References of "Schymanski, Emma 50027893"
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See detailAn annotation database for chemicals of emerging concern in exposome research
Meijer, Jeroen; Lamoree, Marja; Hamers, Timo et al

in Environment International (2021), 152

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See detailpatRoon: open source software platform for environmental mass spectrometry based non-target screening
Helmus, Rick; ter Laak, Thomas L.; van Wezel, Annemarie P. et al

in Journal of Cheminformatics (2021), 13(1), 1

Abstract Mass spectrometry based non-target analysis is increasingly adopted in environmental sciences to screen and identify numerous chemicals simultaneously in highly complex samples. However, current ... [more ▼]

Abstract Mass spectrometry based non-target analysis is increasingly adopted in environmental sciences to screen and identify numerous chemicals simultaneously in highly complex samples. However, current data processing software either lack functionality for environmental sciences, solve only part of the workflow, are not openly available and/or are restricted in input data formats. In this paper we present patRoon , a new R based open-source software platform, which provides comprehensive, fully tailored and straightforward non-target analysis workflows. This platform makes the use, evaluation and mixing of well-tested algorithms seamless by harmonizing various common (primarily open) software tools under a consistent interface. In addition patRoon offers various functionality and strategies to simplify and perform automated processing of complex (environmental) data effectively. patRoon implements several effective optimization strategies to significantly reduce computational times. The ability of patRoon to perform time-efficient and automated non-target data annotation of environmental samples is demonstrated with a simple and reproducible workflow using open-access data of spiked samples from a drinking water treatment plant study. In addition, the ability to easily use, combine and evaluate different algorithms was demonstrated for three commonly used feature finding algorithms. This article, combined with already published works, demonstrate that patRoon helps make comprehensive (environmental) non-target analysis readily accessible to a wider community of researchers. [less ▲]

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See detailOccurrence and Distribution of Pharmaceuticals and their Transformation Products in Luxembourgish Surface Waters
Singh, Randolph UL; Lai, Adelene UL; Krier, Jessy UL et al

E-print/Working paper (2021)

This pre-print describes the analysis of pharmaceuticals and their transformation products in surface water samples collected in Luxembourg from 2019 to 2020. Details of the experimental and computational ... [more ▼]

This pre-print describes the analysis of pharmaceuticals and their transformation products in surface water samples collected in Luxembourg from 2019 to 2020. Details of the experimental and computational tools and workflows used are fully described in the manuscript. Links to the suspect lists, codes used, and data files are also provided. [less ▲]

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See detailELIXIR and Toxicology: a community in development
Martens, Marvin; Stierum, Rob; Schymanski, Emma UL et al

in F1000Research (2021), 10

Toxicology has been an active research field for many decades, with academic, industrial and government involvement. Modern omics and computational approaches are changing the field, from merely disease ... [more ▼]

Toxicology has been an active research field for many decades, with academic, industrial and government involvement. Modern omics and computational approaches are changing the field, from merely disease-specific observational models into target-specific predictive models. Traditionally, toxicology has strong links with other fields such as biology, chemistry, pharmacology and medicine. With the rise of synthetic and new engineered materials, alongside ongoing prioritisation needs in chemical risk assessment for existing chemicals, early predictive evaluations are becoming of utmost importance to both scientific and regulatory purposes. ELIXIR is an intergovernmental organisation that brings together life science resources from across Europe. To coordinate the linkage of various life science efforts around modern predictive toxicology, the establishment of a new ELIXIR Community is seen as instrumental. In the past few years, joint efforts, building on incidental overlap, have been piloted in the context of ELIXIR. For example, the EU-ToxRisk, diXa, HeCaToS, transQST, and the nanotoxicology community have worked with the ELIXIR TeSS, Bioschemas, and Compute Platforms and activities. In 2018, a core group of interested parties wrote a proposal, outlining a sketch of what this new ELIXIR Toxicology Community would look like. A recent workshop (held September 30th to October 1st, 2020) extended this into an ELIXIR Toxicology roadmap and a shortlist of limited investment-high gain collaborations to give body to this new community. This Whitepaper outlines the results of these efforts and defines our vision of the ELIXIR Toxicology Community and how it complements other ELIXIR activities. [less ▲]

