IL1β and TNFα promote RANKL-dependent adseverin expression and osteoclastogenesis
Bibliographic record
Abstract
Adseverin is an actin-binding protein involved in osteoclastogenesis, but its role in inflammation-induced bone loss is not well-defined. Here, we examined whether IL1β and TNFα regulate adseverin expression to control osteoclastogenesis in mouse primary monocytes and RAW264.7 cells. Adseverin was colocalized with subcortical actin filaments and was enriched in the fusopods of fusing cells. In precursor cells, adseverin overexpression boosted the formation of RANKL-induced multinucleated cells. Both IL1β and TNFα enhanced RANKL-dependent TRAcP activity by 1.6-fold and multinucleated cell formation (cells with ≥3 nuclei) by 2.6- and 3.3-fold, respectively. However, IL1β and TNFα did not enhance osteoclast formation in adseverin-knockdown cells. RANKL-dependent adseverin expression in bone marrow cells was increased by both IL1β (5.4-fold) and TNFα (3.3-fold). Luciferase assays demonstrated that this expression involved transcriptional regulation of the adseverin promoter. Activation of the promoter was restricted to a 1118 bp sequence containing an NF-κB binding site, upstream of the transcription start site. TNFα also promoted RANKL-induced osteoclast precursor cell migration. We conclude that IL1β and TNFα enhance RANKL-dependent expression of adseverin, which contributes to fusion processes in osteoclastogenesis.
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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".