Simultaneous Sensing of Codeine and Diclofenac in Water Samples Using an Electrochemical Bi-MIP Sensor and a Voltammetric Electronic Tongue

2021 ◽  
Vol 5 (1) ◽  
pp. 63
Author(s):  
Hafsa El Youbi ◽  
Alassane Diouf ◽  
Benachir Bouchikhi ◽  
Nezha El Bari
Keyword(s):  
Water Samples ◽  
Simultaneous Detection ◽  
Electronic Tongue ◽  
Cross Reactivity ◽  
Reactivity Effect ◽  
Target Analytes ◽  
Voltammetric Electronic Tongue ◽  
Mip Sensor ◽  
Simultaneous Sensing ◽  
Biomimetic Sensor

Codeine and diclofenac overdoses have been widely reported. Here, a biomimetic sensor (bi-MIP) was devised, and an electronic tongue was used to analyze water samples simultaneously containing both these drugs. The bi-MIP sensor limits of detection for diclofenac and codeine taken individually were 0.01 µg/mL and 0.16 µg/mL, respectively. Due to a cross-reactivity effect when using the bi-MIP sensor, the electronic tongue was shown to differentiate samples containing both analytes. The results confirm the feasibility of simultaneous detection of two target analytes via a bi-MIP sensor. Additionally, they demonstrate the ability of a multi-sensor to classify different water samples.

scholarly journals Design of Novel Haptens and Development of Monoclonal Antibody-Based Immunoassays for the Simultaneous Detection of Tylosin and Tilmicosin in Milk and Water Samples

Biomolecules ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. 770 ◽  
Author(s):  
Jian-Xin Huang ◽  
Chan-Yuan Yao ◽  
Jin-Yi Yang ◽  
Zhen-Feng Li ◽  
Fan He ◽  
...  
Keyword(s):  
Monoclonal Antibody ◽  
Water Samples ◽  
Simultaneous Detection ◽  
Aldehyde Group ◽  
Cross Reactivity ◽  
Side Chain ◽  
Enzyme Linked Immunosorbent Assay ◽  
Inhibition Concentration ◽  
Ic50 Values ◽  
Optimized Conditions

In this work, a monoclonal antibody-based indirect competitive enzyme-linked immunosorbent assay (icELISA) was established to detect tylosin and tilmicosin in milk and water samples. A sensitive and specific monoclonal antibody was prepared by rational designed hapten, which was achieved by directly oxidizing the aldehyde group on the side chain of tylosin to the carboxyl group. Under the optimized conditions, the linear range of icELISA for tylosin and tilmicosin were 1.3 to 17.7 ng/mL and 2.0 to 47.4 ng/mL, with half-maximal inhibition concentration (IC50) values of 4.7 and 9.6 ng/mL, respectively. The cross-reactivity with other analogues of icELISA was less than 0.1%. The average recoveries of icELISA for tylosin and tilmicosin ranged from 76.4% to 109.5% in milk and water samples. Besides, the detection results of icELISA showed good correlations with HPLC-MS/MS. The proposed icELISA was satisfied for rapid and specific screening of tylosin and tilmicosin residues in milk and water samples.

scholarly journals Voltammetric Electronic Tongue for the Simultaneous Determination of Three Benzodiazepines

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 5002 ◽  
Author(s):  
Anna Herrera-Chacón ◽  
Farzad Torabi ◽  
Farnoush Faridbod ◽  
Jahan B. Ghasemi ◽  
Andreu González-Calabuig ◽  
...  
Keyword(s):  
Metallic Nanoparticles ◽  
Simultaneous Detection ◽  
Electronic Tongue ◽  
Principal Component ◽  
Quantitative Model ◽  
Discrete Wavelet ◽  
Composite Electrodes ◽  
Voltammetric Sensors ◽  
Voltammetric Electronic Tongue

