Yan, AWC; Sadreev, I; Mackerodt, J; Zhang, Y; Macallan, D; Busch, R; Asquith, B
(2025)
The impact of model assumptions in interpreting cell kinetic studies.
PLOS COMPUTATIONAL BIOLOGY, 21 (6).
e1012704.
ISSN 1553-734X
https://doi.org/10.1371/journal.pcbi.1012704
SGUL Authors: Macallan, Derek Clive
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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.
Item Type: | Article | |||||||||||||||||||||
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Additional Information: | Copyright: © 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. | |||||||||||||||||||||
SGUL Research Institute / Research Centre: | Academic Structure > Infection and Immunity Research Institute (INII) | |||||||||||||||||||||
Journal or Publication Title: | PLOS COMPUTATIONAL BIOLOGY | |||||||||||||||||||||
Editors: | Regoes, Roland R | |||||||||||||||||||||
ISSN: | 1553-734X | |||||||||||||||||||||
Language: | en | |||||||||||||||||||||
Publisher License: | Creative Commons: Attribution 4.0 | |||||||||||||||||||||
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URI: | https://openaccess.sgul.ac.uk/id/eprint/117604 | |||||||||||||||||||||
Publisher's version: | https://doi.org/10.1371/journal.pcbi.1012704 |
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