Paradoxical Impact of Antioxidants on Post-Amadori Glycoxidation
Bibliographic record
Abstract
The inhibition of post-Amadori advanced glycation end product (AGE) formation by three different classes of AGE inhibitors, carbonyl group traps, chelators, and radical-trapping antioxidants, challenge the current paradigms that: 1) AGE inhibitors will not increase the formation of any AGE product, 2) transition metal ions are required for oxidative formation of AGE, and 3) screening AGE inhibitors only in systems containing transition metal ions represents a valid estimate of potential in vivo mechanisms. This work also introduces a novel multifunctional AGE inhibitor, 6-dimethylaminopyridoxamine (dmaPM), designed to function as a combined carbonyl trap, metal ion chelator, and radical-trapping antioxidant. Other AGE inhibitors including pyridoxamine, aminoguanidine, o-phenylenediamine, dipyridoxylamine, and diethylenetriaminepentaacetic acid were also examined. The results during uninterrupted and interrupted ribose glycations show: 1) an unexpected increase in the yield of pentosidine in the presence of radical-trapping phenolic antioxidants such as Trolox and dmaPM, 2) significant formation of Nepsilon-carboxymethyllysine (CML) in the presence of strong chelators and phenolic antioxidants, which implies that there must be nonradical routes to CML, 3) prevention of intermolecular cross-links with radical-trapping inhibitors, and 4) that dmaPM shows excellent inhibition of AGE. Glucose glycations reveal the expected inhibition of pentosidine and CML with all compounds tested, but in a buffer free of trace metal ions the yield of CML in the presence of radical-trapping antioxidants was between the metal ion-free and metal ion-containing controls. Protein molecular weight analyses support the conclusion that Amadori decomposition pathways are constrained in the presence of metal ion chelators and radical traps.
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 | 0.002 |
| 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".