Non-muscle myosin II-dependent cumulus cell migration at ovulation is required for sperm to reach the egg in mice
Bibliographic record
Abstract
At ovulation in mammals, epidermal growth factor (EGFR) signaling in the cumulus granulosa cells that enclose the egg causes them to generate an extracellular matrix and become dispersed within it. This process, termed expansion, is required for sperm to reach the egg. The extracellular signal-related kinase (ERK) pathway mediates matrix production, but the mechanism responsible for cell dispersion is poorly understood. We show that EGFR signaling activates non-muscle myosin II (NMII) in the cumulus cells and that NMII activity is required for full expansion. NMII activation does not require ERK signaling, but instead depends on the Rho-associated coiled-coil containing kinases (ROCK) and the myotonic dystrophy kinase-related CDC42-binding kinases (MRCK). Blocking ROCK or MRCK impairs the ability of the cumulus cells to migrate and reduces the number of sperm that penetrate through the cumulus layer to reach the oocyte. EGFR thus promotes cumulus layer expansion by integrating ERK-dependent production of the matrix with NMII-dependent migration of the cumulus cells within it. Activation by the epidermal growth factor receptor signaling pathway of non-muscle myosin II within the cumulus granulosa cells that surround the oocyte enables their migration away from it thereby facilitating sperm access and fertilization.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".