Bone morphogenetic protein 2 and activin A synergistically stimulate follicle-stimulating hormone β subunit transcription
Bibliographic record
Abstract
Transforming growth factor beta superfamily ligands regulate pituitary FSH production and secretion. The best-described examples are the activins and inhibins, which respectively stimulate and hinder Fshb subunit transcription in gonadotrope cells. More recently, members of the bone morphogenetic protein (BMP) sub-family were shown to regulate FSH production in a manner analogous to the activins. Here, we used the murine gonadotrope cell line, LbetaT2, to investigate mechanisms through which BMP2 regulates the Fshb gene. Although expressed at low levels in LbetaT2 cells, Bmp2 mRNA was readily detected in adult murine pituitary gland. Recombinant BMP2 stimulated Fshb promoter-reporter activity, although its effects were weaker than those of equimolar activin A or B. BMP4 stimulated transcription comparably with BMP2, but BMPs 6 and 7 were about tenfold less potent. Remarkably, BMP2 and activin A synergistically upregulated Fshb transcription and endogenous Fshb mRNA levels in LbetaT2 cells. Although functionally cooperative, the two ligands appeared to use distinct intracellular mechanisms to mediate their responses because neither ligand altered the timing or magnitude of the other's effects. Receptor overexpression analyses suggested that BMP2 may preferentially signal through complexes of the type II receptor, BMPR2, and the type I receptor, activin receptor like kinase (ALK2; Acvr1), to stimulate Fshb transcription. BMP2 rapidly activated the Smad1/5/8 intracellular signaling cascade and Smad8 overexpression potentiated BMP2's effects. In summary, BMPs regulate Fshb transcription in LbetaT2 cells and can amplify the already robust effects of the activins through a distinct signaling mechanism. Because BMP2 is expressed in the adult mouse pituitary, it may act as critical paracrine co-regulator of FSH synthesis by gonadotropes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.003 | 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".