Apoptotic osteocytes regulate osteoclast precursor recruitment and differentiation in vitro
Bibliographic record
Abstract
Fatigue loading causes a spatial distribution of osteocyte apoptosis co-localized with bone resorption spaces peaking around microdamage sites. Since osteocytes have been shown to regulate osteoclast formation and activity, we hypothesize that osteocyte apoptosis regulates osteoclastogenesis. In this study, we used serum-starvation to mimic reduced nutrient transport in microdamaged bone and induce apoptosis in MLO-Y4 osteocyte-like cells; conditioned medium was used to apply soluble factors released by apoptotic osteocytes (aOCY) to healthy non-apoptotic MLO-Y4 cells. Osteoclast precursor (RAW264.7 monocyte) migration and differentiation were assessed in the presence of conditioned media (CM) from: (A) aOCY, (B) osteocytes treated with apoptosis conditioned medium (i.e., healthy osteocytes in the presence of apoptosis cues; apoptosis CM-treated osteocytes (atOCY)), and (C) osteocytes treated with non-apoptosis conditioned medium (i.e., healthy osteocytes in the absence of apoptosis cues; non-apoptosis CM-treated osteocytes (natOCY)). Receptor activator for nuclear factor-κB ligand (RANKL), macrophage colony stimulating factor (M-CSF), vascular endothelial growth factor (VEGF) and osteoprotegerin (OPG) mRNA, and protein expression were measured. Our findings indicate that soluble factors released by aOCY and atOCY promoted osteoclast precursor migration (up to 64% and 24% increase, respectively) and osteoclast formation (up to 450% and 265% increase, respectively). Osteoclast size increased up to 233% in the presence of aOCY and atOCY CM. Recruitment, formation and size were unaltered by natOCY. RANKL mRNA and protein expression were upregulated only in aOCY, while M-CSF and VEGF increased in atOCY. Addition of RANKL-blocking antibody abolished aOCY-induced osteoclast precursor migration and osteoclast formation. VEGF and M-CSF blocking antibodies abolished atOCY-induced osteoclastogenesis. These findings suggest that aOCY directly and indirectly (through atOCY) initiate targeted bone resorption by regulating osteoclast precursor recruitment and differentiation.
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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 | 0.001 |
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".