A simple electrochemical detection of atorvastatin based on disposable screen-printed carbon electrodes modified by molecularly imprinted polymer: Experiment and simulation

Molecularly imprinted composite-based biosensor for the determination of SARS-CoV-2 nucleocapsid protein

This article aims to present a comparative study of three polypyrrole-based molecularly imprinted polymer (MIP) systems for the detection of the recombinant severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleocapsid protein (rN). The rN is known for its relatively low propensity to mutate compared to other SARS-CoV-2 antigens. The aforementioned systems include screen-printed carbon electrodes (SPCE) modified with gold nanostructures (MIP1), platinum nanostructures (MIP2), and the unmodified SPCE (MIP3), which was used for control. Pulsed amperometric detection (PAD) was employed as the detection technique, offering the advantage of label-free detection without the need for an additional redox probe. Calibration curves were constructed using the obtained data to evaluate the response of each system. Non-imprinted systems were also tested in parallel to evaluate the contribution of non-specific binding and assess the affinity sensor's efficiency. The analysis of calibration curves revealed that the AuNS-based MIP1 system exhibited the lowest contribution of non-specific binding and displayed a better fit with the chosen fitting model compared to the other systems. Further analysis of this system included determining the limit of detection (LOD) (51.2 ± 2.8 pg/mL), the limit of quantification (LOQ) (153.9 ± 8.3 pg/mL), and a specificity test using a recombinant receptor-binding domain of SARS-CoV-2 spike protein as a control. Based on the results, the AuNS-based MIP1 system demonstrated high specificity and sensitivity for the label-free detection of SARS-CoV-2 nucleocapsid protein. The utilization of PAD without the need for additional redox probes makes this sensing system convenient and valuable for rapid and accurate virus detection.

Analysis of atorvastatin in environmental waters: Validation of an electrochemical molecularly imprinted polymer sensor with application of life cycle assessment

The widespread presence of pharmaceuticals in wastewater effluents after treatment stands as a significant challenge faced in the field of wastewater management and public health. Governments and the scientific community have worked to meet this urgent need for effective solutions. Nevertheless, the development of detection strategies for pharmaceutical monitorization capable of delivering rapid, on-site, and sensitive responses remains an ongoing necessity. In this work, the performance of a previously developed molecularly imprinted polymer (MIP) based electrochemical sensor for detecting atorvastatin (ATV) in wastewater effluents and surface waters is presented. A simple preconcentration method followed by electrochemical measurements by differential pulse voltammetry (DPV) in 0.1 M phosphate buffer (pH = 7), was implemented. The analytical results were validated with those obtained on a set of 16 water samples by ultra-high performance liquid chromatography coupled to tandem mass spectrometry (UHPLC-MS/MS). Additionally, a life cycle assessment (LCA) was conducted to compare the environmental impact of both methodologies. The results obtained demonstrated that ATV detection using MIP-sensor was reliable when compared to the results found by UHPLC-MS/MS presenting a robust linear correlation coefficient of 0.843. The LCA results show that the novel MIP-sensor technique has lower associated environmental impacts than UHPLC-MS/MS, when the current analytical protocol for pharmaceuticals detection is applied. These findings highlight the potential of the developed MIP-sensor as an eco-friendly analytical tool for routine analysis and point-of-care monitoring of ATV in WWTP wastewater and surface water samples.

A Screen-Printed Voltammetric Sensor Modified with Electropolymerized Molecularly Imprinted Polymer (eMIP) to Determine Gallic Acid in Non-Alcoholic and Alcoholic Beverages

This paper presents a low-cost disposable sensor for gallic acid (GA) detection in non-alcoholic and alcoholic beverages using a screen-printed cell (SPC) whose working electrode (in graphite) is modified with electrosynthesized molecularly imprinted polypyrrole (eMIP). Our preliminary characterization of the electrochemical process shows that gallic acid (GA) undergoes irreversible oxidation at potentials of about +0.3 V. The peak potential is not affected by the presence of the eMIP film and alcohol percentages (ethanol) up to 20%. The GA determination is based on a differential pulse voltammetry (DPV) analysis leveraging its oxidation peak. The calibration data and the figures of merit of the analytical method (LOD, LOQ, and linear range) are calculated. To validate the feasibility of the sensor's application for the dosing of GA in real matrices, some non-alcoholic and alcoholic beverages are analyzed. The results are then compared with those reported in the literature and with the total polyphenol content determined by the Folin-Ciocalteu method. In all cases, the concentrations of GA align with those previously found in the literature for the beverages examined. Notably, the values are consistently lower than the total polyphenol content, demonstrating the sensor's selectivity in discriminating the target molecule from other polyphenols present.

