Acetaminophen, Ascorbic acid and Uric acid (Figure 1
) play an important role in humans’ life. Acetaminophen (N-acetyl-p-aminophenol or paracetamol (PA)) is an antipyretic and analgesic drug commonly used against arthritis, headache, muscle aches, menstrual cramps and fevers [1
]. A high amount of PA can cause the accumulation of toxic metabolites, leading to severe and sometimes fatal hepatotoxicity and nephrotoxicity [2
]. Ascorbic acid (AA) is a vitamin commonly present in many biological systems and in multivitamin formulations. It is widely employed to provide an adequate dietary intake and as an antioxidant [3
]. Its excessive dose may cause headache, trouble sleeping, gastrointestinal discomfort and flushing of the skin [4
]. Uric acid (UA) is the primary product of purine metabolism [5
]. Continuous monitoring of UA in the body fluid is essential since its abnormal concentration levels lead to several diseases, such as hyperuricemia and gout [6
]. Other diseases, such as leukemia and pneumonia are also associated with enhanced urate levels.
Several analytical methods for individual or simultaneous determination of PA, AA and UA have been reported in the literature such as spectrofluorometry [7
], spectrophotometry [9
], chromatography [11
], and capillary zone electrophoresis [13
]. The problem is that these methods can be expensive and need complex procedures. For these reasons, the development of rapid, cheap and effective determination procedures is needed. One proposal to overcome this can be the development of electrochemical sensors [15
]. This kind of devices provide some advantages, such as, low detection limits, wide linear response range, good stability and reproducibility.
However, certain difficulties arise when the simultaneous determination of these three compounds is attempted. The oxidation peaks of PA, AA and UA are almost overlapping on traditional electrodes [16
], which make their simultaneous determination highly difficult. One solution to solve the main drawback is the use of methods based on modified electrodes, which have fascinated many researchers due to their simplicity, high sensitivity, and low cost. In addition, this strategy allows some improvement based on electrocatalysis, liberation from surface fouling and prevention of undesirable reactions competing kinetically with the desired electrode process [17
Modified electrodes [18
] can be prepared by several different techniques based on adsorbing, attaching specific molecules (e.g., peptides [19
] or complexing agents [20
]) to the surface by self-assembled monolayer [22
], coating and entrapment, e.g., is the form of conductive ink [23
]. The last strategy has become interesting for electrochemists in recent times, because this deliberate and controlled modification of the electrode surface can produce new surfaces with interesting properties employed for new devices and applications in electrochemistry.
Nature has developed and optimized an impressive variety of sensing systems used for navigation, spatial orientation, prey detection, object inspection, peer interaction, etc. which provide technologist with inspiring ideas for new concepts for sensors or improvements within the field [24
]. Illustrating examples in chemical sensing is the development of electronic noses (EN) and electronic tongues (ET), both sharing the concept of preferring a number of sensors (a sensor array) with broad selectivity pattern, instead of a single, highly selective sensor. The use of this number of receptors in a combinatorial way is what permits to the animal senses to be effective in detecting thousands of different compounds or situations. In the field of chemical analysis, the main bioinspired systems take after three mammal senses: smell, taste and sight. Therefore, there have been reported electronic noses (EN) [26
], eyes (EE) and tongues (ET) [27
]. From these principles, the EN, formed by an array of sensors with slightly different response to generic compounds has been used for analysis in the gas phase and stands out its closeness to artificial olfaction. In the case of EE, there are also interesting advances reported in the literature. An example is the development of a bioinspired electronic white cane for blind people using whiskers multiple sensor principle for short-range navigation and exploration [28
Similar to the EN is the ET that, according to IUPAC [29
], is defined as is a multisensor system, which consists of a number of low-selective sensors and uses advanced mathematical procedures for signal processing based on pattern recognition and/or multivariate data analysis. This analytical system applied to liquid analysis allows the generation of multidimensional information in combination with chemometric processing, which allows extracting the maximum chemical information from these complex data.
In this way, biomimetic systems, in opposition of classical approaches, use the combination of low selective and/or cross-responsive sensors to obtain rich and complementary analytical information. Next, this complex, multi-dimensional information needs to be processed with proper data treatment tools, which is accomplished with chemometrics. This coupling has been declared one of the ways of progress in developing new sensing schemes [30
]. There are different data processing tools depending on the final application needed. If this is a qualitative goal, PCA is a suitable linear visualization/pattern recognition method. This tool allows the reduction of the dimensionality of a multivariate problem and facilitates the visualization of different categories of the multivariate profiles by remarking similarities and differences between sample clusters. When the purpose is quantitative, different tools are available, given the numeric information is the end result. Some of these are Principal Component Regression (PCR), which departs from a first PCA transformation to build a multivariate regression, Partial Least Squares Regression (PLS), or Artificial Neural Networks (ANNs) [31
In the present work, an eight sensor integrated array of screen-printed electrodes has been developed in base of a multiple screen-printed carbon electrode (SPCE) platform. The voltammetric array, consisting of Graphite/SPCE-Ink, Prussian blue/SPCE-Ink, Cobalt (II) phthalocyanine/SPCE-Ink and Copper oxide (II)/SPCE-Ink was employed for the simultaneous determination of the three aforementioned compounds (PA, AA and UA) by using the Cyclic voltammetry (CV) technique. This represents an example of resolving a mixture where heavily interfering signals are generated and resolving its components is difficulted. In other words, it is shown how to detect simultaneously the different analytes in presence of their interferents, which redox signals overlap. For showing these aspects, firstly, the behavior of the sensors was evaluated separately for each compound; secondly, peak current responses showed that all sensors had differentiated response for the three oxidizable compounds of clinical interest. Finally, a response model was developed to determine mixtures of PA, AA and UA at the µmol·L−1 level.
