Gastrointestinal tract development in fattening lambs fed diets with different amylose to amylopectin ratios
Bibliographic record
Abstract
Thirty-six, 7-d-old male lambs of similar weights were used in the current study to examine the effects of dietary amylose to amylopectin ratios (amylose/amylopectin) on gastrointestinal development in fattening lambs fed concentrates with different sources of starch (tapioca, wheat, maize, and pea) and amylose/amylopectin (0.12, 0.23, 0.24, and 0.48, respectively). The maize starch (MS) and wheat starch (WS) diets improved weight and volume of gastrointestinal. The pea starch diet significantly increased papillar height (P < 0.001), papillar surface area (P = 0.019), and density of papillae (P = 0.001) in the rumen. Additionally, the pea starch diet significantly enhanced villus height, crypt depth, and villus surface area and villus/crypt ratio (P < 0.05) in small intestine. Expressions of insulin-like growth factors I (IGF-1) and insulin-like growth factors’ receptors (IGF-1R) significantly increased in the duodenum mucosa (P = 0.021, P = 0.006, respectively), jejunum mucosa (P = 0.002, P = 0.005, respectively), and ileum mucosa (P = 0.003, P < 0.01, respectively) in the pea starch diet group. The results of the present study show that MS and WS accelerated physical development of rumen and intestine compartments, whereas pea starch increased development of their some morphological parameters, possibly through enhanced expression of genes such as IGF-1 and IGF-1R in fattening lambs.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".