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Record W2129418091 · doi:10.1093/ps/83.11.1897

Muscle (pectoralis major) protein turnover in young broiler chickens fed graded levels of lysine and crude protein

2004· article· en· W2129418091 on OpenAlexaff
María Urdaneta-Rincón, S. Leeson

Bibliographic record

VenuePoultry Science · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsLysineBroilerPhenylalanineProtein turnoverWeight gainAnimal scienceInternal medicineChemistryMuscle proteinStarterEndocrinologyBody weightBiologyBiochemistryProtein biosynthesisFood scienceAmino acidSkeletal muscleMedicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.921
Threshold uncertainty score0.233

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.235
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations55
Published2004
Admission routes1
Has abstractyes

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