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Abstract Fungal infection of grasses, including rice (Oryza sativa), sorghum (Sorghum bicolor), and barley (Hordeum vulgare), induces the formation and accumulation of flavonoid phytoalexins. In maize (Zea mays), however, investigators have emphasized benzoxazinoid and terpenoid phytoalexins, and comparatively little is known about flavonoid induction in response to pathogens. Here, we examined fungus-elicited flavonoid metabolism in maize and identified key biosynthetic enzymes involved in the formation of O-methylflavonoids. The predominant end products were identified as two tautomers of a 2-hydroxynaringenin-derived compound termed xilonenin, which significantly inhibited the growth of two maize pathogens, Fusarium graminearum and Fusarium verticillioides. Among the biosynthetic enzymes identified were two O-methyltransferases (OMTs), flavonoid OMT 2 (FOMT2), and FOMT4, which demonstrated distinct regiospecificity on a broad spectrum of flavonoid classes. In addition, a cytochrome P450 monooxygenase (CYP) in the CYP93G subfamily was found to serve as a flavanone 2-hydroxylase providing the substrate for FOMT2-catalyzed formation of xilonenin. In summary, maize produces a diverse blend of O-methylflavonoids with antifungal activity upon attack by a broad range of fungi. 

Abstract Generative Adversarial Networks trained on samples of simulated or actual events have been proposed as a way of generating large simulated datasets at a reduced computational cost. In this work, a novel approach to perform the simulation of photodetector signals from the time projection chamber of the EXO-200 experiment is demonstrated. The method is based on a Wasserstein Generative Adversarial Network — a deep learning technique allowing for implicit non-parametric estimation of the population distribution for a given set of objects. Our network is trained on real calibration data using raw scintillation waveforms as input. We find that it is able to produce high-quality simulated waveforms an order of magnitude faster than the traditional simulation approach and, importantly, generalize from the training sample and discern salient high-level features of the data. In particular, the network correctly deduces position dependency of scintillation light response in the detector and correctly recognizes dead photodetector channels. The network output is then integrated into the EXO-200 analysis framework to show that the standard EXO-200 reconstruction routine processes the simulated waveforms to produce energy distributions comparable to that of real waveforms. Finally, the remaining discrepancies and potential ways to improve the approach further are highlighted. 

Abstract Liquid xenon time projection chambers are promising detectors to search for neutrinoless double beta decay (0 $$\nu \beta \beta $$ ν β β ), due to their response uniformity, monolithic sensitive volume, scalability to large target masses, and suitability for extremely low background operations. The nEXO collaboration has designed a tonne-scale time projection chamber that aims to search for 0 $$\nu \beta \beta $$ ν β β of $$^{136}$$ 136 Xe with projected half-life sensitivity of $$1.35\times 10^{28}$$ 1.35 × 10 28  yr. To reach this sensitivity, the design goal for nEXO is $$\le $$ ≤ 1% energy resolution at the decay Q -value ( $$2458.07\pm 0.31$$ 2458.07 ± 0.31  keV). Reaching this resolution requires the efficient collection of both the ionization and scintillation produced in the detector. The nEXO design employs Silicon Photo-Multipliers (SiPMs) to detect the vacuum ultra-violet, 175 nm scintillation light of liquid xenon. This paper reports on the characterization of the newest vacuum ultra-violet sensitive Fondazione Bruno Kessler VUVHD3 SiPMs specifically designed for nEXO, as well as new measurements on new test samples of previously characterised Hamamatsu VUV4 Multi Pixel Photon Counters (MPPCs). Various SiPM and MPPC parameters, such as dark noise, gain, direct crosstalk, correlated avalanches and photon detection efficiency were measured as a function of the applied over voltage and wavelength at liquid xenon temperature (163 K). The results from this study are used to provide updated estimates of the achievable energy resolution at the decay Q -value for the nEXO design.