Fibroblast growth factor-2 regulation of sprouty and NR4A genes in bovine ovarian granulosa cells
Bibliographic record
Abstract
Fibroblast growth factors (FGFs) alter ovarian function, at least in part by inhibiting steroid hormone secretion and affecting survival of granulosa cells. The mechanism of action of FGFs in ovarian follicle cells is largely unknown; in the present study we identified the major pathways used by FGF2 in non-luteinizing granulosa cells cultured under serum-free conditions. FGF2 increased abundance of mRNA encoding SPRY1, 2, and 4, but not SPRY3. Common pathways employed by FGF2 in the regulation of SPRY1, 2, and 4, as demonstrated by immunoblot and inhibitor studies, included ERK1/2 and Akt signaling. In contrast, PKC activation was necessary for FGF2-stimulated expression of SPRY1 and 4, but not for SPRY2. Intracellular calcium flux is critical and sufficient for SPRY2 expression, but not for SPRY1 and 4. We also identified the orphan nuclear receptor NR4A1 as a potential early response gene in FGF2 signaling, whose expression, like that of SPRY2, is critically dependent on calcium signaling. Together, these data identify FGF2-target genes in follicular granulosa cells, and demonstrate alternative pathway use for the differential control of SPRY genes.
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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".