Related Experiment Video
Updated: Aug 4, 2025

Determining the Optimal Inhibitory Frequency for Cancerous Cells Using Tumor Treating Fields TTFields
Published on: May 4, 2017
Hopf bifurcation without parameters in deterministic and stochastic modeling of cancer virotherapy, part II
Tuan Anh Phan1, Jianjun Paul Tian2
1Institute for Modeling Collaboration and Innovation, The University of Idaho, Moscow, Idaho 83844, USA.
Abstract:
In part II, we analyze our stochastic model which incorporates microenvironmental noises and uncertainties related to immune responses. Outcomes of the therapy in our model are largely determined by the infectivity constant, the infection value, and stochastic relative immune clearance rates. The infection value is a universal critical value for immune-free ergodic invariant probability measures and persistence in all cases. Asymptotic behaviors of the stochastic model are similar to those of its deterministic counterpart. Our stochastic model displays an interesting dynamical behavior, stochastic Hopf bifurcation without parameters, which is a new phenomenon. We perform numerical study to demonstrate how stochastic Hopf bifurcation without parameters occurs. In addition, we give biological implications about our analytical results in stochastic setting versus deterministic setting.
More Related Videos
Related Concept Videos
Cancer Therapies
However, cancer treatments can pose several challenges, as therapies used to kill cancer cells are generally also toxic to normal cells. Moreover, cancer cells mutate rapidly and can develop resistance to chemical agents or radiation therapy. Besides, all types of cancer cells may not respond to the same therapy. Some cancer cells respond to one...
Adaptive Mechanisms in Cancer Cells
Some of the advantages that cancer cells have on normal cells include - enhanced ability to divide without terminally differentiating, induce new blood vessel formation,...
Mechanisms of Retrovirus-induced Cancers
Cancer Survival Analysis
Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models
Cancer

