The role of carbonic anhydrase-mediated tissue oxygen extraction in a marine teleost acclimated to hypoxia
Bibliographic record
Abstract
With the growing prevalence of hypoxia (O2 levels ≤2 mg l-1) in aquatic and marine ecosystems, there is increasing interest in the adaptive mechanisms fish may employ to better their performance in stressful environments. Here, we investigated the contribution of a proposed strategy for enhancing tissue O2 extraction - plasma-accessible carbonic anhydrase (CA-IV) - under hypoxia in a species of estuarine fish (red drum, Sciaenops ocellatus) that thrives in fluctuating habitats. We predicted that hypoxia-acclimated fish would increase the prevalence of CA-IV in aerobically demanding tissues to confer more efficient tissue O2 extraction. Furthermore, we predicted the phenotypic changes to tissue O2 extraction that occur with hypoxia acclimation may improve respiratory and swim performance under 100% O2 conditions (i.e. normoxia) when compared with performance in fish that have not been acclimated to hypoxia. Interestingly, there were no significant differences in relative CA-IV mRNA expression, protein abundance or enzyme activity between the two treatments, suggesting CA-IV function is maintained under hypoxia. Likewise, respiratory performance of hypoxia-acclimated fish was similar to that of control fish when tested in normoxia. Critical swim speed (Ucrit) was significantly higher in hypoxia-acclimated fish but translated to marginal ecological benefits with an increase of ∼0.3 body lengths per second. Instead, hypoxia-acclimated fish may have relied more heavily on anaerobic metabolism during their swim trials, utilizing burst swimming 1.5 times longer than control fish. While the maintenance of CA-IV may still be an important contributor for hypoxia tolerance, our evidence suggests hypoxia-acclimated red drum are using other mechanisms to cope in an O2-depleted environment.
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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".