The adaptive benefit of evolved increases in hemoglobin-O2 affinity is contingent on tissue O2 diffusing capacity in high-altitude deer mice
Bibliographic record
Abstract
Abstract Background Complex organismal traits are often the result of multiple interacting genes and sub-organismal phenotypes, but how these interactions shape the evolutionary trajectories of adaptive traits is poorly understood. We examined how functional interactions between cardiorespiratory traits contribute to adaptive increases in the capacity for aerobic thermogenesis (maximal O 2 consumption, V̇ O 2 max, during acute cold exposure) in high-altitude deer mice ( Peromyscus maniculatus ). We crossed highland and lowland deer mice to produce F 2 inter-population hybrids, which expressed genetically based variation in hemoglobin (Hb) O 2 affinity on a mixed genetic background. We then combined physiological experiments and mathematical modeling of the O 2 transport pathway to examine the links between cardiorespiratory traits and V̇ O 2 max. Results Physiological experiments revealed that increases in Hb-O 2 affinity of red blood cells improved blood oxygenation in hypoxia but were not associated with an enhancement in V̇ O 2 max. Sensitivity analyses performed using mathematical modeling showed that the influence of Hb-O 2 affinity on V̇ O 2 max in hypoxia was contingent on the capacity for O 2 diffusion in active tissues. Conclusions These results suggest that increases in Hb-O 2 affinity would only have adaptive value in hypoxic conditions if concurrent with or preceded by increases in tissue O 2 diffusing capacity. In high-altitude deer mice, the adaptive benefit of increasing Hb-O 2 affinity is contingent on the capacity to extract O 2 from the blood, which helps resolve controversies about the general role of hemoglobin function in hypoxia tolerance.
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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".