SORA

Advancing, promoting and sharing knowledge of health through excellence in teaching, clinical practice and research into the prevention and treatment of illness

The impact of model assumptions in interpreting cell kinetic studies

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

[img] PDF Published Version
Available under License Creative Commons Attribution.

Download (9MB)
[img] PDF (S1 Fig) Supporting information
Available under License Creative Commons Attribution.

Download (118kB)
[img] Image (PNG) (S2 Fig) Supporting information
Available under License Creative Commons Attribution.

Download (2MB)
[img] PDF (S3 Fig) Supporting information
Available under License Creative Commons Attribution.

Download (233kB)
[img]
Preview
Image (JPEG) (S4 Fig) Supporting information
Available under License Creative Commons Attribution.

Download (137kB) | Preview
[img] PDF (S5 Fig) Supporting information
Available under License Creative Commons Attribution.

Download (19kB)
[img] PDF (S6 Fig) Supporting information
Available under License Creative Commons Attribution.

Download (20kB)
[img] PDF (S7 Fig) Supporting information
Available under License Creative Commons Attribution.

Download (21kB)
[img] PDF (S8 Fig) Supporting information
Available under License Creative Commons Attribution.

Download (19kB)
[img] PDF (S9 Fig) Supporting information
Available under License Creative Commons Attribution.

Download (20kB)
[img] PDF (S10 Fig) Supporting information
Available under License Creative Commons Attribution.

Download (21kB)
[img] PDF (S11 Fig) Supporting information
Available under License Creative Commons Attribution.

Download (166kB)
[img] PDF (S12 Fig) Supporting information
Available under License Creative Commons Attribution.

Download (6kB)
[img] PDF (S13 Fig) Supporting information
Available under License Creative Commons Attribution.

Download (21kB)
[img] PDF (S1 File) Supporting information
Available under License Creative Commons Attribution.

Download (163kB)
[img] Microsoft Excel (S2 File) Supporting information
Available under License Creative Commons Attribution.

Download (34kB)
[img] PDF (S3 File) Supporting information
Available under License Creative Commons Attribution.

Download (365kB)

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
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
Projects:
Project IDFunderFunder ID
103865Z/14/ZWellcome Trusthttp://dx.doi.org/10.13039/100004440
J007439Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
G1001052Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
317040Seventh Framework Programmehttp://dx.doi.org/10.13039/501100004963
764698Horizon 2020https://doi.org/10.13039/501100007601
15012Leukemia and Lymphona ResearchUNSPECIFIED
URI: https://openaccess.sgul.ac.uk/id/eprint/117604
Publisher's version: https://doi.org/10.1371/journal.pcbi.1012704

Actions (login required)

Edit Item Edit Item