Endotoxin in concentrated coarse and fine ambient particles induces acute systemic inflammation in controlled human exposures
Bibliographic record
Abstract
BACKGROUND: Knowledge of the inhalable particulate matter components responsible for health effects is important for developing targeted regulation. OBJECTIVES: In a double-blind randomised cross-over trial of controlled human exposures to concentrated ambient particles (CAPs) and their endotoxin and (1→3)-β-D-glucan components, we evaluated acute inflammatory responses. METHODS: 35 healthy adults were exposed to five 130-min exposures at rest: (1) fine CAPs (~250 µg/m(3)); (2) coarse CAPs (200 µg/m(3)); (3) second coarse CAPs (~200 µg/m(3)); (4) filtered air; and (5) medical air. Induced sputum cell counts were measured at screening and 24 h postexposure. Venous blood total leucocytes, neutrophils, interleukin-6 and high-sensitivity C reactive protein (CRP) were measured pre-exposure, 3 and 24 h postexposure. RESULTS: Relative to filtered air, an increase in blood leucocytes 24 h (but not 3 h) postexposure was significantly associated with coarse (estimate=0.44×10(9) cells/L (95% CI 0.01 to 0.88); n=132) and fine CAPs (0.68×10(9) cells /L (95% CI 0.19 to 1.17); n=132), but not medical air. Similar associations were found with neutrophil responses. An interquartile increase in endotoxin (5.4 ng/m(3)) was significantly associated with increased blood leucocytes 3 h postexposure (0.27×10(9) cells/L (95% CI 0.03 to 0.51); n=98) and 24 h postexposure (0.37×10(9) cells/L (95% CI 0.12 to 0.63); n=98). This endotoxin effect did not differ by particle size. There were no associations with glucan concentrations or interleukin-6, CRP or sputum responses. CONCLUSIONS: In healthy adults, controlled coarse and fine ambient particle exposures independently induced acute systemic inflammatory responses. Endotoxin contributes to the inflammatory role of particle air pollution.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".