The exceptional longevity of the naked mole‐rat may be explained by mitochondrial antioxidant defenses
Bibliographic record
Abstract
Abstract Naked mole‐rats (NMRs) are mouse‐sized mammals that exhibit an exceptionally long lifespan (>30 vs. <4 years for mice), and resist aging‐related pathologies such as cardiovascular and pulmonary diseases, cancer, and neurodegeneration. However, the mechanisms underlying this exceptional longevity and disease resistance remain poorly understood. The oxidative stress theory of aging posits that (a) senescence results from the accumulation of oxidative damage inflicted by reactive oxygen species (ROS) of mitochondrial origin, and (b) mitochondria of long‐lived species produce less ROS than do mitochondria of short‐lived species. However, comparative studies over the past 28 years have produced equivocal results supporting this latter prediction. We hypothesized that, rather than differences in ROS generation, the capacity of mitochondria to consume ROS might distinguish long‐lived species from short‐lived species. To test this hypothesis, we compared mitochondrial production and consumption of hydrogen peroxide (H2O2; as a proxy of overall ROS metabolism) between NMR and mouse skeletal muscle and heart. We found that the two species had comparable rates of mitochondrial H2O2 generation in both tissues; however, the capacity of mitochondria to consume ROS was markedly greater in NMRs. Specifically, maximal observed consumption rates were approximately two and fivefold greater in NMRs than in mice, for skeletal muscle and heart, respectively. Our results indicate that differences in matrix ROS detoxification capacity between species may contribute to their divergence in lifespan.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".