Literature DB >> 21078280

Chemometric-assisted kinetic-spectrophotometric method for simultaneous determination of ascorbic acid, uric acid, and dopamine.

Masoud Rohani Moghadam1, Shayessteh Dadfarnia, Ali Mohammad Haji Shabani, Parviz Shahbazikhah.   

Abstract

A chemometric-assisted kinetic spectrophotometric method has been developed for simultaneous determination of ascorbic acid (AA), uric acid (UA), and dopamine (DA). This method relies on the difference in the kinetic rates of the reactions of analytes with a common oxidizing agent, tris(1,10-phenanthroline) and iron(III) complex (ferritin, [Fe(phen)(3)](3+)) at pH 4.4. The changes in absorbance were monitored spectrophotometrically. The data obtained from the experiments were processed by chemometric methods of artificial neural network (ANN) and partial least squares (PLS). Acceptable techniques of prediction set, randomization t test, cross-validation, and Y randomization were applied for the selection of the best chemometric method. The results showed that feedforward artificial neural network (FFANN) is more efficient than the other chemometric methods. The parameters affecting the experimental conditions were optimized, and it was found that under optimal conditions Beer's law is followed in the concentration ranges of 4.3-74.1, 4.3-78.3, and 2.0-33.0 μM for AA, UA, and DA, respectively. The proposed method was successfully applied to the determination of analytes in serum and urine samples.
Copyright © 2010 Elsevier Inc. All rights reserved.

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Year:  2010        PMID: 21078280     DOI: 10.1016/j.ab.2010.11.007

Source DB:  PubMed          Journal:  Anal Biochem        ISSN: 0003-2697            Impact factor:   3.365


  10 in total

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Authors:  Xinjian Song; Ju Fu; Juan Wang; Chunya Li; Zhihong Liu
Journal:  Mikrochim Acta       Date:  2018-07-09       Impact factor: 5.833

2.  Nitrogen-doped carbon frameworks decorated with palladium nanoparticles for simultaneous electrochemical voltammetric determination of uric acid and dopamine in the presence of ascorbic acid.

Authors:  Yao Yao; Ji Zhong; Zhiwei Lu; Xin Liu; Yanying Wang; Tao Liu; Ping Zou; Xianxiang Dai; Xianxiang Wang; Fang Ding; Cailong Zhou; Qingbiao Zhao; Hanbing Rao
Journal:  Mikrochim Acta       Date:  2019-11-16       Impact factor: 5.833

3.  A ratiometric fluorescence sensor for ascorbic acid determination based on an AND-NAND logic pair.

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Journal:  Mikrochim Acta       Date:  2021-10-12       Impact factor: 5.833

4.  Electrochemical determination of dopamine and uric acid using a glassy carbon electrode modified with a composite consisting of a Co(II)-based metalorganic framework (ZIF-67) and graphene oxide.

Authors:  Jing Tang; Sixun Jiang; Yu Liu; Shengbiao Zheng; Lei Bai; Jiahao Guo; Jianfei Wang
Journal:  Mikrochim Acta       Date:  2018-10-01       Impact factor: 5.833

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Journal:  Mater Today Bio       Date:  2022-04-08

6.  Preparation of Cu₂O-Reduced Graphene Nanocomposite Modified Electrodes towards Ultrasensitive Dopamine Detection.

Authors:  Quanguo He; Jun Liu; Xiaopeng Liu; Guangli Li; Peihong Deng; Jing Liang
Journal:  Sensors (Basel)       Date:  2018-01-12       Impact factor: 3.576

7.  Silver Nanoparticle Modified Electrode Covered by Graphene Oxide for the Enhanced Electrochemical Detection of Dopamine.

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Journal:  Sensors (Basel)       Date:  2017-11-29       Impact factor: 3.576

8.  A New Kinetic Spectrophotometric Method for the Quantitation of Amorolfine.

Authors:  César Soto; Cristian Poza; David Contreras; Jorge Yáñez; Fallon Nacaratte; M Inés Toral
Journal:  J Anal Methods Chem       Date:  2017-02-28       Impact factor: 2.193

9.  Simultaneous Detection of Dopamine and Uric Acid Using a Poly(l-lysine)/Graphene Oxide Modified Electrode.

Authors:  Yuehua Zhang; Wu Lei; Yujuan Xu; Xifeng Xia; Qingli Hao
Journal:  Nanomaterials (Basel)       Date:  2016-09-28       Impact factor: 5.076

10.  An integrated microchannel biosensor platform to analyse low density lactate metabolism in HepG2 cells in vitro.

Authors:  Shengli Mi; Jingjing Xia; Yuanyuan Xu; Zhichang Du; Wei Sun
Journal:  RSC Adv       Date:  2019-03-19       Impact factor: 3.361

  10 in total

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