2015
DOI: 10.1016/j.chemosphere.2015.05.072
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Linking mutagenic activity to micropollutant concentrations in wastewater samples by partial least square regression and subsequent identification of variables

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Cited by 35 publications
(40 citation statements)
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References 41 publications
(52 reference statements)
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“…Virtual Effect-Directed-Analysis attempts to prioritize pollutants for identification with a given effect via statistically correlating chemicals and effects data over a samples set instead of using extensive fractionation. 49…”
Section: Data-drivenmentioning
confidence: 99%
“…Virtual Effect-Directed-Analysis attempts to prioritize pollutants for identification with a given effect via statistically correlating chemicals and effects data over a samples set instead of using extensive fractionation. 49…”
Section: Data-drivenmentioning
confidence: 99%
“…The prioritisation of environmentally relevant chemosensitisers could be realised with a combination of effect-based and chemical screening using multivariate (Hug et al, 2015) and effect-directed analysis (Brack, 2003).…”
Section: Discussionmentioning
confidence: 99%
“…An approach is needed to identify (bioactive) candidate chemicals in complex mixtures that may be relevant on a larger spatial scale [24,35]. The goal of a methodology that has been labeled virtual effect-directed analysis (vEDA) [24] is to assist explaining of biological effects by reducing the complexity of mixture components via multivariate statistics and pattern recognition methods on large sample numbers using a decomposition approach.…”
Section: Deconstructing Mixtures Into Bioactive Componentsmentioning
confidence: 99%
“…6 weeks, along with thousands of chemical signals of varying intensity from LC-MS non-target screening. Applying partial least squares analysis, the number of peaks of interest to explain the variability in mutagenicity was reduced to about 200 signals [35]. The overrepresentation (30 times larger) of nitrogen-containing compounds among the selected peaks, along with enhanced mutagenicity in a diagnostic Ames Salmonella stem (YG 1024) suggested aromatic amines as drivers of mutagenicity.…”
Section: Sufficient Variance (Larger Than the Data Uncertainty)mentioning
confidence: 99%