Study of Fragmentation Behavior of Amadori Rearrangement Products in Lysine-Containing Peptide Model by Tandem Mass Spectrometry
Bibliographic record
Abstract
Protein and peptide glycation with reducing sugars through Maillard reaction is recognized as one of the most critical and fundamental reactions in food and in the human body. Amadori rearrangement products (ARPs) are formed at the initial stage of Maillard reaction and then may be converted into intermediate and advanced glycation products. We report here that using electrospray ionization-mass spectrometry (ESI-MS) to directly and rapidly characterize fragmentation behavior of ARPs in a Lysine-containing peptide-reducing sugars unambiguously model and identify the modification sites in glycated tri- and tetrapeptides. Tandem mass spectrometry (MS2) results showthat the sugar moiety was preferentially fragmented, whereby the neutral loss of small molecules, such as 18 Da (-H2O), 36 Da (-2 x H2O), 54 Da (-3 x H2O), 84 Da (-H2O-HCOH) and 162 Da from monosaccharide (glucose) moieties and 18 Da, 36 Da, 216 Da, 246 Da and 324 Da from disaccharide moieties. Among the fragmented ions, (M-84+H)+ of monosaccharides and (M-246+H)+ of disaccharides are relatively stable. Further multi-stage mass spectrometry (MS3) of (M-84+H)+ for tri- and longer peptides displays peptide sequence and glycation sites by providing modified y ions (y*), and/or modified b ions (b*) and even a modified a ion (a*). The study is useful to monitor and characterize PMTs of glycation in complex protein systems based on ESI-MS related techniques.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".