Synergistic effects of lipopolysaccharides from periodontopathic bacteria on pro-inflammatory cytokine production in an<i>ex vivo</i>whole blood model
Bibliographic record
Abstract
Porphyromonas gingivalis, Treponema denticola, and Tannerella forsythia have been strongly associated with chronic periodontitis. This disease is characterized by an accumulation of inflammatory cells in periodontal tissue and subgingival sites. The secretion of high levels of inflammatory cytokines by those cells is believed to contribute to periodontal tissue destruction. The aim of this study was to investigate the inflammatory response of whole blood from periodontitis patients following challenges with whole cells of P. gingivalis, T. denticola, and T. forsythia or their lipopolysaccharides (LPS), individually and in combination. Whole blood collected from seven periodontitis patients was stimulated with whole cells or LPS and the production of interleukin (IL)-1beta, IL-6, IL-8, and tumor necrosis factor alpha (TNF-alpha) were quantified by enzyme-linked immunosorbent assays. The mono and mixed challenges with whole bacterial cells or LPS induced the secretion of high amounts of IL-1beta, IL-6, IL-8, and TNF-alpha by the mixed leukocyte population from periodontitis patients. In addition, P. gingivalis LPS, T. denticola LPS, and T. forsythia LPS acted in synergy to induce high levels of IL-1beta and TNF-alpha. This study suggests that P. gingivalis, T. denticola, and T. forsythia may contribute to the immunodestructive host response characteristic of periodontitis through synergistic effects of their LPS on the inflammatory response induced by a mixed population of leukocytes.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".