A numerical modelling of an amperometric-enzymatic based uric acid biosensor for GOUT arthritis diseases

A numerical model of an amperometric-enzymatic uric acid biosensor for a non-relentless condition has been developed. This model depends on the arrangement of nonlinear reaction diffusion equations for Michaelis-Menten formalism that depicts the concentrations of substrate and product. The new rough...

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Main Authors: Parthasarathy P, Vivekanandan S
Format: Article
Language:English
Published: Elsevier 2018-01-01
Series:Informatics in Medicine Unlocked
Online Access:http://www.sciencedirect.com/science/article/pii/S2352914818300133
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spelling doaj-11d51482fb004d45832a597a1aa2e1cc2020-11-25T01:22:41ZengElsevierInformatics in Medicine Unlocked2352-91482018-01-0112143147A numerical modelling of an amperometric-enzymatic based uric acid biosensor for GOUT arthritis diseasesParthasarathy P0Vivekanandan S1Corresponding author.; School of Electrical Engineering, VIT University, Tamilnadu, IndiaSchool of Electrical Engineering, VIT University, Tamilnadu, IndiaA numerical model of an amperometric-enzymatic uric acid biosensor for a non-relentless condition has been developed. This model depends on the arrangement of nonlinear reaction diffusion equations for Michaelis-Menten formalism that depicts the concentrations of substrate and product. The new rough scientific articulations for the concentration of substrate (uricase enzyme) and product and the corresponding current response have been derived for all estimations of parameters utilizing the new perturbation technique. The non-dimensional numerical model of the amperometric biosensor can be effectively used to examine the responses. Moreover, the relative impact of these parameters is chosen by the Damkohler number and the impact of current density on this number likewise contemplated. All the analytical results are compared with simulation results using MATLAB program and the numerical outcomes concur with fitting hypotheses. Notwithstanding, strikingly the model likewise proposed that the choice of substrate and product for uric acid biosensor for the application of kidney disease and GOUT arthritis diseases. Keywords: GOUT arthritis, Amperometric, Uric acid, Damkohler number, Diffusion equationshttp://www.sciencedirect.com/science/article/pii/S2352914818300133
collection DOAJ
language English
format Article
sources DOAJ
author Parthasarathy P
Vivekanandan S
spellingShingle Parthasarathy P
Vivekanandan S
A numerical modelling of an amperometric-enzymatic based uric acid biosensor for GOUT arthritis diseases
Informatics in Medicine Unlocked
author_facet Parthasarathy P
Vivekanandan S
author_sort Parthasarathy P
title A numerical modelling of an amperometric-enzymatic based uric acid biosensor for GOUT arthritis diseases
title_short A numerical modelling of an amperometric-enzymatic based uric acid biosensor for GOUT arthritis diseases
title_full A numerical modelling of an amperometric-enzymatic based uric acid biosensor for GOUT arthritis diseases
title_fullStr A numerical modelling of an amperometric-enzymatic based uric acid biosensor for GOUT arthritis diseases
title_full_unstemmed A numerical modelling of an amperometric-enzymatic based uric acid biosensor for GOUT arthritis diseases
title_sort numerical modelling of an amperometric-enzymatic based uric acid biosensor for gout arthritis diseases
publisher Elsevier
series Informatics in Medicine Unlocked
issn 2352-9148
publishDate 2018-01-01
description A numerical model of an amperometric-enzymatic uric acid biosensor for a non-relentless condition has been developed. This model depends on the arrangement of nonlinear reaction diffusion equations for Michaelis-Menten formalism that depicts the concentrations of substrate and product. The new rough scientific articulations for the concentration of substrate (uricase enzyme) and product and the corresponding current response have been derived for all estimations of parameters utilizing the new perturbation technique. The non-dimensional numerical model of the amperometric biosensor can be effectively used to examine the responses. Moreover, the relative impact of these parameters is chosen by the Damkohler number and the impact of current density on this number likewise contemplated. All the analytical results are compared with simulation results using MATLAB program and the numerical outcomes concur with fitting hypotheses. Notwithstanding, strikingly the model likewise proposed that the choice of substrate and product for uric acid biosensor for the application of kidney disease and GOUT arthritis diseases. Keywords: GOUT arthritis, Amperometric, Uric acid, Damkohler number, Diffusion equations
url http://www.sciencedirect.com/science/article/pii/S2352914818300133
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