Applications and challenges of multi-way calibration in electrochemical analysis

Chemometrically assisted differential pulse voltammetry for simultaneous and interference-free quantification of gallic and caffeic acids

This article explores the application of chemometric tools including multivariate curve resolution with alternating least squares for the simultaneous determination of gallic and caffeic acids on the surface of a glassy carbon electrode without additional modification. Gallic and caffeic acids are primary polyphenols, the most abundant in red wines produced in Argentina, and are often used as quality markers for them. These polyphenols significantly contribute to the organoleptic properties of wines from this origin, but their electrochemical signals overlap significantly, making simultaneous quantification challenging without additional experiments such as electrode modification or alternative analytical techniques beyond differential pulse voltammetry. This study successfully quantified these compounds in complex mixtures by generating second-order data from differential pulse voltammetry experiments conducted at various potential steps and subsequently applying multivariate curve resolution with alternating least squares. The use of constraints during optimization prevented rotational ambiguities common in this modeling, leading to unique results in validation samples. The limits of detection (LOD) found for gallic and caffeic acids were 1.6 and 7.6 mg L-1, which are in excellent agreement with the expected concentrations of these compounds in red wines. The concentration ranges analyzed showed a linear dependency (between the LOD and 300 mg L-1) with the signals estimated by the model for both analytes. Advantages such as simplicity, low cost, and high speed, as well as not requiring electrode modification, combined with excellent results obtained for real samples, make it a promising alternative for polyphenol analysis in the wine industry.

Optimisation of electrochemical sensors based on molecularly imprinted polymers: from OFAT to machine learning

Molecularly imprinted polymers (MIPs) rely on synthetic engineered materials able to selectively bind and intimately recognise a target molecule through its size and functionalities. The way in which MIPs interact with their targets, and the magnitude of this interaction, is closely linked to the chemical properties derived during the polymerisation stages, which tailor them to their specific target. Hence, MIPs are in-deep studied in terms of their sensitivity and cross-reactivity, further being used for monitoring purposes of analytes in complex analytical samples. As MIPs are involved in sensor development within different approaches, a systematic optimisation and rational data-driven sensing is fundamental to obtaining a best-performant MIP sensor. In addition, the closer integration of MIPs in sensor development requires that the inner properties of the materials in terms of sensitivity and selectivity are maintained in the presence of competitive molecules, which focus is currently opened. Identifying computational models capable of predicting and reporting the best-performant configuration of electrochemical sensors based on MIPs is of immense importance. The application of chemometrics using design of experiments (DoE) is nowadays increasingly adopted during optimisation problems, which largely reduce the number of experimental trials. These approaches, together with the emergent machine learning (ML) tool in sensor data processing, represent the future trend in design and management of point-of-care configurations based on MIP sensing. This review provides an overview on the recent application of chemometrics tools in optimisation problems during development and analytical assessment of electrochemical sensors based on MIP receptors. A comprehensive discussion is first presented to cover the recent advancements on response surface methodologies (RSM) in optimisation studies of MIPs design. Therefore, the recent advent of machine learning in sensor data processing will be focused on MIPs development and analytical detection in sensors.

Ultrasensitive biosensing of thiram based on detection of the DNA damage induced by thiram: Application to investigation of protective effects of extra virgin olive oil against DNA damage

In this work, a novel electrochemical biosensor was fabricated based on modification of a glassy carbon electrode (GCE) with nafion-DNA/gold nanoparticles/poly-ethylenedioxy pyrrole/multi-walled carbon nanotubes-ionic liquid (NF-DNA/Au NPs/PEDOP/MWCNTs-IL/GCE) with the aim of amperometric detection of the DNA damage induced by thiram (TH). By incubation of the biosensor with the TH, the TH was intercalated within DNA, and the exposed DNA released negative charges at the surface of the biosensor which repelled the probe molecules and caused the amperometric response of the biosensor to be decreased. Protective effects of extra virgin olive oil (EVOO) on the DNA damage induced by the TH were investigated by recording amperometric responses of the biosensor in the presence of EVOO, and the results confirmed that the response of the biosensor didn't change to confirm the protective effects of the EVOO on preventing the DNA damage induced by the TH. A novel and sensitive electroanalytical method was developed for determination of the TH in two linear ranges including 1-6 pM and 7-10 pM based on amperometric detection of the DNA damage induced by the TH which gave a LOD of 0.31 pM. The developed methodology in this work was successful in detection of the DNA damage induced by TH, detection of protective effects of EVOO on preventing DNA damage and determination of the TH in real matrices.

