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In this article we describe the setup of a mechanical system that simulate the stochastic propagation process of a brownian particle inside a fluid. Our system consist of a mechanical oscillator coupled to a recipient which is shacked constantly. Inside the recipient we deposit small "fluid particles" that remain in constant agitation. Inside this "fluid" we insert one bigger test Brownian particle (bigger than the fluid particles) over which the small fluid particles exert random stochastic forces. We analyze the zigzag movement of the Brownian particles by filming the motion and using the free software Tracker in order to realize the image analysis. Our results show an excellent qualitative agreement between the predictions of the brownian motion theory and our experimental results. The advantage of introducing in this way the concepts of brownian motion and molecular diffusion is that we can observe by the naked eye this phenomenon happening. [ABSTRACT FROM AUTHOR]

Cell migration plays important roles in the development of multicellular organisms and processes as immune response and in cancer metastasis. We present here a review on cell migration modelling of single cells on a flat substrate. Re-analyses of experimental data evinced a behavior that deviates from the canonical Langevin model of a particle immersed on a viscous fluid that presents a Brownian persistent motion. The proposition of a semi-empirical model yields a diffusive behavior in short-time intervals and fits the experimental data, but challenges velocity definition and the corresponding measurement protocol. The solution is presented on the form of an anisotropic model for cell migration, that considers an additional, internal variable, that accounts for the spatial symmetry break of a migrating cell. The theoretical results yield the proposition of natural units for the problem that allows the collapse of theoretical and experimental curves onto a single parameter family of curves. We also discuss a simulation model for three dimensional cells migrating on a flat substrate. The simulation results are quantitatively validated using the theoretical results. The simulation model is now ready to be used in investigating cell migration in more complex environments, that imply non-linear interactions and require numerical solutions. [ABSTRACT FROM AUTHOR]