Assessing the fate of fatty acid esters of hydroxy fatty acids, diglycerides and monoacetyldiacylglycerides in grilled ruminant meats marinated with unfiltered beer-based marinades
Bibliographic record
Abstract
Ruminant meats contain functional lipids including fatty acid esters of hydroxy fatty acids (FAHFA), diglycerides (DG), monoacetyldiglycerides (MAcDG) and medium chain triglycerides (McTG) whose consumption in the normal diet can confer benefits for consumer health. However, very little is known concerning how meat processing techniques such as marination and grilling affect the quantity and quality of these functional lipids in ruminant meats. We used ultra high-performance liquid chromatography coupled to high resolution accurate mass tandem mass spectrometry (UHPLC-HRAM-MS/MS) to show how grilling following marination with either India or Wheat ale unfiltered beer-based marinades affected the quantity and quality of these functional lipids in ruminant meats. We observed MAcDG was completely degraded in grilled meats. Both unfiltered beer-based marinades retained higher (p < 0.05) levels of FAHFA, DG and McTG in grilled meats compared to their unmarinated counterparts. Furthermore, India ale-based marinade was more effective (p < 0.05) compared to Wheat ale-based marinade in preserving these lipids in marinated grilled beef and moose meat. Significantly, strong correlations between antioxidants, polyphenols and oxygenated terpenes present in the marinades and preserved lipid molecular species appear to suggest that antioxidants, polyphenols, and oxygenated terpenes present in the marinades could be associated with preservation of these functional lipids in the grilled meats. These findings appear to suggest that marination could preserve some of these functional lipids with India ale-based marination proving to be more effective. However, further work is required to better improve the retention of MAcDG in grilled ruminant meats. This could potentially increase consumption of FAHFA, DG, MAcDG and McTG in the diet and thereby promote consumer health.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".