Poster abstracts
Poster number 35 submitted by Jon Fritz
A multiscale model for extracting biophysical parameters of lung surfactant function under oscillating volume conditions
Jonathan R. Fritz (Biophysics Graduate Program), Joshua A. Englert (Division of Pulmonary, Critical Care, and Sleep Medicine; Department of Internal Medicine; College of Medicine; The Ohio State University), Samir N. Ghadiali (Department of Biomedical Engineering; College of Engineering; The Ohio State University)
Abstract:
Lung surfactant, a lipid-protein mixture coating the air-liquid interface of lung alveoli, helps to stabilize the lung during breathing. Surfactant can be obtained by washing the lungs with saline, but analysis of fluid samples requires a surfactometer. Contemporary surfactometers, such as the constrained drop surfactometer (CDS),1 characterize surfactant function by minimum surface tension and surface tension-area (ST-A) loop area. However, these parameters are indirectly related to biophysical properties of lung surfactant. Thus, the goals of this study were to 1) create a model of the CDS to simulate experimental ST-A loops, 2) parameterize in-vitro loops by in-silico biophysical parameters, and 3) phenotype mouse surfactant samples by mechanistic parameters of surfactant function.
COMSOL, a multi-physics software, was used to simulate the CDS. Flux equations were used to simulate surfactant transport while equations of state were used to relate surface tension to surface concentration during oscillations. Based on previous studies,2 we made a CDS with a sharp-edged droplet stage and a camera to record videos of oscillating droplets. A custom MATLAB code was used to analyze droplet shapes1 and produce surface tension-area loops. A commercial surfactant, Infasurf, was used to validate the model. To investigate model applicability to clinically-relevant samples, we isolated then analyzed surfactant from wild-type mice subjected to either K. pneumoniae infection or injurious ventilation.
The model accurately captures the shape of Infasurf with an R2 value of 0.94. The in-silico model can generate diverse loop shapes. Parameter variation studies as well as sensitivity analysis demonstrate the importance of transport and equation-of-state in regulating loop shape. Preliminary results indicate that global metrics such as minimum surface tension are limited, and that by using this model, we can assess biophysical targets for treating surfactant dysfunction post-injury.
References:
1. Valle, R.P. et. al. 2015. ACS Nano. 9(5)5413-21. 2. Rubenfeld, G.D. et. al. 2005. N Engl J Med. 353:1685-1693.
Keywords: lung, model, biophysics