Space-time fractional diffusion in cell movement models with delay

TL;DR

This paper develops a mathematical model using space-time fractional diffusion equations to describe T cell movement with long pauses and runs, revealing how search strategies and chemokinesis influence target finding efficiency.

Contribution

It introduces a continuous fractional diffusion model derived from microscopic velocity-jump processes that incorporate power-law distributed run and waiting times, tailored for biological cell movement.

Findings

Fractional Laplacians effectively model long-distance cell movements.

Chemokinesis responses can significantly reduce search times.

Numerical experiments validate the model's relevance to biological scenarios.

Abstract

The movement of organisms and cells can be governed by occasional long distance runs, according to an approximate L\'evy walk. For T cells migrating through chronically-infected brain tissue, runs are further interrupted by long pauses, and the aim here is to clarify the form of continuous model equations which describe such movements. Starting from a microscopic velocity-jump model based on experimental observations, we include power-law distributions of run and waiting times and investigate the relevant parabolic limit from a kinetic equation for resting and moving individuals. In biologically relevant regimes we derive nonlocal diffusion equations, including fractional Laplacians in space and fractional time derivatives. Its analysis and numerical experiments shed light on how the searching strategy, and the impact from chemokinesis responses to chemokines, shorten the average time taken to find rare targets in the absence of direct guidance information such as chemotaxis.