Effect of viscosity and fermentability of purified non‐starch polysaccharides (NSP) on kinetics of net glucose and short chain fatty acids (SCFA) portal flux and insulin secretion in porto‐arterial catheterized pigs
Bibliographic record
Abstract
The NSP may lower glycemic and insulin responses, but specific contributions of viscosity and fermentability are unknown. Thus, the effects of NSP on net nutrient portal flux and insulin responses were studied in 4 pigs with 2 catheters [portal vein, carotid artery] and 1 blood flow probe [portal vein]. Semi‐purified [cornstarch, casein] diets supplemented with 5% purified NSP sources were fed in a 2 (low, high viscous; V) × 2 (low, high fermentable; F) factorial arrangement using: low V, low F cellulose (CEL1), high V, low F carboxymethylcellulose (CMC), low V, high F cellulose (CEL2), and high V, high F oat β‐glucan (HVG). Blood was sampled for 12 h postprandially and net nutrient portal flux and insulin secretion were calculated from plasma portal‐arterial differences × flow. Blood flow, portal and carotid glucose and net glucose portal flux peaked at 45 min after feeding ( P <0.001) and were not affected by NSP. However, fermentable NSP (CEL2 and HVG) increased ( P <0.05) net glucose portal flux 46% over 12 h postprandially. Insulin secretion was 44% lower ( P <0.05) for viscous than non viscous NSP. The CEL2 and HVG diets increased ( P <0.05) net SCFA portal flux for propionate and butyrate 48%, indicating increased colonic fermentation. In conclusion, viscosity of NSP reduced insulin secretion and fermentable NSP increased net portal flux of glucose, propionate, and butyrate. Grant Funding Source: ALMA, Danisco, and Alberta Pulse Growers
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".