Analysis of a Nonlinear Mathematical Model Related to Type 1 Diabetes and Growth Hormone
DOI:
https://doi.org/10.66131/JDSC12202628-36Keywords:
Diabetes, Beta Cells, Growth Hormone, Glucose, Compact Invariant SetsAbstract
In this work, a model of nonlinear ordinary differential equations is studied, this model describes the dynamics between beta cells and the somatotropin hormone, better known as growth hormone. Through the Localization of Invariant Compact Sets (LICS) method, a bounded positive invariant domain is established. The objective of the present analysis is to demonstrate the associated effects of growth hormone on glucose variation in the human body. The importance of using mathematical models in this disease lies in the fact that it offers the advantage of helping to understand the evolution of this disease in different scenarios.
References
Bonilla-Bonilla, J. D., Chávez-Sánchez, L., & Legorreta-Haquet, M. V. “Inmunoterapias y su capacidad de
preservar células beta en la diabetes tipo 1: una revisión de la inmunoterapia actual”. In: Bol. Med. Hosp. Infant.
Mex. 82(4) (2025), 203–218. doi: http://dx.doi.org/10.24875/BMHIM.24000174.
Wan, X-X., Zhang, D-Y., Khan, M. A., Zheng, S-Y., Hu, X-M., Zhang, Q., Yang, R-H. & Xiong, K. “Stem
Cell Transplantation in the Treatment of Type 1 Diabetes Mellitus: From Insulin Replacement to Beta-Cell
Replacement.” In: Front. Endocrinol. 13:859638. (2022), 1–13. doi: https://doi.org/10.3389/fendo.2022.
859638.
Álvarez-Castro, P., Isidro, M. L., & Cordido, F. “Secreción de la hormona del crecimiento en la diabetes mellitus”.
In: Endocrinología y Nutrición 50(5) (2003), 156–161. doi: https://doi.org/10.1016/S1575-0922(03)74519-7.
Bertuzzi, A., Salinari, S., & Mingrone, G. “Insulin granule trafficking in β-cells: mathematical model of glucose-
induced insulin secretion.” In: American Journal of Physiology-Endocrinology and Metabolism 293(1) (2007), E396–
E409. doi: https://doi.org/10.1152/ajpendo.00647.2006.
Lenbury, Y., Ruktamatakul, S., & Amornsamarnkul, S. “Modeling insulin kinetics: responses to a single
oral glucose administration or ambulatory-fed conditions.” In: Bio Systems 59(1) (2001), 15–25. doi: https:
//doi.org/10.1016/s0303-2647(00)00136-2.
Palumbo, P., Ditlevsen, S., Bertuzzi, A., & De Gaetano, A. “Mathematical modeling of the glucose-insulin system:
a review.” In: Mathematical biosciences 244(2) (2013), 69–81. doi: https://doi.org/10.1016/j.mbs.2013.05.006.
Ajmera, I., Swat, M., Laibe, C., Le Novère, N., & Chelliah, V. “The impact of mathematical modeling on the
understanding of diabetes and related complications.” In: CPT: pharmacometrics & systems pharmacology 2(7)
(2013), e54. doi: https://doi.org/10.1038/psp.2013.30.
Topp, B., Promislow, K., deVries, G., Miura, R. M., & Finegood, D. T. “A model of beta-cell mass, insulin,
and glucose kinetics: pathways to diabetes.” In: Journal of theoretical biology 206(4) (2000), 605–619. doi: https:
//doi.org/10.1006/jtbi.2000.2150.
Al Ali, H., Daneshkhah, A., Boutayeb, A., & Mukandavire, Z. “Examining Type 1 Diabetes Mathematical
Models Using Experimental Data.” In: Int. J. Environ. Res. Public Health 19(2) (2022), p. 737. doi: https :
//doi.org/10.3390/ijerph19020737.
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Copyright (c) 2026 Erick Vazquez Perez, Diana Gamboa, Konstantin Starkov

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