Effect of periodontopathogen lipopolysaccharides and proinflammatory cytokines on CD46, CD55, and CD59 gene/protein expression by oral epithelial cells
Bibliographic record
Abstract
Membrane-anchored complement regulatory proteins (CRPs), including CD46, CD55, and CD59, protect host cells from complement attack. In the present study, we investigated whether periodontopathogen lipopolysaccharide and proinflammatory cytokines modulate CRP gene/protein expression in human oral epithelial cells. The lipopolysaccharide of Treponema denticola and Tannerella forsythia were the most potent for increasing the gene expression of CD55 and CD59, and to a lesser extent CD46, after a 48-h stimulation. An lipopolysaccharide-induced upregulation of epithelial cell-surface CRP was also demonstrated. The stimulation of epithelial cells with lipopolysaccharide was associated with interleukin-6 (IL-6) and IL-8 secretion. Although these two cytokines had no effect on CD46 and CD55 gene expression in epithelial cells, IL-1β and tumor necrosis factor-α induced a significant upregulation. The cell-surface expression of CRP was also increased by the stimulation of epithelial cells with cytokines. The CD46, CD55, and CD59 gene/protein expression was upregulated by periodontopathogen lipopolysaccharide and proinflammatory cytokines. It can be hypothesized that, when faced with bacterial challenges and inflammatory conditions associated with active periodontal sites, oral epithelial cells may respond by increasing CRP gene/protein expression to avoid cell lysis by the complement system, which is activated during 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 | 0.000 |
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 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".