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    <title language="eng">CRM BAM-A001 eCerto data file</title>
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    <title language="eng">FIORA: Local neighborhood-based prediction of compound mass spectra from single fragmentation events</title>
    <abstract language="eng">Non-targeted metabolomics holds great promise for advancing precision medicine and biomarker discovery. However, identifying compounds from tandem mass spectra remains a challenging task due to the incomplete nature of spectral reference libraries. Augmenting these libraries with simulated mass spectra can provide the necessary references to resolve unmatched spectra, but generating high-quality data is difficult. In this study, we present FIORA, an open-source graph neural network designed to simulate tandem mass spectra. Our main contribution lies in utilizing the molecular neighborhood of bonds to learn breaking patterns and derive fragment ion probabilities. FIORA not only surpasses state-of-the-art fragmentation algorithms, ICEBERG and CFM-ID, in prediction quality, but also facilitates the prediction of additional features, such as retention time and collision cross section. Utilizing GPU acceleration, FIORA enables rapid validation of putative compound annotations and large-scale expansion of spectral reference libraries with high-quality predictions.</abstract>
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    <enrichment key="date_peer_review">24.03.2025</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Yannek Nowatzky</author>
    <author>Francesco Friedrich Russo</author>
    <author>Jan Lisec</author>
    <author>Alexander Kister</author>
    <author>Knut Reinert</author>
    <author>Thilo Muth</author>
    <author>Philipp Benner</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Metabolomics</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Machine Learning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mass spectrometry</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Bioinformatics</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="institutes" number="">1 Analytische Chemie; Referenzmaterialien</collection>
    <collection role="institutes" number="">1.7 Organische Spuren- und Lebensmittelanalytik</collection>
    <collection role="themenfelder" number="">Chemie und Prozesstechnik</collection>
    <collection role="themenfelder" number="">Chemische Charakterisierung und Spurenanalytik</collection>
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    <collection role="institutes" number="">VP.1 eScience</collection>
    <thesisPublisher>Bundesanstalt für Materialforschung und -prüfung (BAM)</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-bam/files/62758/s41467-025-57422-4-1.pdf</file>
  </doc>
  <doc>
    <id>50721</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>3141</pageFirst>
    <pageLast>3152</pageLast>
    <pageNumber/>
    <edition/>
    <issue>13</issue>
    <volume>412</volume>
    <type>article</type>
    <publisherName>Springer</publisherName>
    <publisherPlace/>
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    <contributingCorporation/>
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    <title language="eng">Structural annotation of electro- and photochemically generated transformation products of moxidectin using high-resolution mass spectrometry</title>
    <abstract language="eng">Moxidectin (MOX) is a widely used anthelmintic drug for the treatment of internal and external parasites in food-producing and companion animals. Transformation products (TPs) of MOX, formed through metabolic degradation or acid hydrolysis, May pose a potential environmental risk, but only few were identified so far. In this study, we therefore systematically characterized electro- and photochemically generatedMOX TPs using high-resolution mass spectrometry (HRMS). Oxidative electrochemical (EC) TPs were generated in an electrochemical reactor and photochemical (PC) TPs by irradiation with UV-C light. Subsequent HRMS measurements were performed to identify accuratemasses and deduce occurring modification reactions of derived TPs in a suspected target analysis. In total, 26 EC TPs and 59 PC TPs were found. The main modification reactions were hydroxylation, (de-)hydration, and derivative formation with methanol for EC experiments and isomeric changes, (de-)hydration, and changes at the methoxime moiety for PC experiments. In addition, several combinations of different modification reactions were identified.&#13;
For 17 TPs, we could predict chemical structures through interpretation of acquired MS/MS data. Most modifications could be linked to two specific regions of MOX. Some previously described metabolic reactions like hydroxylation or O-demethylation were confirmed in our EC and PC experiments as reaction type, but the corresponding TPs were not identical to known metabolites or degradation products. The obtained knowledge regarding novel TPs and reactions will aid to elucidate the degradation pathway of MOX which is currently unknown.</abstract>
    <parentTitle language="eng">Analytical and Bioanalytical Chemistry</parentTitle>
    <identifier type="doi">10.1007/s00216-020-02572-1</identifier>
    <enrichment key="date_peer_review">06.05.2020</enrichment>
    <author>Lisa Kotthoff</author>
    <author>S.-L. O’Callaghan</author>
    <author>Jan Lisec</author>
    <author>T. Schwerdtle</author>
    <author>Matthias Koch</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Moxidectin</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Transformation products</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Electrochemical Reactor</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="institutes" number="">1 Analytische Chemie; Referenzmaterialien</collection>
    <collection role="institutes" number="">1.7 Organische Spuren- und Lebensmittelanalytik</collection>
    <collection role="themenfelder" number="">Chemie und Prozesstechnik</collection>
    <collection role="themenfelder" number="">Chemische Charakterisierung und Spurenanalytik</collection>
    <collection role="literaturgattung" number="">Verlagsliteratur</collection>
    <collection role="fulltextaccess" number="">Datei im Netzwerk der BAM verfügbar ("Closed Access")</collection>
  </doc>
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    <id>55391</id>
    <completedYear/>
    <publishedYear>2022</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>10</pageLast>
    <pageNumber/>
    <edition/>
    <issue>18</issue>
    <volume>36</volume>
    <type>article</type>
    <publisherName>Wiley online library</publisherName>
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    <title language="eng">Analysis of electrochemical and liver microsomal transformation products of lasalocid by LC/HRMS</title>
    <abstract language="eng">Rationale: Lasalocid (LAS), an ionophore, is used in cattle and poultry farming as feed additive for its antibiotic and growth-promoting properties. Literature on transformation products (TP) resulting from LAS degradation is limited. So far, only hydroxylation is found to occur as the metabolic reaction during the LAS degradation. To investigate potential TPs of LAS, we used  electrochemistry (EC) and liver microsome (LM) assays to synthesize TPs, which were identified using liquid chromatography high-resolution mass spectrometry (LC/HRMS).&#13;
Methods: Electrochemically produced TPs were analyzed online by direct coupling of the electrochemical cell to the electrospray ionization (ESI) source of a Sciex Triple-TOF high resolution mass spectrometer. Then, EC-treated LAS solution was collected and analyzed offline using LC/HRMS to confirm stable TPs and improve their annotation with a chemical structure due to informative MS/MS spectra. In a complementary approach, TPs formed by rat and human microsomal incubation were investigated using LC/HRMS. The resulting data were used to investigate LAS modification reactions and elucidate the chemical structure of obtained TPs.&#13;
