Biological activities and volatile constituents of Daucus muricatus L. from Algeria
Bibliographic record
Abstract
BACKGROUND: In order to find new bioactive natural products, the antimicrobial and antioxidant activities of essential oil components extracted from the separated organs of the Algerian medicinal and aromatic plant Daucus muricatus L. were studied. RESULTS: The chemical composition of essential oils obtained by hydrodistillation (HD) was investigated using Gas Chromatography-Retention Indices (GC-RI) and GC-Mass Spectrometry (GC-MS). Two types of essential oils were produced by D. muricatus: (i) The oil from roots is mainly composed by nonterpenic oxygenated compounds (59.8 g/100 g), and (ii) the aerial part oils (i.e., the leaves, stems, flowers, and umbels) was mainly composed by terpenic hydrocarbon compounds (62.3-72.2 g/100 g). The chemical composition of the volatile fraction isolated from different organs of Daucus muricatus were studied by HS-SPME/GC-RI and GC-MS after optimization of Solid Phase MicroExtraction parameters. For all organs studied, the main volatiles emitted by the plant were hydrocarbon compounds (60.7-82.2 g/100 g). Only quantitative differences between the volatiles of the separated organs studied were observed. In addition, the activity of the oil of D. muricatus against eight bacterial strains and one yeast was investigated. The oil from roots revealed active against S. aureus, while the essential oil obtained from the aerial parts was active against the yeast C. albicans. CONCLUSIONS: Daucus muricatus essential oil seems be a promising source of natural products with potential antimicrobial activity.
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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".