Cumulus Cell Transcripts Transit to the Bovine Oocyte in Preparation for Maturation1
Bibliographic record
Abstract
So far, the characteristics of a good quality egg have been elusive, similar to the nature of the physiological, cellular, and molecular cues leading to its production both in vivo and in vitro. Current understanding highlights a strong and complex interdependence between the follicular cells and the gamete. Secreted factors induce cellular responses in the follicular cells, and direct exchange of small molecules from the cumulus cells to the oocyte through gap junctions controls meiotic arrest. Studying the interconnection between the cumulus cells and the oocyte, we previously demonstrated that the somatic cells also contribute transcripts to the gamete. Here, we show that these transcripts can be visualized moving down the transzonal projections (TZPs) to the oocyte, and that a time course analysis revealed progressive RNA accumulation in the TZPs, indicating that RNA transfer occurs before the initiation of meiosis resumption under a timetable fitting with the acquisition of developmental competence. A comparison of the identity of the nascent transcripts trafficking in the TZPs, with those in the oocyte increasing in abundance during maturation, and that are present on the oocyte's polyribosomes, revealed transcripts common to all three fractions, suggesting the use of transferred transcripts for translation. Furthermore, the removal of potential RNA trafficking by stripping the cumulus cells caused a significant reduction in maturation rates, indicating the need for the cumulus cell RNA transfer to the oocyte. These results offer a new perspective to the determinants of oocyte quality and female fertility, as well as provide insight that may eventually be used to improve in vitro maturation conditions.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".