Oxidative stress and aging: Is methylglyoxal the hidden enemy?This review is one of a selection of papers published in a Special Issue on Oxidative Stress in Health and Disease.
Bibliographic record
Abstract
Aging is a multifactorial process that involves changes at the cellular, tissue, organ and the whole body levels resulting in decreased functioning, development of diseases, and ultimately death. Oxidative stress is believed to be a very important factor in causing aging and age-related diseases. Oxidative stress is caused by an imbalance between oxidants such as reactive oxygen species (ROS) and antioxidants. ROS are produced from the mitochondrial electron transport chain and many oxidative reactions. Methylglyoxal (MG) is a highly reactive dicarbonyl metabolite formed during glucose, protein and fatty acid metabolism. MG levels are elevated in hyperglycemia and other conditions. An excess of MG formation can increase ROS production and cause oxidative stress. MG reacts with proteins, DNA and other biomolecules, and is a major precursor of advanced glycation end products (AGEs). AGEs are also associated with the aging process and age-related diseases such as cardiovascular complications of diabetes, neurodegenerative diseases and connective tissue disorders. AGEs also increase oxidative stress. In this review we discuss the potential role of MG in the aging process through increasing oxidative stress besides causing AGEs formation. Specific and effective scavengers and crosslink breakers of MG and AGEs are being developed and can become potential treatments to slow the aging process and prevent many diseases.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".