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Record W1976916554 · doi:10.1074/jbc.m708089200

Molecular Proximity of Cystic Fibrosis Transmembrane Conductance Regulator and Epithelial Sodium Channel Assessed by Fluorescence Resonance Energy Transfer

2007· article· en· W1976916554 on OpenAlexaff
Bakhrom K. Berdiev, Estelle Cormet‐Boyaka, Albert Tousson, Yawar J. Qadri, Henderika M.J. Oosterveld‐Hut, Jeong S. Hong, Patricia A. Gonzales, Cathy M. Fuller, Eric J. Sorscher, Gergely L. Lukács, Dale Benos

Bibliographic record

VenueJournal of Biological Chemistry · 2007
Typearticle
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsUniversity of TorontoHospital for Sick ChildrenSickKids Foundation
FundersNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsCystic fibrosis transmembrane conductance regulatorFörster resonance energy transferEpithelial sodium channelCystic fibrosisChemistrySodium channelTransmembrane proteinBiophysicsIon channelConductanceFluorescenceSodiumBiologyBiochemistryGeneticsPhysics

Abstract

fetched live from OpenAlex

We present the evidence for a direct physical association of cystic fibrosis transmembrane conductance regulator (CFTR) and epithelial sodium channel (ENaC), two major ion channels implicated in the pathophysiology of cystic fibrosis, a devastating inherited disease. We employed fluorescence resonance energy transfer, a distance-dependent imaging technique with capability to detect molecular complexes with near angstrom resolution, to estimate the proximity of CFTR and ENaC, an essential variable for possible physical interaction to occur. Fluorescence resonance energy transfer studies were complemented with a classic biochemical approach: coimmunoprecipitation. Our results place CFTR and ENaC within reach of each other, suggestive of a direct interaction between these two proteins.

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)0.001
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.267
Teacher spread0.252 · 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

Citations46
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Biological ChemistrySame topicCystic Fibrosis Research AdvancesFrench-language works237,207