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Record W2809408965 · doi:10.1002/etc.4208

Sublethal metabolic responses to contaminant mixture toxicity in <i>Daphnia magna</i>

2018· article· en· W2809408965 on OpenAlexaff
Nicole D. Wagner, André J. Simpson, Myrna J. Simpson

Bibliographic record

VenueEnvironmental Toxicology and Chemistry · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsOccupational Cancer Research CentreUniversity of Toronto
Fundersnot available
KeywordsDaphnia magnaMetabolomeToxicityMetaboliteChemistryPropranololEnvironmental chemistryCarbamazepinePopulationPharmacologyToxicologyBiologyBiochemistryEndocrinologyMedicineOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Anthropogenic activity is increasing the presence of contaminants that enter waterways through wastewater effluent and urban and/or agricultural runoff, generally in complex mixtures. Depending on the mode of action of the individual contaminant within the mixture, toxicity can occur due to contaminants having similar or dissimilar modes of action. However, it is unknown how the metabolome responds to sublethal contaminant mixtures in the keystone genus Daphnia. In the present study we examined D. magna metabolic responses to acute sublethal exposure of propranolol, carbamazepine, and perfluorooctanesulfonic acid (PFOS) as well as in binary (propranolol–carbamazepine, propranolol–PFOS, carbamazepine–PFOS) and tertiary mixtures (carbamazepine–propranolol–PFOS), all at 10% of the median lethal concentration of the population (LC50). The metabolome was measured using 1H nuclear magnetic resonance (NMR) and characterized using principal component analysis, regression analysis, and fold changes in metabolite relative to the unexposed (control) group. The averaged principal component analysis scores plots revealed that carbamazepine–PFOS and carbamazepine–propranolol–PFOS exposures were significantly different from the control treatment. After normalizing the toxicity of each contaminant, we found that some metabolites responded monotonically, whereas others displayed a nonmonotonic response with increasing toxicity units. The single contaminant exposures and 2 binary mixtures (propranolol–carbamazepine, and propranolol–PFOS) resulted in minimal changes in the identified metabolites, whereas the carbamazepine–PFOS and carbamazepine–propranolol–PFOS displayed increases in several amino acid metabolites and decreases in glucose. Overall, our results highlight the sensitivity of the metabolome to distinguish the composition of the contaminant mixtures, with some mixtures displaying heightened responses versus others. Environ Toxicol Chem 2018;37:2448–2457. © 2018 SETAC

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.257
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2018
Admission routes1
Has abstractyes

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