Results: The online measurements identified a broad variety of TPs, resulting from modification reactions like (de-)hydrogenation, hydration, methylation, oxidation as well as adduct formation with methanol. We consistently observed different ion complexations of LAS and LAS-TPs (Na+; 2Na+ K+; NaNH4 +; KNH4 +). Two stable methylated EC-TPs were found, structurally annotated, and assigned to a likely modification reaction. Using LM incubation, seven TPs were formed, mostly by oxidation/hydroxylation. After the identification of LM-TPs as Na+-complexes, we identified LM-TPs as K+-complexes.&#13;
Conclusion: We identified and characterized TPs of LAS using EC- and LM-based methods. Moreover, we found different ion complexes of LAS-based TPs. This knowledge, especially the different ion complexes, may help elucidate the metabolic and environmental degradation pathways of LAS.</abstract>
    <parentTitle language="eng">Rapid Commun Mass Spectrom</parentTitle>
    <identifier type="doi">10.1002/rcm.9349</identifier>
    <identifier type="urn">urn:nbn:de:kobv:b43-553919</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="date_peer_review">27.07.2022</enrichment>
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    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Lisa Knoche</author>
    <author>Jan Lisec</author>
    <author>Matthias Koch</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mass Spectrometry</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Electrochemistry</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>ECR</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Lasalocid</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Ionophore</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Transformation products</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="institutes" number="">1 Analytische Chemie; Referenzmaterialien</collection>
    <collection role="institutes" number="">1.7 Organische Spuren- und Lebensmittelanalytik</collection>
    <collection role="themenfelder" number="">Chemie und Prozesstechnik</collection>
    <collection role="themenfelder" number="">Chemische Charakterisierung und Spurenanalytik</collection>
    <collection role="literaturgattung" number="">Verlagsliteratur</collection>
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    <collection role="unnumberedseries" number="">Wissenschaftliche Artikel der BAM</collection>
    <thesisPublisher>Bundesanstalt für Materialforschung und -prüfung (BAM)</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-bam/files/55391/Knoche2022a.pdf</file>
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  <doc>
    <id>60173</id>
    <completedYear/>
    <publishedYear>2024</publishedYear>
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    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>22</pageLast>
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    <edition/>
    <issue>5</issue>
    <volume>10</volume>
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    <publisherName>MDPI</publisherName>
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    <title language="eng">Changes in Black Truffle (Tuber melanosporum) Aroma during Storage under Different Conditions</title>
    <abstract language="eng">The enticing aroma of truffles is a key factor for their culinary value. Although all truffle species tend to be pricy, the most intensely aromatic species are the most sought after. Research into the aroma of truffles encompasses various disciplines including chemistry, biology, and sensory science. This study focusses on the chemical composition of the aroma of black truffles (Tuber melanosporum) and the changes occurring under different storage conditions. For this, truffle samples were stored under different treatments, at different temperatures, and measured over a total storage time of 12 days. Measurements of the truffle aroma profiles were taken with SPME/GC–MS at regular intervals. To handle the ample data collected, a systematic approach utilizing multivariate data analysis techniques was taken. This approach led to a vast amount of data which we made publicly available for future exploration. Results reveal the complexity of aroma changes, with 695 compounds identified, highlighting the need for a comprehensive understanding. Principal component analyses offer initial insights into truffle composition, while individual compounds may serve as markers for age (formic acid, 1-methylpropyl ester), freshness (2-Methyl-1-propanal; 1-(methylthio)-propane), freezing (tetrahydrofuran), salt treatment (1-chloropentane), or heat exposure (4-hydroxy-3-methyl-2-butanone). This research suggests that heat treatment or salt contact significantly affects truffle aroma, while freezing and cutting have less pronounced effects in comparison. The enrichment of compounds showing significant changes during storage was investigated with a metabolomic pathway analysis. The involvement of some of the enriched compounds on the pyruvate/glycolysis and sulfur pathways was shown.</abstract>
    <parentTitle language="eng">Journal of Fungi</parentTitle>
    <identifier type="doi">10.3390/jof10050354</identifier>
    <identifier type="urn">urn:nbn:de:kobv:b43-601731</identifier>
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This study focusses on the chemical composition of the aroma of black truffles (Tuber melanosporum) and the changes occurring under different storage conditions. For this, truffle samples were stored under different treatments, at different temperatures, and measured over a total storage time of 12 days. Measurements of the truffle aroma profiles were taken with SPME\/GC\u2013MS at regular intervals. To handle the ample data collected, a systematic approach utilizing multivariate data analysis techniques was taken. This approach led to a vast amount of data which we made publicly available for future exploration. Results reveal the complexity of aroma changes, with 695 compounds identified, highlighting the need for a comprehensive understanding. 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(2019). Poverty Reduction Through Non-Timber Forest Products, Springer."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2647","DOI":"10.1111\/1462-2920.12521","article-title":"Bacteria associated with truffle-fruiting bodies contribute to truffle aroma","volume":"17","author":"Splivallo","year":"2015","journal-title":"Environ. Microbiol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1111\/j.1574-6941.2011.01283.x","article-title":"Truffle br\u00fbl\u00e9: An efficient fungal life strategy","volume":"80","author":"Streiblova","year":"2012","journal-title":"FEMS Microbiol. Ecol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1623","DOI":"10.1111\/nph.17259","article-title":"Geographical based variations in white truffle Tuber magnatum truffle aroma is explained by quantitative differences in key volatile compounds","volume":"230","author":"Niimi","year":"2021","journal-title":"New Phytol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"21281","DOI":"10.1038\/s41598-020-76177-0","article-title":"Predicted climate change will increase the truffle cultivation potential in central Europe","volume":"10","author":"Trnka","year":"2020","journal-title":"Sci. Rep."},{"key":"ref_6","unstructured":"Bruhn, J., and Hall, M. (2011). Burgundy Black Truffle Cultivation in an Agroforestry Practice, University of Missouri Extension."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1002\/ffj.3363","article-title":"Does the host tree exert any influence on the aromatic composition of the black truffle (Tuber melanosporum)?","volume":"32","author":"Ferreira","year":"2017","journal-title":"Flavour Fragr. J."},{"key":"ref_8","first-page":"1006","article-title":"Gourmet food, served by dogs","volume":"323","author":"Bohannon","year":"2009","journal-title":"Science"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/S0953-7562(09)80630-8","article-title":"Dimethyl sulphide: The secret for black truffle hunting by animals?","volume":"94","author":"Talou","year":"1990","journal-title":"Mycol. Res."