DRAGON, a Bone Morphogenetic Protein Co-receptor
Bibliographic record
Abstract
Bone morphogenetic proteins (BMPs) are members of the transforming growth factor (TGF)beta superfamily of ligands that regulate many crucial aspects of embryonic development and organogenesis. Unlike other TGFbeta ligands, co-receptors for BMP ligands have not been described. Here we show that DRAGON, a glycosylphosphatidylinositol-anchored member of the repulsive guidance molecule family, which is expressed early in the developing nervous system, enhances BMP but not TGFbeta signaling. DRAGON binds directly to BMP2 and BMP4 but not to BMP7 or other TGFbeta ligands. The enhancing action of DRAGON on BMP signaling is also reduced by administration of Noggin, a soluble BMP antagonist, indicating that the action of DRAGON is ligand-dependent. DRAGON associates directly with BMP type I (ALK2, ALK3, and ALK6) and type II (ActRII and ActRIIB) receptors, and its signaling is reduced by dominant negative Smad1 and ALK3 or -6 receptors. In the Xenopus embryo, DRAGON both reduces the threshold of the ability of Smad1 to induce mesodermal and endodermal markers and alters neuronal and neural crest patterning. The direct interaction of DRAGON with BMP ligands and receptors indicates that it is a BMP co-receptor that potentiates BMP signaling.
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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) | 0.002 | 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".