MétaCan
Menu
Back to cohort
Record W4296325199 · doi:10.1152/ajpcell.00356.2022

Chronic obstructive pulmonary disease and the modulation of CFTR by acute exposure to cigarette smoke

2022· review· en· W4296325199 on OpenAlexafffund
John W. Hanrahan, Asmahan Abu‐Arish, Francis Wong, Mark J. Turner, Graeme W. Carlile, David Y. Thomas, André M. Cantin

Bibliographic record

VenueAmerican Journal of Physiology-Cell Physiology · 2022
Typereview
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsHealth CanadaMcGill UniversityUniversité de SherbrookeUniversity of SaskatchewanMcGill University Health Centre
FundersCanadian Institutes of Health ResearchGovernment of CanadaCystic Fibrosis Foundation
KeywordsCOPDMedicineCystic fibrosisInflammationPathogenesisCigarette smokeMucusLungDiseasePulmonary diseaseCigarette smokingPulmonary function testingImmunologyPathologyInternal medicineBiologyEnvironmental health

Abstract

fetched live from OpenAlex

Chronic obstructive pulmonary disease (COPD) is a leading cause of death and cigarette smoke is the main risk factor. Detecting its earliest stages and preventing a decline in lung function are key goals. The pathogenesis of COPD is complex but has some similarities to cystic fibrosis (CF), a disease caused by mutations in the cftr gene. CF leads to chronic inflammation, abnormal mucus, and cycles of infection. Cigarette smoke exposure also causes CFTR dysfunction, and it is probably not a coincidence that inflammation, mucus obstruction, and infections are also characteristics of COPD, although the exacerbations can be quite different. We review here the acute effects of cigarette smoke on CFTR function and its potential role in COPD. Understanding CFTR regulation by cigarette smoke may identify novel drug targets and facilitate the development of therapeutics that reduce the progression and severity of COPD.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.003

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 head0.311
Teacher spread0.296 · 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 designNot applicable
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

Citations13
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueAmerican Journal of Physiology-Cell PhysiologySame topicCystic Fibrosis Research AdvancesFrench-language works237,207