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.
This research output has an Altmetric Attention Score of 152. 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.
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#294,142
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#2,334
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#5,286
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Outputs of similar age from Science Advances
#31
of 130 outputs
Altmetric has tracked 26,807,699 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 13,636 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 117.2. This one has done well, scoring higher than 82% of its peers.
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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.