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1007\/s12231-008-9030-y","article-title":"The socioeconomic impact of truffle cultivation in rural Spain","volume":"62","author":"Samils","year":"2008","journal-title":"Econ. Bot."},{"key":"ref_11","unstructured":"Lefevre, C. (2012). Edible Ectomycorrhizal Mushrooms, Springer."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"317","DOI":"10.5424\/fs\/2014232-04771","article-title":"Black truffle cultivation: A global reality","volume":"23","author":"Reyna","year":"2014","journal-title":"For. Syst."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"67","DOI":"10.3354\/cr01494","article-title":"First harvest of P\u00e9rigord black truffle in the UK as a result of climate change","volume":"74","author":"Thomas","year":"2017","journal-title":"Clim. Res."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"688","DOI":"10.1111\/j.1469-8137.2010.03523.x","article-title":"Truffle volatiles: From chemical ecology to aroma biosynthesis","volume":"189","author":"Splivallo","year":"2011","journal-title":"New Phytol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"111434","DOI":"10.1016\/j.fct.2020.111434","article-title":"Species and geographic variability in truffle aromas","volume":"142","author":"Strojnik","year":"2020","journal-title":"Food Chem. Toxicol."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Mustafa, A.M., Angeloni, S., Nzekoue, F.K., Abouelenein, D., Sagratini, G., Caprioli, G., and Torregiani, E. (2020). An Overview on Truffle Aroma and Main Volatile Compounds. 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    <author>Ruben Epping</author>
    <author>Jan Lisec</author>
    <author>Matthias Koch</author>
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      <value>Mass Spectrometry</value>
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      <value>Metabolomics</value>
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      <value>Tuber melanosporum</value>
    </subject>
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      <language>eng</language>
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      <value>Truffle Aroma</value>
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    <title language="eng">LC-HRMS-Based Identification of Transformation Products of the Drug Salinomycin Generated by Electrochemistry and Liver Microsome</title>
    <abstract language="eng">The drug salinomycin (SAL) is a polyether antibiotic and used in veterinary Medicine as coccidiostat and growth promoter. Recently, SAL was suggested as a potential anticancer drug.&#13;
However, transformation products (TPs) resulting from metabolic and environmental degradation of SAL are incompletely known and structural information is missing. In this study, we therefore systematically investigated the formation and identification of SAL derived TPs using electrochemistry (EC) in an electrochemical reactor and rat and human liver microsome incubation (RLM and HLM) as TP generating methods. Liquid chromatography (LC) coupled to high-resolution mass spectrometry (HRMS) was applied to determine accurate masses in a suspected target analysis to identify TPs and to deduce occurring modification reactions of derived TPs. A total of 14 new, structurally different TPs were found (two EC-TPs, five RLM-TPs, and 11 HLM-TPs). The main modification reactions are decarbonylation for EC-TPs and oxidation (hydroxylation) for RLM/HLM-TPs. Of particular interest are potassium-based TPs identified after liver microsome incubation because these might have been overlooked or declared as oxidated sodium adducts in previous, non-HRMS-based studies due to the small mass difference between K and O + Na of 21 mDa. The MS fragmentation pattern of TPs was used to predict the position of identified modifications in the SAL molecule. The obtained knowledge regarding transformation reactions and novel TPs of SAL will contribute to elucidate SAL-metabolites with regards to structural prediction.</abstract>
    <parentTitle language="eng">antibiotics</parentTitle>
    <identifier type="issn">2079-6382</identifier>
    <identifier type="doi">10.3390/antibiotics11020155</identifier>
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    <author>Lisa Knoche</author>
    <author>Jan Lisec</author>
    <author>T. Schwerdtle</author>
    <author>Matthias Koch</author>
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      <value>Salinomycin</value>
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    <subject>
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      <type>uncontrolled</type>
      <value>Ionophore antibiotics</value>
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    <subject>
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      <value>Transformation product</value>
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    <subject>
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      <value>Electrochemistry</value>
    </subject>
    <subject>
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      <value>Rat/human liver microsomes</value>
    </subject>
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      <value>HRMS</value>
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    <title language="eng">Development and Application of Isotope Labelled Internal Standards in a Sum Parameter Method for Ergot Alkaloid Screening of Food</title>
    <abstract language="eng">Ergot alkaloids are a group of toxic compounds, formed by fungi on infested grasses. In 2022, the European Commission set into effect maximum levels for the sum of the twelve major ergot alkaloids in multiple foods. To facilitate the laborious and costly individual quantification of the twelve major ergot alkaloids by HPLC–MS/MS or -FLD, we recently reported a sum parameter method (SPM) for ergot alkaloid quantification. Here, derivatization to lysergic acid hydrazide—a derivative of the mutual ergoline backbone in all ergot alkaloids—allowed simplified determination of all ergot alkaloids in flour via HPLC-FLD. For the measurement of more complex matrices like processed foods, we now developed a MS/MS-based SPM. Two internal standards (IS), isotopically labelled at different positions of the molecule, were synthesized and employed in the MS/MS-measurements. Method performance using either the 13CD3-labelled or the 15N2-labelled IS was evaluated on naturally contaminated rye and wheat flour samples as well as on processed food matrices. Employing the 13CD3-labelled IS leads to lower variances and better consistency with the reference data (obtained by the FLD-based SPM) in flour samples compared to the 15N2-labelled IS. The novel method significantly improves the measurement of ergot alkaloids in complex food matrices, due to their increased selectivity and thus lower interferences. Furthermore, the application of isotope labelled IS obviates the need for time-consuming steps like the determination of recovery rate based, matrix specific correction factors as described in the MS/MS-based European standard method for ergot alkaloid quantification (EN 17425).</abstract>
    <parentTitle language="eng">Food Analytical Methods</parentTitle>
