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Record W2061612454 · doi:10.1177/1753465810371107

Emerging therapies in cystic fibrosis

2010· review· en· W2061612454 on OpenAlexfundno aff
Paula Anderson

Bibliographic record

VenueTherapeutic Advances in Respiratory Disease · 2010
Typereview
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsnot available
FundersBayer CanadaGilead Sciences
KeywordsCystic fibrosisMedicineCystic fibrosis transmembrane conductance regulatorClinical trialLife expectancyDiseaseTargeted therapyImmunologyIntensive care medicineBioinformaticsInternal medicinePopulation

Abstract

fetched live from OpenAlex

The life expectancy of people with cystic fibrosis (CF), a lethal inherited disease, has been greatly extended by advances in therapy. Currently, there are a number of potential drugs for treatment of CF lung disease in clinical trials. These therapies are targeted at all points in the pathogenesis of lung disease, from gene transfer to drugs that treat mucus, infection and inflammation in the airways. An exciting development is that of modulation of the abnormal protein that causes CF, the cystic fibrosis transmembrane conductance regulator (CFTR), where drugs are targeted at specific defects in CFTR transcription, processing or functioning. Inhaled therapies are being developed to augment airway surface liquid height, either by modulating the abnormal ion channel function in the airway epithelial cell or by rehydrating with osmotic agents. Anti-inflammatory therapy is also of great interest in CF and there are several candidate drugs in clinical trials. A number of antibacterial agents formulated for inhalation are at various stages of study or newly approved, which should improve options for chronic management of airway infection. Hopefully, many of these potential therapies will come to market and will further extend the life expectancy of people with CF.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.978
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.042
GPT teacher head0.407
Teacher spread0.365 · 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 designOther design
Domainnot available
GenreReview

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

Citations43
Published2010
Admission routes1
Has abstractyes

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