Automated Author ProfileSayre, Risa R.
Sayre, Risa R.
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 2.0 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Per- and polyfluoroalkyl substances (PFAS) comprise a large class of human-made chemicals that are in widespread use and present concerns for persistence, bioaccumulation and toxicity. Whilst a handful of PFAS have been characterized for their hazard profiles, the vast majority of PFAS have not been extensively studied. A comprehensive evaluation to characterize the hazard profiles of the thousands of available PFAS would require extensive resources in terms of cost, number of animals and time. An alternative and more efficient approach is to develop a structural chemical categorization approach to prioritize which PFAS or categories of PFAS should be subject to additional study. To that end, the U.S. Environmental Protection Agency (EPA), in collaboration with the National Institute of Environmental Health Sciences (NIEHS) Division of Translational Toxicology (DTT), initiated a research project in 2018 to screen approximately 150 PFAS through a battery of alternative model organisms, in vitro cell and biochemical assays, and in vitro toxico kinetic (TK) assays in order to inform chemical category and read-across approaches. The aim of this review summarizes the experimental testing undertaken, how data were processed, what insights were derived from a category perspective and how these might potentially inform subsequent tiered testing.
Authors
- Patlewicz, Grace ;
- Judson, Richard ;
- Friedman, Katie Paul ;
- Wetmore, Barbara A. ;
- DeVito, Michael J. ;
- Harrill, Joshua A. ;
- Carstens, Kelly E. ;
- Houck, Keith A. ;
- Wambaugh, John F. ;
- Padilla, Stephanie ;
- Britton, Katy N. ;
- Shafer, Timothy J. ;
- Degitz, Sigmund ;
- Nyffeler, Jo ;
- Kreutz, Anna ;
- Richard, Ann M. ;
- Williams, Antony J. ;
- Coutros, Katherine ;
- Hornung, Michael W. ;
- Cowden, John ;
- Everett, Logan J. ;
- Willis, Clinton M. ;
- Smeltz, Marci G. ;
- Clifton, M. Scott ;
- Feshuk, Madison ;
- Wall, Jonathan T. ;
- Sayre, Risa R. ;
- Brown, Jason ;
- Thomas, Russell S.
Per- and polyfluoroalkyl substances (PFAS) comprise a large class of human-made chemicals that are in widespread use and present concerns for persistence, bioaccumulation and toxicity. Whilst a handful of PFAS have been characterized for their hazard profiles, the vast majority of PFAS have not been extensively studied. A comprehensive evaluation to characterize the hazard profiles of the thousands of available PFAS would require extensive resources in terms of cost, number of animals and time. An alternative and more efficient approach is to develop a structural chemical categorization approach to prioritize which PFAS or categories of PFAS should be subject to additional study. To that end, the U.S. Environmental Protection Agency (EPA), in collaboration with the National Institute of Environmental Health Sciences (NIEHS) Division of Translational Toxicology (DTT), initiated a research project in 2018 to screen approximately 150 PFAS through a battery of alternative model organisms, in vitro cell and biochemical assays, and in vitro toxico kinetic (TK) assays in order to inform chemical category and read-across approaches. The aim of this review summarizes the experimental testing undertaken, how data were processed, what insights were derived from a category perspective and how these might potentially inform subsequent tiered testing.
Authors
- Patlewicz, Grace ;
- Judson, Richard ;
- Friedman, Katie Paul ;
- Wetmore, Barbara A. ;
- DeVito, Michael J. ;
- Harrill, Joshua A. ;
- Carstens, Kelly E. ;
- Houck, Keith A. ;
- Wambaugh, John F. ;
- Padilla, Stephanie ;
- Britton, Katy N. ;
- Shafer, Timothy J. ;
- Degitz, Sigmund ;
- Nyffeler, Jo ;
- Kreutz, Anna ;
- Richard, Ann M. ;
- Williams, Antony J. ;
- Coutros, Katherine ;
- Hornung, Michael W. ;
- Cowden, John ;
- Everett, Logan J. ;
- Willis, Clinton M. ;
- Smeltz, Marci G. ;
- Clifton, M. Scott ;
- Feshuk, Madison ;
- Wall, Jonathan T. ;
- Sayre, Risa R. ;
- Brown, Jason ;
- Thomas, Russell S.