Tea tree oil in inhibiting oral cariogenic bacterial growth an in vivo study for managing dental caries
Bibliographic record
Abstract
Dental caries is considered a major health burden, and preventive strategies are needed to improve oral health. It is suggested that natural essential oils possess anti-plaque formation properties and exhibit strong antimicrobial activity; however, in vivo studies to support these concepts are scarce. We evaluated the effects of tea tree oil (TTO) on caries initiation and progression in vivo to generate supportive data for clinical studies in patients at high risk of caries. We first assessed TTO in vitro against Streptococcus mutans and Streptococcus sobrinus, two of the most common oral bacteria associated with dental caries development, using bacterial growth assays, biofilm formation, and adhesion assays. TTO efficacy on caries initiation and caries lesion progression was then evaluated in vivo, where complex biofilms are formed on dental enamel. Our results showed that TTO demonstrates strong antimicrobial efficacy by inhibiting bacterial growth and biofilm formation while preventing bacterial adhesion on human teeth. In vivo, TTO application reduced the number and depth of carious lesions. Specifically, the number of caries lesions was lower in the TTO-treated group compared to the control group (13 vs. 19 lesions), and the lesion area was significantly smaller in the TTO-treated group compared to the untreated group (p = 0.003). TTO did not affect the extent of reparative dentin formation. The clinical relevance is primarily for individuals who have difficulties brushing their teeth or those at high risk of developing dental caries, serving as an adjunct to preventive dentistry.
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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 | 0.001 |
| 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 | 0.001 |
| 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".