Cranberry proanthocyanidins inhibit the adherence properties of Candida albicans and cytokine secretion by oral epithelial cells
Bibliographic record
Abstract
BACKGROUND: Oral candidiasis is a common fungal disease mainly caused by Candida albicans. The aim of this study was to investigate the effects of A-type cranberry proanthocyanidins (AC-PACs) on pathogenic properties of C. albicans as well as on the inflammatory response of oral epithelial cells induced by this oral pathogen. METHODS: Microplate dilution assays were performed to determine the effect of AC-PACs on C. albicans growth as well as biofilm formation stained with crystal violet. Adhesion of FITC-labeled C. albicans to oral epithelial cells and to acrylic resin disks was monitored by fluorometry. The effects of AC-PACs on C. albicans-induced cytokine secretion, nuclear factor-kappa B (NF-κB) p65 activation and kinase phosphorylation in oral epithelial cells were determined by immunological assays. RESULTS: Although AC-PACs did not affect growth of C. albicans, it prevented biofilm formation and reduced adherence of C. albicans to oral epithelial cells and saliva-coated acrylic resin discs. In addition, AC-PACs significantly decreased the secretion of IL-8 and IL-6 by oral epithelial cells stimulated with C. albicans. This anti-inflammatory effect was associated with reduced activation of NF-κB p65 and phosphorylation of specific signal intracellular kinases. CONCLUSION: AC-PACs by affecting the adherence properties of C. albicans and attenuating the inflammatory response induced by this pathogen represent potential novel therapeutic agents for the prevention/treatment of oral candidiasis.
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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".