Chemometrics-assisted electrochemical biosensing of cholesterol as the sole precursor of steroids by a novel electrochemical biosensor

This project was performed with the aims of increasing the sensitivity of differential pulse voltammetry (DPV) which itself is a sensitive electroanalytical technique, and also to compare the area under peak (univariate calibration), height of peak (univariate calibration) and whole of vector (multivariate calibration) for calibration purposes. These topics were investigated by fabrication of a novel electrochemical biosensor for determination of cholesterol (CHO). The procedure used in this project was based on the synthesis of molecularly imprinted polymers (MIPs) to the preconcentration of CHO and its biosensing by a rotating glassy carbon electrode (GCE) modified by co-immobilization of cholesterol oxidase (CO), cholesterol esterase (CE) and horseradish peroxidase (HP) onto multiwalled carbon nanotubes-ionic liquid (COCEHP/MWCNTs-IL/GCE). The results showed that the hydrodynamic DPV (HYDPV) was much more sensitive than DPV and using the area under peak for univariate calibration purposes was more suitable than height of peak. Adsorption at the electrode surface is an important trouble which affects the height and position of voltammetric peaks, but the area under peak is not affected by adsorption therefore, it can be more suitable for univariate calibration purposes. The biosensor response was also calibrated by chronoamperometry and the results confirmed that the HYDPV was more sensitive than chronoamperometry. The next attempt was based on recording the biosensor responses based on second-order HYDPV data and modeling of them (whole of vectors) by three-way calibration methods which showed the best performance among the tested methods for determination of CHO. The biosensor response was long-term stable, repeatable and reproducible which was successfully applied to the analysis of serum sample towards determination of CHO whose results were comparable with a reference method.

Sensitive and selective simultaneous biosensing of nandrolone and testosterone as two anabolic steroids by a novel biosensor assisted by second-order calibration

Recently, our research group have focused on an interesting project in which a novel dual template molecularly imprinted (DTMIP) biosensor was fabricated and assisted by second-order differential pulse voltammetric (DPV) data for simultaneous determination of nandrolone decanoate (ND) and testosterone decanoate (TS). An indium tin oxide (ITO) was modified with multiwalled carbon nanotubes-graphene-ionic liquid (MWCNT-Gr-IL) and then, the fullerene C₆₀ was casted onto the surface of MWCNT-Gr-IL/ITO and electrochemically reduced. Finally, DTMIPs were electrosynthesized by electropolymerization of 4-aminobenzoic acid (ABA) as monomer with ND and TS as template molecules to obtain the final structure of the biosensor (DTMIP/C₆₀/MWCNT-Gr-IL/ITO). Structure of the biosensor was electrochemically and microscopically characterized. The ND and TS generated two severely overlapped DPVs at the surface of the biosensor which forced us to assist the biosensor with three-way calibration by second-order DPV data to simultaneous determine them. Two second-order algorithms including multivariate curve resolution alternating least squares (MCR-ALS) and parallel factor analysis2 (PARAFAC2) were used to build second-order calibration models and evaluation of their performance in the analysis of synthetic samples showed more superiority of the MCR-ALS than PARAFC2 which motivated us to select PARAFC2 for the analysis of urine samples as real cases. Application of the biosensor assisted by PARAFC2 for the analysis of urine samples towards simultaneous determination of ND and TS was successful.

