Effects of Breed, Parity, and Folic Acid Supplement on the Expression of Folate Metabolism Genes in Endometrial and Embryonic Tissues from Sows in Early Pregnancy1
Bibliographic record
Abstract
Folic acid and glycine are factors of great importance in early gestation. In sows, folic acid supplement can increase litter size through a decrease in embryonic mortality, while glycine, the most abundant amino acid in the sow oviduct, uterine, and allantoic fluids, is reported to act as an organic osmoregulator. In this study, we report the characterization of cytoplasmic serine hydroxymethyltransferase (cSHMT), T-protein, and vT-protein (variant T-protein) mRNA expression levels in endometrial and embryonic tissues in gestating sows on Day 25 of gestation according to the breed, parity, and folic acid + glycine supplementation. Expression levels of cSHMT, T-protein, and vT-protein mRNA in endometrial and embryonic tissues were performed using semiquantitative reverse transcription-polymerase chain reaction. We also report, for the first time, an alternative splicing event in the porcine T-protein gene. Results showed that a T-protein splice variant, vT-protein, is present in all the tested sow populations. Further characterizations revealed that this T-protein splice variant contains a coding intron that can adopt a secondary structure. Results demonstrated that cSHMT mRNA expression levels were significantly higher in sows receiving the folic acid + glycine supplementation, independently of the breed or parity and in both endometrial and embryonic tissues. Upon receiving the same treatment, the vT-protein and T-protein mRNA expression levels were significantly reduced in the endometrial tissue of Yorkshire-Landrace sows only. These results indicate that modulation of specific gene expression levels in endometrial and embryonic tissues of sows in early gestation could be one of the mechanism involved with the role of folic acid on improving swine reproduction traits.
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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".