Glycerol Supplementation During Oestrus Synchronisation With Fluorogestone Acetate Affects Follicular Proliferation, Maturation and Apoptosis of Granulosa Cells in Pelibuey Ewes
Bibliographic record
Abstract
This study investigated the impact of glycerol supplementation on the expression of markers associated with follicular proliferation, maturation and apoptosis in Pelibuey ewes synchronised with long (11 days) and short (5 days) protocols using intravaginal fluorogestone acetate (FGA). Forty-five adult Pelibuey ewes were divided into five groups: control, short protocol with or without glycerol and long protocol with or without glycerol. Follicular dynamics were monitored by ultrasonography, and granulosa cells were collected 15 h after the onset of oestrus to analyse gene expression using RT-qPCR of genes associated with proliferation, maturation, and apoptosis. Results indicated that glycerol supplementation or the duration of the synchronisation protocol influenced the expression of genes related to apoptosis, proliferation and maturation. Specifically, glycerol-treated groups exhibited decreased BCL2 expression, and the ratio BCL2/BAX was lower in all treatment groups compared to the control, particularly in the short protocol plus glycerol. We conclude that the use of glycerol as an ultrashort supplementation during different synchronisation protocols leads to a delay in maturation and induces apoptotic-related pathways in granulosa cells to granulosa cell likely reducing the oocyte viability. Finally, glycerol treatment does not increase the abundance of PCNA associated with granulosa cell proliferation. However, it is observed that short-term treatments promote proliferation compared to the control group.
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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".