Dechlorane plus monoadducts in a lake ontario (Canada) food web and biotransformation by lake trout (<i>Salvelinus namaycush)</i> liver microsomes
Bibliographic record
Abstract
Compounds related to the high-production-volume flame retardant Dechlorane Plus (DP) were measured in a Lake Ontario food web located downstream of a DP manufacturing plant. These compounds, 1,3- and 1,5-DP-monoadducts (DPMA), are positional isomers and are thought to arise from the incomplete reaction of DP or impurities in the DP starting material during its manufacture. The 1,3-DPMA isomer was measured (0.12-199 ng g(-1) lipid wt) in all trophic levels, whereas 1,5-DPMA was measured only sporadically in the food web and was not detectable in the apex predator, lake trout (Salvelinus namaycush). Concentrations of DPMA isomers when detected in Lake Ontario biota were greater than that of total DP for all trophic levels. The prevalence of 1,3-DPMA in the food web, and especially in lake trout, may be due to obstruction of the existing carbon double bond to enzyme attack, rendering it less readily metabolized. To examine this hypothesis, biotransformation kinetic experiments using in vitro lake trout liver microsomal exposures were performed. Zero-order depletion rate constants for 1,3- and 1,5-DPMA were 92.2 and 134.6 pmole h(-1) , respectively, with corresponding half-lives of 2.03 ± 0.14 h (1,3-DPMA) and 1.39 ± 0.09 h (1,5-DPMA). Furthermore, the 1,5-isomer was depleted to a greater extent than 1,3-DPMA. Specific biotransformation products were not identified. These data support the hypothesis that 1,5-DPMA is more readily metabolized than 1,3-DPMA by lake trout. The present study also shows that the concentrations of these isomers, which the authors speculate might be unintended impurities or byproducts in some technical DP formulations, exceed that of the intended product in biota.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".