Evaluation of bio-compatibility and effectiveness of propolis Tetragonula sp. as dental anti-microbial agent
Bibliographic record
Abstract
Introduction: Bacterial invasion is an important concern in dental therapy procedures.Oral bacteria, such as Enterococcus faecalis (E.faecalis) and Streptococcus mutans (S. mutans) could be more virulent in dysbiosis condition.Utilization of anti-microbial agent, e.g., chlorhexidine digluconate (CHX), is commonly applied for bacterial control in dental practice, since it harbors significant bacterial eradication.However, bio-compatibility concerns arise along with chemical anti-microbial agent towards surrounding tissues.Propolis, with its' various bio-active compounds is reported to inhibit bacterial growth without artificial chemical substance, and making it as a promising alternative anti-microbial agent.Objectives: This study aimed to evaluate anti-bacterial capacity of the propolis compound and its' cyto-toxic effects against human fibroblast.Material and methods: 0.1% and 1% of both ethanolic-(EEP) and water-based (WEP) compounds of local propolis were prepared prior to experimental procedures.Both E. faecalis ATCC 29212 and S. mutans ATCC 25175 were measured at 625 nm for McFarland's initial adjustment, and turbidity at 600 nm for growth evaluation and antibacterial activity.Cyto-toxic effects of both extracts towards fibroblast cells were evaluated through cells viability test using MTS method.Shapiro-Wilk test was performed followed by ANOVA, t-test, or Mann-Whitney U-test.Results: It showed that the EEP tended to be more toxic than the WEP against human fibroblast cells in higher concentrations.Both 1% of WEP and EEP showed significant bacterial inhibitory activities against E. faecalis and S. mutans.Conclusions: These findings suggest the enhanced possibility of propolis-based compound as a promising dental anti-microbial agent.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".