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Record W4252461758 · doi:10.32920/ryerson.14662083.v1

Synthesis Of Molecular Probes For Cystic Fibrosis Research

2021· preprint· en· W4252461758 on OpenAlexaff
Bashar Alkhouri

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsCystic fibrosis transmembrane conductance regulatorCystic fibrosisMutantMembrane proteinMutationPhosphorylationCell biologyChemistryChloride channelTransmembrane proteinIon channelMutant proteinMembraneBiologyBiochemistryGeneGeneticsReceptor

Abstract

fetched live from OpenAlex

Cystic fibrosis (CF) is caused by mutations in the gene coding for the cystic fibrosis transmembrane conductance regulator (CFTR) protein. In healthy individuals, CFTR acts as a phosphorylation and nucleotide regulated channel which mediates the flux of chloride ions across the membrane of epithelial cells. The most common genetic lesion is deletion of phenylalanine residue 508 (F508del-CFTR). The mutation leads primarily to misfolding of the protein, resulting in degradation of most of the protein before it reaches the cell membrane. Also, any F508del-CFTR in the membrane exhibits reduced ion channel activity. The drug-like small molecule VRT-532 has been shown to improve both the trafficking of F508del-CFTR to the cell membrane, as well as its channel function. The exact nature of the interaction of VRT-532 with mutant CFTR is not fully understood. The goal of this research is to help reveal the nature of interaction between VRT-532 and mutant CFTR protein by synthesizing derivatives useful in biochemical studies. Understanding the molecular basis for this interaction will provide us with a template for the development of therapeutically efficacious compounds.

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)0.001
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: none
Teacher disagreement score0.026
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0260.012

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 head0.055
GPT teacher head0.400
Teacher spread0.345 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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