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Methods"],"abstract":"&lt;jats:title&gt;Abstract&lt;\/jats:title&gt;&lt;jats:p&gt;Ergot alkaloids are a group of toxic compounds, formed by fungi on infested grasses. In 2022, the European Commission set into effect maximum levels for the sum of the twelve major ergot alkaloids in multiple foods. To facilitate the laborious and costly individual quantification of the twelve major ergot alkaloids by HPLC\u2013MS\/MS or -FLD, we recently reported a sum parameter method (SPM) for ergot alkaloid quantification. Here, derivatization to lysergic acid hydrazide\u2014a derivative of the mutual ergoline backbone in all ergot alkaloids\u2014allowed simplified determination of all ergot alkaloids in flour via HPLC-FLD. For the measurement of more complex matrices like processed foods, we now developed a MS\/MS-based SPM. Two internal standards (IS), isotopically labelled at different positions of the molecule, were synthesized and employed in the MS\/MS-measurements. 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J Agric Food Chem 30(3):445\u2013450. https:\/\/doi.org\/10.1021\/jf00111a009","journal-title":"J Agric Food Chem"}],"container-title":["Food Analytical Methods"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12161-023-02553-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12161-023-02553-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12161-023-02553-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,18]],"date-time":"2023-11-18T08:28:28Z","timestamp":1700296108000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12161-023-02553-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,18]]},"references-count":18,"alternative-id":["2553"],"URL":"http:\/\/dx.doi.org\/10.1007\/s12161-023-02553-x","relation":{},"ISSN":["1936-9751","1936-976X"],"issn-type":[{"value":"1936-9751","type":"print"},{"value":"1936-976X","type":"electronic"}],"subject":["Safety Research","Safety, Risk, Reliability and Quality","Applied Microbiology and Biotechnology","Food Science","Analytical Chemistry"],"published":{"date-parts":[[2023,11,18]]},"assertion":[{"value":"14 June 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 November 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 November 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Does not apply since neither humans nor animals were involved in this study.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"Maximilian Kuner declares no conflict of interest. Jan Lisec declares no conflict of interest. Marie-Idrissa Picher declares no conflict of interest. Massimo Rigo declares no conflict of interest. J\u00f6rg Konetzki declares no conflict of interest. Hajo Haase declares no conflict of interest. Matthias Koch declares no conflict of interest.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}</enrichment>
    <enrichment key="local_crossrefDocumentType">journal-article</enrichment>
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    <enrichment key="date_peer_review">02.01.2024</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Maximilian Kuner</author>
    <author>Jan Lisec</author>
    <author>Marie-Idrissa Picher</author>
    <author>Massimo Rigo</author>
    <author>Jörg Konetzki</author>
    <author>Hajo Haase</author>
    <author>Matthias Koch</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mycotoxins</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Sum Parameter Method</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Isotope Labelling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>HPLC-MS/MS</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Analytical Chemistry</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Lysergic acid hydrazide</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="institutes" number="">1 Analytische Chemie; Referenzmaterialien</collection>
    <collection role="institutes" number="">1.7 Organische Spuren- und Lebensmittelanalytik</collection>
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    <file>https://opus4.kobv.de/opus4-bam/files/58858/FAM_2023_SumParameter_IS_Ergotalkaloids.pdf</file>
  </doc>
  <doc>
    <id>57396</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>3701</pageFirst>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue>9</issue>
    <volume>28</volume>
    <type>article</type>
    <publisherName>MDPI</publisherName>
    <publisherPlace>Basel</publisherPlace>
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    <contributingCorporation/>
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    <title language="eng">Quantification of Ergot Alkaloids via Lysergic Acid Hydrazide—Development and Comparison of a Sum Parameter Screening Method</title>
    <abstract language="eng">Ergot alkaloids are a group of mycotoxins occurring in products derived from various grasses (e.g., rye) and have been regulated in the EU recently. The new maximum levels refer to the sum of the six most common ergot alkaloids in their two stereoisomeric forms in different food matrices. Typically, these twelve compounds are individually quantified via HPLC-MS/MS or -FLD and subsequently summed up to evaluate food safety in a time-consuming process. Since all these structures share the same ergoline backbone, we developed a novel sum parameter method (SPM) targeting all ergot alkaloids simultaneously via lysergic acid hydrazide. After extraction and clean-up, in analogy to the current European standard method EN 17425 (ESM) for ergot alkaloid quantitation, the samples were derivatized by an optimized hydrazinolysis protocol, which allowed quantitative conversion after 20 min at 100 °C. The new SPM was evaluated against another established HPLC-FLD-based method (LFGB) and the HPLC-MS/MS-based ESM using six naturally contaminated rye and wheat matrix reference materials. While the SPM provided comparable values to the ESM, LFGB showed deviating results. Determined recovery rates, limits of detection and quantification of all three employed methods confirm that the new SPM is a promising alternative to the classical approaches for ergot alkaloid screening in food.</abstract>
    <parentTitle language="eng">Molecules</parentTitle>
    <identifier type="doi">10.3390/molecules28093701</identifier>
    <identifier type="urn">urn:nbn:de:kobv:b43-573968</identifier>
    <identifier type="issn">0015-2684</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="date_peer_review">22.05.2023</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Maximilian Kuner</author>
    <author>Jan Lisec</author>
    <author>Tatjana Mauch</author>
    <author>J. Konetzki</author>
    <author>H. Haase</author>
    <author>Matthias Koch</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Ergot alkaloids</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Sum Parameter</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mycotoxins</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Derivatization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Hydrazinolysis</value>
    </subject>
    <collection role="institutes" number="">1 Analytische Chemie; Referenzmaterialien</collection>
    <collection role="institutes" number="">1.7 Organische Spuren- und Lebensmittelanalytik</collection>
    <collection role="themenfelder" number="">Chemie und Prozesstechnik</collection>
    <collection role="themenfelder" number="">Chemische Charakterisierung und Spurenanalytik</collection>
    <collection role="literaturgattung" number="">Verlagsliteratur</collection>
    <collection role="fulltextaccess" number="">Datei für die Öffentlichkeit verfügbar ("Open Access")</collection>
    <collection role="unnumberedseries" number="">Wissenschaftliche Artikel der BAM</collection>
    <thesisPublisher>Bundesanstalt für Materialforschung und -prüfung (BAM)</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-bam/files/57396/Quantification of Ergot Alkaloids via Lysergic Acid Hydrazide.pdf</file>
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    <publishedYear>2025</publishedYear>
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    <publisherName>GitHub</publisherName>
    <publisherPlace>San Francisco</publisherPlace>
    <creatingCorporation>Bundesanstalt für Materialforschung und -prüfung (BAM)</creatingCorporation>
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    <title language="eng">fioRa</title>
    <abstract language="eng">R package providing a wrapper for the python module 'FIORA' as well as a 'shiny'-App to facilitate data processing and visualization. 'FIORA' allows to predict Mass-Spectra based on the SMILES code of chemical compounds. It is described in the Nature Communications article by Nowatzky et al. (2025).</abstract>
    <identifier type="url">https://github.com/cran/fiora/</identifier>
    <enrichment key="ScientificResourceTypeGeneral">Software</enrichment>
