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Record W2146165562 · doi:10.1093/toxsci/69.1.210

Activation of Human Epithelial Lung A549 Cells by the Pollutant Sodium Sulfite: Enhancement of Neutrophil Adhesion

2002· article· en· W2146165562 on OpenAlexafffund
Martin Pelletier

Bibliographic record

VenueToxicological Sciences · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsInstitut National de la Recherche Scientifique
FundersCanadian Lung AssociationArmand-Frappier Foundation
KeywordsA549 cellChemistrySodium sulfiteCell adhesion moleculeIntercellular Adhesion Molecule-1Cell adhesionCell biologyAdhesionApoptosisBiochemistryBiologyCellSodium

Abstract

fetched live from OpenAlex

Air pollutant exposure may induce deterioration of respiratory health. Concentrations of air particles, ozone, nitrogen dioxide, sulfur dioxide, and sulfate are among the players involved in the initiation and/or exacerbation of lung diseases. We have previously documented that the pollutant sodium sulfite (Na(2)SO(3)) is a human neutrophil agonist. To date, there is no evidence in the literature that Na(2)SO(3) can activate epithelial lung cells. In the present study, we found that Na(2)SO(3) (0.01-10 mM) induces tyrosine phosphorylation events and interleukin-8 production in human epithelial lung A549 cells. In addition, we found that Na(2)SO(3) did not promote A549 cell apoptosis as assessed by the degradation of the cytoskeletal gelsolin protein and by FITC-annexin-V binding. Human neutrophil adhesion to Na(2)SO(3)-induced A549 cells was increased when compared with untreated A549 cells. As assessed by flow cytometry, cell surface expression of intercellular adhesion molecule (ICAM)-1, ICAM-3, and vascular cell adhesion molecule-1 (VCAM-1) on A549 cells was not affected by Na(2)SO(3). We conclude that Na(2)SO(3) can activate A549 cells. In addition, we conclude that neutrophil adhesion to Na(2)SO(3)-induced A549 cells is increased via an ICAM-1-, ICAM-3-, and VCAM-1-independent mechanism.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.021
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.067
GPT teacher head0.314
Teacher spread0.247 · 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
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

Citations33
Published2002
Admission routes2
Has abstractyes

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