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Record W3082580520 · doi:10.1073/pnas.2005981117

RubyACRs, nonalgal anion channelrhodopsins with highly red-shifted absorption

2020· article· en· W3082580520 on OpenAlexafffund
Elena G. Govorunova, Oleg A. Sineshchekov, Hai Li, Yumei Wang, Leonid S. Brown, John L. Spudich

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2020
Typearticle
Languageen
FieldNeuroscience
TopicPhotoreceptor and optogenetics research
Canadian institutionsUniversity of Guelph
FundersNational Institutes of HealthNational Institute of General Medical SciencesNatural Sciences and Engineering Research Council of CanadaGovernment of CanadaWelch Foundation
KeywordsChannelrhodopsinAbsorption (acoustics)IonChemistryBiologyOpticsPhysicsOptogeneticsNeuroscienceOrganic chemistry

Abstract

fetched live from OpenAlex

Significance Our identification and characterization of two anion channelrhodopsins families, one from nonphotosynthetic microorganisms, shows that light-gated anion conductance is more widely spread among eukaryotic lineages than previously thought. The strongly red-shifted absorption spectra of the subset that we designate RubyACRs make them promising candidates for the long-sought inhibitory optogenetic tools producing large passive currents activated by red light, enabling deep tissue penetration. Previously only low-efficiency ion-pumping rhodopsins were available for neural inhibition at similar long wavelengths. The unusual residue composition of the retinal-binding pocket in RubyACRs expands our understanding of color tuning in rhodopsins. Finally, activation of chloride currents by energy transfer from a cytoplasmic fluorescent tag on RubyACRs introduces a potential dimension in molecular engineering of optogenetic tools.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.106
GPT teacher head0.328
Teacher spread0.222 · 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 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

Citations79
Published2020
Admission routes2
Has abstractyes

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