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Showing results 21 to 40 of 106
   Molecular mechanisms defining penetrance of LRRK2-associated Parkinson’s disease; Schymanski, Emma  ; Smajic, Semra et alin Medizinische Genetik (2022), 34(2), 103--116 Detailed reference viewed: 111 (3 UL) Discovering pesticides and their TPs in Luxembourg waters using open cheminformatics approaches; ; Kondic, Todor et alin Environment International (2022), 158 The diversity of hundreds of thousands of potential organic pollutants and the lack of (publicly available) information about many of them is a huge challenge for environmental sciences, engineering, and ... [more ▼] The diversity of hundreds of thousands of potential organic pollutants and the lack of (publicly available) information about many of them is a huge challenge for environmental sciences, engineering, and regulation. Suspect screening based on high-resolution liquid chromatography-mass spectrometry (LC-HRMS) has enormous potential to help characterize the presence of these chemicals in our environment, enabling the detection of known and newly emerging pollutants, as well as their potential transformation products (TPs). Here, suspect list creation (focusing on pesticides relevant for Luxembourg, incorporating data sources in 4 languages) was coupled to an automated retrieval of related TPs from PubChem based on high confidence suspect hits, to screen for pesticides and their TPs in Luxembourgish river samples. A computational workflow was established to combine LC-HRMS analysis and pre-screening of the suspects (including automated quality control steps), with spectral annotation to determine which pesticides and, in a second step, their related TPs may be present in the samples. The data analysis with Shinyscreen (https://gitlab.lcsb.uni.lu/eci/shinyscreen/), an open source software developed in house, coupled with custom-made scripts, revealed the presence of 162 potential pesticide masses and 96 potential TP masses in the samples. Further identification of these mass matches was performed using the open source approach MetFrag (https://msbi.ipb-halle.de/MetFrag/). Eventual target analysis of 36 suspects resulted in 31 pesticides and TPs confirmed at Level-1 (highest confidence), and five pesticides and TPs not confirmed due to different retention times. Spatio-temporal analysis of the results showed that TPs and pesticides followed similar trends, with a maximum number of potential detections in July. The highest detections were in the rivers Alzette and Mess and the lowest in the Sûre and Eisch. This study (a) added pesticides, classification information and related TPs into the open domain, (b) developed automated open source retrieval methods - both enhancing FAIRness (Findability, Accessibility, Interoperability and Reusability) of the data and methods; and (c) will directly support “L’Administration de la Gestion de l’Eau” on further monitoring steps in Luxembourg. [less ▲] Detailed reference viewed: 157 (10 UL)Open Access Repository-Scale Propagated Nearest Neighbor Suspect Spectral Library for Untargeted Metabolomics; ; et al Report (2022) Abstract Despite the increasing availability of tandem mass spectrometry (MS/MS) community spectral libraries for untargeted metabolomics over the past decade, the majority of acquired MS/MS spectra ... [more ▼] Abstract Despite the increasing availability of tandem mass spectrometry (MS/MS) community spectral libraries for untargeted metabolomics over the past decade, the majority of acquired MS/MS spectra remain uninterpreted. To further aid in interpreting unannotated spectra, we created a nearest neighbor suspect spectral library, consisting of 87,916 annotated MS/MS spectra derived from hundreds of millions of public MS/MS spectra. Annotations were propagated based on structural relationships to reference molecules using MS/MS-based spectrum alignment. We demonstrate the broad relevance of the nearest neighbor suspect spectral library through representative examples of propagation-based annotation of acylcarnitines, bacterial and plant natural products, and drug metabolism. Our results also highlight how the library can help to better understand an Alzheimer’s brain phenotype. The nearest neighbor suspect spectral library is openly available through the GNPS platform to help investigators hypothesize candidate structures for unknown MS/MS spectra in untargeted metabolomics data. [less ▲] Detailed reference viewed: 77 (1 UL)The NORMAN Suspect List Exchange (NORMAN-SLE): facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometryMohammed Taha, Hiba ; ; et alin Environmental Sciences Europe (2022), 34(1), 104 Abstract Background The NORMAN Association ( https://www.norman-network.com/ ) initiated the NORMAN Suspect List Exchange (NORMAN-SLE https://www.norman-network.com/nds/SLE/ ) in 2015, following the ... [more ▼] Abstract Background The NORMAN Association ( https://www.norman-network.com/ ) initiated the NORMAN Suspect List Exchange (NORMAN-SLE https://www.norman-network.com/nds/SLE/ ) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for “suspect screening” lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide. Results The NORMAN-SLE contains 99 separate suspect list collections (as of May 2022) from over 70 contributors around the world, totalling over 100,000 unique substances. The substance classes include per- and polyfluoroalkyl substances (PFAS), pharmaceuticals, pesticides, natural toxins, high production volume substances covered under the European REACH regulation (EC: 1272/2008), priority contaminants of emerging concern (CECs) and regulatory lists from NORMAN partners. Several lists focus on transformation products (TPs) and complex features detected in the environment with various levels of provenance and structural information. Each list is available for separate download. The merged, curated collection is also available as the NORMAN Substance Database (NORMAN SusDat). Both the NORMAN-SLE and NORMAN SusDat are integrated within the NORMAN Database System (NDS). The individual NORMAN-SLE lists receive digital object identifiers (DOIs) and traceable versioning via a Zenodo community ( https://zenodo.org/communities/norman-sle ), with a total of \textgreater 40,000 unique views, \textgreater 50,000 unique downloads and 40 citations (May 2022). NORMAN-SLE content is