    <enrichment key="ScientificDateCreatedEnd">11.11.2025</enrichment>
    <enrichment key="ScientificGeolocation">Berlin</enrichment>
    <enrichment key="RelatedIdentifier">https://www.nature.com/articles/s41467-025-57422-4</enrichment>
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    <licence>Allgemeines Deutsches Urheberrecht</licence>
    <author>Jan Lisec</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mass Spectrometry</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="institutes" number="">1 Analytische Chemie; Referenzmaterialien</collection>
    <collection role="institutes" number="">1.7 Organische Spuren- und Lebensmittelanalytik</collection>
    <collection role="themenfelder" number="">Chemie und Prozesstechnik</collection>
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    <collection role="institutes" number="">VP Vizepräsident</collection>
    <collection role="institutes" number="">VP.1 eScience</collection>
  </doc>
  <doc>
    <id>50719</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>7157</pageFirst>
    <pageLast/>
    <pageNumber/>
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    <issue>1</issue>
    <volume>10</volume>
    <type>article</type>
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    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">N-Myc-induced metabolic rewiring creates novel therapeutic vulnerabilities in neuroblastoma</title>
    <abstract language="eng">N-Myc is a transcription factor that is aberrantly expressed in many tumor types and is often correlated with poor patient prognosis. Recently, several lines of evidence pointed to the fact that oncogenic activation of Myc family proteins is concomitant with reprogramming of tumor cells to cope with an enhanced need for metabolites during cell growth. These adaptions are driven by the ability of Myc proteins to act as transcriptional amplifiers in a tissue-of-origin specific manner. Here, we describe the effects of N-Myc overexpression on metabolic reprogramming in neuroblastoma cells. Ectopic expression of N-Myc induced a glycolytic switch that was concomitant with enhanced sensitivity towards 2-deoxyglucose, an inhibitor of glycolysis. Moreover, global metabolic profiling revealed extensive alterations in the cellular metabolome resulting from overexpression of N-Myc. Limited supply with either of the two main carbon sources, glucose or glutamine, resulted in distinct shifts in steady-state metabolite levels and significant changes in glutathione metabolism. Interestingly, interference with glutamine-glutamate conversion preferentially blocked proliferation of N-Myc overexpressing cells, when glutamine levels were reduced. Thus, our study uncovered N-Myc induction and nutrient levels as important metabolic master switches in neuroblastoma cells and identified critical nodes that restrict tumor cell proliferation.</abstract>
    <parentTitle language="eng">Scientific Reports</parentTitle>
    <identifier type="doi">10.1038/s41598-020-64040-1</identifier>
    <identifier type="urn">urn:nbn:de:kobv:b43-507193</identifier>
    <enrichment key="date_peer_review">06.05.2020</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>B. Tjaden</author>
    <author>Jan Lisec</author>
    <author>A. Schramm</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mass-Spectrometry</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Cancer</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>MYCN</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="institutes" number="">1 Analytische Chemie; Referenzmaterialien</collection>
    <collection role="institutes" number="">1.7 Organische Spuren- und Lebensmittelanalytik</collection>
    <collection role="themenfelder" number="">Chemie und Prozesstechnik</collection>
    <collection role="themenfelder" number="">Chemische Charakterisierung und Spurenanalytik</collection>
    <collection role="literaturgattung" number="">Verlagsliteratur</collection>
    <collection role="fulltextaccess" number="">Datei für die Öffentlichkeit verfügbar ("Open Access")</collection>
    <collection role="unnumberedseries" number="">Wissenschaftliche Artikel der BAM</collection>
    <thesisPublisher>Bundesanstalt für Materialforschung und -prüfung (BAM)</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-bam/files/50719/Tjaden2020.pdf</file>
  </doc>
  <doc>
    <id>58681</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>24</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>181</volume>
    <type>article</type>
    <publisherName>Elsevier B.V.</publisherName>
    <publisherPlace/>
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    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">What is in the fish? Collaborative trial in suspect and non-target screening of organic micropollutants using LC- and GC-HRMS</title>
    <abstract language="eng">A collaborative trial involving 16 participants from nine European countries was conducted within the NORMAN network in efforts to harmonise suspect and non-target screening of environmental contaminants in whole fish samples of bream (Abramis brama). Participants were provided with freeze-dried, homogenised fish samples from a contaminated and a reference site, extracts (spiked and non-spiked) and reference sample preparation protocols for liquid chromatography (LC) and gas chromatography (GC) coupled to high resolution mass spectrometry (HRMS). Participants extracted fish samples using their in-house sample preparation method and/or the protocol provided. Participants correctly identified 9-69% of spiked compounds using LC-HRMS and 20-60% of spiked compounds using GC-HRMS. From the contaminated site, suspect screening with participants’ own suspect lists led to putative identification of on average ~145 and ~20 unique features per participant using LC-HRMS and GC-HRMS, respectively, while non-target screening identified on average ~42 and ~56 unique features per participant using LC-HRMS and GC-HRMS, respectively. Within the same sub-group of sample preparation method, only a few features were identified by at least two participants in suspect screening (16 features using LC-HRMS, 0 features using GC-HRMS) and non-target screening (0 features using LC-HRMS, 2 features using GC-HRMS). The compounds identified had log octanol/water partition coefficient (KOW) values ranging from -9.9 to 16 and mass-to-charge ratio (m/z) of 68 to 761 (LC-HRMS and GC-HRMS). A significant linear trend was found between log KOW and m/z for the GC-HRMS data. Overall, these findings indicate that differences in screening results are mainly due to the data analysis workflows used by different participants. Further work is needed to harmonise the results obtained when applying suspect and non-target screening approaches to environmental biota samples.</abstract>
    <parentTitle language="eng">Environment International</parentTitle>
    <identifier type="doi">10.1016/j.envint.2023.108288</identifier>
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Collaborative trial in suspect and non-target screening of organic micropollutants using LC- and GC-HRMS","name":"articletitle","label":"Article Title"},{"value":"Environment International","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.envint.2023.108288","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2023 The Authors. Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"108288"}}</enrichment>
    <enrichment key="local_crossrefDocumentType">journal-article</enrichment>
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    <enrichment key="date_peer_review">13.11.2023</enrichment>
    <author>Wiebke Dürig</author>
    <author>Sofia Lindblad</author>
    <author>Oksana Golovko</author>
    <author>Georgios Gkotsis</author>
    <author>Reza Aalizadeh</author>
    <author>Maria-Christina Nika</author>
    <author>Nikolaos Thomaidis</author>
    <author>Nikiforos A. Alygizakis</author>
    <author>Merle Plassmann</author>
    <author>Peter Haglund</author>
    <author>Qiuguo Fu</author>
    <author>Juliane Hollender</author>
