N-6 and n-3 fatty acids in different beef adipose tissues depending on the presence or absence of the gene responsible for double-muscling
Bibliographic record
Abstract
Levels of n-6 and n-3 PUFAs, including those with 20 and 22 carbon-chains, in concentrate-fed Asturiana de los Valles (AV) yearling bulls with and without the double muscling gene (mh/mh = 24, mh/+ = 26, +/+ = 25) were measured to examine if this gene influences the pattern of PUFA deposition in different adipose tissues. Fatty acid compositions of muscle tissue (longissimus thoracis) and intermuscular and subcutaneous adipose tissues were determined by gas chromatography. The composition of intramuscular fat was unique compared to the other two adipose tissues which were similar in composition. In general, n-6 and n-3 fatty acid elongation and desaturation products were affected by AV genotype and this effect was most evident in n-3 PUFAs of the intramuscular fat of mh/mh (n-6/n-3 = 11.8 and 18:2n-6/18:3n-3 = 25.3) compared to mh/+ and +/+ animals (mean values of n-6/n-3 = 9.86 and 18:2n-6/18:3n-3 = 15.5). PUFA elongation and desaturation end products did not accumulate to any great extent in intermuscular and subcutaneous adipose tissues. Beef from mh/mh cattle showed greater deposition rates of n-3 elongation and desaturation products but their absolute content of total n-3 fatty acids was lower (21 mg/100 g meat) in comparison with mh/+ and +/+ cattle (mean value of 25 mg/100 g meat).
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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 | 0.001 | 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".