The Ephrin Signaling Pathway Regulates Morphology and Adhesion of Mouse Granulosa Cells In Vitro1
Bibliographic record
Abstract
Follicle-stimulating hormone (FSH)-mediated changes in granulosa cell adhesion and morphology are essential for preovulatory follicle development, given the dramatic changes in follicle size and granulosa cell number that occur during this transition. Members of the Eph-ephrin family of cell-positioning and adhesion molecules, a family that consists of ephrin ligands and their Ephrin (Eph) receptors, regulate cell location, adhesion, and migration during embryonic development and tumor growth. However, very little is known about ephrin signaling during folliculogenesis. We have found that FSH increases the expression of several members of the Eph-ephrin family and that this signaling regulates granulosa cell morphology and adhesion. FSH induced increased mRNA levels of the ephrin ligand, ephrin-A5 (Efna5), and its receptors, Eph receptors A3, A5, and A8 (Epha3, Epha5, and Epha8, respectively), in granulosa cells. Immunofluorescence studies indicated that EFNA5 and EPHA5 are located in the membrane of granulosa cells of developing mouse follicles. Eph-ephrin signaling directly affected granulosa cell morphology and adhesion. Recombinant EFNA5 reduced cell spreading and increased cell rounding in mouse primary granulosa cells and in a rat granulosa cell line, whereas EPHA5 reduced granulosa cell adhesion in both model systems. Both FSH and forskolin also increased Efna5 and Epha5 mRNA levels in rat and human granulosa cell lines, indicating that FSH regulates these genes via the cAMP-dependent protein kinase A pathway and that this regulation is conserved across different species. The present study identifies Eph-ephrin signaling as a novel FSH-mediated pathway regulating granulosa cell morphology and adhesion.
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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 | 0.001 | 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) | 0.001 | 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".