Association of leptin genotype with growth performance, adipocyte cellularity, meat quality, and fatty acid profile in beef steers fed flaxseed or high-oleate sunflower seed diets with or without triticale dried distiller’s grains
Bibliographic record
Abstract
Leptin genotypes can be identified as homozygous normal (CC), homozygous mutant (TT), and heterozygous (CT) based on a single-nucleotide polymorphism in exon 2 of the leptin gene, which has been associated with feed intake and fat deposition in cattle. The experiment was designed as 2 × 2 × 2 factorial with three main factors: (1) genotype (CT or TT) and diets fed 2) with or without triticale dried distiller's grains with solubles (DDG), and 3) with either flaxseed (FS) or high-oleate sunflower seed (SS). Evaluations included growth performance, subcutaneous fat deposition, adipocyte cellularity, meat quality, and fatty acid (FA) profile of various depots. Beef steers (n = 40, 459 ± 31 kg) of either CT or TT genotypes were housed in individual pens with ad libitum access to one of the four diets: 75% steam-rolled barley + 10% barley silage with 10% FS or SS (non-DDG diets, NDG) and 46.5% barley + 10% barley silage + 30% DDG, with 8.5% FS or SS, all on a dry matter basis. Growth performance, ultrasound subcutaneous fat thickness, rib eye area (REA), and plasma FA were measured prior to and during the finishing period. At slaughter, samples of subcutaneous fat, perirenal fat, and Longissimus thoracis (LT) muscle were collected for FA analysis and carcass and meat quality were measured. Compared with CT cattle, TT tended to have less (P = 0.06) C18:2-c9,t11 (rumenic acid) in plasma and subcutaneous fat and a greater proportion (P < 0.05) of C18:0 in subcutaneous, perirenal, and LT fat. Cattle with TT genotype also tended (P < 0.1) to have more total saturated and less unsaturated (USFA) and monounsaturated fats (MUFA) and had less (P = 0.04) linoleic acid in LT. Ultrasound fat thickness, REA, and average diameter of adipocytes in subcutaneous fat at 12 wk were not affected (P > 0.39) by genotype. Generally, carcass and meat quality were similar (P > 0.1) among diets, although adding FS tended to increase (P = 0.06) total USFA of subcutaneous fat including omega-3 FA (P < 0.001). For the high-fat diets evaluated, CT cattle would have more potential to produce beef with enhanced health benefits than would TT cattle.
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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".