48 Dietary functional fiber properties for improved health and disease outcomes in pigs
Bibliographic record
Abstract
Abstract In swine production, using feed antibiotics as antimicrobial growth promotants has been reduced; thus, feed alternatives to manage gut health are required. Dietary fiber and similar carbohydrate structures such as resistant starch, oligosaccharides, and exopolysaccharides are nutritional tools that may enhance gut health in pigs. Dietary fiber may have a role to alleviate diarrheal diseases including in pigs post-weaning but can also reduce constipation in sows, but specific functionality depends on fiber properties. Antibiotics are hypothesized to influence gut health via modulation of intestinal microbial profiles; fermentation and intestinal inflammation are considered important mechanisms. Dietary fiber sources differ in a key functional property: fermentability. Rapid fermentation of fiber and oligosaccharides is associated with changes in microbial profiles and increased metabolite production. Recently, microbial composition was hypothesized to be less important and combined output of metabolites should be the focus. Fiber properties may also manipulate retention time and physico-chemical properties of the undigested residue; hence, non-fermentable fiber may prevent constipation in sows. The fiber-like structure resistant starch is not digested and acts as fermentable fiber but has unique properties, because it specifically increases intestinal abundance of bifidobacteria, which are associated with improved gut health. Using crop breeding, feed processing, and feed additives, the structure of fiber and starch can be altered thereby changing its degradation kinetics and affecting its prebiotic activity. Finally, fiber-like structures such as exopolysaccharides from Limosilactobacillus reuteri and unique oligosaccharides may serve as receptor analogues for pathogenic bacteria, e.g., enterotoxigenic Escherichia coli (ETEC). These receptor analogues block lectin domains of bacterial adhesins and thus prevent adherence of pathogens to the gut wall, thereby avoiding initiation of post-weaning diarrhea. In conclusion, dietary fiber and similar structures possess important functional properties that may also provide important solutions to maintain gut health in pigs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| 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) | 0.003 | 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".