Osteocrin Is a Specific Ligand of the Natriuretic Peptide Clearance Receptor That Modulates Bone Growth
Bibliographic record
Abstract
Osteocrin (Ostn) is a recently discovered secreted protein produced by cells of the osteoblast lineage that shows a well conserved homology with members of the natriuretic peptide (NP) family. We hypothesized that Ostn could interact with the NP receptors, thereby modulating NP actions on the skeleton. Ostn binds specifically and saturably to the NP peptide receptor-C (NPR-C) receptor with a Kd of approximately 5 nM with no binding to the GC-A or GC-B receptors. Deletion of several of the residues deemed important for NP binding to NPR-C led to abolition of Ostn binding, confirming the presence of a "natriuretic motif." Functionally, Ostn was able to augment C-type natriuretic peptide-stimulated cGMP production in both pre-chondrocytic (ATDC5) and osteoblastic (UMR106) cells, suggesting increased NP levels due to attenuation of NPR-C associated NP clearance. Ostn-transgenic mice displayed elongated bones and a marked kyphosis associated with elevated bone cGMP levels, suggesting that elevated natriuretic peptide activity contributed to the increased bone length possibly through an increase in growth plate chondrocyte proliferation. Thus, we have demonstrated that Ostn is a naturally occurring ligand of the NPR-C clearance receptor and may act to locally modulate the actions of the natriuretic system in bone by blocking the clearance action of NPR-C, thus locally elevating levels of C-type natriuretic peptide.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".