    <author>Jade Chaker</author>
    <author>Arthur David</author>
    <author>Uwe Kunkel</author>
    <author>André Macherius</author>
    <author>Lidia Belova</author>
    <author>Giulia Poma</author>
    <author>Hugues Preud'Homme</author>
    <author>Catherine Munschy</author>
    <author>Yann Aminot</author>
    <author>Carsten Jaeger</author>
    <author>Jan Lisec</author>
    <author>Martin Hansen</author>
    <author>Katrin Vorkamp</author>
    <author>Linyan Zhu</author>
    <author>Francesca Cappelli</author>
    <author>Claudio Roscioli</author>
    <author>Sara Valsecchi</author>
    <author>Renzo Bagnati</author>
    <author>Belén González</author>
    <author>Ailette Prieto</author>
    <author>Olatz Zuloaga</author>
    <author>Ruben Gil-Solsona</author>
    <author>Pablo Gago-Ferrero</author>
    <author>Sara Rodriguez-Mozaz</author>
    <author>Hélène Budzinski</author>
    <author>Marie-Helene Devier</author>
    <author>Georg Dierkes</author>
    <author>Lise Boulard</author>
    <author>Griet Jacobs</author>
    <author>Stefan Voorspoels</author>
    <author>Heinz Rüdel</author>
    <author>Lutz Ahrens</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>General Environmental Science</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Suspect and non-target analysis</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Biota</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Expobome</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Collaborative trial</value>
    </subject>
    <collection role="ddc" number="628">Sanitär- und Kommunaltechnik; Umwelttechnik</collection>
    <collection role="institutes" number="">1 Analytische Chemie; Referenzmaterialien</collection>
    <collection role="institutes" number="">1.7 Organische Spuren- und Lebensmittelanalytik</collection>
    <collection role="institutes" number="">1.8 Umweltanalytik</collection>
    <collection role="themenfelder" number="">Umwelt</collection>
    <collection role="literaturgattung" number="">Verlagsliteratur</collection>
    <collection role="fulltextaccess" number="">Datei im Netzwerk der BAM verfügbar ("Closed Access")</collection>
  </doc>
  <doc>
    <id>56307</id>
    <completedYear/>
    <publishedYear>2022</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>researchdata</type>
    <publisherName>GitHub</publisherName>
    <publisherPlace>San Francisco, CA, USA</publisherPlace>
    <creatingCorporation>Bundesanstalt für Materialforschung und -prüfung (BAM)</creatingCorporation>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">IsoCor</title>
    <abstract language="eng">Despite numerous advantages offered by hyphenation of chromatography and electrokinetic separation methods with multicollector (MC) ICP-MS for isotope analysis, the main limitation of such systems is the decrease in precision and increase in uncertainty due to generation of short transient signals. To minimize this limitation, most authors compare several isotope ratio calculation methods and establish a multi-step data processing routine based on the precision and accuracy of the methods. However, to the best of our knowledge, there is no universal data processing tool available that incorporates all important steps of the treatment of the transient signals. Thus, we introduce a data processing application (App) IsoCor that facilitates automatic calculation of isotope ratios from transient signals and eases selection of the most suitable method. The IsoCor App performs baseline subtraction, peak detection, mass bias correction, isotope ratio calculation and delta calculation. The feasibility and reliability of the App was proven by reproducing the results from isotope analysis of three elements (neodymium, mercury and sulfur) measured on-line via hyphenated systems. The IsoCor App provides trackability of the results to ensure quality control of the analysis.</abstract>
    <identifier type="url">https://github.com/cran/IsoCor/</identifier>
    <enrichment key="ScientificResourceTypeGeneral">Software</enrichment>
    <enrichment key="ScientificNote">Shiny-App zur Analyse von ICP-MS Daten.</enrichment>
    <enrichment key="RelatedIdentifier">https://doi.org/10.1039/D2JA00208F</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Jan Lisec</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Shiny-App</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>ICP-MS</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Software</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="institutes" number="">1 Analytische Chemie; Referenzmaterialien</collection>
    <collection role="institutes" number="">1.1 Anorganische Spurenanalytik</collection>
    <collection role="institutes" number="">1.7 Organische Spuren- und Lebensmittelanalytik</collection>
    <collection role="themenfelder" number="">Chemie und Prozesstechnik</collection>
    <collection role="themenfelder" number="">Chemische Charakterisierung und Spurenanalytik</collection>
    <collection role="fulltextaccess" number="">Datei für die Öffentlichkeit verfügbar ("Open Access")</collection>
    <collection role="literaturgattung" number="">Graue Literatur</collection>
    <collection role="unnumberedseries" number="">Forschungsdatensätze der BAM</collection>
  </doc>
  <doc>
    <id>56192</id>
    <completedYear/>
    <publishedYear>2022</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>researchdata</type>
    <publisherName>GitHub</publisherName>
    <publisherPlace>San Francisco, CA, USA</publisherPlace>
    <creatingCorporation>Bundesanstalt für Materialforschung und -prüfung (BAM)</creatingCorporation>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">ABID</title>
    <abstract language="eng">In order to automate the spectral comparison for larger libraries of antibodies, we developed the online software ABID 2.0. This open-source software determines the number of matching peptides in the fingerprint spectra. We propose that publications and other documents critically relying on monoclonal antibodies with unknown amino acid sequences should include at least one antibody fingerprint. By fingerprinting an antibody in question, its identity can be confirmed by comparison with a library spectrum at any time and context.</abstract>
    <identifier type="url">https://github.com/BAMresearch/ABID</identifier>
    <enrichment key="ScientificResourceTypeGeneral">Software</enrichment>
    <enrichment key="RelatedIdentifier">https://nbn-resolving.org/urn:nbn:de:kobv:b43-547347</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <licence>GNU General Public License v3.0</licence>
    <author>Jan Lisec</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Software</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Antibody</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>MALDI</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="institutes" number="">1 Analytische Chemie; Referenzmaterialien</collection>
    <collection role="institutes" number="">1.5 Proteinanalytik</collection>
    <collection role="institutes" number="">1.7 Organische Spuren- und Lebensmittelanalytik</collection>
    <collection role="themenfelder" number="">Chemie und Prozesstechnik</collection>
    <collection role="fulltextaccess" number="">Datei für die Öffentlichkeit verfügbar ("Open Access")</collection>
    <collection role="literaturgattung" number="">Graue Literatur</collection>
    <collection role="unnumberedseries" number="">Forschungsdatensätze der BAM</collection>
  </doc>
  <doc>
    <id>50720</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>23</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Revisiting the Association between Human Leukocyte Antigen and End-Stage Renal Disease</title>