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See detailRecent analytical methods for risk assessment of emerging contaminants in ecosystems
Bataineh, Mahmoud; Schymanski, Emma UL; Gallampois, Christine M. J.

in Pollution Assessment for Sustainable Practices in Applied Sciences and Engineering (2021)

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See detailDevelopment and Application of Liquid Chromatographic Retention Time Indices in HRMS-Based Suspect and Nontarget Screening
Aalizadeh, Reza; Alygizakis, Nikiforos A.; Schymanski, Emma UL et al

in Analytical Chemistry (2021), 93(33), 11601--11611

There is an increasing need for comparable and harmonized retention times (tR) in liquid chromatography (LC) among different laboratories, to provide supplementary evidence for the identity of compounds ... [more ▼]

There is an increasing need for comparable and harmonized retention times (tR) in liquid chromatography (LC) among different laboratories, to provide supplementary evidence for the identity of compounds in high-resolution mass spectrometry (HRMS)-based suspect and nontarget screening investigations. In this study, a rigorously tested, flexible, and less system-dependent unified retention time index (RTI) approach for LC is presented, based on the calibration of the elution pattern. Two sets of 18 calibrants were selected for each of ESI+ and ESI-based on the maximum overlap with the retention times and chemical similarity indices from a total set of 2123 compounds. The resulting calibration set, with RTI set to range between 1 and 1000, was proposed as the most appropriate RTI system after rigorous evaluation, coordinated by the NORMAN network. The validation of the proposed RTI system was done externally on different instrumentation and LC conditions. The RTI can also be used to check the reproducibility and quality of LC conditions. Two quantitative structure−retention relationship (QSRR)-based models were built based on the developed RTI systems, which assist in the removal of false-positive annotations. The applicability domains of the QSRR models allowed completing the identification process with higher confidence for substances within the domain, while indicating those substances for which results should be treated with caution. The proposed RTI system was used to improve confidence in suspect and nontarget screening and increase the comparability between laboratories as demonstrated for two examples. All RTI-related calculations can be performed online at http://rti.chem.uoa.gr/. [less ▲]

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See detailLIPAD (LRRK2/Luebeck International Parkinson's Disease) Study Protocol: Deep Phenotyping of an International Genetic Cohort
Usnich, Tatiana; Vollstedt, Eva-Juliane; Schell, Nathalie et al

in Frontiers in Neurology (2021), 12

Background: Pathogenic variants in the Leucine-rich repeat kinase 2 ( LRRK2) gene are the most common known monogenic cause of Parkinson's disease (PD). LRRK2 -linked PD is clinically indistinguishable ... [more ▼]

Background: Pathogenic variants in the Leucine-rich repeat kinase 2 ( LRRK2) gene are the most common known monogenic cause of Parkinson's disease (PD). LRRK2 -linked PD is clinically indistinguishable from idiopathic PD and inherited in an autosomal dominant fashion with reduced penetrance and variable expressivity that differ across ethnicities and geographic regions. Objective: To systematically assess clinical signs and symptoms including non-motor features, comorbidities, medication and environmental factors in PD patients, unaffected LRRK2 pathogenic variant carriers, and controls. A further focus is to enable the investigation of modifiers of penetrance and expressivity of LRRK2 pathogenic variants using genetic and environmental data. Methods: Eligible participants are invited for a personal or online examination which comprises completion of a detailed eCRF and collection of blood samples (to obtain DNA, RNA, serum/plasma, immune cells), urine as well as household dust. We plan to enroll 1,000 participants internationally: 300 with LRRK2 -linked PD, 200 with LRRK2 pathogenic variants but without PD, 100 PD patients with pathogenic variants in the GBA or PRKN genes, 200 patients with idiopathic PD, and 200 healthy persons without pathogenic variants. Results: The eCRF consists of an investigator-rated (1 h) and a self-rated (1.5 h) part. The first part includes the Movement Disorder Society Unified Parkinson's Disease Rating, Hoehn \&Yahr, and Schwab \& England Scales, the Brief Smell Identification Test, and Montreal Cognitive Assessment. The self-rating part consists of a PD risk factor, food frequency, autonomic dysfunction, and quality of life questionnaires, the Pittsburgh Sleep Quality Inventory, and the Epworth Sleepiness as well as the Hospital Anxiety and Depression Scales. The first 15 centers have been initiated and the first 150 participants enrolled (as of March 25th, 2021). Conclusions: LIPAD is a large-scale international scientific effort focusing on deep phenotyping of LRRK2 -linked PD and healthy pathogenic variant carriers, including the comparison with additional relatively frequent genetic forms of PD, with a future perspective to identify genetic and environmental modifiers of penetrance and expressivity Clinical Trial Registration: ClinicalTrials.gov , NCT04214509. [less ▲]

