Bingshuo, Wang

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Author's Bibliography

Longtime evolution and stationary response of a stochastic tumor-immune system with resting T cells

Bingshuo, Wang; Li, Wei; Zhao, Junfeng; Trišović, Nataša

(AIMS Press Journals, 2024)

TY  - JOUR
AU  - Bingshuo, Wang
AU  - Li, Wei
AU  - Zhao, Junfeng
AU  - Trišović, Nataša
PY  - 2024
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/7738
AB  - In this paper, we take the resting T cells into account and interpret the progression and
regression of tumors by a predator-prey like tumor-immune system. First, we construct an appropriate
Lyapunov function to prove the existence and uniqueness of the global positive solution to the system.
Then, by utilizing the stochastic comparison theorem, we prove the moment boundedness of tumor
cells and two types of T cells. Furthermore, we analyze the impact of stochastic perturbations on the
extinction and persistence of tumor cells and obtain the stationary probability density of the tumor cells
in the persistent state. The results indicate that when the noise intensity of tumor perturbation is low,
tumor cells remain in a persistent state. As this intensity gradually increases, the population of tumors
moves towards a lower level, and the stochastic bifurcation phenomena occurs. When it reaches a
certain threshold, instead the number of tumor cells eventually enter into an extinct state, and further
increasing of the noise intensity will accelerate this process.
PB  - AIMS Press Journals
T2  - Mathematical Biosciences and Engineering, Special Issue: Modelling and investigations of predator-prey dynamics
T1  - Longtime evolution and stationary response of a stochastic tumor-immune system with resting T cells
EP  - 2834
IS  - 2
SP  - 2813
VL  - 21
DO  - 10.3934/mbe.2024125
ER  - 
@article{
author = "Bingshuo, Wang and Li, Wei and Zhao, Junfeng and Trišović, Nataša",
year = "2024",
abstract = "In this paper, we take the resting T cells into account and interpret the progression and
regression of tumors by a predator-prey like tumor-immune system. First, we construct an appropriate
Lyapunov function to prove the existence and uniqueness of the global positive solution to the system.
Then, by utilizing the stochastic comparison theorem, we prove the moment boundedness of tumor
cells and two types of T cells. Furthermore, we analyze the impact of stochastic perturbations on the
extinction and persistence of tumor cells and obtain the stationary probability density of the tumor cells
in the persistent state. The results indicate that when the noise intensity of tumor perturbation is low,
tumor cells remain in a persistent state. As this intensity gradually increases, the population of tumors
moves towards a lower level, and the stochastic bifurcation phenomena occurs. When it reaches a
certain threshold, instead the number of tumor cells eventually enter into an extinct state, and further
increasing of the noise intensity will accelerate this process.",
publisher = "AIMS Press Journals",
journal = "Mathematical Biosciences and Engineering, Special Issue: Modelling and investigations of predator-prey dynamics",
title = "Longtime evolution and stationary response of a stochastic tumor-immune system with resting T cells",
pages = "2834-2813",
number = "2",
volume = "21",
doi = "10.3934/mbe.2024125"
}
Bingshuo, W., Li, W., Zhao, J.,& Trišović, N.. (2024). Longtime evolution and stationary response of a stochastic tumor-immune system with resting T cells. in Mathematical Biosciences and Engineering, Special Issue: Modelling and investigations of predator-prey dynamics
AIMS Press Journals., 21(2), 2813-2834.
https://doi.org/10.3934/mbe.2024125
Bingshuo W, Li W, Zhao J, Trišović N. Longtime evolution and stationary response of a stochastic tumor-immune system with resting T cells. in Mathematical Biosciences and Engineering, Special Issue: Modelling and investigations of predator-prey dynamics. 2024;21(2):2813-2834.
doi:10.3934/mbe.2024125 .
Bingshuo, Wang, Li, Wei, Zhao, Junfeng, Trišović, Nataša, "Longtime evolution and stationary response of a stochastic tumor-immune system with resting T cells" in Mathematical Biosciences and Engineering, Special Issue: Modelling and investigations of predator-prey dynamics, 21, no. 2 (2024):2813-2834,
https://doi.org/10.3934/mbe.2024125 . .