Precision care in the treatment of pediatric asthma.

PURPOSE OF REVIEW: Precision medicine in pediatric asthma involves identification of asthma phenotypes, genetic markers, biomarkers, and biologics that target specific pathways. This review includes a discussion of the efficacy of currently approved biologics for pediatric asthma and most recent advances in biomarker/phenotype identification and genetic associations that affect asthma care. RECENT FINDINGS: Biologics targeting type-2 mediated pathways have shown success in the treatment of moderate to severe asthma in pediatric and adult patients. In comparative studies, dupilumab, an interleukin-4 (IL-4) alpha receptor inhibitor, and mepolizumab, an IL-5 inhibitor, have shown more improvement in asthma exacerbation rates and lung function compared to other biologics such as tezepelumab, omalizumab and benralizumab. Other methods used to categorize asthma treatment response have been investigated and include use of biomarkers such as fractional exhaled nitric oxide (FeNO). Genomic studies are also emerging in precision care for pediatric asthma. SUMMARY: An understanding of underlying immunologic and genetic mechanisms affecting the development of asthma in pediatric patients has resulted in the production of numerous targeted therapies that have led to improvement in lung function and reduced exacerbation burden.

Predicting the composition of red wine blends using an array of multicomponent Peptide-based sensors.

Differential sensing using synthetic receptors as mimics of the mammalian senses of taste and smell is a powerful approach for the analysis of complex mixtures. Herein, we report on the effectiveness of a cross-reactive, supramolecular, peptide-based sensing array in differentiating and predicting the composition of red wine blends. Fifteen blends of Cabernet Sauvignon, Merlot and Cabernet Franc, in addition to the mono varietals, were used in this investigation. Linear Discriminant Analysis (LDA) showed a clear differentiation of blends based on tannin concentration and composition where certain mono varietals like Cabernet Sauvignon seemed to contribute less to the overall characteristics of the blend. Partial Least Squares (PLS) Regression and cross validation were used to build a predictive model for the responses of the receptors to eleven binary blends and the three mono varietals. The optimized model was later used to predict the percentage of each mono varietal in an independent test set composted of four tri-blends with a 15% average error. A partial least square regression model using the mouth-feel and taste descriptive sensory attributes of the wine blends revealed a strong correlation of the receptors to perceived astringency, which is indicative of selective binding to polyphenols in wine.