Quantitative analysis of positional isomers of triacylglycerols via electrospray ionization tandem mass spectrometry of sodiated adducts
Bibliographic record
Abstract
Herein we report a reversed-phase high-performance liquid chromatography tandem mass spectrometry (RP-HPLC/MS/MS) method for the analysis of positional isomers of triacylglycerols (TAGs) in vegetable oils. The fragmentation behavior of [M + X](+) ions (X = NH(4), Li, Na or Ag) was studied on a quadrupole-time-of-flight (Q-TOF) mass spectrometer under low-energy collision-induced dissociation (CID) conditions. Mass spectra that were dependent on the X(+) ion and the nature and position of the acyl substituents were observed for four pairs of 'AAB/ABA'-type TAGs, namely PPO/POP, OOP/OPO, LLO/LOL and OOL/OLO (where P is 16:0, palmitic acid; O is 18:1, oleic acid; and L is 18:2, linoleic acid). For the majority of [M + X](+) adducts, the loss of the fatty acid in the outer positions (sn-1 or sn-3) was favored over the loss in the central position (sn-2), which enabled the determination of the fractional abundance of the isomers. Ratios of the intensity of fragment ions at various AAB/ABA compositions produced linear calibration curves with positive slopes, comparable to those obtained traditionally by ESI-MS/MS of [M + NH(4)](+) adducts. The only exceptions were the [M + Ag](+) adducts of the PPO/POP system, which produced calibration curves with negative slopes. Sodium adducts provided the most consistent level of isomeric discrimination for the TAGs studied and also offered the most convenience in that they required no additive to the mobile phase. Therefore, calibration curve data derived from [M + Na](+) adducts were applied to the quantification of TAG regioisomers in sunflower and olive oils. The regiospecific analysis showed that palmitic acid was typically located at positions sn-1 or sn-3, whereas unsaturated fatty acids, oleic and linoleic acids were mostly found at the sn-2 position.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".