The effect of acute exposure to coarse particulate matter air pollution in a rural location on circulating endothelial progenitor cells: results from a randomized controlled study
Bibliographic record
Abstract
CONTEXT: Fine particulate matter (PM) air pollution has been associated with alterations in circulating endothelial progenitor cell (EPC) levels, which may be one mechanism whereby exposures promote cardiovascular diseases. However, the impact of coarse PM on EPCs is unknown. OBJECTIVE: We aimed to determine the effect of acute exposure to coarse concentrated ambient particles (CAP) on circulating EPC levels. METHODS: Thirty-two adults (25.9 ± 6.6 years) were exposed to coarse CAP (76.2 ± 51.5 μg m(-3)) in a rural location and filtered air (FA) for 2 h in a randomized double-blind crossover study. Peripheral venous blood was collected 2 and 20 h post-exposures for circulating EPC (n = 21), white blood cell (n = 24) and vascular endothelial growth factor (VEGF) (n = 16-19) levels. The changes between exposures were compared by matched Wilcoxon signed-rank tests. RESULTS: Circulating EPC levels were elevated 2 [108.29 (6.24-249.71) EPC mL(-1); median (25th-75th percentiles), p = 0.052] and 20 h [106.86 (52.91-278.35) EPC mL(-1), p = 0.008] post-CAP exposure compared to the same time points following FA [38.47 (0.00-84.83) and 50.16 (0.00-104.79) EPC mL(-1)]. VEGF and white blood cell (WBC) levels did not differ between exposures. CONCLUSIONS: Brief inhalation of coarse PM from a rural location elicited an increase in EPCs that persisted for at least 20 h. The underlying mechanism responsible may reflect a systemic reaction to an acute "endothelial injury" and/or a circulating EPC response to sympathetic nervous system activation.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".