Fig 1.
The model has two compartments: lung tissue and blood. The various circles and boxes represent the different inflammatory cells, mediators, and epithelial cell states. Black arrows represent upregulation or transition and black lines with bars represent inhibition or down-regulation. The blue arrows represent movement between the two compartments, either diffusion based or at a constant rate. The red arrows represent movement from the blood into the lung compartment as a result of epithelial barrier degradation.
Table 1.
Table of model variables with descriptions.
Table 2.
Model parameters with descriptions.
Fig 2.
Summary of data ranges used to select plausible parameter sets.
The plot gives the range of experimental values for M0, M1, and M2 macrophages and airspace enlargement used to assess the numerical simulations for biological plausibility. Each range consists of 3–6 experimental observations since some data points were excluded as outliers. Outliers were defined as those being more than two standard deviations outside the mean.
Fig 3.
Average young and old transients.
The solid blue and red lines plotted within the corresponding shaded bands represent the mean response for the transients associated with each experimental group at each time point. The borders of the surrounding bands encompass the 10th and 90th percentile at each time point. M0%, M1%, and M2% represent the percentage of the macrophage activity that is M0, M1, and M2, respectively. These percentages along with the Ee variable were validated by the experimental data at 0 hours and 2 hours. Due to differences in scale, the variables N and AN also include overlays with just the young mean and percentiles plotted.
Fig 4.
Plausible parameter sets separated by age group and epithelial health.
Separation of plausible sets was made using the Eh variable proportion before and after 2 hours of ventilation. Transients were classified as healthy when Eh > 0.9, moderate when 0.5 < Eh < 0.9, or severe when Eh < 0.5. Corresponding percentages were calculated at each level of separation in the flowchart as a percentage of the previous bin.
Fig 5.
Plots of selected model variables for each representative set.
Transients are plotted for Eh (plot A), Ee (plot B), N (plot C), M0 (plot D), M1 (plot E), and M2 (plot F). Due to the differences in scale, plot C also includes a zoomed in plot of just the young transients for the variable N.
Fig 6.
Scaled variable importance for top 10 predictors.
Plots A-D exhibit scaled importance values for all observations (predicting young or old), the old class (predicting healthy or moderate at time 0), the healthy, young class (predicting moderate or severe after 2 hours), and the healthy, old class (predicting moderate or severe after 2 hours), respectively.
Fig 7.
Normalized local sensitivity values for the top ten parameters in each representative set.
Plots A-F are the sensitivities for the parameter sets grouped in Young H2M, Young H2S, Old H2M, Old H2S, Old M2M, and Old M2S, respectively. Parameters indicated with an asterisk had sensitivities greater than 10% of the maximum sensitivity value for all representative sets.
Table 3.
Variable effects of modulating parameters.
Fig 8.
Eh and Ee model transients with varying parameters for example parameter sets from selected groups.
Each model variable was simulated for the baseline value, a 10% increase, and a 10% decrease for the selected parameter. Plots A-C exhibit transients for the varied parameter br using randomly selected parameter set from the representative groups Young H2S, Old H2S, and Old M2S, respectively. Plots D-F exhibit transients for the varied parameter sd using a randomly selected parameter set from the representative groups Young H2S, Old H2S, and Old M2S, respectively.