Resistant starch: Implications of dietary inclusion on gut health and growth in pigs: a review
Bibliographic record
Abstract
Starch from cereal grains, pulse grains, and tubers is a major energy substrate in swine rations constituting up to 55% of the diet. In pigs, starch digestion is initiated by salivary and then pancreatic α-amylase, and has as final step the digestion of disaccharides by the brush-border enzymes in the small intestine that produce monosaccharides (glucose) for absorption. Resistant starch (RS) is the proportion of starch that escapes the enzymatic digestion and absorption in the small intestine. The undigested starch reaches the distal small intestine and hindgut for microbial fermentation, which produces short-chain fatty acids (SCFA) for absorption. SCFA in turn, influence microbial ecology and gut health of pigs. These fermentative metabolites exert their benefits on gut health through promoting growth and proliferation of enterocytes, maintenance of intestinal integrity and thus immunity, and modulation of the microbial community in part by suppressing the growth of pathogenic bacteria while selectively enhancing beneficial microbes. Thus, RS has the potential to confer prebiotic effects and may contribute to the improvement of intestinal health in pigs during the post-weaning period. Despite these benefits to the well-being of pigs, RS has a contradictory effect due to lower energetic efficiency of fermented vs. digested starch absorption products. The varying amount and type of RS interact differently with the digestion process along the gastrointestinal tract affecting its energy efficiency and host physiological responses including feed intake, energy metabolism, and feed efficiency. Results of research indicate that the use of RS as prebiotic may improve gut health and thereby, reduce the incidence of post-weaning diarrhea (PWD) and associated mortality. This review summarizes our current knowledge on the effects of RS on microbial ecology, gut health and growth performance in pigs.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".