Voltammetric sensing using an array of modified SPCE coupled with machine learning strategies for the improved identification of opioids in presence of cutting agents

Altres ajuts: Acord transformatiu CRUE-CSICThis work reports the use of modified screen-printed carbon electrodes (SPCEs) for the identification of three drugs of abuse and two habitual cutting agents, caffeine and paracetamol, combining voltammetric sensing and chemometrics. In order to achieve this goal, codeine, heroin and morphine were subjected to Square Wave Voltammetry (SWV) at pH 7, in order to elucidate their electrochemical fingerprints. The optimized SPCEs electrode array, which have a differentiated response for the three oxidizable compounds, was derived from Carbon, Prussian blue, Cobalt (II) phthalocyanine, Copper (II) oxide, Polypyrrole and Palladium nanoparticles ink-modified carbon electrodes. Finally, Principal Component Analysis (PCA) coupled with Silhouette parameter assessment was used to select the most suitable combination of sensors for identification of drugs of abuse in presence of cutting agents

Label-free aptasensor for lysozyme detection using electrochemical impedance spectroscopy

Acknowledgments: Financial support for this work was provided by Spanish Ministry of Science and Innovation through projects CTQ2013-41577-P and CTQ2016-80170-P and by program ICREA Academia from Generalitat de Catalunya. Dionisia Ortiz-Aguayo thanks the support of Universitat Autònoma de Barcelona for the PIF fellowship.This research develops a label-free aptamer biosensor (aptasensor) based on graphite-epoxy composite electrodes (GECs) for the detection of lysozyme protein using Electrochemical Impedance Spectroscopy (EIS) technique. The chosen immobilization technique was based on covalent bonding using carbodiimide chemistry; for this purpose, carboxylic moieties were first generated on the graphite by electrochemical grafting. The detection was performed using [Fe(CN)]/[Fe(CN)] as redox probe. After recording the frequency response, values were fitted to its electric model using the principle of equivalent circuits. The aptasensor showed a linear response up to 5 µMfor lysozyme and a limit of detection of 1.67 µM. The sensitivity of the established method was 0.090 µM in relative charge transfer resistance values. The interference response by main proteins, such as bovine serum albumin and cytochrome c, has been also characterized. To finally verify the performance of the developed aptasensor, it was applied to wine analysis

Resolution of opiate illicit drugs signals in the presence of some cutting agents with use of a voltammetric sensor array and machine learning strategies

Altres ajuts: Acord transformatiu CRUE-CSICIn the present work, the resolution and quantification of mixtures of different opiates compounds in the presence of common cutting agents using an electronic tongue (ET) is evaluated. More specifically, ternary mixtures of heroin, morphine and codeine were resolved in the presence of caffeine and paracetamol. To this aim, an array of three carbon screen-printed electrodes were modified with different ink-like solutions of graphite, cobalt (II) phthalocyanine and palladium, and their responses towards the different drugs were characterized by means of square wave voltammetry (SWV). Developed sensors showed a good performance with good linearity at the µM level, LODs between 1.8 and 5.33 µM for the 3 actual drugs, and relative standard deviation (RSD) ca. 2% for over 50 consecutive measurements. Next, a quantitative model that allowed the identification and quantification of the individual substances from the overlapped voltammograms was built using partial least squares regression (PLS) as the modelling tool. With this approach, quantification of the different drugs was achieved at the μM level, with a total normalized root mean square error (NRMSE) of 0.084 for the test subset

Simultaneous voltammetric determination of acetaminophen, ascorbic acid and uric acid by use of integrated array of screen-printed electrodes and chemometric tools

In the present work, ternary mixtures of Acetaminophen, Ascorbic acid and Uric acid were resolved using the Electronic tongue (ET) principle and Cyclic voltammetry (CV) technique. The screen-printed integrated electrode array having differentiated response for the three oxidizable compounds was formed by Graphite, Prussian blue (PB), Cobalt (II) phthalocyanine (CoPc) and Copper oxide (II) (CuO) ink-modified carbon electrodes. A set of samples, ranging from 0 to 500 µmol·L, was prepared, using a tilted (3) factorial design in order to build the quantitative response model. Subsequently, the model performance was evaluated with an external subset of samples defined randomly along the experimental domain. Partial Least Squares Regression (PLS) was employed to construct the quantitative model. Finally, the model successfully predicted the concentration of the three compounds with a normalized root mean square error (NRMSE) of 1.00 and 0.99 for the training and test subsets, respectively, and R ≥ 0.762 for the obtained vs. expected comparison graphs. In this way, a screen-printed integrated electrode platform can be successfully used for voltammetric ET applications

Electronic Tongues using Printed Sensor Platforms for Forensic and Security Applications

