Influence of isomalto-oligosaccharides on intestinal microbiota in rats
Bibliographic record
Abstract
AIMS: Isomalto-oligosaccharides (IMO) with α(1 --> 6) and α(1 --> 4) glucosidic linkages are produced by enzymatic conversion of starch. IMO are only partially digestible but data on their influence on intestinal microbiota are limited. It was the aim of this study to investigate the effect of IMO diet on intestinal microbiota and short-chain fatty acids production (SCFA) in rats. METHODS AND RESULTS: Three groups of F344 rats, each consisting of six animals, were fed IMO, inulin or a control diets for six weeks. A qualitative assessment of the intestinal microbiota was achieved by PCR-denaturing gradient gel electrophoresis (DGGE). Major bacterial taxa were quantified by quantitative PCR (qPCR), and SCFA were measured using gas chromatography. Quantitative PCR demonstrated that lactobacilli were one of the dominant bacterial taxa in faecal samples from rats. IMO increased the number of lactobacilli and the total number of intestinal bacteria in rats fed IMO compared with animals receiving control and inulin diets. Furthermore, PCR-DGGE with lactobacilli-specific primers showed an altered biodiversity of lactobacilli in rats fed IMO compared with control diet. CONCLUSIONS: IMO selectively stimulates lactobacilli and increases their diversity in rats. SIGNIFICANCE AND IMPACT OF STUDY: Isomalto-oligosaccharides specifically stimulate growth of intestinal lactobacilli in a rat model system.
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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) | 0.000 | 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".