Oral<i>p</i>-<i>Tert</i>-Octylphenol Exposures Induce Minimal Toxic or Estrogenic Effects in Adult Female Sprague-Dawley Rats
Bibliographic record
Abstract
Contamination of the environment with endocrine-disrupting chemicals (EDC) has raised concerns about potential health hazards for humans and wildlife. Human and wildlife exposure to one such ubiquitous chemical, p-tert-octylphenol (OP), are likely, due to its persistence in the environment and its presence in food, water, and items of daily use. OP is reported to bind to the estrogen receptor (ER) and alter expression of estrogen-responsive genes. Detrimental effects of OP exposures on the reproductive system have been observed in most, but not all, in vivo experiments. This study examined estrogenic effects of oral exposures of adult female rats to OP. In vitro, OP bound weakly to human ER and a co-activator protein, and accelerated proliferation of MCF-7 cells. Adult Sprague-Dawley rats were given OP by gavage daily for 35 d (25, 50, or 125 mg/kg/d). Body and organ weights and ovarian follicle populations were not significantly altered in OP-exposed adult rats, despite detectable levels of OP in reproductive organs. The estrous cycle of rats was slightly altered, but there were no significant estrogen-like changes in histomorphology or gene expression of the uterus. Prepubertal rats given 125 or 250 mg/kg OP by gavage for 3 d had reduced body weight compared to vehicle-exposed rats but failed to show any uterotrophic response, although 17alpha-ethinyl estradiol (EE, 10 microg/kg/d, ip) induced a threefold increase in uterine weight. Overall, results suggest that toxicity will occur before estrogenic effects with oral exposures to OP. Relevant environmental exposures likely pose little risk for estrogenic effects.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 | 0.001 |
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".