Silicone wristbands offer a non-invasive route to assessing and characterizing human exposure to organic contaminants present in a variety of settings. With a wide range of potential contaminants at varying concentrations and the need for an untargeted acquisition, GC with high-resolution mass spectrometry (GC-HRMS) has become a valuable tool for this comprehensive profiling. In this webcast, we will take a closer look at known and unknown compounds that were detected on silicone wristbands and how high-resolution MS increases confidence in compound identifications. In addition, we will look at how it was possible to identify potentially novel biomarkers following in vitro human hepatic metabolism of organophosphorus flame retardants (OPFRs). All together, these studies will show how GC-HRMS can offer an efficient sample workflow, increased confidence in compound identity, and lower detection limits for these environmental contaminants.

Key learning objectives:

  • Learn how silicone wristbands can be used to assess human exposure to contaminants.
  • Learn how GC with high-resolution MS is being used to detect and quantify target compounds using efficient workflows.
  • Learn how unknown compounds can be detected and proposed identifications can increase our understanding of emerging contaminants.

Who should attend:

  • Research scientists
  • Analytical chemists
  • Laboratory managers

About the presenter

Nicholas Herkert, Ph.D., Research Project Manager, Duke University

Nicholas Herkert, Ph.D., Research Project Manager, Duke University

Nicholas Herkert, Ph.D., is a Research Project Manager in Dr. Stapleton’s laboratory at Duke University and the Targeted Organic Analysis Manager of the Duke HHEAR Environmental Analysis Laboratory. He manages GC-MS analysis workflows by maintaining instrument stability and accuracy to produce high quality targeted analytical results. He develops new instrument and laboratory methods to fit evolving research needs and is working to develop novel suspect screening methods for GC-MS analysis.

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