Bigger is faster in the scalable adaptive immune response

Zoonotic pathogens represent a growing global risk, yet the speed of adaptive immune activation across mammalian species remains poorly understood. Despite orders-of-magnitude differences in size and metabolic rate, we show that the time to initiate adaptive immunity is remarkably consistent across species. To understand this invariance, we analyse empirical data showing how the numbers and sizes of lymph nodes scale with body mass, finding that larger animals have both more and larger lymph nodes. Using scaling theory and our mathematical model, we show that larger lymph nodes enable faster search times, conferring an advantage to larger animals that otherwise face slower biological times. This enables mammals to maintain, or even accelerate, the time to initiate the adaptive immune response as body size increases. We validate our analysis in simulations and compare it to empirical data.
, To validate our mathematical model, we implement an agent-based model (ABM), termed the Initial First Contact Time (IFCT) model, using the MASON libraries [1] in Java. The model simulates two types of agents - T cells (searchers) and Dendritic Cells (DCs) (targets). Both are uniformly distributed within a cubic representation of a Lymph Node (LN). LN space is modeled as a continuous Cartesian grid in three dimensions with fixed reflective boundaries.
The IFCT model is run as a discrete-time simulation, with each time step representing one second. At the beginning of each simulation run, a predefined number of T cells and DCs are initialized (see \Cref{tab:inputDataTable}). The positions of DC are static throughout the simulation. T cells, on the other hand, move in each time step with either Brownian motion or a persistent random walk, which was modeled from empirical data in Fricke et al.[2]. We model T cell motion without considering collisions so that T cells pass through each other...., , # Bigger is faster in the scalable adaptive immune response

## Description of the data and file structure

Main folder: IFCT.zip

This repository contains simulated T cell–dendritic cell (DC) initial first-contact time (IFCT) and mean first-contact time (MFCT) data under two different lymph node (LN) volume–mass scaling hypotheses and two different T cell migration modes. All simulations represent a population of naïve T cells searching for a cognate DC inside a 3-D lymph node.

Data are organized by:

LN scaling:

1\. V_M^0.5 — LN volume ∝ M^0.5

2\. V_M^0.67 — LN volume ∝ M^0.67

Migration mode:

1\. BM — Brownian Motion (random walk)

2\. CRW — Correlated Random Walk

DC scaling:

1\. DCConstant — number of DCs does not scale with M

2\. DCHalf — number of DCs scales as M^0.5

Each simulation produces distributions of first-contact times for multiple LN volumes (5 volumes per condition, corresponding to 5 LN sizes), and for 100 stochastic simulations per volume, the V_M^0.67 folder,...,