The impact of model assumptions in interpreting cell kinetic studies
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.
Authors
- Derek C. Macallan (ORCID: https://orcid.org/0000-0002-3014-7148)
- Ada W. C. Yan (ORCID: https://orcid.org/0000-0001-7456-339X)
- Becca Asquith (ORCID: https://orcid.org/0000-0002-5911-3160)
- Jonas Mackerodt (ORCID: https://orcid.org/0000-0002-2044-179X)
- Robert Busch (ORCID: https://orcid.org/0000-0002-4132-0751)
- Ildar Sadreev
- Yan Zhang (ORCID: https://orcid.org/0000-0003-1233-3219)
Institutions
- St George's, University of London (GB)
- Imperial College London (GB)
- University of Roehampton (GB)
Publication Details
- Journal
- PLoS Computational Biology
- Published
- 2025-06-03
- DOI
- https://doi.org/10.1371/journal.pcbi.1012704
- Primary Topic
- Molecular Biology Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Leukemia and Lymphoma Research
- Wellcome Trust
- Imperial College London
- Medical Research Council
- H2020 European Research Council
- FP7 Ideas: European Research Council