Species and tissue specific differences in ROS metabolism to hypoxia- and hyperoxia-recovery exposure in marine sculpins
Bibliographic record
Abstract
Animals that inhabit environments that fluctuate in oxygen must not only contend with disruptions to aerobic metabolism, but also the potential effects of reactive oxygen species (ROS) generation. The goal of this study was to compare aspects of ROS metabolism in response to O2 variability (6 hr hypoxia or hyperoxia, with subsequent normoxic recovery) in two species of intertidal sculpin fishes (Cottidae, Actinopterygii) that can experience O2 fluctuations in their natural environment and differ in whole animal hypoxia tolerance. To assess ROS metabolism, we measured the ratio of glutathione and glutathione disulfide as an indicator of tissue redox environment, MitoP/MitoB ratio to assess in vivo mitochondrial ROS generation, thiobarbituric acid reactive substances (TBARS) for lipid peroxidation, and total oxidative scavenging capacity (TOSC) in the liver, brain, and gill. In the brain, the more hypoxia tolerant O. maculosus showed large increases in TBARS levels following hypoxia and hyperoxia exposure that were generally not associated with large changes in mitochondrial H2O2. In contrast, the less-tolerant S. marmoratus showed no significant changes in TBARS or mitochondrial H2O2 in the brain. More moderate responses were observed in the liver and gill of O. maculosus exposed to hypoxia and hyperoxia with normoxic recovery, whereas S. marmoratus showed more responses to O2 variability in these tissues. Our results show that the relationship between hypoxia tolerance and ROS metabolism is species and tissue specific.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".