, H.; Liu, C. Electrochim. Acta 2012, 61, 148–153. 121. Koposova, E.; Liu, X.; Kisner, A.; Ermolenko, Y.; Shumilova, G.; Offenhäusser, A.; Mourzina, Y. Biosens. Bioelectron. 2014, 57, 54–58. 122. Lee, Y. J.; Park, J. Y.; Kim, Y.; Ko, J. W. Curr. Appl Phys. 2011, 11, 211–216. 123. Gaynor, J. D.; Karakoti, A. S.; Inerbaev, T.; Sanghavi, S.; Nachimuthu, P.; Shutthanandan, V.; Seal, S.; Thevuthasan, S. J. Mater. Chem. B 2013, 1, 3443–3450. 124. Magro, M.; Baratella, D.; Pianca, N.; Toninello, A.; Grancara, S.; Zboril, R.; Vianello, F. Sens. Actuators, B 2013, 176, 315–322. 125. Palmisano, F.; Zambonin, P. G.; Centonze, D. Fresenius’ J., Anal. Chem. 2000, 366, 586–601. 126. Vaidya, R.; Wilkins, E. Med. Eng. Phys. 1994, 16, 416–421. 127. Bridge, K. A.; Higson, S. P. J. Electroanalysis 2001, 13, 191–198. 128. Myler, S.; Eaton, S.; Higson, S. P. J. Anal. Chim. Acta 1997, 357, 55–61. 129. Walker, E.; Wang, J.; Hamdi, N.; Monbouquette, H. G.; Maidment, N. T. Analyst 2007, 132, 1107–1111. 130. Hamdi, N.; Wang, J. J.; Walker, E.; Maidment, N. T.; Monbouquette, H. G. J. Electroanal. Chem. 2006, 591, 33–40. 131. Hamdi, N.; Wang, J. J.; Monbouquette, H. G. J. Electroanal. Chem. 2005, 581, 258–264. 132. Killoran, S. J.; O’Neill, R. D. Electrochim. Acta 2008, 53, 7303–7012. 133. McAteer, K.; O’Neill, R. D. Analyst 1996, 121, 773–777. 134. Lowry, J. P.; Miele, M.; O’Neill, R. D.; Boutelle, M. G.; Fillenz, M. J. Neurosci. Methods 1998, 79, 65–74. 135. Clark, R. A.; Zerby, S. E.; Ewing, A. G. Electrochemistry in neuronal microenvironments; In Electroanalytical Chemistry; Bard, A. J., Rubinstein, I., Eds.; Marcel Dekker: New York, NY, 1998; Vol. 20, pp 227−294. 136. Mizutani, F.; Sato, Y.; Hirata, Y.; Sawaguchi, T.; Yabuki, S. Anal. Chim. Acta 1998, 364, 173–179. 137. Wilson, G. S.; Gifford, R. Biosens. Bioelectron. 2005, 20, 2388–2403. 138. Bartlett, P. N.; Cooper, J. M. J. Electroanal. Chem. 1993, 362, 1–12. 139. Cosnier, S. Electroanalysis 1997, 9, 894–902. 140. Christie, I. M.; Vadgama, P.; Loyd, S. Anal. Chim. Acta 1993, 274, 191–199. 141. Vaidya, R.; Atanasov, P.; Wilkins, E. Med. Eng. Phys. 1995, 17, 416–424. 323 In Oxidative Stress: Diagnostics, Prevention, and Therapy Volume 2; Hepel, et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


142. Burmeister, J. J.; Palmer, M.; Gerhardt, G. A. Biosens. Bioelectron. 2005, 20, 1772–1779. 143. Matsumoto, T.; Furusawa, M.; Fujiwara, H.; Matsumoto, Y.; Ito, N. Sens. Actuators, B 1998, 49, 68–72. 144. Zhang, F.; Chan, S. W.; Spanier, J. E.; Apak, E.; Jin, Q.; Robinson, R. D.; Herman, I. P. Appl. Phys. Lett. 2002, 80, 127. 145. Hu, Y. B.; Mitchell, K. M.; Albahadily, F. N.; Michaelis, E. K.; Wilson, G. S. Brain Res. 1994, 659, 117–125. 146. Brown, F. O.; Lowry, J. P. Analyst 2003, 128, 700–705. 147. Suraniti, E.; Ben-Amor, S.; Landry, P.; Rigoulet, M.; Fontaine, E.; Bottari, S.; Devin, A.; Sojic, N.; Mano, N.; Arbault, S. Angew. Chem., Int. Ed. 2014, 53, 6655–6658. 148. Matharu, Z.; Enomoto, J.; Revzin, A. Anal. Chem. 2013, 85, 932–939. 