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Record W3016981607 · doi:10.1128/mbio.00657-20

Conductance Mechanisms of Rapidly Desensitizing Cation Channelrhodopsins from Cryptophyte Algae

2020· article· en· W3016981607 on OpenAlexafffund
Oleg A. Sineshchekov, Elena G. Govorunova, Hai Li, Yumei Wang, Michael Melkonian, Gane Ka‐Shu Wong, Leonid S. Brown, John L. Spudich

Bibliographic record

VenuemBio · 2020
Typearticle
Languageen
FieldNeuroscience
TopicPhotoreceptor and optogenetics research
Canadian institutionsUniversity of GuelphUniversity of Alberta
FundersNational Institutes of HealthNational Institute of General Medical SciencesNatural Sciences and Engineering Research Council of CanadaGovernment of CanadaWelch Foundation
KeywordsPhototaxisBacteriorhodopsinRhodopsinChannelrhodopsinOptogeneticsBiologyProton transportChemistryBiophysicsBotanyBiochemistryMembraneNeuroscienceRetinal

Abstract

fetched live from OpenAlex

Cation channelrhodopsins, light-gated channels from flagellate green algae, are extensively used as optogenetic photoactivators of neurons in research and recently have progressed to clinical trials for vision restoration. However, the molecular mechanisms of their photoactivation remain poorly understood. We recently identified cryptophyte cation channelrhodopsins, structurally different from those of green algae, which have separately evolved to converge on light-gated cation conductance. This study reveals diversity within this new protein family and describes a subclade with unusually rapid desensitization that results in short transient photocurrents in continuous light. Such transient currents have not been observed in the green algae channelrhodopsins and are potentially useful in optogenetic protocols. Kinetic UV-visible (UV-vis) spectroscopy and photoelectrophysiology reveal that the desensitization is caused by rapid accumulation of a nonconductive photointermediate in the photochemical reaction cycle. The absorption maximum of the intermediate is 330 nm, the shortest wavelength reported in any rhodopsin, indicating a novel chromophore structure.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.012
Threshold uncertainty score0.427

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.103
GPT teacher head0.295
Teacher spread0.192 · 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

Citations35
Published2020
Admission routes2
Has abstractyes

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