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CFTR Folding Consortium: Methods Available for Studies of CFTR Folding and Correction

2011· article· en· W130424176 on OpenAlexaff
Kathryn W. Peters, Tsukasa Okiyoneda, William E. Balch, Ineke Braakman, Jeffrey L. Brodsky, William B. Guggino, Christopher M. Penland, Harvey B. Pollard, Eric J. Sorscher, William R. Skach, Philip Thomas, Gergely L. Lukács, Raymond A. Frizzell

Bibliographic record

VenueMethods in molecular biology · 2011
Typearticle
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsMcGill University
FundersNational Institute of General Medical SciencesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Heart, Lung, and Blood Institute
KeywordsCystic fibrosisProtein engineeringMutantProtein foldingComputational biologyChemistryCell biologyBiologyBiochemistryEnzymeGeneticsGene

Abstract

fetched live from OpenAlex

The CFTR Folding Consortium (CFC) was formed in 2004 under the auspices of the Cystic Fibrosis Foundation and its drug discovery and development affiliate, CFF Therapeutics. A primary goal of the CFC is the development and distribution of reagents and assay methods designed to better understand the mechanistic basis of mutant CFTR misfolding and to identify targets whose manipulation may correct CFTR folding defects. As such, reagents available from the CFC primarily target wild-type CFTR NBD1 and its common variant, F508del, and they include antibodies, cell lines, constructs, and proteins. These reagents are summarized here, and two protocols are described for the detection of cell surface CFTR: (a) an assay of the density of expressed HA-tagged CFTR by ELISA and (b) the generation and use of an antibody to CFTR's first extracellular loop for the detection of endogenous CFTR. Finally, we highlight a systematic collection of assays, the CFC Roadmap, which is being used to assess the cellular locus and mechanism of mutant CFTR correction. The Roadmap queries CFTR structure-function relations at levels ranging from purified protein to well-differentiated human airway primary cultures.

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)0.004
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.103
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.152
GPT teacher head0.517
Teacher spread0.366 · 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.

Study designBench or experimental
Domainnot available
GenreMethods

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

Citations35
Published2011
Admission routes1
Has abstractyes

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