Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 457

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Benchmarking Organic Micropollutants in Wastewater, Recycled Water and Drinking Water with In Vitro Bioassays

Open access
Escher, Beate I., Allinson, Mayumi, Altenburger, Rolf, Bain, Peter A., Balaguer, Patrick, Busch, Wibke, Crago, Jordan, Denslow, Nancy D., Dopp, Elke, Hilscherova, Klara, Humpage, Andrew R., Kumar, Anu, Grimaldi, Marina, Jayasinghe, B. Sumith, Jarosova, Barbora, Jia, Ai, Makarov, Sergei, Maruya, Keith A., Medvedev, Alex, Mehinto, Alvine C., Mendez, Jamie E., Poulsen, Anita, Prochazka, Erik, Richard, Jessica, Schifferli, Andrea, Schlenk, Daniel, Scholz, Stefan, Shiraishi, Fujio, Snyder, Shane, Su, Guanyong, Tang, Janet Y. M., Burg, Bart van der, Linden, Sander C. van der, Werner, Inge, Westerheide, Sandy D., Wong, Chris K. C., Yang, Min, Yeung, Bonnie H. Y., Zhang, Xiaowei, Leusch, Frederic D. L.·2014·Environmental Science & Technology

Abstract

Thousands of organic micropollutants and their transformation products occur in water. Although often present at low concentrations, individual compounds contribute to mixture effects. Cell-based bioassays that target health-relevant biological endpoints may therefore complement chemical analysis for water quality assessment. The objective of this study was to evaluate cell-based bioassays for their suitability to benchmark water quality and to assess efficacy of water treatment processes. The selected bioassays cover relevant steps in the toxicity pathways including induction of xenobiotic metabolism, specific and reactive modes of toxic action, activation of adaptive stress response pathways and system responses. Twenty laboratories applied 103 unique in vitro bioassays to a common set of 10 water samples collected in Australia, including wastewater treatment plant effluent, two types of recycled water (reverse osmosis and ozonation/activated carbon filtration), stormwater, surface water, and drinking water. Sixty-five bioassays (63%) showed positive results in at least one sample, typically in wastewater treatment plant effluent, and only five (5%) were positive in the control (ultrapure water). Each water type had a characteristic bioanalytical profile with particular groups of toxicity pathways either consistently responsive or not responsive across test systems. The most responsive health-relevant endpoints were related to xenobiotic metabolism (pregnane X and aryl hydrocarbon receptors), hormone-mediated modes of action (mainly related to the estrogen, glucocorticoid, and antiandrogen activities), reactive modes of action (genotoxicity) and adaptive stress response pathway (oxidative stress response). This study has demonstrated that selected cell-based bioassays are suitable to benchmark water quality and it is recommended to use a purpose-tailored panel of bioassays for routine monitoring.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/es403899t

Cites

4 of 4 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

See all 457

Metadata

Authors
Escher, B. I., Allinson, M., Altenburger, R., Bain, P. A., Balaguer, P., Busch, W., Crago, J., Denslow, N. D., Dopp, E., Hilscherova, K., Humpage, A. R., Kumar, A., Grimaldi, M., Jayasinghe, B. S., Jarosova, B., Jia, A., Makarov, S., Maruya, K. A., Medvedev, A., Mehinto, A. C., Mendez, J. E., Poulsen, A., Prochazka, E., Richard, J., Schifferli, A., Schlenk, D., Scholz, S., Shiraishi, F., Snyder, S., Su, G., Tang, J. Y. M., Burg, B. V. D., Linden, S. C. V. D., Werner, I., Westerheide, S. D., Wong, C. K. C., Yang, M., Yeung, B. H. Y., Zhang, X., & Leusch, F. D. L.
Venue
Environmental Science & Technology
Published
2013-12-26
Volume
48
Issue
3
Pages
1940-1956
ISSN
  • 0013-936X (ISSN-L)
  • 1520-5851
OpenAlex
W2039023381
Cited by
457
References
4
FWCI
23.74
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.