Heparin acts synergistically with interleukin-11 to induce STAT3 activation and in vitro osteoclast formation
Bibliographic record
Abstract
We have previously demonstrated that long-term heparin treatment causes cancellous bone loss in rats due in part to an increase in the number of osteoclasts lining the trabecular bone surface. In the present study, we investigated this phenomenon by examining the ability of heparin to synergistically enhance interleukin-11 (IL-11)-induced osteoclast formation. Treatment of murine calvaria and bone marrow cells with IL-11 was found to induce the formation of tartrate-resistant acid phosphatase-positive (TRAP(+)) multinucleated cells (MNCs) in a dose-dependent fashion. No effect was seen when cocultures were treated with heparin alone. However, when cocultures were treated with both IL-11 and heparin, IL-11's ability to induce TRAP(+) MNC formation was enhanced 6-fold. In an attempt to resolve the mechanism responsible for this effect, we examined the ability of heparin to influence IL-11 signaling using murine calvaria cells. Heparin was found to enhance both IL-11-induced STAT3-DNA complex formation and transactivation without altering either STAT3 (signal transducer and activator of transcription-3) tyrosine or serine phosphorylation. Heparin was also found to enhance IL-11's ability to induce the expression of both receptor activator of nuclear factor-kappaB ligand (RANKL) and glycoprotein (gp) 130. When taken together, these findings suggest a plausible mechanism by which heparin may cause increased osteoclastogenesis and therefore bone loss when administered long-term.
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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) | 0.000 | 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) | 0.000 | 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".