Acute exposure to an environmentally relevant concentration of diclofenac elicits oxidative stress in the culturally important galaxiid fish <i>Galaxias maculatus</i>
Bibliographic record
Abstract
Abstract Diclofenac is a nonsteroidal anti-inflammatory drug (NSAID) of growing concern in aquatic environments worldwide; nevertheless, knowledge of its effects on aquatic biota is restricted to a few model species with limited information regarding its mechanisms of impact. In the present study, diclofenac accumulation, its effects on metabolic rate, ionoregulation, and oxidative stress were examined at environmentally relevant (0.17 µg L−1) and elevated (763 µg L−1) concentrations in a culturally and economically important galaxiid fish, inanga (Galaxias maculatus), from the Southern Hemisphere. This species is among the most widespread freshwater fish in the world but its sensitivity to emerging contaminants is unknown. Following an acute 96-h exposure, bioconcentration of diclofenac was measured in the inanga whole-body, resulting in an estimated bioconcentration factor of 87 for the 0.17-µg L−1 exposure concentration, approaching values where transfer through the food chain should be considered. Lipid peroxidation in the liver was significantly elevated at both 0.17- and 763-µg L−1 exposure concentrations but lipid peroxidation in the kidney and gill decreased after diclofenac exposure. Catalase activity was also elevated in the liver of inanga but activity decreased in the gill. There were no effects of diclofenac on metabolic rate or ion (sodium and calcium) influx rates. These data indicate that toxicologically relevant adverse outcomes and bioconcentration of diclofenac at environmentally relevant levels warrant additional study in this important fish. Environ Toxicol Chem 2018;37:224–235. © 2017 SETAC
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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".