Increasing the Sensitivity of Phospholipid Analyses from Biological Extracts via Trimethylation Enhancement using Diazomethane (TrEnDi) and Tandem Mass Spectrometry
Bibliographic record
Abstract
TrEnDi is a novel rapid in-solution technique for quaternization of phospholipid amino groups and methylation of phosphate groups via reaction with diazomethane and tetrafluoroboric acid. TrEnDi significantly enhanced the sensitivity of mass spectrometry and tandem MS studies of phosphatidylethanolamine, phosphatidylserine, phosphatidylcholine and sphingomyelin standards. Use of 13C-diazomethane enabled creation of independent precursor ion scans (PIS) for modified PE and modified PC species which would otherwise can produce undistinguishable isobaric species. The efficacy of the technique was tested on a complex biological sample. 13C-TrEndi provided a drastic sensitivity enhancement for PE and PS species enabling the identification and quantitation of several species which were below the limit of detection and quantitation prior to modification. Derivatization provided a modest sensitivity enhancement for PC species and allowed quantitation of several PC species that were below the limit of quantitation prior to modification. SM species exhibited neither sensitivity increase nor hindrance after modification.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".