Terminally differentiated osteoclasts organize centrosomes into large clusters for microtubule nucleation and bone resorption
Bibliographic record
Abstract
Osteoclasts are highly specialized, multinucleated cells responsible for the selective resorption of the dense, calcified bone matrix. Microtubules (MTs) contribute to the polarization and trafficking events involved in bone resorption by osteoclasts; however, the origin of these elaborate arrays is less clear. Osteoclasts arise through cell fusion of precursor cells. Previous studies have suggested that centrosome MT nucleation is lost during this process, with the nuclear membrane and its surrounding Golgi serving as the major MT organizing centers (MTOCs) in these cells. Here we reveal that precursor cell centrosomes are maintained and functional in the multinucleated osteoclast and interestingly form large MTOC clusters, with the clusters organizing significantly more MTs compared with individual centrosomes. MTOC cluster formation requires dynamic MTs and minus-end directed MT motor activity. Inhibition of these centrosome clustering elements had a marked impact on both F-actin ring formation and bone resorption. Together these findings show that multinucleated osteoclasts employ unique centrosomal clusters to organize the extensive MTs during bone attachment and 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 | 0.000 | 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) | 0.001 | 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".