Cytoprotective effect of Proanthocyanidin‐rich cranberry fraction against bacterial cell wall‐mediated toxicity in macrophages and epithelial cells
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Recent studies brought evidence regarding the potential beneficial effects of cranberry polyphenols for periodontal infections. In this study, we evaluated the capacity of a proanthocyanidin-rich cranberry fraction to protect macrophages and oral epithelial cells against cytotoxicity induced by bacterial components. U937 cells, differentiated into adherent macrophage-like cells, as well as oral epithelial cells were treated with cell wall or lipopolysaccharide preparations from periodontopathogens. Cell viability was monitored using a commercial MTT (3-[4,5-diethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide) assay. The cytoprotective effect was evaluated by pre-incubating human cells with a proanthocyanidin-rich cranberry fraction prior to treatment with the bacterial components at toxic concentrations. Among the various bacterial components tested, Peptostreptotoccus micros cell wall was found to be the most toxic for macrophages and epithelial cells and was thus selected for further analyses. Treatment of monocyte-derived macrophages with cell wall of P. micros (20 microg/ml) decreased the cell viability by approximately 50%. Adding the cranberry fraction prior to treating cells with P. micros cell wall dose-dependently protected monocyte-derived macrophages from the toxic effect. A dose-dependent cytoprotective effect of the cranberry fraction was also observed with oral epithelial cells treated with P. micros cell wall. This study suggests that cranberry polyphenols may exert a protective effect for host cells against the toxicity induced by bacterial components.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it