Ovulation, Pregnancy Rate and Early Embryonic Development in Vernal Transitional Mares Treated with Equine- or Porcine-FSH
Bibliographic record
Abstract
The objective of this study was to compare the efficacy of purified equine- and porcine-FSH treatment regimes in mares in early vernal transition. Mares (n = 22) kept under ambient light were examined ultrasonographically per-rectum, starting January 30th. They were assigned to one of two treatment groups using a sequential alternating treatment design when a follicle >or= 25 mm was detected. In the eFSH group, mares were treated twice daily with equine-FSH, and in the pFSH group mares were treated twice daily with porcine-FSH; treatments were continued until follicle(s) >or= 35 mm, and 24 h later hCG was administered. Oestrous mares were inseminated with fresh semen and examined for pregnancy on days 11-20 post-ovulation. In the eFSH group, 11/11 (100%) mares developed follicle(s) >or= 35 mm, 8/11 (73%) ovulated and 6/8 (75%) conceived. In the pFSH group, 5/11 (45%) developed follicle(s) >or= 35 mm, 4/11 (36%) ovulated and 3/4 (75%) conceived. Treatment with eFSH resulted in a greater ovarian stimulation; higher number of pre-ovulatory-sized follicles, higher number of ovulations and higher number of embryos (p < 0.05). Following ovulation, serum progesterone concentrations were correlated with the number of CLs and supported early embryonic development; maternal recognition of pregnancy occurred in all pregnant mares. We concluded that eFSH can be used to effectively induce follicular growth and ovulation in vernal transitional mares; however, if bred, diagnosis and management of twins' pregnancies would be required prior to day 16 because of the increased risk of multiple embryos per pregnancy. Conversely, the current pFSH treatment regime cannot be recommended.
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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".