Digestible Methionine + Cysteine: Digestible Lysine Ratio in Diets for Broilers Submitted to Inflammatory Challenge
Bibliographic record
Abstract
ABSTRACT Methionine (Met) and cysteine (Cys) are nutrients in broiler diets, responsible for strengthening protein synthesis, immunity, and metabolic regulation. To estimate the ideal digestible Met + Cys:digestible Lysine (Lys) ratio for broilers under a lipopolysaccharide (LPS) inflammatory challenge, 384 male broilers were distributed in a completely randomized 4×2 factorial design, with four ratios of dig. Met + Cys:dig. Lys (0.69, 0.73, 0.77, and 0.81) and two conditions (with or without challenge). Each treatment had eight replicates, with six birds per experimental unit (EU). The evaluated parameters included broilers’ weight gain (WG), feed intake (FI), and feed conversion ratio (FCR); jejunum mRNA transcript levels of nuclear factor kappa-B (NF-Κb), glutathione peroxidase (GPX), superoxide dismutase (SOD), glutathione synthetase (GSS), and methionine adenosyltransferase 2 (MAT2); relative weights of liver and spleen, and fat mass (%) and lean mass (%). A linear regression model would estimate the ideal ratio if an effect had occurred. No interaction (p>0.05) was observed between the factors for all the data, nor did the different ratios had any effect (p>0.05) either. LPS-administered exhibited reduced performance, heavier liver and spleen, and lower GSS expression. Hence, the lowest dig Met + Cys:dig Lys ratio (0.69) was sufficient to maintain the performance parameters, the relative weight of lymphoid organs, fat and lean mass, and NF-Kb, GPX, SOD, GSS, MAT2, and CBS mRNA transcript levels in the jejunum.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".