The mare as a model for luteinized unruptured follicle syndrome: intrafollicular endocrine milieu
Bibliographic record
Abstract
Luteinized unruptured follicle (LUF) syndrome is a recurrent anovulatory dysfunction that affects up to 23% of women with normal menstrual cycles and up to 73% with endometriosis. Mechanisms underlying the development of LUF syndrome in mares were studied to provide a potential model for human anovulation. The effect of extended increase in circulating LH achieved by administration of recombinant equine LH (reLH) or a short surge of LH and decrease in progesterone induced by prostaglandin F2α (PGF2α) on LUF formation (Experiment 1), identification of an optimal dose of COX-2 inhibitor (flunixin meglumine, FM; to block the effect of prostaglandins) for inducing LUFs (Experiment 2), and evaluation of intrafollicular endocrine milieu in LUFs (Experiment 3) were investigated. In Experiment 1, mares were treated with reLH from Day 7 to Day 15 (Day 0=ovulation), PGF2α on Day 7, or in combination. In Experiment 2, FM at doses of 2.0 or 3.0 mg/kg every 12 h and human chorionic gonadotropin (hCG) (1500 IU) were administered after a follicle ≥32 mm was detected. In Experiment 3, FM at a dose of 2.0 mg/kg every 12 h plus hCG was used to induce LUFs and investigate the intrafollicular endocrine milieu. No LUFs were induced by reLH or PGF2α treatment; however, LUFs were induced in 100% of mares using FM. Intrafollicular PGF2α metabolite, PGF2α, and PGE2 were lower and the ratio of PGE2:PGF2α was higher in the induced LUF group. Higher levels of intrafollicular E2 and total primary sex steroids were observed in the induced LUF group along with a tendency for higher levels of GH, cortisol, and T; however, LH, PRL, VEGF-A, and NO did not differ between groups. In conclusion, this study reveals part of the intrafollicular endocrine milieu and the association of prostaglandins in LUF formation, and indicates that the mare might be an appropriate model for studying the poorly understood LUF syndrome.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".