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Metabolomics identified distinct molecular-level responses in Daphnia magna after exposure to phenanthrene and its oxygen and nitrogen containing analogs

2025· article· en· W4408746743 on OpenAlexafffund
Salwa Hajir, Karl J. Jobst, Sonya Kleywegt, Myrna J. Simpson

Bibliographic record

VenueChemosphere · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolomics and Mass Spectrometry Studies
Canadian institutionsMinistry of the Environment, Conservation and ParksMemorial University of NewfoundlandThe Scarborough HospitalUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaMinistère de l’Environnement, de la Protection de la nature et des ParcsUniversity of TorontoGovernment of Ontario
KeywordsDaphnia magnaPhenanthreneMetabolomicsEnvironmental chemistryOxygenChemistryNitrogenDaphniaBiologyEcologyToxicityBioinformaticsOrganic chemistry

Abstract

fetched live from OpenAlex

The prevalence of polycyclic aromatic hydrocarbons and their oxygenated and nitrogen containing analogs in freshwater ecosystems are of concern due to their reported toxicity to several aquatic species including Daphnia magna . This study explored the molecular-level responses of phenanthrene (PHEN), 9,10-phenanthrenequinone (PHQ), and phenanthridine (PN) as little is known about the impacts of these pollutants on the metabolic profile of D. magna . For this purpose, D . magna was exposed to three sub-lethal concentrations of these pollutants for 24 h. To assess molecular-level responses, 52 polar metabolites were extracted from individual adult daphnids, and analyzed using a mass spectrometry-based targeted metabolomics approach. Exposure to PN resulted in the most statistically significant changes to the metabolic profile of D. magna followed by PHQ, and then PHEN exposures. After PN exposure, the biochemical pathway analysis showed that all exposure concentrations shared 21 perturbed metabolic pathways. However, the number of disrupted metabolic pathways increased with increasing exposure concentrations for PHEN and PHQ. The results suggest that PN and PHQ exposures are more disruptive due to the presence of reactive functional groups when compared to PHEN exposure. For the tested concentration ranges, the findings indicate that exposure to PN resulted in non-monotonic disruptions across exposure concentrations. In contrast, exposure to PHEN and PHQ elicited perturbations that were concentration-dependent. Although the reported median effective concentration (EC 50 ) for PN is higher than PHEN and PHQ, our data shows that metabolomics captures molecular-level changes that may not be detected by traditional toxicity metrics. • Exposure to phenanthridine resulted in the most metabolic perturbations. • Non-monotonic responses were noted after phenanthridine exposure. • Phenanthrene and 9,10-phenanthrenequonine exposures were concentration-dependent. • Metabolomics detected molecular-level changes after 24 h of pollutant exposure.

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 score0.002
Threshold uncertainty score0.004

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 head0.011
GPT teacher head0.257
Teacher spread0.246 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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