Osteoclasts: characteristics and regulation of formation and activity
Bibliographic record
Abstract
Introduction Bone tissue adapts itself continuously to changing demands during development and growth (modeling) and in response to stress or damage (remodeling). The modeling and remodeling processes involve degradation of bone tissue by large multinucleated cells, called osteoclasts, and synthesis and deposition of new bone by mononuclear cuboidal cells lining bone, called osteoblasts. A close anatomical and functional relationship exists between resorptive and formative cells at discrete remodeling sites called ‘basic multicellular units of bone remodeling’ or BMU (Frost, 1966). This is, in all likelihood, responsible for the phenomenon in which treatments of metabolic bone disease developed to inhibit resorption often result in simultaneous inhibition of formation. The mechanism(s) whereby the actions of the resorbing osteoclasts and the bone forming osteoblasts are co-ordinated are not yet clear. Nevertheless, striking progress has been made in our understanding of osteoblast—osteoclast interaction with regard to regulating osteoclast formation. This chapter focuses on osteoclasts and osteoclastic bone resorption. Morphological characteristics of osteoclasts, the processes whereby osteoclasts degrade bone, the origin of osteoclasts and the regulation of osteoclast formation and activity will be reviewed here. Morphological characteristics of osteoclasts Osteoclasts are easily recognized in histological sections of bone tissue as large multinucleated cells with up to 25 nuclei and are found in close association with bone surfaces (Fig. 3.1).
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".