Initiation of the expression of peroxisome proliferator - activated receptor gamma (PPAR gamma) in the rat ovary and the role of FSH
Bibliographic record
Abstract
PPARgamma is highly expressed in granulosa cells by 23 days post-partum (pp) and is down-regulated in response to the LH surge. We tested the hypothesis that high levels of FSH during the neonatal period trigger the expression of PPARgamma. To determine when PPARgamma expression is initiated, ovaries were collected from neonatal rats. Messenger RNA for PPARgamma was undetectable on day 1, low from days 5-14, and increased by day 19 pp (p < 0.05). PPARgamma was detected in select granulosa cells in primary/early secondary follicles. Messenger RNA for the FSH receptor was detected as early as day 1 and remained steady throughout day 19 pp. The FSH receptor was detected by immunoblot analysis in ovaries collected 1, 2, and 5-9 days pp. In a subsequent experiment, neonatal rats were treated with acyline (GnRH antagonist) which significantly reduced FSH (p < 0.05) but not levels of mRNA for PPARgamma. The role of FSH in the induction of PPARgamma expression was further assessed in ovarian tissue from FORKO mice. Both mRNA and protein for PPARgamma were identified in ovarian tissue from FORKO mice. In summary, the FSH/FSH receptor system is present in granulosa cells prior to the onset of expression of PPARgamma. Reducing FSH during the neonatal period, or the ability to respond to FSH, did not decrease expression of mRNA for PPARgamma. These data indicate that FSH is not a primary factor initiating the expression of PPARgamma and that other agents play a role in activating its expression in the ovary.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".