Particulate Matter Induces Translocation of IL-6 from the Lung to the Systemic Circulation
Bibliographic record
Abstract
The biological mechanisms responsible for an association between elevated concentrations of ambient particulate matter (PM) and increased cardiovascular morbidity and mortality remain unclear. Our laboratory showed that exposure to PM induces systemic inflammation that contributes to vascular dysfunction. This study was designed to determine whether the lung is a major source of systemic inflammatory mediators, using IL-6 as a surrogate marker. We also sought to determine the impact on vascular dysfunction after exposure to PM of less than 10 μm in diameter (PM(10)). C57BL/6 mice were intratracheally exposed to a single instillation of PM(10) (10 or 200 μg) or saline. Four hours or 24 hours after exposure, venous and arterial blood samples were simultaneously collected from the right atrium and descending aorta. Concentrations of IL-6 were measured in bronchoalveolar lavage fluid (BALF) and serum samples. Vascular functional responses to acetylcholine (ACh) and phenylephrine were measured in the abdominal aorta. Concentrations of IL-6 in BALF samples were increased at 4 and 24 hours after exposure to PM(10). At baseline, concentrations of IL-6 in venous blood were higher than those in arterial blood. Exposure to PM(10) reversed this arteriovenous gradient, 4 hours after exposure. The relaxation responses of the abdominal aorta to ACh decreased 4 hours after exposure to 200 μg PM(10). In IL-6 knockout mice, the instillation of recombinant IL-6 increased IL-6 concentrations in the blood, and exposure to PM(10) did not cause vascular dysfunction. These results support our hypothesis that exposure to PM(10) increases pulmonary inflammatory mediators that translocate to the circulation, contributing to systemic inflammation, with downstream effects such as vascular dysfunction.
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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 | 0.001 |
| 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".