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Photoreceptor IFT Complexes Containing Chaperones, Guanylyl Cyclase 1 and Rhodopsin

2009· article· en· W2107772204 on OpenAlexfundno aff
Reshma Bhowmick, Mei Li, Jun Sun, Sheila A. Baker, Christine Insinna, Joseph C. Besharse

Bibliographic record

VenueTraffic · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and Kidney Cyst Diseases
Canadian institutionsnot available
FundersNational Eye InstituteNational Institutes of HealthUniversity of British Columbia
KeywordsIntraflagellar transportCiliumCell biologyBiologyRhodopsinKinesinGreen fluorescent proteinTransport proteinMembrane proteinFlagellumBiochemistryGeneMembraneMicrotubule

Abstract

fetched live from OpenAlex

Intraflagellar transport (IFT) provides a mechanism for the transport of cilium-specific proteins, but the mechanisms for linkage of cargo and IFT proteins have not been identified. Using the sensory outer segments (OS) of photoreceptors, which are derived from sensory cilia, we have identified IFT-cargo complexes containing IFT proteins, kinesin 2 family proteins, two photoreceptor-specific membrane proteins, guanylyl cyclase 1 (GC1, Gucy2e) and rhodopsin (RHO), and the chaperones, mammalian relative of DNAJ, DnajB6 (MRJ), and HSC70 (Hspa8). Analysis of these complexes leads to a model in which MRJ through its binding to IFT88 and GC1 plays a critical role in formation or stabilization of the IFT-cargo complexes. Consistent with the function of MRJ in the activation of HSC70 ATPase activity, Mg-ATP enhances the co-IP of GC1, RHO, and MRJ with IFT proteins. Furthermore, RNAi knockdown of MRJ in IMCD3 cells expressing GC1-green fluorescent protein (GFP) reduces cilium membrane targeting of GC1-GFP without apparent effect on cilium elongation.

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 score0.002
Threshold uncertainty score0.006

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)0.0010.000

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 head0.009
GPT teacher head0.240
Teacher spread0.230 · 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

Citations71
Published2009
Admission routes1
Has abstractyes

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