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Record W2161369215 · doi:10.1083/jcb.200606003

Mechanism of transport of IFT particles in <i>C. elegans</i> cilia by the concerted action of kinesin-II and OSM-3 motors

2006· article· en· W2161369215 on OpenAlexaff
Xiaoyu Pan, Guangshuo Ou, Gul Civelekoglu‐Scholey, Oliver E. Blacque, Nicholas Endres, Tao Li, Alex Mogilner, Michel R. Leroux, Ronald D. Vale, Jonathan M. Scholey

Bibliographic record

VenueThe Journal of Cell Biology · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and Kidney Cyst Diseases
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsIntraflagellar transportCiliumKinesinBiologyMicrotubuleCaenorhabditis elegansCell biologyMotor proteinMolecular motorFlagellumHeterotrimeric G proteinBardet–Biedl syndromeG proteinGeneticsSignal transductionPhenotype

Abstract

fetched live from OpenAlex

The assembly and function of cilia on Caenorhabditis elegans neurons depends on the action of two kinesin-2 motors, heterotrimeric kinesin-II and homodimeric OSM-3-kinesin, which cooperate to move the same intraflagellar transport (IFT) particles along microtubule (MT) doublets. Using competitive in vitro MT gliding assays, we show that purified kinesin-II and OSM-3 cooperate to generate movement similar to that seen along the cilium in the absence of any additional regulatory factors. Quantitative modeling suggests that this could reflect an alternating action mechanism, in which the motors take turns to move along MTs, or a mechanical competition, in which the motors function in a concerted fashion to move along MTs with the slow motor exerting drag on the fast motor and vice versa. In vivo transport assays performed in Bardet-Biedl syndrome (BBS) protein and IFT motor mutants favor a mechanical competition model for motor coordination in which the IFT motors exert a BBS protein-dependent tension on IFT particles, which controls the IFT pathway that builds the cilium foundation.

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 score0.006
Threshold uncertainty score0.178

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 head0.006
GPT teacher head0.216
Teacher spread0.209 · 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

Citations201
Published2006
Admission routes1
Has abstractyes

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