Controlled human exposure to diesel exhaust: results illuminate health effects of traffic-related air pollution and inform future directions
Bibliographic record
Abstract
Air pollution is an issue of increasing interest due to its globally relevant impacts on morbidity and mortality. Controlled human exposure (CHE) studies are often employed to investigate the impacts of pollution on human health, with diesel exhaust (DE) commonly used as a surrogate of traffic related air pollution (TRAP). This paper will review the results derived from 104 publications of CHE to DE (CHE-DE) with respect to health outcomes. CHE-DE studies have provided mechanistic evidence supporting TRAP's detrimental effects on related to the cardiovascular system (e.g., vasomotor dysfunction, inhibition of fibrinolysis, and impaired cardiac function) and respiratory system (e.g., airway inflammation, increased airway responsiveness, and clinical symptoms of asthma). Oxidative stress is thought to be the primary mechanism of TRAP-induced effects and has been supported by several CHE-DE studies. A historical limitation of some air pollution research is consideration of TRAP (or its components) in isolation, limiting insight into the interactions between TRAP and other environmental factors often encountered in tandem. CHE-DE studies can help to shed light on complex conditions, and several have included co-exposure to common elements such as allergens, ozone, and activity level. The ability of filters to mitigate the adverse effects of DE, by limiting exposure to the particulate fraction of polluted aerosols, has also been examined. While various biomarkers of DE exposure have been evaluated in CHE-DE studies, a definitive such endpoint has yet to be identified. In spite of the above advantages, this paradigm for TRAP is constrained to acute exposures and can only be indirectly applied to chronic exposures, despite the critical real-world impact of living long-term with TRAP. Those with significant medical conditions are often excluded from CHE-DE studies and so results derived from healthy individuals may not apply to more susceptible populations whose further study is needed to avoid potentially misleading conclusions. In spite of limitations, the contributions of CHE-DE studies have greatly advanced current understanding of the health impacts associated with TRAP exposure, especially regarding mechanisms therein, with important implications for regulation and policy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".