Feeding Sprague Dawley Rats With Jordanian Wild Edible Plants and a High Fat Diet Reduced the Malondialdehyde Levels
Bibliographic record
Abstract
The objective of this study was to determine the effect of selected Jordanian wild edible plant on lipid peroxidation and lipid profile in adult male Sprague Dawley rats fed high-fat diet. Fiftysix male, adult Sprague-Dawley rats at eight weeks of age, weighing about 200g were distributed into 7 experimental groups, 7 rats each . The groups included a negative control group that was fed a normal fat diet (NFD) and a possitve control group that was fed a high fat diet (HFD) (45% calories from fat). The six treatment groups were fed a HFD for the first 4 weeks of the experiment and a HFD with 9% of one of the selected dried plants for another 4 weeks. The treatment groups are sumac, thyme, clary, gundelia, garden rocket and wild mint. Blood samples were collected from the right heart ventricle. Serum malondialdehyde, lipid profile and fasting blood glucose were measured for rats. Results showed that the addition of different dried plant powders to the HFD did not significantly affect serum levels of TG, TC, HDL, LDL and fasting blood glucose. On the other hand, malondialdehyde (MDA) levels were significantly (p < 0.05) higher in the HFD group (4.09±0.45 mmol/ml) than those of other groups. MDA serum levels for the other groups were as follows: NFD (2.47±0.05), sumac (2.45±0.13), thyme (2.88±0.07), clary (2.97±0.16), garden rocket (2.96±0.11), gundelia (2.92±0.16) and wild mint (2.68±0.09). These levels were not sinificantly different from each other. It is concluded that incorporating dried plant powders in rat diets had a significantly positive effect only on lipid peroxidation assay as indicated by serum MDA levels.
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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) | 0.000 | 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) | 0.002 | 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".