Cranberry components inhibit interleukin‐6, interleukin‐8, and prostaglandin E<sub>2</sub> production by lipopolysaccharide‐activated gingival fibroblasts
Bibliographic record
Abstract
Periodontitis is a chronic inflammatory disease that affects the tooth supporting tissues. Gingival fibroblasts are the most abundant cells in periodontal tissues and participate actively in the host inflammatory response to periodontopathogens, which is known to mediate local tissue destruction in periodontitis. The aim of this study was to investigate the effect of a proanthocyanidin-enriched cranberry fraction, prepared from cranberry juice concentrate, on inflammatory mediator production by gingival fibroblasts stimulated by the lipopolysaccharide (LPS) of Aggregatibacter actinomycetemcomitans. Interleukin (IL)-6, IL-8, and prostaglandin E(2) (PGE(2)) production by fibroblasts treated with the cranberry fraction and stimulated by A. actinomycetemcomitans LPS was evaluated by enzyme-linked immunosorbent assay. Changes induced by A. actinomycetemcomitans LPS and the cranberry fraction in the expression and phosphorylation state of fibroblast intracellular signaling proteins were characterized by antibody microarrays. The LPS-induced IL-6, IL-8, and PGE(2) responses of gingival fibroblasts were inhibited by treatment with the cranberry fraction. This fraction was found to inhibit fibroblast intracellular signaling proteins, a phenomenon that may lead to a down-regulation of activating protein-1 activity. Cranberry components also reduced cyclooxygenase 2 expression. This study suggests that cranberry juice contains molecules with interesting properties for the development of new host-modulating therapeutic strategies in the adjunctive treatment of periodontitis.
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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 | 0.004 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".