A Pilot Study on Antimalarial Effects of Moringa oleifera Leaf Extract in Plasmodium berghei Infection in Mice
Bibliographic record
Abstract
The emergence and spread of antimalarial drug resistance of Plasmodium parasites, as well as hypoglycemia, during malaria infection, and subsequent death, are critical problems in malaria-endemic areas. Hence, finding new compounds, especially plant extracts having antimalarial and anti-hypoglycemic activities, are urgently needed. The present study aimed to investigate the antimalarial and anti-hypoglycemic effects of Moringa oleifera leaf extract in Plasmodium berghei infection in mice. Aqueous crude extract of M. oleifera leaves was freshly prepared and used for an efficacy test in vivo. Groups of ICR mice (5 mice in each) were infected with 1´107 infected red blood cells of P. berghei ANKA by intraperitoneal injection and given the extract orally with doses of 100, 500, and 1000 mg/kg for 4 consecutive days. Parasitemia and plasma glucose levels were subsequently measured. The results showed that M. oleifera leaf extract presented significant (p < 0.001) inhibition of parasitemia in a dose-dependent manner. Moreover, this extract exerted anti-hypoglycemia effects in infected mice in a dose-dependent manner. The highest degrees of activity were found at a dose of 1000 mg/kg of the extract. Additionally, no effect on plasma glucose was found in normal mice treated with this extract. It can be concluded that aqueous crude extract of M. oleifera leaves exerted antimalarial and anti-hypoglycemic effects in P. berghei infection in mice.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".