Comparative anthelmintic efficacy of Arundo donax, Areca catechu, and Ferula assa-foetida against Haemonchus contortus
Bibliographic record
Abstract
In the present study, anthelmintic activities of Arundo (A.) donax L., Areca (Ar.) catechu L., and Ferula (F.) assa-foetida L. were determined. Leaves of A. donax L., latex of F. assa-foetida L. and seeds of Ar. catechu L. in different solvent fractions were subjected to in vitro (egg hatch assay; EHA, and adult motility assay; AMA) and in vivo (faecal egg count reduction test; FECRT) tests of anthelmintic activity using Haemonchus contortus model. In the AMA, crude aqueous methanol extracts (CAME) and ethyl acetate fractions of F. assa-foetida at 10 hr post-treatment showed maximum mortality of H. contortus at 12.5-50 mg mL-1. In the EHA, CAME of F. assa-foetida was identified as a potent ovicide based on its low LC50 (16.9 µg mL-1), followed in order by Ar. catechu and A. donax. Results from the FECRT also showed the extract of F. assa-foetida L. to be more effective than those of Ar. catechu L. and A. donax L., against the gastrointestinal parasitic nematodes. Chloroform and ethyl acetate fractions showed better anthelmintic activities against the adult worms in vitro, while CAME of these plants were better than their crude powders in vivo. It is recommended to document and investigate indigenous knowledge of possible medicinal plants to plan scientific trials that may justify their endorsement.
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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".