Oocyte-derived BMP15 but not GDF9 down-regulates connexin43 expression and decreases gap junction intercellular communication activity in immortalized human granulosa cells
Bibliographic record
Abstract
In the ovary, connexin-coupled gap junctions in granulosa cells play crucial roles in follicular and oocyte development as well as in corpus luteum formation. Our previous work has shown that theca cell-derived bone morphogenetic protein (BMP)4 and BMP7 decrease gap junction intercellular communication (GJIC) activity via the down-regulation of connexin43 (Cx43) expression in immortalized human granulosa cells. However, the effects of oocyte-derived growth factors on Cx43 expression remain to be elucidated. The present study was designed to investigate the effects of oocyte-derived growth differentiation factor (GDF)9 and BMP15 on the expression of Cx43 in a human granulosa cell line, SVOG. We also examined the effect relative to GJIC activity and investigated the potential mechanisms of action. In SVOG cells, treatment with BMP15 but not GDF9 significantly decreased Cx43 mRNA and protein levels and GJIC activity. These suppressive effects, along with the induction of Smad1/5/8 phosphorylation, were attenuated by co-treatment with a BMP type I receptor inhibitor, dorsomorphin. Furthermore, knockdown of the central component of the transforming growth factor-β superfamily signaling pathway, Smad4, using small interfering RNA reversed the suppressive effects of BMP15 on Cx43 expression and GJIC activity. The suppressive effects of BMP15 on Cx43 expression were further confirmed in primary human granulosa-lutein cells obtained from infertile patients undergoing an in vitro fertilization procedure. These findings suggest that oocyte-derived BMP15 decreases GJIC activity between human granulosa cells by down-regulating Cx43 expression, most likely via a Smad-dependent signaling pathway.
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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".