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Stable isotope labelling is one of the best methods currently available for quantifying cell dynamics in vivo, particularly in humans where the absence of toxicity makes it preferable over other techniques such as CFSE or BrdU. Interpretation of stable isotope labelling data (as for BrdU and CFSE) necessitates simplifying assumptions. Here we investigate the impact of three of the most commonly used simplifying assumptions: (i) that the cell population of interest is closed, (ii) that the population of interest is kinetically homogeneous, and (iii) that the population is spatially homogeneous and suggest pragmatic ways in which the resulting errors can be reduced.

More information Original publication

DOI

10.1371/journal.pcbi.1012704

Type

Journal article

Publication Date

2025-06-01T00:00:00+00:00

Volume

21

Keywords

Models, Biological, Humans, Kinetics, Isotope Labeling, Computational Biology, Computer Simulation, Cell Proliferation