Analysis of Protein Glycation Products by MALDI‐TOF/MS
Bibliographic record
Abstract
Matrix-assisted laser desorption ionization-mass spectrometry with time-of-flight detection (MALDI-TOF/MS) is a promising tool to analyze advanced glycation end product (AGE)-modified proteins. The combination of soft ionization (MALDI) with time-of-flight mass detection allows analysis of peptides and proteins of a molecular mass up to 300 kDa with minimal sample workup. Because the direct structural analysis of intact AGE proteins is not possible due to the formation of broad and poorly resolved peaks, peptide mapping was introduced into the analysis of AGE proteins by MALDI-TOF/MS, allowing site-specific analysis of defined AGEs. When methylglyoxal-modified lysozyme was subjected to MALDI-TOF/MS peptide mapping, methylimidazolone and argpyrimidine attached to the arginine residue and carboxyethyl (CEL) bound to the lysine were detected on peptide(aa1-7) (KVFGRCE). In contrast, only one methylimidazolone was found on peptide(aa8-35) (LAAAMKRHGLDNYRGYSLGNWVCAAKFE) and peptide(aa120-129) (VQAWIRGCRL), respectively. The analysis of AGE protein, which had been incubated with glucose, revealed the presence of an Amadori product and a carboxymethyl residue (CML) on peptide(aa1-7) and peptide(aa8-35), as well as an imidazolone A on peptide(aa120-129). Furthermore, the early Maillard reaction of lysozyme, which had been glycated by seven different sugars, was monitored by MALDI-TOF/MS peptide mapping. Finally, this approach was successfully applied for site- and product-specific relative quantification of AGEs. For example, kinetics of CML and Amadori product formation on peptide(aa1-7), as well as imidazolone A formation on peptide(aa120-129), were determined.
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 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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".