Effect of dry matter intake on visceral organ mass, cellularity, and the protein expression of ATP synthase, Na<sup>+</sup>/K<sup>+</sup>-ATPase, proliferating cell nuclear antigen and ubiquitin in feedlot steers
Bibliographic record
Abstract
Twenty-four steers [467 ± 7.2 kg initial body weight (BW)] predominately of Angus breeding were used to determine the effect of dry matter intake (1.25, 1.50, 1.75, and 2.00% of BW) on visceral mass, cellularity, and the protein expression of ATP synthase, Na+/K+-ATPase, proliferating cell nuclear antigen (PCNA) and ubiquitin. There were linear increases (P ≤ 0.05) in weights of total viscera, total digestive tract, liver, kidney, heart, lung, spleen, rumen, and abomasum with increasing dry matter intake (DMI). Protein concentration decreased linearly (P < 0.05) in small intestinal mucosa as DMI increased. PCNA expression increased linearly (P < 0.01) in liver as DMI increased. PCNA expression was affected quadratically (P < 0.05) in pancreas and small intestinal mucosa with an increase when DMI increased from 1.25 to 1.75% of BW, and a decrease when DMI increased from 1.75 to 2% of BW. ATP synthase, Na+/K+-ATPase, and ubiquitin expression in pancreas and ubiquitin expression in small intestinal mucosa increased linearly (P < 0.05) as DMI increased. These results indicate that increasing DMI increases the mass of visceral organs and carcass and influences expression of proteins influencing energy utilization and efficiency in pancreas, small intestine, liver, and sternomandibularis muscle.Key words: Dry matter intake, visceral organ mass, cellular energy metabolism, steer
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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) | 0.001 | 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 | 0.000 |
| 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".