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Record W2066171223 · doi:10.1080/01902140802490723

PROTEASE-ACTIVATED RECEPTOR (PAR)<sub>1</sub>ALTERS BIOELECTRIC PROPERTIES OF DISTAL LUNG EPITHELIA WITHOUT COMPROMISING BARRIER FUNCTION

2009· article· en· W2066171223 on OpenAlexaff
Theo J. Moraes, Bijan Rafii, Frank Niessen, Tomoko Suzuki, Raiza Martin, Éric Vachon, Wolfgang F. Vogel, Wolfram Ruf, Hugh OʼBrodovich, Gregory P. Downey

Bibliographic record

VenueExperimental Lung Research · 2009
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsToronto General HospitalUniversity Health NetworkHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsParacellular transportBarrier functionProteaseCell biologyReceptorProtease-activated receptorProteasesProtease-activated receptor 2LungChemistryTight junctionBiophysicsBiologyPermeability (electromagnetism)BiochemistryImmunologyInternal medicineMembraneMedicineEnzymeEnzyme-linked receptor

Abstract

fetched live from OpenAlex

Proteinases contribute to the pathogenesis of various lung diseases, partly through activating cell surface receptors by limited proteolytic cleavage. The authors provide evidence that in primary cultures of distal lung epithelia, basolateral protease-activated receptor 1 activation rapidly reduces transepithelial resistance but does not alter paracellular permeability to small uncharged solutes. Changes in transepithelial resistance were partially blocked by ion transport inhibitors and were completely blocked by placing cells in low chloride buffer. In vivo studies did not reveal enhanced lung permeability in response to pulmonary or intravenous administration of protease-activated receptor 1 activators. This information is relevant as strategies to inhibit protease-activated receptor 1 signaling are considered in order to preserve lung epithelial barrier function.

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)0.000
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 score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.067
GPT teacher head0.389
Teacher spread0.322 · 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

Citations3
Published2009
Admission routes1
Has abstractyes

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