Temperature dependence of haemoglobin–oxygen affinity in heterothermic vertebrates: mechanisms and biological significance
Bibliographic record
Abstract
As demonstrated by August Krogh et al. a century ago, the oxygen-binding reaction of vertebrate haemoglobin is cooperative (described by sigmoid O(2) equilibrium curves) and modulated by CO(2) and protons (lowered pH) that - in conjunction with later discovered allosteric effectors (chloride, lactate and organic phosphate anions) - enhance O(2) unloading from blood in relatively acidic and oxygen-poor tissues. Based on the exothermic nature of the oxygenation of the haem groups, haemoglobin-O(2) affinity also decreases with rising temperature. This thermal sensitivity favours oxygen unloading in warm working muscles, but may become detrimental in regionally heterothermic animals, for example in cold-tolerant birds and mammals and warm-bodied fish, where it may perturb the balance between O(2) unloading and O(2) requirement in organs with substantially different temperatures than at the respiratory organs and thus commonly is reduced or obliterated. Given that the oxygenation of haemoglobin is linked with the endothermic release of allosteric effectors, increased effector interaction is an effective strategy that is widely exploited to achieve adaptive reductions in the temperature dependence of blood-O(2) affinity. The molecular mechanisms implicated in heterothermic vertebrates from different taxonomic groups reveal remarkable variability, both as regards the effectors implicated (protons in tunas, organic phosphates in sharks and billfish, chloride ions in ruminants and chloride and phosphate anions in the extinct woolly mammoth, etc.) and binding sites for the same effectors, indicating multiple evolutionary origins, but convergent physiological functionality (reductions in temperature dependence of O(2) -binding affinity that safeguard tissue O(2) supply).
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".