The Effects of Medicago Sativa and Allium Porrum on Iron Overload in Rats
Bibliographic record
Abstract
PURPOSE: Iron overload may occur due to regular blood transfusions and high intestinal iron absorption. Currently, there is no effective drug without side effects for the treatment of iron excess in thalassemia and other iron storage diseases, except chelation therapy, which is the only safe method for iron excretion. Thus, scientists are more focused on medicinal plants rich in phytochemical compounds for the removal of iron in thalassemia. Therefore this study was managed to discover the therapeutic potential of hydro-alcoholic extract of Allium porrum and Medicago sativa for iron chelating potential. METHODS: Aerial parts of Allium porrum and Medicago sativa were collected in Yasuj Iran. Rats were divided into seven groups each containing six. Extracts were administrated in four groups (two groups for each extract) by single doses of each plant with 200 and 400 mg/kg body weight by (i.p.) route every other day for 28 days. Group 1 as negative control received saline (0.5 ml/kg) by (i.p.) route. Positive control received iron dextran 200 mg/kg body weight. Experimental groups 1 and 2 for each plant extract were fed with 200 and 400 mg/kg, hydro-alcoholic extract respectively via (i.p.) route, 1 h after the injection of iron dextran. Standard group was treated with deferoxamine (DF) 50 mg/kg by (i.p.) route 1 h after the injection of iron dextran. Serum iron (SI) and serum total iron binding capacity (TIBC) were determined .The serum ferritin was then measured using enzyme immunoassay ELISA kit for rat. For Analysis of data ANOVA test was used. RESULTS: Hydro-alcoholic extract of Medicago sativa and Allium porrum at 400 mg/kg showed significant (p<0.05) iron chelating activity compared to control. The plant extracts with dose 200 mg/kg also reduced the iron and ferritin content but the effect was lower level compared to higher doses. The plant extract effects were similar to that of standard drug deferoxamine. Iron and ferritin levels were significantly reduced in experimental groups when compared to positive group especially in Medicago sativap<0.05. There was no difference between standard drugs and last concentration of plant extracts. CONCLUSION: Protective effect of M. sativa and A. Porrum against iron overload in rat model was reported. Significant decrease in serum ferritin and iron concentration was reported in iron overload rats which induced by iron dextran.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| 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".