Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Supercritical Fluid Chromatography

Supercritical Fluid Chromatography

Supercritical fluid chromatography (SFC) provides a beneficial substitute for gas chromatography (GC) and liquid chromatography (LC) for certain samples because it merges the top attributes of both techniques. SFC allows the separation and analysis of compounds that GC or LC does not easily manage. These compounds are traditionally nonvolatile or thermally unstable, making GC unsuitable and lacking functional groups required for HPLC analysis.
SFC utilizes a supercritical fluid mobile phase,...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Cardiac screening in adolescents: Insights from a 15-year Student Heart Check program.

Heart rhythm O2·2026

Same author

Expanding the genetic spectrum of autosomal recessive microcephaly in Pakistani families.

BMC neurology·2026

Same author

Distinct Plasmodium falciparum Erythrocyte Membrane Protein 1 Domain Cassette-Associated Antibody Gaps Specific to Cerebral Malaria and Severe Malarial Anemia.

The Journal of infectious diseases·2026

Same author

A curated geospatial dataset of chemicals used in hydraulic fracturing and their functions.

Journal of environmental quality·2026

Same author

Reimagining clinical psychology for a changing planet.

Psychology and psychotherapy·2026

Same author

Non-negligible disparities in source-specific ambient PM<sub>2.5</sub> across economic groups over space and time in China.

Journal of hazardous materials·2026

Same journal

AmesNet: A Task-Conditioned Deep Learning Model with Enhanced Sensitivity and Generalization in Ames Mutagenicity Prediction.

Chemical research in toxicology·2026

Same journal

DNA Structure-Dependent Enrichment of Oxidative Lesions.

Chemical research in toxicology·2026

Same journal

Characterizing the Reactive Metabolites of Colony-Stimulating Factor 1 Receptor Inhibitor PLX5622 in Liver Microsomes and Mice.

Chemical research in toxicology·2026

Same journal

Quantitation of E-Cigarette Aerosol Mass in Liquid Impinger Solution Using the <sup>13</sup>C of E-Liquids: Application for Metal Analyses.

Chemical research in toxicology·2026

Same journal

Beyond Heuristics: A Model-Agnostic Framework for Uncertainty Quantification in QSAR via Adaptive Conformal Prediction.

Chemical research in toxicology·2026

Same journal

20-Hydroxyeicosatetraenoic Acid Ameliorates Nickel Nanoparticle-Induced Epithelial-Mesenchymal Transition by Modulating the FFAR1/NF-kB Pathway.

Chemical research in toxicology·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Aug 8, 2025

Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow

Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow

Published on: April 18, 2019

A New CSRML Structure-Based Fingerprint Method for Profiling and Categorizing Per- and Polyfluoroalkyl Substances

Ann M Richard¹, Ryan Lougee², Matthew Adams²

¹Center for Computational Toxicology & Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, North Carolina 27711, United States.

Chemical Research in Toxicology

|March 2, 2023

Summary

This summary is machine-generated.

This study introduces novel PFAS-specific chemotypes (TxP_PFAS) for analyzing per- and polyfluoroalkyl substances (PFAS). These chemotypes enable automated, structure-based categorization of PFAS, improving chemical inventory analysis.

More Related Videos

Investigating Long-Distance Transport of Perfluoroalkyl Acids in Wheat via a Split-Root Exposure Technique

Investigating Long-Distance Transport of Perfluoroalkyl Acids in Wheat via a Split-Root Exposure Technique

Published on: September 28, 2022

Separation and Identification of Conventional Microplastics from Farmland Soils

Separation and Identification of Conventional Microplastics from Farmland Soils

Published on: March 21, 2025

Related Experiment Videos

Last Updated: Aug 8, 2025

Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow

Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow

Published on: April 18, 2019

Investigating Long-Distance Transport of Perfluoroalkyl Acids in Wheat via a Split-Root Exposure Technique

Investigating Long-Distance Transport of Perfluoroalkyl Acids in Wheat via a Split-Root Exposure Technique

Published on: September 28, 2022

Separation and Identification of Conventional Microplastics from Farmland Soils

Separation and Identification of Conventional Microplastics from Farmland Soils

Published on: March 21, 2025

Area of Science:

Environmental Chemistry
Cheminformatics
Toxicology

Background:

Per- and polyfluoroalkyl substances (PFAS) encompass over 14,000 diverse chemical structures.
Analyzing and categorizing the vast PFAS structure space is crucial for understanding their environmental occurrence and potential concerns.
Current methods for profiling PFAS may not be efficient for large-scale analysis.

Purpose of the Study:

To develop a novel set of PFAS-specific chemotypes (TxP_PFAS) for enhanced cheminformatic analysis.
To create a computationally efficient and reproducible method for categorizing PFAS based on chemical structure.
To demonstrate the utility of TxP_PFAS in profiling and categorizing the PFASSTRUCT inventory.

Main Methods:

Utilized publicly available ToxPrint chemotypes and the ChemoTyper application.
Developed 129 TxP_PFAS chemotypes, including modified bond-type ToxPrints and fluorinated chain/ring patterns.
Applied TxP_PFAS to profile the PFASSTRUCT inventory and compare with expert-based PFAS categories (e.g., OECD Global PFAS list).

Main Results:

Created a new PFAS-specific fingerprint set (TxP_PFAS) with 129 chemotypes, reducing chemotype counts by an average of 54% compared to ToxPrints.
Demonstrated that TxP_PFAS can be visualized, filtered, and used to construct chemically intuitive, structure-based PFAS categories.
Showcased TxP_PFAS's ability to recapitulate expert-based PFAS categories using clear, computationally implementable structure rules.

Conclusions:

TxP_PFAS chemotypes provide a powerful tool for the computational analysis and categorization of large PFAS inventories.
This approach facilitates harmonized PFAS categorization, improves communication, and enables more efficient, chemically informed exploration of PFAS.
The developed method supports computational modeling and reduces the need for expert consultation in PFAS classification.