New insight into interference-free and highly sensitive dopamine electroanalysis

Early diagnosis of Parkinson's disease and hyperprolactinemia based on electrochemical dopamine (DA) sensing appears as an efficient and promising practical diagnostic method. However, the coexistence of DA in real samples with ascorbic acid (AA) and uric acid (UA), which oxidize at potentials close to its own, prevents the accurate electrochemical DA sensing and therefore, hinders the effective diagnosis of these diseases. In this work, we successfully combined the electrostatic proprieties of GO, the electron transfer properties of an AuNPs@MWCNTs nanocomposite and the ability of thiol group of the amino acid l-cysteine to react chemically with carbonyl groups of UA, to develop a novel approach that enabled complete suppression of interference from AA and UA and hence, accurate DA electroanalysis in the conditions close to those of human blood serum. The chemical reaction between l-cysteine and UA was evidenced by monitoring the DPV responses of UA under different conditions. XRD, Raman spectroscopy, XPS and FE-SEM revealed the successful synthesis of GO and AuNPs@MWCNTs. The study of the electrode material (GO-AuNPs@MWCNTs) morphology via FE-SEM and HR-TEM showed that AuNPs@MWCNTs are distributed throughout the exfoliated GO layers. The fabricated sensor was calibrated in the concentration range of 0.5-5 μM, in the presence of the highest blood concentrations of AA and UA for healthy individuals. A linear relationship was observed and the LOD was found to be 1.31 nM (S/N = 3). Furthermore, the sensor showed good electron transfer kinetics, good repeatability and reproducibility, satisfactory long-term stability, and recoveries in human blood serum.

The Effect of Polymerization Techniques on the Creation of Molecularly Imprinted Polymer Sensors and Their Application on Pharmaceutical Compounds

Molecularly imprinted polymers (MIPs) have become more prevalent in fabricating sensor applications, particularly in medicine, pharmaceuticals, food quality monitoring, and the environment. The ease of their preparation, adaptability of templates, superior affinity and specificity, improved stability, and the possibility for downsizing are only a few benefits of these sensors. Moreover, from a medical perspective, monitoring therapeutic medications and determining pharmaceutical compounds in their pharmaceutical forms and biological systems is very important. Additionally, because medications are hazardous to the environment, effective, quick, and affordable determination in the surrounding environment is of major importance. Concerning a variety of performance criteria, including sensitivity, specificity, low detection limits, and affordability, MIP sensors outperform other published technologies for analyzing pharmaceutical drugs. MIP sensors have, therefore, been widely used as one of the most crucial techniques for analyzing pharmaceuticals. The first part of this review provides a detailed explanation of the many polymerization techniques that were employed to create high-performing MIP sensors. In the subsequent section of the review, the utilization of MIP-based sensors for quantifying the drugs in their pharmaceutical preparation, biological specimens, and environmental samples are covered in depth. Finally, a critical evaluation of the potential future research paths for MIP-based sensors clarifies the use of MIP in pharmaceutical fields.

3D printed graphite-based electrode coupled with batch injection analysis: An affordable high-throughput strategy for atorvastatin determination

