Toward understanding the impacts of sediment contamination on a native fish species: transcriptional effects, EROD activity, and biliary PAH metabolites
Bibliographic record
Abstract
Both frequency and intensity of flood events are expected to increase as a result of global climate change in the upcoming decades, potentially resulting in increased re-suspension of sediments in fluvial systems. Contamination of these re-suspended sediments with legacy contaminants, including dioxins and dioxin-like compounds (DLCs), as well as polycyclic aromatic hydrocarbons (PAHs) is of great ecotoxicological concern. DLCs, and to some extent also PAHs, exhibit their toxicity through activation of the aryl hydrocarbon receptor (AhR). However, interactions of DLCs with pathways other than those known to be mediated through the AhR are not fully understood to date. This study aimed to investigate molecular and biochemical effects in roach ( Rutilus rutilus) during a 10 days exposure to suspensions of three natural sediments that differed in the level of DLC contamination. Concentrations of biliary PAH metabolites and hepatic 7-ethoxyresorufin- O -deethylase activity were quantified in exposed fish. Furthermore, the abundance of transcripts of several genes related to energy metabolism, response to oxidative stress, and apoptosis, as well as cytochrome P450 1A ( cyp1a ) was quantified. Biliary PAH metabolites and activation of the AhR were confirmed as suitable early warning biomarkers of exposure to suspended sediments containing DLCs and PAHs that corresponded well with analytically determined concentrations of those contaminants. Although the abundances of transcripts of superoxide dismutase ( sod ), protein kinase c delta ( pkcd ), and ATP-binding cassette transporter c9 ( abcc9) were altered by the treatment compared with unexposed control fish, none of these showed a time- or concentration-dependent response. The abundance of transcripts of pyruvate carboxylase ( pc ) and transferrin variant d ( tfd ) remained unaltered by the treatments. We have shown that contaminated sediments can become a risk for fish during re-suspension events (e.g., flooding and dredging). We have also demonstrated that roach, which are native to most European freshwater systems, are suitable sentinel species due to their great sensitivity and ecological relevance. Roach may be particularly suitable in future field studies to assess the toxicological concerns associated with the release of DLCs and PAHs during sediment re-suspension.
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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) | 0.001 | 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".