Effect of ractopamine on whole body and splanchnic energy metabolism in Holstein steers
Bibliographic record
Abstract
This study was designed to examine the influence of ractopamine (RAC) on whole-body and splanchnic energy balance. Six growing Holstein steers [body weight (BW) = 402 ± 39.5 kg] surgically fitted with an arterial and portal, hepatic, and mesenteric venous indwelling catheters were used in a repeated measures study. Treatments were a basal diet of alfalfa cubes fed at approximately 1.5× maintenance energy requirements (days 1-21) and basal plus RAC (430 mg head d-1; days 22-42). On day 14 of each period, splanchnic and portal-drained viscera (PDV) energy balances were determined as the product of arterio-venous O2 difference and blood flow. Blood flow was determined using down-stream dilution of p-aminohippuric acid. Whole-body energy balance was determined on days 15-21 of each period, which included 7 d total excreta collection and 3 d of respiratory gas exchange measurements. Body weight and DM intake were greater (P < 0.05) for steers receiving RAC compared with those receiving the control diet; however, no difference was observed in either BW or DMI when expressed on a BW0.75 basis. Similarly, as a function of BW0.75, whole-body heat production (691 kJ kg BW0.75 d-1; P = 0.96) and retained N (0.85 g kg BW0.75 d-1; P = 0.34) and energy (298 kJ kg BW0.75 d-1; P = 0.71) were unaffected by RAC. In contrast, RAC tended to decrease (P = 0.09) energy use by splanchnic tissues (191 vs. 156 kJ kg BW0.75 d-1), largely due to a reduction (P = 0.12) in energy use by the PDV (100 vs. 86 kJ kg BW0.75 d-1). These data indicate that although whole-body energy use is not affected by RAC, energy use by splanchnic tissues is decreased, thereby increasing energy use by peripheral tissues.Key words: Bovine, ractopamine, beta-agonist, energy balance, metabolism
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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 | 0.000 | 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".