Metabolic state can define the ovarian response to environmental contaminants and medicinal plants
Bibliographic record
Abstract
Environmental contaminants and medicinal plants can affect reproductive processes. The aim of this study was to investigate the effect of maternal metabolic status on the response of mouse ovaries to the environmental contaminants benzene and xylene, as well as to extracts of the medicinal plant yucca. Ovaries isolated from normal-lean and slightly obese mice were cultured with or without 0.1% benzene or xylene for 24 h. Similarly, ovaries isolated from normal-lean, slightly obese, and significantly obese mice were cultured for 24 h with or without an extract of Yucca shidigera (YS, 10 μ g/mL). We found that the metabolic status did not influence the release of basal progesterone (P4), testosterone (T), or insulin-like growth factor I (IGF-I), but obesity influenced the effects of the environmental contaminants and YS. Benzene reduced P4 output in ovaries from obese but not normal-lean mice; it also reduced IGF-I (but not T) release from ovaries irrespective of the metabolic status. Xylene dramatically increased P4 and T (but not IGF-I) release by ovaries from normal-lean mice, but there were no changes in P4 and only small increases in T output in obese mice. YS increased P4 (but not T or IGF-I) release in normal-lean and slightly obese animal ovaries, whilst significant obesity was associated with a lack of P4 response to YS. Obesity might affect the basal ovarian release of T or IGF-I and increases the sensitivity of ovaries to the action of benzene but decreases their responsiveness to xylene and YS.
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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".