Starch digestion, large-bowel fermentation and intestinal mucosal cell proliferation in rats treated with the α-glucosidase inhibitor acarbose
Bibliographic record
Abstract
Acarbose (Glucobay; Bayer) is an alpha-glucosidase inhibitor used to treat diabetes and which may have a role in the prevention of type 2 diabetes. The present study investigated the effects of acarbose treatment on the site and extent of starch digestion, large-bowel fermentation and intestinal mucosal cell proliferation. Eighteen young male Wistar rats were fed "Westernised" diets containing 0, 250 and 500 mg acarbose/kg (six rats/diet) for 21 d. For most variables measured, both acarbose doses had similar effects. Acarbose treatment suppressed starch digestion in the small bowel but there was compensatory salvage by bacterial fermentation in the large bowel. This was accompanied by a substantial hypertrophy of small- and large-bowel tissue and a consistent increase in crypt width along the intestine. Caecal total SCFA pool size was increased more than 4-fold, with even bigger increases for butyrate. These changes in butyrate were reflected in increased molar proportions of butyrate in blood from both the portal vein and heart. There was little effect of acarbose administration on crypt-cell proliferation (significant increase for mid-small intestine only). This is strong evidence against the hypothesis that increased fermentation and increased supply of butyrate enhances intestinal mucosal cell proliferation. In conclusion, apart from the increased faecal loss of starch, there was no evidence of adverse effects of acarbose on the aspects of large-bowel function investigated.
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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 | 0.001 |
| 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 | 0.001 |
| 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".