    <abstract language="eng">Multiple works have studied possible associations between human leukocyte antigen (HLA) alleles and end stage renal disease (ESRD). However, there are several contradictions in these previous works and no consistent HLA associations with ESRD itself have been identified. Most of these works have several limitations, for instance, the population size was too small, or only limited HLA loci were studied. The presented work aims to revisit the association between ESRD and HLA antigens while taking in to account the previously overlooked limitations. Here, we compared the HLA polymorphism (at HLA-A, -B, -C, -DRB1, -DQB1 and DQA1 loci) in ESRD patients (n=497) and controls (n=672). Our data identified several HLA alleles that displayed a significant positive or negative association with ESRD. We also determined whether heterozygosity or homozygosity of the ESRD-associated HLA alleles at different loci could modify the prevalence of the disease. Few HLA allele combinations displayed significant associations with ESRD among which HLA-A*3 –HLA-A*26 combination showed the highest strength of association (OR= 4.488, P≤ 0.05) with ESRD. However, the age of ESRD onset was not affected by HLA allele combinations at different loci. Most of the previous works have studied the association of HLA with ESRD in homogeneous ethnic groups and have interpreted their data accordingly. Here, we also performed an extensive literature analysis to determine whether the association of HLA to ESRD can be similar across different ethnic groups. This analysis showed that at least for certain alleles, the association of HLA to ESRD can be similar in different ethnic groups. For instance, HLA-A*11, HLA-DRB1*11, and HLA-DRB1*4 all showed significant positive associations with ESRD in different ethnic groups. The findings of our study will help in determining possible protective or susceptible roles of various HLA alleles in ESRD.</abstract>
    <parentTitle language="eng">bioRxiv</parentTitle>
    <identifier type="doi">10.1101/2020.03.18.996330</identifier>
    <author>N. Noureen</author>
    <author>F. A. Shah</author>
    <author>Jan Lisec</author>
    <author>H. Usman</author>
    <author>M. Khalid</author>
    <author>R. Munir</author>
    <author>N. Zaidi</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mass-Spectrometry</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>HLA</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Renal disease</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="institutes" number="">1 Analytische Chemie; Referenzmaterialien</collection>
    <collection role="institutes" number="">1.7 Organische Spuren- und Lebensmittelanalytik</collection>
    <collection role="themenfelder" number="">Chemie und Prozesstechnik</collection>
    <collection role="themenfelder" number="">Chemische Charakterisierung und Spurenanalytik</collection>
    <collection role="fulltextaccess" number="">Datei im Netzwerk der BAM verfügbar ("Closed Access")</collection>
    <collection role="literaturgattung" number="">Graue Literatur</collection>
  </doc>
  <doc>
    <id>58902</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>lecture</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">When drowning in data - start swimming</title>
    <abstract language="eng">A presentation on the subject of Automatic Data Processing Skills in Chemistry to Enhance Scientific Research.</abstract>
    <enrichment key="eventName">7th PhD Seminar of the German Working Group for Analytical Spectroscopy (DAAS) in the GDCh Division of Analytical Chemistry</enrichment>
    <enrichment key="eventPlace">Berlin, Germany</enrichment>
    <enrichment key="eventStart">15.11.2023</enrichment>
    <enrichment key="eventEnd">17.11.2023</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="InvitedTalks">1</enrichment>
    <author>Jan Lisec</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Data</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Automation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Programming</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="institutes" number="">1 Analytische Chemie; Referenzmaterialien</collection>
    <collection role="institutes" number="">1.7 Organische Spuren- und Lebensmittelanalytik</collection>
    <collection role="themenfelder" number="">Chemie und Prozesstechnik</collection>
    <collection role="fulltextaccess" number="">Datei im Netzwerk der BAM verfügbar ("Closed Access")</collection>
    <collection role="literaturgattung" number="">Präsentation</collection>
  </doc>
  <doc>
    <id>59596</id>
    <completedYear/>
    <publishedYear>2024</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>lecture</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Metabolomics</title>
    <abstract language="eng">A 90 minutes overview on metabolomics as an analytical method for life sciences.</abstract>
    <enrichment key="eventName">IceBio Network training event</enrichment>
    <enrichment key="eventPlace">Grenoble, France</enrichment>
    <enrichment key="eventStart">29.02.2024</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="InvitedTalks">1</enrichment>
    <author>Jan Lisec</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mass Spectrometry</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Metabolomics</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Data Analyses</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="institutes" number="">1 Analytische Chemie; Referenzmaterialien</collection>
    <collection role="institutes" number="">1.7 Organische Spuren- und Lebensmittelanalytik</collection>
    <collection role="institutes" number="">1.8 Umweltanalytik</collection>
    <collection role="themenfelder" number="">Chemie und Prozesstechnik</collection>
    <collection role="themenfelder" number="">Chemische Charakterisierung und Spurenanalytik</collection>
    <collection role="fulltextaccess" number="">Datei im Netzwerk der BAM verfügbar ("Closed Access")</collection>
    <collection role="literaturgattung" number="">Präsentation</collection>
  </doc>
  <doc>
    <id>52800</id>
    <completedYear/>
    <publishedYear>2021</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>64</pageFirst>
    <pageLast>67</pageLast>
    <pageNumber/>
    <edition/>
    <issue>Juni</issue>
    <volume>69</volume>
    <type>article</type>
    <publisherName>Wiley-VCH</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Mehr Analyten, kleinere Proben</title>
    <abstract language="deu">Molekülmassenspektrometrie entwickelt sich weg von klassischer Target- hin zu Nontarget-Analytik. Elementmassenspektrometrie liefert hohe Ortsauflösung beim Element-Imaging und analysiert einzelne Zellen. Aufgrund der Fortschritte bei den Geräten für Timeof-Flight-Massenspektrometrie mit induktiv gekoppeltem Plasma (ICPToF-MS) lässt sich das gesamte Periodensystem der Elemente in kurzen transienten Signalen quasi-simultan massenspektrometrisch erfassen.</abstract>
    <parentTitle language="deu">Nachrichten aus der Chemie</parentTitle>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Björn Meermann</author>
    <author>Jan Lisec</author>
    <author>Carsten Jaeger</author>
    <author>Jessica Saatz</author>
    <author>Heike Traub</author>
    <author>Marcus von der Au</author>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Massenspektrometrie</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Non-target</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>ICP-ToF-MS</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Laser Ablation/Imaging</value>
    </subject>
    <collection role="ddc" number="543">Analytische Chemie</collection>
    <collection role="institutes" number="">1 Analytische Chemie; Referenzmaterialien</collection>
    <collection role="institutes" number="">1.1 Anorganische Spurenanalytik</collection>
    <collection role="institutes" number="">1.6 Anorganische Referenzmaterialien und Gasanalytik</collection>
    <collection role="institutes" number="">1.7 Organische Spuren- und Lebensmittelanalytik</collection>
    <collection role="institutes" number="">1.8 Umweltanalytik</collection>
    <collection role="themenfelder" number="">Chemie und Prozesstechnik</collection>
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    <title language="eng">CRM BAM-B003 eCerto data file</title>
