5-Nitrosalicylic Acid as a Novel Matrix for In-Source Decay in Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry
Bibliographic record
Abstract
The matrix-assisted laser desorption/ionization in-source decay (MALDI-ISD) of peptides and glycans was studied using an oxidizing chemical, 5-nitrosalicylic acid (5-NSA) as the matrix. The use of 5-NSA for the MALDI-ISD of peptides and glycans promoted fragmentation pathways involving "hydrogen-deficient" radical precursors. Hydrogen abstraction from peptides resulted in the production of a "hydrogen-deficient" peptide radical that contained a radical site on the amide nitrogen in the peptide backbone with subsequent radical-induced cleavage at the Cα-C bonds. Cleavage at the Cα-C bond leads to the production of an a (•)/x fragment pair and the radical a (•) ions then undergo further hydrogen abstraction to form a ions after Cα-C bond cleavage. Since the Pro residue does not contain a nitrogen-centered radical site, Cα-C bond cleavage does not occur at this site. Alternatively, the specific cleavage of CO-N bonds leads to a b (•)/y fragment pair at Xxx-Pro which occurs via hydrogen abstraction from the Cα-H in the Pro residue. In contrast, "hydrogen-deficient" glycan radicals were generated by hydrogen abstraction from hydroxyl groups in glycans. Both glycosidic and cross-ring cleavages occurred as the result of the degradation of "hydrogen-deficient" glycan radicals. Cross-ring cleavage ions are potentially useful in linkage analysis, one of the most critical steps in the characterization of glycans. Moreover, isobaric glycans could be distinguished by structure specific ISD ions, and the molar ratio of glycan isomers in a mixture can be estimated from their fragment ions abundance ratios. MALDI-ISD with 5-NSA could be a useful method for the sequencing of peptides including the location of post-translational modifications, identification and semi-quantitative analysis of mixtures of glycan isomers.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".