Effect of prebiotic fibre supplementation on hepatic gene expression and serum lipids: a dose–response study in JCR:LA-cp rats
Bibliographic record
Abstract
Prebiotic fibres have been proposed to promote weight loss and lower serum cholesterol; however, the mechanisms are not fully understood. The aim of the present research was to identify possible mechanisms through which prebiotic fibres improve serum lipids. Lean and obese JCR:La-cp rats aged 8 weeks consumed one of three diets supplemented with 0, 10 or 20 % prebiotic fibre for 10 weeks. Rats were anaesthetised and a fasting blood sample was taken for lipid analysis. Real-time PCR was used to determine gene expression for cholesterol and fatty acid regulatory genes in liver tissue. Liver and caecal digesta cholesterol and TAG content were quantified. Both doses of prebiotic fibre lowered serum cholesterol levels by 24 % in the obese hyperlipidaemic rats (P < 0.05). This change was associated with an increase in caecal digesta as well as an up-regulation of genes involved in cholesterol synthesis and bile production. Additionally, there was a 42 % reduction in TAG accumulation in the liver of the obese rats with 10 % prebiotic diet (P < 0.05); however, no change in liver fatty acid synthase (FAS). Prebiotic fibres appear to lower cholesterol levels through increased cholesterol excretion in the form of bile and inhibit the accumulation of TAG in the liver through a mechanism unrelated to FAS. These effects appear to be limited to the obese model and particularly the 10 % dose. The present work is significant as it provides insight into the mechanisms of action for prebiotic fibres on lipid metabolism and furthers the development of dietary treatments for hypercholesterolaemia.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".