Methylglyoxal and Advanced Glycation Endproducts: New Therapeutic Horizons?
Bibliographic record
Abstract
Advanced glycation endproducts (AGEs) are unavoidable byproducts of various metabolic pathways. They are formed by reactive metabolic intermediates such as methylglyoxal (MG), glyoxal, and 3-deoxyglucosone. These reactive intermediates bind to proteins, DNA, and other molecules and disrupt their structures and functions, which leads to different diseases such as vascular complications of diabetes, atherosclerosis, hypertension, Alzheimer's disease, and aging. In recent years, more compounds that prevent the formation of AGEs or degrade the existing AGEs have been produced and patented. They include: 1) aminoguanidine, 2) drugs used in the treatment of type 2 diabetes such as metformin and pioglitazone (patented), 3) angiotensin receptor blockers and angiotensin converting enzyme inhibitors, 4) pentoxyfylline (patented), 5) metal ion chelators desferoxamine and penicillamine, 6) antioxidants such as vitamin C or E, 7) amino group capping agents such as aspirin, 8) enzymes that cause deglycation of Amadori products, the Amadoriases, 9) compounds that mostly break alpha-dicarbonyl cross-links such as phenacylthiazolium bromide and its stable derivative ALT-711 (Alagebrium), and 10) derivatives of aryl ureido and aryl carboxaminido phenoxy isobutyric acids (patented). While some of these anti-AGE compounds are being used in clinical practice (such as metformin, pioglitazone, pentoxyfylline and aspirin) or tested in clinical trials (such as aminoguanidine and ALT-711), most of them are commonly used as experimental tools to investigate the role of AGEs in different disease conditions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".