Muscle (pectoralis major) protein turnover in young broiler chickens fed graded levels of lysine and crude protein
Bibliographic record
Abstract
An evaluation of muscle (pectoralis major) protein turnover using the phenylalanine flood dose technique was assessed in broiler chicks fed graded dietary lysine levels with CP at 170, 210, 250, and 290 g/kg diet. Chicks at 21 d old were injected with 1 mL/100 g BW of a phenylalanine solution (120 micromol L-[ring-2H5)]-phenylalanine). Muscle protein gain was assessed in chicks at 19 and 23 d of age. No differences were found in weight gain at lysine levels higher than 1.22% of the diet. Dietary lysine levels affected fractional synthesis rate (FSR, %/ d) of muscle with 170 and 210 g of CP/kg diet but not with 250 and 290 g of CP/kg. However, there was increasing FSR with increasing diet lysine levels at 290 g of CP/ kg. Breast muscle protein deposition (absolute growth rate, AGR, mg/d) reached a plateau with 1.22% dietary lysine at CP levels of 170,210, and 290 g/kg diet, confirming the observation on gross muscle weight. In terms of absolute synthesis rate/AGR with minimal absolute breakdown rate (ABR), the diet containing 210 g of CP/kg with 1.22% lysine was the most appropriate for chicks to 21 d. Levels of lysine influenced protein synthesis more so than protein degradation. These data suggest that both protein synthesis and breakdown increase at levels of dietary lysine and CP above those required for maximizing growth.
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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 | 0.000 |
| 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".