Effect of superstimulation protocols on nuclear maturation and distribution of lipid droplets in bovine oocytes
Bibliographic record
Abstract
Our objective was to study the effect of superstimulation protocols on nuclear maturation of the oocyte and the distribution of lipid droplets in the ooplasm. Heifers (n=4 each group) during the luteal phase were either treated with FSH for 4 days (Short FSH), FSH for 4 days followed by 84h of gonadotropin free period (FSH Starvation) or for 7 days (Long FSH) starting from the day of wave emergence. In all groups, LH was given 24h after induced luteolysis (penultimate day of FSH) and cumulus-oocyte complexes were collected 24h later. Oocytes were stained for nuclear maturation (Lamin/chromatin) and lipid droplets (Nile red). The Long FSH group had a greater proportion of mature oocytes (metaphase II) compared with heifers in the Short FSH and FSH Starvation groups (59/100 vs 5/23 and 2/25, respectively; P<0.01). On average across all groups, oocytes contained 22pL of lipids (3.3% of ooplasm volume) distributed as 3000 droplets. Average volume of individual lipid droplets was higher in the FSH Starvation (11.5±1.5 10(-3) pL, P=0.03) compared with the Short and Long FSH groups (7.2±0.6 10(-3) and 8.0±0.8 10(-3) pL, respectively). In conclusion, both FSH Starvation and Short FSH treatments yielded a lower proportion of mature oocytes compared with the Long FSH treatment. Furthermore, FSH starvation led to an accumulation of larger lipid droplets in the ooplasm, indicating atresia. Our results indicate that a longer superstimulation period in beef cattle yields higher numbers and better-quality oocytes.
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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".