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Record W3186288373 · doi:10.1128/mbio.01656-21

Cation and Anion Channelrhodopsins: Sequence Motifs and Taxonomic Distribution

2021· article· en· W3186288373 on OpenAlexafffund
Elena G. Govorunova, Oleg A. Sineshchekov, Hai Li, Yumei Wang, Leonid S. Brown, Alyssa Palmateer, Michael Melkonian, Shifeng Cheng, Eric Carpenter, Jordan Patterson, Gane Ka‐Shu Wong, John L. Spudich

Bibliographic record

VenuemBio · 2021
Typearticle
Languageen
FieldNeuroscience
TopicPhotoreceptor and optogenetics research
Canadian institutionsUniversity of AlbertaUniversity of Guelph
FundersNational Institute of Neurological Disorders and StrokeNational Institute of General Medical SciencesAgricultural Science and Technology Innovation ProgramNatural Sciences and Engineering Research Council of CanadaOffice of ScienceNational Institutes of HealthGovernment of CanadaUniversities Space Research AssociationJoint Genome InstituteWelch FoundationU.S. Department of Energy
KeywordsChannelrhodopsinChlamydomonasChlamydomonas reinhardtiiMetagenomicsBiologyOptogeneticsTransmembrane domainContext (archaeology)RhodopsinComputational biologyGeneticsGeneBiochemistryRetinal

Abstract

fetched live from OpenAlex

Channelrhodopsins are widely used in neuroscience and cardiology as research tools and are considered prospective therapeutics, but their natural diversity and mechanisms remain poorly characterized. Genomic and metagenomic sequencing projects are producing an ever-increasing wealth of data, whereas biophysical characterization of the encoded proteins lags behind. In this study, we used manual and automated patch clamp recording of representative members of four channelrhodopsin families, including a family in dinoflagellates that we report in this study. Our results contribute to a better understanding of molecular determinants of ionic selectivity, photocurrent desensitization, and spectral tuning in channelrhodopsins.

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 score0.014
Threshold uncertainty score0.241

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 head0.098
GPT teacher head0.316
Teacher spread0.218 · 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

Citations38
Published2021
Admission routes2
Has abstractyes

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