Simultaneous estimation of rates of DNA damage induced by three important chemotherapy drugs by a novel electrochemical biosensor assisted by chemometric multivariate calibration methods

In this work, a novel electrochemical biosensor assisted by multivariate calibration methods was developed for simultaneous estimation of rates of DNA damage induced by doxorubicin (DX), daunorubicin (DR) and idarubicin (ID), and also to simultaneous determination of the drugs. A glassy carbon electrode was efficiently modified and used as the biosensing platform. Binding and interactions of DX, DR and ID with DNA were modeled by molecular docking methods, and theoretical information was completed by experimental results. The methylene blue was able to intercalate within the DNA structure and by incubation of the biosensor with DX or DR or ID, the methylene blue was replaced by drug and therefore, the voltammetric signal of the biosensor was changed due to the exposed DNA and repelling the electrochemical probe molecules carrying negative charge. The DNA damage induced by each drug was individually monitored by differential pulse voltammetry and then, rates of DNA damage were calibrated and validated by mixture design and multivariate calibration methods. The developed multivariate calibration model constructed based on vectorization of the data was able to simultaneous detection of the rates of DNA damage induced by all the three drugs. The change in the biosensor response in the presence of the drugs was also modeled by multivariate calibration methods to simultaneous determination of the drugs.

Introducing an interesting and novel strategy based on exploiting first-order advantage from spectrofluorimetric data for monitoring three toxic metals in living cells

In this work, we did our best to develop a novel and interesting analytical method based on coupling of spectrofluorimetry with first-order multivariate calibration techniques for simultaneous determination of lead (Pd), zinc (Zn) and cadmium (Cd) in HeLa cells. To achieve this goal, quenching of the emission of graphene (GR) was individually investigated in the presence of Pb, Zn and Cd and then, according to the linear ranges obtained from individual calibration graphs, a multivariate calibration model was developed based on modeling of the quenching of the emission of GR in the presence of the mixtures of Pb, Zn and Cd. First-order multivariate calibration models were constructed by partial least squares (PLS), principal component regression (PCR), orthogonal signal correction-PLS (OSC-PLS), continuum power regression (CPR), robust continuum regression (RCR) and partial robust M-regression (PRM) and their performances were evaluated and statistically compared. Finally, the OSC-PLS was chosen as the best model with the best practical performance for analytical purposes.

Second-order electrochemical data generation to quantify carvacrol in oregano essential oils

A novel analytical method using voltammetric second-order modeling based on multivariate curve resolution-alternating least-square (MCR-ALS) is presented for the first time for the quantitation of carvacrol (CAR) in oregano essential oils (OEO). The second-order cyclic voltammetry data were generated on the basis that CAR shows a diffusional system. Thus, the scan rate (v) was used as a second instrumental mode and cyclic voltammograms at different v were acquired for a single sample, generating the second-order data. CAR determination was performed in presence of thymol, included as a potential interferent. Results demonstrated that MCR-ALS successfully exploited the second-order advantage and the recoveries were not statistically different than 100%. The limits of detection and quantitation were estimated using the MCR-ALS which were 6.27 × 10^-5°mol°L^-1°and 1.90 × 10^-4°mol L^-1, respectively. Finally, the developed methodology was implemented to quantify of CAR in OEO samples.

Resolving interactions of miglitol with normal and glycated human serum albumin by multivariate methods

This article reports results of one of our projects related to the investigation of interactions of miglitol (MIG) with normal human serum albumin (HSA) and glycated HSA (GHSA) with the help of recording spectroscopic and electrochemical data. The experimental data were analyzed by conventional and chemometric methods to extract useful information for comprehensive justifications of the interactions of the MIG with HSA and GHSA. Hard- and soft-modeling chemometric methods were used to extract quantitative and qualitative information. Then, molecular docking techniques were used to further investigation of the binding of the MIG with HSA and GHSA and the extracted results were compatible with those obtained by experimental methods. Finally, according to the binding of the BV with HSA and GHSA, second-order differential pulse voltammetric data were recorded and calibrated with three-way calibration methods for exploiting second-order advantage for determination of the GHSA in the presence of the HSA to develop a novel chemometrics assisted-electroanalytical method for diagnostic and monitoring of diabetic.

