Fatty Acid Profile of Canadian Dairy Products with Special Attention to the trans-Octadecenoic Acid and Conjugated Linoleic Acid Isomers
Bibliographic record
Abstract
Current scientific evidence indicates that consumption of industrial trans fatty acids (TFA) produced via partial hydrogenation of vegetable oils increases the risk of coronary heart disease. However, some studies have suggested that ruminant TFA, especially vaccenic acid (VA or 11t-18:1) and rumenic acid (RA or 9c,11t-18:2), which is a conjugated linoleic acid (CLA) isomer, may have potential beneficial health effects for humans. To date, no concerted effort has been made to provide detailed isomer composition of ruminant TFA and CLA of Canadian dairy products, information that is required to properly assess their nutritional impacts. To this end, we analyzed the fatty acid profile of popular brands of commercial cheese (n = 17), butter (n = 12), milk (n = 8), and cream (n = 4) sold in retail stores in Ottawa, Canada, in 2006-2007 by silver nitrate thin-layer chromatography and gas liquid chromatography. The average total TFA content of cheese, butter, milk, and cream samples were 5.6, 5.8, 5.8, and 5.5% of total fatty acids, respectively. VA was the major trans-octadecenoic acid (18:1) isomer in all the Canadian dairy samples with average levels of (as % total trans-18:1) 33.9% in cheese, 35.6% in butter, 31.0% milk, and 30.1% in cream. The different dairy products contained very similar levels of CLA, which ranged from 0.5 to 0.9% of total fat. RA was the major CLA isomer of all the dairy products, accounting for 82.4-83.2% of total CLA. There were no significant differences (P > 0.05) in the fatty acid profile between the 4 different dairy groups, which suggests lack of processing effects on the fatty acid profile of dairy fat.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 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".