Antimicrobial Activity of Plants Collected from Serpentine Outcrops in Sri Lanka
Bibliographic record
Abstract
Thirty-two plant species collected from serpentine (ultramafic) soils in Sri Lanka were screened for antimicrobial properties against three Gram-positive and two Gramnegative bacteria, a non-acid fast bacterium, and the yeast, Candida albicans. Methanol extracts of 29 species belonging to 12 families were active against at least one microorganism. Activity against the Gram-positive and non-acid fast bacteria was common, however, only two taxa, Lantana camara L. (Verbenaceae) and a species of Phyllanthus L. (Euphorbiaceae), were active against the Gram-negative bacterium Pseudomonas aeruginosa. None of the species was active against the other Gram-negative bacterium, Escherichia coli, or C. albicans. Photoactivity was observed from extracts of 10 species belonging to 10 families, including Convolvulaceae, Lamiaceae, and Rhamnaceae where photoactivity has not been previously reported. Interestingly, Leucas zeylanica (L.) R. Br. (Lamiaceae), one of only three species collected from more than one site, showed population-level variation in photoactivity. This is the first study where plants from highly stressful serpentine environments have been tested for antimicrobial activity. Our findings suggest that plants from serpentine environments may have altered antimicrobial activities when compared to their relatives from non-serpentine environments, urging the need to pay attention to substrate, habitat, etc., when collecting plants to test for antimicrobial 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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".