How are estimated cellular turnover rates influenced by the dynamics of a source population?
Fig 6
Similar description of the deuterium labelled fraction of CD57
+CD4+ T cells based on different models despite radically different estimated rates. The above plots show the best fits of the two sub-population kinetic heterogeneity model (a), the two sub-population kinetic heterogeneity and the one population ES model (b), and the two sub-population kinetic heterogeneity and the two population ES model (c) to the deuterated-water labelling data of CD57-CD4+ and CD57+CD4+ memory T cells of individual DW02 from Ahmed et al. (2020) [15]. See S1 Text for the system of equations (equation E). The labelling data of the cell populations and the data of the body deuterium concentration were digitized from the original article for re-analysis. The parameters describing the deuterium concentration in the body water of individual DW02 are ,
/day,
, where
is the predicted asymptote of deuterium enrichment in body water,
is the estimated turnover rate of water and
is the estimated initial deuterium concentration in body water. See [15] for the equations. The above fits were based on the assumption that cells differentiate from one population into the other without division, i.e.,
. Note that the vertical axis gives the non-normalized deuterium enrichment (APE; atom percent excess) measured in the population, as was reported in the original work [15].