Multiple roles of M‐CSF in human osteoclastogenesis
Bibliographic record
Abstract
Although the critical role of M-CSF in osteoclastogenesis is well documented, there has been no detailed analysis of how it regulates human osteoclast formation and function in vitro. We used a human osteoclastogenesis model employing CFU-GM osteoclast precursors cultured for 14 days on dentine with RANKL, with varying exposure to exogenous human M-CSF. Short-term treatment of precursors with M-CSF (10-100 ng/mL) resulted in increased proliferation with or without RANKL. Treatment with M-CSF (1-100 ng/mL) for 14 days caused a biphasic concentration-dependent stimulation of formation, fusion, and resorption peaking at 10-50 ng/mL and almost complete abolition of resorption at 100 ng/mL. Time-course studies using M-CSF (25 ng/mL) showed that osteoclast size, nuclei/cell, and resorption increased with longer duration of M-CSF treatment. When treatment was restricted to the first 4 days, M-CSF (25-100 ng/mL) stimulated formation of normal numbers of osteoclasts that resorbed less. Blockade of endogenous M-CSF signaling with neutralizing M-CSF antibody during the first week of culture extensively inhibited osteoclastogenesis, whereas blockade during the second week produced only a small reduction in resorption. Treatment with M-CSF during the second week of culture caused a small increase in osteoclast number and a concentration-dependent increase in cytoplasmic spreading with inhibition of resorption. We have shown that M-CSF modulates multiple steps of human osteoclastogenesis, including proliferation, differentiation and fusion of precursors. In the later stages of osteoclastogenesis, M-CSF modulates osteoclast-resorbing activity, but is not required for survival. Modulation of M-CSF signaling is a potential therapeutic target for conditions associated with excess bone resorption.
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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 | 0.001 | 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 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".