Combination of neovestitol and vestitol impair the subgingival multispecies biofilm development
Bibliographic record
Abstract
The aim of this study was to evaluate effects of neovestitol-vestitol fraction (NVF) on an in vitro subgingival multispecies biofilm. The 33-species biofilm was formed for seven days using a Calgary device. Starting on day 3, treatments for applied twice daily for 1 min each: NV (400–1,600 µg ml–1), chlorhexidine 0.12% (CHX; positive control) or vehicle (negative control). After seven days, metabolic activity and microbial composition were accessed through colorimetric reaction and DNA–DNA hybridization, respectively. ANOVA/Tukey’s and Kruskal–Wallis/Dunn’s were performed (p < 0.05). NV1,600 and NV800 and CHX significantly reduced biofilm metabolic activity by 67%, 48% and 64% respectively, compared to vehicle-treatment. NV1,600, NV800 and CHX reduced red complex proportions versus vehicle-treatment. NV1,600 also reduced orange complex and increased healthy-associated purple complex compared to negative control (p < 0.05). NV1,600, NV800 and CHX reduced nine species, including Fusobacterium periodonticum and Porphyromonas gingivalis. NV1,600 also reduced Fusobacterium nucleatum polymorphum. NV seems to be a good candidate to control biofilm formation and pathogenicity in dental practice.
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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".