2. Materials and Methods
2.1. Chemicals and Reagents
All solutions were made up using sterilized Milli-Q water (Millipore, Billerica, MA, USA). Cobalt (II) phthalocyanine (CoPc), Copper (II) oxide (CuO) nanopowder (<50 nm), Polypyrrole doped (PP) and Palladium, powder submicron 99.9+% (Pd), which were used as modifiers, were purchased from Sigma-Aldrich (St. Louis, MO, USA). Prussian blue was from Acros Organics (Geel, Belgium). The preparation of the ink composite was done using mesitylene and polystyrene, obtained from Sigma-Aldrich (St. Louis, MO, USA). Graphite powder (particle size < 50 µm) was received from BDH (BDH Laboratory Supplies, Poole, UK). Potassium chloride was purchased from Merck (Darmstadt, Germany).
Acetaminophen (PA), Ascorbic acid (AA), Uric acid (UA) and hydrogen peroxide (H2O2) solution were purchased from Sigma-Aldrich (St. Louis, MO, USA).
All the measurements were carried out using 50 mM phosphate buffer (PBS) solution and 0.1 M KCl solution at pH 7.
2.2. Electronic Tongue
The voltammetric ET was formed by an integrated array of eight screen-printed electrodes as working electrodes (8W110 Electrodes, ceramic substrate: 50 × 27 × 1 mm. and electric contacts composed of silver) from DropSens (Oviedo, Spain). The electrochemical cell consisted on: 8 working electrode (carbon, 2.95 mm diameter), auxiliary electrode (carbon) and pseudo reference electrode (Silver) [32
Electrochemical measurements were performed at room temperature (25 °C), using a portable Multi Potentiostat/Galvanostat µStat 8000 from DropSens controlled through its Dropview Multichannel 5.5 software package. A complete Cyclic voltammogram was recorded for each sample and for each electrode by cyclic the potential between −1.5 and +1.5 V with a step potential of 9 mV and a scan rate of 50 mV·s−1.
2.3. Modification of the Electrode Surface
The nanomaterial SPCE/modifier was produced in the form of a conductive ink-like composite. The corresponding modifier, graphite and polystyrene were thoroughly mixed with mesitylene for 2 h (Figure 2
) using a magnetic stirrer. After that, 2 min of sonication was performed in order to obtain a medium thick solution. The ink-like composite was dropped 5 µL onto the surface of a screen-printed carbon electrodes (SPCE) and dried at 40 °C for at least 1 h in order to remove the solvent. Once the sensor was prepared, the next step is an activation [33
] in order to enhance sensing performances of modified ink (Figure 3
displays the typical gain achieved after activation). Electrochemical activation consisted of 10 repetitive voltammetric cycles at 50 mV·s−1
between 1.5 and −1.5 V using 10 mM H2
in phosphate buffer (pH 7). After activation, electrodes were rinsed with deionized water and dried in air.
2.4. Characterization by Scanning Electron Microscopy
The morphological characterization of the modified screen-printed electrode was performed by Scanning Electron Microscopy (SEM). A scanning electron microscope with field emission gun (FEG-SEM) of Zeiss, model MERLIN SM0087 was used.
2.5. Sample Preparation
According to the European Pharmacopoeia [35
] the size of the data set needed for building the calibration is dependent on interfering properties and the number of analytes that needs to be handled in the model. In the majority of the cases, the size of the learning data set for calibration needs to be large when the interfering variations are acquired randomly. However, when the major interferences can be controlled they can be varied according to a statistical experimental design.
In this case, the second option was accomplished using a tilted factorial experimental design [36
(27 samples) for the train subset. This tilted model consisted of a factorial design with a 45° rotation in each axis. With this approach it is possible to avoid the repetition of numeric values. Meanwhile, the validation of the constructed model was done with an external test set (12 samples), these were distributed randomly within the experimental domain (0 to 500 µmol·L−1
) for each compound (Figure 4
Samples were prepared in buffer solution (50 mM phosphate buffer solution at pH 7 containing 0.1 M KCl). Fresh stock solutions of pharmaceutical compounds were prepared the same day of the measurements, in order to avoid/reduce the day-to-day variability.
2.6. Data Processing
The statistical treatment and data analysis were performed using routines developed by the authors using MATLAB R2017a (MathWorks, Natick, MA, USA); in particular, the functionalities “plsregress” from the Statistics and Machine Learning Toolbox, was the one employed for the response model; the web page Clustvis [37
] was the one used for PCA calculation; Sigmaplot (Systat Software Inc., San Jose, CA, USA) was used to graphically represent and analyze the results.
The presented work reported for a first time in our group the simultaneous voltammetric detection of Acetaminophen, Ascorbic acid and Uric acid combining a multi screen-printed electrode integrated array with advanced chemometrics. This study clearly illustrates one of the capabilities of the biomimetc systems, concretely, ET. The ET strategy allowed the possibility, first to differentiate the compounds, next, to determine and quantify simultaneously a substance in the presence of other ones with overlapping redox potentials.
The samples were analyzed by combining the Cyclic voltammetry (CV) technique for extracting the fingerprint of the individual substances and mixtures, coupled with chemometrics strategies, which permitted the resolution of the overlapping signal and its identification.
The use of Principal Component Analysis (PCA) as qualitative tool was useful to determine the capability of the sensors to distinguish the different compounds under study, while in a further purpose resolution and quantification of ternary mixtures was achieved employing Partial Least Squares Regression (PLS) model.
Therefore, this work demonstrates the advantages of screen-printed integrated electrochemical sensors for on-field analysis results in a promising methodology that could substitute the classical time-consuming, methods. Future works will try to detect these analytes in real pharmaceutical study case.