Muramyl dipeptide and mononuclear cell supernatant induce Langhans-type cells from human monocytes
Bibliographic record
Abstract
Muramyl dipeptide (MDP) in bacterial cell walls reportedly evokes epithelioid cell granulomas. We examined its effects on multinucleated-giant-cell (MGC) formation from monocytes. Supernatant of concanavalin A-stimulated peripheral blood mononuclear cells (conditioned medium) generated MGCs from monocytes. MDP significantly increased the fusion index of Langhans-type MGCs (LGCs) but did not affect total MGCs. N-Acetylmuramyl-L-alanyl-L-isoglutamine, an MDP analogue, had no effect on MGC formation. MGCs were produced by conditioned medium from CD14(++)/CD16(-) monocytes. MDP enhanced the LGC fusion index from CD14(++)/CD16(-) monocytes. MGCs were not produced from CD14(+)/CD16(+) monocytes or immature dendritic cells induced by granulocyte macrophage-colony stimulating factor (GM-CSF) and interleukin (IL) 4 and only weakly produced from macrophage (M)-CSF- or GM-CSF-induced macrophages. Added MDP did not generate MGCs from CD14(+)/CD16(+) monocytes or dendritic cells but enhanced LGC formation from macrophages. Because IFN-gamma, IL-3, and GM-CSF reportedly are important in LGC induction, we added anti-IFN-gamma, anti-IL-3, or anti-GM-CSF monoclonal antibody (mAb) concomitantly to the monocyte culture treated with conditioned medium alone or plus MDP. Anti-IFN-gamma mAb completely abrogated MGC generation, whereas anti-GM-CSF and anti-IL-3 mAbs significantly inhibited LGCs. These findings suggest that CD14(++)/CD16(-) monocytes are fused to form LGCs by MDP derived from granulomatous-disease-causing pathogens with inflammatory mediators such as IFN-gamma, IL-3, and GM-CSF.
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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) | 0.001 | 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) | 0.001 | 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".