Controlled human exposures: a review and comparison of the health effects of diesel exhaust and wood smoke
Bibliographic record
Abstract
Abstract One of the most pressing issues in global health is air pollution. Emissions from traffic-related air pollution and biomass burning are two of the most common sources of air pollution. Diesel exhaust (DE) and wood smoke (WS) have been used as models of these pollutant sources in controlled human exposure (CHE) experiments. The aim of this review was to compare the health effects of DE and WS using results obtained from CHE studies. A total of 119 CHE-DE publications and 25 CHE-WS publications were identified for review. CHE studies of DE generally involved shorter exposure durations and lower particulate matter concentrations, and demonstrated more potent dysfunctional outcomes than CHE studies of WS. In the airways, DE induces neutrophilic inflammation and increases airway hyperresponsiveness, but the effects of WS are unclear. There is strong evidence that DE provokes systemic oxidative stress and inflammation, but less evidence exists for WS. Exposure to DE was more prothrombotic than WS. DE generally increased cardiovascular dysfunction, but limited evidence is available for WS. Substantial heterogeneity in experimental methodology limited the comparison between studies. In many areas, outcomes of WS exposures tended to trend in similar directions to those of DE, suggesting that the effects of DE exposure may be useful for inferring possible responses to WS. However, several gaps in the literature were identified, predominantly pertaining to elucidating the effects of WS exposure. Future studies should strongly consider performing head-to-head comparisons between DE and WS using a CHE design to determine the differential effects of these exposures.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".