17α-Ethynylestradiol and Levonorgestrel Exposure of Rainbow Trout RTL-W1 Cells at 18 °C and 21 °C Mainly Reveals Thermal Tolerance, Absence of Estrogenic Effects, and Progestin-Induced Upregulation of Detoxification Genes
Bibliographic record
Abstract
Fish are exposed to increased water temperatures and aquatic pollutants, including endocrine-disrupting compounds (EDCs). Although each stressor can disturb fish liver metabolism independently, combined effects may exist. To unveil the molecular mechanisms behind the effects of EDCs and temperature, fish liver cell lines are potential models needing better characterisation. Accordingly, we exposed the rainbow trout RTL-W1 cells (72 h), at 18 °C and 21 °C, to ethynylestradiol (EE2), levonorgestrel (LNG), and a mixture of both hormones (MIX) at 10 µM. The gene expression of a selection of targets related to detoxification (CYP1A, CYP3A27, GST, UGT, CAT, and MRP2), estrogen exposure (ERα, VtgA), lipid metabolism (FAS, FABP1, FATP1), and temperature stress (HSP70b) was analysed by RT-qPCR. GST expression was higher after LNG exposure at 21 °C than at 18 °C. LNG further enhanced the expression of CAT, while both LNG and MIX increased the expressions of CYP3A27 and MRP2. In contrast, FAS expression only increased in MIX, compared to the control. ERα, VtgA, UGT, CYP1A, HSP70b, FABP1, and FATP1 expressions were not influenced by the temperature or the tested EDCs. The RTL-W1 model was unresponsive to EE2 alone, sensitive to LNG (in detoxification pathway genes), and mainly insensitive to the temperature range but had the potential to unveil specific interactions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".