Effect of Lippia alba and Cymbopogon citratus essential oils on biofilms of Streptococcus mutans and cytotoxicity in CHO cells
Bibliographic record
Abstract
BACKGROUND: Caries is a public health problem, given that it prevails in 60 to 90% of the school-age global population. Multiple factors interact in its etiology, among them dental plaque is necessary to have lactic acid producing microorganisms like Streptococcus from he Mutans group. Existing prevention and treatment measures are not totally effective and generate adverse effects, which is why it is necessary to search for complementary strategies for their management. AIM: The study sought to evaluate the eradication capacity of Streptococcus mutans biofilms and the toxicity on eukaryotic cells of Lippia alba and Cymbopogon citratus essential oils. METHODOLOGY: Essential oils were extracted from plant material through steam distillation and then its chemical composition was determined. The MBEC-high-throughput (MBEC-HTP) (Innovotech, Edmonton, Alberta, Canada) assay used to determine the eradication concentration of S. mutans ATCC 35668 strain biofilms. Cytotoxicity was evaluated on CHO cells through the MTT cell proliferation assay. RESULTS: The major components in both oils were Geraniol and Citral; in L. alba 18.9% and 15.9%, respectively, and in C. citratus 31.3% and 26.7%. The L. alba essential oils presented eradication activity against S. mutans biofilms of 95.8% in 0.01mg/dL concentration and C. citratus essential oils showed said eradication activity of 95.4% at 0.1, 0.01mg/dL concentrations and of 93.1% in the 0.001mg/dL concentration; none of the concentrations of both essential oils showed toxicity on CHO cells during 24h. CONCLUSION: The L. alba and C. citratus essential oils showed eradication activity against S. mutans biofilms and null cytotoxicity, evidencing the need to conduct further studies that can identify their active components and in order to guide a safe use in treating and preventing dental caries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".