The longest-lived metazoan, Arctica islandica, exhibits high mitochondrial H2O2 removal capacities
Bibliographic record
Abstract
• Mitochondria from the extremely long-lived marine bivalve Arctica islandica consumes 3–14 times more hydrogen peroxide than two shorter-lived counterparts. • This finding supports previous results on mammals and points to consumption of reactive oxygen species (ROS), as a key determinant of a long-lived mitochondrial phenotype. • Overall, these results support the mitochondrial oxidative stress theory of aging (MOSTA), although more work needs to be done to assess net production of hydrogen peroxide in these species. A greater capacity of endogenous matrix antioxidants has recently been hypothesized to characterize mitochondria of long-lived species, curbing bursts of reactive oxygen species (ROS) generated in this organelle. Evidence for this has been obtained from studies comparing the long-lived naked mole rat to laboratory mice. We tested this hypothesis by comparing the longest-lived metazoan, the marine bivalve Arctica islandica (MLSP = 507 y), with shorter-lived and evolutionarily related species. We used a recently developed fluorescent technique to assess mantle and gill tissue mitochondria’s capacity to consume hydrogen peroxide (H 2 O 2 ) in multiple physiological states ex vivo . Depending on the type of respiratory substrate provided, mitochondria of Arctica islandica could consume between 3 and 14 times more H 2 O 2 than shorter-lived species. These findings support the contention that a greater capacity for the elimination of ROS characterizes long-lived species, a novel property of mitochondria thus far demonstrated in two key biogerontological models from distant evolutionary lineages.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".