In order to improve cancer treatments, cancer cell differentiation and immunotherapy are the subjects of several studies in different branches of interdisciplinary sciences. In this work, we develop a new population model that integrates other complementary ones, thus emphasizing the relationship between cancer cells at different differentiation stages and the main immune system cells. For this new system, specific ranges were found where transdifferentiation of differentiated cancer cells can occur. In addition, a specific therapy against cancer stem cells was analysed by simulating cytotoxic cell vaccines. In reference to the latter, the different combinations of parameters that optimize it were studied.
In previous work, we presented a model that integrates cancer cell differentiation and immunotherapy, analysing a particular therapy against cancer stem cells by cytotoxic cell vaccines. As every biological system is exposed to random fluctuations, is important to incorporate stochasticity in the models to adequate their behaviour to experimental observations. Thus, we propose a necessary upgrade to the former model incorporating fluctuations in it. On the one hand, we added multiplicative noise throughout the proposed system, and on the other, we specifically analysed the influence of demographic and multiplicative noise on the parameters of reproduction and death in cancer cells. In both cases, we studied the dynamics for different values of the parameters involved. It was observed that the final number of cancer cells decreases for different combinations of these parameters and noise intensity.
Individual neuron models give a comprehensive explanation of the behavior of the electrical potential of cell membranes. These models were and are a source of constant analysis to understand the functioning of, mainly, the complexity of the brain. In this work, using the Izhikevich model, we propose, analyze and characterize the transmission of a signal between two neurons unidirectionally coupled. Two possible states were characterized (sub-threshold and over-threshold) depending on the values of the signal amplitude, as well also the relationship between the transmitted and received signal taking into account the coupling. Furthermore, the activation of the emitting neuron (its transition from a resting state to spiking state) and the transmission to the receptor neuron were analyzed by adding white noise to the system.
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