Activation of Human Epithelial Lung A549 Cells by the Pollutant Sodium Sulfite: Enhancement of Neutrophil Adhesion
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".