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See detailDiscovering Pesticides and their Transformation Products in Luxembourg Waters using Open Cheminformatics Approaches
Krier, Jessy UL; Singh, Randolph UL; Kondic, Todor UL et al

E-print/Working paper (2021)

Abstract 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 ... [more ▼]

Abstract 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://git-r3lab.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 135 potential TP masses in the samples. Further identification of these mass matches was performed using the open source 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 ▲]

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See detailOccurrence and Distribution of Pharmaceuticals and Their Transformation Products in Luxembourgish Surface Waters
Singh, Randolph UL; Lai, Adelene UL; Krier, Jessy UL et al

in ACS Environmental Au (2021)

Pharmaceuticals and their transformation products (TPs) are continuously released into the aquatic environment via anthropogenic activity. To expand knowledge on the presence of pharmaceuticals and their ... [more ▼]

Pharmaceuticals and their transformation products (TPs) are continuously released into the aquatic environment via anthropogenic activity. To expand knowledge on the presence of pharmaceuticals and their known TPs in Luxembourgish rivers, 92 samples collected during routine monitoring events between 2019 and 2020 were investigated using nontarget analysis. Water samples were concentrated using solid-phase extraction and then analyzed using liquid chromatography coupled to a high-resolution mass spectrometer. Suspect screening was performed using several open source computational tools and resources including Shinyscreen (https://git-r3lab.uni.lu/eci/shinyscreen/), MetFrag (https://msbi.ipb-halle.de/MetFrag/), PubChemLite (https://zenodo.org/record/4432124), and MassBank (https://massbank.eu/MassBank/). A total of 94 pharmaceuticals, 88 confirmed at a level 1 confidence (86 of which could be quantified, two compounds too low to be quantified) and six identified at level 2a, were found to be present in Luxembourg rivers. Pharmaceutical TPs (12) were also found at a level 2a confidence. The pharmaceuticals were present at median concentrations up to 214 ng/L, with caffeine having a median concentration of 1424 ng/L. Antihypertensive drugs (15), psychoactive drugs (15), and antimicrobials (eight) were the most detected groups of pharmaceuticals. A spatiotemporal analysis of the data revealed areas with higher concentrations of the pharmaceuticals, as well as differences in pharmaceutical concentrations between 2019 and 2020. The results of this work will help guide activities for improving water management in the country and set baseline data for continuous monitoring and screening efforts, as well as for further open data and software developments. [less ▲]

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See detailRetrospective non-target analysis to support regulatory water monitoring: from masses of interest to recommendations via in silico workflows
Lai, Adelene UL; Singh, Randolph UL; Kovalova, Lubomira et al

in Environmental Sciences Europe (2021), 33(1), 43

Abstract Background Applying non-target analysis (NTA) in regulatory environmental monitoring remains challenging—instead of having exploratory questions, regulators usually already have specific ... [more ▼]

