Mapping Acute Systemic Effects of Inhaled Particulate Matter and Ozone: Multiorgan Gene Expression and Glucocorticoid Activity
Bibliographic record
Abstract
Recent epidemiological studies have demonstrated associations between air pollution and adverse effects that extend beyond respiratory and cardiovascular disease, including low birth weight, appendicitis, stroke, and neurological/neurobehavioural outcomes (e.g., neurodegenerative disease, cognitive decline, depression, and suicide). To gain insight into mechanisms underlying such effects, we mapped gene profiles in the lungs, heart, liver, kidney, spleen, cerebral hemisphere, and pituitary of male Fischer-344 rats immediately and 24h after a 4-h exposure by inhalation to particulate matter (0, 5, and 50mg/m(3) EHC-93 urban particles) and ozone (0, 0.4, and 0.8 ppm). Pollutant exposure provoked differential expression of genes involved in a number of pathways, including antioxidant response, xenobiotic metabolism, inflammatory signalling, and endothelial dysfunction. The mRNA profiles, while exhibiting some interorgan and pollutant-specific differences, were remarkably similar across organs for a set of genes, including increased expression of redox/glucocorticoid-sensitive genes and decreased expression of inflammatory genes, suggesting a possible hormonal effect. Pollutant exposure increased plasma levels of adrenocorticotropic hormone and the glucocorticoid corticosterone, confirming activation of the hypothalamic-pituitary-adrenal axis, and there was a corresponding increase in markers of glucocorticoid activity. Although effects were transient and presumably represent an adaptive response to acute exposure in these healthy animals, chronic activation and inappropriate regulation of the hypothalamic-pituitary-adrenal axis are associated with adverse neurobehavioral, metabolic, immune, developmental, and cardiovascular effects. The experimental data are consistent with epidemiological associations of air pollutants with extrapulmonary health outcomes and suggest a mechanism through which such health effects may be induced.
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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) | 0.000 | 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".