Bioaccumulation, Trophic Transfer, and Biotransformation of Polychlorinated Diphenyl Ethers in a Simulated Aquatic Food Chain
Bibliographic record
Abstract
Polychlorinated diphenyl ethers (PCDEs) are detected in aquatic environments and demonstrate adverse effects in aquatic organisms. However, data regarding the environmental behavior of PCDEs in aquatic ecosystems are lacking. In the present study, a simulated aquatic food chain ( Scenedesmus obliquus – Daphnia magna – Danio rerio ) was constructed in a lab setting, and the bioaccumulation, trophic transfer, and biotransformation of 12 PCDE congeners were quantitatively investigated for the first time. The log-transformed bioaccumulation factors (BCFs) of PCDEs in S. obliquus, D. magna, and D. rerio were in the range of 2.94–3.77, 3.29–4.03, and 2.42–2.89 L/kg w.w., respectively, indicating the species-specific bioaccumulation of PCDE congeners. The BCF values increased significantly with the increasing number of substituted Cl atoms, with the exception of CDE 209. The number of Cl atoms at the para and meta positions were found to be the major positive contributing factors for BCFs in the case of the same number of substituted Cl. The lipid-normalized biomagnification factors (BMFs) of S. obliquus to D. magna, D. magna to D. rerio, and the whole food chain for the 12 PCDE congeners ranged at 1.08–2.27, 0.81–1.64, and 0.88–3.64, respectively, suggesting that some congeners had BMFs comparable to PBDEs and PCBs. Dechlorination was the only metabolic pathway observed for S. obliquus and D. magna . For D. rerio, dechlorination, methoxylation, and hydroxylation metabolic pathways were observed. 1 H nuclear magnetic resonance (NMR) experiments and theoretical calculations confirmed that methoxylation and hydroxylation occurred at the ortho position of the benzene rings. In addition, reliable quantitative structure–property relationship (QSPR) models were constructed to qualitatively describe the relationships between molecular structure descriptors and BCFs for PCDEs. These findings provide insights into the movement and transformation of PCDEs in aquatic ecosystems.
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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 | 0.000 | 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) | 0.000 | 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".