Ovarian stimulation with GnRH agonist, but not GnRH antagonist, partially restores the expression of endometrial integrin 3 and leukaemia-inhibitory factor and improves uterine receptivity in mice
Bibliographic record
Abstract
BACKGROUND: The impact of different ovarian stimulation (OS) protocols on endometrial receptivity remains controversial. In this study, the effects of different OS on the expression of endometrial integrin beta3 subunit and leukaemia-inhibitory factor (LIF) during the implantation window and the implantation rate in mice were investigated. METHODS: Three OS protocols were used, involving either pregnant mare's serum gonadotrophin (PMSG) alone, PMSG plus GnRH agonist or PMSG plus GnRH antagonist. Uterus samples were collected at 48 h after OS or ovulation and were detected with immunohistochemistry, Western blot and RT-PCR analyses. Normal embryos at gestation day 4 were transferred into the uteri of mice in the control and OS groups. RESULTS: All OS groups showed a significant decrease in the expression of both the endometrial integrin beta3 subunit and LIF during the implantation window and the implantation rate. Among the three OS groups, GnRH agonist-treated mice showed a higher endometrial integrin beta3 subunit and LIF expression and a higher implantation rate. No significant difference was found in the measured indices between the GnRH antagonist and PMSG groups. CONCLUSIONS: OS may inhibit the expression of endometrial integrin beta3 subunit and LIF and impair endometrial receptivity in mice. OS with GnRH agonist, but not GnRH antagonist, may partially restore the endometrial physiological secretion and improve uterine receptivity.
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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".