Effects of Anogeissus leiocarpus on Haematological Parameters of Mice Infected with Plasmodium berghei
Bibliographic record
Abstract
Haematological parameters are frequently used to support the diagnosis of several diseases including malaria. Anogeissus leiocapus is used traditionally to treat malaria and has been shown to possess profound antimalarial activities in Plasmodium berghei infected mice. This study evaluated the effects of the methanolic extracts of A. leiocarpus on the haematological status of P. berghei-infected mice. Twenty albino mice were inoculated intra-peritoneally with P. berghei while 5 others were left uninfected to serve as control, (Group A). Group B, negative control, received distilled water. Group C (positive control) was treated with artesunate at 5 mg/kg body weight while A. leiocarpus extract was orally administered at 100 and 200 mg/kg body weight for 4 days to Groups D and E respectively. On the fifth day of treatment, haematological parameters (red blood cell (RBC), white blood cell (WBC) and platelet counts; packed cell volume (PCV), haemoglobin (Hb) concentration and differential leukocyte count) were assessed using standard methods. A. leiocarpus at 100 mg/kg and 200 mg/kg body weight increased the haemoglobin, RBC and PCV levels of treated P. Berghei infected mice compared to negative control. Lymphocyte levels of these same groups significantly (p<0.05) increased while neutrophil level reduced. Our findings show that A. leiocarpus has anti-anaemic 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 | 0.000 | 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".