Biocompatible combinations of nisin and licorice polyphenols exert synergistic bactericidal effects against Enterococcus faecalis and inhibit NF-κB activation in monocytes
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
Enterococcus faecalis is one of the bacterial species most frequently isolated from persistent endodontic and apical periodontal infections. The aim of the present study was to evaluate the synergistic antibacterial effects of nisin and selected licorice polyphenols (glabridin, licoricidin, licochalcone A) against planktonic and biofilm-embedded E. faecalis cells. The biocompatibility and anti-inflammatory properties of the nisin/licorice polyphenol combinations were also investigated. The lantibiotic bacteriocin (nisin), the two isoflavonoids (glabridin, licoricidin), and the chalcone (licochalcone A) efficiently inhibited the growth of E. faecalis, with MICs ranging from 6.25 to 25 µg/mL. Combining nisin with each licorice polyphenol individually resulted in a significant synergistic antibacterial effect. Following a 30-min contact, nisin in combination with either glabridin, licoricidin, or licochalcone A caused significant biofilm killing. The nisin/licorice polyphenol combinations had no cytotoxic effects (oral epithelial cells, gingival fibroblasts, and stem cells of the apical papilla), with the exception of nisin/glabridin, when used at their MICs. Lastly, we showed that nisin/glabridin, nisin/licoricidin, and nisin/licochalcone A inhibit NF-κB activation induced by E. faecalis in a monocyte model, suggesting that these combinations possess anti-inflammatory properties. The present study provides evidence that combinations of nisin and glabridin, licoricidin, or licochalcone A show promise as root canal disinfection agents.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.001 |
| 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 it