Uterine crowding in the sow affects litter sex ratio, placental development and embryonic myogenin expression in early gestation
Bibliographic record
Abstract
Uterine crowding in the pig results in intrauterine growth restriction (IUGR), and permanently affects fetal muscle fibre development, representing production losses for the commercial pig herd. The present study sought to understand how different levels of uterine crowding in sows affects muscle fibre development in the early embryo at the time of muscle fibre differentiation and proliferation. Sows either underwent surgical, unilateral oviduct ligation (LIG; n = 10) to reduce the number of embryos in the uterus, or remained as intact, relatively-crowded controls (CTR; n = 10). Embryos and placentae were collected at Day 30 of gestation, and myogenic regulatory factor (MRF) transcript abundance was determined using real-time PCR for both myogenin (MYOG) and myoblast differentiation 1 (MYOD1). Unilateral tubal ligation resulted in lower numbers of embryos in utero, higher placental weights and a higher male : female sex ratio (P < 0.05). Relative MYOD1 expression was not different, but MYOG expression was higher (P < 0.05) in the LIG group embryos; predominantly due to effects on the male embryos. Relatively modest uterine crowding therefore affects MRF expression, even at very early stages of embryonic development, and could contribute to reported differences in fetal muscle fibre development, birthweight and thus post-natal growth performance in swine.
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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".