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Record W4381547125 · doi:10.7554/elife.85414.sa2

Author response: Evolution of an extreme hemoglobin phenotype contributed to the sub-Arctic specialization of extinct Steller’s sea cows

2023· peer-review· en· W4381547125 on OpenAlexaff
Anthony V. Signore, Phillip R. Morrison, Colin J. Brauner, Angela Fago, Roy E. Weber, Kevin L. Campbell

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldNeuroscience
TopicNeuroscience of respiration and sleep
Canadian institutionsUniversity of British ColumbiaUniversity of Manitoba
Fundersnot available
KeywordsPhenotypeBiologyAllosteric regulationEvolutionary biologyZoologyGeographyGeneGenetics

Abstract

fetched live from OpenAlex

In 1741, shipwrecked naturalist Georg Wilhelm Steller made detailed observations of large marine mammals grazing on seaweed in the shallow waters surrounding a remote island in the North Pacific Ocean. Within thirty years, these ‘Steller’s sea cows’ had been hunted to extinction. Unlike their remaining tropical relatives – dugongs and manatees – Steller’s sea cows were specialized to cold, sub-Arctic environments. Measuring up to 10 meters long, they were much larger than other sea cow species. This, along with having very thick skin, helped them to reduce heat loss. Previous work showed that the hemoglobin protein – which binds to and carries oxygen around mammalian bodies – of Steller’s sea cows had a decreased affinity for oxygen, resulting in greater delivery of oxygen to organs and tissues. It was thought that this could be an adaptation to fuel heightened metabolic heat production in cold conditions. Studies of ancient DNA also identified the substitution of a single building block in the Steller’s sea cow hemoglobin protein that is not present in other mammals and was suspected to underlie this modification. To determine how this unique substitution affects Steller’s sea cow hemoglobin function – and whether it contributed to their ability to live in cold environments – Signore et al. generated hemoglobin proteins of Steller’s sea cows, dugongs and Florida manatees. Testing their biochemical properties showed that this single exchange profoundly alters multiple aspects of how the Steller’s sea cow hemoglobin works. Alongside reducing hemoglobin’s oxygen affinity, the Steller’s sea cow substitution also makes the protein more soluble, potentially increasing the level of hemoglobin within red blood cells. Additionally, it eliminates hemoglobin sensitivity to a molecule involved in oxygen binding – known as DPG – saving energy by no longer requiring production of this molecule. Furthermore, the same substitution makes hemoglobin less sensitive to changes in temperature, which would have helped to safeguard the delivery of oxygen to cool limbs and other extremities, reducing costly heat loss. Together, these changes in hemoglobin would have helped the Steller’s sea cow to more efficiently transport oxygen around the body. Importantly, generating and testing Steller’s sea cow pre-natal hemoglobins suggested this substitution may have also helped to enhance the fetal growth rate of these immense marine mammals by improving gas exchange between the mother and fetus. Signore et al. have revealed how a mutated form of hemoglobin allowed an extinct mammal to adapt to an extreme environment. Similar methods could be used to understand the physiological attributes of other extinct animals. In the future, this increased understanding of hemoglobin mutations could aid the development of human hemoglobin substitutes for therapeutic uses.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.104
Threshold uncertainty score0.348

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.1040.028

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.

Opus teacher head0.109
GPT teacher head0.346
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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