Terpenoids isolated from Tunisian <i>Nigella sativa</i> L. essential oil with antioxidant activity and the ability to inhibit nitric oxide production
Bibliographic record
Abstract
ABSTRACT Fractionation of the essential oil from the seeds of Nigella sativa (Ranunculaceae) led to the isolation of four terpenoids: trans‐ (1), cis‐sabinene hydrate methyl ether (2), 1,2‐epoxy‐menth‐4‐ene (3) and 1,2‐epoxy‐menth‐4(8)‐ene (4). Structure elucidation was performed using NMR (1D and 2D NMR) experiments and mass spectral data. Compounds 3 and 4 are reported for the first time as natural products. Bioactivities of the compounds were assessed. The four compounds exhibit antioxidant activity in vitro, as assessed by the oxygen radical absorbance capacity test. Moreover, compounds 1, 2 and 4 displayed strong ability to inhibit oxidative stress in human skin WS‐1 fibroblasts cells, with IC50 values of 0.32, 0.005 and 0.43 µ m, respectively. In addition, the four tested compounds significantly inhibited nitric oxide release by lipopolysaccharide‐activated RAW 264.7 macrophages. The results show that the most effective compound was cis‐sabinene hydrate methyl ether (2). In addition, the cis‐configurated compound (2) exerted stronger activities in comparison with the trans‐configurated compound (1), suggesting geometric stereoselectivity for the biological activities. Copyright © 2011 John Wiley & Sons, Ltd.
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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) | 0.001 | 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) | 0.002 | 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".