MétaCan
Menu
Back to cohort
Record W3201165649 · doi:10.1101/2021.09.17.460684

Kalium rhodopsins: Natural light-gated potassium channels

2021· preprint· en· W3201165649 on OpenAlexafffund
Elena G. Govorunova, Yueyang Gou, Oleg A. Sineshchekov, Hai Li, Yumei Wang, Leonid S. Brown, Mingshan Xue, John L. Spudich

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2021
Typepreprint
Languageen
FieldNeuroscience
TopicPhotoreceptor and optogenetics research
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaNational Institutes of Health
KeywordsOptogeneticsChannelrhodopsinPotassium channelBiophysicsPotassiumChemistryCell permeabilityNeuroscienceBiologyBiochemistry

Abstract

fetched live from OpenAlex

Abstract We report a family of K + channels, kalium channelrhodopsins (KCRs) from a fungus-like protist. Previously known potassium channels, widespread and mainly ligand- or voltage-gated, share a conserved pore-forming domain and K + -selectivity filter. KCRs differ in that they are light-gated and they have independently evolved an alternative K + selectivity mechanism. The KCRs are potent, highly selective of K + over Na + , and open in less than 1 millisecond following photoactivation. Their permeability ratio P K /P Na of ∼ 20 make KCRs powerful hyperpolarizing tools that suppress excitable cell firing upon illumination, demonstrated here in mouse cortical neurons. KCRs enable specific optogenetic photocontrol of K + gradients promising for the study and potential treatment of potassium channelopathies such as epilepsy, Parkinson’s disease, and long-QT syndrome and other cardiac arrhythmias. One-Sentence Summary Potassium-selective channelrhodopsins long-sought for optogenetic research and therapy of neurological and cardiac diseases.

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.031
GPT teacher head0.266
Teacher spread0.235 · 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

Citations10
Published2021
Admission routes2
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicPhotoreceptor and optogenetics researchFrench-language works237,207