Regulation of Anti‐Müllerian Hormone and Its Receptor Expression around Follicle Deviation in Cattle
Bibliographic record
Abstract
The anti-Müllerian hormone (AMH) is an important marker of ovarian reserve and for predicting the response to superovulatory treatments in several species. The objective of this study was to investigate whether AMH and its receptor (AMHR2) are regulated in bovine granulosa cells during follicular development. In the first experiment, granulosa cells were retrieved from the two largest follicles on days 2 (before), 3 (at the expected time) or 4 (after deviation) of follicular wave. In the second experiment, four doses of FSH (30, 30, 20 and 20 mg) or saline were administered twice a day starting on Day 2 of the first follicular wave of the cycle. Granulosa cells and follicular fluid were collected from the two largest follicles 12 h after the last injection of FSH or saline. AMH mRNA abundance was similar in granulosa cells of the two largest follicles (F1 and F2) before deviation (Day 2), but greater in dominant (DF) than subordinate follicles (SF) at the expected time (Day 3) and after (Day 4) deviation (p < 0.05). In experiment 1, AMH mRNA levels declined in both DF and SF near the expected time and after deviation when compared to before deviation. There was no difference in AMHR2 mRNA levels before and during follicular deviation (p > 0.05), but they tended to be greater in DFs than SFs (p < 0.1) after deviation. Experiment 2 showed that AMH and AMHR2 mRNA in granulosa cells and AMH protein abundance in follicular fluid were similar (p > 0.05) between both co-dominant follicles collected from the FSH-treated cows. These findings indicate the followings: AMH mRNA levels decrease in both DFs and SFs during follicular deviation; granulosa cells from heathy follicles express more AMH mRNA compared to subordinate follicles undergoing atresia and FSH stimulates AMH and AMHR2 mRNA expression in granulosa cells of co-dominant follicles.
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How this classification was reachedexpand
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 | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".