Characterization of methanolysis products from plasmalogenic lipids in horse muscle tissue
Bibliographic record
Abstract
Muscle tissue is known to contain plasmalogenic lipids. Traditional methodologies for the analysis of lipids in muscle consists of methanolysis followed by gas chromatography (GC). The resultant dimethylacetals (DMA) are difficult to resolve because of extensive overlap with fatty acid methyl esters. In this study a new two-step procedure was applied to isolate DMAs from FAMEs from methanolysed horse muscle lipids (n=48) after saponification and solvent partitioning. Both total and isolated DMAs were analysed by GC and the extent of overlap was evident. The total methylated mixture was also analyzed using GC with online reduction (GC-OR x GC) which confirmed the identity of the FAME, DMA and aldehyde products. The DMA content in horse muscle tissue was found to be 55.7 mg DMAs in 100 g of meat, or 3.10 % of total lipids. The saturates 16:0 and 18:0 were the predominant DMA isomers, and 18:3n-3 and 18:2n-6 DMA were identified in this tissue. Samples with a higher (> 3 g/100 g of meat) intramuscular fat (IM) content showed a lower (p ≤ 0.05) absolute content of the DMAs compared to samples with lower IM fat content (15.3 vs 29.3 mg/g of fat, respectively).
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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".