Monitoring cyclic acyloxonium ion formation in palmitin systems using infrared spectroscopy and isotope labelling technique
Bibliographic record
Abstract
Abstract To confirm the possible involvement of acyloxonium ions as reactive intermediates in food related lipids, their formation was monitored in triplamitin, 1,2 dipalmitin, 1‐monopalmitin and specifically labelled tripalmitin (1,1,1‐13C3) using Fourier‐transform IR spectroscopy (FTIR). Reactions were conducted at 100°C using a mixture of ZnCl2 and the lipids. When tripalmitin or 1,2‐dipalmitin samples were heated at 100°C in the presence of ZnCl2 a new band centred at 1651 cm−1 was formed and increased over time. When 13C‐labelled tripalmitin (1,1,1‐13C3) was studied the spectrum exhibited an expected 40 cm−1 shift from 1651 to 1611cm−1 indicating the involvement of the carbonyl carbon in the formation of the band. The 1‐monopalmitin generated a similar but weaker band at higher temperatures and requiring longer times. These observations may indicate that under hydrophobic environment acyloxonium ions are preferentially formed with neighbouring ester groups assisted by the catalytic action of a free hydroxyl group serving as a proton transfer site. In the absence of such a free hydroxyl group tripalmitin undergoes acyloxonium ion formation at a slower rate than 1,2‐dipalmitoyl glycerol, whereas, 1‐monopalmitoyl glycerol due to the absence of a neighbouring ester shows even slower transformation efficiencies. This order of reactivity may however change in the presence of water.
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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".