Optimizing dose of aqueous extract of Mangifera indica L stem bark for treating anaemia and its effect on some disaccharidases activity in iron deficient weanling rats
Bibliographic record
Abstract
Iron deficiency, the main cause of anaemia, has been linked with decreased disaccharidases activity. The highest prevalence of iron deficiency is recorded in Africa where plants, including Mangifera indica , with ethnobotanical claims of being used for the treatment of iron deficiency anaemia are ‘housed’. Although some scientific findings have been reported on the anti-anaemic potential of M. indica , none is yet to give a clearer picture of this ethnobotanical claim. This work investigates the effects of aqueous extract of M. indica stem bark on iron deficiency anaemia and disaccharidases' activities in iron deficient rat. The aqueous extract formulated into three doses, 25, 50 and 75 mg/kg body weight were administered to weanling albino rats induced with iron deficiency through diet. After four weeks of feeding the rats, the Packed Cell Volume, Haemoglobin concentration and Red Blood Cell count of the iron deficient rats were significantly reduced (P < 0.05) compared to those of healthy rats fed with iron sufficient feed. These iron status indicators were significantly increased (P < 0.05) in rats treated with the extract when compared with untreated rats. The extract also revert decreased sucrase and lactase activity in treated iron deficient rats when compared with untreated rats. The efficacy of the extract may be due to its components including iron, saponin and cardiac glycosides. This work proposed 25 mg/kg body weight as the likely non-lethal effective dose of the extract for the treatment of anaemia, though, further toxicological studies are still required to ascertain this claim.
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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 | 0.001 |
| 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".