Comparing Subcutaneous Adipose Tissue in Beef and Muskox with Emphasis on <i>trans</i> 18:1 and Conjugated Linoleic Acids
Bibliographic record
Abstract
Muskox (Ovibos moschatus) are ruminant animals native to the far north and little is known about their fatty acid composition. Subcutaneous adipose tissue (backfat) from 16 wild muskox was analyzed and compared to backfat from 16 barley fed beef cattle. Muskox backfat composition differed substantially from beef and the most striking difference was a high content of 18:0 (26.8 vs. 9.77%). This was accompanied by higher levels of most other saturated fatty acids except beef had more 16:0. Muskox backfat also had a lower level of cis-18:1 and this was related to a lower expression of steroyl-CoA desaturase mRNA. Beef backfat had a higher level of total trans-18:1 (4.25 vs. 2.67%). The most prominent trans-18:1 isomers in beef backfat were 10t-18:1 (2.13%) and 11t-18:1 (0.77%) whereas the most prominent isomers in muskox backfat were 11t-18:1 (1.41%), 13t/14t- (0.27%) and 16t-18:1 (0.23%). The total conjugated linoleic acid (CLA) content was higher in beef backfat than muskox (0.67 vs. 0.50%) with 9c,11t-18:2 as the most abundant CLA isomer. The second most abundant CLA isomer in beef backfat was 7t,9c-18:2 (0.10%) whereas in muskox it was 11t13c-18:2 (0.04%). Muskox backfat had a higher content of 18:3n-3 and its elongation and desaturation products 20:5n-3, 22:5n-3 and 22:6n-3 and a lower n-6/n-3 ratio. Overall, the high forage diet of muskox seemed to produce a healthier fatty acid profile and highlighted the need to develop feeding strategies for intensively raising beef that will not negatively impacting fatty acid composition.
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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".