Abstract Background Applying non-target analysis (NTA) in regulatory environmental monitoring remains challenging—instead of having exploratory questions, regulators usually already have specific questions related to environmental protection aims. Additionally, data analysis can seem overwhelming because of the large data volumes and many steps required. This work aimed to establish an open in silico workflow to identify environmental chemical unknowns via retrospective NTA within the scope of a pre-existing Swiss environmental monitoring campaign focusing on industrial chemicals. The research question addressed immediate regulatory priorities: identify pollutants with industrial point sources occurring at the highest intensities over two time points. Samples from 22 wastewater treatment plants obtained in 2018 and measured using liquid chromatography–high resolution mass spectrometry were retrospectively analysed by (i) performing peak-picking to identify masses of interest; (ii) prescreening and quality-controlling spectra, and (iii) tentatively identifying priority “known unknown” pollutants by leveraging environmentally relevant chemical information provided by Swiss, Swedish, EU-wide, and American regulators. This regulator-supplied information was incorporated into MetFrag, an in silico identification tool replete with “post-relaunch” features used here. This study’s unique regulatory context posed challenges in data quality and volume that were directly addressed with the prescreening, quality control, and identification workflow developed. Results One confirmed and 21 tentative identifications were achieved, suggesting the presence of compounds as diverse as manufacturing reagents, adhesives, pesticides, and pharmaceuticals in the samples. More importantly, an in-depth interpretation of the results in the context of environmental regulation and actionable next steps are discussed. The prescreening and quality control workflow is openly accessible within the R package Shinyscreen, and adaptable to any (retrospective) analysis requiring automated quality control of mass spectra and non-target identification, with potential applications in environmental and metabolomics analyses. Conclusions NTA in regulatory monitoring is critical for environmental protection, but bottlenecks in data analysis and results interpretation remain. The prescreening and quality control workflow, and interpretation work performed here are crucial steps towards scaling up NTA for environmental monitoring. [less ▲]

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See detailFAIR-ifying the Exposome Journal: Templates for Chemical Structures and Transformations
Schymanski, Emma UL; Bolton, Evan E.

in Exposome (2021)

Abstract The exposome, the totality of lifetime exposures, is a new and highly complex paradigm for health and disease. Tackling this challenge requires an effort well beyond single individuals or ... [more ▼]

Abstract The exposome, the totality of lifetime exposures, is a new and highly complex paradigm for health and disease. Tackling this challenge requires an effort well beyond single individuals or laboratories, where every piece of the puzzle will be vital. The launch of this new Exposome journal coincides with the evolution of the exposome through its teenage years and into a growing maturity in an increasingly open and FAIR (findable, accessible, interoperable, reusable) world. This letter discusses how both authors and the Exposome journal alike can help increase the FAIRness of the chemical structural information and the associated metadata in the journal, aiming to capture more details about the chemistry of exposomics. The proposed chemical structure template can serve as an interoperable supplementary format that is made accessible through the website and more findable by linking the DOI of this data file to the article DOI metadata, supporting further reuse. An additional Transformations template provides authors with a means to connect predecessor (parent, substrate) molecules to successor (transformation product, metabolite) molecules and thus provide FAIR connections between observed (i.e., experimental) chemical exposures and biological responses, to help improve the public knowledgebase on exposome-related transformations. These connections are vital to extend current biochemical knowledge and to fulfil the current Exposome definition of “the cumulative measure of environmental influences and associated biological responses throughout the lifespan including exposures from the environment, diet, behaviour, and endogenous processes”. [less ▲]

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See detailEmpowering Large Chemical Knowledge Bases for Exposomics: PubChemLite Meets MetFrag
Schymanski, Emma UL; Kondic, Todor UL; Neumann, Steffen et al

E-print/Working paper (2020)

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See detailUpdate on NORMAN-SLE / SusDat for NORMAN-CWG-NTS Meeting (17 Nov 2020)
Schymanski, Emma UL

Scientific Conference (2020, November 17)

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See detailDigital Detective Work: Connecting Cheminformatics, Mass Spectrometry and our Environment (analytica Conference)
Schymanski, Emma UL; Bolton, Evan

Scientific Conference (2020, October 20)

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See detailData Science and Environmental Cheminformatics (SanDAL Workshop, Uni Lu)
Schymanski, Emma UL

Presentation (2020, October 13)

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See detailMeasuring the Environmental Exposome (ISES2020)
Schymanski, Emma UL

Scientific Conference (2020, September 21)

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See detailSchadstoffen auf der Spur mit Umweltcheminformatik
Schymanski, Emma UL

Scientific Conference (2020, September 17)

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