Chemical Composition, Antimicrobial and Antioxidant Properties of the Volatile Oil and Methanol Extract of <i>Xenophyllum Poposum</i>
Bibliographic record
Abstract
The essential oil and methanol extract of northwestern Argentina medicinal plant Xenophyllum poposum, collected in Catamarca province, were investigated. GC and GC-MS analyses of the essential oil identified 56 compounds accounting for 92.9%. The main components of the oil were delta-cadinene (16.5%), 6-hydroxytremetone (14.7%), epi-alpha-cadinol (12.0%), alpha-cadinol (8.8%), gamma-cadinene (7.5%), 1-epi-cubenol (4.2%) and alpha-muurolene (3.0%). The essential oil exhibited antibacterial activities against five pathogenic strains as well as antifungal activities against two pathogenic fungi. The methanol extract showed antibacterial activity against two strains of Staphylococcus aureus and two pathogenic fungal strains. The main components isolated from the methanol extract were the antifungal 4-hydroxy-3-(isopenten-2-yl)-acetophenone, 6-hydroxytremetone, and tremetone. 6-Hydroxytremetone showed activity against all the fungal strains and one of the S. aureus strains assayed. Antioxidant and radical-scavenging properties of the methanol extract and essential oil were determined using the 2,2'-diphenyl-1-picrylhydrazyl assay and beta-carotene bleaching (BCB) test. The methanol extract and the essential oil showed, respectively, moderate and weak antioxidant activity when compared to butylated hydroxytoluene.
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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".