Lyso‐form fragment ions facilitate the determination of stereospecificity of diacyl glycerophospholipids
Bibliographic record
Abstract
In this work we report the development of a novel methodology for the determination of stereospecificity of diacyl glycerophospholipids, including glycerophosphatidic acids (PA), glycerophosphoserines (PS), glycerophosphoglycerols (PG), glycerophosphoinositols (PI), and glycerophosphoethanolamines (PE), which can be conventionally ionized in negative ion mode. This methodology uses MS(2) recorded on a hybrid quadrupole time-of-flight mass spectrometer to determine the stereospecificity of diacyl glycerophospholipids based on the lyso-form fragment ions, attributed to the neutral loss of fatty acyl moieties. The fragmentation patterns of a variety of diacyl glycerophospholipid standards were first fully examined over a wide range of collision energy. We observed that lyso-form fragment ions corresponding to the neutral loss of fatty acyl moieties attached to the sn2 position as free fatty acids ([M-Sn2](-) ) and as ketenes ([M-(Sn2-H(2) O)](-) ) exhibited consistently higher intensity than their counterpart ions due to the neutral loss of fatty acyl moieties attached to the sn1 position ([M-Sn1](-) and [M-(Sn1-H(2) O)](-) ). Therefore, we concluded that an empirical fragmentation rule can be used to precisely determine the stereospecificity of diacyl glycerophospholipids, primarily on the basis of relative abundance of the lyso-form fragment ions. We then examined the product ion spectra of diacyl glycerophospholipids recorded from lipid extracts of rat hepatoma cells, where the stereospecific information of these lipids was conclusively determined. Combining the novel methodology reported in this work with the currently widely practiced mass spectrometric techniques such as multiple precursor ion scans (MPIS), fatty acyl scans (FAS), and multidimensional mass spectrometry based shotgun lipidomics (MDMS-SL), should enable a reliable and convenient platform for comprehensive glycerophospholipid profiling.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".