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Record W2140054854 · doi:10.1098/rspb.2013.2950

Repeated functional convergent effects of Na <sub>V</sub> 1.7 on acid insensitivity in hibernating mammals

2013· article· en· W2140054854 on OpenAlexaff
Zhen Liu, Wei Wang, Tongzuo Zhang, Gong‐Hua Li, Kai He, Jing‐Fei Huang, Xuelong Jiang, Robert W. Murphy, Peng Shi

Bibliographic record

VenueProceedings of the Royal Society B Biological Sciences · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsRoyal Ontario Museum
Fundersnot available
KeywordsHibernating myocardiumChemistryBiophysicsBiologyInternal medicineMedicine

Abstract

fetched live from OpenAlex

Hibernating mammals need to be insensitive to acid in order to cope with conditions of high CO2; however, the molecular basis of acid tolerance remains largely unknown. The African naked mole-rat (Heterocephalus glaber) and hibernating mammals share similar environments and physiological features. In the naked mole-rat, acid insensitivity has been shown to be conferred by the functional motif of the sodium ion channel NaV1.7. There is now an opportunity to evaluate acid insensitivity in other taxa. In this study, we tested for functional convergence of NaV1.7 in 71 species of mammals, including 22 species that hibernate. Our analyses revealed a functional convergence of amino acid sequences, which occurred at least six times independently in mammals that hibernate. Evolutionary analyses determined that the convergence results from both parallel and divergent evolution of residues in the functional motif. Our findings not only identify the functional molecules responsible for acid insensitivity in hibernating mammals, but also open new avenues to elucidate the molecular underpinnings of acid insensitivity in mammals.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.019
GPT teacher head0.195
Teacher spread0.176 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations27
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Royal Society B Biological SciencesSame topicBat Biology and Ecology StudiesFrench-language works237,207