Phenolic Composition, Antioxidant Capacity and Antibacterial Activity of White Wormwood (Artemisia herba-alba)
Bibliographic record
Abstract
Artemisia herba-alba Asso. (Wormwood) is a wild aromatic herb that is popular for its healing and medicinal effects and has been used in conventional as well as modern medicine. This research aimed at the extraction, identification, and quantification of phenolic compounds in the aerial parts of wormwood using Soxhlet extraction, as well as characterizing their antimicrobial and anitoxidant effects. The phenolic compounds were identified in different extracts by column chromatography, thin layer chromatography (TLC), and high performance liquid chromatography. Five different fractions, two from ethyl acetate extraction and three from ethanolic extraction were obtained and evaluated further. The antimicrobial activity of each fractions was evaluated against two Gram-positive (Bacillus cereus and Staphylococcus aureus) and two Gram-negative microorganisms (Escherichia coli and Proteus vulgaris) using the disc-diffusion assay and direct TLC bioautography assay. Fraction I inhibited B. cereus and P. vulgaris, Fraction II inhibited B. cereus and E. coli, Fraction III inhibited all, except for P. vulgaris, while Fractions IV and V did not exhibit strong antimicrobial effects. Their antioxidant capabilities were also measured by calculating their ability to scavenge the free radical using DPPH method and the ferric reducing antioxidant power (FRAP) assay. Ethanolic fractions III and V demonstrated excellent antioxidant properties with IC50 values less than 15.0 μg/mL, while other fractions also had IC50 values less than 80.0 μg/mL. These antioxidant effects were highly associated with the number of phenolic hydroxyl group on the phenolics they contained. These extracts demonstrated antimicrobial effects, suggesting the different phenolic compounds in these extracts had specific inhibitory effects on the growth of each bacteria. The results of this study suggested that the A. herba-alba can be a source of phenolic compounds with natural antimicrobial and antioxidant properties which can be used for potential pharmaceutical applications.
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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 | 0.001 |
| 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".