An adherent condition is required for formation of multinuclear osteoclasts in the presence of macrophage colony-stimulating factor and receptor activator of nuclear factor κB ligand
Bibliographic record
Abstract
Identification of receptor activator of nuclear factor-kappaB (RANK) and RANK-ligand (RANKL) has provided new insights into the osteoclast differentiation pathway. Osteoclast precursor cells were isolated using monoclonal antibodies against c-Fms and RANK, and the effect of adherence on the in vitro differentiation and proliferation of these cells was examined in 2 different types of stromal-cell-free culture systems: a semisolid culture medium (a nonadherent system) and a liquid culture medium (an adherent system). Osteoclast precursor cells were not able to differentiate into mature osteoclasts efficiently in the semisolid culture system. Trimerized RANKL enhanced osteoclast differentiation in semisolid cultures, but not to the extent seen when cells were allowed to adhere to plastic. Initial precursor cells were capable of differentiating into macrophages or osteoclasts. Once these cells were transferred to adherent conditions, striking differentiation was induced. Multinuclear cells were observed even after they had displayed phagocytic activity, which suggests that cell adhesion plays an important role in the differentiation of osteoclast precursor cells. Integrins, especially the arginine-glycine-aspartic acid (RGD)-recognizing integrins alpha(v) and beta(3), were needed for osteoclast-committed precursor cells to proliferate in order to form multinuclear osteoclasts, and the increase in cell density affected the formation of multinuclear cells. A model of osteoclast differentiation with 2 stages of precursor development is proposed: (1) a first stage, in which precursor cells are bipotential and capable of anchorage-independent growth, and (2) a second stage, in which the further proliferation and differentiation of osteoclast-committed precursor cells is anchorage-dependent. (Blood. 2000;96:4335-4343)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".