Bone morphogenetic protein 2 inhibits growth differentiation factor 8-induced cell signaling via upregulation of gremlin2 expression in human granulosa-lutein cells
Bibliographic record
Abstract
BACKGROUND: Bone morphogenetic protein 2 (BMP2), growth differentiation factor 8 (GDF8) and their functional receptors are expressed in human ovarian follicles, and these two intrafollicular factors play essential roles in regulating follicle development and luteal function. As BMP antagonists, gremlin1 (GREM1) and gremlin2 (GREM2) suppress BMP signaling through blockage of ligand-receptor binding. However, whether BMP2 regulates the expression of GREM1 and GREM2 in follicular development remains to be determined. METHODS: In the present study, we investigated the effect of BMP2 on the expression of GREM1 and GREM2 and the underlying mechanisms in human granulosa-lutein (hGL) cells. An established immortalized human granulosa cell line (SVOG) and primary hGL cells were used as study models. The expression of GREM1 and GREM2 were examined following cell incubation with BMP2 at different concentrations and time courses. The TGF-β type I inhibitors (dorsomorphin, DMH-1 and SB431542) and small interfering RNAs targeting ALK2, ALK3, SMAD2/3, SMAD1/5/8 and SMAD4 were used to investigate the involvement of the SMAD-dependent pathway. RESULTS: Our results showed that BMP2 significantly increased the expression of GREM2 (but not GREM1) in a dose- and time-dependent manner. Using a dual inhibition approach combining kinase inhibitors and siRNA-mediated knockdown, we found that the BMP2-induced upregulation of GREM2 expression was mediated by the ALK2/3-SMAD1/5-SMAD4 signaling pathway. Moreover, we demonstrated that BMP2 pretreatment significantly attenuated the GDF8-induced phosphorylation of SMAD2 and SMAD3, and this suppressive effect was reversed by knocking down GREM2 expression. CONCLUSIONS: Our findings provide new insight into the molecular mechanisms by which BMP2 modulates the cellular activity induced by GDF8 through the upregulated expression of their antagonist (GREM2).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".