149. Bartosz, G. Clin. Chim. Acta 2006, 368, 53–76. 150. Chen, R.; Warden, J. T.; Stenken, J. A. Anal. Chem. 2004, 76, 4734–4740. 151. Dwyer, D. J.; Belenky, P. A.; Yang, J. H.; MacDonald, I. C.; Martell, J. D.; Takahashi, N.; Chan, C. T. Y.; Lobritz, M. A.; Braff, D.; Schwarz, E. G.; Ye, J. D.; Pati, M.; Vercruysse, M.; Ralifo, P. S.; Allison, K. R.; Khalil, A. S.; Ting, A. Y.; Walker, G. C.; Collins, J. J. Proc. Natl. Acad. Sci. U. S. A. 2014, 111, E2100–E2109. 152. Roubaud, V.; Sankarapandi, S.; Kuppusamy, P.; Tordo, P.; Zweier, J. L. Anal. Biochem. 1998, 257, 210–217. 153. Rosen, G. M.; Pou, S.; Ramos, C. L.; Cohen, M. S.; Britigan, B. E. FASEB J. 1995, 9, 200–209. 154. Kalyanaraman, B.; Darley-Usmar, V.; Davies, K. J. A.; Dennery, P. A.; Forman, H. J.; Grisham, M. B.; Mann, G. E.; Moore, K.; Roberts, L. J., II; Ischiropoulos, H. Free Radical Biol. Med. 2012, 52, 1–6. 155. Murrant, C. L.; Reid, M. B. Microsc. Res. Tech. 2001, 55, 236–248. 156. Özel, R. E.; Wallace, K. N.; Andreescu, S. Environ. Sci.: Nano 2014, 1, 27–36. 157. Chen, W.; Ren, Q. Q.; Yang, Q.; Wen, W.; Zhao, Y. D. Anal. Lett. 2012, 45, 156–167. 158. Ganesana, M.; Erlichman, J. S.; Andreescu, S. Free Radical Biol. Med. 2012, 53, 2240–2249. 159. Manning, P.; McNeil, C. J.; Cooper, J. M.; Hillhouse, E. W. Free Radical Biol. Med. 1998, 24, 1304–1309. 160. Gobi, K. V.; Mizutani, F. J. Electroanal. Chem. 2000, 484, 172–181. 161. Ge, B.; Lisdat, F. Anal. Chim. Acta 2002, 454, 53–64. 162. Tian, Y.; Mao, L.; Okajima, T.; Ohsaka, T. Anal. Chem. 2002, 74, 2428–2434. 163. Cortina-Puig, M.; Muñoz-Berbel, X.; Rouillon, R.; Calas-Blanchard, C.; Marty, J. L. Bioelectrochemistry 2009, 76, 76–80. 164. Beissenhirtz, M. K.; Scheller, F. W.; Lisdat, F. Electroanalysis 2003, 15, 1425–1435. 165. Beissenhirtz, M. K.; Scheller, F. W.; Lisdat, F. Anal. Chem. 2004, 76, 4665–4671. 324 In Oxidative Stress: Diagnostics, Prevention, and Therapy Volume 2; Hepel, et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


166. Wegerich, F.; Turano, P.; Allegrozzi, M.; Möhwald, H.; Lisdat, F. Anal. Chem. 2009, 81, 2976–2984. 167. Scheller, W.; Jin, W.; Ehrentreich-Förster, E.; Ge, B.; Lisdat, F.; Büttemeier, R.; Wollenberger, U.; Scheller, F. W. Electroanalysis 1999, 11, 703–706. 168. Büttemeyer, R.; Philipp, A. W.; Mall, J. W.; Ge, B.; Scheller, F. W.; Lisdat, F. Microsurgery 2002, 22, 108–113. 169. Henderson, J. R.; Swalwell, H.; Boulton, S.; Manning, P.; McNeil, C. J.; Birch-Machin, M. A. Free Radical Res. 2009, 43, 796–802. 170. Rahman, M. A.; Kothalam, A.; Choe, E. S.; Won, M. S.; Shim, Y. B. Anal. Chem. 2012, 84, 6654–6660. 171. Descroix, S.; Bedioui, F. Electroanalysis 2001, 13, 524–528. 172. Mesároš, Š.; Vaňková, Ž.; Grunfeld, S.; Mesárošová, A.; Malinski, T. Anal. Chim Acta 1998, 358, 27–33. 173. Song, M. I.; Bier, F. F.; Scheller, F. W. Bioelectrochem. Bioenerg. 1995, 38, 419–422. 174. Lvovich, V.; Scheeline, A. Anal. Chem. 1997, 69, 454–462. 