Expression Profiles of Reproduction- and Thyroid Hormone-Related Transcripts in the Brains of Chemically-Induced Intersex Frogs
Bibliographic record
Abstract
Endocrine disrupting chemicals can induce intersex animals in amphibians and fish. Our previous study in frogs demonstrated that chemically-induced intersex animals can display different hepatic profiles of transcript levels than normal animals. In this study, we extend the observations to the developing frog brain. We investigated the effects of finasteride and fadrozole known to induce female- and male-biased sexual development on Silurana tropicalis brain mRNA levels. Real-time RT-PCR analysis of transcript levels of sex steroid- and thyroid hormone-related genes in the brain demonstrated that in finasteride-induced intersex animals, the mRNA levels of aromatase, estrogen receptor α, thyroid hormone receptor β and deiodinase type 3 were higher compared to both control males and females. Furthermore, finasteride-induced intersex animals expressed higher mRNA levels of both androgen receptor and estrogen receptor β compared to control females and to control males, respectively. Furthermore, fadrozole did not affect any of the genes analyzed in the brain but was effective at reducing aromatase activity. Intersex animals display different profiles of transcript levels in the brain whether the intersex condition was induced by an anti-androgen or anti-estrogen treatment. Finally, we conclude that a complex relationship exists between thyroid hormone-responsive genes and androgen status in frogs.
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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 | 0.001 | 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) | 0.002 | 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".