Dietary rhubarb (<i>Rheum rhaponticum</i>) stalk fibre does not lower plasma cholesterol levels in diabetic rats
Bibliographic record
Abstract
Rhubarb (Rheum rhapontiam) stalk fibre was previously shown to be hypolipidaemic under clinical and experimental conditions. The present study was undertaken to investigate whether rhubarb stalk fibre has a hypolipidaemic effect under diabetic conditions. Two models of diabetic rats were used: streptozotocin-induced diabetic rats, and diabetes-prone BB (BBdp) rats. The plasma cholesterol and triacylglycerol concentrations were elevated after the onset of diabetes in BBdp rats, but not in sterptozotocin-induced diabetic rats. The rhubarb-fibre diet had no effect on the plasma cholesterol or triacylglycerol concentrations of diabetic rats. The hypolipidaemic effect of rhubarb stalk fibre has been suggested to be due to the bile-acid-binding capacity of rhubarb fibre, which in turn up regulates cholesterol 7alpha-hydroxylase (cyp7a) activity. cyp7a is the first and the rate-limiting enzyme in the breakdown of cholesterol to bile acids. We measured the cyp7a activity and mRNA levels in control and diabetic rats fed rhubarb- and cellulose-fibre diets. The cyp7a activity and mRNA abundance were increased in both diabetic rat models, indicating that bile acid synthesis is enhanced in diabetes. Feeding a diet enriched with rhubarb fibre caused a slight but significant increase (P<0.05) in cyp7a enzyme activity in BBdp rats, but no change in cyp7a mRNA abundance was detected. These results suggest that although a rhubarb-fibre-enriched diet increased cyp7a activity in BBdp rats, there was no apparent therapeutic benefit in terms of lowering plasma cholesterol concentrations.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".