Simultaneous determination of methyl, ethyl, propyl, and butyl parabens in sweetener samples without any previous pretreatment using square wave voltammetry and multiway calibration

Parabens are compounds used as chemical preservatives in cosmetics, drugs, and food. Some can cause adverse effects on human health. In this study, a square wave voltammetric method using a glassy carbon electrode was developed for simultaneous determination of methyl, ethyl, propyl, and butyl parabens in sweeteners. To overcome the strong overlap of voltammetric signals caused by calibrated and uncalibrated constituents, unfolded partial least squares with residual bilinearization (U-PLS/RBL) was used. The U-PLS/RBL calibration model was constructed and evaluated using a validation set obtained using a Taguchi design. Satisfactory and unbiased results were obtained with a linear response in the range of 0.78-4.48 μmol L^-1 and recoveries from 82.64% to 121.77%. As far as the authors know, a voltammetric method that simultaneously determines four parabens in complex samples such as sweeteners without any previous pretreatment has not yet been reported in the literature.

Chemometrics in investigation of small molecule-biomacromolecule interactions: A review

Chemometrics is chemical discipline in which mathematical and statistical methods are coupled with chemical data to extract useful information which cannot be extracted by the use of conventional methods. When experimental techniques are assisted by chemometric methods, very interesting studies will be performed which enable us to obtain valuable information about the system under our study. Chemico-biological interactions are very useful studies which are performed to obtain information about binding of small molecules with biological macromolecules. Recently, these studies have been assisted by chemometric methods to perform advanced studies which can help us to have a deep insight to them. Literature survey showed us that multivariate analysis of the chemico-biological interactions is becoming popular and nowadays, chemometricians are using multivariate chemometric methods for resolving chemico-biological interactions. This article focuses on the works published in the literature to provide a background for those who are interested to work in this field and finally, the results will be discussed and concluded.

Chemometric modeling of the electrochemical data to investigate proline cis/trans isomeration effect on aggregation of Tau protein

Tau protein (Tau) is a proline-rich protein and in this work, we have developed a very interesting strategy based on combination of electrochemistry with chemometric methods to investigate proline cis/trans isomeration effect on the Tau aggregation. To achieve this goal, the proline residues at RTPPK motif have been replaced by alanine to generate RTPAK, RTAPK and RTAAK mutants of the Tau. Then, cyclic voltammetric (CV) responses of the Tau and RTPAK, RTAPK and RTAAK as its mutants in the presence of heparin (HEP) as an anionic inducing agent which could trigger aggregation of the Tau were recorded at physiological conditions every hour during 12 h. Therefore, 48 data sets of titrations were obtained which were handled by chemometric methods to extract useful information about aggregation of the Tau. The data were hard-modeled by EQUISPEC, SQUAD, REACTLAB and SPECFIT to extract useful quantitative information. Our results confirmed that the strength of the binding of the HEP with proteins was obeyed from Tau > RTPAK ~ RTAPK > RTAAK which confirmed that the aggregation of the proteins was obeyed from this order as well. Therefore, aggregation of the Tau is decreased by transforming Cis isomer to Trans even in the presence of an anionic inducing agent such as HEP which may have value for the treatment of Alzheimer's disease.

