297 Exposure to high level of NEFAs slightly impairs the in vitro maturation and the in vitro fertilized embryos in porcine.
Bibliographic record
Abstract
Increasing evidence indicates that maternal malnutrition leads to decreased female fertility and deregulated metabolic homeostasis in offspring, and these performances may be related to the high level of non-esterified fatty acids (NEFAs) in the maternal follicular fluid (FF), but the mechanisms remain unclear. This study is aiming to explore the effect of abnormal NEFAs level on porcine oocyte maturation and early embryo development. We used porcine monolayer of granulosa cells and cumulus-oocyte complexes co-cultured system to mimic the follicular microenvironment. 1% and 10% of porcine FF (PFF) were used to find whether we can more effectively explore the effect of NEFAs by diminishing the interference of PFF. With 1% PFF, the maturation rate was 73.20 % (n=106) which was not significantly different compared to 10% PFF group (86.57 %, n=163), and the blastocyst rate was also similar (27.23 %, n=19 vs. 25.42 %, n=25). Considering the main components of NEFAs in PFF, NEFAs level (combination of 468 μM palmitic acid, 194 μM stearic acid, and 534 μM oleic acid) was used and named High Combi group. After 44 h co-cultured, the maturation rate of High Combi group (with a limited number of replicates) seemed lower than the group without supplement of NEFAs (49.98 % vs 73.20 %, P>0.05), and most of these oocytes in High Combi were retarded at Metaphase I. After in vitro fertilization, the blastocyst rate was also decreased (not significant) in High Combi group (20. 30 % vs. 27.23 %). Therefore, with decreased PFF concentration of 1% we can more properly explore the effect of NEFAs, and our preliminary results showed the possible slight impairment of the high NEFAs level on porcine oocyte maturation and the development of early embryos, making this system a good model for studying the transgenerational effect at the transcriptomic and epigenetic level.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".