Folliculogenesis, embryo parameters and post-transfer recipient pregnancy rate following equine follicle-stimulating hormone (eFSH) treatment in cycling donor mares
Bibliographic record
Abstract
BACKGROUND: Induction of multiple ovulations, or superovulation, may potentially increase the efficiency of equine embryo transfer programs. Our objective was to investigate the effects of equine follicle-stimulating hormone (eFSH) treatment on the success rate of embryo transfer programs in mares. METHODS: In the research facility of the University of Saskatchewan, Canada, we studied 12 donor mares and 37 recipient mares during the physiological breeding season. Donor mares were used in two consecutive oestrous cycles: the first served as the control cycle and in the second an eFSH regimen was applied (eFSH cycle). In the control cycle, mares were administered human chorionic gonadotropin (hCG) to induce ovulation when a follicle ≥35 mm in diameter was detected by transrectal ultrasonographic examination. In the second oestrous cycle, twice-daily eFSH treatment was initiated when a follicle ≥25 mm was detected and treatment ceased when a follicle ≥35 mm was present, at which time hCG was administered. All donor mares were artificially inseminated while in oestrus using fresh semen collected from a stallion of proven fertility. At 8 days post-ovulation, embryos were recovered transcervically and transferred individually to the uterus of a synchronised recipient mare. RESULTS: The eFSH treatment stimulated the ovary and resulted in greater numbers of ovulations and recovered embryos; however the recovered embryos tended to have a lower morphological grade than the control embryos, and the recipient pregnancy rate per transferred embryo was lower than anticipated. CONCLUSION: The numbers of recipient pregnancies and foals born that resulted from eFSH treatment were not different from the control.
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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 | 0.001 |
| 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".