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Record W4328049563 · doi:10.1073/pnas.2220728120

Whale shark rhodopsin adapted to deep-sea lifestyle by a substitution associated with human disease

2023· article· en· W4328049563 on OpenAlexfundno aff
Kazuaki Yamaguchi, Mitsumasa Koyanagi, Keiichi Sato, Akihisa Terakita, Shigehiro Kuraku

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2023
Typearticle
Languageen
FieldNeuroscience
TopicPhotoreceptor and optogenetics research
Canadian institutionsnot available
FundersInstitute of GeneticsRIKENJapan Society for the Promotion of ScienceMinistry of Education, Culture, Sports, Science and Technology
KeywordsRhodopsinDeep seaPelagic zoneBiologyWhaleAdaptation (eye)EcologyFisheryRetinalBiochemistry

Abstract

fetched live from OpenAlex

Spectral tuning of visual pigments often facilitates adaptation to new environments, and it is intriguing to study the visual ecology of pelagic sharks with secondarily expanded habitats. The whale shark, which dives into the deep sea of nearly 2,000 meters besides near-surface filter feeding, was previously shown to possess the 'blue-shifted' rhodopsin (RHO), which is a signature of deep-sea adaptation. In this study, our spectroscopy of recombinant whale shark RHO mutants revealed that this blue shift is caused dominantly by an unprecedented spectral tuning site 94. In humans, the mutation at the site causes congenital stationary night blindness (CSNB) by reducing the thermal stability of RHO. Similarly, the RHO of deep-diving whale shark has reduced thermal stability, which was experimentally shown to be achieved by site 178 and 94. RHOs having the natural substitution at site 94 are also found in some Antarctic fishes, suggesting that the blue shift by the substitution at the CSNB site associated with the reduction in thermal stability might be allowed in cold-water deep-sea habitats.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.092
GPT teacher head0.355
Teacher spread0.263 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations11
Published2023
Admission routes1
Has abstractyes

Explore more

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