Distinct metabolic adjustments arise from acclimation to constant hypoxia and intermittent hypoxia in estuarine killifish (<i>Fundulus heteroclitus</i>)
Bibliographic record
Abstract
ABSTRACT Many fish experience daily cycles of hypoxia in the wild, but the physiological strategies for coping with intermittent hypoxia are poorly understood. We examined how killifish adjust O2 supply and demand during acute hypoxia, and how these responses are altered after prolonged acclimation to constant or intermittent patterns of hypoxia exposure. We acclimated killifish to normoxia (∼20 kPa O2), constant hypoxia (2 kPa) or intermittent cycles of nocturnal hypoxia (12 h:12 h normoxia:hypoxia) for 28 days, and then compared whole-animal O2 consumption rates (ṀO2) and tissue metabolites during exposure to 12 h of hypoxia followed by reoxygenation in normoxia. Normoxia-acclimated fish experienced a pronounced 27% drop in ṀO2 during acute hypoxia, and modestly increased ṀO2 upon reoxygenation. They strongly recruited anaerobic metabolism during acute hypoxia, indicated by lactate accumulation in plasma, muscle, liver, brain, heart and digestive tract, as well as a transient drop in intracellular pH, and they increased hypoxia inducible factor (HIF)-1α protein abundance in muscle. Glycogen, glucose and glucose-6-phosphate levels suggested that glycogen supported brain metabolism in hypoxia, while the muscle used circulating glucose. Acclimation to constant hypoxia caused a stable ∼50% decrease in ṀO2 that persisted after reoxygenation, with minimal recruitment of anaerobic metabolism, suggestive of metabolic depression. By contrast, fish acclimated to intermittent hypoxia maintained sufficient O2 transport to support normoxic ṀO2, modestly recruited lactate metabolism and increased ṀO2 dramatically upon reoxygenation. Both groups of hypoxia-acclimated fish had similar glycogen, ATP, intracellular pH and HIF-1α levels as normoxic controls. We conclude that different patterns of hypoxia exposure favour distinct strategies for matching O2 supply and O2 demand.
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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".