Hazard assessment of legacy contaminated sites: bioassay-driven analysis of complex mixtures in fish
Bibliographic record
Abstract
Ecological risk assessment (ERA) of contaminated groundwater presents significant limitations due to its often-complex chemical composition and to dynamic processes affecting exposure of organisms in receiving surface waters. The overall aim of this thesis was to better inform ERA of legacy-contaminated sites where groundwater contamination could reach surface water and may impact freshwater organisms. Groundwater mixtures were collected from a pesticide packaging and handling facility in Manitoba, Canada with samples defined as reference zone (RZ), moderate industrial activity zone (MIAZ), and high industrial activity zone (HIAZ) based on historical site activities and chemical characterization of groundwater. Bioassay-driven analyses in combination with molecular assessments were used to characterize the potential ecotoxicological hazard posed by groundwater from a legacy contaminated site to fathead minnow (Pimephales promelas, FHM) as a model organism. To reduce live-animal testing, the potential for molecular assessments in early life stages (ELS) of FHM before independent feeding was evaluated using a novel transcriptomics tool, EcoToxChip, to predict apical responses at higher levels of biological organizations. The potential for laboratory toxicity responses to be predictive of outdoor mesocosms responses was also evaluated. RZ treatments were not toxic to FHMs relative to negative control, and therefore, served as an appropriate site-reference to which effects observed at MIAZ and HIAZ treatments were compared. Overall results revealed that oxidative stress could be the main mechanism of toxicity of contaminants present in MIAZ and HIAZ groundwater mixtures, which included pesticides, hydrocarbons, volatile organic compounds, and degradation products. This toxic mechanism could have led to mortality, deformity, increased swimming activity, and anxiety-like behavior, genotoxicity, hepatotoxicity, and impaired reproductive fitness observed in FHMs in laboratory. No such responses were observed in outdoor mesocosms, hence laboratory assays overestimated effects relative to the more environmentally relevant scenario. We found that molecular responses were predictive of apical outcomes and effects observed in ELS were predictive of those observed in adult fish. Therefore, this thesis supports the use of novel transcriptomics approaches in ELS of fish as an input of mechanistic information and an alternative to live animal and field-level testing for ERAs of complex mixtures found at comparable sites.
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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 | 0.001 | 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".