Surviving anoxia: the maintenance of energy production and tissue integrity during anoxia and reoxygenation
Bibliographic record
Abstract
ABSTRACT The development of anoxia within tissues represents a significant challenge to most animals because of the decreased capacity for aerobic ATP production, the associated loss of essential cellular functions and the potential for detrimental tissue oxidation upon reoxygenation. Despite these challenges, there are many animals from multiple phyla that routinely experience anoxia and can fully recover. In this Review, we integrate knowledge gained from studies of anoxia-tolerant species across many animal taxa. We primarily focus on strategies used to reduce energy requirements, minimize the consequences of anaerobic ATP production and reduce the adverse effects of reactive oxygen species, which are responsible for tissue damage with reoxygenation. We aim to identify common strategies, as well as novel solutions, to the challenges of anoxia exposure. This Review chronologically examines the challenges faced by animals as they enter anoxia, as they attempt to maintain physiological function during prolonged anoxic exposure and, finally, as they emerge from anoxia. The capacity of animals to survive anoxia is also considered in relation to the increasing prevalence of anoxic zones within marine and freshwater environments, and the need to understand what limits survival.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".