Antimicrobial efficacy of <scp>DJK</scp>‐5 peptide in combination with <scp>EDTA</scp> against biofilms in dentinal tubules: Primary irrigation, recovery and re‐irrigation
Bibliographic record
Abstract
AIM: To investigate the dynamic recovery of biofilms within dentinal tubules after primary irrigation with different protocols, and to evaluate the efficacy of various re-irrigation protocols on recovered biofilm, considering factors such as smear layer, nutrient conditions, and primary irrigants. METHODOLOGY: A total of 416 mono or multi-species biofilms samples were prepared from human teeth and incubated for 3 weeks. After inducing a smear layer on half of the samples, all specimens were irrigated with one of the following irrigant sequences: (1) 6% NaOCl +17% EDTA, (2) 6% NaOCl +8.5% EDTA, (3) 6% NaOCl and (8.5% EDTA +10 μg/mL DJK-5 antimicrobial peptide), or (4) sterile water. Thirty-two samples were used to assess immediate effect, whilst the rest were re-incubated to assess biofilms recovery. Nutrient conditions were defined based on whether culture media were changed (nutrient-rich) or not (nutrient-poor) during re-incubation. After 16 weeks, recovered biofilms underwent re-irrigation using four additional protocols, with or without DJK-5 peptide, based on primary irrigants. Confocal laser scanning microscopy was employed to evaluate immediate irrigant effects, biofilms recovery intervals (1, 3, 5, 8, 12, and 16 weeks after primary irrigation), and re-irrigation effects at the 16-week. Statistical analysis included one-way anova and two-way mixed anova tests. RESULTS: The DJK-5 peptide irrigation protocols demonstrated the highest killing rates during primary irrigation and resulted in a longer biofilms recovery time of 16 weeks compared to non-peptide protocols (p < .001). Both primary irrigation type and smear layer presence significantly influenced biofilms recovery (p < .001). In the absence of smear layer, re-irrigation efficacy didn't significantly differ from primary irrigation, regardless of primary irrigation type or nutrient conditions. However, with a smear layer present, re-irrigation led to significantly higher proportion of dead bacteria compared to primary irrigation (p < .05). Inclusion of the DJK-5 peptide into the re-irrigation protocol displayed superior killing rate compared to other protocols (p < .001). CONCLUSIONS: Biofilms exhibited susceptibility to both peptide and non-peptide protocols during re-irrigation, irrespective of nutrient conditions or primary irrigation protocols. The DJK-5 peptide irrigation protocols consistently displayed superior effectiveness compared to non-peptide protocols.
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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".