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Record W2803751009 · doi:10.3390/metabo8020034

Investigation of Daphnia magna Sub-Lethal Exposure to Organophosphate Esters in the Presence of Dissolved Organic Matter Using 1H NMR-Based Metabolomics

2018· article· en· W2803751009 on OpenAlexafffund
Vera Kovacevic, Myrna J. Simpson

Bibliographic record

VenueMetabolites · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Toxicology and Ecotoxicology
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDaphnia magnaChemistryDissolved organic carbonOrganophosphateEnvironmental chemistryTriphenyl phosphateToxicityBioavailabilityPartition coefficientMetabolitePhosphateMetabolomicsOrganic matterPesticideChromatographyBiochemistryOrganic chemistryPharmacologyEcologyFire retardantBiology

Abstract

fetched live from OpenAlex

Organophosphate esters (OPEs) are frequently detected in aquatic environments. Hydrophobic OPEs with high octanol-water partition coefficients (Log KOW) will likely sorb to dissolved organic matter (DOM) and consequently alter OPE bioavailability and sub-lethal toxicity. 1H nuclear magnetic resonance (NMR)-based metabolomics was used to evaluate how DOM (5 mg organic carbon/L) alters the metabolic response of Daphnia magna exposed to sub-lethal concentrations of three individual OPEs with varying hydrophobicity. D. magna exposed to the hydrophilic contaminant (Log KOW = 1.43) tris(2-chloroethyl) phosphate (TCEP) did not have substantial metabolic changes and DOM did not alter the metabolic response. There were significant increases in amino acids and a decrease in glucose from exposure to the hydrophobic contaminant (Log KOW = 3.65) tris(2-butoxyethyl) phosphate (TBOEP) which DOM did not mitigate, likely due to the high sub-lethal toxicity of TBOEP. Exposure to DOM and the hydrophobic contaminant (Log KOW = 4.76) triphenyl phosphate (TPhP) resulted in a unique metabolic response which was unlike TPhP only exposure, perhaps because DOM may be an additional stressor with TPhP exposure. Therefore, Log KOW values may not always predict how sub-lethal contaminant toxicity will change with DOM and there should be more consideration to incorporate DOM in sub-lethal ecotoxicology testing.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.038
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.230
Teacher spread0.213 · 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 teacher head, not a consensus.

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

Citations21
Published2018
Admission routes2
Has abstractyes

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