Modulation of Osteoclastogenesis with Macrophage M1- and M2-Inducing Stimuli
Bibliographic record
Abstract
Macrophages are generated through the differentiation of monocytes in tissues and they have important functions in innate and adaptive immunity. In addition to their roles as phagocytes, macrophages can be further differentiated, in the presence of receptor activator of nuclear factor kappa-B ligand (RANKL) and macrophage colony-stimulating factor (M-CSF), into osteoclasts (multinucleated giant cells that are responsible for bone resorption). In this work, we set out to characterize whether various inflammatory stimuli, known to induce macrophage polarization, can alter the type of multinucleated giant cell obtained from RANKL differentiation. Following a four-day differentiation protocol, along with lipopolysaccharide (LPS)/interferon gamma (IFNγ) as one stimulus, and interleukin-4 (IL-4) as the other, three types of multinucleated cells were generated. Using various microscopy techniques (bright field, epifluorescence and scanning electron), functional assays, and western blotting for osteoclast markers, we found that, as expected, RANKL treatment alone resulted in osteoclasts, whereas the addition of LPS/IFNγ to RANKL pre-treated macrophages generated Langhans-type giant cells, while IL-4 led to giant cells resembling foreign body giant cells with osteoclast-like characteristics. Finally, to gain insight into the modulation of osteoclastogenesis, we characterized the formation and morphology of RANKL and LPS/IFNγ-induced multinucleated giant cells.
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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".