GnRH agonist (buserelin) up regulates estrogen receptor α mRNA but not estrogen receptor β and progesterone receptor mRNA in bovine endometrium in vitro
Bibliographic record
Abstract
The local modulatory role of gonadotropin releasing hormone (GnRH), gonadotropin releasing hormone receptor (GnRH-R) system in regulating steroid hormone receptors at the endometrial level is still not known. Estrogen and progesterone maintain uterine functions by acting through their corresponding receptors; estrogen receptors (ERα and ERβ) and progesterone receptors (PR). We recently demonstrated GnRH-R in bovine endometrium and find the co-existence of GnRH and steroid hormone receptors in endometrium as interesting. Our objective was to determine the effect of a GnRH agonist (buserelin), on the expression of ERα, ERβ, and PR messenger RNA (mRNA) in bovine endometrium. Reproductive tracts were collected from slaughtered cows at a local abattoir, and endometrial explants were treated with buserelin (0, 200, 500, 1000 ng mL-1 respectively), GnRH antagonist-antide (500 ng mL-1) and antide + buserelin (500+200 ng mL-1) for 6 h and stored at -80°C for RNA extraction. Two micrograms of total RNA was subjected to reverse transcription polymerase chain reaction, PCR products electrophoresed (2% agrose gel); visualized and statistically analyzed. The results showed that buserelin (200 ng mL-1) increased the expression of ERα in the luteal phase endometrium. In addition, the expression of endometrial ERα was greater during the follicular than luteal phase. This up regulation of ERα mRNA in luteal phase endometrium suggests that GnRH administration may influence pregnancy in bovines. Key words: GnRH, bovine, endometrium, estrogen receptors, progesterone receptors
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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".