Eugenol as a natural antioxidant for porcine in vitro embryo production
Bibliographic record
Abstract
Oxidative stress negatively affects oocyte quality and embryo development during in vitro embryo production (IVEP). Plant-derived antioxidants, such as eugenol (EG), have emerged as promising alternatives to mitigate the detrimental impacts of reactive oxygen species (ROS) and enhance IVEP outcomes and embryo quality. This study evaluated EG as a potential antioxidant for porcine oocyte in vitro maturation (IVM) and embryo culture (IVC). In the first experiment, cumulus-oocyte complexes (COCs) were matured in vitro with varying concentrations of EG (0, 10, 20, 30, 40, 60 or 80 μM), and subsequent cleavage, development, morphology and total cell number at the blastocyst stage were assessed. The 60 μM (EG60) concentration was selected for further experiments, as it yielded the highest numerical rate of blastocyst formation and a significantly higher proportion of expanded blastocysts. In the second experiment, IVM medium with EG60 or cysteine (CYS; 100 μg/mL) supported similar blastocyst development rates, although no additive effect was observed when both were combined. Notably, EG60 significantly reduced ROS levels in matured oocytes and produced a numerically higher, hence not statistically significant, rate of hatched blastocysts compared to CYS. Additionally, PTGS1 mRNA abundance in cumulus cells (CCs) was significantly higher in the EG60 group than in the CYS group. Finally, the supplementation of the IVC medium with 80 μM EG reduced ROS levels in blastocysts but did not significantly improve embryo development rates and blastocyst cell number. These findings suggest that eugenol is an effective natural antioxidant for enhancing in vitro embryo production 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 | 0.001 |
| 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".