Altered burst swimming in rainbow trout <i>Oncorhynchus mykiss</i> exposed to natural and synthetic oestrogens
Bibliographic record
Abstract
Juvenile rainbow trout Oncorhynchus mykiss were exposed to two concentrations each of 17β-oestradiol (E2; natural oestrogen hormone) or 17α-ethinyl oestradiol (EE2; a potent synthetic oestrogen hormone) to evaluate their potential effects on burst-swimming performance. In each of six successive burst-swimming assays, burst-swimming speed (Uburst ) was lower in fish exposed to 0.5 and 1 µg l(-1) E2 and EE2 for four days compared with control fish. A practice swim (2 days prior to exposure initiation) in control fish elevated initial Uburst values, but this training effect was not evident in the 1 µg l(-1) EE2-exposed fish. Several potential oestrogen-mediated mechanisms for Uburst reductions were investigated, including effects on metabolic products, osmoregulation and blood oxygen-carrying capacity. Prior to burst-swimming trials, fish exposed to E2 and EE2 for 4 days had significantly reduced erythrocyte numbers and lower plasma glucose concentrations. After six repeated burst-swimming trials, plasma glucose, lactate and creatinine concentrations were not significantly different among treatment groups; however, plasma Cl(-) concentrations were significantly reduced in E2- and EE2-treated fish. In summary, E2 and EE2 exposure altered oxygen-carrying capacity ([erythrocytes]) and an osmoregulatory-related variable ([Cl(-) ]), effects that may underlie reductions in burst-swimming speed, which will have implications for fish performance in the wild.
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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".