Effect of Glutamine Supplementation on Splanchnic Metabolism in Lactating Dairy Cows
Bibliographic record
Abstract
The suggestion that glutamine (Gln) might become conditionally essential postpartum in dairy cows has been examined through increased postruminal supply of Gln. Net nutrient flux through the splanchnic tissues and mammary gland was measured in 7 multiparous Holstein cows receiving abomasal infusions of water or 300 g/d of Gln for 21 d in a crossover design. Milk yield increased significantly (by 3%) in response to Gln supplementation, but the 2.4% increase in milk protein yield was not statistically significant. Glutamine treatment had no effect on portal or hepatic venous blood flows. Net portal appearance of Gln and Glu was increased by Gln supplementation, accounting for 83% of the infused dose with, therefore, only limited amounts available to provide additional energy to fuel metabolism of the portal-drained viscera. The extra net portal appearance of Gln was offset, however, by a corresponding increase in hepatic removal such that net Gln splanchnic release was not different between treatments. Nonetheless, the Gln treatment resulted in a 43% increase in plasma Gln concentration. Infusions of Gln did not affect splanchnic flux of other nonessential amino acids or of essential amino acids. Glutamine supplementation increased plasma urea-N concentration and tended to increase net hepatic urea flux, with a numerical increase in liver hepatic O2 consumption. There were no effects on glucose in terms of plasma concentration, net portal appearance, net liver release, or postliver supply, suggesting that Gln supplementation had no sparing effect on glucose metabolism. Furthermore, mammary uptake of glucose and amino acids, including Gln, was not affected by Gln supplementation. In conclusion, this study did not support the hypothesis that supplemental Gln would reduce glucose utilization across the gut or increase liver gluconeogenesis or mammary glutamine uptake to increase milk protein synthesis.
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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 | 0.001 |
| 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 | 0.001 | 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".