SMAD3 directly regulates cell cycle genes to maintain arrest in granulosa cells of mouse primordial follicles
Bibliographic record
Abstract
Primordial follicles, consisting of granulosa cell (GC)-enveloped oocytes are maintained in a state of developmental arrest until activated to grow. The mechanism that operates to maintain this arrested state in GCs is currently unknown. Here, we show the TGFβ-activated transcription factor SMAD3 is expressed in primordial GC nuclei alongside the cell cycle proteins, cyclin D2 (CCND2) and P27. Using neonatal C57/Bl6 mouse ovaries densely populated with primordial follicles, CCND2 protein co-localised and was detected in complex with P27 by immunofluorescence and co-immunoprecipitation, respectively. In the same tissue, SMAD3 co-precipitated with DNA sequences upstream of Ccnd2 and Myc transcription start sites implicating both as direct SMAD3 targets. In older ovaries follicle growth was associated with nuclear exclusion of SMAD3 and reduced P27 and CCND2 in GCs, alongside elevated Myc expression. Brief (2 H) exposure of neonatal ovaries to TGFβ1 (10 ng/ml) in vitro led to immediate dissociation of SMAD3 from the Ccnd2 and Myc promoters. This coincided with elevated Myc and phospho-S6, an indicator of mTOR signalling, followed by a small increase in mean primordial GC number after 48 H. These findings highlight a concentration-dependent role for TGFβ signalling in the maintenance and activation of primordial follicles, through SMAD-dependent and independent signalling pathways, respectively.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".