Evaluation of the Chemical Composition, the Antioxidant and Antimicrobial Activities of<i>Mentha × piperita</i>Essential Oil against Microbial Growth and Biofilm Formation
Bibliographic record
Abstract
This study aimed to investigate the antioxidant activity of Mentha x piperita L. essential oil (EO), and its antimicrobial effects on different microbial (bacteria and yeast) species. Mentha piperita L. was collected from the Chiffa an Algerian locality. The extraction of the essential oil was carried out on the fresh aerial part of the plant. The Extracted EO was subjected to gas chromatography (GC) evaluating the different chemical constituent. To assess the antioxidant activity of the EO, we measured the Diphenyl-1-picrylhydrazyl. To evaluate the antimicrobial activity of the EO, we use various clinical and reference microorganisms. Our results showed that the EO contained several chemicals that include 32.93 % menthol, 24.41 % menthone, 8.08 % cis-caran, and 7.89 % eucalyptol (1,8-cineole). The extracted EO does have significant antioxidant activity that increases with the high concentrations of the EO. We also showed that the EO has antimicrobial activity reducing the growth and biofilm formation of bacteria and yeast (Candida albicans). The percentage of growth reduction was ranged from 40 % to almost 100 %, depending on the tested microbes. Altogether, our data suggest the potential antimicrobial activity of M. Piperita EO that may be of good use to control infections with mammalians and environment.
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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 | 0.000 |
| 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".