Buried alive: How osteoblasts become osteocytes
Bibliographic record
Abstract
During osteogenesis, osteoblasts lay down osteoid and transform into osteocytes embedded in mineralized bone matrix. Despite the fact that osteocytes are the most abundant cellular component of bone, little is known about the process of osteoblast-to-osteocyte transformation. What is known is that osteoblasts undergo a number of changes during this transformation, yet retain their connections to preosteoblasts and osteocytes. This review explores the osteoblast-to-osteocyte transformation during intramembranous ossification from both morphological and molecular perspectives. We investigate how these data support five schemes that describe how an osteoblast could become entrapped in the bone matrix (in mammals) and suggest one of the five scenarios that best fits as a model. Those osteoblasts on the bone surface that are destined for burial and destined to become osteocytes slow down matrix production compared to neighbouring osteoblasts, which continue to produce bone matrix. That is, cells that continue to produce matrix actively bury cells producing less or no new bone matrix (passive burial). We summarize which morphological and molecular changes could be used as characters (or markers) to follow the transformation process.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".