La present tesi doctoral té com a fi l'estudi de noves plataformes sensores combinant principis de llengua electrònica i eines quimiomètriques. Per assolir aquest objectiu s'han aplicat els coneixements adquirits al grup de Sensors i Biosensors de la Universitat Autònoma de Barcelona. El fonament d'aquesta investigació té com a objectiu principal el desenvolupament de sensors electroquímics, emprant el concepte de matrius de sensors per a aplicacions en diferents camps d'estudi. El tipus de sensor utilitzat va ser imprès, bé mitjançant la tècnica de serigrafia o bé mitjançant injecció de tinta. L'ús d'aquests sistemes proporciona informació multicomponent que cal tractar amb eines de la quimiometria. Les mesures electroquímiques van ser obtingudes mitjançant diferents tècniques electroanalítiques basades en el fonament de la voltamperometria, concretament la cíclica i la d'ona quadrada. La part matemàtica i de processament de dades van ser tractades utilitzant l'anàlisi de components principals i càlcul del coeficient Silhouette per a estudis qualitatius. A més, es van utilitzar algoritmes d'aprenentatge coneguts com a "Machine Learning Algorithms" per a la identificació de les mescles en estudi. L'ús d'aquests criteris estadístics ha servit per optimitzar la composició de la matriu de sensors. D'altra banda, els estudis quantitatius es van abordar emprant algoritmes de càlcul més complexos com ara la regressió de mínims quadrats parcials i les xarxes neuronals artificials com a simulació dels sistemes biomimètics. Les aplicacions d'aquests sistemes s'han realitzat en dos camps d'estudi ben diferenciats. Un d'ells és la quantificació de diferents compostos farmacèutics (mescles ternàries de acetaminofè, àcid ascòrbic i àcid úric) com a prova de concepte per validar el procediment experimental desenvolupat. En el segon cas, l'estudi està enfocat a la identificació i posterior quantificació de diferents drogues d'abús i els seus agents de tall corresponents. En concret, es van identificar i quantificar mescles d'opiacis com són l'heroïna, la morfina i la codeïna. A més, es van afegir a les mescles concentracions comunament emprades de diferents agents de tall (paracetamol i cafeïna) amb la finalitat de simular la detecció de mostres reals trobades al mercat il·lícit de la droga. Per concloure l'estudi, es va desenvolupar una aplicació per a la quantificació de diferents agents de tall (mescles ternàries de benzocaïna, fenacetina i paracetamol) trobades de manera comuna en mostres de cocaïna. Totes aquestes aproximacions tenen com a objectiu final la implementació de noves estratègies per a la ràpida detecció de drogues il·lícites en punts de control liderats per les autoritats.La presente tesis doctoral tiene como fin el estudio de nuevas plataformas sensoras combinando principios de lengua electrónica y herramientas quimiométricas. Para lograr esta meta se han aplicado los conocimientos adquiridos en el grupo de Sensores y Biosensores de la Universidad Autónoma de Barcelona. El fundamento de esta investigación se centra como objetivo principal en el desarrollo de sensores electroquímicos, empleando el concepto de matrices de sensores para aplicaciones en diferentes campos de estudio. El tipo de sensor utilizado fue impreso, bien mediante la técnica de serigrafía o bien mediante inyección de tinta. El uso de estos sistemas proporciona información multicomponente que requiere ser tratada con herramientas de quimiometría. Las medidas electroquímicas fueron obtenidas a través de diferentes técnicas electroanalíticas basadas en el fundamento de la voltamperometría, concretamente la cíclica y la de onda cuadrada. La parte matemática y de procesamiento de datos fueron tratados utilizando el análisis de componentes principales y cálculo del coeficiente Silhouette para estudios cualitativos. Además, se utilizaron algoritmos de aprendizaje comúnmente conocidos como "Machine Learning Algorithms" para la identificación de las mezclas en estudio. El uso de estos criterios estadísticos ha servido para optimizar la composición de la matriz de sensores. Por otra parte, los estudios cuantitativos se abordaron empleando algoritmos de cálculo más complejos como pueden ser la regresión de mínimos cuadrados parciales y las redes neuronales artificiales como simulación de los sistemas biomiméticos. Las aplicaciones de estos sistemas se han realizado en dos campos de estudio bien diferenciados. Uno de ellos, es la cuantificación de diferentes compuestos farmacéuticos (mezclas ternarias de acetaminofeno, ácido ascórbico y ácido úrico) como prueba de concepto para validar el procedimiento experimental desarrollado. En el segundo caso, el estudio está enfocado a la identificación y posterior cuantificación de diferentes drogas de abuso y sus agentes de corte correspondientes. En concreto, se identificaron y cuantificaron mezclas de opiáceos como son la heroína, la morfina y la codeína. Además, se añadieron a las mezclas concentraciones comúnmente empleadas de diferentes agentes de corte (paracetamol y cafeína) con la finalidad de simular la detección de muestras reales encontradas en el mercado ilícito de la droga. Para concluir el estudio, se desarrolló una aplicación para la cuantificación de diferentes agentes de corte (mezclas ternarias de benzocaína, fenacetina y paracetamol) halladas de forma común en muestras de cocaína. Todas estas aproximaciones tienen como objetivo final la implementación de nuevas estrategias para la rápida detección de drogas ilícitas en puntos de control liderados por las autoridades.The aim of this doctoral thesis is to study new sensor platforms combining electronic tongues principles and chemometric tools. To achieve this goal, the knowledge acquired in the Sensors and Biosensors group of the Universitat Autònoma de Barcelona has been applied. The main objective of this research is focused on the development of electrochemical sensors, using the concept of sensor arrays for applications in different fields of study. The type of sensor employed was printed, either by screen-printing or inkjet printing techniques. The use of these systems provides multicomponent information that needs to be treated with chemometric tools. The electrochemical measurements were obtained using different electroanalytical techniques based on the fundamentals of Voltammetry, namely Cyclic and Square Wave. The data processing part was treated using Principal Component Analysis and Silhouette Coefficient Calculation for qualitative studies. In addition, learning algorithms commonly known as "Machine Learning Algorithms" were used for the identification of the mixtures under study. The use of these statistical criteria has served to optimise the composition of the sensor matrix. In contrast, quantitative studies were approached using more complex calculation algorithms such as Partial Least Squares Regression and Artificial Neural Networks as a simulation of the biomimetic systems. The application of these systems has been focused on two distinct fields of study. One is the quantification of different pharmaceutical compounds (ternary mixtures of acetaminophen, ascorbic acid and uric acid) as a proof of concept to validate the experimental procedure developed. In the second case, the study is focused on the identification and subsequent quantification of different drugs of abuse and their corresponding cutting agents. Specifically, mixtures of opiates such as heroin, morphine and codeine were identified and quantified. Moreover, commonly used concentrations of different cutting agents (paracetamol and caffeine) were added to the mixtures in order to simulate the detection of real samples found in the illicit drug market. To conclude the study, an application was developed for the quantification of different cutting agents (ternary mixtures of benzocaine, phenacetin, and paracetamol) commonly found in cocaine samples. All these approaches are ultimately aimed at implementing new strategies for the rapid detection of illicit drugs at checkpoints led by the authorities

