Age-dependent ventilator-induced lung injury: Mathematical modeling, experimental data, and statistical analysis
| dc.contributor.author | Hay, Quintessa | en |
| dc.contributor.author | Grubb, Christopher | en |
| dc.contributor.author | Minucci, Sarah | en |
| dc.contributor.author | Valentine, Michael S. | en |
| dc.contributor.author | Van Mullekom, Jennifer H. | en |
| dc.contributor.author | Heise, Rebecca L. | en |
| dc.contributor.author | Reynolds, Angela M. | en |
| dc.date.accessioned | 2024-03-13T12:43:11Z | en |
| dc.date.available | 2024-03-13T12:43:11Z | en |
| dc.date.issued | 2024-02-22 | en |
| dc.description.abstract | A variety of pulmonary insults can prompt the need for life-saving mechanical ventilation; however, misuse, prolonged use, or an excessive inflammatory response, can result in ventilator-induced lung injury. Past research has observed an increased instance of respiratory distress in older patients and differences in the inflammatory response. To address this, we performed high pressure ventilation on young (2-3 months) and old (20-25 months) mice for 2 hours and collected data for macrophage phenotypes and lung tissue integrity. Large differences in macrophage activation at baseline and airspace enlargement after ventilation were observed in the old mice. The experimental data was used to determine plausible trajectories for a mathematical model of the inflammatory response to lung injury which includes variables for the innate inflammatory cells and mediators, epithelial cells in varying states, and repair mediators. Classification methods were used to identify influential parameters separating the parameter sets associated with the young or old data and separating the response to ventilation, which was measured by changes in the epithelial state variables. Classification methods ranked parameters involved in repair and damage to the epithelial cells and those associated with classically activated macrophages to be influential. Sensitivity results were used to determine candidate in-silico interventions and these interventions were most impact for transients associated with the old data, specifically those with poorer lung health prior to ventilation. Model results identified dynamics involved in M1 macrophages as a focus for further research, potentially driving the age-dependent differences in all macrophage phenotypes. The model also supported the pro-inflammatory response as a potential indicator of age-dependent differences in response to ventilation. This mathematical model can serve as a baseline model for incorporating other pulmonary injuries. | en |
| dc.description.version | Published version | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.doi | https://doi.org/10.1371/journal.pcbi.1011113 | en |
| dc.identifier.issue | 2 | en |
| dc.identifier.orcid | Van Mullekom, Jennifer [0000-0003-0123-2965] | en |
| dc.identifier.uri | https://hdl.handle.net/10919/118407 | en |
| dc.identifier.volume | 20 | en |
| dc.language.iso | en | en |
| dc.publisher | PLOS | en |
| dc.rights | Creative Commons Attribution 4.0 International | en |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en |
| dc.title | Age-dependent ventilator-induced lung injury: Mathematical modeling, experimental data, and statistical analysis | en |
| dc.title.serial | PLOS Computational Biology | en |
| dc.type | Article - Refereed | en |
| dc.type.dcmitype | Text | en |
| dc.type.other | Article | en |
| pubs.organisational-group | /Virginia Tech | en |
| pubs.organisational-group | /Virginia Tech/Science | en |
| pubs.organisational-group | /Virginia Tech/Science/Statistics | en |