Compound heterozygote variants: c.848A > G; p.Glu283Gly and c.890C > T; p.Ala297Val, of Isovaleric acid-CoA dehydrogenase (IVD) gene causing severe Isovaleric acidemia with hyperammonemia.

With the execution of expanded newborn screen (NBS) program nationwide, it is uncommon to see severe hyperammonemia associated with isovaleric acidemia (IVA). We present a seven-day-old boy with severe IVA complicated by hyperammonemia. This child was flagged by NBS at 4 days old, but confirmatory testing was delayed due to COVID19 pandemic and parental skepticism. His parents did not adhere to the leucine-restricted diet as recommended. On day 7, the patient presented to the ER with ammonia of 588 µg/dL. Ammonia subsequently rose to >1000 µg/dL. This child received carnitine, 1 dose of Ammonul (sodium benzoate and sodium phenylacetate), arginine, carglumic acid (Carbaglu) and CRRT. Plasma amino acid assay revealed a glutamine level of 256 µmol/L, which is below the lower limit of normal upon arrival to ER and PICU. The hyperammonemia was corrected in 15 h and with the continued use of carglumic acid for 3 days, there was no rebound of hyperammonemia. However, the patient suffered from bone marrow suppression associated with the organic acidemia and required frequent platelet transfusions, as well as G-CSF for neutropenia. The management of this patient provides supporting evidence of the many theoretic metabolic "facts" including why Ammonul is not helpful in organic acidemias.

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.