Antimicrobial, Cytotoxic, and Anti-Inflammatory Activities of<i> Pimenta dioica</i> and<i> Rosmarinus officinalis</i> Essential Oils
Bibliographic record
Abstract
Essential oils (EOs) are natural products composed of a mixture of volatile and aromatic compounds extracted from different parts of plants that have shown antimicrobial activities against pathogens. In this study, EOs extracted from Pimenta dioica (Myrtaceae) and Rosmarinus officinalis (Lamiaceae) were assessed for their antimicrobial activities using a panel of pathogenic Gram-positive, Gram-negative, and fungal strains. The antimicrobial activity was measured by the minimal inhibitory concentration required for the growth inhibition of the microorganisms. The cytotoxicity of the EOs was tested ex vivo using the model of human-derived macrophage THP-1 cells. In addition, an inflammatory response was evaluated using the anti-inflammatory cytokine IL-10 and the proinflammatory cytokines IL-6 and TNF-α. Results showed that both EOs had antimicrobial activity and different pathogens were exposed to concentrations ranging between 600 and 2000 μg/mL. In addition, the EOs showed no inflammatory activity when exposed to human macrophages, but a potent anti-inflammatory activity was measured when the oil from Rosmarinus officinalis was exposed to macrophages. This study demonstrates that the use of EOs is an effective alternative for pathogenic bacterial and fungal control, alone or in combination with antibiotic therapy. Moreover, the oil extracted from Rosmarinus officinalis could be used as potent anti-inflammatory 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 | 0.000 | 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".