Effects of Estrogen Contamination on Human Cells: Modeling and Prediction Based on Michaelis-Menten Kinetics
DOI: 10.4236/jwarp.2009.15040   PDF    HTML     4,560 Downloads   8,325 Views   Citations


In this paper, we propose a novel prevention strategy to alert citizens when water is contaminated by estro-gen. Epidemiological studies have shown that chronic exposure to high blood level of estrogen is associated with the development of breast cancer. The preventive strategy proposed in this paper is based on the predic-tion of estrogen effects on human living cells. Based on first principle insights, we develop in this work, a mathematical model for this prediction purpose. Dynamic measurements of cell proliferation response to es-trogen stimulation were continuously monitored by a real-time cell electronic sensor (RT-CES) and used in order to estimate the parameters of the model developed.

Share and Cite:

F. IBRAHIM, B. HUANG, J. XING, W. ROA and S. GABOS, "Effects of Estrogen Contamination on Human Cells: Modeling and Prediction Based on Michaelis-Menten Kinetics," Journal of Water Resource and Protection, Vol. 1 No. 5, 2009, pp. 336-344. doi: 10.4236/jwarp.2009.15040.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] J. S. Patrick, J. A. Franklin, and J. J. C. James, “The en-vironmental science of drinking water,” ISBN-13: 978?0 ?7506?7876?6, 2005.
[2] K. N. Rajesh, “Endocrine disruptors: Effects on male and female reproductive systems,” CRC Press, 1st Edition ISBN-10: 0849331641, 1999.
[3] P. Lemieux and S. Fuqua, “The role of the estrogen re-ceptor in tumor progression,” The Journal of Steroid Bio-chemistry and Molecular Biology, Vol. 56, No. 87?91, 1996.
[4] R. A. Hess and K. Carnes, “The role of estrogen in testis and the male reproductive tract: A review and species comparison,” Animal Reproduction, Vol. 1, pp. 5?30. 2004.
[5] M. L. Johnson, A. Salveson, L. Holmes, M. S. Denison, and D. M. Fry, “Environmental estrogens in agricultural drain water from the central valley of California,” Journal Bulletin of Environmental Contamination and Toxicology, Vol. 60, pp. 609?614, 1998.
[6] B. Huang and J. Z. Xing, “Dynamic modeling and prediction of cytotoxicity on microelectronic cell sen-sor array,” Canadian Journal of Chemical Engineering, Vol. 86, pp. 393?405, 2006.
[7] J. Z. Xing, L. Zhu, J. A. Jackson, S.Gabos, X. J. Sun, X. B. Wang, and X. Xu, “Dynamic monitoring of cytotoxic-ity on microelectronic sensors,” Chemical Research in Toxicology, Vol. 18, pp. 154?161, 2005.
[8] J. Z. Xing, L. Zhu, S. Gabos, and L. Xie, “Microelec-tronic cell sensor assay for detection of cytotoxicity and prediction of acute toxicity,” Toxicology in Vitro, Vol. 20, pp. 995?1004, 2006.
[9] T. M. Brosnan, “Early warning monitoring to detect haz-ardous events in water supplies,” In An ILSI Risk Sci-ence Institute Workshop Report, 1999.
[10] R. P. Araujo and D. L. S. McElwain, “A history of the study of solid tumour growth: The contribution of mathematical modeling,” Bulletin of Mathematical Biol-ogy, Vol. 66, pp. 1039?1091, 2004.
[11] F. Kozusko and M. Bourdeau, “A unified model of sig-moid tumour growth based on cell proliferation and qui-escence,” Cell Proliferation, Vol. 40, pp. 824?834, 2007.
[12] P. Castorina and D. Zappala, “Tumor gompertzian grow- th by cellular energetic balance,” Physica A, Vol. 365, pp. 473?480, 2006.
[13] J. C. Panetta, “A mathematical model of breast and ovar-ian cancer treated with paclitaxel,” Mathematical Biosci-ence, Vol. 146, pp. 89?113, 1997.
[14] M. Eisen, “Mathematical models in cell biology and can-cer chemotherapy,” Springer 30, New York, 1979.
[15] P. F. Lebowitz and S. M. Swain, “Cancer chemotherapy and biotherapy: Principles and practice,” Fourth Edition, Hormonal Therapy for Brest Cancer, Lippincott Williams and Wilkins, New York, pp. 809?838, 2006.
[16] “Lawrence livermore national laboratory exploring the link between diet and cancer,” https:// www.llnl.gov/ str/ December05/ Kulp.html.
[17] A. W. El-Kareh and T. W. Secomby, “Two-mechanism Peak concentration model for cellular pharmacodynamics of doxorubicin,” Neoplasia, Vol. 7, pp. 705?713, 2005.
[18] R. E. Eliaz, S. Nir, C. Marty, and F. C. Szoka, “Determi-nation and modeling of kinetics of cancer cell killing by doxorubicin and doxorubicin encapsulated in targeted li-posomes,” Cancer Research, Vol. 64, pp. 711?718, 2004.
[19] K. D. Bird, “Analysis of variance via confidence inter-val,” ISBN 0 76196357, SAGE Publication, 2004.

Copyright © 2023 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.