Derivatization of small oligosaccharides prior to analysis by matrix‐assisted laser desorption/ionization using glycidyltrimethylammonium chloride and Girard's reagent T
Bibliographic record
Abstract
In matrix-assisted laser desorption/ionization (MALDI) analyses of small oligosaccharides a very large increase in sensitivity (by a factor of 1000) may be obtained by introducing a quaternary ammonium center ('quaternization'). Such a quaternary ammonium center may be introduced into the saccharide by reaction with commercially available glycidyltrimethylammonium chloride (GTMA), or by using Girard's reagent T (Naven and Harvey, Rapid Commun. Mass Spectrom. 1996; 10: 829). GTMA reacts with alcohol functionalities, whereas Girard's reagent T is specific for aldehyde and keto groups. Thus reducing saccharides can be derivatized by both GTMA and Girard's reagent T. For example, glucose or cellobiose having a stock concentration of 3 x 10(-5) M (5 microg/mL) produces no sugar-derived signals in conventional MALDI, but their quaternized derivatives, also at 3 x 10(-5) M, yield intense signals, with the matrix-derived signals only being weak. Similar results were obtained for glucosamine. Non-reducing saccharides as well as sugar alcohols can be derivatized using GTMA; thus, although sucrose, raffinose and sorbitol do not react with Girard's reagent T, they all produce intense signals after derivatization with GTMA. An example of the application of these derivatization reactions is provided by the analysis of oligosaccharides in beer.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".