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Development of a Symptom-Based Tool for Screening of Children at High Risk of Preschool Asthma

Despite advances in asthma therapeutics, the burden remains highest in preschool children; therefore, it is critical to identify primary care tools that distinguish preschool children at high risk for burdensome disease for further evaluation.

Biodiesel Exhaust Toxicity with and without Diethylene Glycol Dimethyl Ether Fuel Additive in Primary Airway Epithelial Cells Grown at the Air-Liquid Interface

Biodiesel usage is increasing steadily worldwide as the push for renewable fuel sources increases. The increased oxygen content in biodiesel fuel is believed to cause decreased particulate matter (PM) and increased nitrous oxides within its exhaust.

Lung inflammation and simulated airway resistance in infants with cystic fibrosis

Cystic fibrosis (CF) is characterized by small airway disease; but central airways may also be affected. We hypothesized that airway resistance estimated from computational fluid dynamic (CFD) methodology in infants with CF was higher than controls and that early airway inflammation in infants with CF is associated with airway resistance.

Systems biology and bile acid signalling in microbiome-host interactions in the cystic fibrosis lung

The study of the respiratory microbiota has revealed that the lungs of healthy and diseased individuals harbour distinct microbial communities. Imbalances in these communities can contribute to the pathogenesis of lung disease. How these imbalances occur and establish is largely unknown. This review is focused on the genetically inherited condition of Cystic Fibrosis.

Does machine learning have a role in the prediction of asthma in children?

Asthma is the most common chronic lung disease in childhood. There has been a significant worldwide effort to develop tools/methods to identify children's risk for asthma as early as possible for preventative and early management strategies. Unfortunately, most childhood asthma prediction tools using conventional statistical models have modest accuracy, sensitivity, and positive predictive value.