Vaccination against follistatin affects reproductive potential in cycling gilts
Bibliographic record
Abstract
Primiparous sows (gilts) were actively vaccinated against follistatin in an attempt to modify litter size. Forty-seven gilts were vaccinated four times against a recombinant porcine follistatin (FS) or a sham vaccine (CTL) and were allowed to mature naturally prior to breeding. At breeding, FS antibody titers ranged from 0 to 1:6400 in the FS vaccinated gilts, and were not detectable in the CTL gilts. Overall, follistatin vaccination did not affect the total number of pigs born live (FS = 10.9 ± 0.5, CTL = 10.3 ± 0.4), stillborn (FS = 0.4 ± 0.1, CTL = 0.4 ± 0.2) or mummified (FS = 0.1 ± 0.1, CTL = 0.3 ± 0.1). However, separation of the FS vaccinated gilts into low (≤1:400, n = 16) and high (>1:400, n = 7) titer groups revealed significant differences in piglets born alive (FS high titer = 12.9 ± 0.9, FS low titer = 10.0 ± 0.5: P = 0.01) and total number of piglets born (FS high titer = 13.0 ± 0.8, FS low titer = 10.8 ± 0.6: P = 0.08). This study shows that vaccination of gilts against follistatin increased litter size in those gilts which achieved a high antibody titer to follistatin. Key words: Swine, follistatin, immunoneutralization, fecundity, litter size
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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".