Trimethylation Enhancement Using Diazomethane (TrEnDi) II: Rapid In-Solution Concomitant Quaternization of Glycerophospholipid Amino Groups and Methylation of Phosphate Groups via Reaction with Diazomethane Significantly Enhances Sensitivity in Mass Spectrometry Analyses via a Fixed, Permanent Positive Charge
Bibliographic record
Abstract
A novel mass spectrometry (MS)-based lipidomics strategy that exposes glycerophospholipids to an ethereal solution of diazomethane and acid, derivatizing them to contain a net fixed, permanent positive charge, is described. The sensitivity of modified lipids to MS detection is enhanced via improved ionization characteristics as well as consolidation of ion dissociation to form one or two strong, characteristic polar headgroup fragments. Our strategy has been optimized to enable a priori prediction of ion fragmentation patterns for four subclasses of modified glycerophospholipid species. Our method enables analyte ionization regardless of proton affinity, thereby decreasing ion suppression and permitting predictable precursor ion-based quantitation with improved sensitivity in comparison to MS-based methods that are currently used on unmodified lipid precursors.
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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) | 0.001 | 0.000 |
| 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) | 0.000 | 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".