Abstract: The present disclosure relates to computer-implemented systems for identifying a patient with cystic fibrosis as having a high risk for upper respiratory infections or systemic inflammation, based on the patient's stool microbiota. The systems use machine learning models trained with data comprising (a) risk classifications for subjects with cystic fibrosis and (b) stool microbiota information for each of the subjects. The present disclosure also relates to methods of reducing frequency and/or number of upper respiratory infections in a patient with cystic fibrosis. The present disclosure also relates to methods of identifying a patient with cystic fibrosis (CF) as having a high risk for frequent upper respiratory infections or high systemic inflammation based on the patient's stool microbiota.

Abstract: Methods of flash sintering have been developed in which particle are initially coated with thin layers by atomic layer deposition (ALD). Examples are provided in which 8 mol % yttria-stabilized zirconia (8YSZ) particles are coated with small quantities of Al2O3 by particle atomic layer deposition (ALD). Sintered materials that result from the process have been characterized. Sintered materials having unique characteristics are also described.