175. Pernot, P.; Mothet, J. P.; Schuvailo, O.; Soldatkin, A.; Pollegioni, L.; Pilone, M.; Adeline, M. T.; Cespuglio, R.; Marinesco, S. Anal. Chem. 2008, 80, 1589–1597. 176. Endo, K.; Miyasaka, T.; Mochizuki, S.; Aoyagi, S.; Himi, N.; Asahara, H.; Tsujioka, K.; Sakai, K. Sens. Actuators, B 2002, 83, 30–34. 177. Tian, Y.; Mao, L.; Okajima, T.; Ohsaka, T. Biosens. Bioelectron. 2005, 21, 557–564. 178. Wang, X.; Han, M.; Bao, J.; Tu, W.; Dai, Z. Anal. Chim. Acta 2012, 717, 61–66. 179. Beissenhirtz, M. K.; Scheller, F. W.; Viezzoli, M. S.; Lisdat, F. Anal. Chem. 2005, 78, 928–935. 180. Kapp, A.; Beissenhirtz, M. K.; Geyer, F.; Scheller, F.; Viezzoli, M. S.; Lisdat, F. Electroanalysis 2006, 18, 1909–1915. 181. Tian, Y.; Mao, L. Q.; Okajima, T.; Ohsaka, T. Biosens. Bioelectron. 2005, 21, 557–564. 182. Ohsaka, T.; Tian, Y.; Shioda, M.; Kasahara, S.; Okajima, T. Chem. Commun. 2002, 990–991. 183. Tian, Y.; Ariga, T.; Takashima, N.; Okajima, T.; Mao, L. Q.; Ohsaka, T. Electrochem. Commun. 2004, 6, 609–614. 184. Yuasa, M.; Oyaizu, K.; Yamaguchi, A.; Ishikawa, M.; Eguchi, K.; Kobayashi, T.; Toyoda, Y.; Tsutsui, S. Polym. Adv. Technol. 2005, 16, 287–292. 185. Yuasa, M.; Oyaizu, K.; Yamaguchi, A.; Ishikawa, M.; Eguchi, K.; Kobayashi, T.; Toyoda, Y.; Tsutsui, S. Polym. Adv. Technol. 2005, 16, 616–621. 186. Fujita, M.; Tsuruta, R.; Kasaoka, S.; Fujimoto, K.; Tanaka, R.; Oda, Y.; Nanba, M.; Igarashi, M.; Yuasa, M.; Yoshikawa, T.; Maekawa, T. Free Radical Biol. Med. 2009, 47, 1039–1048. 187. Arbault, S.; Pantano, P.; Jankowski, J. A.; Vuillaume, M.; Amatore, C. Anal. Chem. 1995, 67, 3382–3390. 325 In Oxidative Stress: Diagnostics, Prevention, and Therapy Volume 2; Hepel, et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


188. Arbault, S.; Pantano, P.; Sojic, N.; Amatore, C.; Best-Belpomme, M.; Sarasin, A.; Vuillaume, M. Carcinogenesis 1997, 18, 569–574. 189. Arbault, S.; Sojic, N.; Bruce, D.; Amatore, C.; Sarasin, A.; Vuillaume, M. Carcinogenesis 2004, 25, 509–515. 190. Wang, Y.; Noël, J.-M.; Velmurugan, J.; Nogala, W.; Mirkin, M. V.; Lu, C.; Collignon, M. G.; Lemaître, F.; Amatore, C. Proc. Natl. Acad. Sci. U. S. A. 2012, 109, 11534–11539. 191. Amatore, C.; Arbault, S.; Bruce, D.; de Oliveira, P.; Erard, M.; Vuillaume, M. Chem. - Eur. J. 2001, 7, 4171–4179. 192. Szabo, C.; Ischiropoulos, H.; Radi, R. Nat. Rev. Drug Discovery 2007, 6, 662–680. 193. Pacher, P.; Beckman, J. S.; Liaudet, L. Physiol. Rev. 2007, 87, 315–424. 194. Mythri, R.; Harish, G.; Dubey, S.; Misra, K.; Srinivas Bharath, M. M. Mol. Cell. Biochem. 2011, 347, 135–143. 195. Ahmad, R.; Rasheed, Z.; Ahsan, H. Immunopharmacol. Immunotoxicol. 2009, 31, 388–396. 196. García-Ruiz, I.; Fernández-Moreira, D.; Solís-Muñoz, P.; RodríguezJuan, C.; Díaz-Sanjuán, T.; Muñoz-Yagüe, T.; Solís-Herruzo, J. A. J. Proteome Res. 2010, 9, 2450–2459. 197. Kim, J.; Seok, Y. M.; Jung, K. J.; Park, K. M. Am. J. Physiol-Renal. 2009, 297, F461–F470. 198. Yang, D.; Wang, H. L.; Sun, Z. N.; Chung, N. W.; Shen, J. G. J. Am. Chem. Soc. 2006, 128, 6004–6005. 