The 3D version of this simulation solves the IL-2 reaction-diffusion equation on an 8×8×8 tissue voxel cube and renders it with instanced 3D spheres you orbit around. This 2D version is not a camera view of that cube — it solves the same class of equation natively on a flat lattice (a monolayer culture dish instead of a 3D tissue block), and renders the whole concentration field directly as a live heatmap you can read at a glance, with no camera needed:
∂C/∂t = D·∇²C + S·[activated Teff] − Vmax·C/(C+Km)
Here ∇² is the 2D five-point Laplacian stencil (four neighbours instead of six), which changes the actual diffusion behaviour of the field — a point source spreads and equilibrates differently on a 2D lattice than in a 3D volume for the same D. The consumption term Vmax·C/(C+Km) is the same saturating Michaelis–Menten CD25 uptake kinetics as the 3D model, with Vmax set by local Treg + Teff density and the avidity slider.
Each effector cell still accumulates a survival "signal" when local C is above a STAT5-signalling threshold and loses it below threshold, undergoing cytokine-withdrawal apoptosis (Bim-mediated) when the signal hits zero. Raise Treg count or avidity and watch the heatmap darken and the surviving effector population collapse — the same equilibrium physics as the 3D model, computed and displayed through a genuinely 2D-native numerical scheme.
- Treg count — number of high-affinity IL-2 sinks on the lattice.
- CD25 avidity — how fast each Treg consumes local IL-2 relative to an effector cell.
- Antigen stimulation — how much IL-2 activated effector cells secrete.
- Tissue diffusion — how quickly IL-2 spreads across the lattice instead of staying locally concentrated.
Real-world relevance: this IL-2-sink mechanism is why low-dose IL-2 therapy (which favors Tregs, whose receptor is far more sensitive) is used to calm autoimmune disease, while high-dose IL-2 (which also reaches lower-affinity receptors on effector/NK cells) is used to boost anti-tumor immunity.