Synergistic antimicrobial potential of EGCG and fosfomycin against biofilms associated with endodontic infections
Bibliographic record
Abstract
OBJECTIVE: This study aimed to evaluate the cytotoxicity and synergistic effect of epigallocatechin gallate (EGCG) and fosfomycin (FOSFO) on biofilms of oral bacteria associated with endodontic infections. METHODOLOGY: This study determined minimum inhibitory and bactericidal concentration (MIC/MBC) and fractionated inhibitory concentration (FIC) of EGCG and FOSFO against Enterococcus faecalis, Actinomyces israelii, Streptococcus mutans, and Fusobacterium nucleatum. Monospecies and multispecies biofilms with those bacteria formed in polystyrene microplates and in radicular dentin blocks of bovine teeth were treated with the compounds and control chlorhexidine (CHX) and evaluated by bacterial counts and microscopy analysis. Toxicity effect of the compounds was determined on fibroblasts culture by methyl tetrazolium assays. RESULTS: The combination of EGCG + FOSFO demonstrated synergism against all bacterial species, with an FIC index ranging from 0.35 to 0.5. At the MIC/FIC concentrations, EGCG, FOSFO, and EGCG+FOSFO were not toxic to fibroblasts. EGCG+FOSFO significantly reduced monospecies biofilms of E. faecalis and A. israelli, whereas S. mutans and F. nucleatum biofilms were eliminated by all compounds. Scanning electron microscopy of multispecies biofilms treated with EGCG, EGCG+FOSFO, and CHX at 100x MIC showed evident biofilm disorganization and substantial reduction of extracellular matrix. Confocal microscopy observed a significant reduction of multispecies biofilms formed in dentin tubules with 84.85%, 78.49%, and 50.6% of dead cells for EGCG+FOSFO, EGCG, and CHX at 100x MIC, respectively. CONCLUSION: EGCG and fosfomycin showed a synergistic effect against biofilms of oral pathogens related to root canal infections without causing cytotoxicity.
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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".