<i>In vitro</i>antiplasmodial activity and toxicity assessment of some plants from Nigerian ethnomedicine
Bibliographic record
Abstract
CONTEXT: The emergence and spread of Plasmodium falciparum-resistant parasites to nearly all available antimalarial drugs pose a threat to malaria control and necessitates the need to continue the search for new effective and affordable drugs. Ethnomedicine has been shown to be a potential source of antimalarial compounds or source of template for the synthesis of novel antimalarial molecules. OBJECTIVE: The antiplasmodial activity and toxicity assessment of 30 plant extracts from eight medicinal plants identified in Nigerian ethnomedicine for the treatment of febrile illnesses were evaluated. MATERIALS AND METHODS: In vitro antimalarial activity was evaluated using Plasmodium falciparum NF54 (sensitive to all antimalarial drugs) and K1 (chloroquine/pyrimethamine resistant) strains in the [(3)H]-hypoxanthine incorporation assay. Toxicity was determined against mammalian L6 cells using Alamar blue assay. RESULTS: The ethyl acetate extract of leaves of Ocimum gratissimum Linn. (Labiatae) and hexane extract of stem bark of Trema orientalis (L.) Blume (Ulmaceae) showed the highest antiplasmodial activity (IC(50) 1.8-1.93 µg/mL) against P. falciparum K1 strain but elicited low cytotoxicity (selective index >10). However, hexane, ethyl acetate or methanol extracts of leaves of Terminalia catappa Linn. (Combretaceae), Jatropha curcas Linn. (Euphorbiaceae), Vitex doniana Sweet. (Verbenaceae) and stem bark of Vitex doniana displayed antiplasmodial activity (IC(50) 2.3-16.9 µg/mL) with good selectivity (21-120) for malaria parasites. DISCUSSION AND CONCLUSION: The antiplasmodial activity of Terminalia catappa and Vitex doniana against P. falciparum K1 is being reported for the first time in Nigerian ethnomedicine and these plants could be potential source of antimalarial agents.
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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 | 0.000 | 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".