Particle‐induced pulmonary acute phase response may be the causal link between particle inhalation and cardiovascular disease
Bibliographic record
Abstract
Inhalation of ambient and workplace particulate air pollution is associated with increased risk of cardiovascular disease. One proposed mechanism for this association is that pulmonary inflammation induces a hepatic acute phase response, which increases risk of cardiovascular disease. Induction of the acute phase response is intimately linked to risk of cardiovascular disease as shown in both epidemiological and animal studies. Indeed, blood levels of acute phase proteins, such as C-reactive protein and serum amyloid A, are independent predictors of risk of cardiovascular disease in prospective epidemiological studies. In this review, we present and review emerging evidence that inhalation of particles (e.g., air diesel exhaust particles and nanoparticles) induces a pulmonary acute phase response, and propose that this induction constitutes the causal link between particle inhalation and risk of cardiovascular disease. Increased levels of acute phase mRNA and proteins in lung tissues, bronchoalveolar lavage fluid and plasma clearly indicate pulmonary acute phase response following pulmonary deposition of different kinds of particles including diesel exhaust particles, nanoparticles, and carbon nanotubes. The pulmonary acute phase response is dose-dependent and long lasting. Conversely, the hepatic acute phase response is reduced relative to lung or entirely absent. We also provide evidence that pulmonary inflammation, as measured by neutrophil influx, is a predictor of the acute phase response and that the total surface area of deposited particles correlates with the pulmonary acute phase response. We discuss the implications of these findings in relation to occupational exposure to nanoparticles.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".