PSX-A-2 Effects of Dietary Crude Protein Level and Corn Grain Processing on Whole-Body Urea Kinetics and in-Vitro Urea Secretion Into the Rumen of Sheep
Bibliographic record
Abstract
Abstract In ruminants, urea-N salvaging allows secretion of endogenously-produced urea (UER) into the rumen, where it can provide N for microbial growth. Our objective was to determine the effects of dietary crude protein content and corn grain processing on whole-body urea kinetics and in vitro serosal-to-mucosal urea flux (Jsm-urea) across ruminal epithelia. Thirty-two Rideau-Arcott ram lambs were blocked by BW into groups of 4 and then randomly allocated within block to one of 4 dietary treatments (n = 8) in a 2 × 2 factorial design. Dietary factors were crude protein content (10.9% [LP] vs. 15.8% [HP]) and corn grain processing (whole-shelled [WSC] vs. steam-flaked [SFC]). Feeding SFC was expected to provide more ruminally-fermentable energy than WSC. Four blocks of animals (n = 4) were used in 4-d continuous infusions of 15N-15N with concurrent collections of urine and feces to determine whole-body urea kinetics. After 23 d of dietary exposure, lambs were killed to collect ruminal epithelia which were mounted in Ussing chambers to determine Jsm-urea. Lambs fed HP had greater N intake (P = 0.01) and total N excretion (P = 0.002) than those fed LP; however, retained N (g/d or % of N intake) was similar between the 2 groups. When expressed as absolute amounts, urea-N secreted into the gut (GER) and urea-N used for anabolic purposes (UUA) were similar across diets; however, lambs fed the LP diet had a greater GER/UER ratio (P = 0.02) and tended to have a greater UUA/GER ratio (P = 0.05) than lambs fed the HP diet. Diet had no effect on ruminal Jsm-urea. Grain processing had no effects on GER, UUA and Jsm-urea. These results suggest ruminants fed protein-restricted diets have a greater dependence on urea secretion into the gut to provide N for anabolic use.
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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) | 0.001 | 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 | 0.001 |
| 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".