The impact of model assumptions in interpreting cell kinetic studies
File(s)journal.pcbi.1012704.pdf (9.47 MB)
Published version
Author(s)
Type
Journal Article
Abstract
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.
Editor(s)
Regoes, Roland R
Date Issued
2025-06-03
Date Acceptance
2024-12-09
Citation
PLoS Computational Biology, 2025, 21 (6)
ISSN
1553-734X
Publisher
Public Library of Science (PLoS)
Journal / Book Title
PLoS Computational Biology
Volume
21
Issue
6
Copyright Statement
: © 2025 Yan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
License URL
Identifier
10.1371/journal.pcbi.1012704
Subjects
Humans
Isotope Labeling
Computational Biology
Cell Proliferation
Kinetics
Models, Biological
Computer Simulation
Publication Status
Published
Article Number
e1012704
Date Publish Online
2025-06-03