Application of resistant starch in swine and poultry diets with particular reference to gut health and function
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The immediate post-weaning period poses a major challenge on the survival of piglets. Similarly, newly hatched chicks face life threatening challenges due to enteric infections. In the past several years, in-feed antibiotics have been used to reduce these production problems and improve growth. However, in-feed antibiotics have been banned in many jurisdictions and therefore the most effective alternatives to in-feed antibiotics must be developed. To date, several studies have been conducted to develop alternatives to antibiotics. One of the potential candidates as alternatives to in-feed antibiotics is resistant starch (RS). Resistance starch is a type of starch that resists enzymatic digestion in the upper parts of the gastrointestinal tract and therefore passes to hindgut where it can be fermented by resident microorganisms. Microbial fermentation of RS in the hindgut results in the production of short chain fatty acids (SCFA). Production of SCFA in turn results in growth and proliferation of colonic and cecal cells, increased expression of genes involved in gut development, and creation of an acidic environment. The acidic environment suppresses the growth of pathogenic microorganisms while selectively promoting the growth of beneficial microbes. Thus, RS has the potential to improve gut health and function by modifying and stabilising gut microbial community and by improving the immunological status of the host. In this review, we discussed the roles of RS in modifying and stabilising gut microbiota, gut health and function, carcass quality, and energy metabolism and growth performance in pigs and poultry.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it