Antibacterial Effects of Chewing Stick Extracts on Streptococcus Mutans
Bibliographic record
Abstract
Background: Streptococcus mutans is considered as a major microorganism causing tooth decay, affecting individuals globally. Different types of chewing sticks possess anti cariogenic properties, traditionally been consumed in maintaining dental hygiene. Usage of these sticks can be economical in developing and rural regions where dental caries is a major health concern. Objective: The current study aims to evaluate antibacterial action of different type of chewing sticks extract on Streptococcus mutans. Methods: Aqueous extracts of Azadiracta indica (Neem), Melia azedarach (Bakain), Mangifera indica (Mango), Salvadora persica (Peelu), Terminalia chebula (Harhar), Dalbeigia sissoo (Tali) and Juglans regia (Akhrot) plants which have justified folk use were prepared in Punjab University College of Pharmacy, Punjab University. Next, in vitro antimicrobial activity was studied by broth dilution method in Post Graduate Medical Institute, Lahore. Moreover, minimum inhibitory concentration (MIC) as well as the minimum bactericidal concentration (MBC) were quantitatively evaluated on basis of turbidity index. Results: There is a significant effect of aqueous extracts of plants on the bacterial inhibition. MIC and MBC values were in the range of 6.125 to 100 mg/mL against S. mutans. The notable effect occurred with aqueous extracts of Azadiracta indica showing MIC and MBC values as 6.25mg/mL and 12.5 mg/mL, respectively. Alternatively, Salvadora persica demonstrated 8.33mg/mL and 16.66 mg/mL values of these parameters Conclusions: Each plant studied exhibited moderate to high antibacterial activity against tested bacterial strain. However, Azadirachta indica and Salvadora persica aqueous extracts showed promising effect against Streptococcus mutans
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".