Influence of exposure to coarse, fine and ultrafine urban particulate matter and their biological constituents on neural biomarkers in a randomized controlled crossover study
Bibliographic record
Abstract
BACKGROUND: Epidemiological studies have reported associations between air pollution and neuro-psychological conditions. Biological mechanisms behind these findings are still not clear. OBJECTIVES: We examined changes in blood and urinary neural biomarkers following exposure to concentrated ambient coarse, fine and ultrafine particles. METHODS: ) and filtered medical air. Exposures lasted 130min, separated by ≥2weeks, and the biological constituents endotoxin and β-1,3-d-glucan of each particle size fraction were measured. Blood and urine samples were collected pre-exposure, and 1-hour and 21-hour post-exposure to determine neural biomarker levels. Mixed-model regressions assessed associations between exposures and changes in biomarker levels. RESULTS: +1)], one-hour post-exposure. Fine CAP was marginally associated with increased blood UCHL1 when compared with exposure to filtered medical air [17.7% (-1.7%, 37.2%), p=0.07] 21hours post-exposure. Ultrafine CAP was not significantly associated with changes in any blood and urinary neural biomarkers examined. CONCLUSION: Ambient coarse particulate matter and its biological constituents may influence neural biomarker levels that reflect perturbations of blood-brain barrier integrity and systemic stress response.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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 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".