@article{ErlerRiebeBeitzetal.2020,
  author    = {Erler, Alexander and Riebe, Daniel and Beitz, Toralf and L{\"o}hmannsr{\"o}ben, Hans-Gerd and Grothusheitkamp, Daniela and Kunz, Thomas and Methner, Frank-J{\"u}rgen},
  title     = {Characterization of volatile metabolites formed by molds on barley by mass and ion mobility spectrometry},
  series = {Journal of mass spectrometr},
  volume    = {55},
  journal   = {Journal of mass spectrometr},
  number    = {5},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {1076-5174},
  doi       = {10.1002/jms.4501},
  pages     = {1 -- 10},
  year      = {2020},
  abstract  = {The contamination of barley by molds on the field or in storage leads to the spoilage of grain and the production of mycotoxins, which causes major economic losses in malting facilities and breweries. Therefore, on-site detection of hidden fungus contaminations in grain storages based on the detection of volatile marker compounds is of high interest. In this work, the volatile metabolites of 10 different fungus species are identified by gas chromatography (GC) combined with two complementary mass spectrometric methods, namely, electron impact (EI) and chemical ionization at atmospheric pressure (APCI)-mass spectrometry (MS). The APCI source utilizes soft X-radiation, which enables the selective protonation of the volatile metabolites largely without side reactions. Nearly 80 volatile or semivolatile compounds from different substance classes, namely, alcohols, aldehydes, ketones, carboxylic acids, esters, substituted aromatic compounds, alkenes, terpenes, oxidized terpenes, sesquiterpenes, and oxidized sesquiterpenes, could be identified. The profiles of volatile and semivolatile metabolites of the different fungus species are characteristic of them and allow their safe differentiation. The application of the same GC parameters and APCI source allows a simple method transfer from MS to ion mobility spectrometry (IMS), which permits on-site analyses of grain stores. Characterization of IMS yields limits of detection very similar to those of APCI-MS. Accordingly, more than 90\% of the volatile metabolites found by APCI-MS were also detected in IMS. In addition to different fungus genera, different species of one fungus genus could also be differentiated by GC-IMS.},
  language  = {en}
}
@article{SchomoellerWeisvonBarbyetal.2019,
  author    = {Schom{\"o}ller, Anne and Weis, Katharina and von Barby, Reena and H{\"u}bler, Axel and Mayer, Frank and Erler, Thomas},
  title     = {Restless legs syndrome in childhood and adolescence},
  series = {Somnologie : Schlafforschung und Schlafmedizin ; Organ der Deutschen Gesellschaft f{\"u}r Schlafforschung und Schlafmedizin (DGSM)},
  volume    = {23},
  journal   = {Somnologie : Schlafforschung und Schlafmedizin ; Organ der Deutschen Gesellschaft f{\"u}r Schlafforschung und Schlafmedizin (DGSM)},
  number    = {2},
  publisher = {Springer},
  address   = {Cham},
  issn      = {1432-9123},
  doi       = {10.1007/s11818-018-0188-y},
  pages     = {104 -- 108},
  year      = {2019},
  language  = {en}
}
@article{DunkerBoydDurkaetal.2022,
  author    = {Dunker, Susanne and Boyd, Matthew and Durka, Walter and Erler, Silvio and Harpole, W. Stanley and Henning, Silvia and Herzschuh, Ulrike and Hornick, Thomas and Knight, Tiffany and Lips, Stefan and M{\"a}der, Patrick and Švara, Elena Motivans and Mozarowski, Steven and Rakosy, Demetra and R{\"o}mermann, Christine and Schmitt-Jansen, Mechthild and Stoof-Leichsenring, Kathleen and Stratmann, Frank and Treudler, Regina and Virtanen, Risto and Wendt-Potthoff, Katrin and Wilhelm, Christian},
  title     = {The potential of multispectral imaging flow cytometry for environmental monitoring},
  series = {Cytometry part A},
  volume    = {101},
  journal   = {Cytometry part A},
  number    = {9},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {1552-4922},
  doi       = {10.1002/cyto.a.24658},
  pages     = {782 -- 799},
  year      = {2022},
  abstract  = {Environmental monitoring involves the quantification of microscopic cells and particles such as algae, plant cells, pollen, or fungal spores. Traditional methods using conventional microscopy require expert knowledge, are time-intensive and not well-suited for automated high throughput. Multispectral imaging flow cytometry (MIFC) allows measurement of up to 5000 particles per second from a fluid suspension and can simultaneously capture up to 12 images of every single particle for brightfield and different spectral ranges, with up to 60x magnification. The high throughput of MIFC has high potential for increasing the amount and accuracy of environmental monitoring, such as for plant-pollinator interactions, fossil samples, air, water or food quality that currently rely on manual microscopic methods. Automated recognition of particles and cells is also possible, when MIFC is combined with deep-learning computational techniques. Furthermore, various fluorescence dyes can be used to stain specific parts of the cell to highlight physiological and chemical features including: vitality of pollen or algae, allergen content of individual pollen, surface chemical composition (carbohydrate coating) of cells, DNA- or enzyme-activity staining. Here, we outline the great potential for MIFC in environmental research for a variety of research fields and focal organisms. In addition, we provide best practice recommendations.},
  language  = {en}
}