The evolutionary and physiological significance of the Hif pathway in teleost fishes
Bibliographic record
Abstract
The hypoxia-inducible factor (HIF) pathway is a key regulator of cellular O2 homeostasis and an important orchestrator of the physiological responses to hypoxia (low O2) in vertebrates. Fish can be exposed to significant and frequent changes in environmental O2, and increases in Hif-α (the hypoxia-sensitive subunit of the transcription factor Hif) have been documented in a number of species as a result of a decrease in O2. Here, we discuss the impact of the Hif pathway on the hypoxic response and the contribution to hypoxia tolerance, particularly in fishes of the cyprinid lineage, which includes the zebrafish (Danio rerio). The cyprinids are of specific interest because, unlike in most other fishes, duplicated paralogs of the Hif-α isoforms arising from a teleost-specific genome duplication event have been retained. Positive selection has acted on the duplicated paralogs of the Hif-α isoforms in some cyprinid sub-families, pointing to adaptive evolutionary change in the paralogs. Thus, cyprinids are valuable models for exploring the evolutionary significance and physiological impact of the Hif pathway on the hypoxic response. Knockout in zebrafish of either paralog of Hif-1α greatly reduces hypoxia tolerance, indicating the importance of both paralogs to the hypoxic response. Here, with an emphasis on the cardiorespiratory system, we focus on the role of Hif-1α in the hypoxic ventilatory response and the regulation of cardiac function. We explore the effects of the duration of the hypoxic exposure (acute, sustained or intermittent) on the impact of Hif-1α on cardiorespiratory function and compare relevant data with those from mammalian systems.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".