Viewing the noise propagation mechanism in a unidirectional transition cascade from the perspective of stability*

Abstract

Noise and noise propagation are inevitable and play a constructive role in various biological processes. The stability of cell homeostasis is also a critical issue. In the unidirectional transition cascade of colon cells, stem cells (SCs) are the source. They differentiate into transit-amplifying cells (TACs), and TACs differentiate into fully differentiated cells (FDCs). Two differentiation processes are irreversible. The stability factor is introduced so that the noise propagation mechanism from the perspective of stability is studied according to the noise propagation formulas. It is found that the value of the stability factor corresponding to the minimum noise in FDCs may be the best choice to enable colon cells to maintain high stability and low noise of the cascade. Moreover, for the source cell, the total noise only includes intrinsic noise; for the downstream cell with self-proliferation capability, the total noise mainly depends on its intrinsic noise and transmitted noise from upstream cells, and its intrinsic noise is dominant. For the downstream cell without self-proliferation capability, the total noise is mainly determined by transmitted noises from upstream cells, and there is a minimum value. This work provides a new approach for studying the mechanism of noise propagation while considering the stability of cell homeostasis in biological systems.

Stochastic optimal control for norovirus transmission dynamics by contaminated food and water

“…The role of stochasticity has a large impact on epidemiology, fluctuations might be random but positively autocorrelated, such that the environment is comparable to the recent past (red noise), or random and uncorrelated with the past (white noise), the stochastic noises, can be analytically calculated by considering aerial image as a probability density function of photons. [18][19][20][21][22] The deterministic and the stochastic modeling techniques are the two main types of approach for epidemic modeling. When it comes to mathematical modelling of biological phenomena, stochastic differential equation models are preferable to deterministic models because they can provide a higher level of realism than their deterministic versions.…”