Inulin fiber dose-dependently modulates energy balance, glucose tolerance, gut microbiota, hormones and diet preference in high-fat-fed male rats.
Bibliographic record
Abstract
Inulin, a popular prebiotic fiber, has been reported to promote satiety and fat loss; however, the dose-response effects of inulin on energy balance and diet preference, and whether the metabolic effects are independent of calorie restriction are not well characterized. Therefore, we compared the effects of diets varying in inulin concentrations on food intake, energy expenditure, body composition, gut microbiota and hormones, and assessed whether inulin-induced hypophagia was due to reduced diet preference. In experiment 1, male rats were randomized to six high-fat diet groups: control (CON, 0% inulin), 2.5% inulin (2.5IN), 10% inulin (10IN), 25% inulin (25IN), 25% cellulose (25CE) or pair-fed to 25IN (25PF) for 21 days. We demonstrate that inulin dose-dependently decreased caloric intake and respiratory quotient; improved glucose tolerance; increased the abundance of Bacteroidetes and Bifidobacterium spp.; decreased Clostridium clusters I and IV; increased butyryl-CoA:acetate CoA-transferase in cecum; upregulated peptide YY, cholecystokinin and proglucagon transcripts in the cecum and colon; and increased plasma peptide YY and glucagon-like peptide-1 concentrations. Importantly, unlike 25PF, 25IN attenuated the reduction in energy expenditure associated with calorie restriction and decreased adiposity. In experiment 2, following four training periods, diet preferences were determined. Although 10IN and 25IN decreased caloric intake, and 25CE increased caloric intake, during training, all high-fiber diets were less preferred. Taken together, this work demonstrates that inulin dose-dependently decreased caloric intake, modulated gut microbiota and upregulated satiety hormones, with metabolic effects being largely independent of caloric restriction.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.001 |
| 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".