Cranberry Proanthocyanidins Neutralize the Effects of Aggregatibacter actinomycetemcomitans Leukotoxin
Bibliographic record
Abstract
Aggregatibacter actinomycetemcomitans is a Gram-negative bacterium that has been strongly associated with localized aggressive periodontitis. The capacity of A. actinomycetemcomitans to produce a leukotoxin (LtxA) that activates pyroptosis in macrophages and induces the release of endogenous danger signals is thought to play a key role in the disease process. The aim of the present study was to investigate the effects of cranberry proanthocyanidins (PACs) on gene expression and cytotoxic activities of LtxA. We showed that cranberry PACs dose-dependently attenuate the expression of genes making up the leukotoxin operon, including ltxB and ltxC, in the two strains of A. actinomycetemcomitans tested. Cranberry PACs (≥62.5 µg/mL) protected macrophages against the cytotoxic effect of purified LtxA. Moreover, cranberry PACs reduced caspase-1 activation in LtxA-treated macrophages and consequently decreased the release of both IL-1β and IL-18, which are known as damage-associated molecular patterns (DAMPs) and contribute to the progression of periodontitis by increasing cell migration and osteoclastogenesis. In addition, cranberry PACs reduced the expression of genes encoding the P2X7 receptor and NALP3 (NACHT, LRR and PYD domains-containing protein 3), which play key roles in pore formation and cell death. Lastly, cranberry PACs blocked the binding of LtxA to macrophages and consequently reduced the LtxA-mediated cytotoxicity. In summary, the present study showed that cranberry PACs reduced LtxA gene expression in A. actinomycetemcomitans and neutralized the cytolytic and pro-inflammatory responses of human macrophages treated with LtxA. Given these properties, cranberry PACs may represent promising molecules for prevention and treatment of the aggressive form of periodontitis caused by A. actinomycetemcomitans.
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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".