Monitoring Glycation of Lysozyme by Electrospray Ionization Mass Spectrometry
Bibliographic record
Abstract
Electrospray ionization mass spectrometry (ESI-MS) was used to study the glycation of lysozyme by D-glucose (LZM-G) and by D-fructose (LZM-F) under dry heating conditions in the presence and in the absence of oxygen. ESI-MS proved to be a precise method for monitoring protein glycation with respect to following the extent of glycation and changes in the glycoconjugate profile with time. The ESI-MS spectrum of glycated LZM revealed a heterogeneous distribution of glycoforms of LZM at different reaction stages. D-Glucose showed a higher level of reactivity with the amino groups of LZM than D-fructose, both in the presence and in the absence of oxygen. The presence of oxygen in the reaction system induced oxidative side reactions, which competed with and slowed the initial rate of formation of Amadori or Heyns products. The more reactive glycoxidation products formed during the initial stages of incubation in the presence of oxygen accelerated the rate of glycation during the later stages of incubation and increased the involvement of arginine residues of LZM in the glycation reaction. The interaction between the initial glycoxidation product(s) of the reducing sugars and intact lysozyme during the later stages of incubation was observed by the appearance of a different cluster of glycoconjugates in the mass spectrum during the latter stages of incubation. The molecular weight differences between the molecular ions of the new cluster of glycoconjugates are consistent with the formation of D-glucosone from the autoxidation of D-glucose or from the oxidative cleavage of the glucose-lysozyme imine adduct in the lysozyme-glucose system. The effect of oxygen-induced glycoxidation on the glycation reaction was also more pronounced in the LZM-G system compared with that in the LZM-F system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 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".