Spectral deep learning for prediction and prospective validation of functional groups.

State-of-the-art identification of the functional groups present in an unknown chemical entity requires the expertise of a skilled spectroscopist to analyse and interpret Fourier transform infra-red (FTIR), mass spectroscopy (MS) and/or nuclear magnetic resonance (NMR) data. This process can be time-consuming and error-prone, especially for complex chemical entities that are poorly characterised in the literature, or inefficient to use with synthetic robots producing molecules at an accelerated rate. Herein, we introduce a fast, multi-label deep neural network for accurately identifying all the functional groups of unknown compounds using a combination of FTIR and MS spectra. We do not use any database, pre-established rules, procedures, or peak-matching methods. Our trained neural network reveals patterns typically used by human chemists to identify standard groups. Finally, we experimentally validated our neural network, trained on single compounds, to predict functional groups in compound mixtures. Our methodology showcases practical utility for future use in autonomous analytical detection.

Targeting polyamine biosynthesis to stimulate beta cell regeneration in zebrafish.

Type 1 diabetes (T1D) is a disease characterized by destruction of the insulin-producing beta cells. Currently, there remains a critical gap in our understanding of how to reverse or prevent beta cell loss in individuals with T1D. Previous studies in mice discovered that pharmacologically inhibiting polyamine biosynthesis using difluoromethylornithine (DFMO) resulted in preserved beta cell function and mass. Similarly, treatment of non-obese diabetic mice with the tyrosine kinase inhibitor Imatinib mesylate reversed diabetes. The promising findings from these animal studies resulted in the initiation of two separate clinical trials that would repurpose either DFMO (NCT02384889) or Imatinib (NCT01781975) and determine effects on diabetes outcomes; however, whether these drugs directly stimulated beta cell growth remained unknown. To address this, we used the zebrafish model system to determine pharmacological impact on beta cell regeneration. After induction of beta cell death, zebrafish embryos were treated with either DFMO or Imatinib. Neither drug altered whole-body growth or exocrine pancreas length. Embryos treated with Imatinib showed no effect on beta cell regeneration; however, excitingly, DFMO enhanced beta cell regeneration. These data suggest that pharmacological inhibition of polyamine biosynthesis may be a promising therapeutic option to stimulate beta cell regeneration in the setting of diabetes.