18 Impact of nutritional management strategies on the gastrointestinal development, barrier function and metabolism of the calf and cow.
Bibliographic record
Abstract
Abstract Gut health is a critical determinant of overall performance, disease resistance, and productivity in calves and cows. The gastrointestinal epithelium is tasked with nutrient absorption while maintaining a barrier against harmful luminal contents, making it a highly metabolically active and organ system. In fact, the gastrointestinal tract (GIT), accounts for up to 20% of total oxygen consumption in ruminants, highlighting its substantial energy demand. Key developmental transitions—such as birth, weaning, and the onset of lactation—require major structural and functional adaptations in both the upper and lower GIT. These transitions, however, also expose animals to periods of physiological stress and compromised gut barrier function. In calves, the preweaning period presents a high risk for gastrointestinal disorders and diseases, often exacerbated by microbial and gut barrier dysfunction. Weaning introduces significant stress as the digestive system shifts from milk-based to solid diets, often leading to transient inflammation, altered microbiota, and increased gut permeability, particularly in the lower gut. In adult cows, the transition to highly fermentable, energy-dense diets during early lactation poses another critical challenge. This abrupt dietary shift can disrupt ruminal and intestinal integrity, leading to ruminal acidosis and systemic inflammation via translocation of microbial endotoxins. Nutrients, microbial metabolites, such as butyrate, and gut hormones, including glucagon-like peptide 2 and insulin-like growth factor, play vital roles in stimulating epithelial growth and repair. Understanding how these factors interact to influence gut proliferation and barrier function is crucial, especially when balanced against the energetic cost of gut tissue expansion. Ultimately, optimizing gut development and resilience during key life stages holds promise for improving health, feed efficiency, and lifetime productivity in cattle.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".