Anti-Leishmanial Activity of Artemisia persica, A. spicigera, and A. fragrance against Leishmania major
Bibliographic record
Abstract
Background: Neglected tropical diseases (NTDs) like zoonotic cutaneous leishmaniasis (ZCL), is a widespread infectious disease with high mortality and morbidity. Various medications are used for treating the disease, but several side effects and drug resistance have been reported. Herbal medicines are unlimited sources for discovering new medications to treat infectious diseases. We aimed to determine the leishmanicidal activity of three species of Iranian Artemisia herbal plant extracts in in-vitro. Methods: In-vitro anti-leishmanial activity of ethanolic extracts on both promastigotes and amastigotes was determined by using MTT method. IC50, CC50, EC50 and SI were calculated. The study was done in 2019-2020 in Iran University of Medical Sciences, Tehran, Iran. Results: All of the three Artemisia species significantly reduced the number of parasite promastigotes. Among them, A. persica had the highest leishmanicidal activity against parasite promastigotes. Cytotoxicity assay elucidated that the Artemisia had no toxicity to the host cells, and killed the L. major amastigotes very efficiently. By increasing the dose of extracts, the parasite number in both phases (promastigotes and amastigotes) was reduced significantly. Conclusion: These results indicated satisfactory anti-leishmanial activity of Artemisia extracts against ZCL in-vitro. Accordingly, Artemisia ethanolic extracts might be considered as a strong, effective and safe herbal compound for clearing the L. major with less toxicity to the host macrophages cells. Hence, it may be recognized as an excellent herbal therapy for treating the ZCL.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".