Diel cycling hypoxia enhances hypoxia-tolerance in rainbow trout (<i>Oncorhynchus mykiss</i>): evidence of physiological and metabolic plasticity
Bibliographic record
Abstract
Many fish naturally encounter a daily cycle of hypoxia but it is unclear whether this exposure hardens hypoxia-intolerant fish to future hypoxia or leads to accumulated stress and death. Rainbow trout (Oncorhynchus mykiss) is a putatively hypoxia-sensitive species found in rivers and estuaries that may routinely experience hypoxic events. Trout were exposed to 1 of 4 135h treatments in a swim-tunnel respirometer: 1) air-saturated control (20.7 kPa PO2); 2) diel cycling O2 (20.7-4.2 kPa over 24h); 3) acute hypoxia (130h at 20.7 kPa PO2 followed by 5h at 4.2 kPa PO2); 4) the mean oxygen tension (12.4 kPa PO2) experienced by the diel cycled fish. Some responses were similar in diel O2 cycled and mean PO2-treated fish but overall exposure to ecologically-representative diel hypoxia cycles improved hypoxia tolerance. Diel hypoxia-induced protective responses included increased inducible HSP70 concentration and mean corpuscular hemoglobin concentration, as well as reduced plasma cortisol. Acclimation to diel hypoxia allowed metabolic rates to decline during hypoxia, reduced oxygen debt following subsequent exposures, and allowed fish to return to an anabolic phenotype. The data demonstrate that acute diel cycling hypoxia improves hypoxia tolerance in previously intolerant fish through the activation of cellular protective mechanisms and a reduction in metabolic O2 requirements.
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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".