Exploring the potential of combining chemometric approaches to model non-linear multi-way data with quantitative purposes - A case study

Second-order based calibration methods have been widely investigated capitalizing on the inherent benefits of the data structure and the decomposition models, demonstrating that second-order advantage is a property that conspires to a high likelihood success in the resolution of systems of varying complexity. This work aims to demonstrate the applicability of a combined chemometric strategy to solve non-linear multivariate calibration systems in the presence of non-multilinear multi-way data. The determination of histamine by differential pulse voltammetry at different pH is presented as case study. The experimental system has the outstanding difficulty arisen from the large displacement along the potential axis by the pH, which was successfully overcome by implementation of the presented combined strategy. For data modeling, MCR-ALS, U-PLS/RBL and U-PCA/RBL-RBF were used. MCR-ALS allowed unraveling the non-linear behavior between the signal and the concentration, and extracting the underlying profiles of the constituent. Quantitative analysis was performed through the three models, and a comparative evaluation of the predictive performance was done. The best results were achieved with U-PCA/RBL-RBF (mean recovery = 101%) whereas, MCR-ALS yield the lowest mean recovery for all samples (70%).

Application of magnetic nanomaterials in electroanalytical methods: A review

Magnetic nanomaterials (MNMs) have gained high attention in different fields of studies due to their ferromagnetic/superparamagnetic properties and their low toxicity and high biocompatibility. MNMs contain magnetic elements such as iron and nickel in metallic, bimetallic, metal oxide, and mixed metal oxide. In electroanalytical methods, MNMs have been applied as sorbents for sample preparation before the electrochemical detection (sorbent role), as the electrode modifier (catalytic role), and the integration of the above two roles (as both sorbent and catalytic agent). In this paper, the application of MNMs in electroanalytical methods have been classified based on the main role of the nanomaterial and discussed separately. Furthermore, catalytic activities of MNMs in electroanalytical methods such as redox electrocatalytic, nanozymes catalytic (peroxidase, catalase activity, oxidase activity, superoxide dismutase activity), catalyst gate, and nanocontainer have been discussed.

An elegant technology for ultrasensitive impedimetric and voltammetric determination of cholestanol based on a novel molecularly imprinted electrochemical sensor

In this work, a novel molecularly imprinted electrochemical sensor (MIES) has been fabricated based on electropolymerization of a molecularly imprinted polymer (MIP) onto a glassy carbon electrode (GCE) modified with gold-palladium alloy nanoparticles (AuPd NPs)/polydopamine film (PDA)/multiwalled carbon nanotubes-chitosan-ionic liquid (MWCNTs-CS-IL) for voltammetric and impedimetric determination of cholestanol (CHO). Modifications applied to the bare GCE formed an excellent biocompatible composite film which was able to selectively detect CHO molecules. Modifications applied to the bare GCE were characterized by scanning electron microscopy (SEM), cyclic voltammetry (CV) and electrochemical impedance spectroscopy (SEM). Under optimal experimental conditions, the sensor was able to detect CHO in the range of 0.1-60 pM and 1-50 pM by EIS and DPV, respectively. Moreover, the sensor showed high sensitivity, selectivity, repeatability, reproducibility, low interference and good stability towards CHO determination. Our records confirmed that the sensor was successfully able to the analysis real samples for determination of CHO.

Coupling of digital image processing and three-way calibration to assist a paper-based sensor for determination of nitrite in food samples

In this work, a novel and very interesting analytical methodology based on coupling of digital image processing and three-way calibration has been developed for determination of nitrite in food samples.

Matrix augmentation as an efficient method for resolving interaction of bromocriptine with human serum albumin: trouble shooting and simultaneous resolution

This work reports the results of an interesting study related to the investigation of interactions of bromocriptine (BCP) with human serum albumin (HSA) by mathematicall modelling of voltammetric and spectroscopic data into an augmented data matrix and its resolution by multivariate curve resolution-alternating least squares (MCR-ALS). The quality of the results obtained by MCR-ALS was examined by MCR-BANDS and its outputs confirmed the absence of rotational ambiguities in the MCR-ALS results. BCP-HSA interactions were also modeled by molecular docking methods to verify the results obtained from experimental sections and fortunately, they were compatible. Hard modeling of the experimental data by EQUISPEC helped us to calculate the binding constant of the complex formed from BCP-HSA interactions which was in a good agreement with that of calculated from direct analysis of the experimental data. Finally, with the help of two different amperometric measurements based on BCP-HSA interactions a novel electroanalytical method was developed for biosensing of HSA in serum samples.

