This research develops a physics-based method for measuring lung elasticity from medical imaging to predict which emphysema patients will benefit from lung valve treatment. By creating detailed elasticity maps, the work aims to improve treatment selection, enhance patient outcomes, and provide new quantitative tools for assessing lung health.

This research investigates why blocking an early asthma “alarmin” signal often fails as a treatment. Using mouse models, it reveals that environmental differences—particularly the microbiome—can bypass this signal and still drive asthma. Understanding microbiome health may help predict treatment success and lead to more personalized, effective asthma therapies.