Follicular dynamics and gene expression in granulosa cells, corpora lutea and oocytes from gilts of breeds with low and high ovulation rates
Bibliographic record
Abstract
Follicular dynamics and the expression of candidate genes using real-time polymerase chain reaction (PCR) were compared during the oestrous cycle of pig breeds with high (commercial line; n=24) and low (local Brazilian Piau; n=21) ovulation rates and prolificacy. Gilts were killed on Days 0, 4, 10 and 18 of the oestrous cycle and visible ovarian follicles were classified by follicular diameter. Recovered cumulus-oocyte complexes were classified as normal or atretic and frozen in liquid nitrogen until RNA extraction. Low ovulation rates and/or prolificacy in Piau gilts was associated with a different pattern of follicle development, with lower numbers of small follicles on Day 18, fewer large follicles on Days 0 and 18 (P≤0.05) and a higher proportion of atretic follicles on Days 0 and 18 (P≤0.05). Compared with commercial line gilts, less-prolific Piau gilts exhibited higher expression of apoptotic genes during luteolysis (CASP3 and FASL; P≤0.05), decreased expression of TGFBR2 and BAX mRNA in the corpus luteum (P≤0.05), higher expression of apoptotic genes (FAS, BCL2 and CASP8; P≤0.05) in granulosa cells and a greater abundance (P≤0.05) of genes controlling oocyte-secreted factors (GDF9, BMP15 and BMP6), suggesting underlying mechanisms controlling differences in follicular development, ovulation rate and inherent prolificacy in this pig breed.
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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".