↓ Skip to main content

Science Advances

Hidden drivers of low-dose pharmaceutical pollutant mixtures revealed by the novel GSA-QHTS screening method

Overview of attention for article published in Science Advances, September 2016
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

news
12 news outlets
twitter
90 X users
facebook
18 Facebook pages

Citations

dimensions_citation
39 Dimensions

Readers on

mendeley
98 Mendeley
citeulike
1 CiteULike
Title
Hidden drivers of low-dose pharmaceutical pollutant mixtures revealed by the novel GSA-QHTS screening method
Published in
Science Advances, September 2016
DOI 10.1126/sciadv.1601272
Pubmed ID
Authors

Ismael Rodea-Palomares, Miguel Gonzalez-Pleiter, Soledad Gonzalo, Roberto Rosal, Francisco Leganes, Sergi Sabater, Maria Casellas, Rafael Muñoz-Carpena, Francisca Fernández-Piñas

Abstract

The ecological impacts of emerging pollutants such as pharmaceuticals are not well understood. The lack of experimental approaches for the identification of pollutant effects in realistic settings (that is, low doses, complex mixtures, and variable environmental conditions) supports the widespread perception that these effects are often unpredictable. To address this, we developed a novel screening method (GSA-QHTS) that couples the computational power of global sensitivity analysis (GSA) with the experimental efficiency of quantitative high-throughput screening (QHTS). We present a case study where GSA-QHTS allowed for the identification of the main pharmaceutical pollutants (and their interactions), driving biological effects of low-dose complex mixtures at the microbial population level. The QHTS experiments involved the integrated analysis of nearly 2700 observations from an array of 180 unique low-dose mixtures, representing the most complex and data-rich experimental mixture effect assessment of main pharmaceutical pollutants to date. An ecological scaling-up experiment confirmed that this subset of pollutants also affects typical freshwater microbial community assemblages. Contrary to our expectations and challenging established scientific opinion, the bioactivity of the mixtures was not predicted by the null mixture models, and the main drivers that were identified by GSA-QHTS were overlooked by the current effect assessment scheme. Our results suggest that current chemical effect assessment methods overlook a substantial number of ecologically dangerous chemical pollutants and introduce a new operational framework for their systematic identification.

X Demographics

X Demographics

The data shown below were collected from the profiles of 90 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 98 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Switzerland 1 1%
Unknown 97 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 23 23%
Student > Ph. D. Student 14 14%
Student > Master 11 11%
Professor 8 8%
Professor > Associate Professor 4 4%
Other 12 12%
Unknown 26 27%
Readers by discipline Count As %
Environmental Science 27 28%
Agricultural and Biological Sciences 9 9%
Engineering 6 6%
Biochemistry, Genetics and Molecular Biology 4 4%
Medicine and Dentistry 4 4%
Other 14 14%
Unknown 34 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 151. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 December 2016.
All research outputs
#271,990
of 25,377,790 outputs
Outputs from Science Advances
#2,151
of 12,215 outputs
Outputs of similar age
#5,320
of 345,276 outputs
Outputs of similar age from Science Advances
#31
of 130 outputs
Altmetric has tracked 25,377,790 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,215 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 120.2. This one has done well, scoring higher than 82% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 345,276 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 130 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.