ArticleEnvironmental science & technology2022
High-Performance Data Processing Workflow Incorporating Effect-Directed Analysis for Feature Prioritization in Suspect and Nontarget Screening.
Article in Environmental science & technology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- In Vitro Bioassay Evidence for Chemical Mixture Propagation from the Environment to Humans.Environmental science & technology · 2026Article
- Emerging Chemical Hazards in Animal-Derived Foods: From Public Health to Detection and Control Solutions.China CDC weekly · 2026Article
- Combination of Chromatographic and Machine Learning-Driven Virtual Fractionation Identifies Aryl Hydrocarbon Receptor Agonists in Sediments.Environmental science & technology · 2026Article
- Data-Driven Filter for Detector Oscillation Artifacts in Time-of-Flight Mass Spectrometry.Analytical chemistry · 2026Article
- Identification of Emerging Organic Pollutants in Aquatic Environments Under the Omics-Based Framework: A Review.Molecules (Basel, Switzerland) · 2026Review
- Comparison of the phenolic and antioxidant potential of five European herbal remedies by effect-directed analysis using offline two-dimensional liquid chromatography-high resolution mass spectrometry.Analytical and bioanalytical chemistry · 2026Article
- Eco-Friendly Sample Preparation Trends for Exogenous Toxic Organic Compounds in Food: A Sustainable Perspective for LC-MS Analysis.Foods (Basel, Switzerland) · 2026Review
- Emerging flame retardants in the marine environment: A comprehensive review of occurrence, fate and analytical challenges.Eco-Environment & Health · 2025Review
- High-Throughput Effect-Directed Analysis of Androgenic Compounds in Hospital Wastewater: Identifying Effect Drivers through Non-Target Screening Supported by Toxicity Prediction.Environmental science & technology · 2025Article
- Machine Learning-based Classification for the Prioritization of Potentially Hazardous Chemicals with Structural Alerts in Nontarget Screening.Environmental science & technology · 2025Article
- Progress, applications, and challenges in high-throughput effect-directed analysis for toxicity driver identification - is it time for HT-EDA?Analytical and bioanalytical chemistry · 2025Review
- Generic and accurate prediction of retention times in liquid chromatography by post-projection calibration.Communications chemistry · 2024Article
- Mixture Risk Assessment of Complex Real-Life Mixtures-The PANORAMIX Project.International journal of environmental research and public health · 2022Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Effect-directed analysis (EDA) aims at the detection of bioactive chemicals of emerging concern (CECs) by combining toxicity testing and high-resolution mass spectrometry (HRMS). However, consolidation of toxicological and chemical analysis techniques to identify bioactive CECs remains challenging and laborious. In this study, we incorporate state-of-the-art identification approaches in EDA and propose a robust workflow for the high-throughput screening of CECs in environmental and human samples. Three different sample types were extracted and chemically analyzed using a single high-performance liquid chromatography HRMS method. Chemical features were annotated by suspect screening with several reference databases. Annotation quality was assessed using an automated scoring system. In parallel, the extracts were fractionated into 80 micro-fractions each covering a couple of seconds from the chromatogram run and tested for bioactivity in two bioassays. The EDA workflow prioritized and identified chemical features related to bioactive fractions with varying levels of confidence. Confidence levels were improved with the in silico software tools MetFrag and the retention time indices platform. The toxicological and chemical data quality was comparable between the use of single and multiple technical replicates. The proposed workflow incorporating EDA for feature prioritization in suspect and nontarget screening paves the way for the routine identification of CECs in a high-throughput manner.
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