Fenugreek seeds reduce atherogenic diet-induced cholesterol gallstone formation in experimental mice
Bibliographic record
Abstract
Dietary hypocholesterolemic adjuncts may have a beneficial role in the prevention and treatment of cholesterol gallstones (CGS). In this investigation, fenugreek (Trigonella foenum-graecum) seed was evaluated for this potential on the experimental induction of CGS in laboratory mice. CGS was induced by maintaining mice on a lithogenic diet (0.5% cholesterol) for 10 weeks. Fenugreek seed powder was included at 5%, 10%, and 15% of this lithogenic diet. Dietary fenugreek significantly lowered the incidence of CGS in these mice; the incidence was 63%, 40%, and 10% in the 5%, 10%, and 15% fenugreek groups, respectively, compared with 100% in the lithogenic control. The antilithogenic influence of fenugreek is attributable to its hypocholesterolemic effect. Serum cholesterol level was decreased by 26%-31% by dietary fenugreek, while hepatic cholesterol was lowered by 47%-64% in these high cholesterol-fed animals. Biliary cholesterol was 8.73-11.2 mmol/L as a result of dietary fenugreek, compared with 33.6 mmol/L in high-cholesterol feeding without fenugreek. Cholesterol saturation index in bile was reduced to 0.77-0.99 in fenugreek treatments compared with 2.57 in the high-cholesterol group. Thus, fenugreek seed offers health-beneficial antilithogenic potential by virtue of its favourable influence on cholesterol metabolism.
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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) | 0.001 | 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".