This work integrated a lab-made conductive graphite/polylactic acid (Grp/PLA, 40:60% w/w) filament into a 3D pen to print customized electrodes (cylindrical design). Thermogravimetric analysis validated the incorporation of graphite into the PLA matrix, while Raman spectroscopy and scanning electron microscopy images indicated a graphitic structure with the presence of defects and highly porous, respectively. The electrochemical features of the 3D-printed Gpt/PLA electrode were systematically compared to that achieved using commercial carbon black/polylactic acid (CB/PLA, from Protopasta®) filament. The 3D printed Gpt/PLA electrode "in the native form" provided lower charge transfer resistance (Rct = 880 Ω) and a more kinetically favored reaction (K⁰ = 1.48 × 10^-3 cm s^-1) compared to the 3D printed CB/PLA electrode (chemically/electrochemically treated). Moreover, a method by batch injection analysis with amperometric detection (BIA-AD) was developed to determine atorvastatin (ATR) in pharmaceutical and water samples. Using the 3D printed Gpt/PLA electrode, a wider linear range (1-200 μmol L^-1), sensitivity (3-times higher), and lower detection limit (LOD = 0.13 μmol L^-1) were achieved when compared to the CB/PLA electrode. Repeatability studies (n = 15, RSD <7.3%) attested to the precision of the electrochemical measurements, and recovery percentages between 83 and 108% confirmed the accuracy of the method. Remarkably, this is the first time that ATR has been determined by the BIA-AD system and a low-cost 3D-printed device. This approach is promising to be implemented in research laboratories for quality control of pharmaceuticals and can also be useful for on-site environmental analysis.

Computational Modelling and Sustainable Synthesis of a Highly Selective Electrochemical MIP-Based Sensor for Citalopram Detection

A novel molecularly imprinted polymer (MIP) has been developed based on a simple and sustainable strategy for the selective determination of citalopram (CTL) using screen-printed carbon electrodes (SPCEs). The MIP layer was prepared by electrochemical in situ polymerization of the 3-amino-4 hydroxybenzoic acid (AHBA) functional monomer and CTL as a template molecule. To simulate the polymerization mixture and predict the most suitable ratio between the template and functional monomer, computational studies, namely molecular dynamics (MD) simulations, were carried out. During the experimental preparation process, essential parameters controlling the performance of the MIP sensor, including CTL:AHBA concentration, number of polymerization cycles, and square wave voltammetry (SWV) frequency were investigated and optimized. The electrochemical characteristics of the prepared MIP sensor were evaluated by both cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) techniques. Based on the optimal conditions, a linear electrochemical response of the sensor was obtained by SWV measurements from 0.1 to 1.25 µmol L-1 with a limit of detection (LOD) of 0.162 µmol L-1 (S/N = 3). Moreover, the MIP sensor revealed excellent CTL selectivity against very close analogues, as well as high imprinting factor of 22. Its applicability in spiked river water samples demonstrated its potential for adequate monitoring of CTL. This sensor offers a facile strategy to achieve portability while expressing a willingness to care for the environment.

Electropolymerized, Molecularly Imprinted Polymer on a Screen-Printed Electrode-A Simple, Fast, and Disposable Voltammetric Sensor for Trazodone

In recent years, analytical chemistry has been facing new challenges, particularly in developing low-cost, green, and easy-to-reproduce methods. In this work, a simple, reproducible, and low-cost electrochemical (voltammetric) molecularly imprinted polymer (MIP) sensor was designed specifically for the detection of trazodone (TZD). Trazodone (TZD) is an antidepressant drug consumed worldwide since the 1970s. By combining electropolymerization (surface imprinting) with screen-printed electrodes (SPCEs), the sensor is easy to prepare, is environmentally friendly (uses small amounts of reagents), and can be used for in situ analysis through integration with small, portable devices. The MIP was obtained using cyclic voltammetry (CV), using 4-aminobenzoic acid (4-ABA) as the functional monomer in the presence of TZF molecules in 0.1 M HCl. Non-imprinted control was also constructed in the absence of TZD. Both polymers were characterized using CV, and TZD detection was performed with DPV using the oxidation of TZD. The polymerization conditions were studied and optimized. Comparing the TZD signal for MIP/SPCE and NIP/SPCE, an imprinting factor of 71 was estimated, indicating successful imprinting of the TZD molecules within the polymeric matrix. The analytical response was linear in the range of 5–80 µM, and an LOD of 1.6 µM was estimated. Selectivity was evaluated by testing the sensor for molecules with a similar structure to TZD, and the ability of MIP/SPCE to selectively bind to TZD was proven. The sensor was applied to spiked tap water samples and human serum with good recoveries and allowed for a fast analysis (around 30 min).