Inhibitory effect of sodium fluoride and chlorhexidine on the growth of oral lactobacilli
Bibliographic record
Abstract
The accumulation of microorganisms in dental plaque is related to the etiology of caries and periodontal disease, with a high prevalence worldwide. The prophylactic measures include the use of chemical agents as NaF and chlorhexidine. Lactic acid bacteria are members of the normal microbiota of the oral cavity being discussed with regard to their beneficial or detrimental effect in this environment. The present study was performed to determine the growth of some species of Lactobacillus at different concentrations of NaF and chlorhexidine. The strains were isolated from both caries-free and caries patients. Their growth parameters were evaluated by the application of the Gompertz model to the experimental data of optical density as a measurement of growth. The degree of inhibition of the growth of all of the lactobacilli studied was different, depending on each particular strain. NaF at 1 mmol x L(-1) inhibited between 5% and 46%, at 5 mmol x L(-1) between 13% and 65%, and at 20 mmol x L(-1) between 57% and 84%. CHX at higher concentrations (197 and 98 mmol x L(-1) showed a complete inhibition of some of the strains. The significance of the results was evaluated by the application of a multivariate analysis and also compared with the inhibition of pathogenic Streptococcus mutans and with lactobacilli strains from collection cultures.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".