199. Sun, Z. N.; Wang, H. L.; Liu, F. Q.; Chen, Y.; Tam, P. K. H.; Yang, D. Org. Lett. 2009, 11, 1887–1890. 200. Ueno, T.; Urano, Y.; Kojima, H.; Nagano, T. J. Am. Chem. Soc. 2006, 128, 10640–0641. 201. Sieracki, N. A.; Gantner, B. N.; Mao, M.; Horner, J. H.; Ye, R. D.; Malik, A. B.; Newcomb, M. E.; Bonini, M. G. Free Radical Biol. Med. 2013, 61, 40–50. 202. Lin, W.; Buccella, D.; Lippard, S. J. J. Am. Chem. Soc. 2013, 135, 13512–13520. 203. Xue, J.; Ying, X.; Chen, J.; Xian, Y.; Jin, L.; Jin, J. Anal. Chem. 2000, 72, 5313–5321. 204. Cortés, J. S.; Granados, S. G.; Ordaz, A. A.; Jiménez, J. A. L.; Griveau, S.; Bedioui, F. Electroanalysis 2007, 19, 61–64. 205. Kubant, R.; Malinski, C.; Burewicz, A.; Malinski, T. Electroanalysis 2006, 18, 410–416. 206. Koh, W. C. A.; Son, J. I.; Choe, E. S.; Shim, Y. B. Anal. Chem. 2010, 82, 10075–10082. 207. Wang, Y.; Chen, Z. Talanta 2010, 82, 534–539. 208. Hosu, S. I.; Wang, Q.; Vasilescu, A.; Peteu, S. F.; Raditoiu, V.; Railian, S.; Zaitsev, V.; Turcheniuk, K.; Wang, Q.; Li, M.; Boukherroub, R.; Szunerits, S. RSC Adv. 2015, 5, 1474–1484. 209. Quinton, D.; Girard, A.; Kim, L. T. T.; Raimbault, V.; Griscom, L.; Razan, F.; Griveaua, S.; Bedioui, F. Lab Chip 2011, 11, 1342–1350. 326 In Oxidative Stress: Diagnostics, Prevention, and Therapy Volume 2; Hepel, et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2015.


210. Kim, L. T. O. T.; Escriou, V.; Griveau, S.; Girard, A.; Griscom, L.; Razan, F.; Bedioui, F. Electrochim. Acta 2014, 140, 33–36. 211. Sardesai, N. P.; Ganesana, M.; Karimi, A.; Leiter, J. C.; Andreescu, S. Anal. Chem. 2015, 87, 2996–3003. 212. Behrend, C. E.; Cassim, S. M.; Pallone, M. J.; Daubenspeck, J. A.; Hartov, A.; Roberts, D. W.; Leiter, J. C. J. Neurosci. Methods 2009, 180, 278–289. 213. Sazonova, N.; Njagi, J. I.; Marchese, Z. S.; Ball, M. S.; Andreescu, S. Schuckers, S. Detection and Prediction of Concentrations of Neurotransmitters Using Voltammetry and Pattern Recognition. Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society; Minneapolis, MN, September 3−6, 2009; IEEE: 2009. 214. Stefan-van Staden, R. I.; Moldoveanu, I.; van Staden, J. F. J. Neurosci. Methods 2014, 229, 1–7. 215. Isik, S.; Berdondini, L.; Oni, J.; Blöchl, A.; Koudelka-Hep, M.; Schuhmann, W. Biosens. Bioelectron. 2005, 20, 1566–1572. 216. Chang, S. C.; Pereira-Rodrigues, N.; Henderson, J. R.; Cole, A.; Bedioui, F.; McNeil, C. J. Biosens. Bioelectron. 2005, 21, 917–922. 217. Isik, S.; Castillo, J.; Blöchl, A.; Csöregi, E.; Schuhmann, W. Bioelectrochemistry 2007, 70, 173–179. 218. Actis, P.; Maalouf, M. M.; Kim, H. J.; Lohith, A.; Vilozny, B.; Seger, R. A.; Pourmand, N. ACS Nano 2013, 8, 546–553. 219. Clausmeyer, J.; Actis, P.; López Córdoba, A.; Korchev, Y.; Schuhmann, W. Electrochem. Commun. 2014, 40, 28–30. 220. Schrlau, M. G.; Dun, N. J.; Bau, H. H. ACS Nano 2009, 3, 563–568. 221. Prabhulkar, S.; Tian, H.; Wang, X.; Zhu, J. J.; Li, C. Z. Antioxid. Redox Signaling 2012, 17, 1796–1822.

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