Do Antioxidant Strategies Work against Aging and Age‐associated Disorders?
Bibliographic record
Abstract
The free radical theory of aging was initially proposed by Harman half a century ago primarily to explain biological aging processes. Although administration of so-called antioxidant chemicals, which have been tested in the past for several decades, turned out to be mostly ineffective in prolonging the life spans of animals, the same theory of age-associated diseases appears to be increasingly supported in the last two decades. Despite these difficulties, the success in extending life span of 4 different animal species (mice, rats, hamsters, and dogs) with (-)deprenyl (including a study of our group) indicates that there might exist another type of antioxidant strategy in addition to a simple administration of antioxidant chemicals. (-)Deprenyl has also been shown to increase superoxide dismutase (SOD) and catalase (CAT) activities selectively in brain dopaminergic tissues. Interestingly, we have recently shown that another propargylamine, rasagiline not only increases antioxidant enzyme activities (CAT and SOD) in brain dopaminergic regions as (-)deprenyl does, but also increases CAT and SOD activities in extrabrain catecholaminergic systems such as the heart and kidneys as well. These recent observations coupled with previous observations on the life span of animals with (-)deprenyl suggest that pharmacological modulation of endogenous antioxidant enzyme activities could be one potential antioxidant strategy against aging and age-associated disorders. If the causal relationship between the two effects of (-)deprenyl exists as we hypothesized, we might be able to advance the elucidation of mechanism(s) of aging based on the free radical theory of aging.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".