The presented manuscript reports the simultaneous detection of a ternary mixture of the benzodiazepines diazepam, lorazepam, and flunitrazepam using an array of voltammetric sensors and the electronic tongue principle. The electrodes used in the array were selected from a set of differently modified graphite epoxy composite electrodes; specifically, six electrodes were used incorporating metallic nanoparticles of Cu and Pt, oxide nanoparticles of CuO and WO3, plus pristine electrodes of epoxy-graphite and metallic Pt disk. Cyclic voltammetry was the technique used to obtain the voltammetric responses. Multivariate examination using Principal Component Analysis (PCA) justified the choice of sensors in order to get the proper discrimination of the benzodiazepines. Next, a quantitative model to predict the concentrations of mixtures of the three benzodiazepines was built employing the set of voltammograms, and was first processed with the Discrete Wavelet Transform, which fed an artificial neural network response model. The developed model successfully predicted the concentration of the three compounds with a normalized root mean square error (NRMSE) of 0.034 and 0.106 for the training and test subsets, respectively, and coefficient of correlation R ≥ 0.938 in the predicted vs. expected concentrations comparison graph.

scholarly journals Neonatal wearable device for colorimetry-based real-time detection of jaundice with simultaneous sensing of vitals

2021 ◽  
Vol 7 (10) ◽  
pp. eabe3793
Author(s):  
Go Inamori ◽  
Umihiro Kamoto ◽  
Fumika Nakamura ◽  
Yutaka Isoda ◽  
Azusa Uozumi ◽  
...  
Keyword(s):  
Heart Rate ◽  
Oxygen Saturation ◽  
Neonatal Jaundice ◽  
Treatment Approach ◽  
Combined Treatment ◽  
Simultaneous Detection ◽  
Clinical Experiments ◽  
Simultaneous Sensing ◽  
Severe Hyperbilirubinemia ◽  
Transcutaneous Bilirubinometer

Neonatal jaundice occurs in >80% of newborns in the first week of life owing to physiological hyperbilirubinemia. Severe hyperbilirubinemia could cause brain damage owing to its neurotoxicity, a state commonly known as kernicterus. Therefore, periodic bilirubin monitoring is essential to identify infants at-risk and to initiate treatment including phototherapy. However, devices for continuous measurements of bilirubin have not been developed yet. Here, we established a wearable transcutaneous bilirubinometer that also has oxygen saturation (SpO2) and heart rate (HR) sensing functionalities. Clinical experiments with neonates demonstrated the possibility of simultaneous detection of bilirubin, SpO2, and HR. Moreover, our device could consistently measure bilirubin during phototherapy. These results demonstrate the potential for development of a combined treatment approach with an automatic link via the wearable bilirubinometer and phototherapy device for optimization of the treatment of neonatal jaundice.

Establishment and Preliminary Application of Multiplex Fluorescent Quantitative PCR for Simultaneous Detection of BVDV, BRV and BCV

2021 ◽  
Author(s):  
Liyun Chang ◽  
Zhiyong Liu ◽  
Yuelan Zhao ◽  
Yan Li ◽  
Jianhua Qin
Keyword(s):  
Quantitative Pcr ◽  
Quantitative Methods ◽  
Diarrheal Disease ◽  
Quantitative Polymerase Chain Reaction ◽  
Simultaneous Detection ◽  
Cross Reactivity ◽  
N Gene ◽  
Established Method ◽  
Diarrhea Virus ◽  
Fluorescence Quantitative Pcr

Background: In this study, we aimed to establish a multiplex fluorescence quantitative polymerase chain reaction (PCR) method for the identification and detection of bovine viral diarrhea virus (BVDV), bovine rotavirus (BRV) and bovine coronavirus (BCV). Methods: Based on the highly conserved sequences of BVDV E2 gene, BRV VP6 gene and BCV N gene in GenBank, specific primers were designed to amplify the target gene fragments of each virus and the reaction conditions and system were optimized. Multiple fluorescence quantitative methods were established by fluorescence quantitative PCR. Result: The minimum detection limits of plasmid standards for BVDV, BRV and BCV by multiplex fluorescence quantitative PCR were 1.19×102 copies/μL, 3.89×101 copies/μL and 3.74×101 copies/μL, respectively. The lowest sensitivity of the established method was 100 times higher than that of conventional PCR and had high sensitivity. Furthermore, BVDV, BRV and BCV were amplified specifically, with no cross-reactivity with Escherichia coli (E. coli), Salmonella and infectious bovine rhinotracheitis virus (IBRV). The intra-and inter-group coefficients of variation were less than 1%, showing good assay repeatability. Using the established method and ordinary multiplex PCR to simultaneously detect 150 clinical diarrheal disease material samples, the coincidence rate of samples with mixed infection of the three viruses was 83.3%. The results showed that the multiplex fluorescent quantitative PCR detection method established in this study provides a rapid, sensitive and specific technique for clinical diagnosis and epidemiological monitoring of BVDV, BRV and BCV.