progressively integrated into large open chemical databases such as PubChem ( https://pubchem.ncbi.nlm.nih.gov/ ) and the US EPA’s CompTox Chemicals Dashboard ( https://comptox.epa.gov/dashboard/ ), enabling further access to these lists, along with the additional functionality and calculated properties these resources offer. PubChem has also integrated significant annotation content from the NORMAN-SLE, including a classification browser ( 101 ). Conclusions The NORMAN-SLE offers a specialized service for hosting suspect screening lists of relevance for the environmental community in an open, FAIR manner that allows integration with other major chemical resources. These efforts foster the exchange of information between scientists and regulators, supporting the paradigm shift to the “one substance, one assessment” approach. New submissions are welcome via the contacts provided on the NORMAN-SLE website ( https://www.norman-network.com/nds/SLE/ ). [less ▲] Detailed reference viewed: 92 (2 UL)Historical Exposomics and High Resolution Mass SpectrometryAurich, Dagny ; ; Schymanski, Emma in Exposome (2021), 00(0), Awareness of the exposome and its influence on health has increased in the last decade. As past exposures can cause changes in human health many years later, delving into the past is relevant for both ... [more ▼] Awareness of the exposome and its influence on health has increased in the last decade. As past exposures can cause changes in human health many years later, delving into the past is relevant for both diagnostic and prevention purposes, but remains a challenging task. Lifestyle, diet, and socioeconomic information of the past should be well documented and compatible with modern data science methods. While chemical analysis nowadays makes use of high resolution mass spectrometry (HR-MS) for highly sensitive and comprehensive coverage of samples plus retrospective analysis, these data archives are in the very early stages. Since past measurements are often only available for a limited set of chemicals, adding to this knowledge requires careful selection of sample types and sampling sites, which may not always be available. The choice of analytes and analytical methods should be suitable for the study question —which is not always clear in advance in exposomics. Data interpretation and the use of appropriate databases are indispensable for a proper exposure assessment, and as databases and knowledge grow, re-analysis of physically or digitally archived samples could enable “continuous monitoring” efforts. This review focuses on the chemical analytical approaches necessary to capture the complexity of the historical exposome. Various sample types, analytes as well as analyses and data interpretation methods are discussed in relation to chemical exposures, while the connection to health remains in focus. It ends with perspectives and challenges in assessing the historical exposome, discussing how we can “learn from the past” to build a better future. [less ▲] Detailed reference viewed: 148 (22 UL)Finding Small Molecules and their Metabolites in Big DataSchymanski, Emma Presentation (2021, December 15) Detailed reference viewed: 58 (0 UL)Exploring the Exposomewith HPCSchymanski, Emma Presentation (2021, November 10) Detailed reference viewed: 64 (1 UL)Emerging Contaminants, Cheminformatics, Mass Spectrometry and the ExposomeSchymanski, Emma Presentation (2021, October 26) Detailed reference viewed: 56 (0 UL)Chemical contamination of the sea – (management of the knowns and) Research on the unknownsSchymanski, Emma Scientific Conference (2021, October 20) Detailed reference viewed: 50 (0 UL)Update on NORMAN-SusDat NORMAN-SLE (Suspect List Exchange)Schymanski, Emma Scientific Conference (2021, September 14) Detailed reference viewed: 64 (0 UL)Harnessing the Exposome, Cheminformatics and Mass Spectrometry for Clinical MetabolomicsSchymanski, Emma Scientific Conference (2021, September 14) Detailed reference viewed: 59 (0 UL)Identifying Exposome Chemicals: Measured Data Metadata, Metabolism and More …Schymanski, Emma Scientific Conference (2021, September 10) Detailed reference viewed: 57 (0 UL)Cheminformatics and Mass Spectrometry meets Clinical MetabolomicsSchymanski, Emma Scientific Conference (2021, September 01) Detailed reference viewed: 52 (0 UL)Exposome Boot Camp PubChemLite Lab: Cheminformatics for the ExposomeSchymanski, Emma Presentation (2021, July 23) Detailed reference viewed: 58 (0 UL)FAIR chemical structures in the Journal of CheminformaticsSchymanski, Emma ; in Journal of Cheminformatics (2021), 13(1), 50 Abstract The ability to access chemical information openly is an essential part of many scientific disciplines. The Journal of Cheminformatics is leading the way for rigorous, open cheminformatics in many ... [more ▼] Abstract The ability to access chemical information openly is an essential part of many scientific disciplines. The Journal of Cheminformatics is leading the way for rigorous, open cheminformatics in many ways, but there remains room for improvement in primary areas. This letter discusses how both authors and the journal alike can help increase the FAIR ness (Findability, Accessibility, Interoperability, Reusability) of the chemical structural information in the journal. A proposed chemical structure template can serve as an interoperable Additional File format (already accessible ), made more findable by linking the DOI of this data file to the article DOI metadata, supporting further reuse . [less ▲] Detailed reference viewed: 119 (0 UL)Discovering Contaminants their TPs in Luxembourg Waters using Open Cheminformatics ApproachesSchymanski, Emma Presentation (2021, July 02) Detailed reference viewed: 66 (3 UL)Discovering Pesticides, Pharmaceuticals TPs in Luxembourg Waters using Open Cheminformatics Approaches; ; Kondic, Todor et alScientific Conference (2021, June 24) Detailed reference viewed: 112 (3 UL)Open Science @LCSB-ECISchymanski, Emma Presentation (2021, June 17) Detailed reference viewed: 58 (1 UL)Defining a Manageable, Dynamic Chemical Space for ExposomicsSchymanski, Emma Scientific Conference (2021, April 27) Detailed reference viewed: 60 (0 UL)Cheminformatics and the Exposome in Health and DiseaseSchymanski, Emma ; Aurich, Dagny Scientific Conference (2021, April 10) Detailed reference viewed: 65 (4 UL) |
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