Investigation of antiemetic, antimicrobial and anti-radical properties of methanolic extract of Foeniculum vulgare: A medicinal herb
Bibliographic record
Abstract
Objectives: This study was conducted to investigate the antiemetic, antimicrobial and anti-radical activity of methanolic extracts of Foeniculum vulgare. Materials and Methods: The antiemetic assay was carried out by using chick emetic model with minor modifications by calculating the mean decrease in the number of retching. The antimicrobial activity of the crude extract was performed by Disc Diffusion method. The anti-radical activity was determined by the 2, 2-diphenyl-2-picrylhydrazyl hydrate (DPPH) method.Results: The anti-emetic activity of Foeniculum vulgare leaves on young chicks revealed that these extracts have a less anti-emetic effect. The group of chicks treated with Chlorpromazine was found to have 60.6 retches as compared to the 66 retches of the control group, thus Chlorpromazine reduced the retches by 7.93%. The chickens treated with leaves extracts inhibited the retches up to 2.03%. The minimum antimicrobial effect was found in this methanol crude extract. The extract did not appear potent in terms of both zones of inhibition and spectrum of activity. In anti-radical activity test, the extract showed moderate free radical scavenging activity with IC50 value 240.39μg/ml. while compared to that of the reference standard ascorbic acid.Conclusion: Methanolic extract of Foeniculum vulgare leaves have minimum anti-emetic and anti-microbial activities and moderate anti-radical 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 | 0.001 | 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".