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Related Concept Videos

Effects of EDTA on End-Point Detection Methods01:18

Effects of EDTA on End-Point Detection Methods

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Different methods, such as visual observance of metal-ion indicators, spectroscopic techniques, and potentiometric methods, can determine the endpoint of an EDTA titration.
In the visual method, metal-ion indicators (metallochromic dyes), which have distinct colors in their free and complex forms, are added to the mixture to signal the titration's end point. They form stable complexes with metal ions, but these complexes are weaker than the corresponding metal–EDTA complexes. As a...
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High-Performance Data Processing Workflow Incorporating Effect-Directed Analysis for Feature Prioritization in

Tim J H Jonkers1, Jeroen Meijer1,2, Jelle J Vlaanderen2

  • 1Department of Environment & Health, Faculty of Science, Amsterdam Institute of Molecular and Life Sciences, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands.

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This study introduces a streamlined effect-directed analysis (EDA) workflow for identifying bioactive chemicals of emerging concern (CECs). The enhanced method combines high-resolution mass spectrometry and bioassays for efficient, high-throughput screening in various samples.

Keywords:
TTR-bindingantibioticbioassayeffect-directed analysisenvironmentsuspect and nontarget screening

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Area of Science:

  • Environmental Chemistry
  • Toxicology
  • Analytical Chemistry

Background:

  • Effect-directed analysis (EDA) integrates toxicity testing and high-resolution mass spectrometry (HRMS) for detecting chemicals of emerging concern (CECs).
  • Current EDA methods face challenges in consolidating toxicological and chemical data for efficient CEC identification, making the process laborious.
  • High-throughput screening of bioactive CECs in environmental and human samples is crucial for risk assessment.

Purpose of the Study:

  • To develop and validate a robust, high-throughput workflow for effect-directed analysis (EDA) of chemicals of emerging concern (CECs).
  • To integrate advanced identification approaches, including in silico tools, to enhance the accuracy and efficiency of CEC detection.
  • To demonstrate the workflow's applicability across diverse sample types (environmental and human).

Main Methods:

  • A single high-performance liquid chromatography HRMS method was employed for chemical analysis of extracted samples.
  • Chemical features were annotated using suspect screening against multiple reference databases, with quality assessed by an automated scoring system.
  • Extracts were fractionated and tested for bioactivity in parallel bioassays, with subsequent prioritization of bioactive chemical features.

Main Results:

  • The proposed EDA workflow successfully prioritized and identified chemical features linked to bioactive fractions with improved confidence using MetFrag and retention time indices.
  • Annotation quality was consistently high, regardless of using single or multiple technical replicates, indicating robust data.
  • The workflow demonstrated comparability in toxicological and chemical data quality across different sample types.

Conclusions:

  • The integrated EDA workflow offers a significant advancement for the routine, high-throughput identification of CECs in complex matrices.
  • This approach streamlines the process of linking chemical structures to biological activity, aiding in the assessment of emerging environmental and human health risks.
  • The validated workflow paves the way for more efficient monitoring and management of CECs.