Emerging approach for analytical characterization and geographical classification of Moroccan and French honeys by means of a voltammetric electronic tongue

2018 ◽  
Vol 243 ◽  
pp. 36-42 ◽  
Author(s):  
Nadia El Alami El Hassani ◽  
Khalid Tahri ◽  
Eduard Llobet ◽  
Benachir Bouchikhi ◽  
Abdelhamid Errachid ◽  
...  
Keyword(s):  
Electronic Tongue ◽  
Analytical Characterization ◽  
Voltammetric Electronic Tongue

scholarly journals Evaluation of Feature Selection Techniques in a Multifrequency Large Amplitude Pulse Voltammetric Electronic Tongue

2020 ◽  
Vol 2 (1) ◽  
pp. 62
Author(s):  
Luis F. Villamil-Cubillos ◽  
Jersson X. Leon-Medina ◽  
Maribel Anaya ◽  
Diego A. Tibaduiza
Keyword(s):  
Feature Selection ◽  
Large Amplitude ◽  
Electronic Tongue ◽  
Supervised Machine Learning ◽  
Recursive Feature Elimination ◽  
Support Vector ◽  
Variance Filter ◽  
Supervised Machine Learning Classifiers ◽  
Voltammetric Electronic Tongue ◽  
Feature Selection Techniques

An electronic tongue is a device composed of a sensor array that takes advantage of the cross sensitivity property of several sensors to perform classification and quantification in liquid substances. In practice, electronic tongues generate a large amount of information that needs to be correctly analyzed, to define which interactions and features are more relevant to distinguish one substance from another. This work focuses on implementing and validating feature selection methodologies in the liquid classification process of a multifrequency large amplitude pulse voltammetric (MLAPV) electronic tongue. Multi-layer perceptron neural network (MLP NN) and support vector machine (SVM) were used as supervised machine learning classifiers. Different feature selection techniques were used, such as Variance filter, ANOVA F-value, Recursive Feature Elimination and model-based selection. Both 5-fold Cross validation and GridSearchCV were used in order to evaluate the performance of the feature selection methodology by testing various configurations and determining the best one. The methodology was validated in an imbalanced MLAPV electronic tongue dataset of 13 different liquid substances, reaching a 93.85% of classification accuracy.

scholarly journals Quantitative analysis and resolution of pharmaceuticals in the environment using multivariate curve resolution-alternating least squares (MCR-ALS)

2019 ◽  
Vol 69 (2) ◽  
pp. 217-231 ◽  
Author(s):  
Ahmed Mostafa ◽  
Heba Shaaban
Keyword(s):  
Least Squares ◽  
Water Samples ◽  
Alternating Least Squares ◽  
Multivariate Curve Resolution ◽  
Least Squares Regression ◽  
Environmental Matrices ◽  
Curve Resolution ◽  
Real Water Samples ◽  
Target Analytes ◽  
Spectrophotometric Data

Abstract The study presents the application of multivariate curve resolution alternating least squares (MCR-ALS) with a correlation constraint for simultaneous resolution and quantification of ketoprofen, naproxen, paracetamol and caffeine as target analytes and triclosan as an interfering component in different water samples using UV-Vis spectrophotometric data. A multivariate regression model using the partial least squares regression (PLSR) algorithm was developed and calculated. The MCR-ALS results were compared with the PLSR obtained results. Both models were validated on external sample sets and were applied to the analysis of real water samples. Both models showed comparable and satisfactory results with the relative error of prediction of real water samples in the range of 1.70–9.75 % and 1.64–9.43 % for MCR-ALS and PLSR, resp. The obtained results show the potential of MCR-ALS with correlation constraint to be applied for the determination of different pharmaceuticals in complex environmental matrices.

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