Primary and Re-exposure effects of D-enantiomeric peptide on metabolism, diversity, and composition of oral biofilms at different stages of recovery
Bibliographic record
Abstract
The persistence of bacteria in the root canal system is the primary cause of recurrent apical periodontitis. The adaptability of residual bacteria to changing environmental conditions is a key survival strategy of biofilms, often leading to endodontic treatment failure. DJK-5 is a protease-resistant, broad-spectrum D-enantiomeric peptide that degrades or prevents the accumulation of guanosine penta- and tetraphosphates, which are important for biofilm formation. We evaluated the effects of primary antimicrobial agents and nutrient conditions on the recovery, metabolism, diversity, and composition of oral biofilms, and investigated how these factors affect the efficacy of DJK-5 and chlorhexidine (CHX) during re-exposure. Primary irrigants and nutrient conditions significantly influenced biofilm recovery, metabolic activity, diversity, and composition. Biofilm recovery was slower in nutrient-poor groups compared to nutrient-rich ones, and nutrient availability had the greatest effect on shaping both the diversity and composition of the biofilms. Water and DJK-5 groups showed similar biofilm diversity trends, while CHX generally led to lower diversity. Results indicate that primary irrigants and nutrient conditions significantly impact biofilm composition, diversity, and recovery. However, these changes did not compromise DJK-5's effectiveness in killing of biofilm microbes during re-exposure of recovered biofilms.
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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".