Effects of EGF and melatonin on gene expression of cumulus cells and further<i>in vitro</i>embryo development in bovines
Bibliographic record
Abstract
Summary Despite previous research demonstrating the benefits of including growth factors and antioxidants to maturation medium to support embryo production, to date the effect of epidermal growth factor (EGF) and melatonin (Mel) on oocyte competency has not been studied. This study supplementedin vitromaturation (IVM) medium with EGF (10 ng/ml) and Mel (50 ng/ml) alone, or in combination, and evaluated cumulus cell (CC) gene expression and the development and quality of parthenogenetic blastocysts. No differences in CC gene expression levels indicative of developmental potential were found among the treatment groups. Antioxidant geneCuZnSODwas significantly (P< 0.05) decreased in CCs from the Mel group. Moreover, blastocyst rates on day 7 were significantly increased in EGF or Mel (P< 0.05), but not EGF+Mel. Significant decrease (P< 0.05) inGPX1,CuZnSOD,SLC2A1andHSPA1A(P= 0.07) mRNA levels was observed in blastocysts from the Mel group.OCT4gene expression was significantly increased (P< 0.05) in EGF+Mel and confirmed using immunofluorescence. Our results indicate that, despite the lack of changes of competence-related genes in CCs, IVM medium supplemented with Mel improved the culture environment sufficiently, resulting in improved blastocysts. Moreover, EGF and Mel combined during maturation increasedOCT4gene and protein expression in blastocysts, indicating its potential for stem cells.
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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".