Fabrication of a novel impedimetric biosensor for label free detection of DNA damage induced by doxorubicin

In this work, a novel impedimetric biosensor has been fabricated for detection of DNA damage induced by doxorubicin (DX). Cytochrome P450 reductase (CPR) is required for electron transfer from nicotinamide adenine dinucleotide phosphate (NADPH) to cytochrome P450 (CP450) which causes DX to undergo a one-electron reduction of the p-quinone residue to form the semiquinone radical resulting in the generation of free hydroxyl radical which causes DNA damage. After modification of bare glassy carbon electrode (GCE) with multiwalled carbon nanotubes (MWCNTs) and chitosan (Ch), CPR and CP450 were co-immobilized onto the surface of Ch/MWCNTs/GCE by cross-linking CPR, CP450 and Ch through addition of glutaraldehyde. Then, the DNA was assembled onto the surface of CPRCP450/Ch/MWCNTs/GCE to fabricate the biosensor (DNA/CPRCP450/Ch/MWCNTs/GCE). Modifications applied to the bare GCE to fabricate the biosensor were characterized by CV, EIS and SEM. The DNA/CPRCP450/Ch/MWCNTs/GCE was treated in the damaging solution (DX + NADPH) which caused a significant DNA damage and the exposed DNA bases reduced the electrostatic repulsion of the negatively charged redox probe leading to Faradaic impedance changes. Performance of the biosensor for detection of DNA damage in the presence of Spinach extract was also examined and finally, an indirect impedimetric method was developed for determination of DX.

Online Third-Order Liquid Chromatographic Data with Native and Photoinduced Fluorescence Detection for the Quantitation of Organic Pollutants in Environmental Water

Third-order liquid chromatographic data were generated online for the simultaneous quantitation of six organic environmental pollutants. The employed strategy consists in reducing the linear flow rate at the column outlet. A postcolumn UV reactor and a fluorimetric detector allowed to properly record both photoinduced and native excitation-emission fluorescence matrices (EEPIFMs and EEFMs, respectively). The obtained third-order liquid chromatography data were chemometrically processed with the multivariate curve resolution-alternating least-squares model. The sensitivity of the overall analytical method was enhanced by a very simple solid-phase extraction with C18 membranes, to be able to successfully apply it to natural water samples tested as real matrices. Favorable detection limits for the investigated pollutants, ranging from 0.02 to 0.27 ng mL^-1, were attained, with relative prediction errors between 2 and 7%. Since the studied samples contain uncalibrated interferents, the applied strategy achieves the second-order advantage. Implications regarding the potential achievement of the third-order advantage are discussed.

Developing a novel paper-based enzymatic biosensor assisted by digital image processing and first-order multivariate calibration for rapid determination of nitrate in food samples

For the first time, a novel analytical method based on a paper based enzymatic biosensor assisted by digital image processing and first-order multivariate calibration has been reported for rapid determination of nitrate in food samples. The platform of the biosensor includes a piece of Whatman filter paper impregnated with Griess reagent (3-nitroaniline, 1-naphthylamine and hydrochloric acid) and nitrate reductase. After dropping a distinct volume of nitrate solution onto the biosensor surface, nitrate reductase selectively reduces nitrate to nitrite and then the Griess reagent selectively reacts with nitrite to produce a red colored azo dye. Therefore, the color intensity of the produced azo dye is correlated with nitrate concentration. After image capture, the images were processed and digitized in the MATLAB environment by the use of an image processing toolbox and the vectors produced by the digital image processing step were used as inputs of the first-order multivariate calibration algorithms. Several multivariate calibration algorithms and pre-processing techniques have been used to build multivariate calibration models for verifying which technique offers the best predictions towards nitrate concentrations in synthetic samples and the best algorithm has been chosen for nitrate determination in potato, onion, carrot, cabbage and lettuce samples as real cases.