The Aqueous Extract of Cocos nucifera L. (Arecaceae) Effectively Treat Induced Anemia. Experimental Study on Wistar Rats
Bibliographic record
Abstract
Anaemia is a serious public health problem especially in developing countries as Benin. Cocos nucifera is one of medicinal plants used in Benin to treat anemia. This study aimed to test its therapeutic efficacy in anemia treatment. Method: Five groups of five Wistar rats each were formed. The rats of four groups were rendered anemic by injection of phenylhydrazine (hemolysis) in the first two days D0 and D1. From the second to the fifteenth day (D2 to D15), anemic groups were gavaged either by the aqueous extract of Cocos nucifera at 200 or 300 mg / kg body weight/day, or by vitafer, a reference drug against anemia. The last anemic group was not treated. The group of non-anemic rats served as a control. Blood samples were collected for all rats on days D0, D2, D7, D10 and D15 to assess blood count and osmotic resistance of red blood cells. Results: The phytochemical analysis revealed the presence of tannins, flavonoids, leucoanthocyanes, steroids, quinone derivatives, reducing compounds and mucilage. The extract like the vitafer corrected completely anemia before two weeks by stimulating hemoglobin synthesis, production and early release of immature red cells in the blood stream. Its effect was dose dependent, quite specific and did not affect platelet lineage. Conclusion: Cocos nucifera has a good therapeutic efficacy and may be considered for transformation into improved traditional medicines (ITM) after study of its biological tolerance and appropriate clinical trials.
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 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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".