    <abstract language="eng">Data file (RData) containing measurement data recorded during the production process of the Certified Reference Material BAM-B003 containing  per- and polyfluoroalkyl substances (PFAS) in textiles. The data can be most conveniently openend using the Shiny-App eCerto which is accessible at https://www.bam.de/eCerto.</abstract>
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    <author>Jan Lisec</author>
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    <title language="eng">Proposal NFDI4Chem 2025-2030 In the National Research Data Infrastructure (NFDI) — Our Vision: All Chemists Publish FAIR Data</title>
    <abstract language="eng">The first funding period of NFDI4Chem established a robust foundation for research data management (RDM) in chemistry by promoting FAIR data principles and creating a cohesive infrastructure to capture well-annotated data early in the lab through electronic lab notebooks (ELNs) and making this data available in public repositories. Key achievements include standardised data formats and metadata, a federated repository environment, and improved data visibility and accessibility. Training programs and outreach have significantly increased awareness and adoption of best RDM practices. In the second funding period, the consortium aims to advance these achievements by consolidating this infrastructure, developing a model for its sustainable maintenance and operation, and fostering cultural change for its widespread adoption. Goals include ensuring seamless data workflows from laboratories to open repositories, enhancing interoperability, and supporting innovative research through AI-ready data. The work plan is organised into six task areas (TAs). TA1 (Management) provides leadership and supports all other TAs in achieving their objectives. TA2 (Smart Lab) aims to develop a fully digital research environment, including an ELN as a modular platform. This environment will support data collection, management, storage, analysis, and sharing. Integrating devices and external resources will enable seamless data transfer to repositories. TA3 (Repositories) will consolidate the repository ecosystem. The goal is to integrate repositories into a federated system for better accessibility and interoperability, ensuring long-term data availability and sustainability. TA4 (Metadata, Data Standards, and Publication Standards) focuses on developing and promoting new data and metadata standards in an international community process. This includes applying ontologies to create a semantic foundation for linking research data, making it machine-readable and enabling knowledge graphs. TA5 (Community and Training) is dedicated to fostering a cultural shift towards digital chemistry through continuous engagement, collecting requirements, and providing extensive training and support through workshops and open education resources. It will promote FAIR-compliant machine learning applications, embedding RDM into academic curricula to ensure future scientists are well-versed in these practices. TA6 (Synergies and Cross-Cutting Topics) aims to enhance collaboration across NFDI consortia and beyond. This includes developing ontologies, terminology services, the search service, and other cross-cutting solutions, integrating these developments into existing infrastructure, enabling interdisciplinary data harmonisation and fostering machine learning applications.</abstract>
    <parentTitle language="eng">Research Ideas and Outcomes</parentTitle>
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    <author>Sonja Herres-Pawlis</author>
    <author>Johannes Liermann</author>
    <author>Oliver Koepler</author>
    <author>Christoph Bannwarth</author>
    <author>Theo Bender</author>
    <author>Thomas Bocklitz</author>
    <author>Franziska Boehm</author>
    <author>Christian Bonatto Minella</author>
    <author>Frank Biedermann</author>
    <author>Werner Brack</author>
    <author>Ricardo Cunha</author>
    <author>Paul Czodrowski</author>
    <author>Franziska Eberl</author>
    <author>Thomas Engel</author>
    <author>Albert Engstfeld</author>
    <author>Tillmann G. Fischer</author>
    <author>Pascal Friedrich</author>
    <author>Frank Glorious</author>
    <author>Benjamin Golub</author>
    <author>Christoph Grathwol</author>
    <author>Rainer Haag</author>
    <author>Johannes Hunold</author>
    <author>Christoph Jacob</author>
    <author>Jochen Johannsen</author>
    <author>John Jollife</author>
    <author>Stefan Kast</author>
    <author>Carsten Kettner</author>
    <author>Stefan Kuhn</author>
    <author>Giacomo Lanza</author>
    <author>Jan Lisec</author>
    <author>Georg Manolikakes</author>
    <author>Ricardo Mata</author>
    <author>Jens Meiler</author>
    <author>Matthias Müller</author>
    <author>Ralph Müller-Pfefferkorn</author>
    <author>Jochen Ortmeyer</author>
    <author>Wendy Patterson</author>
    <author>Jürgen Pleiss</author>
    <author>Annalisa Riedel</author>
    <author>Jens Riedel</author>
    <author>Ulrich Schatzschneider</author>
    <author>Leonie Schuster</author>
    <author>Peter Seeberger</author>
    <author>Johann-Nikolaus Seibert</author>
    <author>Peter Stadler</author>
    <author>Kirsten Zeitler</author>
    <subject>
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      <value>Research Data Management</value>
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      <value>FAIR</value>
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    <title language="eng">Recent Advances in Electrochemical Analysis of Phenylurea Herbicides</title>
    <abstract language="eng">Phenylurea herbicides (PUHs) are extensively used in modern agriculture due to their high efficiency in weed control; however, their widespread application has led to persistent environmental contamination and growing public health concerns. Reliable, sensitive, and selective analytical methods are therefore essential for monitoring these compounds in environmental and food matrices. Although several recent reviews have addressed electrochemical sensors and biosensors for a broad range of pollutants, there is currently no dedicated review focusing exclusively on PUHs while integrating electrochemical sensors, biosensors, molecularly imprinted polymers (MIPs), and electrochemical detection coupled with liquid chromatography (LC). This review provides a comprehensive and critical overview of electrochemical strategies developed for the analysis of PUHs. Core electroanalytical techniques, including cyclic voltammetry (CV), differential pulse voltammetry (DPV), square wave voltammetry (SWV), and chronoamperometry (CA), are discussed in terms of their fundamental principles, analytical roles, and suitability for mechanistic investigation, quantitative determination, and rapid screening. Electrochemical impedance spectroscopy (EIS) is also examined, particularly for its application in the characterization of electrode interfaces and in electrochemical biosensor development. Furthermore, the integration of electrochemical methods with mass spectrometry is highlighted as a powerful approach for elucidating redox mechanisms and identifying electrochemical transformation products. More than one hundred electrochemical sensors and biosensors reported between 1993 and 2025 are critically evaluated, with emphasis on electrode materials, surface modification strategies, detection mechanisms, analytical performance, and applicability to real samples. The advantages and limitations of electrochemical sensors, biosensors, and MIP-based platforms are systematically discussed in the context of sensitivity, selectivity, response time, and matrix effects. By synthesizing current advances and identifying remaining challenges, this review aims to provide clear guidance for future research and to support the development of robust, efficient, and application-oriented electrochemical methods for PUHs analysis.</abstract>
    <parentTitle language="eng">Sensors and Actuators Reports</parentTitle>
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