Response of human macrophage‐like cells to stimulation by <i>Fusobacterium nucleatum</i> ssp. <i>nucleatum</i> lipopolysaccharide
Bibliographic record
Abstract
Monocytes/macrophages are key members of the innate immune system and are present in higher numbers in active periodontal lesions than in inactive sites. The aim of this study was to characterize the response of human monocyte U937 cells, differentiated into adherent macrophages by treatment with phorbol-12-myristate 13-acetate, to stimulation by Fusobacterium nucleatum ssp. nucleatum lipopolysaccharide. Attachment of (3)H-lipopolysaccharide to macrophage-like cells was partially inhibited by anti-CD14 and anti-TLR4 polyclonal antibodies. Fusobacterial lipopolysaccharide did not cause cell apoptosis or block apoptosis induced by camptothecin. Lipopolysaccharide up-regulated the secretion of the pro-inflammatory cytokines interleukin-1beta, interleukin-6, and tumor necrosis factor-alpha as well as the chemokine interleukin-8 by macrophage-like cells. In addition, it increased phospholipase C and D activities, which likely contributed to the high levels of prostaglandin E(2) detected in the cell culture supernatant. Lastly, the amount of matrix metalloproteinase-9 produced by macrophage-like cells was significantly increased by the lipopolysaccharide treatment. Interestingly, fusobacterial cells acquired matrix metalloproteinase-9 activity following incubation in the presence of the culture supernatant of lipopolysaccharide-stimulated macrophage-like cells. In summary, the lipopolysaccharide of F. nucleatum ssp. nucleatum has a large array of biological effects on macrophage-like cells. This monocytic responsiveness to lipopolysaccharide may be a key regulator of periodontitis.
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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 | 0.000 | 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) | 0.001 | 0.001 |
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".