Analysis of molecular species of peroxide adducts of triacylglycerols following treatment of corn oil with <i>tert</i>‐butyl hydroperoxide
Bibliographic record
Abstract
We recently demonstrated that exposure of synthetic mono- and diunsaturated triacylglycerols to tert-butylhydroperoxide (TBHP) leads to formation of stable adducts of the oxidizing agent and the unsaturated esters (Sjövall, O., Kuksis, A., and Kallio, H., Reversed Phase High-Performance Liquid Chromatographic Separation of tert-Butyl Hydroperoxide Oxidation Products of Unsaturated Triacylglycerols, J. Chromatogr. A 905, 119-132, 2001). In the present study we isolated and identified the TBHP adducts of corn oil triacylglycerols. The much wider range of molecular species available in the corn oil permitted us to demonstrate that the yield of the adducts varies with the degree of unsaturation of the triacylglycerol. The highest yields were obtained for the linoleate (20%, of linoleoyl-containing residual triacylglycerols) and the lowest ones for the oleate (5% of oleoyl-containing residual triacylglycerols) triacylglycerols, whereas the saturated triacylglycerols did not give TBHP adducts in readily detectable amounts. Normal-phase thin-layer chromatography along with reversed-phase high-performance liquid chromatography/mass spectrometry (LC/MS) with electrospray ionization was used to isolate and separate the major molecular species of polyunsaturated triacylglycerols and corresponding TBHP adducts. As an extreme example, the dilinoleoylmonooleoylglycerol was identified as the mono-, di-, tri-, tetra-, and penta-TBHP adduct. LC/MS with electrospray ionization at elevated capillary exit voltage (pseudo tandem mass spectrometry) was used to confirm structures of the [M-RCOOH]+ ions and the absence of TBHP adducts of [M-RCOOH]+. It is concluded that stable adduct formation is an unavoidable complication of preparation of oxotriacylglycerols by oxidation with concentrated TBHP solutions and care must be taken to resolve the adducts from the desired oxidation product.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".