Xiaoxu Zhong, Hieu T M Nguyen, Eri Takematsu, Guillem Pratx
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Diffusion-aware compartment model of the cellular uptake of ^{18}F-fluorodeoxyglucose.
Compartment models are widely used in fields such as epidemiology and biomedicine to describe the exchange of uniformly distributed materials between interconnected compartments. However, their application in biological fluids is limited by the assumption of infinitely large diffusivity, especially in environments such as tumors or subcutaneous tissue, where diffusion is considerably lower. To address this, we develop a diffusion-aware compartment model that maintains the simplicity of traditional compartment models while offering greater accuracy. We conducted experiments on the uptake of ^{18}F-fluorodeoxyglucose (FDG), a radionuclide, by cells grown in culture plates and found a good agreement between the measured and predicted cellular radioactivity. We identify two critical dimensionless parameters that compare the amount of FDG (i) replenished by diffusion and (ii) available in the culture medium to the amount of FDG taken up by cells. We demonstrate that the diffusion-aware compartment model reduces to the three-compartment model when FDG diffusion is fast relative to cellular uptake, and it further simplifies to the two-compartment model when sufficient FDG is available in the culture medium. The semianalytic solutions of the diffusion-aware compartment model can be easily extended to study other scenarios, such as drug transport and bubble growth dynamics.
期刊介绍:
Physical Review E (PRE), broad and interdisciplinary in scope, focuses on collective phenomena of many-body systems, with statistical physics and nonlinear dynamics as the central themes of the journal. Physical Review E publishes recent developments in biological and soft matter physics including granular materials, colloids, complex fluids, liquid crystals, and polymers. The journal covers fluid dynamics and plasma physics and includes sections on computational and interdisciplinary physics, for example, complex networks.