Anti -Anaemic Potentials of Tigernut Extract Administered on Rat Exposed to Phenylhydrazine Induced Toxicity
Bibliographic record
Abstract
Anaemia is a public health problem that affect both the rich and poor, and it possess a serious challenge to the health care profession, consequently this research is therefore aim at investigating the anti - anaemic potentials of Tigernut (C. esculentus) extract administered to albino wistar rats exposed to Phenylhydrazine induced toxicity. Forty (40) male albino Wistar rats weighing between 180- 250g were used for this study. They were randomly divided into four (4) groups of ten (10) rats each. Control group received normal feed and drinking water. Extract group received 600mg/kg bw of aqueous extract of Tigernut orally, PHZ group received PHZ induction and PHZ + Extract group received PHZ induction + 600mg/kg bw of aqueous extract of Tigernut. The feeding regimens lasted for 4 weeks, after which blood samples were collected via cardiac puncture for estimation of different parameters. Results showed that ingestion of aqueous extract of C. esculentus was able to reverse the significant decrease in RBC (p<0.01), HB (p<0.001), PCV (p<0.001) and Fe+ (p<0.01) values occasion by PHZ induction, back to appreciable level. In conclusion ingestion of C. esculentus extract is capable of reversing the derogatory effect imposed on hemopoietic processes following PHZ induction. Since C. esculentus is cheap and readily available it can therefore be recommended for the management of anaemic condition pending the availability of a viable health facility.
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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".