The Effects of Zataria Multiflora Hydroalcoholic Extract on Some Liver Enzymes, Cholesterol, Triglyceride, HDL-Cholesterol, LDL-Cholesterol, Albumin and Total Protein in Rat
Bibliographic record
Abstract
Zataria multiflora is a valuable medicinal plant grown extensively in Iran, Pakistan and Afghanistan. The chemical compositions of their extracts have been extensively characterized in Iran and Pakistan. The present study was undertaken to investigate the effects of Zataria multiflora on some liver enzymes, triglyceride, cholesterol, HDL-cholesterol, LDL-cholesterol, albumin and total protein in rat. Sixty adult male Wistar rats weighing about 200 to 220 g were divided into six groups of ten. The control group (group 1) did not receive any drug. The sham group (group 2) received 2 cc of distilled water. The other four experimental groups (groups 3 to 6) including very low (100 mg/kg BW), low (200 mg/kg BW), medium (300 mg/kg BW) and maximum dose (400 mg/kg BW) received Zataria multiflora hydroalcoholic extract intraperitoneally daily for 28 days. After 28 days all animals in the different groups were weighed and blood samples were collected from heart vein. Serum biochemical parameters were measured using validated standard methods. The results of this study showed Zattaria multiflora hydroalcoholic extract analyses various lipids in lipid tissues and transfer to blood for elimination from body.
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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".