Anti-Inflammatory, Antioxidant, Antibiotic, and Cytotoxic Activities of Tanacetum vulgare L. Essential Oil and Its Constituents
Bibliographic record
Abstract
Background: Tanacetum vulgare L. (Asteraceae) is a perennial herb that has been used to treat multiple ailments. Regional variability of the chemical composition of T. vulgare essential oils is well-known. Despite these regional chemotypes, most relevant studies did not analyze the complete chemical composition of the T. vulgare essential oil and its constituents in relation to their biological activities. Here, we assess the anti-inflammatory, antioxidant, antibacterial, and cytotoxic activities of T. vulgare collected from northern Quebec (Saguenay-Lac-St-Jean), Canada. Methods: Essential oil was extracted from plants by steam distillation and analyzed using GC-FID. Biological activities of essential oil and its main constituents were evaluated in vitro. Results: We identified the major compounds as camphor, borneol, and 1,8-cineole. The oil possesses anti-inflammatory activity inhibiting NO production. It also inhibits intracellular DCFH oxidation induced by tert-butylhydroperoxide. Anti-inflammatory activity of essential oil appears driven mainly by α-humulene while antioxidant activity is provided by α-pinene and caryophyllene oxide. Essential oil from T vulgare was active against both Escherichia coli and Staphylococcus aureus with camphor and caryophyllene oxide responsible for antibacterial activity. Finally, T. vulgare essential oil was slightly cytotoxic against the human healthy cell line WS1 while α-humulene and caryophyllene oxide were moderately cytotoxic against A-549, DLD-1, and WS1. Conclusion: We report, for the first time, links between the specific compounds found in T. vulgare essential oil and anti-inflammatory, antioxidant, antibacterial, and cytotoxic activities. T. vulgare essential oil possesses interesting biological properties.
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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 | 0.001 | 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".