An electrochemical sensor based on chitosan capped with gold nanoparticles combined with a voltammetric electronic tongue for quantitative aspirin detection in human physiological fluids and tablets.
Aspirin
/ analysis
Biosensing Techniques
/ instrumentation
Body Fluids
/ chemistry
Calibration
Carbon
/ chemistry
Chitosan
/ chemistry
Data Analysis
Discriminant Analysis
Electrochemical Techniques
/ instrumentation
Electrodes
Electronic Nose
Gold
/ chemistry
Humans
Least-Squares Analysis
Metal Nanoparticles
/ chemistry
Principal Component Analysis
Regression Analysis
Reproducibility of Results
Spectroscopy, Fourier Transform Infrared
Tablets
Aspirin
Electrochemical sensor
Human fluids
Multivariate data analysis
Voltammetric electronic tongue
Journal
Materials science & engineering. C, Materials for biological applications
ISSN: 1873-0191
Titre abrégé: Mater Sci Eng C Mater Biol Appl
Pays: Netherlands
ID NLM: 101484109
Informations de publication
Date de publication:
May 2020
May 2020
Historique:
received:
26
09
2019
revised:
17
12
2019
accepted:
13
01
2020
entrez:
25
3
2020
pubmed:
25
3
2020
medline:
5
1
2021
Statut:
ppublish
Résumé
Inflammatory diseases increase has recently sparked the research interest for drugs diagnostic tools development. At therapeutic doses, acetylsalicylic acid (ASA or aspirin) is widely used for these diseases' treatment. ASA overdoses can however give rise to adverse side effects including ulcers, gastric damage. Hence, development of simple, portable and sensitive methods for ASA detection is desirable. This paper reports aspirin analysis in urine, saliva and pharmaceutical tablet using an electrochemical sensor and a voltammetric electronic tongue (VE-Tongue). The electrochemical sensor was fabricated by self-assembling chitosan capped with gold nanoparticles (Cs + AuNPs) on a screen-printed carbon electrode (SPCE). It exhibits a logarithmic-linear relationship between its response and the ASA concentration in the range between 1 pg/mL and 1 μg/mL. A low detection limit (0.03 pg/mL), good selectivity against phenol and benzoic acid interference, and successful practical application were demonstrated. Qualitative analysis was performed using the VE-Tongue based unmodified metal electrodes combined with two chemometric approaches to classify urine samples spiked with different aspirin concentrations. Partial least squares (PLS) method provided prediction models obtained from the data of both devices with a regression correlation coefficient R
Identifiants
pubmed: 32204094
pii: S0928-4931(19)33595-7
doi: 10.1016/j.msec.2020.110665
pii:
doi:
Substances chimiques
Tablets
0
Carbon
7440-44-0
Gold
7440-57-5
Chitosan
9012-76-4
Aspirin
R16CO5Y76E
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
110665Informations de copyright
Copyright © 2020 Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of competing interest The authors declare no conflicting interests.