Effects of Acute Exposure to the Non-steroidal Anti-inflammatory Drug Ibuprofen on the Developing North American Bullfrog (<i>Rana catesbeiana</i>) Tadpole
Bibliographic record
Abstract
A variety of pharmaceutical chemicals can represent constituents of municipal effluent outflows that are dispersed into aquatic receiving environments worldwide. Increasingly, there is concern as to the potential of such bioactive substances to interact with wildlife species at sensitive life stages and affect their biology. Using a combination of DNA microarray, quantitative real-time polymerase chain reaction, and quantitative nuclease protection assays, we assessed the ability of sub-lethal and environmentally relevant concentrations of ibuprofen (IBF), a non-steroidal anti-inflammatory agent and prevalent environmental contaminant, to function as a disruptor of endocrine-mediated post-embryonic development of the frog. While the LC50 of IBF for pre-metamorphic Rana catesbeiana tadpoles is 41.5 mg/L (95% confidence interval: 32.3-53.5 mg/L), exposure to concentrations in the ppb range elicited molecular responses both in vivo and in organ culture. A nominal concentration of 15 μg/L IBF (actual = 13.7 μg/L) altered the abundance of 26 mRNA transcripts within the liver of exposed pre-metamorphic R. catesbeiana tadpoles within 6 d. IBF-treated animals demonstrated subsequent disruption of thyroid hormone-mediated reprogramming in the liver transcriptome affecting constituents of several metabolic, developmental, and signaling pathways. Cultured tadpole tail fin treated with IBF for 48 h also demonstrated altered mRNA levels at drug concentrations as low as 1.5 μg/L. These observations raise the possibility that IBF may alter the post-embryonic development of anuran species in freshwater environs, where IBF is a persistent or seasonal pollutant.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".