Role of leptin receptors in granulosa cells during ovulation
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Bibliographic record
Abstract
Leptin is an important hormone influencing reproductive function. However, the mechanisms underpinning the role of leptin in the regulation of reproduction remain to be completely deciphered. In this study, our objective is to understand the mechanisms regulating the expression of leptin receptor (Lepr) and its role in ovarian granulosa cells during ovulation. First, granulosa cells were collected from superovulated mice to profile mRNA expression of Lepr isoforms (LeprA and LeprB) throughout follicular development. Expression of LeprA and LeprB was dramatically induced in the granulosa cells of ovulating follicles at 4 h after human chorionic gonadotropin (hCG) treatment. Relative abundance of both mRNA and protein of CCAAT/enhancer-binding protein β (Cebpβ) increased in granulosa cells from 1 to 7 h post-hCG. Furthermore, chromatin immunoprecipitation assay confirmed the recruitment of Cebpβ to Lepr promoter. Thus, hCG-induced transcription of Lepr appears to be regulated by Cebpβ, which led us to hypothesise that Lepr may play a role during ovulation. To test this hypothesis, we used a recently developed pegylated superactive mouse leptin antagonist (PEG-SMLA) to inhibit Lepr signalling during ovulation. I.p. administration of PEG-SMLA (10 μg/g) to superovulated mice reduced ovulation rate by 65% compared with control treatment. Although the maturation stage of the ovulated oocytes remained unaltered, ovulation genes Ptgs2 and Has2 were downregulated in PEG-SMLA-treated mice compared with control mice. These results demonstrate that Lepr is dramatically induced in the granulosa cells of ovulating follicles and this induction of Lepr expression requires the transcription factor Cebpβ. Lepr plays a critical role in the process of ovulation by regulating, at least in part, the expression of the important genes involved in the preovulatory maturation of follicles.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it