60 research outputs found

    Electrospray Ionization with High-Resolution Mass Spectrometry as a Tool for Lignomics: Lignin Mass Spectrum Deconvolution

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    Capability to characterize lignin, lignocellulose, and their degradation products is essential for development of new renewable feedstocks. Electrospray ionization high-resolution time-offlight mass spectrometry (ESI HR TOF MS) method was developed expanding the lignomics toolkit while targeting the simultaneous detection of low and high molecular weight (MW) lignin species. The effect of a broad range of electrolytes and various ionization conditions on ion formation and ionization effectiveness was studied using a suite of mono-, di- and triarene lignin model compounds as well as intact lignin. Contrary to the previous studies, the positive ionization mode was found to be more effective for methoxy-substituted arenes and polyphenols, i.e., species of a broadly varied MW structurally similar to the native lignin. For the first time, we report an effective formation of multiply charged species of lignin with the subsequent mass spectrum deconvolution in the presence of 100 mmol·L-1 formic acid in the positive ESI mode. The developed method enabled the detection of lignin species with an MW between 150 and 9,000 Da or higher, depending on the mass analyzer. The obtained Mn and Mw values of 1,500 and 2,500 Da, respectively, were in good agreement with those determined by gel permeation chromatography. Furthermore, the deconvoluted ESI mass spectrum was similar to that obtained with matrixassisted laser desorption/ionization (MALDI) TOF MS, yet featuring a higher signal-to-noise ratio. The formation of multiply charged species was confirmed with ESI ion mobility HR Q-TOF MS

    A dataset of acoustic measurements from soundscapes collected worldwide during the COVID-19 pandemic

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    Political responses to the COVID-19 pandemic led to changes in city soundscapes around the globe. From March to October 2020, a consortium of 261 contributors from 35 countries brought together by the Silent Cities project built a unique soundscape recordings collection to report on local acoustic changes in urban areas. We present this collection here, along with metadata including observational descriptions of the local areas from the contributors, open-source environmental data, open-source confinement levels and calculation of acoustic descriptors. We performed a technical validation of the dataset using statistical models run on a subset of manually annotated soundscapes. Results confirmed the large-scale usability of ecoacoustic indices and automatic sound event recognition in the Silent Cities soundscape collection. We expect this dataset to be useful for research in the multidisciplinary field of environmental sciences
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