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Record W1973733377 · doi:10.1073/pnas.0706618104

Loss of Bardet–Biedl syndrome proteins causes defects in peripheral sensory innervation and function

2007· article· en· W1973733377 on OpenAlexaff
Perciliz L. Tan, Travis P. Barr, Peter N. Inglis, Norimasa Mitsuma, Susan M. Huang, Miguel A. García-González, Brian A. Bradley, Stephanie Coforio, Phillip J. Albrecht, Terry Watnick, Gregory G. Germino, Philip L. Beales, Michael J. Caterina, Michel R. Leroux, Frank L. Rice, Nicholas Katsanis

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and Kidney Cyst Diseases
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMechanosensationBardet–Biedl syndromeCiliumCiliopathiesBiologySensory systemPhenotypeCell biologyTRPV4NeuroscienceCaenorhabditis elegansTRPV1Intraflagellar transportTransient receptor potential channelMutantGeneticsGeneIon channel

Abstract

fetched live from OpenAlex

Reception and interpretation of environmental stimuli is critical for the survival of all organisms. Here, we show that the ablation of BBS1 and BBS4, two genes mutated in Bardet-Biedl syndrome and that encode proteins that localize near the centrioles of sensory neurons, leads to alterations of s.c. sensory innervation and trafficking of the thermosensory channel TRPV1 and the mechanosensory channel STOML3, with concomitant defects in peripheral thermosensation and mechanosensation. The thermosensory phenotype is recapitulated in Caenorhabditis elegans, because BBS mutants manifest deficient thermosensory responses at both physiological and nociceptive temperatures and defective trafficking of OSM-9, a polymodal sensory channel protein and a functional homolog of TRPV1 or TRPV4. Our findings suggest a hitherto unrecognized, but essential, role for mammalian basal body proteins in the acquisition of mechano- and thermosensory stimuli and highlight potentially clinical features of ciliopathies in humans.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.418
Threshold uncertainty score0.176

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.020
GPT teacher head0.270
Teacher spread0.250 · 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

Citations78
Published2007
Admission routes1
Has abstractyes

Explore more

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