Hypolipidemic influence of dietary fenugreek (Trigonella foenum-graecum) seeds and garlic (Allium sativum) in experimental myocardial infarction
Bibliographic record
Abstract
The cardioprotective influence of dietary fibre-rich fenugreek seeds and the well-established hypolipidemic spice garlic was evaluated both individually and in combination in isoproterenol induced myocardial infarcted rats. It was particularly examined whether pretreatment with dietary fenugreek, garlic or fenugreek + garlic would be beneficial under hypercholesterolemic conditions by their influence on the tissue lipid profile. Four groups each of male Wistar rats were maintained on either a basal diet or a high cholesterol diet for 8 weeks. Dietary interventions with fenugreek, garlic and the combination of fenugreek and garlic were made by including 10% fenugreek seed powder, 2% freeze-dried garlic powder, and 10% fenugreek seed powder + 2% garlic powder. At the end of the diet regimen, myocardial infarction was induced with isoproterenol (i.p. 80 mg kg(-1)) twice at intervals of 12 h. The disturbed activities of cardiac marker enzymes in serum and the heart confirmed isoproterenol induced myocardial infarction. Dietary fenugreek, garlic or fenugreek + garlic was found to ameliorate the pathological changes in heart tissue and lipid abnormalities in serum and the heart, the beneficial effect being higher with the combination of fenugreek and garlic, invariably amounting to an additive effect. The results also indicated that the hypercholesterolemic situation aggravated the myocardial damage during isoproterenol-induced myocardial infarction. This dietary intervention study suggested that the combination of fenugreek seeds and garlic offers a higher beneficial influence in exerting the cardioprotective effect.
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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 | 0.000 | 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".