Effect of Atorvastatin on PM <sub>10</sub> -induced Cytokine Production by Human Alveolar Macrophages and Bronchial Epithelial Cells
Bibliographic record
Abstract
Exposure to ambient air pollution particles (PM(10)) has been associated with increased cardiovascular morbidity and mortality. Inhaled pollutants induce a pulmonary and systemic inflammatory response that is thought to exacerbate cardiovascular disease. The 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors (statins) have been shown to have anti-inflammatory effects that could contribute to their beneficial effect in cardiovascular disease. The aim of this study is to determine the effects of statins on PM(10)-induced cytokine production in human bronchial epithelial cells (HBECs) and alveolar macrophages (AMs). Primary HBECs and AMs are obtained from resected human lung. Cells are pretreated with different concentrations of atorvastatin for 24 hours and then exposed to 100 microg/mL urban air pollution particles (EHC-93). Cytokine levels (interleukin-1beta, interleukin-8, granulocyte-macrophage colony-stimulating factor, interleukin-6, and tumor necrosis factor-alpha) are measured at messenger RNA and protein levels using real-time polymerase chain reaction and bead-based multiplex immunoassay, respectively. PM(10) exposure increases production of these cytokines by both cell types. Atorvastatin attenuates PM(10)-induced messenger RNA expression and cytokine production by AMs but not by HBECs. It is concluded that statins can modulate the PM(10)-induced inflammatory response in the lung by reducing mediator production by AMs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".