Interleukin-8: novel roles in human airway smooth muscle cell contraction and migration
Bibliographic record
Abstract
In patients with cystic fibrosis (CF) and asthma, elevated levels of interleukin-8 (IL-8) are found in the airways. IL-8 is a CXC chemokine that is a chemoattractant for neutrophils through CXCR1 and CXCR2 G protein-coupled receptors. We hypothesized that IL-8 acts directly on airway smooth muscle cells (ASMC) in a way that may contribute to the enhanced airway responsiveness and airway remodeling observed in CF and asthma. The aim of this study was to determine whether human ASMC (HASMC) express functional IL-8 receptors (CXCR1 and CXCR2) linked to cell contraction and migration. Experiments were conducted on cells harvested from human lung specimens. Real-time PCR and fluorescence-activated cell sorting analysis showed that HASMC expressed mRNA and protein for both CXCR1 and CXCR2. Intracellular Ca(2+) concentration ([Ca(2+)](i)) increased from 115 to 170 nM in response to IL-8 (100 nM) and decreased after inhibition of phospholipase C (PLC) with U-73122. On blocking the receptors with specific neutralizing antibodies, changes in [Ca(2+)](i) were abrogated. IL-8 also contracted the HASMC, decreasing the length of cells by 15%, and induced a 2.5-fold increase in migration. These results indicate that HASMC constitutively express functional CXCR1 and CXCR2 that mediate IL-8-triggered Ca(2+) release, contraction, and migration. These data suggest a potential role for IL-8 in causing abnormal airway structure and function in asthma and CF.
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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) | 0.001 | 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".