Respiratory Adaptations to High‐Altitude Hypoxia in Deer Mice ( <i>Peromyscus maniculatus</i> )
Bibliographic record
Abstract
The unremitting hypoxia at high altitudes challenges small endotherms to extract enough oxygen from the environment to survive, exercise, and generate enough heat for thermoregulation. We compared the control of breathing and pulmonary gas‐exchange between highland and lowland populations of deer mice to determine the physiological specializations important for living in high‐altitude hypoxia. Mice were acclimated to normoxia or hypobaric hypoxia (simulating hypoxia at ~4300 m elevation) for 4–5 months. The hypoxic ventilatory response (HVR) was measured using whole‐body and restraint plethysmography in response to step‐wise decreases in inspired O 2 fraction. Hypoxia acclimation enhanced the HVR in lowlanders, such that total ventilation and arterial saturation were higher across a range of inspired O 2 . Hypoxia acclimation also made breathing pattern more effective in lowlanders, as reflected by higher tidal volumes and lower breathing frequencies at a given total ventilation, and it allowed lowlanders to maintain higher heart rates in deep hypoxia. In contrast, hypoxia acclimation had no effect on these traits in highlanders, who exhibited a fixed HVR and breathing pattern that was similar to hypoxia‐acclimated lowlanders, and highlanders also maintained higher arterial saturations in hypoxia than lowlanders. In contrast, hypoxia acclimation similarly enhanced the hypercapnic ventilatory response (measured in normoxia during step‐wise increases in inspired CO 2 , from 0% to 6%) in both populations. Therefore, ventilatory acclimatization to hypoxia is absent in highland deer mice, which have a fixed HVR that is effective for gas exchange, through a mechanism that appears independent of evolved changes in the plasticity of CO 2 chemosensitivity. Support or Funding Information Supported by NSERC of Canada.
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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 | 0.001 |
| 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".