Stochastic modelling of the oral cancer proliferation and death in the presence of Thymoquinone as anticancer therapeutics

Oral cancer is one of the most commonly known cancer worldwide. Thymoquinone (TQ) an extract from Nigella sativa, has clinically been proven as an anticancer therapeutic agent for oral cancer due to its intrinsic pharmacological characteristics. Understanding the mechanisms of oral cancer proliferat...

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Main Authors: Tabassum, Shabana, Norhayati, Rosli, Wastuti Hidayati, Suriyah, Solachuddin Jauhari, Arief Ichwan
Format: Conference or Workshop Item
Language:English
Published: IOP Publishing 2021
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/35079/1/Tabassum_2021_J._Phys.__Conf._Ser._1988_012007.pdf
http://umpir.ump.edu.my/id/eprint/35079/
https://doi.org/10.1088/1742-6596/1988/1/012007
http://10.1088/1742-6596/1988/1/012007
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Institution: Universiti Malaysia Pahang
Language: English
id my.ump.umpir.35079
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spelling my.ump.umpir.350792022-09-02T05:19:23Z http://umpir.ump.edu.my/id/eprint/35079/ Stochastic modelling of the oral cancer proliferation and death in the presence of Thymoquinone as anticancer therapeutics Tabassum, Shabana Norhayati, Rosli Wastuti Hidayati, Suriyah Solachuddin Jauhari, Arief Ichwan QA Mathematics RA Public aspects of medicine Oral cancer is one of the most commonly known cancer worldwide. Thymoquinone (TQ) an extract from Nigella sativa, has clinically been proven as an anticancer therapeutic agent for oral cancer due to its intrinsic pharmacological characteristics. Understanding the mechanisms of oral cancer proliferation and death in the presence of TQ is crucial so that the insight of the interaction of cancer cells and TQ can be discovered. Cancer cells in the presence of TQ is subjected to the uncontrolled factors of the environmental noise. Deterministic model is inadequate to explain this behaviour. Herein, a stochastic model is proposed to illustrate the dynamics of HSC-3 oral cancer cell lines in the presence of TQ. The deterministic model is perturbed with the noisy behaviour which then leads to the stochastic model. The model is simulated by using a four-stage stochastic Runge-Kutta (SRK4) method and the kinetic parameters are estimated by using the maximum likelihood estimation (MLE) method. The prediction quality of the model is measured by using root mean square error (RMSE). The low values of RMSE show the best-fit of the stochastic model. IOP Publishing 2021 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/35079/1/Tabassum_2021_J._Phys.__Conf._Ser._1988_012007.pdf Tabassum, Shabana and Norhayati, Rosli and Wastuti Hidayati, Suriyah and Solachuddin Jauhari, Arief Ichwan (2021) Stochastic modelling of the oral cancer proliferation and death in the presence of Thymoquinone as anticancer therapeutics. In: Simposium Kebangsaan Sains Matematik ke-28 (SKSM28), 29-18 July, 2021 , Kuantan. pp. 1-8., 1988 (012007). https://doi.org/10.1088/1742-6596/1988/1/012007 http://10.1088/1742-6596/1988/1/012007
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic QA Mathematics
RA Public aspects of medicine
spellingShingle QA Mathematics
RA Public aspects of medicine
Tabassum, Shabana
Norhayati, Rosli
Wastuti Hidayati, Suriyah
Solachuddin Jauhari, Arief Ichwan
Stochastic modelling of the oral cancer proliferation and death in the presence of Thymoquinone as anticancer therapeutics
description Oral cancer is one of the most commonly known cancer worldwide. Thymoquinone (TQ) an extract from Nigella sativa, has clinically been proven as an anticancer therapeutic agent for oral cancer due to its intrinsic pharmacological characteristics. Understanding the mechanisms of oral cancer proliferation and death in the presence of TQ is crucial so that the insight of the interaction of cancer cells and TQ can be discovered. Cancer cells in the presence of TQ is subjected to the uncontrolled factors of the environmental noise. Deterministic model is inadequate to explain this behaviour. Herein, a stochastic model is proposed to illustrate the dynamics of HSC-3 oral cancer cell lines in the presence of TQ. The deterministic model is perturbed with the noisy behaviour which then leads to the stochastic model. The model is simulated by using a four-stage stochastic Runge-Kutta (SRK4) method and the kinetic parameters are estimated by using the maximum likelihood estimation (MLE) method. The prediction quality of the model is measured by using root mean square error (RMSE). The low values of RMSE show the best-fit of the stochastic model.
format Conference or Workshop Item
author Tabassum, Shabana
Norhayati, Rosli
Wastuti Hidayati, Suriyah
Solachuddin Jauhari, Arief Ichwan
author_facet Tabassum, Shabana
Norhayati, Rosli
Wastuti Hidayati, Suriyah
Solachuddin Jauhari, Arief Ichwan
author_sort Tabassum, Shabana
title Stochastic modelling of the oral cancer proliferation and death in the presence of Thymoquinone as anticancer therapeutics
title_short Stochastic modelling of the oral cancer proliferation and death in the presence of Thymoquinone as anticancer therapeutics
title_full Stochastic modelling of the oral cancer proliferation and death in the presence of Thymoquinone as anticancer therapeutics
title_fullStr Stochastic modelling of the oral cancer proliferation and death in the presence of Thymoquinone as anticancer therapeutics
title_full_unstemmed Stochastic modelling of the oral cancer proliferation and death in the presence of Thymoquinone as anticancer therapeutics
title_sort stochastic modelling of the oral cancer proliferation and death in the presence of thymoquinone as anticancer therapeutics
publisher IOP Publishing
publishDate 2021
url http://umpir.ump.edu.my/id/eprint/35079/1/Tabassum_2021_J._Phys.__Conf._Ser._1988_012007.pdf
http://umpir.ump.edu.my/id/eprint/35079/
https://doi.org/10.1088/1742-6596/1988/1/012007
http://10.1088/1742-6596/1988/1/012007
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