Label-Free Aptasensor for Lysozyme Detection Using Electrochemical Impedance Spectroscopy

This research develops aptasensors for Lysozyme protein detection [...

Label-free aptasensor for lysozyme detection using electrochemical impedance spectroscopy

Acknowledgments: Financial support for this work was provided by Spanish Ministry of Science and Innovation through projects CTQ2013-41577-P and CTQ2016-80170-P and by program ICREA Academia from Generalitat de Catalunya. Dionisia Ortiz-Aguayo thanks the support of Universitat Autònoma de Barcelona for the PIF fellowship.This research develops a label-free aptamer biosensor (aptasensor) based on graphite-epoxy composite electrodes (GECs) for the detection of lysozyme protein using Electrochemical Impedance Spectroscopy (EIS) technique. The chosen immobilization technique was based on covalent bonding using carbodiimide chemistry; for this purpose, carboxylic moieties were first generated on the graphite by electrochemical grafting. The detection was performed using [Fe(CN)]/[Fe(CN)] as redox probe. After recording the frequency response, values were fitted to its electric model using the principle of equivalent circuits. The aptasensor showed a linear response up to 5 µMfor lysozyme and a limit of detection of 1.67 µM. The sensitivity of the established method was 0.090 µM in relative charge transfer resistance values. The interference response by main proteins, such as bovine serum albumin and cytochrome c, has been also characterized. To finally verify the performance of the developed aptasensor, it was applied to wine analysis

Simultaneous voltammetric determination of acetaminophen, ascorbic acid and uric acid by use of integrated array of screen-printed electrodes and chemometric tools

In the present work, ternary mixtures of Acetaminophen, Ascorbic acid and Uric acid were resolved using the Electronic tongue (ET) principle and Cyclic voltammetry (CV) technique. The screen-printed integrated electrode array having differentiated response for the three oxidizable compounds was formed by Graphite, Prussian blue (PB), Cobalt (II) phthalocyanine (CoPc) and Copper oxide (II) (CuO) ink-modified carbon electrodes. A set of samples, ranging from 0 to 500 µmol·L, was prepared, using a tilted (3) factorial design in order to build the quantitative response model. Subsequently, the model performance was evaluated with an external subset of samples defined randomly along the experimental domain. Partial Least Squares Regression (PLS) was employed to construct the quantitative model. Finally, the model successfully predicted the concentration of the three compounds with a normalized root mean square error (NRMSE) of 1.00 and 0.99 for the training and test subsets, respectively, and R ≥ 0.762 for the obtained vs. expected comparison graphs. In this way, a screen-printed integrated electrode platform can be successfully used for voltammetric ET applications