Lactobacillus plantarum lipoteichoic acid disrupts mature Enterococcus faecalis biofilm
Bibliographic record
Abstract
Apical periodontitis is caused by biofilm-mediated root canal infection. Early phase oral bacterial biofilms are inhibited by Lactobacillus plantarum lipoteichoic acid (Lp.LTA). However, mature biofilms that develop over 3 weeks are more resistant to traditional endodontic medicaments. Therefore, this study examined the effectiveness of Lp.LTA on disrupting mature Enterococcus faecalis biofilms, and on enhancing the effects of endodontic medicaments. LTA was purified from L. plantarum through butanol extraction followed by hydrophobic and ion-exchange chromatography. E. faecalis biofilms were formed over 3 weeks on glass bottom dishes and in dentin blocks obtained from human single-rooted premolars. These mature biofilms were treated with or without Lp.LTA for 1 h, followed by additional treatment with either chlorhexidine digluconate (CHX), calcium hydroxide (CH), or triple antibiotics for 24 h. Biofilms on glass were live/dead stained and quantified by ZEN through confocal laser microscopy. Bio-films in dentin were fixed, sputter coated and analyzed by ImageJ with scanning electron microscopy. Preformed E. faecalis mature biofilms on the culture dishes were dose-dependently disrupted by Lp.LTA. Lp.LTA potentiated the effects of CHX or CH on the disruption of mature biofilm. Interestingly, CHX-induced disruption of preformed E. faecalis mature biofilms was synergistically enhanced only when pre-treated with Lp.LTA. Furthermore, in the dentin block model, Lp.LTA alone reduced E. faecalis mature biofilm and pre-treatment with Lp.LTA promoted the anti-biofilm activity of CHX. Lp.LTA could be an anti-biofilm or supplementary agent that can be effective for E. faecalis-biofilm-induced diseases.
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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) | 0.001 | 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) | 0.000 | 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 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".