Characterization of FSH signalling networks in bovine cumulus cells: a perspective on oocyte competence acquisition
Bibliographic record
Abstract
Understanding the mechanisms regulating oocyte developmental competence is essential to enhance the clinical efficiency of assisted reproduction. FSH orchestrates the acquisition of oocyte competence, both in vivo and in vitro. Multiple pathways are implicated in FSH signalling; however, their precise coordination remains unresolved. A robust system to investigate FSH signalling is oocyte in vitro maturation (IVM) and we have previously demonstrated better bovine embryo development after FSH addition for the first 6 h during IVM. Using this model, we investigated FSH signalling in cumulus through transcriptomic and pharmacological tools. We demonstrate modulation of cumulus transcriptome by FSH mainly through protein kinase A (PKA) and epidermal growth factor (EGF) pathways. Differentially expressed transcripts were implicated in cumulus expansion, steroidogenesis, cell metabolism and oocyte competence. FSH required rouse-sarcoma oncogene (SRC) for EGF receptor transactivation. PKA and EGF pathway crosstalk was investigated using extracellular signal-regulated kinases (ERK1/2) phosphorylation as the functional end-point. FSH enhanced ERK1/2 activation by the EGF pathway with a simultaneous diminution through PKA. More specifically, FSH increased dual specific phosphatase (DUSP1) transcripts via PKA although DUSP1 protein did not change since EGF was required to prevent degradation. Our findings implicate FSH in PKA and EGF pathway activation, which interact to maintain appropriate levels of ERK1/2 phosphorylation and eventually cumulus expansion, metabolism and steroidogenesis. Moreover, considering the implication of the EGF pathway in GDF9 and BMP15 actions, our findings suggest that FSH may have a role in modulation of the cumulus response to oocyte-secreted factors. This information has implications for improvement of IVM and hence oocyte developmental competence.
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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".