Fig 1.
Model diagram detailing neutrophil phenotypes and critical feedback loops.
The system is divided into modules based on the level at which the interactions occur. The systemic level includes the interactions between the pathogen (P), four neutrophil phenotypes (basal: NB, migratory: NM, killing: NK and killing and migratory: NK/M) and chemokine IL-8. The receptor level interactions include the intracellular dynamics of CXCR-1/2, namely activation, internalization and recycling. Two types of feedback occur between the two levels, active surface receptors can trigger the phenotype conversion of the neutrophils and IL-8 produced at the systemic level triggers the trafficking of the receptors. A CXCR-1/2 independent activation via fMLP is included to model general pro-inflammatory response. The systemic damage (D) indicates the overall damage (direct and indirect) caused by the action of the killer neutrophils.
Table 1.
Initial conditions.
Table 2.
Shared parameter values.
Table 3.
Unique parameter values.
Fig 2.
Posterior distributions of parameters allowed to vary across ensembles.
Each parameter was fit separately to data from surviving and non-surviving animals. Values for the mean, 25th-75th percentile, and 2.5th to 97.5th percentiles are shown. Parameters distributions were compared using a two-sample Kolmogorov-Smirnov test. *p<0.05, **p<0.01, ***p<0.001.
Fig 3.
Simulated model fits with their experimental training data.
Mean (red), 25th-75th percentile (dark blue), and 5th-95th percentile trajectories of the simulated ensemble are shown. Experimental data points are shown in black with error bars representing one standard deviation above and below the mean. Results are shown for surviving (left) and non-surviving (right) animals for all observables with corresponding experimental data; (A) pathogen levels, (B) free IL-8 levels, (C) white blood cell counts, (D) neutrophil elastase / α1-PI complex levels, and (E) creatinine levels.
Fig 4.
Model predictions for neutrophil phenotype dynamics following infection.
Mean (red), 25th-75th percentile (dark blue), and 5th-95th percentile trajectories of the simulated ensemble are shown. Predictions are shown for surviving (left) and non-surviving (right) animals for the four neutrophil phenotypes considered in the model; (A) basal neutrophils, which were calibrated with white blood cell count data, as well as (B) migratory neutrophils, (C) killer neutrophils, and (D) killer/migratory neutrophils for which there is no experimental data.
Fig 5.
Model predictions for maximal levels of each neutrophil phenotype compared across ensembles.
Maximal values for each neutrophil phenotype from each trajectory in both ensembles were recorded. Values for the mean, 25th-75th percentile, and 2.5th to 97.5th percentiles are shown. Distributions were compared using a two sample T-test. *p<0.05, **p<0.01, ***p<0.001.
Fig 6.
Factors affecting cumulative systemic damage.
(A) Cumulative damage seen in survivors and non-survivors. The histograms show the area under the damage curve until 144 hr. The rate parameters were sampled from the generated ensemble for each population. The distribution used for GSA contains 4000 samples for each population. (B-C) Prime drivers of cumulative damage. First order and total effect Sobol’ indices which explained most of the variance are tabulated here for the survivor and non-survivor population respectively. (D) Functional dependence of AUCD on killer cell decay rate for the survivors (S) and non-survivors (NS). The green line has been added for visual guidance of the trend and is based on the mean trend identified by the RS-HDMR component functions. For each population, damage decreases with increase in the decay rate of the killer neutrophil. (E) Prime drivers of cumulative damage for the combined population. (F) Functional dependence of AUCD on CXCR1 induced naïve to killer neutrophil transition rate for the survivors and non-survivors. The green line shows that within the population, damage is not particularly sensitive to the transition rate, but increased transition rate could be responsible for higher damage levels seen in non-surviving population.
Fig 7.
Model diagram showing receptor level treatment implementation.
The extracorporeal treatment introduces a trapped receptor state for CXCR-1/2. This state prevents IL-8 induced phenotype transition, which limits NK generation. The treatment is modeled entirely in the receptor level of model, leaving the systemic level (see Fig 1) unchanged.
Fig 8.
Effects of simulated treatment on animal survival rates.
Survival rates of a simulated population of animals following treatment with the proposed extracorporeal device considering a device-receptor affinity of (A) 1x10-2 M, (B) 1x10-3 M, (C) 1x10-4 M, (D) 1x10-5 M. In all cases the time of treatment was varied between 0 and 12 hours post infection and ended between 0 and 100 hours post infection.