Temporal candidate gene expression in the sow placenta and embryo during early gestation and effect of maternal Progenos supplementation on embryonic and placental development
Bibliographic record
Abstract
The present study characterised gene expression associated with embryonic muscle development and placental vascularisation during early gestation in the pig and examined effects of Progenos supplementation in early pregnancy. Tissues were collected from commercial multiparous sows (n = 48) from Days 16 to 49 of gestation. In the placenta, qPCR revealed that vascular endothelial growth factor (VEGFA) expression did not change from Day 17 to 49 of gestation; however, KDR receptor and angiopoietin-1 and -2 expression were differentially regulated, with periods of high expression corresponding to two critical phases of angiogenesis in the pig. In the embryo, the pattern of myogenesis-related gene expression was consistent with available literature. A commercially available nutritional supplement Progenos (20 g day⁻¹ L-arginine) added to the diet of sows from either Day 15 to 29 (P15-29; n = 33), Day 30 to 44 (n = 29) or from Day 15 to 44 (n = 76) of gestation tended to increase (P = 0.058) embryonic growth rate compared with non-supplemented controls (n = 79) and angiogenin expression was higher (P = 0.028) at Day 30 of gestation in placentae from sows on the P15-29 Progenos treatment. These results are consistent with proposed beneficial effects of l-arginine on early embryonic development and placental vascularisation.
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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".