162 The interactions between dietary fiber and lipid sources alter the predicted production and absorption of caecal and colorectal volatile fatty acids in growing pigs
Bibliographic record
Abstract
Abstract A combination of in vivo and in vitro fermentation methodologies was used to determine the interactive effects of dietary fiber (DF) and lipid types on volatile fatty acids (VFA) production and absorption, and organic matter (OM) fermentability in the cecum and colorectal tract of pigs. Eight ileal- and caecal-cannulated Yorkshire barrows were fed either pectin- or cellulose-containing diets that were supplemented with either corn oil or beef tallow in two independent Youden squares with a 2×2 factorial arrangement of treatments (n = 6). Ileal and caecal digesta were collected, freeze-dried and fermented using inoculum from fresh caecal digesta and feces, respectively, to determine VFA production and absorption, and fermentability of OM. There were interactions (P < 0.001) between DF and lipid types observed in which the addition of corn oil increased the quantity of caecal and colorectal acetic acid production and caecal acetic absorption, caecal butyric production, predicted caecal OM fermentability, and the predicted colorectal propionic acid in pectin diets but did not have effects in cellulose diets. The addition of beef tallow increased (P < 0.001) the production of caecal butyric and propionic acids during in vitro fermentation in cellulose diets and fermentability of OM in pectin diets. The interactions between DF and lipids on gastrointestinal fermentation largely depends on the degree of saturation of fatty acids in dietary lipids. The addition of beef tallow selectively decreased the production and absorption of individual SCFA in pectin and cellulose diets but increased caecal butyric and propionic acid production in cellulose diets and the fermentability of OM in pectin diets.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".